Next Article in Journal
The Role of the MAPK Signaling, Topoisomerase and Dietary Bioactives in Controlling Cancer Incidence
Next Article in Special Issue
Epigenetic Mechanisms of Tamoxifen Resistance in Luminal Breast Cancer
Previous Article in Journal / Special Issue
Targeting H19, an Imprinted Long Non-Coding RNA, in Hepatic Functions and Liver Diseases
Article Menu

Export Article

Diseases 2017, 5(1), 12; doi:10.3390/diseases5010012

Review
Milk’s Role as an Epigenetic Regulator in Health and Disease
Bodo C. Melnik 1,* and Gerd Schmitz 2
1
Department of Dermatology, Environmental Medicine and Health Theory, Faculty of Human Sciences, University of Osnabrück, Am Finkenhügel 7a, D-49076 Osnabrück, Germany
2
Institute for Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, University of Regensburg, Franz-Josef-Strauß-Allee 11, D-93053 Regensburg, Germany
*
Correspondence: Tel.: +49-5241-988-060; Fax: +49-5241-25801
Academic Editor: Takeo Kubota
Received: 7 January 2017 / Accepted: 7 March 2017 / Published: 15 March 2017

Abstract

:
It is the intention of this review to characterize milk’s role as an epigenetic regulator in health and disease. Based on translational research, we identify milk as a major epigenetic modulator of gene expression of the milk recipient. Milk is presented as an epigenetic “doping system” of mammalian development. Milk exosome-derived micro-ribonucleic acids (miRNAs) that target DNA methyltransferases are implicated to play the key role in the upregulation of developmental genes such as FTO, INS, and IGF1. In contrast to miRNA-deficient infant formula, breastfeeding via physiological miRNA transfer provides the appropriate signals for adequate epigenetic programming of the newborn infant. Whereas breastfeeding is restricted to the lactation period, continued consumption of cow’s milk results in persistent epigenetic upregulation of genes critically involved in the development of diseases of civilization such as diabesity, neurodegeneration, and cancer. We hypothesize that the same miRNAs that epigenetically increase lactation, upregulate gene expression of the milk recipient via milk-derived miRNAs. It is of critical concern that persistent consumption of pasteurized cow’s milk contaminates the human food chain with bovine miRNAs, that are identical to their human analogs. Commercial interest to enhance dairy lactation performance may further increase the epigenetic miRNA burden for the milk consumer.
Keywords:
breastfeeding; DNA methyltransferase; epigenetic regulation; exosome; FTO; infant formula; lactation; miRNA-148a; milk; non-communicalbe diseases of civilization

1. Introduction

The environment in early life has an important influence on human growth and development, including the “programming” of far-reaching effects on the risk of developing non-communicable diseases in later life [1,2]. Thus, recent research focuses on the role of early nutrition for the epigenetic basis of developmental programming [3]. Milk is the first postnatal nutritional environment of all mammals from the beginning of extrauterine life to the end of the lactation period. Milk is a very complex secretory product of ancient adaptation strictly controlled by the lactation genome representing a most critical maternal regulator of offspring development [4]. Neolithic humans differ is this regard as they are persistently exposed to the milk of another species, predominantly to the milk of dairy cows.
There is accumulating evidence that milk functions as a transmitter or relay between the maternal lactation genome and epigenetic regulation of genes of the milk recipient, who under physiological conditions is the newborn infant, but under Neolithic conditions is the human consumer of bovine milk [5,6]. In fact, epigenetic processes are considered to play a pivotal role in regulating tissue-specific gene expression and hence alterations in these processes can induce long-term changes in gene expression and metabolism which persist throughout life course [7,8,9]. Because human milk protects against diseases of civilization in later life [10,11], the World Health Organization recommends exclusive breastfeeding for up to six months with continuation of breastfeeding for at least the first two years [12].
We have already suggested that milk exerts its functional role as an epigenetic imprinting system for the milk recipient [6,13]. To fulfil its function as an epigenetic regulator, milk transfers lactation-specific miRNAs, which are secreted as extracellular vesicles derived from mammary gland epithelial cells (MECs) [14]. The majority of milk-derived miRNAs are transported in exosomes, secreted nanoparticles (30–100 nm) surrounded by a stable lipid bilayer membrane protecting and ensuring long-distance miRNA transfer. Indeed, exosomes are appreciated as important factors of epigenetic regulation that modify stem cell biology [15]. Accumulating evidence supports the view that milk-derived exosomal miRNAs reach the systemic circulation of the newborn infant and the human consumer of cow’s milk (reviewed in [16,17,18,19,20,21]). To understand the role of milk exosomal miRNAs as crucial epigenetic transmitters for mother-child communication, it is mandatory to be familiar with the basics of extracellular vesicle biology.

2. Extracellular Vesicles: Signalosomes for Intercellular Communication

In 1946, extracellular vesicles (EVs) were first detected as procoagulant platelet-derived particles in normal plasma [22] and later on have been described as “platelet dust” [23]. In the 1980s, exosomes were described as vesicles of endosomal origin secreted from reticulocytes [24,25,26]. In the meantime, EVs have been classified into three main groups: (1) exosomes (30–100 nm in diameter) formed via the endocytic pathway; (2) microvesicles (100–2000 nm) formed by budding out of the plasma membrane in a calcium-dependent process; and (3) apoptotic bodies (>1000 nm) formed by blebbing of the plasma membrane during the process of apoptosis (recently reviewed in [27]). Exosomes are a subclass of EVs with a buoyant density of 1.10–1.19 g/mL that are enriched with tetraspanin proteins. They are assembled in intraluminal vesicles (ILVs) contained in multi-vesicular bodies (MVBs) that are released by fusing with the cell membrane. Their cargos are proteins, lipids, RNAs and miRNAs mediating intercellular communication between different cell types in the body, and thus affecting normal and pathological conditions. Their biogenesis, secretion, and intercellular interaction has recently been reviewed extensively [28]. The functional significance of exosomes lies in their capacity to transfer information to the recipient cell thereby modulating gene and cell functions [27,29]. Thus, exosomes transfer functional RNAs from a donor to an acceptor cell, analogous to hormones that can signal in paracrine and autocrine modes [30,31]. The presence of functional RNA in microvesicles was first detected in 2006 for murine stem cell-derived EVs [32]. In 2007, the uptake of mRNAs and miRNAs of murine mast cell-derived exosomes by human mast cells has been reported for the first time [33]. There is recent evidence indicating that exchange of genetic information utilizing persistent bidirectional communication mediated by stem cell EVs could regulate stemness, self-renewal, and differentiation in stem cells and their subpopulations [34,35].

3. Milk Exosomes: Long-Distance Transmitters of Lactation-Specific miRNAs

Milk exosomes are regarded as indispensable signalosomes mediating cellular communication between the mother and her nursing infant [13,14,17,18,19,20,21]. In 2007, immune-regulatory exosomes from human colostrum and mature human milk have been isolated and characterized for the first time [36]. In the meantime, milk-derived exosomes have been detected in colostrum and mature milk of humans, cows, buffalos, goats, pigs, marsupial tammar wallabies and rodents [36,37,38,39,40,41,42,43,44,45,46,47,48]. Milk miRNAs have been detected in both the fat fraction of milk and skimmed milk [17,49,50]. The largest membrane-coated vesicles present in milk are the milk fat globules (MFGs) that transport the main fraction of milk lipids, predominantly triacylglycerols [51]. The major bovine milk fat globule membrane (MFGM) proteins butyrophilin, xanthin oxidase, adipophilin, and lactadherin exhibited a 15- to 30-fold reduction in abundance in bovine milk exosome membranes, demonstrating that the secretion of MFGs (lipid droplets) and milk exosomes represent two distinct secretory pathways originating from the ER directly or through the Golgi complex [42]. Nevertheless, exosome-like vesicles have recently been observed within cytoplasmic crescents of human MFGs [52]. There are at least four major cellular sources of milk exosomes: (1) direct exosome release via mammary epithelial cells (MECs) during different stages of lactation; (2) indirect exosome sequestration from MFGs; (3) exosome release by various immune-related cells in milk, and (4) exosome release via nonimmune-related cells such as milk stem cells [17,42,50,52,53,54,55,56,57]. It should be emphasized however that the majority of human milk miRNAs primarily originates from MECs resulting in unique miRNA profiles of fractionated milk (Figure 1) [14].

3.1. Stability of Milk Exosomal miRNAs

miRNAs are very stable and can be effectively retrieved and analyzed from formalin-fixed paraffin-embedded tissues [58,59]. Exosomal package of miRNAs serves as a special biological modification increasing their stability, an important functional feature for miRNA transfer between cells. Exosomes exhibit a rigid lipid bilayer membrane, which compared to their parent cells is enriched in cholesterol and sphingomyelin [60]. The exosome membrane serves as a protective barrier for external degradative insults. In contrast to exosome-free synthetic miRNAs, exosomal miRNAs of human milk resist harsh external conditions [43]. Acidification of bovine milk to mimic the acidic gastrointestinal tract environment did not affect RNA yield and quality [38]. miRNAs of pasteurized cow’s milk have also been shown to be stable under degradative conditions, such as RNase treatment, but were degraded by the addition of detergent, which destroys the protective lipid bilayer membrane [40,61]. In contrast to macrophage-derived exosomes, bovine milk-derived exosomes were much more stable under degrading conditions, including low pH, boiling and freezing [62]. However, pasteurization and homogenization of cow’s milk caused a substantial loss of miRNAs (63% loss of miRNA-200c, 67% loss of miRNA-29b in skim milk). In contrast, effects of cold storage and somatic cell content were quantitatively minor (<2% loss) [63]. Buffalo milk miRNA-21 and miRNA-500 were found stable under different household storage conditions indicating that these could be biologically available to milk consumers [48]. Heating in the microwave caused a 40% loss of miRNA-29b but no loss of miRNA-200c [63]. Ultra-sonication treatment of bovine colostrum exosomes abolished their immune-regulatory activity pointing to the critical role of exosome membrane integrity for exosome function [44]. Fermentation results in quantitative changes of milk-derived exosomes and reduction of milk miRNA levels [64]. Milk exosomes exhibit cross-species tolerance with no adverse immune and inflammatory responses [65]. Recently, 200–300 nm large, miRNA-223- and miRNA-125b-enriched EVs have been demonstrated in cow’s milk that also resist digestion under simulated gastrointestinal tract conditions [66].
Taken together, human and bovine milk exosomes resist harsh gastrointestinal tract conditions, important requirements for exosomal miRNA transfer into the systemic circulation (Figure 1) [19].

3.2. Milk Exosome Uptake

Cells are able to take up exosomes by a variety of endocytic pathways, including clathrin-dependent endocytosis, and clathrin-independent pathways such as caveolin-mediated uptake, macropinocytosis, phagocytosis, and lipid raft-mediated internalization [67,68,69,70,71]. Exosomes can easily cross endothelial barriers including the blood-brain barrier [72,73]. First uptake studies of milk exosomes have been performed with macrophages. It has been demonstrated that both human and bovine milk exosomes carrying miRNA and RNA were taken up by human macrophages [61,62,74]. Intestinal uptake of bovine milk exosomes by intestinal epithelial cells (IECs) is mediated by temperature-dependent endocytosis and depends on cell and exosome surface glycoproteins in IECs (Figure 1) [75,76]. PKH67-labeled bovine milk exosomes have been detected in IECs of the ileum and isolated splenocytes of mice that received bovine milk exosomes by daily oral gavage [75]. It has recently been demonstrated that porcine milk exosomes promoted proliferation of IECs [77]. Porcine milk exosomes significantly raised mice' villus height, crypt depth and the ratio of villus length to crypt depth of intestinal tissues [77]. In addition, human vascular endothelial cells (VECs) have also been shown to transport bovine exosomes by endocytosis [78], which supports our view that milk-derived exosomes and their miRNA cargo may reach the systemic circulation and peripheral tissues of the milk recipient (Figure 1) [6,19]. In fact, it has been reported that bovine milk miRNA-29b and miRNA-200c are dose-dependently absorbed and modify gene expression in peripheral blood mononuclear cells (PBMCs) of human milk consumers [79]. Chen et al. [77] recently demonstrated that the addition of porcine milk exosomes to IPEC-J2 intestinal cells raised intracellular levels of milk-specific miRNA-7134, miRNA-1343, miRNA-2320, miRNA-181a, miRNA-769-3p, and miRNA-128. This resulted in a significant suppression of FAS mRNA, which is a target of miRNA-2320 and miRNA-181a, and decreases of SERPINE mRNA, a target of miRNA-769-3p and miRNA-128, respectively [77].
These data suggest that milk exosome-derived miRNAs enter IECs and reach the systemic circulation [79]. There is further translational evidence supporting that milk exosomal miRNAs reach the bloodstream and modulate gene expression of the milk recipient. For instance, highly expressed lactation-specific miRNAs have been detected in the serum of the neonate wallaby (Macropus eugenii) in comparison to adult blood, suggesting systemic uptake of these milk-derived miRNAs [46]. Furthermore, immune-related exosomal miRNAs have been detected in higher numbers in the colostrum than in mature porcine milk [41]. The detection of higher concentrations of these immune-related miRNAs in the serum of “colostrum-only” fed piglets compared with the “mature milk-only” fed piglets further indicates the uptake of milk-derived miRNAs into the systemic circulation of the piglet [41]. Moreover, an integrated genomics and computational analysis has characterized the likelihood of milk-derived miRNAs to get transferred into the human circulation [80]. Remarkably, predicted target genes of 14 highly expressed miRNAs of bovine milk fractions were related with organismal development such as hematological, cardiovascular, skeletal, muscular, and immune system development [81] favoring a systemic gene-regulatory role of milk-derived miRNAs (functional hypothesis) [6,14,16,17,19,79,81].
It should be mentioned that the “nutritional hypothesis” of milk-derived exosomes is primarily based on three mouse models, which are inherently problematic: (1) miRNA-375 KO mice; (2) miRNA-200c/141 KO mice [82] and (3) transgenic mice presenting high levels of miRNA-30b in milk [83]. These models may all be inappropriate to study the physiological traffic of milk miRNAs to the newborn mammal as they are based on aberrant miRNA expression and did not control exosome-mediated miRNA transfer [19]. The study of Auerbauch et al. [84], which could not detect bovine milk-derived miRNAs in human plasma, may have been compromised by sample damages due to an interrupted cold chain [19].
In summary, the majority of studies supports the view that exosome-derived lactation-specific miRNAs reach the systemic circulation of the milk recipient and exert gene-regulatory functions in the newborn infant as well as the adult human consumer of cow’s milk (Table 1) [6,14,16,17,19,79,81,85].

3.3. Milk’s Exosomal miRNAs

In 1988, Brenner [86] hypothesized that RNAs may function as extracellular communicators involved in eukaryotic development. Secreted miRNAs represent a newly recognized most important layer of gene regulation in eukaryotes, which plays a relevant role for intercellular communication [87,88,89]. miRNAs are part of the epigenetic machinery and are predicted to regulate nearly 60% of all human genes [90,91]. miRNAs bind through partial sequence homology to the 3′-untranslated region (3′-UTR) of their target mRNAs located in the RNA silencing complex (RISC) and cause either translational block or less frequently mRNA degradation [90]. miRNAs that are enclosed by membranous vesicles, such as exosomes, play a pivotal role for horizontal miRNA transfer [89]. Milk is apparently the most efficient long-distance miRNA transmitter modifying epigenetic regulation of its recipient. It is thus not surprising that human milk contains the highest concentration of total RNAs including miRNAs in comparison to all other body fluids [92]. Exosomes are highly specialized microvesicles that transfer miRNAs to recipient cells subsequently modifying their target gene expression [30,31]. Exosomes are thus regarded as intercellular signaling organelles (signalosomes) that participate in intercellular communication [27,28,29,30,31,93,94,95,96]. Recently, it has been reported that human milk exosomes also deliver long non-coding RNAs, which have also been implicated to be involved in the epigenetic regulation of the immune system and metabolism [97].
Our insights into active sorting mechanisms of lactation-specific miRNAs into milk exosomes are still in its infancy. However, a specific repertoire of miRNAs selectively exported to exosomes indicates an active sorting mechanism [98,99]. The expression of cellular miRNAs or specific miRNA target sequences can determine the presence of miRNAs in exosomes [100]. The sumoylated protein heterogeneous nuclear ribonucleoprotein A2B1 (HNRNPA2B1) recognizes the EXOmotif (GGAG tetranucleotide) in miRNAs and thereby accomplishes their loading into exosomes [98,99]. It has also been suggested that the addition of non-templated nucleotides to the 3′end of miRNAs might promote miRNA sorting into exosomes [101]. RNA-binding protein Y-box protein 1 (YBX1) plays an important role in sorting and secretion of miRNAs into exosomes [102]. At present, two possible routes for miRNA egress via exosomes have been suggested: an Ago2-associated pathway and an RNA-binding-protein-dependent chaperone-mediated sorting pathway [102]. Notably, the chaperone-mediated pathway includes HNRNPA2B1 and YBX1 [99,102].

4. Epigenetic Regulation of Lactation

Lactation describes the secretion of milk from the mammary glands and the period of time that a mother lactates to feed and epigenetically program her young. During lactation MECs dramatically enhance milk protein and milk lipid synthesis. A network of genes participates in coordinating bovine milk fat synthesis and secretion. Experimental data highlight a pivotal role for a concerted action among PPARG, PPARGC1A, and INSIG1. Expression of stearoyl-CoA desaturase (SCD), the most abundant gene measured, appears to be key during milk fat synthesis [103]. Recent evidence indicates that miRNAs control the homeostatic regulation of cholesterol and triacylglycerol metabolism [104,105,106]. In comparison to nonlactating mammary glands of the Chinese swamp buffalo, the expression of miRNA-148a among other lactation-related miRNAs significantly increased during lactation [107]. In goat MECs, miRNA-148a and miRNA-17-5p have been shown to synergistically increase milk triacylglycerol synthesis via regulation of PPARGC1A and PPARA. Notably, overexpression of miRNA-148a and miRNA-17-5p promoted triacylglycerol synthesis while knockdown of miRNA-148a and miRNA-17-5p impaired triacylglycerol synthesis in goat MECs [108]. Furthermore, miRNAs are appreciated to play an increasing role in mammary gland homeostasis [109]. Recently, a miRNA-mediated crosstalk between the human placenta and the lactating breast has been suggested [110]. Upon exposure of human MECs to umbilical cord blood-derived microvesicles, microvesicle uptake was examined by fluorescence confocal microscopy associated with increased production of the milk protein β-casein [110]. Intruigingly, a recent study provided evidence that genome-wide miRNA binding site variation between extinct wild aurochs and modern cattle identifies candidate miRNA-regulated domestication genes including MIR148a [111].
There is recent interest in the epigenetic regulation of bovine and goat milk production for further maximization of milk yield [112,113,114]. It is of critical importance to realize that DNA demethylation of lactation-specific genes is a critical regulatory mechanism that increases gene expression for milk protein and lipid synthesis. In the lactating cow, mammary gland-specific hypomethylation of the αS1-casein gene increased casein expression [115]. Hypomethylation of casein genes during lactation have also been demonstrated in other species [113]. In accordance, abundant lactation-specific miRNAs that target DNA methyltransferases (DNMTs) are involved in the activation of lactation-related biosynthetic pathways.
miRNA-148a, miRNA-148b, and miRNA-152 are three members of the miRNA-148/152 family that share substantial homology in their seed sequence. Wang et al. [116] found that the expression of miRNA-152 significantly increased during lactation in the mammary glands of dairy cows producing high quality milk compared with miRNA-152 levels in cows producing low quality milk. The forced expression of miRNA-152 in dairy cow MECs resulted in a marked reduction of DNMT1 at both mRNA and protein levels. This in turn led to a decrease in global DNA methylation and increased the expression of two lactation-related genes, serine/threonine protein kinase AKT and peroxisome proliferator-activated receptor-γ (PPARG), whereas inhibition of miRNA-152 showed the opposite results. Furthermore, miRNA-152 enhanced the viability and multiplication capacity of dairy cow MECs [116].
Milk-related miRNAs in bovine MECs are under the influence of lactogenic hormones such as dexamethasone, insulin, and prolactin (DIP) [117]. Intriguingly, the expression of miRNA-148a was significantly elevated by DIP treatment in bovine MEC culture medium [117]. Muroya et al. [117] reported that elevated miRNA-148a levels in DIP-treated bovine MECs are associated with their increase in milk during the bovine lactation period. Importantly, DNMT1 is a direct target of miRNA-148a [118]. The expression of DNMT1 is inversely related to the expression miRNA-148a and miRNA-152 [119,120]. Furthermore, miRNA-148a directly downregulates the expression DNMT3B [121]. Furthermore, miRNA-148a directly targets the mRNAs of ABCA1, LDLR and CPT1A, thus attenuates cholesterol efflux, hepatic LDL uptake, and mitochondrial fatty acid β-oxidation [106].
Bian et al. [122] showed that miRNA-29s regulate the DNA methylation level by inversely targeting both DNMT3A and DNMT3B in dairy cow MECs. The inhibition of miRNA-29s caused global DNA hypermethylation and increased the methylation levels of the promoters of important lactation-related genes, including casein-α s1 (CSN1S1), E74-like factor 5 (ELF5), PPARγ (PPARG), sterol regulatory element binding protein-1 (SREBP1), and glucose transporter-1 (GLUT1). The inhibition of miRNA-29s reduced the secretion of lactoprotein, triacylglycerols and lactose by dairy cow MECs. The treatment of dairy cow MECs with 5-aza-2′-deoxycytidine decreased the methylation levels of the MIR29B promoter and increased the expression of miRNA-29b [122]. The enhancement of lactation activity and milk yield was thus associated with upregulation of DNMT3A- and DNMT3B-targeting miRNA-29s. In fact, the miRNA-29 family (miRNA29a, miRNA29b, and miRNA29c) has intriguing complementarities to the 3′-UTRs of DNMT3A and DNMT3B, two key de novo methyltransferases involved in DNA methylation [123]. The Ets transcription factor ELF5 is essential for normal alveolar development and lactation [124]. Notably, an increase in ELF5 expression was associated with decreasing ELF5 promoter methylation in differentiating HC11 mammary epithelial cells [125]. Similarly, purified MECs from mice had increased ELF5 expression and decreased promoter methylation during pregnancy [125].
miRNA-145 is another miRNA epigenetically involved in the regulation of metabolism of fatty acids in goat MECs [126]. Overexpression of miRNA-145 increased the transcription of genes associated with milk fat synthesis resulting in the expansion of the lipid droplet compartment, increase of triacylglycerol accumulation, and upregulation of the proportion of unsaturated fatty acids. In contrast, silencing of miRNA-145 impaired fatty acid synthesis [126]. Remarkably, inhibition of miRNA-145 increased methylation levels of FAS, SCD1, PPARG, and SREBP1. Notably, insulin-induced gene 1 (INSIG1) is a direct target of miR-145. INSIG1 binds the sterol-sensing domain of SREBP cleavage-activating protein (SCAP) and facilitates retention of the SREBP/SCAP complex in the endoplasmic reticulum [127]. miRNA-145-mediated downregulation of INSIG1 thus promotes cholesterol biosynthesis.
miRNA-21 is another abundant miRNA of cow’s milk, which indirectly inhibits DNMT1 expression by targeting Ras guanyl nucleotide-releasing protein-1 (RASGRP1) [118]. Furthermore, miRNA-21 targets multiple tumor suppressor genes (PTEN, Sprouty) and inhibitors of translation (PDCD4) resulting in the upregulation of mTORC1-mediated translation [6,128,129].
Whereas lactation-specific miRNAs directly target critical genes involved in the gene-regulatory network of lactation including milk protein and milk lipid synthesis, it is of utmost importance to realize that these lactation-associated miRNAs via targeting DNMTs demethylate critical DNA promoter regions of lactation-related genes including CSN1S1, ELF5, PPARG, SREBP1, and GLUT1. The generation of DNMT-targeting miRNAs (miRNA-152, miRNA-148a, miRNA-29, miRNA-21) is thus a fundamental epigenetic mechanism increasing lactation-specific gene transcription thereby enhancing lactation performance as well as milk yield in domestic animals. A genetic selection of domestic cows with increased activity of DNMT-targeting miRNAs may thus enhance milk protein and lipid yield [111].

5. DNMT-Targeting miRNAs of Milk: Activators of the Recipient’s Epigenome

miRNA-148a-3p is by far the most abundant miRNA detected in human milk, bovine colostrum and bovine mature milk, porcine colostrum and porcine mature milk [37,40,41,43,130]. Notably, miRNA-148a is highly expressed in human and bovine milk fat [49,130] and has been measured in substantial amounts in bovine skim milk and human milk exosomes [43]. It is possible that MFGs of nonpasteurized cow’s milk release miRNA-148a carried in crescent exosomes [52]. It has been reported that miRNA-148a-3p levels increased after homogenization and thus pressure-induced dispersion of MFGs [130].
The miRNA-29 family (miRNA-29a, miRNA-29b and miRNA-29c) has been detected in bovine colostrum and bovine milk [40,44,64,79]. miRNA-29b levels in PBMCs of healthy volunteers increased in a dose-dependent manner after consumption of pasteurized cow’s milk [79].
miRNA-21 is a major miRNA of human milk exosomes [43], human milk fat [49], human, bovine, and buffalo milk as well as porcine colostrum and porcine mature milk [37,41,65,131]. It is of critical importance to appreciate that the nucleotide seeding sequences of miRNA-148a-3p, miRNA-21-5p, and miRNA-29b-1-3p of Homo sapiens and Bos taurus are identical (mirbase.org) (Table 2). This allows the suppression of human DNMTs by these abundant miRNAs of human and bovine milk.
There are two interactive mechanisms of DNA demethylation: (1) passive demethylation through inhibition of DNA methyltransferases (DNMTs) and (2) active demethylation mediated by ten-eleven-translocation (TET) 2 and 3 [132]. TET2 binding to CpG-rich regions requires the interaction of TET2 with the protein IDAX (inhibitor of DVL/axin complex also known as CXXC4) [133]. Intriguingly, the CXXC DNA-binding domains can bind unmethylated DNA and recruit TET2 via IDAX [134]. Thus, milk-derived miRNA-mediated DNMT inhibition may promote further active TET2-mediated DNA demethylation, a critical epigenetic mechanism promoting milk-controlled gene expression.

6. Activation of Developmental Genes via DNA CpG Demethylation

6.1. FTO

Milk, the postnatal nutritional environment of the growing infant, should provide sustained mechanisms activating both transcription and translation. Circumstantial evidence supports milk’s role as an activator of fat mass- and obesity-associated protein (FTO)-driven transcription as well as mechanistic target of rapamycin complex 1 (mTORC1)-mediated translation [135,136]. FTO is a N6-methyladenosine (m6A) demethylase that selectively removes m6A modifications from target mRNAs [137,138,139,140]. The m6A modification in mRNA is extremely widespread, and functionally important because it modulates the eukaryotic transcriptome via influencing mRNA splicing, export, localization, translation, and stability [139]. RNA m6A modifications are involved in the regulation of diverse RNA functions including development, cell reprogramming and circadian rhythm [140,141]. In general, the m6A mark of RNA is regarded as a negative regulator of gene expression and protein translation [142,143,144]. Notably, m6A peaks at the stop codons and 3′-UTRs, which are recognized by the human YTH domain family 2 (YTHDF2) to regulate mRNA degradation [143]. Furthermore, m6A blocks mRNA binding to the mRNA stabilizer human antigen R (HuR) [143].
Notably, loss-of function mutation of the m6A demethylase FTO is associated with postnatal growth retardation in humans [145]. In accordance, FTO knockdown in mice decreased body weight, altered metabolism, and retarded growth [146], whereas FTO overexpression in mice led to a dose-dependent increase in body and fat mass, increased food intake resulting in obesity [147]. There is compelling evidence that FTO plays a pivotal regulatory role for postnatal growth and energy expenditure [146,147,148,149,150]. Overexpression of FTO resulted in global decrease of m6A in RNAs [137]. It is known that single nucleotide polymorphisms (SNPs) in the first intron of FTO are associated with increased body weight, adiposity and type 2 diabetes mellitus (T2DM) [151,152,153]. Recent evidence indicates that not only FTO SNPs result in increased FTO activity but also epigenetic modulations associated with demethylation of specific CpG sites in the first intron of FTO [154,155,156,157]. Milk-derived DNMT-targeting exosomal miRNAs (miRNA-148a, miRNA-152, miRNA-21, miRNA-29s) may play a pivotal epigenetic role in reducing CpG methylation of critical gene regulatory sites of FTO resulting in increased FTO expression required for increased postnatal mRNA transcription (Figure 2) [135].

6.2. NRF2

mTORC1, the nutrient-sensitive kinase, which increases milk-induced translation [136] and anabolism [158] is closely associated with FTO activity [159,160]. FTO couples the availability of leucine, a critical activator of mTORC1 [161], to leucyl-tRNA synthase-mediated activation of mTORC1 [159,160]. Notably, the link between amino acid availability and mTORC1 signaling is dependent upon the demethylase activity of FTO [159]. Milk-mediated epigenetic activation of FTO gene expression may thus augment downstream mTORC1 signaling.
There are further potential milk-mediated epigenetic mechanisms that activate mTORC1 and mTORC1-driven translation. Nuclear factor erythroid 2-related factor 2 (NRF2) is an important transcription factor, which is under epigenetic control. DNMT inhibition increased NRF2 at both messenger RNA and protein levels via NRF2 DNA demethylation [162]. NRF2 is a direct transcriptional activator of the MTOR gene [163], which codes the core component of the mTORC1 and mTORC2 complexes [164]. NRF2 also upregulates RagD, a small G-protein activator of mTORC1 [165,166]. Moreover, NRF2 activates miRNA-29-coding genes [167,168], which further attenuate DNMT3B expression causing further feed forward epigenetic upregulation of NRF2 expression (Figure 2).

6.3. INS

Insulin is a pivotal activator of anabolic PI3K-mTORC1 signaling [169]. Milk consumption results in increased postprandial plasma levels of insulin [136]. Remarkably, insulin gene (INS) expression is regulated by DNA methylation [170]. Kuroda et al. [170] demonstrated that β-cell-specific demethylation of INS enhances insulin expression, whereas DNA methylation suppresses insulin expression. Notably, the INS promoter is specifically demethylated in insulin-producing cells. INS promoter CpG demethylation may play a crucial role in β-cell maturation and tissue-specific insulin gene expression. Milk exosomal DNMT-targeting miRNAs (miRNA-148a, miRNA-21 and miRNA-29s) may thus enhance insulin secretion required for mTORC1-driven translation and anabolism (Figure 2). In fact, murine miRNA-29a was recently reported to be a positive regulator of insulin secretion in vivo [171].

6.4. IGF1

Insulin-like growth factor-1, the sister hormone of insulin, is the strongest growth factor and promotes mTORC1 signaling [169]. Milk consumption significantly increases serum levels of IGF-1 [172] and is associated with increased linear growth of children consuming cow’s milk [173]. Since IGF-1 controls postnatal growth, Ouni et al. [174] tested whether the CpG methylation of the two promoters (P1 and P2) of the IGF1 gene is a potential epigenetic contributor to the individual variation in circulating IGF-1 and stature in growing children. The methylation of a cluster of six CpGs located within the proximal part of the IGF1 P2 promoter showed a strong negative association with serum IGF-1 and growth [174]. Methylation of CpGs in the P2 promoter is negatively associated with the increased transcriptional activity of P2 promoter in patients' PBMCs following GH administration [175].
Taken together, accumulating translational evidence underlines the physiological role of milk miRNA-mediated epigenetic upregulation of critical activators of mTORC1, such as mTOR, FTO, insulin and IGF-1, which all increase in a DNA demethylation-dependent manner (Figure 2).

6.5. CAV1

Caveolin 1 (Cav-1) is a plasma membrane microdomain-associated protein with the capacity to modulate signaling activities in a context-dependent fashion. Cav-1 interacts with insulin receptor (IR) and IGF-1 receptor (IGF-1R) stimulating IGF-1- and IR signal transduction. Cav-1 binds to low-density lipoprotein (LDL) receptor-related protein 6 (LRP6) to generate an integrated signaling module that leads to the activation of IGF-1R/IR that finally enhances Akt–mTORC1 signaling [176,177,178]. Remarkably, demethylation of exon 1 and first intron of the Cav-1 gene (CAV1) is accompanied by a strong induction of Cav-1 expression [179], which has been observed during adipocyte differentiation [179]. It is conceivable, that milk miRNAs that target DNMTs may enhance insulin-, IGF-1-, and mTORC1 signaling via epigenetic stimulation of Cav-1 expression, which may enhance milk exosome uptake.

6.6. FOXP3

FoxP3, the master transcription factor of regulatory T cells (Tregs), plays a key role in Treg function, which is strongly related to the induction of tolerance against self-antigens (prevention of autoimmunity) and environmental allergens including food allergens (prevention of allergy) [180,181,182]. Adymre et al. [36] presented first evidence that the addition of isolated human milk exosomes to PBMCs increased the number of FoxP3+ Tregs. FoxP3 acts as a lineage-specifying factor that determines the unique properties of these immunosuppressive cells [183]. Epigenetic modifications in the CpG-rich Treg-specific demethylated region (TSDR) in the FOXP3 locus are associated with stable FoxP3 expression [184,185]. Notably, stable FoxP3 expression was found only for cells displaying enhanced TSDR demethylation [183]. Recently, a linear correlation between FoxP3 expression and the degree of TSDR demethylation has been confirmed [186]. Thus, TSDR is an important epigenetic site regulating FoxP3 expression. Epigenetic imprinting in this region is thus critical for the establishment of a stable Treg lineage [183,184,185,186,187]. In contrast, hypermethylation of FOXP3 has been associated with reduced Treg function and development of allergy [188,189]. Notably, atopic individuals express lower numbers of demethylated FoxP3+ Tregs [190].
DNMT1 and DNMT3b are associated with the FOXP3 locus in CD4+ T cells [191]. TSDR demethylation using the DNMT inhibitor 5-aza-2′-deoxycytidine resulted in strong and stable induction of FoxP3, indicating that epigenetic regulation of FOXP3 can be predictably controlled via DNMT inhibition to generate functionally stable Tregs [192]. Milk-derived exosomal miRNAs that target DNMT1 (miRNA-148a, miRNA-21) and DNMT3B (miRNA-148a, miRNA-29b) have been suggested to play a fundamental epigenetic role for milk-induced FoxP3 expression and Treg stabilization [130,193,194]. Thus, there is accumulating evidence that milk exosomal miRNAs are pivotal epigenetic regulators that shape intestinal and systemic immunity [36,193,194,195].
A recent epigenetic pilot study in Dutch children showed general DNA hypermethylation in the group of children with cow’s milk allergy (CMA) compared to healthy control children [196]. FOXP3 TSDR demethylation was significantly lower in children with active IgE-mediated CMA than in either children who outgrew CMA or in healthy children [186]. Maternal rat milk in comparison with miRNA-deficient artificial formula increased mesenteric lymph node FoxP3 expression and decreased serum IgE levels to β-lactoglobulin in allergy-prone rat pups [197]. Thus, milk miRNAs operate like DNMT inhibitors that increase the stability of FOXP3 gene expression enhancing the suppressive capacity of Tregs, promoting an immune tolerance environment [198]. This perception is in accordance with our vision that milk exosomal miRNAs shape the epigenetic environment of FoxP3-driven tolerance induction, a key mechanism for the prevention of autoimmunity and allergy [193,194,199]. It is conceivable that the availbility of the Treg-inducer milk provides a tolerogenic environment that is important for the tolerance of foreign food antigens encountered with the introduction of solid food in infants.

6.7. NRA4

The NR4A subfamily includes orphan nuclear receptors that belong to the larger nuclear receptors (NRs) superfamily of eukaryotic transcription factors that act as molecular switches in gene regulation modulating a complex network of cellular signaling pathways [200]. Importantly, NR4As including NR4A1, NR4A2, and NR4A3 are reported to regulate Treg cell development through activation of FOXP3 [201,202]. NRA4 receptors directly activate the promoter of FOXP3 and forced activation of NRA4 receptors promoted the Treg developmental program [202,203,204]. NRA4 transcription factors are thus regarded as nursing factors for the development of Tregs [205].
Milk, the epigenetic nursing system for immune cell and Treg development, may be able to promote NR4A expression. For instance, promoter CpG demethylation combined with histone hyperacetylation elucidated a regulatory mechanism that increased luteinizing hormone receptor (LHR) gene expression [206]. Intriguingly, NR4A3 was epigenetically silenced by NR4A3 promoter methylation, whereas NR4A3 promoter demethylation increased its expression [207]. Furthermore, NR4A3 transcription is induced by inhibition of the histone deacetylases HDAC1 and HDAC3 [208]. DNMT1 is known to associate and interact with HDACs [209,210]. The recruitment of methyl CpG binding protein 2 (MeCP2) to methylated CpG dinucleotides represents a major mechanism by which DNA methylation can repress transcription. MeCP2 silences gene expression partly by recruiting HDAC activity [211]. For instance, transcriptional silencing from the H19 imprinting control region involves recruitment of MeCP2 and HDAC activity [212]. Milk miRNA-148a-mediated suppression of DNMT1 may thus impair the binding of MeCP2 and thus HDAC recruitment resulting in histone hyperacetylation thereby promoting the expression of developmental genes such as the NR4A subfamily of orphan nuclear receptors (Figure 2).

6.8. NFKBI

Milk has important effects on neonatal intestinal health and reduces the risk of necrotizing enterocolitis (NEC) in preterm infants [213]. NEC is associated with increased serum levels of proinflammatory cytokine resulting from activation of the nuclear factor kappa B (NF-κB) pathway such as interleukin-1 (IL-1) and tumor necrosis factor-α (TNFα) [214]. In an NEC model using Caco-2 intestinal cells, human milk supernatant inhibited the expression of proinflammatory cytokines IL-1β, IL-6 and TNFα [215], which are upregulated by activated NF-κB signaling. Nuclear factor κ of light polypeptide gene enhancer in B-cells inhibitor-α (IκBα) is a critical inhibitor of NF-κB. IκBα inhibits NF-κB by masking the nuclear localization signals of NF-κB proteins and keeping them sequestered in an inactive state in the cytoplasm [216]. Furthermore, IκBα blocks the ability of NF-κB transcription factors to bind to DNA, which is required for NF-κB’s proper functioning [217]. Notably, IκBα expression is higher in IECs lacking DNMTs than in IECs with active DNMT expression [218]. The CpG methylation status in the promoter of NFKBI exerts strong influences on NF-κB signaling of IECs [218]. Hypomethylation of the promoter of NFKBI increases IκBα expression, whereas methylation down-regulates IκBα expression. Absence of DNMTs in IECs resulted in lower NF-κB activation [218]. It is thus conceivable that milk miRNA-mediated down-regulation of DNMT expression exerts anti-inflammatory epigenetic modifications that enhance IκBα-mediated suppression of pro-inflammatory NF-κB signaling. In this regard, milk-miRNA-mediated upregulation of IκBα resembles the anti-inflammatory action of glucocorticoids, whose mode of action is the promotion of IκBα expression [219,220].

6.9. LCT

In the great majority of mammals, the intestinal expression of lactase fades after weaning except for mutant humans exhibiting lactase persistence. It is not known how the lactase gene (LCT) is dramatically downregulated with age in most individuals but remains active in others. According to recent evidence epigenetically controlled regulatory elements account for the differences in lactase mRNA levels among individuals, intestinal cell types and species [221]. There is good evidence that the persistence of high intestinal lactase activity into adult life is attributable to transcriptional regulation of LCT [222]. In Europeans, a single nucleotide substitution (-13910C>T) with intron 13 of MCM6, the gene adjacent to LCT, is strongly associated with lactase persistence. This substitution resides within an enhancer of LCT increasing promoter activity [223,224,225,226]. Seven epigenetically regulated regions have been identified that include the LCT enhancer located within intron 13 of MCM6, which house the functional DNA variants [221]. Low LCT transcription observed with the lactase nonpersistence haplotype was associated with a higher methylation status of intron 13, in contrast to a low methylation status of intron 13 in the lactase persistence haplotype resulting in high lactase expression [221].
We hypothesize that milk-derived miRNAs targeting DNMTs may maintain the low methylation status of intron 13, thus promoting lactase production during the period of breastfeeding. After weaning, the physiological disappearance of milk miRNA-mediated DNMT suppression might downregulate intestinal lactase expression, which is no more required after the lactation period. However, persistent milk consumption in Neolithic humans with a need to handle persisting lactose exposure may have increased natural selection pressure favoring the mutational cytosine > thymidine exchange at intron 13 (-13910C>T), which may contribute to reduced intron 13 cytosine methylation, thereby maintaining persistent high lactase expression.

7. Appetite Control and Feeding Reward

The newborn infant needs continuous access to calories and milk-derived signal transduction for appropriate postnatal growth, which requires active suckling, a strenuous effort for the newborn infant. Epigenetic mechanisms of milk may thus regulate the magnitude of appetite and reward signals in order to guarantee adequate and continuous calorie intake during the postnatal growth phase. Increased expression of the RNA m6A demethylase FTO in mice with two additional copies of FTO (FTO-4 mice) exhibited increased hyperphagia and adiposity [227]. Importantly, FTO overexpression reduced ghrelin mRNA m6A methylation, concomitantly increasing ghrelin mRNA and protein levels [228] (Figure 3). Ghrelin functions as an orexigenic neuropeptide in the central nervous system and regulates energy homeostasis and reward from food intake [229]. Ghrelin increases appetite by triggering receptors in the arcuate nucleus [230]. The ghrelin receptor is expressed in the brain to regulate feeding, including hypothalamic nuclei involved in energy balance regulation and reward-linked areas such as the ventral tegmental area [231]. Ghrelin signaling at the level of the mesolimbic system is one of the key molecular substrates that provides a physiological signal connecting gut and reward pathways [231]. Ghrelin interacts with neuropeptide Y Y1 and opioid receptors to increase food reward [232]. Milk intake via epigenetic upregulation of FTO may thus trigger ghrelin signaling thereby enhancing appetite and suckling reward to secure postnatal food intake required for postnatal growth and development. The key mechanisms enhancing ghrelin expression of the milk recipient may be increased epigenetic upregulation of hypothalamic FTO expression via milk miRNA-mediated demethylation of the FTO gene. In the offspring of obese female Sprague Dawley rats at weaning, hypothalamic FTO mRNA expression was increased significantly and FTO was correlated with both visceral and epididymal fat mass and hyperphagia [233]. Thus, human milk via FTO-mediated m6A-demethylation of ghrelin mRNA may maintain specific orexigenic and reward signals, whilst ensuring appropriate appetite regulation, a developmental requirement adjusting physiological growth trajectories of the human infant (Figure 3).
Persistent uptake of bovine milk exosomal miRNAs may epigenetically enhance long-term orexigenic signaling promoting overgrowth and obesity of the human consumer of cow’s milk. In fact, epidemiological studies confirmed enhanced BMI and linear growth in relation to cow’s milk consumption in children and adolescents [173,234].
Activation of dopaminergic signaling plays an important role in the midbrain and frontal cortex during postnatal development [235,236]. Midbrain dopaminergic neurons in the substantia nigra pars compacta and ventral tegmental area regulate extrapyramidal movement and important cognitive functions, including motivation, habit learning, and reward associations [237]. Variations in FTO are the strongest common genetic determinants of adiposity, and may partly act by influencing dopaminergic signaling in the brain leading to altered reward processing that promotes appropriate food intake [238]. Remarkably, FTO regulates the activity of the dopaminergic midbrain circuitry [239]. Inactivation of FTO impairs dopamine receptor type 2 (D2R) and type 3 (D3R)-dependent control of neuronal activity and behavioral responses [239]. Analysis of global m6A modification of mRNAs in the midbrain and striatum of FTO-deficient mice revealed increased m6A levels in a subset of mRNAs important for neuronal signaling, including many in the dopaminergic signaling pathway (Table 3) [239].
Conversely, milk-mediated upregulation of FTO stimulated via DNMT-targeting exosomal miRNAs may increase FTO expression and m6A demethylation of specific mRNAs promoting dopaminergic transmission. Milk exosome-derived miRNAs may adjust the right epigenetic magnitude of FTO-mediated dopaminergic signaling during the lactation period to maintain an appropriate neuronal growth, self-regulated food intake and feeding reward. Persistently overactivated FTO expression by continued cow’s milk consumption may maintain a state of hyperphagia promoting obesity.

8. Intestinal Growth

There is compelling evidence that IECs are able to take up bovine milk exosomes [75,76]. Porcine milk exosomes fed to mice transferred miRNAs, which increased in IECs and modified specific target gene expression promoting IEC proliferation [77]. Lipids are of particular importance for the maintenance and synthesis of cell membranes, which are required for intestinal growth. A key transcription factor of lipid synthesis is SREBP1, which is upregulated via activated AKT-mediated signal transduction. Notably, it has been demonstrated in bovine MECs that the expression of both AKT and SREBP1 underlie epigenetic miRNA-29/DNMT-mediated demethylation of their corresponding promoter regions [122]. Human milk contains and transfers milk stem cells with multilineage differentiation potential to the newborn infant [54,55]. Notably, DNMT inhibition promoted the differentiation of human induced pluripotent stem cells into functional enterocytes [240].
It is thus conceivable that milk-derived DNMT-targeting miRNAs support IEC maturation as well as milk stem cell differentiation into enterocytes, potential contributions for appropriate growth, maturation and function of the infant’s gut.

9. Adipogenesis

In humans, new adipocyte formation occurs throughout childhood and adolescence, with fat cell numbers plateauing around the age of 20 years [241]. Approximately 10% of fat cells are renewed annually at all adult ages [241]. Three new mesenchymal phenotypes were expressed in cultures of Swiss 3T3 and C3H/10T1/2CL8 mouse cells treated with the DNMT inhibitor 5-azacytidine. These phenotypes were characterized as contractile striated muscle cells, biochemically differentiated adipocytes and chondrocytes capable of the biosynthesis of cartilage-specific proteins [242]. Mesenchymal stem cells (MSCs) from different tissues may be marked by lineage-specific promoter hypomethylation [243]. Hypomethylation of adipogenic loci in undifferentiated cells may reflect a commitment of these cells to a specific lineage [243]. Uncultured adipose stem cells (ASCs) display hypomethylated promoters of the adipogenic genes leptin (LEP), PPAR-γ2 (PPARG2), fatty acid-binding protein 4 (FABP4), and lipoprotein lipase (LPL) [243]. Londoño Gentile et al. [244] recently reported that silencing of DNMT1 can accelerate adipocyte differentiation. DNMT1 gene expression is induced early in 3T3-L1 adipocyte mitotic clonal expansion and is critical for maintenance of DNA and histone H3K9 methylation patterns during this period. However, absence of DNMT1 results in accelerated adipocyte differentiation associated with precocious adipocyte-specific gene expression and lipid accumulation [236]. Later in differentiation, DNMT1 levels decline in an ATP-citrate lyase (ACL)-dependent manner. ACL-mediated suppression of DNMT1 occurs at least in part by promoting expression of miRNA-148a, which represses DNMT1 [244].
miRNA-21, another abundant exosomal miRNA of human, bovine and porcine milk, has recently been shown to enhance adipogenic differentiation from porcine bone marrow-derived mesenchymal stem cells [245]. Lim et al. [246] identified 31 genes whose promoters were significantly differentially methylated between white (WAT) and brown adipogenesis (BAT) at all three time points of differentiation. Among them, five genes belong to the Hox family; their expression levels were anti-correlated with promoter methylation, suggesting a regulatory role of DNA methylation in transcription. Blocking DNA methylation with 5-aza-cytidine increased the expression of these genes, with the most prominent effect on Hoxc10, a repressor of BAT marker expression [246].
Caveolin 1 (Cav-1) is an essential constituent of adipocyte caveolae which binds the β-subunit of the IR and is implicated in the regulation of insulin signaling. During adipocyte differentiation of 3T3-L1 cells the promoter, exon 1 and first intron of the Cav-1 gene undergo a demethylation process that is accompanied by a strong induction of Cav-1 expression, indicating that epigenetic mechanisms must have a pivotal role in this differentiation process [179].
Recent evidence links FTO overexpression to enhanced expression of the pro-adipogenic short isoform of the transcription factor RUNX1T1 [152]. FTO controls mRNA splicing by regulating the ability of the splicing factor SRSF2 to bind to mRNA in an m6A-dependent manner [152]. The pro-adipogenic short isoform of RUNX1T1 stimulates mitotic clonal expansion of MEFs and thus enhances adipocyte numbers [247]. Overexpression of porcine FTO in differentiating porcine intramuscular preadipocytes was located in the nucleus significantly increased the mRNA levels of adipocyte differentiation transcription factors PPARγ, CCAAT/enhancer binding protein-α (CEBPα), lipoprotein lipase and fatty acid synthase [248]. In human skeletal muscle, FTO mRNA expression positively associates with glucose oxidation rates as well as expression of genes involved in oxidative phosphorylation including PPAR-γ coactivator 1-α (PGC1α) [249] (Table 3). Although genes involved in methylation were differentially regulated in skeletal muscle of FTO-4 mice, no effect of FTO overexpression on m6A methylation of total mRNA was detected [227]. However, an m6A hypomethylation state was associated with increased FTO expression in mice fed with high-fat diet, whereas the supplementation of the methyl donor betaine prevented these changes [250].
Milk miRNA-mediated DNMT suppression may thus activate FTO-mediated activation of adipogenic transcription factors such as RUNX1T1, PPARγ, CEBPα, SREBP1, and PGC1α. Milk-mediated exosomal transfer of DNMT-targeting miRNAs might exert inhibitory posttranscriptional activity on adipose tissue DNMT1 expression promoting adipocyte differentiation and adipogenesis.

10. Myogenesis

Muscle mass acquisition in the adult human is primarily dependent on mechanical stimuli and active muscle contraction, which activates mTORC1 signaling [251,252]. Repetitive active muscle contractions significantly upregulate the metabolic transcription factor NR4A3 [253]. The newborn infant, however, with a still undeveloped neuromuscular system may depend on other stimuli for muscle cell differentiation and growth. In fact, NR4A3 expression is involved in postnatal development and its expression critically depends on nutritional status [254]. Milk-derived exosomal miRNAs apparently provide the required epigenetic signals for muscle cell differentiation and appropriate muscle protein acquisition. It should be kept in mind that NR4A3 expression is epigenetically induced by NR4A3 promoter demethylation [207]. Genome demethylation with either 5-azacytidine treatment or overexpression of the antisense RNA against DNMT1 induced transdifferentiation of mouse fibroblasts into myoblasts [242,255]. Furthermore, it has been shown that demethylation of the distal enhancer of the MyoD gene and the MyoG promoter is essential for the initiation of the myogenic differentiation program [256,257]. Milk-miRNA-mediated suppression of DNMT1 expression may thus augment myogenesis via epigenetic activation of myogenic transcription factors, which closely interact with mTORC1 signaling [258,259].
miRNA-148a is not only involved in adipogenesis but also enhances myogenic differentiation. Overexpression of miRNA-148a significantly promoted myogenic differentiation of both C2C12 myoblast and primary muscle cells. Blocking the function of miRNA-148a with a 2′-O-methylated antisense oligonucleotide inhibitor repressed C2C12 myoblast differentiation [260]. Rho-associated coiled-coil containing protein kinase 1 (ROCK1), a known inhibitor of myogenesis, has been identified as a direct target of miRNA-148a (Table 2) [261].
Members of the Polycomb group proteins (PcGs), YY1 and Ezh2 together regulate a number of muscle loci including both muscle structure genes and muscle relevant miRNAs [261]. Notably, Rybp, an YY1 interacting PcG protein, is able to target Rybp directly through a conserved binding site on its 3′-UTR. miRNA-29 promotes myogenesis via inhibition of Rybp, which acts as a negative regulator of skeletal myogenesis [262]. It is thus conceivable that milk-derived exosomal miRNA-148a and miRNA-29 support the epigenetic program of myogenesis.

11. Osteogenesis

Recent evidence indicates that NRF2 represents a key pathway in regulating bone metabolism. NRF2 expression, which is upregulated by DNMT inhibition [162], is required for normal postnatal bone acquisition in mice [263]. Mice lacking NRF2 exhibited a marked deficit in postnatal bone acquisition, which was most severe at 3 weeks of age when osteoblast numbers were 12-fold less than observed in control animals [263]. Thus, milk exosomal miRNA-mediated suppression of DNMTs may promote NRF2-driven postnatal osteogenesis. HDAC4 and TGFβ3 have been demonstrated to function as negative regulators in chondrocytes and osteoblasts. Importantly, miRNA-29b promotes osteogenesis by directly down-regulating these negative regulators of osteoblast differentiation through binding to target 3′-UTR sequences [264]. Thus, miRNA-29b is a key regulator of development of the osteoblast phenotype by targeting anti-osteogenic factors [264].
RUNX2 is another important regulator of osteogenesis. HDAC4 and HDAC5 deacetylate RUNX2, allowing the protein to undergo Smurf-mediated degradation. Inhibition of HDAC increases RUNX2 acetylation, and potentiates bone morphogenetic protein 2 (BMP-2)-stimulated osteoblast differentiation thereby increasing bone formation [265]. TGFβ inhibits osteoblast differentiation through inhibition of the function of RUNX2 by SMAD3 [266]. HDAC4 or 5 is required for efficient TGFβ-mediated inhibition of RUNX2 function [266]. Notably, bovine milk-derived miRNA-29b, which shares the identical seed sequence as human miRNA-29b, has been shown to increase dose-dependently in the serum of healthy human adults after consumption of pasteurized cow’s milk and increased RUNX2 expression in PBMCs of the milk consumers [79]. It is thus conceivable that milk exosome-derived miRNAs control the epigenetic status of RUNX2 and NRF2 promoting osteogenesis.
Recently, miRNA-21, which is also an abundant miRNA of bovine and human milk, has been shown to promote osteogenic differentiation of human bone marrow-derived stem cells [267]. Elevated expression of miRNA-21 has been demonstrated with an increased differentiation potential in human mesenchymal stem cells (hMSCs) during adipogenesis and osteogenesis [245,268,269]. Thus, milk-derived exosomal miRNAs may have an impact on hMSC differentiation. One of the five most abundant exosomal miRNAs isolated from bone marrow derived mesenchymal stem cells, which is involved in osteogenic differentiation, is miRNA-148a [270].
Taken together, miRNA-148a, the most abundant miRNA of milk, is epigenetically involved in the differentiation of Tregs, adipogenesis, myogenesis and osteogenesis.

12. Epidermal Differentiation

Intriguingly, not only bone formation but also epidermal barrier integrity of the skin depends on NRF2 signaling. Late cornified envelope 1 genes are transcriptional targets of NRF2 [271]. There is evidence that already in utero amniotic fluid activates NRF2 to improve epidermal barrier function [272]. After birth, milk-derived miRNAs targeting DNMTs may support epigenetic NRF2-mediated expression of cornified envelope proteins crucial for skin barrier function. The epidermal growth factor receptor (EGFR) plays a key role for the regulation of epidermal proliferation [273]. EGFR signaling and protein half-life are tightly regulated. Mitogen-inducible gene 6 (MIG6) is a multiadaptor protein involved in the regulation of receptor tyrosine kinase signaling. MIG6 regulates EGFR signaling and turnover by binding EGFR and directly inhibiting tyrosine kinase activity, increasing clathrin-dependent EGFR endocytosis and trafficking into the lysosome, promoting EGFR degradation [274,275,276]. MIG6 has been identified as a negative regulator of EGFR-mediated skin morphogenesis [277]. Deletion of the mouse gene encoding MIG6 causes hyperactivation of endogenous EGFR and sustained signaling through the MAPK pathway [277]. It is important to mention that MIG6 has been identified as a direct target of miRNA-148a (Table 2) [278]. In this regard, milk-derived exosomal miRNA-148a may promote epidermal proliferation as well as proliferation of other EGFR-dependent cells (Table 4) [279].

13. Milk-Mediated Epigenetic Signaling and Diseases of Civilization

There is recent interest in the role of miRNA signaling during the perinatal period for life-long epigenetic programming [18,280]. The great majority of clinical and epidemiological studies demonstrated that cow’s milk consumption during pregnancy increased fetal growth and birth weight of the newborn infant [280].
High birth weight and accelerated postnatal weight gain are associated with an increased risk of obesity. Accelerated infant and childhood weight gain are associated with increased energy intake and diminished satiety response at the age of 5 years [281]. Perinatal programming of energy intake and eating behavior provide a potential mechanism linking early life influences with later obesity, T2DM and cardiovascular disease [281]. Notably, single nucleotide polymorphisms of FTO, which are associated with increased FTO expression increase the risk for obesity and T2DM [282,283,284,285,286,287]. FTO expression is not only controlled by the nucleotide sequence but also by epigenetic regulation of FTO. Continued uptake of milk-derived exosomes that carry DNMT-targeting miRNAs may represent an overlooked mechanism that modifies early programming of the human epigenome promoting FTO-driven food intake and the development of diseases of civilization such as diabesity, allergy, neurodegenerative diseases, and cancer [135].
Continued consumption of cow’s milk during childhood and adolescence accelerates growth trajectories associated with increased BMI [234], linear growth [173] and early onset of menarche [288]. Accelerated growth during infancy and increased BMI in early life are known to enhance the risk for obesity [289,290,291], T2DM [292,293], allergy [294,295,296] and cancer later in life [297,298,299].

13.1. Obesity

Milk-derived miRNA-148a and miRNA-21 are critically involved in adipogenesis. Persistent intake of both adipogenic miRNAs apparently promotes obesity. Remember that miRNA-148a directly targets the pivotal genes regulating triglyceride synthesis (FAS), cholesterol homeostasis (LDLR), cholesterol efflux (ABCA1), and β-oxidation (CTPA1) [106]. miRNA-148a via targeting DNMT1 and subsequent promoter hypomethylation enhances adipogenic gene expression including insulin (INS), insulin-like growth factor-1 (IGF1), caveolin-1 (CAV1), leptin (LEP), PPAR-γ2 (PPARG2), fatty acid-binding protein 4 (FABP4), and lipoprotein lipase (LPL) [170,174,175,179,243]. Additionally, milk miRNA-148a-mediated FTO promoter demethylation may further enhance RNA transcription of the key adipogenic transcription factors RUNX1T1, PPARγ, CEBPα, and PGC1α via erasing m6A marks on their target mRNAs.
Milk-mediated exosomal transfer of DNMT-targeting miRNAs may thus exert inhibitory posttranscriptional activity on adipose tissue DNMT1 expression promoting adipocyte differentiation and adipogenesis. Increased hypothalamic FTO expression in the rat correlated with both visceral and epididymal fat mass and hyperphagia [233]. FTO overexpression in mice led to a dose-dependent increase in body and fat mass, and increased food intake resulting in obesity [147]. FTO overexpression enhanced the expression of the pro-adipogenic short isoform of the transcription factor RUNX1T1 [152], which stimulates mitotic clonal expansion of MEFs and thus enhances adipocyte numbers [247]. In addition, overexpression of FTO in porcine intramuscular preadipocytes increased the mRNA levels of adipocyte differentiation transcription factors PPARγ, CCAAT/enhancer binding protein-α (CEBPα), lipoprotein lipase (LPL) and fatty acid synthase (FAS) [248]. Milk-mediated epigenetic overexpression of FTO may thus promote the expression of key adipogenic transcription factors as well as clonal expansion of adipocyte numbers. Persistent milk signaling is thus a critical FTO-related epigenetic mechanism inducing obesity [135].
FABP4 is another key obesity-associated gene [300]. FABP4, a member of the intracellular lipid-binding protein family, is predominantly expressed in adipose tissue, and plays an important role in maintaining glucose and lipid homeostasis [301]. FABP4 functions as a cytosolic lipid chaperone in macrophages and is involved in regulating macrophage ER stress [302]. Increased expression of FABP4 in plasma and PBMCs has been associated with obesity and atherogenic dyslipidemia [301,303,304]. Furthermore, palmitate activation via FABP4 triggers hepatocellular apoptosis via altered phospholipid composition and steatosis by acylation into complex lipids [305]. Furthermore, FABP4 overexpression has been associated with upregulated expression of pro-inflammatory cytokines including interleukin 6 (IL-6) [306,307]. Indeed, a positive dose-dependent association has been detected between milk intake and increased serum IL-6 levels [308]. Thus, overexpression of FABP4 is involved in critical metabolic and pro-inflammatory aberrations associated with the complex pathogenesis of obesity and steatosis. Importantly, it has recently been demonstrated that miRNA-148a via targeting DNMT1 increased FABP4 promoter hyomethylation thereby enhancing FABP4 expression [243,307]. Thus, we predict that in analogy to FTO the expression of FABP4 may as well underly milk-mediated epigenetic upregulation.
There is recent interest in the role of miRNA-21 in the pathogenesis of obesity and diabetes [309]. Cow’s milk is a rich source of exosomal miRNA-21 [37,48]. It has been demonstrated that miRNA-21 acts as a bidirectional switch in the formation of insulin-producing cells by regulating the expression of target and downstream genes (SOX6, RPBJ and HES1) [310]. Deletion of murine miRNA-21 specifically in hepatocytes indicated a crucial role for hepatic miRNA-21 in metabolic disorders associated with diet-induced obesity. Deletion of miRNA-21 in hepatocytes increased insulin sensitivity and modulated the expression of multiple key metabolic transcription factors involved in fatty acid uptake, de novo-lipogenesis, gluconeogenesis and glucose output [311]. Furthermore, long-term inhibition of miRNA-21 reduced body weight and adipocyte size in db/db mice [312]. Thus, persistent uptake of exosomal miRNA-21 via persistent cow’s milk consumption may enhance the risk for obesity and T2DM [6,135,136].
Taken together, cow’s milk transfers obesogenic and orexigenic miRNAs, predominantly miRNA-148a and miRNA-21, that maintain an epigenetic status that is intimately involved in the pathogenesis of diabesity.

13.2. Type 2 Diabetes Mellitus

Early onset of menarche, which is related to milk consumption in early childhood [288], is associated with increased risk of T2DM (extensively reviewed recently [313]). Intake of cow’s milk in contrast to fermented milk products has been associated with incident T2DM as reported in the EPIC-InterAct Study including 315,428 European participants and 22,085 cases of T2DM [314]. In contrast to equivalent amounts of meat protein, high intakes of milk increased serum insulin and insulin resistance in 8-year-old boys [315]. The Physicians’ Health Study (n = 21,660) reported a significant increase of diabetes prevalence from 1.7% to 2.6% in men who consumed ≤1 whole milk serving per week in comparison to participants who consumed ≥2 whole milk serving per week, respectively [316]. Translational evidence linked milk-derived miRNAs to the pathogenesis of T2DM [135,317].
It has been demonstrated that cow’s milk consumption increases miRNA-29b levels in PBMCs in a dose-dependent manner [79]. The miRNA-29 family is among the most abundantly expressed miRNAs in pancreas and liver and is regarded as a diabetogenic risk marker [318,319,320]. Kurtz et al. [321] showed that miRNA-29 was upregulated in the livers of DIO mice and in Zucker diabetic fatty (fa/fa) rats. In this model, miRNA-29 functioned through regulation of the transcription factor FOXA2 (FOXA2-mediated regulation of PPARGC1A, HMGCS2 and ABHD5). Obesity in pregnant sheep leads to increased miRNA-29 expression in the liver tissue of offspring lambs, along with decreased markers of insulin signaling, suggesting fetal programming of miRNA-29 expression [322]. Dooley et al. [171] recently investigated the function of miRNA-29 in glucose regulation using miRNA-29a/b-1 (miRNA-29a)-deficient mice and newly generated miRNA 29b-2/c (miRNA-29c) deficient mice. miRNA-29a was identified as a positive regulator of insulin secretion in vivo, with dysregulation of the exocytotic machinery sensitizing β-cells to overt diabetes after unfolded protein stress. By contrast, in the liver both miRNA-29a and miRNA-29c were important negative regulators of insulin signaling via PI3K regulation. Global or hepatic insufficiency of miRNA-29 potently inhibited obesity and prevented the onset of diet induced insulin resistance [171]. These results confirmed strong regulatory functions for the miRNA-29 family in diabesity. Persistent transfer of milk exosomal miRNA-29 via cow’s milk consumption may thus represent a critical epigenetic factor in the pathogenesis T2DM.
Hypomethylation of specific CpG sites of FTO have been reported to enhance FTO expression [154]. In fact, decreased FTO methylation has been demonstrated in pancreatic islets of T2DM patients compared to non-diabetic controls [155]. Furthermore, CpG sites in the first intron of FTO of peripheral blood leukocytes exhibited significant hypomethylation in T2DM patients relative to controls [156].
miRNA-29 via targeting DNMT3B and miRNA-148a via targeting DNMT1 may decrease FTO promoter methylation associated with higher FTO expression resulting in decreased m6A levels in mRNAs. In fact, the m6A contents in the RNA from T2DM patients and diabetic rats were significantly lower compared with the control groups [323]. Notably, FTO mRNA levels were significantly higher in T2DM patients than in controls and inversely correlated with m6A content of mRNAs [323]. Thus, not only SNPs result in FTO overexpression but more frequent epigenetic modifications such as milk-mediated FTO overexpression should be appreciated as key drivers of diabesity.
Increased FABP4 expression has been linked to insulin resistance and T2DM [301,324,325,326]. Expression of FABP4 in the muscle and adipose tissues of T2DM rats were positively correlated [324]. Elevation of circulating FABP4 levels is associated with diabesity, hypertension, cardiac dysfunction, atherosclerosis, and cardiovascular events [325,326]. It is noteworthy to mention that SNPs associated with increased expression of FTO and FABP4 are related to increased milk yield, milk fat and protein content of dairy cows [327,328].

13.3. Cancer

Milk consumption has been associated with dose-dependent mortality increase [308]. In contrast, low consumption of milk and other dairy products due to lactose intolerance was associated with decreased risks of lung, breast, and ovarian cancers in a population-based study in Sweden (n = 22,788) [329]. A prospective study of 25,892 Norwegian women reported that consumers of 0.75 L or more of full-fat milk daily had a relative risk of 2.91 for breast cancer compared with those who consumed 0.15 L or less [330]. Recent evidence underlines that FTO expression may have a critical role for the risk of breast cancer, especially in HER2-overexpressed breast cancer [331]. Notably, exogenous FABP4 was shown to increase breast cancer cell proliferation [332].
There is compelling evidence for the association of whole milk consumption and prostate cancer (PCa), the most common cancer in men of civilized societies [316,317]. A recent meta-analysis considering 11 population-based cohort studies involving 778,929 individuals demonstrated the existence of a linear dose-response relationship between whole milk intake and increase of PCa mortality risk [333]. Intriguingly, recent evidence links miRNA-148a to the promotion of LNCaP prostate cell growth [334]. Importantly, miRNA-148a targets the largest number of known PCa drivers [334]. The addition of cow milk as an exogenous source of miRNA-148a to LNCaP prostate cancer cells in vitro stimulated PCa cell growth producing an average increase in growth rate of over 30% [335]. EGFR signaling promotes survival of prostate tumor-initiating cells and circulating tumor cells that metastasize to bone [336]. Note that EGFR expression in PCa cells is negatively regulated by MIG6 [337], which is a direct target of miRNA-148a [278].
In contrast to PCa, a meta-analysis involving over 900,000 subjects and over 5200 colorectal cancer (CRC) cases supports an inverse association between nonfermented milk consumption and risk of CRC in men [338]. It should be noticed that in contrast to fermented milk, nonfermented milk contains higher amounts of bioactive miRNAs including miRNA-148a, the most abundant miRNA of cow’s milk [63]. Downregulation of miRNA-148a expression plays a critical role in CRC carcinogenesis and progression [339,340,341]. Thus, milk-derived miRNA-148a loaded exosomes may substitute miRNA-148a deficiency in colorectal adenoma cells thereby preventing their further progression to CRC.
In the pathogenesis of PCa, miRNA-148a is apparently a critically ‘oncomiR’ such as miRNA-21 [342,343,344,345], which is one of the earliest identified cancer-promoting ‘oncomiRs’, targeting numerous tumor suppressor genes associated with proliferation, apoptosis and invasion [346,347,348]. Moreover, exosomal miRNA-21 has been considered as potential biomarker of cancer [349]. Furthermore, increased expression of circulating miRNA-21 has been reported in patients with breast cancer [350], lung cancer [350], colorectal carcinoma [350], and hepatocellular carcinoma [351,352,353]. Hepatocellular carcinoma has recently been related to increased consumption of cow’s milk [354].
Exosomal milk-derived miRNA-148a and miRNA-21 may thus provide oncogenic signals inducing an epigenetic landscape for tumorigenesis maintained by the consumption of cow’s milk in the majority of cancers except CRC.

13.4. Neurodegenerative Diseases

Accumulating evidence points to the important role of dietary epigenetic regulation in the amyloidopathy Alzheimer’s disease (AD) and the synucleinopathy Parkinson’s disease (PD) [355,356,357,358,359]. Notably, AD and PD are both tauopathies. mTORC1 induces abnormally hyperphosphorylated tau proteins, which aggregate resulting in compromised microtubule stability [360]. Abnormally hyperphosphorylated tau aggregates form paired helical filaments in neurofibrillary tangles, a key hallmark of AD and other tauopathies [361]. mTORC1 is involved in regulating tau distribution in subcellular organelles and in the initiation of tau secretion from cells to extracellular space [361]. mTORC1 was activated in the AD brains and the activation level of mTOR signaling correlates with cognitive severity of AD patients [362]. As outlined above, FTO plays a pivotal role for mTORC1 activation [159,160] and milk has been identified as a critical activator of mTORC1-dependent translation [135,136].

13.4.1. Alzheimer’s Disease

AD was recently defined as type 3 diabetes mellitus (T3DM) with the combination of apoE4 homozygosity [355,363]. Carriers of the common FTO rs9939609 A allele polymorphism exhibit a reduction in frontal lobe volume of the brain and an impaired verbal fluency performance [364,365]. A population-based study from Sweden found that carriers of the FTO rs9939609 A allele have an increased risk for incident AD [366]. The FTO risk allele rs9939609A is associated with lower nucleus accumbens volumes, suggesting that the higher body weight of risk-allele carriers might be due to changes within reward-related brain structures [366]. Furthermore, an interaction between FTO and APOE was found, with increased risk for dementia for those carrying both FTO AA and APOE ε4 [367]. Increased levels of brain APOE ε4 mRNA have been detected in AD cases compared to controls with the same allele [368]. The APOE ε4 allele is associated with a gene-dose-dependent increase in AD risk and in the severity of amyloid-β (Aβ) pathology [369], whereas the APOE ε3 allele is thought to protect against Aβ neurotoxicity [369]. A transgenic mouse model of AD expressing human APOE isoforms indicated that different APOE alleles might influence clearing soluble Aβ from the brain [370]. Blocking the apoE/Aβ interaction ameliorates Aβ-related pathology in APOE ε2 and ε4 targeted replacement AD model mice [371].
Interestingly, APOE has recently been demonstrated to be differentially methylated in AD [372]. The three common alleles of APOE, ε2, ε3 and ε4, are defined by two SNPs that reside in the coding region of exon 4, which overlaps with a well-defined CpG island (CGI). Both SNPs change not only the protein codon but also the quantity of CpG dinucleotides, primary sites for DNA methylation. Foraker et al. [372] suggested that the presence of an ε4 allele changes the DNA methylation landscape of the APOE CGI and that such epigenetic alteration may contribute to AD susceptibility. To explore the relationship between APOE genotype, AD risk, and DNA methylation of the APOE CGI, they evaluated the methylation profiles of post mortem brain from 15 AD and 10 control subjects. They observed a tissue-specific decrease in DNA methylation with AD and identified two AD-specific differentially methylated regions (DMRs), which were also associated with APOE genotype. One DMR was completely unmethylated in a subpopulation of genomes, possibly due to a subset of brain cells carrying deviated APOE methylation profiles. This study suggests that the APOE CGI is differentially methylated in AD brain in a tissue- and APOE-genotype-specific manner, which might contribute to neural cell dysfunction in AD brain [372]. Genetic variation in introns 1 and 2 of the FTO gene may as well contribute to AD risk [373].
It is conceivable that in analogy to APOE, SNPs of FTO may modify FTO methylation. Remarkably, impaired satiation and increased feeding behavior has been reported in the triple-transgenic AD mouse model [374], which may point to an increased FTO expression. Exosomal transfer of DNMT1-targeting miRNA-148a via cow’s milk consumption may decrease APOE and FTO methylation. APOE and FTO SNPs may as well modify the magnitude of functionally important CpG methylations.

13.4.2. Parkinson’s Disease

Several studies show an association between milk consumption and the risk of PD [375,376,377,378,379,380,381]. The largest meta-analysis of 304,193 subjects including 1083 PD cases reported a linear dose-response relationship between milk intake and PD risk, which increased by 17% for every 200 g/day increment in milk intake [380]. Recently, milk intake has been associated with substantia nigra neuron loss in decedent brains unaffected by PD [381]. The impairment of DNA methylation has been implicated to represent a crucial mechanism of cognitive aging and related neurodegeneration [382]. The expression of α-synuclein (SNCA) is an important factor in the pathogenesis of PD [383,384]. Decreased methylation at SNCA intron 1 might contribute to deregulation of α-synuclein expression in sporadic PD cases, highlighting the involvement of aberrant epigenetic mechanisms in PD pathology [383,384]. One of the major hallmarks of PD is the occurrence of intracellular protein deposits in the dying neurons, termed Lewy bodies, which contain different proteins, including aggregated α-synuclein and its interacting protein synphilin-1 [385,386]. In a yeast model, α-synuclein inhibited phospholipase D, induced lipid droplet accumulation, and affected vesicle trafficking [387]. A number of common genetic variants have been identified, which contribute to cognitive dysfunction in PD, including variants in catechol-O-methyl-transferase, microtubule-associated protein tau, apoE, mutations in glucocerebrosidase and α-synuclein [388,389]. Importantly, α-synuclein sequesters DNMT1 from the nucleus [390]. In fact, a significant decrease in DNA methylation in the frontal cortex of patients with PD and the related disorder Dementia with Lewy bodies, have been associated with the retention of DNMT1 in the cytoplasm [390]. The DNMT1-targeting miRNA-148a plays a critical role for the regulation of neurological development in the brain of the zebrafish [391]. As exosomes are able to cross the blood-brain barrier, it is conceivable that bovine milk exosomes reach human brain cells.
Continued consumption of cow’s milk and persistent uptake of bovine exosomal miRNA-148a, which is identical with human miRNA-148a, may represent an epigenetic mechanism suppressing DNMT1, which via SNCA demethylation may increase the expression of α-synuclein, a key aggregating protein in PD (Table 5).

14. Metformin

There is compelling evidence that all diseases of civilization, i.e., diabesity, neurodegenerative diseases, breast and prostate cancer are related to overexpression of mTORC1 [392,393,394,395,396,397,398]. We have recently presented evidence that metformin functions at multiple regulatory layers as an inhibitor of mTORC1 signaling [399]. In this regard, attenuation of mTORC1 signaling via metformin is just the opposite of milk-induced activation of mTORC1 signaling [136].
Interestingly, Zhong et al. [400] recently reported that metformin induces genome-wide alterations in DNA methylation by modulating the activity of S-adenosylhomocysteine hydrolase (SAHH). The developmentally regulated H19 lncRNA binds to and inhibits SAHH, the only mammalian enzyme capable of hydrolyzing S-adenosylhomocysteine (SAH). SAH is a potent feedback inhibitor of S-adenosylmethionine (SAM)-dependent methyltransferases that methylate diverse cellular components, including DNA, RNA, proteins, lipids and neurotransmitters [401]. Zhou et al. [402] demonstrated that H19 knockdown activates SAHH, leading to increased DNMT3B-mediated methylation of an lncRNA-encoding gene Nctc1 within the Igf2-H19-Nctc1 locus. Genome-wide methylation profiling revealed methylation changes at numerous gene loci consistent with SAHH modulation by H19 [402]. Intriguingly, metformin acts by upregulating miRNA let-7 through AMPK activation, leading to degradation of H19 lncRNA, which normally binds to and inactivates SAHH. Thus, metformin-induced H19 knockdown activates SAHH, enabling DNMT3B to methylate a subset of genes. It should be noted that all three DNMTs (DNMT1, DNMT3A and DNMT3B) are SAM-dependent. In this regards, milk-miRNA-148a and miRNA-29b-mediated DNMT suppression resulting in DNA demethylation features just the opposite epigenetic signaling compared to metformin-induced DNA methylation.
It should be noticed that metformin’s action on mTORC1 signaling and metformin’s epigenetic modifications in DNA methylation may be interconnected. Promoter methylation of NRF2 attenuates the expression of NRF2, which is a key transcription factor promoting MTOR expression [163]. In fact, coadministration of metformin with rapamycin effectively inhibited PCa progression in HiMyc mice [403]. Metformin lowers Ser-129 phosphorylated α-synuclein levels via mTOR-dependent protein phosphatase 2A activation [404]. In human, tau transgenic mice, metformin has been shown to act on tau phosphorylation via mTOR/protein phosphatase 2A signaling and may thus be of therapeutic value for the treatment of AD [405].

15. Enhancement of Dairy Milk Yield: A Potential Health Hazard

Enhanced milk quality and quantity has become a major selection criterion for the genetic modification of dairy livestock. Epigenetic miRNA-mediated regulations play a major role in bovine mammary gland development and lactation performance [111,122]. Key miRNAs that are abundantly expressed in lactating bovine MECs that promote lactation performance, lipid and protein synthesis include the DNMT-targeting miRNA-148/152- and the miRNA-29 family [116,117,122]. The selection of dairy cows with high expression of these lactogenic miRNAs bears the risk of increased milk exosomal transfer of these DNMT-targeting miRNAs to the human milk consumer [135]. Thus, efforts of dairy research to increase the milk yield of dairy cows may modify the composition and miRNA content of bovine milk exosomes reaching the human milk consumer (Figure 4). Intriguingly, in bovine MEC cultures, the expression of miRNA-148a was stimulated by treatment with dexamethasone, insulin, and prolactin (DIP) [117]. The medium-to-cell expression ratio of miRNA-148a was significantly elevated in these DIP-treated bovine MECs, suggesting extracellular secretion of miRNA-148a into the culture medium after hormonal stimulation of lactation [117]. As already delineated, miRNA-mediated suppression of DNMT expression and consecutive hypomethylation of lactation-related genes (AKT, PPARG, SREBP1, CSN1S1, ELF5, GLUT1) activates lipogenesis, protein synthesis and thus milk yield [108,109,114]. Via exosome transfer, milk of high yield dairy cows may expose the human milk consumer to a most critically overexpressed epigenetic machinery. Maximization of lactation performance over the last decades apparently modified the epigenetic signaling magnitude of cow’s milk further increasing the risk of diseases of civilization (Figure 4). Whereas veterinary medicine unintentionally further increases the burden of miRNA-148a for the human milk consumer, lipidologists are concerned about high expression of miRNA-148a in the context of dyslipidemia and cardiovascular disease and recommend miRNA-148a inhibition as a promising therapeutic approach [406].

16. Future Prospects and Conclusions

Milk, mammals’ masterpiece of evolution for maternal-neonatal programming, apparently modifies critical checkpoints of epigenetic regulation of the milk recipient, who under physiological conditions is the newborn infant. Based on our translational insights, we have identified a fundamental epigenetic signaling motive of milk that involves the transfer of DNMT-targeting miRNAs, such as milk’s most abundant miRNA-148a, to the milk recipient. miRNA-mediated DNMT suppression results in hypomethylation and thereby activation of pivotal developmental genes important for metabolic (INS, IGF1, CAV1), immunological (FOXP3, NRA4), adipogenic (FTO, FABP4, CAV1, PPARG2, SREBP1, LPL), myogenic (NR4A3), osteogenic (NRF2), and epidermal (NRF2) programming. Milk’s epigenetic miRNA signaling predominantly affects stem cell differentiation such as FTO-mediated adipogenesis. In this regard, milk can be regarded as mammals’ natural “doping system” modifying the recipient’s epigenome. In contrast, metformin, the most common biguanide drug for the treatment of T2DM and for the prevention of Western diseases, increases DNA genome-wide DNA methylation. It should be kept in mind that mammalian biology restricts the epigenetic doping of milk to the limited period of lactation and controls this essential system via the action of the well-preserved species-adapted lactation genome.
There is good reason to conclude that milk’s epigenetic machinery during postnatal life is of critical importance for life-long metabolic programming. It is conceivable that human milk’s epigenetic signaling is beneficial for the infant’s development and health. It is thus of critical concern that milk’s miRNA-based epigenetic signaling is deficient or functionally absent in artificial infant formula bearing the risk of inappropriate metabolic and immunological programming.
We conclude that the persistent abuse of milk’s epigenetic signaling via continued consumption of pasteurized cow’s milk increases the risk for diseases of civilization. Persistent hypomethylation of critical genes such as FTO are associated with the pathogenesis of diabesity, neurodegenerative diseases, and common cancers. Whereas fermentation of milk impairs milk’s exosomal miRNAs, pasteurized, refrigerated cow’s milk still pollutes abundant miRNAs with epigenetic potential into the human food chain. In fact, since the 1950s with the widespread distribution of household refrigerators the incidence of non-communicable diseases of civilization increased steadily. A deeper understanding of milk’s epigenetic capabilities makes “non-communicable” diseases to be communicable. In this regard, we are afraid of commercial efforts enforcing lactation performance in dairy cows which we claim to represent a serious health hazard modifying the human epigenome and epitranscriptome. Whereas pasteurization was formerly introduced to remove pathogenic bacteria from milk, we urge to remove milk’s DNMT-targeting miRNAs from the human food chain. The elimination of commercial milk’s epigenetic machinery but its introduction into artificial infant formula will be two promising approaches for the prevention of Western diseases of civilization.

Acknowledgments

G.S. is funded by the BMFT German Epigenome Programme (DEEP: 01KU1216J).

Author Contributions

B.C.M. and G.S. performed translational research. B.C.M. wrote the manuscript and gathered translational evidence for milk’s role as an epigenetic regulator. G.S. supported the manuscript especially in the field of lipid metabolism. Both authors proofread and approved the final manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

AGO2: argonaute 2; AKT: V-AKT murine thymoma viral oncogene homolog; ASC: adipose stem cells; BAT: brown adipose tissue; BCAA: branched-chain amino acid; BMI: body mass index; BMP: bone morphogenetic protein; CDX2: caudal-type homeobox transcription factor 2; CMA: cow’s milk allergy; CRC: colorectal cancer; DMR: differentially methylated region; DNMT: DNA methyltransferase; EGFR: epidermal growth factor receptor; EMT: epithelial-mesenchymal transition; ESCRT: endosomal sorting complex required for transport; EV: extracellular vesicle; FABP4: fatty acid binding protein 4; FAS: fatty acid synthase; FoxP3: forkhead box P3; FTO: fat mass- and obesity-associated gene; GLUT1: glucose transporter 1; HNRNPA2B1: heterogeneous nuclear ribonucleoprotein A2B1; HSP: heat shock protein; HuR: human antigen R; IDAX: inhibitor of DVL/axin complex; IgE: immunoglobulin E; IGF-1: insulin-like growth factor-1; IGF1R: insulin-like growth factor-1 receptor; IκBα: nuclear factor κB inhibitor α; IL: interleukin; ILV: intralumial vesicles (ILVs); INS: insulin gene; LCT: lactase gene; m6A: N6-methyladenosine; LPL: lipoprotein lipase; METTL: methyltransferase-like; MFG: milk fat globule; MFGM: milk fat globule membrane; miRNA: micro-ribonucleic acid; ILV: intralumial vesicles; MIG6: mitogen-inducible gene 6; mTORC1: mechanistic target of rapamycin complex 1; MVB: multi-vesicular body; NEC: necrotizing enterocolitis; NF-κB: nuclear factor κB; p53: transformation-related protein 53; NR4A3: nuclear receptor subfamily 4, group A, member 3; NRF2: nuclear factor erythroid 2-related factor 2; PCa: prostate cancer; PCNA: proliferating cell nuclear antigen; NFKBI: nuclear factor of κ light chain gene enhancer in B cells inhibitor α; PBMC: peripheral blood mononuclear cell; PI3K: phosphatidylinositol 3-kinase; PGC1α: PPAR-γ coactivator 1-α; PPARγ: peroxisome proliferator-activated receptor-γ; PP2A: protein phosphatase 2A; RASGRP1: Ras guanyl nucleotide-releasing protein-1; RNA: ribonucleic acid; RISC: RNA-induced silencing complex; ROCK1: Rho-associated coiled-coil containing protein kinase 1; RUNX1T1: Runt-related transcription factor 1, translocated to, 1; SAH: S-adenosylhomocysteine; SAHH: S-adenosylhomocysteine hydrolase; SAM: S-adenosylmethionine; SCD1: stearoyl-CoA desaturase 1; SNP: single nucleotide polymorphisms; SREBP-1: sterol regulatory element-binding protein 1; TCR: T cell receptor; T2DM: type 2 diabetes mellitus; T3DM: type 3 diabetes mellitus; TET: ten-eleven-translocation; TGFβ: transforming growth factor-β; TNF: tumor necrosis factor; TSDR: Treg-specific demethylated region; UTR: untranslated region; WAT: white adipose tissue; YBX1: RNA-binding protein Y-box protein 1.

References

  1. Godfrey, K.M.; Costello, P.M.; Lillycrop, K.A. Development, epigenetics and metabolic programming. Nestle Nutr. Inst. Workshop Ser. 2016, 85, 71–80. [Google Scholar] [PubMed]
  2. Landecker, H. Food as exposure: Nutrinonal epigenetics and the new metabolism. Biosocieties 2011, 6, 167–194. [Google Scholar] [CrossRef] [PubMed]
  3. Vickers, M.H. Early life nutrition, epigenetics and programming of later life disease. Nutrients 2014, 6, 2165–2178. [Google Scholar] [CrossRef] [PubMed]
  4. Power, M.L.; Schulkin, J. Maternal regulation of offspring development in mammals is an ancient adaptation tied to lactation. Appl. Transl. Genom. 2013, 2, 55–63. [Google Scholar] [CrossRef] [PubMed]
  5. Ozkan, H.; Tuzun, F.; Kumral, A.; Duman, N. Milk kinship hypothesis in light of epigenetic knowledge. Clin. Epigenet. 2012, 4, 14. [Google Scholar] [CrossRef] [PubMed]
  6. Melnik, B.C.; John, S.M.; Schmitz, G. Milk is not just food but most likely a genetic transfection system activating mTORC1 signaling for postnatal growth. Nutr. J. 2013, 12, 103. [Google Scholar] [CrossRef] [PubMed]
  7. Mathers, J.C.; Strathdee, G.; Relton, C.L. Induction of epigenetic alterations by dietary and other environmental factors. Adv. Genet. 2010, 71, 3–39. [Google Scholar] [PubMed]
  8. Lillycrop, K.A.; Burdge, G.C. Epigenetic mechanisms linking early nutrition to long term health. Best Pract. Res. Clin. Endocrinol. Metab. 2012, 26, 667–676. [Google Scholar] [CrossRef] [PubMed]
  9. Koletzko, B.; Chourdakis, M.; Grote, V.; Hellmuth, C.; Prell, C.; Rzehak, P.; Uhl, O.; Weber, M. Regulation of early human growth: Impact on long-term health. Ann. Nutr. Metab. 2014, 65, 101–109. [Google Scholar] [CrossRef] [PubMed]
  10. Ip, S.; Chung, M.; Raman, G.; Chew, P.; Magula, N.; DeVine, D.; Trikalinos, T.; Lau, J. Breastfeeding and maternal and infant health outcomes in developed countries. Evid. Rep. Technol. Assess. (Full Rep) 2007, 153, 1–186. [Google Scholar]
  11. Victora, C.G.; Bahl, R.; Barros, A.J.; França, G.V.; Horton, S.; Krasevec, J.; Murch, S.; Sankar, M.J.; Walker, N.; Rollins, N.C.; Lancet Breastfeeding Series Group. Breastfeeding in the 21st century: Epidemiology, mechanisms, and lifelong effect. Lancet 2016, 387, 475–490. [Google Scholar] [CrossRef]
  12. Kramer, M.S. Breast is best: The evidence. Early Hum. Dev. 2010, 86, 729–732. [Google Scholar] [CrossRef] [PubMed]
  13. Melnik, B.C.; John, S.M.; Carrera-Bastos, P.; Schmitz, G. Milk: A postnatal imprinting system stabilizing FoxP3 expression and regulatory T cell differentiation. Clin. Transl. Allergy 2016, 6, 18. [Google Scholar] [CrossRef] [PubMed]
  14. Alsaweed, M.; Lai, C.T.; Hartmann, P.E.; Geddes, D.T.; Kakulas, F. Human milk miRNAs primarily originate from the mammary gland resulting in unique miRNA profiles of fractionated milk. Sci. Rep. 2016, 6, 20680. [Google Scholar] [CrossRef] [PubMed]
  15. Bakhshandeh, B.; Kamaleddin, M.A.; Aalishah, K. A Comprehensive review on exosomes and microvesicles as epigenetic factors. Curr. Stem Cell Res. Ther. 2017, 12, 31–36. [Google Scholar] [CrossRef] [PubMed]
  16. Zempleni, J.; Baier, S.R.; Howard, K.M.; Cui, J. Gene regulation by dietary microRNAs. Can. J. Physiol. Pharmacol. 2015, 93, 1097–1102. [Google Scholar] [CrossRef] [PubMed]
  17. Alsaweed, M.; Hartmann, P.E.; Geddes, D.T.; Kakulas, F. MicroRNAs in breastmilk and the lactating breast: Potential immunoprotectors and developmental regulators for the infant and the mother. Int. J. Environ. Res. Public Health 2015, 12, 13981–14020. [Google Scholar] [CrossRef] [PubMed]
  18. Floris, I.; Kraft, J.D.; Altosaar, I. Roles of microRNA across prenatal and postnatal periods. Int. J. Mol. Sci. 2016, 17, E1994. [Google Scholar] [CrossRef] [PubMed]
  19. Melnik, B.C.; Kakulas, F.; Geddes, D.T.; Hartmann, P.E.; John, S.M.; Carrera-Bastos, P.; Cordain, L.; Schmitz, G. Milk miRNAs: Simple nutrients or systemic functional regulators? Nutr. Metab. (Lond.) 2016, 13, 42. [Google Scholar] [CrossRef] [PubMed]
  20. Perge, P.; Nagy, Z.; Decmann, Á.; Igaz, I.; Igaz, P. Potential relevance of microRNAs in inter-species epigenetic communication, and implications for disease pathogenesis. RNA Biol. 2016, 1–11. [Google Scholar] [CrossRef] [PubMed]
  21. Zempleni, J.; Aguilar-Lozano, A.; Sadri, M.; Sukreet, S.; Manca, S.; Wu, D.; Zhou, F.; Mutai, E. Biological activities of extracellular vesicles and their cargos from bovine and human milk in humans and implications for infants. J. Nutr. 2017, 147, 3–10. [Google Scholar] [CrossRef] [PubMed]
  22. Chargaff, E.; West, R. The biological significance of the thromboplastic protein of blood. J. Biol. Chem. 1946, 166, 189–197. [Google Scholar] [PubMed]
  23. Wolf, P. The nature and significance of platelet products in human plasma. Br. J. Haematol. 1967, 13, 269–288. [Google Scholar] [CrossRef] [PubMed]
  24. Pan, B.T.; Johnstone, R.M. Fate of the transferrin receptor during maturation of sheep reticulocytes in vitro: Selective externalization of the receptor. Cell 1983, 33, 967–978. [Google Scholar] [CrossRef]
  25. Harding, C.; Heuser, J.; Stahl, P. Endocytosis and intracellular processing of transferrin and colloidal gold-transferrin in rat reticulocytes: Demonstration of a pathway for receptor shedding. Eur. J. Cell. Biol. 1984, 35, 256–263. [Google Scholar] [PubMed]
  26. Johnstone, R.M.; Adam, M.; Hammond, J.R.; Orr, L.; Turbide, C. Vesicle formation during reticulocyte maturation. Association of plasma membrane activities with released vesicles (exosomes). J. Biol. Chem. 1987, 262, 9412–9420. [Google Scholar] [PubMed]
  27. Yáñez-Mó, M.; Siljander, P.R.; Andreu, Z.; Zavec, A.B.; Borràs, F.E.; Buzas, E.I.; Buzas, K.; Casal, E.; Cappello, F.; Carvalho, J.; et al. Biological properties of extracellular vesicles and their physiological functions. J. Extracell. Vesicles 2015, 4, 27066. [Google Scholar] [CrossRef] [PubMed]
  28. Colombo, M.; Raposo, G.; Théry, C. Biogenesis, secretion, and intercellular interactions of exosomes and other extracellular vesicles. Annu. Rev. Cell Dev. Biol. 2014, 30, 255–289. [Google Scholar] [CrossRef] [PubMed]
  29. Van Niel, G.; Porto-Carreiro, I.; Simoes, S.; Raposo, G. Exosomes: A common pathway for a specialized function. J. Biochem. 2006, 140, 13–21. [Google Scholar] [CrossRef] [PubMed]
  30. Fritz, J.V.; Heintz-Buschart, A.; Ghosal, A.; Wampach, L.; Etheridge, A.; Galas, D.; Wilmes, P. Sources and functions of extracellular small RNAs in human circulation. Annu. Rev. Nutr. 2016, 36, 301–336. [Google Scholar] [CrossRef] [PubMed]
  31. Zhang, W.; Peng, P.; Shen, K. Role of exosome shuttle RNA in cell-to-cell communication. Zhongguo Yi Xue Ke Xue Yuan Xue Bao 2016, 38, 480–483. [Google Scholar] [PubMed]
  32. Ratajczak, J.; Miekus, K.; Kucia, M.; Zhang, J.; Reca, R.; Dvorak, P.; Ratajczak, M.Z. Embryonic stem cell-derived microvesicles reprogram hematopoietic progenitors: Evidence for horizontal transfer of mRNA and protein delivery. Leukemia 2006, 20, 847–856. [Google Scholar] [CrossRef] [PubMed]
  33. Valadi, H.; Ekström, K.; Bossios, A.; Sjöstrand, M.; Lee, J.J.; Lötvall, J.O. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat. Cell Biol. 2007, 9, 654–659. [Google Scholar] [CrossRef] [PubMed]
  34. Turturici, G.; Tinnirello, R.; Sconzo, G.; Geraci, F. Extracellular membrane vesicles as a mechanism of cell-to-cell communication: Advantages and disadvantages. Am. J. Physiol. Cell Physiol. 2014, 306, C621–C633. [Google Scholar] [CrossRef] [PubMed]
  35. Nawaz, M.; Fatima, F.; Vallabhaneni, K.C.; Penfornis, P.; Valadi, H.; Ekström, K.; Kholia, S.; Whitt, J.D.; Fernandes, J.D.; Pochampally, R.; et al. Extracellular Vesicles: Evolving factors in stem cell biology. Stem Cells Int. 2016, 2016, 1073140. [Google Scholar] [CrossRef] [PubMed]
  36. Admyre, C.; Johansson, S.M.; Qazi, K.R.; Filén, J.J.; Lahesmaa, R.; Norman, M.; Neve, E.P.; Scheynius, A.; Gabrielsson, S. Exosomes with immune modulatory features are present in human breast milk. J. Immunol. 2007, 179, 1969–1978. [Google Scholar] [CrossRef] [PubMed]
  37. Chen, X.; Gao, C.; Li, H.; Huang, L.; Sun, Q.; Dong, Y.; Tian, C.; Gao, S.; Dong, H.; Guan, D.; et al. Identification and characterization of microRNAs in raw milk during different periods of lactation, commercial fluid, and powdered milk products. Cell Res. 2010, 20, 1128–1137. [Google Scholar] [CrossRef] [PubMed]
  38. Hata, T.; Murakami, K.; Nakatani, H.; Yamamoto, Y.; Matsuda, T.; Aoki, N. Isolation of bovine milk-derived microvesicles carrying mRNAs and microRNAs. Biochem. Biophys. Res. Commun. 2010, 396, 528–533. [Google Scholar] [CrossRef] [PubMed]
  39. Kosaka, N.; Izumi, H.; Sekine, K.; Ochiya, T. microRNA as a new immune-regulatory agent on breast milk. Silence 2010, 1, 7. [Google Scholar] [CrossRef] [PubMed]
  40. Izumi, H.; Kosaka, N.; Shimizu, T.; Sekine, K.; Ochiya, T.; Takase, M. Bovine milk contains microRNA and messenger RNA that are stable under degradative conditions. J. Dairy Sci. 2012, 95, 4831–4841. [Google Scholar] [CrossRef] [PubMed]
  41. Gu, Y.; Li, M.; Wang, T.; Liang, Y.; Zhong, Z.; Wang, X.; Zhou, Q.; Chen, L.; Lang, Q.; He, Z.; et al. Lactation-related microRNA expression profiles of porcine breast milk exosomes. PLoS ONE 2012, 7, e43691. [Google Scholar] [CrossRef] [PubMed]
  42. Reinhardt, T.A.; Lippolis, J.D.; Nonnecke, B.J.; Sacco, R.E. Bovine milk exosome proteome. J. Proteom. 2012, 75, 1486–1492. [Google Scholar] [CrossRef] [PubMed]
  43. Zhou, Q.; Li, M.; Wang, X.; Li, Q.; Wang, T.; Zhu, Q.; Zhou, X.; Wang, X.; Gao, X.; Li, X. Immune-related microRNAs are abundant in breast milk exosomes. Int. J. Biol. Sci. 2012, 8, 118–123. [Google Scholar] [CrossRef] [PubMed]
  44. Sun, Q.; Chen, X.; Yu, J.; Zen, K.; Zhang, C.Y.; Li, L. Immune modulatory function of abundant immune-related microRNAs in microvesicles from bovine colostrum. Protein Cell 2013, 4, 197–210. [Google Scholar] [CrossRef] [PubMed]
  45. Chen, T.; Xi, Q.Y.; Ye, R.S.; Cheng, X.; Qi, Q.E.; Wang, S.B.; Shu, G.; Wang, L.N.; Zhu, X.T.; Jiang, Q.Y.; et al. Exploration of microRNAs in porcine milk exosomes. BMC Genom. 2014, 15, 100. [Google Scholar] [CrossRef] [PubMed]
  46. Modepalli, V.; Kumar, A.; Hinds, L.A.; Sharp, J.A.; Nicholas, K.R.; Lefevre, C. Differential temporal expression of milk miRNA during the lactation cycle of the marsupial tammar wallaby (Macropus eugenii). BMC Genom. 2014, 15, 1012. [Google Scholar] [CrossRef] [PubMed]
  47. Na, R.S.; E, G.X.; Sun, W.; Sun, X.W.; Qiu, X.Y.; Chen, L.P.; Huang, Y.F. Expressional analysis of immune-related miRNAs in breast milk. Genet. Mol. Res. 2015, 14, 11371–11376. [Google Scholar] [CrossRef] [PubMed]
  48. Baddela, V.S.; Nayan, V.; Rani, P.; Onteru, S.K.; Singh, D. Physicochemical biomolecular insights into Buffalo milk-derived nanovesicles. Appl. Biochem. Biotechnol. 2016, 178, 544–557. [Google Scholar] [CrossRef] [PubMed]
  49. Munch, E.M.; Harris, R.A.; Mohammad, M.; Benham, A.L.; Pejerrey, S.M.; Showalter, L.; Hu, M.; Shope, C.D.; Maningat, P.D.; Gunaratne, P.H.; et al. Transcriptome profiling of microRNA by Next-Gen deep sequencing reveals known and novel miRNA species in the lipid fraction of human breast milk. PLoS ONE 2013, 8, e50564. [Google Scholar] [CrossRef] [PubMed]
  50. Alsaweed, M.; Lai, C.T.; Hartmann, P.E.; Geddes, D.T.; Kakulas, F. Human milk cells and lipids conserve numerous known and novel miRNAs, some of which are differentially expressed during lactation. PLoS ONE 2016, 11, e0152610. [Google Scholar] [CrossRef] [PubMed]
  51. Heid, H.W.; Keenan, T.W. Intracellular origin and secretion of milk fat globules. Eur. J. Cell Biol. 2005, 84, 245–258. [Google Scholar] [CrossRef] [PubMed]
  52. Gallier, S.; Vocking, K.; Post, J.A.; Van De Heijning, B.; Acton, D.; Van Der Beek, E.M.; Van Baalen, T. A novel infant milk formula concept: Mimicking the human milk fat globule structure. Colloids Surf. B Biointerfaces 2015, 136, 329–339. [Google Scholar] [CrossRef] [PubMed]
  53. Reinhardt, T.A.; Sacco, R.E.; Nonnecke, B.J.; Lippolis, J.D. Bovine milk proteome: Quantitative changes in normal milk exosomes, milk fat globule membranes and whey proteomes resulting from Staphylococcus aureus mastitis. J. Proteom. 2013, 82, 141–154. [Google Scholar] [CrossRef] [PubMed]
  54. Hassiotou, F.; Beltran, A.; Chetwynd, E.; Stuebe, A.M.; Twigger, A.J.; Metzger, P.; Trengove, N.; Lai, C.T.; Filgueira, L.; Blancafort, P.; et al. Breastmilk is a novel source of stem cells with multilineage differentiation potential. Stem Cells 2012, 30, 2164–2174. [Google Scholar] [CrossRef] [PubMed]
  55. Hassiotou, F.; Geddes, D.T.; Hartmann, P.E. Cells in human milk: State of the science. J. Hum. Lact. 2013, 29, 171–182. [Google Scholar] [CrossRef] [PubMed]
  56. Irmak, M.K.; Oztas, Y.; Oztas, E. Integration of maternal genome into the neonate genome through breast milk mRNA transcripts and reverse transcriptase. Theor. Biol. Med. Model. 2012, 9, 20. [Google Scholar] [CrossRef] [PubMed]
  57. Sun, J.; Aswath, K.; Schroeder, S.G.; Lippolis, J.D.; Reinhardt, T.A.; Sonstegard, T.S. MicroRNA expression profiles of bovine milk exosomes in response to Staphylococcus aureus infection. BMC Genom. 2015, 16, 806. [Google Scholar] [CrossRef] [PubMed]
  58. Klopfleisch, R.; Weiss, A.T.; Gruber, A.D. Excavation of a buried treasure—DNA, mRNA, miRNA and protein analysis in formalin fixed, paraffin embedded tissues. Histol. Histopathol. 2011, 26, 797–810. [Google Scholar] [PubMed]
  59. Streichert, T.; Otto, B.; Lehmann, U. MicroRNA expression profiling in archival tissue specimens: Methods and data processing. Mol. Biotechnol. 2012, 50, 159–169. [Google Scholar] [CrossRef] [PubMed]
  60. Record, M.; Carayon, K.; Poirot, M.; Silvente-Poirot, S. Exosomes as new vesicular lipid transporters involved in cell-cell communication and various pathophysiologies. Biochim. Biophys. Acta 2014, 1841, 108–120. [Google Scholar] [CrossRef] [PubMed]
  61. Izumi, H.; Tsuda, M.; Sato, Y.; Kosaka, N.; Ochiya, T.; Iwamoto, H.; Namba, K.; Takeda, Y. Bovine milk exosomes contain microRNA and mRNA and are taken up by human macrophages. J. Dairy Sci. 2015, 98, 2920–2933. [Google Scholar] [CrossRef] [PubMed]
  62. Pieters, B.C.; Arntz, O.J.; Bennink, M.B.; Broeren, M.G.; van Caam, A.P.; Koenders, M.I.; van Lent, P.L.; van den Berg, W.B.; de Vries, M.; van der Kraan, P.M.; et al. Commercial cow milk contains physically stable extracellular vesicles expressing immunoregulatory TGF-β. PLoS ONE 2015, 10, e0121123. [Google Scholar] [CrossRef] [PubMed]
  63. Howard, K.M.; Jati Kusuma, R.; Baier, S.R.; Friemel, T.; Markham, L.; Vanamala, J.; Zempleni, J. Loss of miRNAs during processing and storage of cow’s (Bos taurus) milk. J. Agric. Food Chem. 2015, 63, 588–592. [Google Scholar] [CrossRef] [PubMed]
  64. Yu, S.; Zhao, Z.; Sun, L.; Li, P. Fermentation results in quantitative changes in milk-derived exosomes and different effects on cell growth and survival. J. Agric. Food Chem. 2017, 65, 1220–1228. [Google Scholar] [CrossRef] [PubMed]
  65. Munagala, R.; Aqil, F.; Jeyabalan, J.; Gupta, R.C. Bovine milk-derived exosomes for drug delivery. Cancer Lett. 2016, 371, 48–61. [Google Scholar] [CrossRef] [PubMed]
  66. Benmoussa, A.; Lee, C.H.; Laffont, B.; Savard, P.; Laugier, J.; Boilard, E.; Gilbert, C.; Fliss, I.; Provost, P. Commercial dairy cow milk microRNAs resist digestion under simulated gastrointestinal tract conditions. J. Nutr. 2016, 146, 2206–2215. [Google Scholar] [CrossRef] [PubMed]
  67. Tian, T.; Wang, Y.; Wang, H.; Zhu, Z.; Xiao, Z. Visualizing of the cellular uptake and intracellular trafficking of exosomes by live-cell microscopy. J. Cell. Biochem. 2010, 111, 488–496. [Google Scholar] [CrossRef] [PubMed]
  68. Vickers, K.C.; Remaley, AT. Lipid-based carriers of microRNAs and intercellular communication. Curr. Opin. Lipidol. 2012, 23, 91–97. [Google Scholar] [CrossRef] [PubMed]
  69. Boon, R.A.; Vickers, K.C. Intercellular transport of microRNAs. Arterioscler. Thromb. Vasc. Biol. 2013, 33, 186–192. [Google Scholar] [CrossRef] [PubMed]
  70. Tian, T.; Zhu, Y.L.; Hu, F.H.; Wang, Y.Y.; Huang, N.P.; Xiao, Z.D. Dynamics of exosome internalization and trafficking. J. Cell. Physiol. 2013, 228, 1487–1495. [Google Scholar] [CrossRef] [PubMed]
  71. Tian, T.; Zhu, Y.L.; Zhou, Y.Y.; Liang, G.F.; Wang, Y.Y.; Hu, F.H.; Xiao, Z.D. Exosome uptake through clathrin-mediated endocytosis and macropinocytosis and mediating miR-21 delivery. J. Biol. Chem. 2014, 289, 22258–22267. [Google Scholar] [CrossRef] [PubMed]
  72. Yang, T.; Martin, P.; Fogarty, B.; Brown, A.; Schurman, K.; Phipps, R.; Yin, V.P.; Lockman, P.; Bai, S. Exosome delivered anticancer drugs across the blood-brain barrier for brain cancer therapy in Danio rerio. Pharm. Res. 2015, 32, 2003–2014. [Google Scholar] [CrossRef] [PubMed]
  73. Ha, D.; Yang, N.; Nadithe, V. Exosomes as therapeutic drug carriers and delivery vehicles across biological membranes: Current perspectives and future challenges. Acta Pharm. Sin. B 2016, 6, 287–296. [Google Scholar] [CrossRef] [PubMed]
  74. Lässer, C.; Alikhani, V.S.; Ekström, K.; Eldh, M.; Paredes, P.T.; Bossios, A.; Sjöstrand, M.; Gabrielsson, S.; Lötvall, J.; Valadi, H. Human saliva, plasma and breast milk exosomes contain RNA: Uptake by macrophages. J. Transl. Med. 2011, 9, 9. [Google Scholar] [CrossRef] [PubMed]
  75. Arntz, O.J.; Pieters, B.C.; Oliveira, M.C.; Broeren, M.G.; Bennink, M.B.; de Vries, M.; van Lent, P.L.; Koenders, M.I.; van den Berg, W.B.; van der Kraan, P.M.; et al. Oral administration of bovine milk derived extracellular vesicles attenuates arthritis in two mouse models. Mol. Nutr. Food Res. 2015, 59, 1701–1712. [Google Scholar] [CrossRef] [PubMed]
  76. Wolf, T.; Baier, S.R.; Zempleni, J. The intestinal transport of bovine milk exosomes is mediated by endocytosis in human colon carcinoma Caco-2 cells and rat small intestinal IEC-6 cells. J. Nutr. 2015, 145, 2201–2206. [Google Scholar] [CrossRef] [PubMed]
  77. Chen, T.; Xie, M.Y.; Sun, J.J.; Ye, R.S.; Cheng, X.; Sun, R.P.; Wei, L.M.; Li, M.; Lin, D.L.; Jiang, Q.Y.; et al. Porcine milk-derived exosomes promote proliferation of intestinal epithelial cells. Sci. Rep. 2016, 6, 33862. [Google Scholar] [CrossRef] [PubMed]
  78. Kusuma, R.J.; Manca, S.; Friemel, T.; Sukreet, S.; Nguyen, C.; Zempleni, J. Human vascular endothelial cells transport foreign exosomes from cow’s milk by endocytosis. Am. J. Physiol. Cell Physiol. 2016, 310, C800–C807. [Google Scholar] [CrossRef] [PubMed]
  79. Baier, S.R.; Nguyen, C.; Xie, F.; Wood, J.R.; Zempleni, J. MicroRNAs are absorbed in biologically meaningful amounts from nutritionally relevant doses of cow milk and affect gene expression in peripheral blood mononuclear cells, HEK-293 kidney cell cultures, and mouse livers. J. Nutr. 2014, 144, 1495–1500. [Google Scholar] [CrossRef] [PubMed]
  80. Shu, J.; Chiang, K.; Zempleni, J.; Cui, J. Computational characterization of exogenous microRNAs that can be transferred into human circulation. PLoS ONE 2015, 10, e0140587. [Google Scholar] [CrossRef] [PubMed]
  81. Li, R.; Dudemaine, P.L.; Zhao, X.; Lei, C.; Ibeagha-Awemu, E.M. Comparative analysis of the miRNome of bovine milk fat, whey and cells. PLoS ONE 2016, 11, e0154129. [Google Scholar] [CrossRef] [PubMed]
  82. Title, A.C.; Denzler, R.; Stoffel, M. Uptake and function studies of maternal milk-derived microRNAs. J. Biol. Chem. 2015, 290, 23680–23691. [Google Scholar] [CrossRef] [PubMed]
  83. Laubier, J.; Castille, J.; Le Guillou, S.; Le Provost, F. No effect of an elevated miR-30b level in mouse milk on its level in pup tissues. RNA Biol. 2015, 12, 26–29. [Google Scholar] [CrossRef] [PubMed]
  84. Auerbach, A.; Vyas, G.; Li, A.; Halushka, M.; Witwer, K. Uptake of dietary milk miRNAs by adult humans: A validation study. F1000Research 2016, 5, 721. [Google Scholar] [CrossRef] [PubMed]
  85. Alsaweed, M.; Lai, C.T.; Hartmann, P.E.; Geddes, D.T.; Kakulas, F. Human milk cells contain numerous miRNAs that may change with milk removal and regulate multiple physiological processes. Int. J. Mol. Sci. 2016, 17, E956. [Google Scholar] [CrossRef] [PubMed]
  86. Brenner, S.A. Extracellular ‘communicator RNA’. FEBS Lett. 1988, 233, 225–228. [Google Scholar] [CrossRef]
  87. Liang, H.; Huang, L.; Cao, J.; Zen, K.; Chen, X.; Zhang, C.Y. Regulation of mammalian gene expression by exogenous microRNAs. Wiley Interdiscip. Rev. RNA 2012, 3, 733–742. [Google Scholar] [CrossRef] [PubMed]
  88. Chen, X.; Liang, H.; Zhang, J.; Zen, K.; Zhang, C.Y. Secreted microRNAs: A new form of intercellular communication. Trends Cell Biol. 2012, 22, 125–132. [Google Scholar] [CrossRef] [PubMed]
  89. Chen, X.; Liang, H.; Zhang, J.; Zen, K.; Zhang, C.Y. Horizontal transfer of microRNAs: Molecular mechanisms and clinical applications. Protein Cell 2012, 3, 28–37. [Google Scholar] [CrossRef] [PubMed]
  90. Ambros, V. The functions of animal microRNAs. Nature 2004, 431, 350–355. [Google Scholar] [CrossRef] [PubMed]
  91. He, L.; Hannon, G.J. MicroRNAs: Small RNAs with a big role in gene regulation. Nat. Rev. Genet. 2004, 5, 522–531. [Google Scholar] [CrossRef] [PubMed]
  92. Weber, J.A.; Baxter, D.H.; Zhang, S.; Huang, D.Y.; Huang, K.H.; Lee, M.J.; Galas, D.J.; Wang, K. The microRNA spectrum in 12 body fluids. Clin. Chem. 2010, 56, 1733–1741. [Google Scholar] [CrossRef] [PubMed]
  93. Corrado, C.; Raimondo, S.; Chiesi, A.; Ciccia, F.; De Leo, G.; Alessandro, R. Exosomes as intercellular signaling organelles involved in health and disease: Basic science and clinical applications. Int. J. Mol. Sci. 2013, 14, 5338–5366. [Google Scholar] [CrossRef] [PubMed]
  94. Ludwig, A.K.; Giebel, B. Exosomes: Small vesicles participating in intercellular communication. Int. J. Biochem. Cell Biol. 2012, 44, 11–15. [Google Scholar] [CrossRef] [PubMed]
  95. Iraci, N.; Leonardi, T.; Gessler, F.; Vega, B.; Pluchino, S. Focus on extracellular vesicles: Physiological role and signalling properties of extracellular membrane vesicles. Int. J. Mol. Sci. 2016, 17, 171. [Google Scholar] [CrossRef] [PubMed]
  96. Kalra, H.; Drummen, G.P.; Mathivanan, S. Focus on extracellular vesicles: Introducing the next small big thing. Int. J. Mol. Sci. 2016, 17, 170. [Google Scholar] [CrossRef] [PubMed]
  97. Karlsson, O.; Rodosthenous, R.S.; Jara, C.; Brennan, K.J.; Wright, R.O.; Baccarelli, A.A.; Wright, R.J. Detection of long non-coding RNAs in human breastmilk extracellular vesicles: Implications for early child development. Epigenetics 2016. [Google Scholar] [CrossRef] [PubMed]
  98. Villarroya-Beltri, C.; Baixauli, F.; Gutiérrez-Vázquez, C.; Sánchez-Madrid, F.; Mittelbrunn, M. Sorting it out: Regulation of exosome loading. Semin. Cancer Biol. 2014, 28, 3–13. [Google Scholar] [CrossRef] [PubMed]
  99. Villarroya-Beltri, C.; Gutiérrez-Vázquez, C.; Sánchez-Cabo, F.; Pérez-Hernández, D.; Vázquez, J.; Martin-Cofreces, N.; Martinez-Herrera, D.J.; Pascual-Montano, A.; Mittelbrunn, M.; Sánchez-Madrid, F. Sumoylated hnRNPA2B1 controls the sorting of miRNAs into exosomes through binding to specific motifs. Nat. Commun. 2013, 4, 2980. [Google Scholar] [CrossRef] [PubMed]
  100. Squadrito, M.L.; Baer, C.; Burdet, F.; Maderna, C.; Gilfillan, G.D.; Lyle, R.; Ibberson, M.; De Palma, M. Endogenous RNAs modulate microRNA sorting to exosomes and transfer to acceptor cells. Cell Rep. 2014, 8, 1432–1446. [Google Scholar] [CrossRef] [PubMed]
  101. Koppers-Lalic, D.; Hackenberg, M.; Bijnsdorp, I.V.; van Eijndhoven, M.A.; Sadek, P.; Sie, D.; Zini, N.; Middeldorp, J.M.; Ylstra, B.; de Menezes, R.X.; et al. Nontemplated nucleotide additions distinguish the small RNA composition in cells from exosomes. Cell Rep. 2014, 8, 1649–1658. [Google Scholar] [CrossRef] [PubMed]
  102. Shurtleff, M.J.; Temoche-Diaz, M.M.; Karfilis, K.V.; Ri, S.; Schekman, R. Y-box protein 1 is required to sort microRNAs into exosomes in cells and in a cell-free reaction. eLife 2016, 5, e19276. [Google Scholar] [CrossRef] [PubMed]
  103. Bionaz, M.; Loor, J.J. Gene networks driving bovine milk fat synthesis during the lactation cycle. BMC Genom. 2008, 9, 366. [Google Scholar] [CrossRef] [PubMed]
  104. Yang, Z.; Cappello, T.; Wang, L. Emerging role of microRNAs in lipid metabolism. Acta Pharm. Sin. B 2015, 5, 145–150. [Google Scholar] [CrossRef] [PubMed]
  105. Goedeke, L.; Rotllan, N.; Canfrán-Duque, A.; Aranda, J.F.; Ramírez, C.M.; Araldi, E.; Lin, C.S.; Anderson, N.N.; Wagschal, A.; de Cabo, R.; et al. MicroRNA-148a regulates LDL receptor and ABCA1 expression to control circulating lipoprotein levels. Nat. Med. 2015, 21, 1280–1289. [Google Scholar] [CrossRef] [PubMed]
  106. Wagschal, A.; Najafi-Shoushtari, S.H.; Wang, L.; Goedeke, L.; Sinha, S.; deLemos, A.S.; Black, J.C.; Ramírez, C.M.; Li, Y.; Tewhey, R.; et al. Genome-wide identification of microRNAs regulating cholesterol and triglyceride homeostasis. Nat. Med. 2015, 21, 1290–1297. [Google Scholar] [CrossRef] [PubMed]
  107. Cai, X.; Liu, Q.; Zhang, X.; Ren, Y.; Lei, X.; Li, S.; Chen, Q.; Deng, K.; Wang, P.; Zhang, H.; Shi, D. Identification and analysis of the expression of microRNA from lactating and nonlactating mammary glands of the Chinese swamp buffalo. J. Dairy Sci. 2017, 100, 1971–1986. [Google Scholar] [CrossRef] [PubMed]
  108. Chen, Z.; Luo, J.; Sun, S.; Cao, D.; Shi, H.; Loor, J.J. miR-148a and miR-17-5p synergistically regulate milk TAG synthesis via PPARGC1A and PPARA in goat mammary epithelial cells. RNA Biol. 2017, 1–13. [Google Scholar] [CrossRef] [PubMed]
  109. Gigli, I.; Maizon, D.O. microRNAs and the mammary gland: A new understanding of gene expression. Genet. Mol. Biol. 2013, 36, 465–474. [Google Scholar] [CrossRef] [PubMed]
  110. Wang, D.J.; Wang, C.M.; Wang, Y.T.; Qiao, H.; Fang, L.Q.; Wang, Z.B. Lactation-related microRNA expression in microvesicles of human umbilical cord blood. Med. Sci. Monit. 2016, 22, 4542–4554. [Google Scholar] [CrossRef] [PubMed]
  111. Braud, M.; Magee, D.A.; Park, S.D.; Sonstegard, T.S.; Waters, S.M.; MacHugh, D.E.; Spillane, C. Genome-wide microRNA binding site variation between extinct wild aurochs and modern cattle identifies candidate microRNA-regulated domestication genes. Front. Genet. 2017, 8, 3. [Google Scholar] [CrossRef] [PubMed]
  112. Singh, K.; Erdman, R.A.; Swanson, K.M.; Molenaar, A.J.; Maqbool, N.J.; Wheeler, T.T.; Arias, J.A.; Quinn-Walsh, E.C.; Stelwagen, K. Epigenetic regulation of milk production in dairy cows. J. Mammary Gland Biol. Neoplasia 2010, 15, 101–112. [Google Scholar] [CrossRef] [PubMed]
  113. Singh, K.; Molenaar, A.J.; Swanson, K.M.; Gudex, B.; Arias, J.A.; Erdman, R.A.; Stelwagen, K. Epigenetics: A possible role in acute and transgenerational regulation of dairy cow milk production. Animal 2012, 6, 375–381. [Google Scholar] [CrossRef] [PubMed]
  114. Lin, X.; Luo, J.; Zhang, L.; Zhu, J. MicroRNAs synergistically regulate milk fat synthesis in mammary gland epithelial cells of dairy goats. Gene Expr. 2013, 16, 1–13. [Google Scholar] [CrossRef] [PubMed]
  115. Platenburg, G.J.; Vollebregt, E.J.; Karatzas, C.N.; Kootwijk, E.P.; De Boer, H.A.; Strijker, R. Mammary gland-specific hypomethylation of Hpa II sites flanking the bovine alpha S1-casein gene. Transgenic Res. 1996, 5, 421–431. [Google Scholar] [CrossRef] [PubMed]
  116. Wang, J.; Bian, Y.; Wang, Z.; Li, D.; Wang, C.; Li, Q.; Gao, X. MicroRNA-152 regulates DNA methyltransferase 1 and is involved in the development and lactation of mammary glands in dairy cows. PLoS ONE 2014, 9, e101358. [Google Scholar] [CrossRef] [PubMed]
  117. Muroya, S.; Hagi, T.; Kimura, A.; Aso, H.; Matsuzaki, M.; Nomura, M. Lactogenic hormones alter cellular and extracellular microRNA expression in bovine mammary epithelial cell culture. J. Anim. Sci. Biotechnol. 2016, 7, 8. [Google Scholar] [CrossRef] [PubMed]
  118. Pan, W.; Zhu, S.; Yuan, M.; Cui, H.; Wang, L.; Luo, X.; Li, J.; Zhou, H.; Tang, Y.; Shen, N. MicroRNA-21 and microRNA-148a contribute to DNA hypomethylation in Lupus CD4+ T cells by directly and indirectly targeting DNA methyltransferase 1. J. Immunol. 2010, 184, 6773–6781. [Google Scholar] [CrossRef] [PubMed]
  119. Long, X.R.; He, Y.; Huang, C.; Li, J. MicroRNA-148a is silenced by hypermethylation and interacts with DNA methyltransferase 1 in hepatocellular carcinogenesis. Int. J. Oncol. 2014, 44, 1915–1922. [Google Scholar] [CrossRef] [PubMed]
  120. Xu, Q.; Jiang, Y.; Yin, Y.; Li, Q.; He, J.; Jing, Y.; Qi, Y.T.; Xu, Q.; Li, W.; Lu, B.; et al. A regulatory circuit of miR-148a/152 and DNMT1 in modulating cell transformation and tumor angiogenesis through IGF-IR and IRS1. J. Mol. Cell Biol. 2013, 5, 3–13. [Google Scholar] [CrossRef] [PubMed]
  121. Duursma, A.M.; Kedde, M.; Schrier, M.; le Sage, C.; Agami, R. miR-148 targets human DNMT3b protein coding region. RNA 2008, 14, 872–877. [Google Scholar] [CrossRef] [PubMed]
  122. Bian, Y.; Lei, Y.; Wang, C.; Wang, J.; Wang, L.; Liu, L.; Liu, L.; Gao, X.; Li, Q. Epigenetic regulation of miR-29s affects the lactation activity of dairy cow mammary epithelial cells. J. Cell. Physiol. 2015, 230, 2152–2163. [Google Scholar] [CrossRef] [PubMed]
  123. Fabbri, M.; Garzon, R.; Cimmino, A.; Liu, Z.; Zanesi, N.; Callegari, E.; Liu, S.; Alder, H.; Costinean, S.; Fernandez-Cymering, C.; et al. MicroRNA-29 family reverts aberrant methylation in lung cancer by targeting DNA methyltransferases 3A and 3B. Proc. Natl. Acad. Sci. USA 2007, 104, 15805–15810. [Google Scholar] [CrossRef] [PubMed]
  124. Oakes, S.R.; Naylor, M.J.; Asselin-Labat, M.L.; Blazek, K.D.; Gardiner-Garden, M.; Hilton, H.N.; Kazlauskas, M.; Pritchard, M.A.; Chodosh, L.A.; Pfeffer, P.L.; et al. The Ets transcription factor Elf5 specifies mammary alveolar cell fate. Genes Dev. 2008, 22, 581–586. [Google Scholar] [CrossRef] [PubMed]
  125. Lee, H.J.; Hinshelwood, R.A.; Bouras, T.; Gallego-Ortega, D.; Valdés-Mora, F.; Blazek, K.; Visvader, J.E.; Clark, S.J.; Ormandy, C.J. Lineage specific methylation of the Elf5 promoter in mammary epithelial cells. Stem Cells 2011, 29, 1611–1619. [Google Scholar] [CrossRef] [PubMed]
  126. Wang, H.; Shi, H.; Luo, J.; Yi, Y.; Yao, D.; Zhang, X.; Ma, G.; Loor, J.J. MiR-145 regulates lipogenesis in goat mammary cells via targeting INSIG1 and epigenetic regulation of lipid-related genes. J. Cell. Physiol. 2017, 232, 1030–1040. [Google Scholar] [CrossRef] [PubMed]
  127. Yang, T.; Espenshade, P.J.; Wright, M.E.; Yabe, D.; Gong, Y.; Aebersold, R.; Goldstein, J.L.; Brown, M.S. Crucial step in cholesterol homeostasis: Sterols promote binding of SCAP to INSIG-1, a membrane protein that facilitates retention of SREBPs in ER. Cell 2002, 110, 489–500. [Google Scholar] [CrossRef]
  128. Hayashi, A.A.; Nones, K.; Roy, N.C.; McNabb, W.C.; Mackenzie, D.S.; Pacheco, D.; McCoard, S. Initiation and elongation steps of mRNA translation are involved in the increase in milk protein yield caused by growth hormone administration during lactation. J. Dairy Sci. 2009, 92, 1889–1899. [Google Scholar] [CrossRef] [PubMed]
  129. Sciascia, Q.; Pacheco, D.; McCoard, S.A. Increased milk protein synthesis in response to exogenous growth hormone is associated with changes in mechanistic (mammalian) target of rapamycin (mTOR)C1-dependent and independent cell signaling. J. Dairy Sci. 2013, 96, 2327–2338. [Google Scholar] [CrossRef] [PubMed]
  130. Kirchner, B.; Pfaffl, M.W.; Dumpler, J.; von Mutius, E.; Ege, M.J. microRNA in native and processed cow’s milk and its implication for the farm milk effect on asthma. J. Allergy Clin. Immunol. 2016, 137, 1893–1895. [Google Scholar] [CrossRef] [PubMed]
  131. Simpson, M.R.; Brede, G.; Johansen, J.; Johnsen, R.; Storrø, O.; Sætrom, P.; Øien, T. Human breast milk miRNA, maternal probiotic supplementation and atopic dermatitis in offspring. PLoS ONE 2015, 10, e0143496. [Google Scholar] [CrossRef] [PubMed]
  132. Koh, K.P.; Rao, A. DNA methylation and methylcytosine oxidation in cell fate decisions. Curr. Opin. Cell Biol. 2013, 25, 152–161. [Google Scholar] [CrossRef] [PubMed]
  133. Ko, M.; An, J.; Bandukwala, H.S.; Chavez, L.; Aijö, T.; Pastor, W.A.; Segal, M.F.; Li, H.; Koh, K.P.; Lähdesmäki, H.; et al. Modulation of TET2 expression and 5-methylcytosine oxidation by the CXXC domain protein IDAX. Nature 2013, 497, 122–126. [Google Scholar] [CrossRef] [PubMed]
  134. Dunican, D.D.; Pennings, S.; Meeha, R.R. The CXXC-TET bridge—Mind the methylation gap! Cell Res. 2013, 23, 973–974. [Google Scholar] [CrossRef] [PubMed]
  135. Melnik, B.C. Milk: An epigenetic amplifier of FTO-mediated transcription? Implications for Western diseases. J. Transl. Med. 2015, 13, 385. [Google Scholar] [CrossRef] [PubMed]
  136. Melnik, B.C. Milk—A nutrient system of mammalian evolution promoting mTORC1-dependent translation. Int. J. Mol. Sci. 2015, 16, 17048–17087. [Google Scholar] [CrossRef] [PubMed]
  137. Jia, G.; Fu, Y.; Zhao, X.; Dai, Q.; Zheng, G.; Yang, Y.; Yi, C.; Lindahl, T.; Pan, T.; Yang, Y.G.; et al. N6-methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO. Nat. Chem. Biol. 2011, 7, 885–887. [Google Scholar] [CrossRef] [PubMed]
  138. Meyer, K.D.; Jaffrey, S.R. The dynamic epitranscriptome: N6-Methyladenosine and gene expression control. Nat. Rev. Mol. Cell Biol. 2014, 15, 313–326. [Google Scholar] [CrossRef] [PubMed]
  139. Maity, A.; Das, B. N6-methyladenosine modification in mRNA: Machinery, function and implications for health and diseases. FEBS J. 2016, 283, 1607–1630. [Google Scholar] [CrossRef] [PubMed]
  140. Wu, R.; Jiang, D.; Wang, Y.; Wang, X. N(6)-methyladenosine (m(6)A) methylation in mRNA with a dynamic and reversible epigenetic modification. Mol. Biotechnol. 2016, 58, 450–459. [Google Scholar] [CrossRef] [PubMed]
  141. Adhikari, S.; Xiao, W.; Zhao, Y.L.; Yang, Y.G. m(6)A: Signaling for mRNA splicing. RNA Biol. 2016, 13, 756–759. [Google Scholar] [CrossRef] [PubMed]
  142. Chhabra, R. miRNA and methylation: A multifaceted liaison. Chembiochem 2015, 16, 195–203. [Google Scholar] [CrossRef] [PubMed]
  143. Wang, Y.; Li, Y.; Toth, J.I.; Petroski, M.D.; Zhang, Z.; Zhao, J.C. N6-methyladenosine modification destabilizes developmental regulators in embryonic stem cells. Nat. Cell Biol. 2014, 16, 191–198. [Google Scholar] [CrossRef] [PubMed]
  144. Wang, Y.; Zhao, J.C. Update: Mechanisms Underlying N6-Methyladenosine Modification of Eukaryotic mRNA. Trends Genet. 2016, 32, 763–773. [Google Scholar] [CrossRef] [PubMed]
  145. Boissel, S.; Reish, O.; Proulx, K.; Kawagoe-Takaki, H.; Sedgwick, B.; Yeo, G.S.; Meyre, D.; Golzio, C.; Molinari, F.; Kadhom, N.; et al. Loss-of-function mutation in the dioxygenase-encoding FTO gene causes severe growth retardation and multiple malformations. Am. J. Hum. Genet. 2009, 85, 106–111. [Google Scholar] [CrossRef] [PubMed]
  146. Fischer, J.; Koch, L.; Emmerling, C.; Vierkotten, J.; Peters, T.; Brüning, J.C.; Rüther, U. Inactivation of the Fto gene protects from obesity. Nature 2009, 458, 894–898. [Google Scholar] [CrossRef] [PubMed]
  147. Church, C.; Moir, L.; McMurray, F.; Girard, C.; Banks, G.T.; Teboul, L.; Wells, S.; Brüning, J.C.; Nolan, P.M.; Ashcroft, F.M.; et al. Overexpression of Fto leads to increased food intake and results in obesity. Nat. Genet. 2010, 42, 1086–1092. [Google Scholar] [CrossRef] [PubMed]
  148. Peters, T.; Ausmeier, K.; Rüther, U. Cloning of Fatso (Fto), a novel gene deleted by the Fused toes (Ft) mouse mutation. Mamm. Genome 1999, 10, 983–986. [Google Scholar] [PubMed]
  149. Gao, X.; Shin, Y.H.; Li, M.; Wang, F.; Tong, Q.; Zhang, P. The fat mass and obesity associated gene FTO functions in the brain to regulate postnatal growth in mice. PLoS ONE 2010, 5, e14005. [Google Scholar] [CrossRef] [PubMed]
  150. Speakman, J.R. The ‘Fat Mass and Obesity related’ (FTO) gene: Mechanisms of impact on obesity and energy balance. Curr. Obes. Rep. 2015, 4, 73–91. [Google Scholar] [CrossRef] [PubMed]
  151. Berulava, T.; Horsthemke, B. The obesity-associated SNPs in intron 1 of the FTO gene affect primary transcript levels. Eur. J. Hum. Genet. 2010, 18, 1054–1056. [Google Scholar] [CrossRef] [PubMed]
  152. Zhao, X.; Yang, Y.; Sun, B.F.; Shi, Y.; Yang, X.; Xiao, W.; Hao, Y.J.; Ping, X.L.; Chen, Y.S.; Wang, W.J.; et al. FTO-dependent demethylation of N6-methyladenosine regulates mRNA splicing and is required for adipogenesis. Cell Res. 2014, 24, 1403–1419. [Google Scholar] [CrossRef] [PubMed]
  153. Kim, Y.J.; Lee, H.S.; Kim, Y.K.; Park, S.; Kim, J.M.; Yun, J.H.; Yu, H.Y.; Kim, B.J. Association of metabolites with obesity and type 2 diabetes based on FTO genotype. PLoS ONE 2016, 11, e0156612. [Google Scholar] [CrossRef] [PubMed]
  154. Liu, Z.W.; Zhang, J.T.; Cai, Q.Y.; Zhang, H.X.; Wang, Y.H.; Yan, H.T.; Wu, H.M.; Yang, X.J. Birth weight is associated with placental fat mass- and obesity-associated gene expression and promoter methylation in a Chinese population. J. Matern. Fetal Neonatal Med. 2016, 29, 106–111. [Google Scholar] [CrossRef] [PubMed]
  155. Dayeh, T.; Volkov, P.; Salö, S.; Hall, E.; Nilsson, E.; Olsson, A.H.; Kirkpatrick, C.L.; Wollheim, C.B.; Eliasson, L.; Rönn, T.; et al. Genome-wide DNA methylation analysis of human pancreatic islets from type 2 diabetic and non-diabetic donors identifies candidate genes that influence insulin secretion. PLoS Genet. 2014, 10, e1004160. [Google Scholar] [CrossRef] [PubMed]
  156. Toperoff, G.; Kark, J.D.; Aran, D.; Nassar, H.; Ahmad, W.A.; Sinnreich, R.; Azaiza, D.; Glaser, B.; Hellman, A. Premature aging of leukocyte DNA methylation is associated with type 2 diabetes prevalence. Clin. Epigenet. 2015, 7, 35. [Google Scholar] [CrossRef] [PubMed]
  157. Rönn, T.; Ling, C. DNA methylation as a diagnostic and therapeutic target in the battle against type 2 diabetes. Epigenomics 2015, 7, 451–460. [Google Scholar] [CrossRef] [PubMed]
  158. Howell, J.J.; Ricoult, S.J.; Ben-Sahra, I.; Manning, B.D. A growing role for mTOR in promoting anabolic metabolism. Biochem. Soc. Trans. 2013, 41, 906–912. [Google Scholar] [CrossRef] [PubMed]
  159. Gulati, P.; Cheung, M.K.; Antrobus, R.; Church, C.D.; Harding, H.P.; Tung, Y.C.; Rimmington, D.; Ma, M.; Ron, D.; Lehner, P.J.; et al. Role for the obesity-related FTO gene in the cellular sensing of amino acids. Proc. Natl. Acad. Sci. USA 2013, 110, 2557–2562. [Google Scholar] [CrossRef] [PubMed]
  160. Gulati, P.; Yeo, G.S. The biology of FTO: From nucleic acid demethylase to amino acid sensor. Diabetologia 2013, 56, 2113–2121. [Google Scholar] [CrossRef] [PubMed]
  161. Manifava, M.; Smith, M.; Rotondo, S.; Walker, S.; Niewczas, I.; Zoncu, R.; Clark, J.; Ktistakis, N.T. Dynamics of mTORC1 activation in response to amino acids. eLife 2016, 5, e19960. [Google Scholar] [CrossRef] [PubMed]
  162. Cao, H.; Wang, L.; Chen, B.; Zheng, P.; He, Y.; Ding, Y.; Deng, Y.; Lu, X.; Guo, X.; Zhang, Y.; et al. DNA demethylation upregulated Nrf2 expression in Alzheimer’s disease cellular model. Front. Aging Neurosci. 2016, 7, 244. [Google Scholar] [CrossRef] [PubMed]
  163. Bendavit, G.; Aboulkassim, T.; Hilmi, K.; Shah, S.; Batist, G. Nrf2 transcription factor can directly regulate mTOR: Linking cytoprotective gene expression to a major metabolic regulator that generates redoox activity. J. Biol. Chem. 2016, 291, 25476–25488. [Google Scholar] [CrossRef] [PubMed]
  164. Zheng, L.; Zhang, W.; Zhou, Y.; Li, F.; Wie, H.; Peng, J. Recent advances in understanding amino acid sensing mechanisms that regulate mTORC1. Int. J. Mol. Sci. 2016, 17, E1636. [Google Scholar] [CrossRef] [PubMed]
  165. Shibata, T.; Saito, S.; Kokubu, A.; Suzuki, T.; Yamamoto, M.; Hirohashi, S. Global downstream pathway analysis reveals a dependence of oncogenic NF-E2-related factor 2 mutation on the mTOR growth signaling pathway. Cancer Res. 2010, 70, 9095–9105. [Google Scholar] [CrossRef] [PubMed]
  166. Sasaki, H.; Shitara, M.; Yokota, K.; Hikosaka, Y.; Moriyama, S.; Yano, M.; Fujii, Y. RagD gene expression and NRF2 mutations in lung squamous cell carcinomas. Oncol. Lett. 2012, 4, 1167–1170. [Google Scholar] [CrossRef] [PubMed]
  167. Kurinna, S.; Schäfer, M.; Ostano, P.; Karouzakis, E.; Chiorino, G.; Bloch, W.; Bachmann, A.; Gay, S.; Garrod, D.; Lefort, K.; et al. A novel Nrf2-miR-29-desmocollin-2 axis regulates desmosome function in keratinocytes. Nat. Commun. 2014, 5, 5099. [Google Scholar] [CrossRef] [PubMed]
  168. Kurinna, S.; Werner, S. NRF2 and microRNAs: New but awaited relations. Biochem. Soc. Trans. 2015, 43, 595–601. [Google Scholar] [CrossRef] [PubMed]
  169. Dibble, C.C.; Cantley, L.C. Regulation of mTORC1 by PI3K signaling. Trends Cell Biol. 2015, 25, 545–555. [Google Scholar] [CrossRef] [PubMed]
  170. Kuroda, A.; Rauch, T.A.; Todorov, I.; Ku, H.T.; Al-Abdullah, I.H.; Kandeel, F.; Mullen, Y.; Pfeifer, G.P.; Ferreri, K. Insulin gene expression is regulated by DNA methylation. PLoS ONE 2009, 4, e6953. [Google Scholar] [CrossRef]
  171. Dooley, J.; Garcia-Perez, J.E.; Sreenivasan, J.; Schlenner, S.M.; Vangoitsenhoven, R.; Papadopoulou, A.S.; Tian, L.; Schonefeldt, S.; Serneels, L.; Deroose, C.; et al. The microRNA-29 family dictates the balance between homeostatic and pathological glucose handling in diabetes and obesity. Diabetes 2016, 65, 53–61. [Google Scholar] [CrossRef] [PubMed]
  172. Qin, L.Q.; He, K.; Xu, J.Y. Milk consumption and circulating insulin-like growth factor-I level: A systematic literature review. Int. J. Food Sci. Nutr. 2009, 60 (Suppl. 7), 330–340. [Google Scholar] [CrossRef] [PubMed]
  173. Hoppe, C.; Mølgaard, C.; Michaelsen, K.F. Cow’s milk and linear growth in industrialized and developing countries. Annu. Rev. Nutr. 2006, 26, 131–173. [Google Scholar] [CrossRef] [PubMed]
  174. Ouni, M.; Gunes, Y.; Belot, M.P.; Castell, A.L.; Fradin, D.; Bougnères, P. The IGF1 P2 promoter is an epigenetic QTL for circulating IGF1 and human growth. Clin. Epigenet. 2015, 7, 22. [Google Scholar] [CrossRef] [PubMed]
  175. Ouni, M.; Belot, M.P.; Castell, A.L.; Fradin, D.; Bougnères, P. The P2 promoter of the IGF1 gene is a major epigenetic locus for GH responsiveness. Pharmacogen. J. 2016, 16, 102–106. [Google Scholar] [CrossRef] [PubMed]
  176. Tahir, S.A.; Yang, G.; Goltsov, A.; Song, K.D.; Ren, C.; Wang, J.; Chang, W.; Thompson, T.C. Caveolin-1-LRP6 signaling module stimulates aerobic glycolysis in prostate cancer. Cancer Res. 2013, 73, 1900–1911. [Google Scholar] [CrossRef] [PubMed]
  177. Tang, W.; Feng, X.; Zhang, S.; Ren, Z.; Liu, Y.; Yang, B.; lv, B.; Cai, Y.; Xia, J.; Ge, N. Caveolin-1 confers resistance of hepatoma cells to anoikis by activating IGF-1 pathway. Cell. Physiol. Biochem. 2015, 36, 1223–1236. [Google Scholar] [CrossRef] [PubMed]
  178. Palacios-Ortega, S.; Varela-Guruceaga, M.; Martínez, J.A.; de Miguel, C.; Milagro, F.I. Effects of high glucose on caveolin-1 and insulin signaling in 3T3-L1 adipocytes. Adipocyte 2015, 5, 65–80. [Google Scholar] [CrossRef] [PubMed]
  179. Palacios-Ortega, S.; Varela-Guruceaga, M.; Milagro, F.I.; Martínez, J.A.; de Miguel, C. Expression of caveolin 1 is enhanced by DNA demethylation during adipocyte differentiation. Status of insulin signaling. PLoS ONE 2014, 9, e95100. [Google Scholar] [CrossRef] [PubMed]
  180. Palomares, O.; Yaman, G.; Azkur, A.K.; Akkoc, T.; Akdis, M.; Akdis, C.A. Role of Treg in immune regulation of allergic diseases. Eur. J. Immunol. 2010, 40, 1232–1240. [Google Scholar] [CrossRef] [PubMed]
  181. Pellerin, L.; Jenks, J.A.; Bégin, P.; Bacchetta, R.; Nadeau, K.C. Regulatory T cells and their roles in immune dysregulation and allergy. Immunol. Res. 2014, 58, 358–368. [Google Scholar] [CrossRef] [PubMed]
  182. Alroqi, F.J.; Chatila, T.A. T regulatory cell biology in health and disease. Curr. Allergy Asthma Rep. 2016, 16, 27. [Google Scholar] [CrossRef] [PubMed]
  183. Huehn, J.; Beyer, M. Epigenetic and transcriptional control of Foxp3+ regulatory T cells. Semin. Immunol. 2015, 27, 10–18. [Google Scholar] [CrossRef] [PubMed]
  184. Polansky, J.K.; Kretschmer, K.; Freyer, J.; Floess, S.; Garbe, A.; Baron, U.; Olek, S.; Hamann, A.; von Boehmer, H.; Huehn, J. DNA methylation controls Foxp3 gene expression. Eur. J. Immunol. 2008, 38, 1654–1663. [Google Scholar] [CrossRef] [PubMed]
  185. Polansky, J.K.; Schreiber, L.; Thelemann, C.; Ludwig, L.; Krüger, M.; Baumgrass, R.; Cording, S.; Floess, S.; Hamann, A.; Huehn, J. Methylation matters: Binding of Ets-1 to the demethylated Foxp3 gene contributes to the stabilization of Foxp3 expression in regulatory T cells. J. Mol. Med. 2010, 88, 1029–1040. [Google Scholar] [CrossRef] [PubMed]
  186. Paparo, L.; Nocerino, R.; Cosenza, L.; Aitoro, R.; D’Argenio, V.; Del Monaco, V.; Di Scala, C.; Amoroso, A.; Di Costanzo, M.; Salvatore, F.; et al. Epigenetic features of FoxP3 in children with cow’s milk allergy. Clin. Epigenet. 2016, 8, 86. [Google Scholar] [CrossRef] [PubMed]
  187. Janson, P.C.; Winerdal, M.E.; Marits, P.; Thörn, M.; Ohlsson, R.; Winqvist, O. FOXP3 promoter demethylation reveals the committed Treg population in humans. PLoS ONE 2008, 3, e1612. [Google Scholar] [CrossRef] [PubMed]
  188. Bacchetta, R.; Gambineri, E.; Roncarolo, M.G. Role of regulatory T cells and FOXP3 in human diseases. J. Allergy Clin. Immunol. 2007, 120, 227–235. [Google Scholar] [CrossRef] [PubMed]
  189. Nadeau, K.; McDonald-Hyman, C.; Noth, E.M.; Pratt, B.; Hammond, S.K.; Balmes, J.; Tager, I. Ambient air pollution impairs regulatory T-cell function in asthma. J. Allergy Clin. Immunol. 2010, 126, 845–852. [Google Scholar] [CrossRef] [PubMed]
  190. Hinz, D.; Bauer, M.; Röder, S.; Olek, S.; Huehn, J.; Sack, U.; Borte, M.; Simon, J.C.; Lehmann, I.; Herberth, G.; LINA study group. Cord blood Tregs with stable FOXP3 expression are influenced by prenatal environment and associated with atopic dermatitis at the age of one year. Allergy 2012, 67, 380–389. [Google Scholar] [CrossRef] [PubMed]
  191. Lal, G.; Bromberg, J.S. Epigenetic mechanisms of regulation of Foxp3 expression. Blood 2009, 114, 3727–3735. [Google Scholar] [CrossRef] [PubMed]
  192. Lal, G.; Zhang, N.; van der Touw, W.; Ding, Y.; Ju, W.; Bottinger, E.P.; Reid, S.P.; Levy, D.E.; Bromberg, J.S. Epigenetic regulation of Foxp3 expression in regulatory T cells by DNA methylation. J. Immunol. 2009, 182, 259–273. [Google Scholar] [CrossRef] [PubMed]
  193. Melnik, B.C.; John, S.M.; Schmitz, G. Milk: An exosomal microRNA transmitter promoting thymic regulatory T cell maturation preventing the development of atopy? J. Transl. Med. 2014, 12, 43. [Google Scholar] [CrossRef] [PubMed]
  194. Melnik, B.C.; John, S.M.; Schmitz, G. Milk: An epigenetic inducer of FoxP3 expression. J. Allergy Clin. Immunol. 2016, 138, 937–938. [Google Scholar] [CrossRef] [PubMed]
  195. Parigi, S.M.; Eldh, M.; Larssen, P.; Gabrielsson, S.; Villablanca, E.J. Breast milk and solid food shaping intestinal immunity. Front. Immunol. 2015, 6, 415. [Google Scholar] [CrossRef] [PubMed]
  196. Petrus, N.C.; Henneman, P.; Venema, A.; Mul, A.; van Sinderen, F.; Haagmans, M.; Mook, O.; Hennekam, R.C.; Sprikkelman, A.B.; Mannens, M. Cow’s milk allergy in Dutch children: An epigenetic pilot survey. Clin. Transl. Allergy 2016, 6, 16. [Google Scholar] [CrossRef] [PubMed]
  197. Tooley, K.L.; El-Merhibi, A.; Cummins, A.G.; Grose, R.H.; Lymn, K.A.; DeNichilo, M.; Penttila, I.A. Maternal milk, but not formula, regulates the immune response to beta-lactoglobulin in allergy-prone rat pups. J. Nutr. 2009, 139, 2145–2151. [Google Scholar] [CrossRef] [PubMed]
  198. Lopez-Pastrana, J.; Shao, Y.; Chernaya, V.; Wang, H.; Yang, X.F. Epigenetic enzymes are the therapeutic targets for CD4(+)CD25(+/high)Foxp3(+) regulatory T cells. Transl. Res. 2015, 165, 221–240. [Google Scholar] [CrossRef] [PubMed]
  199. Bluestone, J.A. FOXP3, the transcription factor at the heart of the rebirth of immune tolerance. J. Immunol. 2017, 198, 979–980. [Google Scholar] [CrossRef] [PubMed]
  200. Ranhotra, H.S. The NR4A orphan nuclear receptors: Mediators in metabolism and diseases. J. Recept. Signal Transduct. Res. 2015, 35, 184–188. [Google Scholar] [CrossRef] [PubMed]
  201. Sekiya, T.; Kashiwagi, I.; Yoshida, R.; Fukaya, T.; Morita, R.; Kimura, A.; Ichinose, H.; Metzger, D.; Chambon, P.; Yoshimura, A. Nr4a receptors are essential for thymic regulatory T cell development and immune homeostasis. Nat. Immunol. 2013, 14, 230–237. [Google Scholar] [CrossRef] [PubMed]
  202. Won, H.Y.; Hwang, E.S. Transcriptional modulation of regulatory T cell development by novel regulators NR4As. Arch. Pharm. Res. 2016, 39, 1530–1536. [Google Scholar] [CrossRef] [PubMed]
  203. Sekiya, T.; Kondo, T.; Shichita, T.; Morita, R.; Ichinose, H.; Yoshimura, A. Suppression of Th2 and Tfh immune reactions by Nr4a receptors in mature T reg cells. J. Exp. Med. 2015, 212, 1623–1640. [Google Scholar] [CrossRef] [PubMed]
  204. Sekiya, T.; Nakatsukasa, H.; Lu, Q.; Yoshimura, A. Roles of transcription factors and epigenetic modifications in differentiation and maintenance of regulatory T cells. Microbes Infect. 2016, 18, 378–386. [Google Scholar] [CrossRef] [PubMed]
  205. Bandukwala, H.S.; Rao, A. ‘Nurr’ishing Treg cells: Nr4a transcription factors control Foxp3 expression. Nat. Immunol. 2013, 14, 201–203. [Google Scholar] [CrossRef] [PubMed]
  206. Zhang, Y.; Fatima, N.; Dufau, M.L. Coordinated changes in DNA methylation and histone modifications regulate silencing/derepression of luteinizing hormone receptor gene transcription. Mol. Cell. Biol. 2005, 25, 7929–7939. [Google Scholar] [CrossRef] [PubMed]
  207. Yeh, C.M.; Chang, L.Y.; Lin, S.H.; Chou, J.L.; Hsieh, H.Y.; Zeng, L.H.; Chuang, S.Y.; Wang, H.W.; Dittner, C.; Lin, C.Y.; et al. Epigenetic silencing of the NR4A3 tumor suppressor, by aberrant JAK/STAT signaling, predicts prognosis in gastric cancer. Sci. Rep. 2016, 6, 31690. [Google Scholar] [CrossRef] [PubMed]
  208. Zhao, Y.; Nomiyama, T.; Findeisen, H.M.; Qing, H.; Aono, J.; Jones, K.L.; Heywood, E.B.; Bruemmer, D. Epigenetic regulation of the NR4A orphan nuclear receptor NOR1 by histone acetylation. FEBS Lett. 2014, 588, 4825–4830. [Google Scholar] [CrossRef] [PubMed]
  209. El-Osta, A.; Wolffe, A.P. DNA methylation and histone deacetylation in the control of gene expression: Basic biochemistry to human development and disease. Gene Expr. 2000, 9, 63–75. [Google Scholar] [CrossRef] [PubMed]
  210. Dobosy, J.R.; Selker, E.U. Emerging connections between DNA methylation and histone acetylation. Cell. Mol. Life Sci. 2001, 58, 721–727. [Google Scholar] [CrossRef] [PubMed]
  211. Fuks, F.; Hurd, P.J.; Wolf, D.; Nan, X.; Bird, A.P.; Kouzarides, T. The methyl-CpG-binding protein MeCP2 links DNA methylation to histone methylation. J. Biol. Chem. 2003, 278, 4035–4040. [Google Scholar] [CrossRef] [PubMed]
  212. Drewell, R.A.; Goddard, C.J.; Thomas, J.O.; Surani, M.A. Methylation-dependent silencing at the H19 imprinting control region by MeCP2. Nucleic Acids Res. 2002, 30, 1139–1144. [Google Scholar] [CrossRef] [PubMed]
  213. Sisk, P.M.; Lovelady, C.A.; Dillard, R.G.; Gruber, K.J.; O’Shea, T.M. Early human milk feeding is associated with a lower risk of necrotizing enterocolitis in very low birth weight infants. J. Perinatol. 2007, 27, 428–433. [Google Scholar] [CrossRef] [PubMed]
  214. Wang, W.; Xue, L.; Ma, T.; Li, Y.; Li, Z. Non-intervention observation: Dynamic evolution laws of inflammatory response in necrotizing enterocolitis. Exp. Ther. Med. 2016, 12, 1770–1774. [Google Scholar] [CrossRef] [PubMed]
  215. Ruan, W.Y.; Bi, M.Y.; Feng, W.W.; Wang, Y.J.; Bu, W.Q.; Lu, L. Effect of human breast milk on the expression of proinflammatory cytokines in Caco-2 cells after hypoxia/re-oxygenation. Rev. Investig. Clin. 2016, 68, 105–111. [Google Scholar]
  216. Ferreiro, D.U.; Komives, E.A. Molecular mechanisms of system control of NF-kappaB signaling by IkappaBalpha. Biochemistry 2010, 49, 1560–1567. [Google Scholar] [CrossRef] [PubMed]
  217. Verma, I.M.; Stevenson, J.K.; Schwarz, E.M.; Van Antwerp, D.; Miyamoto, S. Rel/NF-kappa B/I kappa B family: Intimate tales of association and dissociation. Genes Dev. 1995, 9, 2723–2735. [Google Scholar] [CrossRef] [PubMed]
  218. O’Gorman, A.; Colleran, A.; Ryan, A.; Mann, J.; Egan, L.J. Regulation of NF-kappaB responses by epigenetic suppression of IkappaBalpha expression in HCT116 intestinal epithelial cells. Am. J. Physiol. Gastrointest. Liver Physiol. 2010, 299, G96–G105. [Google Scholar] [CrossRef] [PubMed]
  219. Scheinman, R.I.; Cogswell, P.C.; Lofquist, A.K.; Baldwin, A.S., Jr. Role of transcriptional activation of I kappa B alpha in mediation of immunosuppression by glucocorticoids. Science 1995, 270, 283–286. [Google Scholar] [CrossRef] [PubMed]
  220. Auphan, N.; DiDonato, J.A.; Rosette, C.; Helmberg, A.; Karin, M. Immunosuppression by glucocorticoids: Inhibition of NF-kappa B activity through induction of I kappa B synthesis. Science 1995, 270, 286–290. [Google Scholar] [CrossRef] [PubMed]
  221. Labrie, V.; Buske, O.J.; Oh, E.; Jeremian, R.; Ptak, C.; Gasiūnas, G.; Maleckas, A.; Petereit, R.; Žvirbliene, A.; Adamonis, K.; et al. Lactase nonpersistence is directed by DNA-variation-dependent epigenetic aging. Nat. Struct. Mol. Biol. 2016, 23, 566–573. [Google Scholar] [CrossRef] [PubMed]
  222. Swallow, D.M.; Troelsen, J.T. Escape from epigenetic silencing of lactase expression is triggered by a single-nucleotide change. Nat. Struct. Mol. Biol. 2016, 23, 505–507. [Google Scholar] [CrossRef] [PubMed]
  223. Olds, L.C.; Sibley, E. Lactase persistence DNA variant enhances lactase promoter activity in vitro: Functional role as a cis regulatory element. Hum. Mol. Genet. 2003, 12, 2333–2340. [Google Scholar] [CrossRef] [PubMed]
  224. Troelsen, J.T.; Olsen, J.; Møller, J.; Sjöström, H. An upstream polymorphism associated with lactase persistence has increased enhancer activity. Gastroenterology 2003, 125, 1686–1694. [Google Scholar] [CrossRef] [PubMed]
  225. Lewinsky, R.H.; Jensen, T.G.; Møller, J.; Stensballe, A.; Olsen, J.; Troelsen, J.T. T-13910 DNA variant associated with lactase persistence interacts with Oct-1 and stimulates lactase promoter activity in vitro. Hum. Mol. Genet. 2005, 14, 3945–3953. [Google Scholar] [CrossRef] [PubMed]
  226. Wang, Z.; Maravelias, C.; Sibley, E. Lactase gene promoter fragments mediate differential spatial and temporal expression patterns in transgenic mice. DNA Cell Biol. 2006, 25, 215–222. [Google Scholar] [CrossRef] [PubMed]
  227. Merkestein, M.; McTaggart, J.S.; Lee, S.; Kramer, H.B.; McMurray, F.; Lafond, M.; Boutens, L.; Cox, R.; Ashcroft, F.M. Changes in gene expression associated with FTO overexpression in mice. PLoS ONE 2014, 9, e97162. [Google Scholar]
  228. Karra, E.; O’Daly, O.G.; Choudhury, A.I.; Yousseif, A.; Millership, S.; Neary, M.T.; Scott, W.R.; Chandarana, K.; Manning, S.; Hess, M.E.; et al. A link between FTO, ghrelin, and impaired brain food-cue responsivity. J. Clin. Investig. 2013, 123, 3539–3551. [Google Scholar] [CrossRef] [PubMed]
  229. Burger, K.S.; Berner, L.A. A functional neuroimaging review of obesity, appetitive hormones and ingestive behavior. Physiol. Behav. 2014, 136, 121–127. [Google Scholar] [CrossRef] [PubMed]
  230. Hewson, A.K.; Dickson, S.L. Systemic administration of ghrelin induces Fos and Egr-1 proteins in the hypothalamic arcuate nucleus of fasted and fed rats. J. Neuroendocrinol. 2000, 12, 1047–1049. [Google Scholar] [CrossRef] [PubMed]
  231. Perello, M.; Dickson, S.L. Ghrelin signalling on food reward: A salient link between the gut and the mesolimbic system. J. Neuroendocrinol. 2015, 27, 424–434. [Google Scholar] [CrossRef] [PubMed]
  232. Skibicka, K.P.; Shirazi, R.H.; Hansson, C.; Dickson, S.L. Ghrelin interacts with neuropeptide Y Y1 and opioid receptors to increase food reward. Endocrinology 2012, 153, 1194–1205. [Google Scholar] [CrossRef] [PubMed]
  233. Caruso, V.; Chen, H.; Morris, M.J. Early hypothalamic FTO overexpression in response to maternal obesity—Potential contribution to postweaning hyperphagia. PLoS ONE 2011, 6, e25261. [Google Scholar] [CrossRef] [PubMed]
  234. Wiley, A.S. Dairy and milk consumption and child growth: Is BMI involved? An analysis of NHANES 1999–2004. Am. J. Hum. Biol. 2010, 22, 517–525. [Google Scholar] [CrossRef] [PubMed]
  235. Parmar, M.S.; Jaumotte, J.D.; Zigmond, M.J.; Cavanaugh, J.E. ERK1, 2, and 5 expression and activation in dopaminergic brain regions during postnatal development. Int. J. Dev. Neurosci. 2015, 46, 44–50. [Google Scholar] [CrossRef] [PubMed]
  236. Ye, Y.; Mastwal, S.; Cao, V.Y.; Ren, M.; Liu, Q.; Zhang, W.; Elkahloun, A.G.; Wang, K.H. Dopamine is required for activity-dependent amplification of Arc mRNA in developing postnatal frontal cortex. Cereb. Cortex 2016. [Google Scholar] [CrossRef] [PubMed]
  237. Luo, S.X.; Huang, E.J. Dopaminergic neurons and brain reward pathways: From neurogenesis to circuit assembly. Am. J. Pathol. 2016, 186, 478–488. [Google Scholar] [CrossRef] [PubMed]
  238. Heni, M.; Kullmann, S.; Ahlqvist, E.; Wagner, R.; Machicao, F.; Staiger, H.; Häring, H.U.; Almgren, P.; Groop, L.C.; Small, D.M.; et al. Interaction between the obesity-risk gene FTO and the dopamine D2 receptor gene ANKK1/TaqIA on insulin sensitivity. Diabetologia 2016, 59, 2622–2631. [Google Scholar] [CrossRef] [PubMed]
  239. Hess, M.E.; Hess, S.; Meyer, K.D.; Verhagen, L.A.; Koch, L.; Brönneke, H.S.; Dietrich, M.O.; Jordan, S.D.; Saletore, Y.; Elemento, O.; et al. The fat mass and obesity associated gene (Fto) regulates activity of the dopaminergic midbrain circuitry. Nat. Neurosci. 2013, 16, 1042–1048. [Google Scholar] [CrossRef] [PubMed]
  240. Kodama, N.; Iwao, T.; Kabeya, T.; Horikawa, T.; Niwa, T.; Kondo, Y.; Nakamura, K.; Matsunaga, T. Inhibition of mitogen-activated protein kinase kinase, DNA methyltransferase, and transforming growth factor-β promotes differentiation of human induced pluripotent stem cells into enterocytes. Drug Metab. Pharmacokinet. 2016, 31, 193–200. [Google Scholar] [CrossRef] [PubMed]
  241. Spalding, K.L.; Arner, E.; Westermark, P.O.; Bernard, S.; Buchholz, B.A.; Bergmann, O.; Blomqvist, L.; Hoffstedt, J.; Näslund, E.; Britton, T.; et al. Dynamics of fat cell turnover in humans. Nature 2008, 453, 783–787. [Google Scholar] [CrossRef] [PubMed]
  242. Taylor, S.M.; Jones, P.A. Multiple new phenotypes induced in 10T1/2 and 3T3 cells treated with 5-azacytidine. Cell 1979, 17, 771–779. [Google Scholar] [CrossRef]
  243. Noer, A.; Sørensen, A.L.; Boquest, A.C.; Collas, P. Stable CpG hypomethylation of adipogenic promoters in freshly isolated, cultured, and differentiated mesenchymal stem cells from adipose tissue. Mol. Biol. Cell 2006, 17, 3543–3556. [Google Scholar] [CrossRef] [PubMed]
  244. Londoño Gentile, T.; Lu, C.; Lodato, P.M.; Tse, S.; Olejniczak, S.H.; Witze, E.S.; Thompson, C.B.; Wellen, K.E. DNMT1 is regulated by ATP-citrate lyase and maintains methylation patterns during adipocyte differentiation. Mol. Cell. Biol. 2013, 33, 3864–3878. [Google Scholar]
  245. An, X.; Ma, K.; Zhang, Z.; Zhao, T.; Zhang, X.; Tang, B.; Li, Z. miR-17, miR-21, and miR-143 enhance adipogenic differentiation from porcine bone marrow-derived mesenchymal stem cells. DNA Cell Biol. 2016, 35, 410–416. [Google Scholar] [CrossRef] [PubMed]
  246. Lim, Y.C.; Chia, S.Y.; Jin, S.; Han, W.; Ding, C.; Sun, L. Dynamic DNA methylation landscape defines brown and white cell specificity during adipogenesis. Mol. Metab. 2016, 5, 1033–1041. [Google Scholar] [CrossRef] [PubMed]
  247. Merkestein, M.; Laber, S.; McMurray, F.; Andrew, D.; Sachse, G.; Sanderson, J.; Li, M.; Usher, S.; Sellayah, D.; Ashcroft, F.M.; et al. FTO influences adipogenesis by regulating mitotic clonal expansion. Nat. Commun. 2015, 6, 6792. [Google Scholar] [CrossRef] [PubMed]
  248. Chen, X.; Zhou, B.; Luo, Y.; Huang, Z.; Jia, G.; Liu, G.; Zhao, H. Tissue distribution of porcine FTO and its effect on porcine intramuscular preadipocytes proliferation and differentiation. PLoS ONE 2016, 11, e0151056. [Google Scholar] [CrossRef] [PubMed]
  249. Grunnet, L.G.; Nilsson, E.; Ling, C.; Hansen, T.; Pedersen, O.; Groop, L.; Vaag, A.; Poulsen, P. Regulation and function of FTO mRNA expression in human skeletal muscle and subcutaneous adipose tissue. Diabetes 2009, 58, 2402–2408. [Google Scholar] [CrossRef] [PubMed]
  250. Chen, J.; Zhou, X.; Wu, W.; Wang, X.; Wang, Y. FTO-dependent function of N6-methyladenosine is involved in the hepatoprotective effects of betaine on adolescent mice. J. Physiol. Biochem. 2015, 71, 405–413. [Google Scholar] [CrossRef] [PubMed]
  251. Goodman, C.A. The role of mTORC1 in regulating protein synthesis and skeletal muscle mass in response to various mechanical stimuli. Rev. Physiol. Biochem. Pharmacol. 2014, 166, 43–95. [Google Scholar] [PubMed]
  252. Bond, P. Regulation of mTORC1 by growth factors, energy status, amino acids and mechanical stimuli at a glance. J. Int. Soc. Sports Nutr. 2016, 13, 8. [Google Scholar] [CrossRef] [PubMed]
  253. Petrie, M.A.; Kimball, A.L.; McHenry, C.L.; Suneja, M.; Yen, C.L.; Sharma, A.; Shields, R.K. Distinct skeletal muscle gene regulation from active contraction, passive vibration, and whole body heat stress in humans. PLoS ONE 2016, 11, e0160594. [Google Scholar] [CrossRef] [PubMed]
  254. Pérez-Sieira, S.; López, M.; Nogueiras, R.; Tovar, S. Regulation of NR4A by nutritional status, gender, postnatal development and hormonal deficiency. Sci. Rep. 2014, 4, 4264. [Google Scholar] [CrossRef] [PubMed]
  255. Szyf, M.; Rouleau, J.; Theberge, J.; Bozovic, V. Induction of myogenic differentiation by an expression vector encoding the DNA methyltransferase cDNA sequence in the antisense orientation. J. Biol. Chem. 1992, 267, 12831–12836. [Google Scholar] [PubMed]
  256. Lucarelli, M.; Fuso, A.; Strom, R.; Scarpa, S. The dynamics of myogenin site-specific demethylation is strongly correlated with its expression and with muscle differentiation. J. Biol. Chem. 2001, 276, 7500–7506. [Google Scholar] [CrossRef] [PubMed]
  257. Palacios, D.; Puri, P.L. The epigenetic network regulating muscle development and regeneration. J. Cell. Physiol. 2006, 207, 1–11. [Google Scholar] [CrossRef] [PubMed]
  258. Park, I.H.; Chen, J. Mammalian target of rapamycin (mTOR) signaling is required for a late-stage fusion process during skeletal myotube maturation. J. Biol. Chem. 2005, 280, 32009–32017. [Google Scholar] [CrossRef] [PubMed]
  259. Hatfield, I.; Harvey, I.; Yates, E.R.; Redd, J.R.; Reiter, L.T.; Bridges, D. The role of TORC1 in muscle development in Drosophila. Sci. Rep. 2015, 5, 9676. [Google Scholar] [CrossRef] [PubMed]
  260. Zhang, J.; Ying, Z.Z.; Tang, Z.L.; Long, L.Q.; Li, K. MicroRNA-148a promotes myogenic differentiation by targeting the ROCK1 gene. J. Biol. Chem. 2012, 287, 21093–21101. [Google Scholar] [CrossRef] [PubMed]
  261. Wang, H.; Sun, H.; Guttridge, D.C. microRNAs: Novel components in a muscle gene regulatory network. Cell Cycle 2009, 8, 1833–1837. [Google Scholar] [CrossRef] [PubMed]
  262. Zhou, L.; Wang, L.; Lu, L.; Jiang, P.; Sun, H.; Wang, H. A novel target of microRNA-29, Ring1 and YY1-binding protein (Rybp), negatively regulates skeletal myogenesis. J. Biol. Chem. 2012, 287, 25255–25265. [Google Scholar] [CrossRef] [PubMed]
  263. Kim, J.H.; Singhal, V.; Biswal, S.; Thimmulappa, R.K.; DiGirolamo, D.J. Nrf2 is required for normal postnatal bone acquisition in mice. Bone Res. 2014, 2, 14033. [Google Scholar] [CrossRef] [PubMed]
  264. Li, Z.; Hassan, M.Q.; Jafferji, M.; Aqeilan, R.I.; Garzon, R.; Croce, C.M.; van Wijnen, A.J.; Stein, J.L.; Stein, G.S.; Lian, J.B. Biological functions of miR-29b contribute to positive regulation of osteoblast differentiation. J. Biol. Chem. 2009, 284, 15676–15684. [Google Scholar] [CrossRef] [PubMed]
  265. Jeon, E.J.; Lee, K.Y.; Choi, N.S.; Lee, M.H.; Kim, H.N.; Jin, Y.H.; Ryoo, H.M.; Choi, J.Y.; Yoshida, M.; Nishino, N.; et al. Bone morphogenetic protein-2 stimulates Runx2 acetylation. J. Biol. Chem. 2006, 281, 16502–16511. [Google Scholar] [CrossRef] [PubMed]
  266. Kang, J.S.; Alliston, T.; Delston, R.; Derynck, R. Repression of Runx2 function by TGF-beta through recruitment of class II histone deacetylases by Smad3. EMBO J. 2005, 24, 2543–2555. [Google Scholar] [CrossRef] [PubMed]
  267. Chen, D.; Wang, Z. Adrenaline inhibits osteogenesis via repressing miR-21 expression. Cell Biol. Int. 2017, 41, 8–15. [Google Scholar] [CrossRef] [PubMed]
  268. Mei, Y.; Bian, C.; Li, J.; Du, Z.; Zhou, H.; Yang, Z.; Zhao, R.C. miR-21 modulates the ERK-MAPK signaling pathway by regulating SPRY2 expression during human mesenchymal stem cell differentiation. J. Cell. Biochem. 2013, 114, 1374–1384. [Google Scholar] [CrossRef] [PubMed]
  269. Trohatou, O.; Zagoura, D.; Bitsika, V.; Pappa, K.I.; Antsaklis, A.; Anagnou, N.P.; Roubelakis, M.G. Sox2 suppression by miR-21 governs human mesenchymal stem cell properties. Stem Cells Transl. Med. 2014, 3, 54–68. [Google Scholar] [CrossRef] [PubMed]
  270. Xu, J.F.; Yang, G.H.; Pan, X.H.; Zhang, S.J.; Zhao, C.; Qiu, B.S.; Gu, H.F.; Hong, J.F.; Cao, L.; Chen, Y.; et al. Altered microRNA expression profile in exosomes during osteogenic differentiation of human bone marrow-derived mesenchymal stem cells. PLoS ONE 2014, 9, e114627. [Google Scholar] [CrossRef] [PubMed]
  271. Ishitsuka, Y.; Huebner, A.J.; Rice, R.H.; Koch, P.J.; Speransky, V.V.; Steven, A.C.; Roop, D.R. Lce1 family members are Nrf2-target genes that are induced to compensate for the loss of loricrin. J. Investig. Dermatol. 2016, 136, 1656–1663. [Google Scholar] [CrossRef] [PubMed]
  272. Huebner, A.J.; Dai, D.; Morasso, M.; Schmidt, E.E.; Schäfer, M.; Werner, S.; Roop, D.R. Amniotic fluid activates the nrf2/keap1 pathway to repair an epidermal barrier defect in utero. Dev. Cell 2012, 23, 1238–1246. [Google Scholar] [CrossRef] [PubMed]
  273. Pastore, S.; Mascia, F.; Mariani, V.; Girolomoni, G. The epidermal growth factor receptor system in skin repair and inflammation. J. Investig. Dermatol. 2008, 128, 1365–1374. [Google Scholar] [CrossRef] [PubMed]
  274. Zhang, X.; Pickin, K.A.; Bose, R.; Jura, N.; Cole, P.A.; Kuriyan, J. Inhibition of the EGF receptor by binding of MIG6 to an activating kinase domain interface. Nature 2007, 450, 741–744. [Google Scholar] [CrossRef] [PubMed]
  275. Ying, H.; Zheng, H.; Scott, K.; Wiedemeyer, R.; Yan, H.; Lim, C.; Huang, J.; Dhakal, S.; Ivanova, E.; Xiao, Y.; et al. Mig-6 controls EGFR trafficking and suppresses gliomagenesis. Proc. Natl. Acad. Sci. USA 2010, 107, 6912–6917. [Google Scholar] [CrossRef] [PubMed]
  276. Fiorentino, L.; Pertica, C.; Fiorini, M.; Talora, C.; Crescenzi, M.; Castellani, L.; Alemà, S.; Benedetti, P.; Segatto, O. Inhibition of ErbB-2 mitogenic and transforming activity by RALT, a mitogen-induced signal transducer which binds to the ErbB-2 kinase domain. Mol. Cell. Biol. 2000, 20, 7735–7750. [Google Scholar] [CrossRef] [PubMed]
  277. Ferby, I.; Reschke, M.; Kudlacek, O.; Knyazev, P.; Pantè, G.; Amann, K.; Sommergruber, W.; Kraut, N.; Ullrich, A.; Fässler, R.; et al. Mig6 is a negative regulator of EGF receptor-mediated skin morphogenesis and tumor formation. Nat. Med. 2006, 12, 568–573. [Google Scholar] [CrossRef] [PubMed]
  278. Kim, J.; Zhang, Y.; Skalski, M.; Hayes, J.; Kefas, B.; Schiff, D.; Purow, B.; Parsons, S.; Lawler, S.; Abounader, R. microRNA-148a is a prognostic oncomiR that targets MIG6 and BIM to regulate EGFR and apoptosis in glioblastoma. Cancer Res. 2014, 74, 1541–1553. [Google Scholar] [CrossRef] [PubMed]
  279. Vu, H.L.; Rosenbaum, S.; Capparelli, C.; Purwin, T.J.; Davies, M.A.; Berger, A.C.; Aplin, A.E. MIG6 is MEK regulated and affects EGF-induced migration in mutant NRAS melanoma. J. Investig. Dermatol. 2016, 136, 453–463. [Google Scholar] [CrossRef] [PubMed]
  280. Melnik, B.C.; John, S.M.; Schmitz, G. Milk consumption during pregnancy increases birth weight, a risk factor for the development of diseases of civilization. J. Transl. Med. 2015, 13, 13. [Google Scholar] [CrossRef] [PubMed]
  281. Van Deutekom, A.W.; Chinapaw, M.J.; Vrijkotte, T.G.; Gemke, R.J. The association of birth weight and postnatal growth with energy intake and eating behavior at 5 years of age—A birth cohort study. Int. J. Behav. Nutr. Phys. Act. 2016, 13, 15. [Google Scholar] [CrossRef] [PubMed]
  282. Frayling, T.M. Genome-wide association studies provide new insights into type 2 diabetes aetiology. Nat. Rev. Genet. 2007, 8, 657–662. [Google Scholar] [CrossRef]
  283. Lindgren, C.M.; McCarthy, M.I. Mechanisms of disease: Genetic insights into the etiology of type 2 diabetes and obesity. Nat. Clin. Pract. Endocrinol. Metab. 2008, 4, 156–163. [Google Scholar] [CrossRef] [PubMed]
  284. Basile, K.J.; Johnson, M.E.; Xia, Q.; Grant, S.F. Genetic susceptibility to type 2 diabetes and obesity: Follow-up of findings from genome-wide association studies. Int. J. Endocrinol. 2014, 2014, 769671. [Google Scholar] [CrossRef] [PubMed]
  285. Zdrojowy-Wełna, A.; Tupikowska, M.; Kolackov, K.; Bednarek-Tupikowska, G. The role of fat mass and obesity-associated gene (FTO) in obesity—An overview. Endokrynol. Pol. 2014, 65, 224–231. [Google Scholar] [CrossRef] [PubMed]
  286. Zhao, X.; Yang, Y.; Sun, B.F.; Zhao, Y.L.; Yang, Y.G. FTO and obesity: Mechanisms of association. Curr. Diabetes Rep. 2014, 14, 486. [Google Scholar] [CrossRef] [PubMed]
  287. Sebert, S.; Salonurmi, T.; Keinänen-Kiukaanniemi, S.; Savolainen, M.; Herzig, K.H.; Symonds, M.E.; Järvelin, M.R. Programming effects of FTO in the development of obesity. Acta Physiol. 2014, 210, 58–69. [Google Scholar] [CrossRef] [PubMed]
  288. Wiley, A.S. Milk intake and total dairy consumption: Associations with early menarche in NHANES 1999–2004. PLoS ONE 2011, 6, e14685. [Google Scholar] [CrossRef] [PubMed]
  289. Sullivan, E.L.; Grove, K.L. Metabolic imprinting in obesity. Forum Nutr. 2010, 63, 186–194. [Google Scholar] [PubMed]
  290. Koletzko, B. Childhood obesity: Current situation and future opportunities. J. Pediatr. Gastroenterol. Nutr. 2016, 63 (Suppl. S1), S18–S21. [Google Scholar] [PubMed]
  291. Smego, A.; Woo, J.G.; Klein, J.; Suh, C.; Bansal, D.; Bliss, S.; Daniels, S.R.; Bolling, C.; Crimmins, N.A. High body mass index in infancy may predict severe obesity in early childhood. J. Pediatr. 2016. [Google Scholar] [CrossRef] [PubMed]
  292. Gruszfeld, D.; Socha, P. Early nutrition and health: Short- and long-term outcomes. World Rev. Nutr. Diet. 2013, 108, 32–39. [Google Scholar] [PubMed]
  293. Reynolds, C.M.; Gray, C.; Li, M.; Segovia, S.A.; Vickers, M.H. Early life nutrition and energy balance disorders in offspring in later life. Nutrients 2015, 7, 8090–8111. [Google Scholar] [CrossRef] [PubMed]
  294. Egan, K.B.; Ettinger, A.S.; Bracken, M.B. Childhood body mass index and subsequent physician-diagnosed asthma: A systematic review and meta-analysis of prospective cohort studies. BMC Pediatr. 2013, 13, 121. [Google Scholar] [CrossRef] [PubMed]
  295. Brüske, I.; Flexeder, C.; Heinrich, J. Body mass index and the incidence of asthma in children. Curr. Opin. Allergy Clin. Immunol. 2014, 14, 155–160. [Google Scholar] [CrossRef] [PubMed]
  296. Melnik, B.C. The potential mechanistic link between allergy and obesity development and infant formula feeding. Allergy Asthma Clin. Immunol. 2014, 10, 37. [Google Scholar] [CrossRef] [PubMed]
  297. Günther, A.L.; Schulze, M.B.; Kroke, A.; Diethelm, K.; Joslowski, G.; Krupp, D.; Wudy, S.; Buyken, A.E. Early diet and later cancer risk: Prospective associations of dietary patterns during critical periods of childhood with the GH-IGF axis, insulin resistance and body fatness in younger adulthood. Nutr. Cancer 2015, 67, 877–892. [Google Scholar] [CrossRef] [PubMed]
  298. Von Bonsdorff, M.B.; Törmäkangas, T.; Rantanen, T.; Salonen, M.K.; Osmond, C.; Kajantie, E.; Eriksson, J.G. Early life body mass trajectories and mortality in older age: Findings from the Helsinki Birth Cohort Study. Ann. Med. 2015, 47, 34–39. [Google Scholar] [CrossRef] [PubMed]
  299. Burdge, G.C.; Lillycrop, K.A.; Jackson, A.A. Nutrition in early life, and risk of cancer and metabolic disease: Alternative endings in an epigenetic tale? Br. J. Nutr. 2009, 101, 619–630. [Google Scholar] [CrossRef] [PubMed]
  300. Bag, S.; Ramaiah, S.; Anbarasu, A. fabp4 is central to eight obesity associated genes: A functional gene Network-based polymorphic study. J. Theor. Biol. 2015, 364, 344–354. [Google Scholar] [CrossRef] [PubMed]
  301. Khalyfa, A.; Bhushan, B.; Hegazi, M.; Kim, J.; Kheirandish-Gozal, L.; Bhattacharjee, R.; Capdevila, O.S.; Gozal, D. Fatty-acid binding protein 4 gene variants and childhood obesity: Potential implications for insulin sensitivity and CRP levels. Lipids Health Dis. 2010, 9, 18. [Google Scholar] [CrossRef] [PubMed]
  302. Erbay, E.; Babaev, V.R.; Mayers, J.R.; Makowski, L.; Charles, K.N.; Snitow, M.E.; Fazio, S.; Wiest, M.M.; Watkins, S.M.; Linton, M.F.; et al. Reducing endoplasmic reticulum stress through a macrophage lipid chaperone alleviates atherosclerosis. Nat. Med. 2009, 15, 1383–1391. [Google Scholar] [CrossRef] [PubMed]
  303. Zamaninour, N.; Mirzaei, K.; Keshavarz, S.A.; Ansar, H.; Hossein-Nezhad, A. New insight into determining indicators of metabolic status in women: Expression of PPARγ and FABP4 in PBMCs. Women Health 2016, 1–14. [Google Scholar] [CrossRef] [PubMed]
  304. Cabré, A.; Babio, N.; Lázaro, I.; Bulló, M.; Garcia-Arellano, A.; Masana, L.; Salas-Salvadó, J. FABP4 predicts atherogenic dyslipidemia development. The PREDIMED study. Atherosclerosis 2012, 222, 229–234. [Google Scholar] [CrossRef] [PubMed]
  305. Seeßle, J.; Liebisch, G.; Schmitz, G.; Stremmel, W.; Chamulitrat, W. Palmitate activation by fatty acid transport protein 4 as a model system for hepatocellular apoptosis and steatosis. Biochim. Biophys. Acta 2015, 1851, 549–565. [Google Scholar] [CrossRef] [PubMed]
  306. Terra, X.; Quintero, Y.; Auguet, T.; Porras, J.A.; Hernández, M.; Sabench, F.; Aguilar, C.; Luna, A.M.; Del Castillo, D.; Richart, C. FABP 4 is associated with inflammatory markers and metabolic syndrome in morbidly obese women. Eur. J. Endocrinol. 2011, 164, 539–547. [Google Scholar] [CrossRef] [PubMed]
  307. Yang, A.; Zhang, H.; Sun, Y.; Wang, Y.; Yang, X.; Yang, X.; Zhang, H.; Guo, W.; Zhu, G.; Tian, J.; et al. Modulation of FABP4 hypomethylation by DNMT1 and its inverse interaction with miR-148a/152 in the placenta of preeclamptic rats and HTR-8 cells. Placenta 2016, 46, 49–62. [Google Scholar] [CrossRef] [PubMed]
  308. Michaëlsson, K.; Wolk, A.; Langenskiöld, S.; Basu, S.; Warensjö Lemming, E.; Melhus, H.; Byberg, L. Milk intake and risk of mortality and fractures in women and men: Cohort studies. BMJ 2014, 349, g6015. [Google Scholar] [CrossRef] [PubMed]
  309. Sekar, D.; Venugopal, B.; Sekar, P.; Ramalingam, K. Role of microRNA 21 in diabetes and associated/related diseases. Gene 2016, 582, 14–18. [Google Scholar] [CrossRef] [PubMed]
  310. Bai, C.; Li, X.; Gao, Y.; Wang, K.; Fan, Y.; Zhang, S.; Ma, Y.; Guan, W. Role of microRNA-21 in the formation of insulin-producing cells from pancreatic progenitor cells. Biochim. Biophys. Acta 2016, 1859, 280–293. [Google Scholar] [CrossRef] [PubMed]
  311. Calo, N.; Ramadori, P.; Sobolewski, C.; Romero, Y.; Maeder, C.; Fournier, M.; Rantakari, P.; Zhang, F.P.; Poutanen, M.; Dufour, J.F.; et al. Stress-activated miR-21/miR-21* in hepatocytes promotes lipid and glucose metabolic disorders associated with high-fat diet consumption. Gut 2016. [Google Scholar] [CrossRef] [PubMed]
  312. Seeger, T.; Fischer, A.; Muhly-Reinholz, M.; Zeiher, A.M.; Dimmeler, S. Long-term inhibition of miR-21 leads to reduction of obesity in db/db mice. Obesity (Silver Spring) 2014, 22, 2352–2360. [Google Scholar] [CrossRef] [PubMed]
  313. Janghorbani, M.; Mansourian, M.; Hosseini, E. Systematic review and meta-analysis of age at menarche and risk of type 2 diabetes. Acta Diabetol. 2014, 51, 519–528. [Google Scholar] [CrossRef] [PubMed]
  314. Sluijs, I.; Forouhi, N.G.; Beulens, J.W.; van der Schouw, Y.T.; Agnoli, C.; Arriola, L.; Balkau, B.; Barricarte, A.; Boeing, H.; Bueno-de-Mesquita, H.B.; et al. The amount and type of dairy product intake and incident type 2 diabetes: Results from the EPIC-InterAct Study. Am. J. Clin. Nutr. 2012, 96, 382–390. [Google Scholar] [CrossRef] [PubMed]
  315. Hoppe, C.; Mølgaard, C.; Vaag, A.; Barkholt, V.; Michaelsen, K.F. High intakes of milk, but not meat, increase s-insulin and insulin resistance in 8-year-old boys. Eur. J. Clin. Nutr. 2005, 59, 393–398. [Google Scholar] [CrossRef] [PubMed]
  316. Song, Y.; Chavarro, J.E.; Cao, Y.; Qiu, W.; Mucci, L.; Sesso, H.D.; Stampfer, M.J.; Giovannucci, E.; Pollak, M.; Liu, S.; et al. Whole milk intake is associated with prostate cancer-specific mortality among U.S. male physicians. J. Nutr. 2013, 143, 189–196. [Google Scholar] [CrossRef] [PubMed]
  317. Melnik, B.C. The pathogenic role of persistent milk signaling in mTORC1- and milk-microRNA-driven type 2 diabetes mellitus. Curr. Diabetes Rev. 2015, 11, 46–62. [Google Scholar] [CrossRef] [PubMed]
  318. Peng, H.; Zhong, M.; Zhao, W.; Wang, C.; Zhang, J.; Liu, X.; Li, Y.; Paudel, S.D.; Wang, Q.; Lou, T. Urinary miR-29 correlates with albuminuria and carotid intima-media thickness in type 2 diabetes patients. PLoS ONE 2013, 8, e82607. [Google Scholar] [CrossRef] [PubMed]
  319. Arnold, N.; Koppula, P.R.; Gul, R.; Luck, C.; Pulakat, L. Regulation of cardiac expression of the diabetic marker microRNA miR-29. PLoS ONE. 2014, 9, e103284. [Google Scholar] [CrossRef] [PubMed]
  320. Deiuliis, J.A. MicroRNAs as regulators of metabolic disease: Pathophysiologic significance and emerging role as biomarkers and therapeutics. Int. J. Obes. 2016, 40, 88–101. [Google Scholar] [CrossRef] [PubMed]
  321. Kurtz, C.L.; Peck, B.C.; Fannin, E.E.; Beysen, C.; Miao, J.; Landstreet, S.R.; Ding, S.; Turaga, V.; Lund, P.K.; Turner, S.; et al. MicroRNA-29 fine-tunes the expression of key FOXA2-activated lipid metabolism genes and is dysregulated in animal models of insulin resistance and diabetes. Diabetes 2014, 63, 3141–3148. [Google Scholar] [CrossRef] [PubMed]
  322. Nicholas, L.M.; Rattanatray, L.; MacLaughlin, S.M.; Ozanne, S.E.; Kleemann, D.O.; Walker, S.K.; Morrison, J.L.; Zhang, S.; Muhlhäusler, B.S.; Martin-Gronert, M.S.; et al. Differential effects of maternal obesity and weight loss in the periconceptional period on the epigenetic regulation of hepatic insulin-signaling pathways in the offspring. FASEB J. 2013, 27, 3786–3796. [Google Scholar] [CrossRef] [PubMed]
  323. Shen, F.; Huang, W.; Huang, J.T.; Xiong, J.; Yang, Y.; Wu, K.; Jia, G.F.; Chen, J.; Feng, Y.Q.; Yuan, B.F.; et al. Decreased N(6)-methyladenosine in peripheral blood RNA from diabetic patients is associated with FTO expression rather than ALKBH5. J. Clin. Endocrinol. Metab. 2015, 100, E148–E154. [Google Scholar] [CrossRef] [PubMed]
  324. Su, D.; Zhang, C.L.; Gao, Y.C.; Liu, X.Y.; Li, C.P.; Huangfu, J.; Xiao, R. Gene expression and correlation of Pten and Fabp4 in liver, muscle, and adipose tissues of type 2 diabetes rats. Med. Sci. Monit. 2015, 21, 3616–3621. [Google Scholar] [CrossRef] [PubMed]
  325. Bagheri, R.; Qasim, A.N.; Mehta, N.N.; Terembula, K.; Kapoor, S.; Braunstein, S.; Schutta, M.; Iqbal, N.; Lehrke, M.; Reilly, M.P. Relation of plasma fatty acid binding proteins 4 and 5 with the metabolic syndrome, inflammation and coronary calcium in patients with type-2 diabetes mellitus. Am. J. Cardiol. 2010, 106, 1118–1123. [Google Scholar] [CrossRef] [PubMed]
  326. Furuhashi, M.; Saitoh, S.; Shimamoto, K.; Miura, T. Fatty acid-binding protein 4 (FABP4): Pathophysiological insights and potent clinical biomarker of metabolic and cardiovascular diseases. Clin. Med. Insights Cardiol. 2015, 8 (Suppl. 3), 23–33. [Google Scholar] [CrossRef] [PubMed]
  327. Zielke, L.G.; Bortfeldt, R.H.; Reissmann, M.; Tetens, J.; Thaller, G.; Brockmann, G.A. Impact of variation at the FTO locus on milk fat yield in Holstein dairy cattle. PLoS ONE 2013, 8, e63406. [Google Scholar] [CrossRef] [PubMed]
  328. Zhou, H.; Cheng, L.; Azimu, W.; Hodge, S.; Edwards, G.R.; Hickford, J.G. Variation in the bovine FABP4 gene affects milk yield and milk protein content in dairy cows. Sci. Rep. 2015, 5, 10023. [Google Scholar] [CrossRef] [PubMed]
  329. Ji, J.; Sundquist, J.; Sundquist, K. Lactose intolerance and risk of lung, breast and ovarian cancers: Aetiological clues from a population-based study in Sweden. Br. J. Cancer 2015, 112, 149–152. [Google Scholar] [CrossRef] [PubMed]
  330. Gaard, M.; Tretli, S.; Løken, E.B. Dietary fat and the risk of breast cancer: A prospective study of 25,892 Norwegian women. Int. J. Cancer 1995, 63, 13–17. [Google Scholar] [CrossRef] [PubMed]
  331. Tan, A.; Dang, Y.; Chen, G.; Mo, Z. Overexpression of the fat mass and obesity associated gene (FTO) in breast cancer and its clinical implications. Int. J. Clin. Exp. Pathol. 2015, 8, 13405–13410. [Google Scholar] [PubMed]
  332. Guaita-Esteruelas, S.; Bosquet, A.; Saavedra, P.; Gumà, J.; Girona, J.; Lam, E.W.; Amillano, K.; Borràs, J.; Masana, L. Exogenous FABP4 increases breast cancer cell proliferation and activates the expression of fatty acid transport proteins. Mol. Carcinog. 2017, 56, 208–217. [Google Scholar] [CrossRef] [PubMed]
  333. Lu, W.; Chen, H.; Niu, Y.; Wu, H.; Xia, D.; Wu, Y. Dairy products intake and cancer mortality risk: A meta-analysis of 11 population-based cohort studies. Nutr. J. 2016, 15, 91. [Google Scholar] [CrossRef] [PubMed]
  334. Murata, T.; Takayama, K.; Katayama, S.; Urano, T.; Horie-Inoue, K.; Ikeda, K.; Takahashi, S.; Kawazu, C.; Hasegawa, A.; Ouchi, Y.; et al. miR-148a is an androgen-responsive microRNA that promotes LNCaP prostate cell growth by repressing its target CAND1 expression. Prostate Cancer Prostatic Dis. 2010, 13, 356–361. [Google Scholar] [CrossRef] [PubMed]
  335. Tate, P.L.; Bibb, R.; Larcom, L.L. Milk stimulates growth of prostate cancer cells in culture. Nutr. Cancer 2011, 63, 1361–1366. [Google Scholar] [CrossRef] [PubMed]
  336. Day, K.C.; Hiles, G.L.; Kozminsky, M.; Dawsey, S.J.; Paul, A.; Broses, L.J.; Shah, R.; Kunja, L.P.; Hall, C.; Palanisamy, N.; et al. HER2 and EGFR overexpression support metastatic progression of prostate cancer to bone. Cancer Res. 2017, 77, 74–85. [Google Scholar] [CrossRef] [PubMed]
  337. Siu, A.; Virtanen, C.; Jongstra, J. PIM kinase isoform specific regulation of MIG6 expression and EGFR signaling in prostate cancer cells. Oncotarget 2011, 2, 1134–1144. [Google Scholar] [CrossRef] [PubMed]
  338. Ralston, R.A.; Truby, H.; Palermo, C.E.; Walker, K.Z. Colorectal cancer and nonfermented milk, solid cheese, and fermented milk consumption: A systematic review and meta-analysis of prospective studies. Crit. Rev. Food Sci. Nutr. 2014, 54, 1167–1179. [Google Scholar] [CrossRef] [PubMed]
  339. Takahashi, M.; Cuatrecasas, M.; Balaguer, F.; Hur, K.; Toiyama, Y.; Castells, A.; Boland, C.R.; Goel, A. The clinical significance of MiR-148a as a predictive biomarker in patients with advanced colorectal cancer. PLoS ONE 2012, 7, e46684. [Google Scholar] [CrossRef] [PubMed]
  340. Hibino, Y.; Sakamoto, N.; Naito, Y.; Goto, K.; Oo, H.Z.; Sentani, K.; Hinoi, T.; Ohdan, H.; Oue, N.; Yasui, W. Significance of miR-148a in colorectal neoplasia: Downregulation of miR-148a contributes to the carcinogenesis and cell invasion of colorectal cancer. Pathobiology 2015, 82, 233–241. [Google Scholar] [CrossRef] [PubMed]
  341. Li, Y.; Deng, X.; Zeng, X.; Peng, X. The role of mir-148a in cancer. J. Cancer 2016, 7, 1233–1241. [Google Scholar] [CrossRef] [PubMed]
  342. Zhang, H.L.; Yang, L.F.; Zhu, Y.; Yao, X.D.; Zhang, S.L.; Dai, B.; Zhu, Y.P.; Shen, Y.J.; Shi, G.H.; Ye, D.W. Serum miRNA-21: Elevated levels in patients with metastatic hormone-refractory prostate cancer and potential predictive factor for the efficacy of docetaxel-based chemotherapy. Prostate 2011, 71, 326–331. [Google Scholar] [CrossRef] [PubMed]
  343. Shen, J.; Hruby, G.W.; McKiernan, J.M.; Gurvich, I.; Lipsky, M.J.; Benson, M.C.; Santella, R.M. Dysregulation of circulating microRNAs and prediction of aggressive prostate cancer. Prostate 2012, 72, 1469–1477. [Google Scholar] [CrossRef] [PubMed]
  344. Filella, X.; Foj, L. Prostate cancer detection and prognosis: From prostate specific antigen (PSA) to exosomal biomarkers. Int. J. Mol. Sci. 2016, 17, E1784. [Google Scholar] [CrossRef] [PubMed]
  345. Gao, Y.; Guo, Y.; Wang, Z.; Dai, Z.; Xu, Y.; Zhang, W.; Liu, Z.; Li, S. Analysis of circulating miRNAs 21 and 375 as potential biomarkers for early diagnosis of prostate cancer. Neoplasma 2016, 63, 623–628. [Google Scholar] [CrossRef] [PubMed]
  346. Feng, Y.H.; Tsao, C.J. Emerging role of microRNA-21 in cancer. Biomed. Rep. 2016, 5, 395–402. [Google Scholar] [CrossRef] [PubMed]
  347. Melnik, B.C. MiR-21: An environmental driver of malignant melanoma? J. Transl. Med. 2015, 13, 202. [Google Scholar] [CrossRef] [PubMed]
  348. Pfeffer, S.R.; Yang, C.H.; Pfeffer, L.M. The role of miR-21 in cancer. Drug Dev. Res. 2015, 76, 270–277. [Google Scholar] [CrossRef] [PubMed]
  349. Shi, J. Considering exosomal miR-21 as a biomarker for cancer. J. Clin. Med. 2016, 5, E42. [Google Scholar] [CrossRef] [PubMed]
  350. Chen, H.; Liu, H.; Zou, H.; Chen, R.; Dou, Y.; Sheng, S.; Dai, S.; Ai, J.; Melson, J.; Kittles, R.A.; et al. Evaluation of plasma miR-21 and miR-152 as diagnostic biomarkers for common types of human cancers. J. Cancer 2016, 7, 490–499. [Google Scholar] [CrossRef] [PubMed]
  351. Huang, J.T.; Liu, S.M.; Ma, H.; Yang, Y.; Zhang, X.; Sun, H.; Zhang, X.; Xu, J.; Wang, J. Systematic review and meta-analysis: Circulating miRNAs for diagnosis of hepatocellular carcinoma. J. Cell. Physiol. 2016, 231, 328–335. [Google Scholar] [CrossRef] [PubMed]
  352. Li, G.; Shen, Q.; Li, C.; Li, D.; Chen, J.; He, M. Identification of circulating microRNAs as novel potential biomarkers for hepatocellular carcinoma detection: A systematic review and meta-analysis. Clin. Transl. Oncol. 2015, 17, 684–693. [Google Scholar] [CrossRef] [PubMed]
  353. Wang, H.; Hou, L.; Li, A.; Duan, Y.; Gao, H.; Song, X. Expression of serum exosomal microRNA-21 in human hepatocellular carcinoma. Biomed. Res. Int. 2014, 2014, 864894. [Google Scholar] [CrossRef] [PubMed]
  354. Duarte-Salles, T.; Fedirko, V.; Stepien, M.; Trichopoulou, A.; Bamia, C.; Lagiou, P.; Lukanova, A.; Trepo, E.; Overvad, K.; Tjønneland, A.; et al. Dairy products and risk of hepatocellular carcinoma: The European Prospective Investigation into Cancer and Nutrition. Int. J. Cancer 2014, 135, 1662–1672. [Google Scholar] [CrossRef] [PubMed]
  355. Chouliaras, L.; Rutten, B.P.; Kenis, G.; Peerbooms, O.; Visser, P.J.; Verhey, F.; van Os, J.; Steinbusch, H.W.; van den Hove, D.L. Epigenetic regulation in the pathophysiology of Alzheimer’s disease. Prog. Neurobiol. 2010, 90, 498–510. [Google Scholar] [CrossRef] [PubMed]
  356. Otaegui-Arrazola, A.; Amiano, P.; Elbusto, A.; Urdaneta, E.; Martínez-Lage, P. Diet, cognition, and Alzheimer’s disease: Food for thought. Eur. J. Nutr. 2014, 53, 1–23. [Google Scholar] [CrossRef] [PubMed]
  357. Davinelli, S.; Calabrese, V.; Zella, D.; Scapagnini, G. Epigenetic nutraceutical diets in Alzheimer’s disease. J. Nutr. Health Aging 2014, 18, 800–805. [Google Scholar] [CrossRef] [PubMed]
  358. Lardenoije, R.; Iatrou, A.; Kenis, G.; Kompotis, K.; Steinbusch, H.W.; Mastroeni, D.; Coleman, P.; Lemere, C.A.; Hof, P.R.; van den Hove, D.L.; et al. The epigenetics of aging and neurodegeneration. Prog. Neurobiol. 2015, 131, 21–64. [Google Scholar] [CrossRef] [PubMed]
  359. Wüllner, U.; Kaut, O.; deBoni, L.; Piston, D.; Schmitt, I. DNA methylation in Parkinson‘s disease. J. Neurochem. 2016, 139 (Suppl. 1), 108–120. [Google Scholar] [CrossRef] [PubMed]
  360. Tang, Z.; Bereczki, E.; Zhang, H.; Wang, S.; Li, C.; Ji, X.; Branca, R.M.; Lehtiö, J.; Guan, Z.; Filipcik, P.; et al. Mammalian target of rapamycin (mTor) mediates tau protein dyshomeostasis: Implication for Alzheimer disease. J. Biol. Chem. 2013, 288, 15556–15570. [Google Scholar] [CrossRef] [PubMed]
  361. Tang, Z.; Ioja, E.; Bereczki, E.; Hultenby, K.; Li, C.; Guan, Z.; Winblad, B.; Pei, J.J. mTor mediates tau localization and secretion: Implication for Alzheimer’s disease. Biochim. Biophys Acta 2015, 1853, 1646–1657. [Google Scholar] [CrossRef] [PubMed]
  362. Sun, Y.X.; Ji, X.; Mao, X.; Xie, L.; Jia, J.; Galvan, V.; Greenberg, D.A.; Jin, K. Differential activation of mTOR complex 1 signaling in human brain with mild to severe Alzheimer’s disease. J. Alzheimers Dis. 2014, 38, 437–444. [Google Scholar] [PubMed]
  363. Leszek, J.; Trypka, E.; Tarasov, V.V.; Md Ashraf, G. Type 3 diabetes mellitus: A novel implication of Alzheimer Disease. Curr. Top. Med. Chem. 2017. [Google Scholar] [CrossRef]
  364. Ho, A.J.; Stein, J.L.; Hua, X.; Lee, S.; Hibar, D.P.; Leow, A.D.; Dinov, I.D.; Toga, A.W.; Saykin, A.J.; Shen, L.; et al. Alzheimer’s Disease Neuroimaging Initiative. A commonly carried allele of the obesity-related FTO gene is associated with reduced brain volume in the healthy elderly. Proc. Natl. Acad. Sci. USA 2010, 107, 8404–8409. [Google Scholar] [CrossRef] [PubMed]
  365. Benedict, C.; Jacobsson, J.A.; Rönnemaa, E.; Sällman-Almén, M.; Brooks, S.; Schultes, B.; Fredriksson, R.; Lannfelt, L.; Kilander, L.; Schiöth, H.B. The fat mass and obesity gene is linked to reduced verbal fluency in overweight and obese elderly men. Neurobiol. Aging 2011, 32, 1159.e1–1159.e5. [Google Scholar] [CrossRef] [PubMed]
  366. De Groot, C.; Felius, A.; Trompet, S.; de Craen, A.J.; Blauw, G.J.; van Buchem, M.A.; Delemarre-van de Waal, H.A.; van der Grond, J. Association of the fat mass and obesity-associated gene risk allele, rs9939609A, and reward-related brain structures. Obesity (Silver Spring) 2015, 23, 2118–2122. [Google Scholar] [CrossRef] [PubMed]
  367. Keller, L.; Xu, W.; Wang, H.X.; Winblad, B.; Fratiglioni, L.; Graff, C. The obesity related gene, FTO, interacts with APOE, and is associated with Alzheimer’s disease risk: A prospective cohort study. J. Alzheimers Dis. 2011, 23, 461–469. [Google Scholar] [PubMed]
  368. Yamagata, K.; Urakami, K.; Ikeda, K.; Ji, Y.; Adachi, Y.; Arai, H.; Sasaki, H.; Sato, K.; Nakashima, K. High expression of apolipoprotein E mRNA in the brains with sporadic Alzheimer’s disease. Dement. Geriatr. Cogn. Disord. 2001, 12, 57–62. [Google Scholar] [CrossRef] [PubMed]
  369. Caesar, I.; Gandy, S. Evidence that an APOE ε4 ‘double whammy’ increases risk for Alzheimer’s disease. BMC Med. 2012, 10, 36. [Google Scholar] [CrossRef] [PubMed]
  370. Castellano, J.M.; Kim, J.; Stewart, F.R.; Jiang, H.; DeMattos, R.B.; Patterson, B.W.; Fagan, A.M.; Morris, J.C.; Mawuenyega, K.G.; Cruchaga, C.; et al. Human apoE isoforms differentially regulate brain amyloid-β peptide clearance. Sci. Transl. Med. 2011, 3, 89ra57. [Google Scholar] [CrossRef] [PubMed]
  371. Pankiewicz, J.E.; Guridi, M.; Kim, J.; Asuni, A.A.; Sanchez, S.; Sullivan, P.M.; Holtzman, D.M.; Sadowski, M.J. Blocking the apoE/Aβ interaction ameliorates Aβ-related pathology in APOE ε2 and ε4 targeted replacement Alzheimer model mice. Acta Neuropathol. Commun. 2014, 2, 75. [Google Scholar] [CrossRef] [PubMed]
  372. Foraker, J.; Millard, S.P.; Leong, L.; Thomson, Z.; Chen, S.; Keene, C.D.; Bekris, L.M.; Yu, C.E. The APOE gene is differentially methylated in Alzheimer’s Disease. J. Alzheimers Dis. 2015, 48, 745–755. [Google Scholar] [CrossRef] [PubMed]
  373. Reitz, C.; Tosto, G.; Mayeux, R.; Luchsinger, J.A.; NIA-LOAD/NCRAD Family Study Group; Alzheimer’s Disease Neuroimaging Initiative. Genetic variants in the Fat and Obesity Associated (FTO) gene and risk of Alzheimer’s disease. PLoS ONE 2012, 7, e50354. [Google Scholar] [CrossRef] [PubMed]
  374. Adebakin, A.; Bradley, J.; Gümüsgöz, S.; Waters, E.J.; Lawrence, C.B. Impaired satiation and increased feeding behaviour in the triple-transgenic Alzheimer’s disease mouse model. PLoS ONE 2012, 7, e45179. [Google Scholar] [CrossRef] [PubMed]
  375. Chen, H.; Zhang, S.M.; Hernán, M.A.; Willett, W.C.; Ascherio, A. Diet and Parkinson’s disease: A potential role of dairy products in men. Ann. Neurol. 2002, 52, 793–801. [Google Scholar] [CrossRef] [PubMed]
  376. Park, M.; Ross, G.W.; Petrovitch, H.; White, L.R.; Masaki, K.H.; Nelson, J.S.; Tanner, C.M.; Curb, J.D.; Blanchette, P.L.; Abbott, R.D. Consumption of milk and calcium in midlife and the future risk of Parkinson disease. Neurology 2005, 64, 1047–1051. [Google Scholar] [CrossRef] [PubMed]
  377. Chen, H.; O’Reilly, E.; McCullough, M.L.; Rodriguez, C.; Schwarzschild, M.A.; Calle, E.E.; Thun, M.J.; Ascherio, A. Consumption of dairy products and risk of Parkinson’s disease. Am. J. Epidemiol. 2007, 165, 998–1006. [Google Scholar] [CrossRef] [PubMed]
  378. Kyrozis, A.; Ghika, A.; Stathopoulos, P.; Vassilopoulos, D.; Trichopoulou, D.; Trichopoulou, A. Dietary and lifestyle variables in relation to incidence of Parkinson’s disease in Greece. Eur. J. Epidemiol. 2013, 28, 67–77. [Google Scholar] [CrossRef] [PubMed]
  379. Sääksjärvi, K.; Knekt, P.; Lundqvist, A.; Männistö, S.; Heliövaara, M.; Rissanen, H.; Järvinen, R. A cohort study on diet and the risk of Parkinson’s disease: The role of food groups and diet quality. Br. J. Nutr. 2013, 109, 329–337. [Google Scholar] [CrossRef] [PubMed]
  380. Jiang, W.; Ju, C.; Jiang, H.; Zhang, D. Dairy foods intake and risk of Parkinson’s disease: A dose-response meta-analysis of prospective cohort studies. Eur. J. Epidemiol. 2014, 29, 613–619. [Google Scholar] [CrossRef] [PubMed]
  381. Abbott, R.D.; Ross, G.W.; Petrovitch, H.; Masaki, K.H.; Launer, L.J.; Nelson, J.S.; White, L.R.; Tanner, C.M. Midlife milk consumption and substantia nigra neuron density at death. Neurology 2016, 86, 512–519. [Google Scholar] [CrossRef] [PubMed]
  382. Xu, X. DNA methylation and cognitive aging. Oncotarget 2015, 6, 13922–13932. [Google Scholar] [CrossRef] [PubMed]
  383. Jowaed, A.; Schmitt, I.; Kaut, O.; Wüllner, U. Methylation regulates alpha-synuclein expression and is decreased in Parkinson’s disease patients’ brains. J. Neurosci. 2010, 30, 6355–6359. [Google Scholar] [CrossRef] [PubMed]
  384. Matsumoto, L.; Takuma, H.; Tamaoka, A.; Kurisaki, H.; Date, H.; Tsuji, S.; Iwata, A. CpG demethylation enhances alpha-synuclein expression and affects the pathogenesis of Parkinson’s disease. PLoS ONE 2010, 5, e15522. [Google Scholar] [CrossRef] [PubMed]
  385. Swinnen, E.; Büttner, S.; Outeiro, T.F.; Galas, M.C.; Madeo, F.; Winderickx, J.; Franssens, V. Aggresome formation and segregation of inclusions influence toxicity of α-synuclein and synphilin-1 in yeast. Biochem. Soc. Trans. 2011, 39, 1476–1481. [Google Scholar] [CrossRef] [PubMed]
  386. Engelender, S.; Kaminsky, Z.; Guo, X.; Sharp, A.H.; Amaravi, R.K.; Kleiderlein, J.J.; Margolis, R.L.; Troncoso, J.C.; Lanahan, A.A.; Worley, P.F.; et al. Synphilin-1 associates with alpha-synuclein and promotes the formation of cytosolic inclusions. Nat. Genet. 1999, 22, 110–114. [Google Scholar] [PubMed]
  387. Outeiro, T.F.; Lindquist, S. Yeast cells provide insight into alpha-synuclein biology and pathobiology. Science 2003, 302, 1772–1775. [Google Scholar] [CrossRef] [PubMed]
  388. Goris, A.; Williams-Gray, C.H.; Clark, G.R.; Foltynie, T.; Lewis, S.J.; Brown, J.; Ban, M.; Spillantini, M.G.; Compston, A.; Burn, D.J.; et al. Tau and alpha-synuclein in susceptibility to, and dementia in, Parkinson’s disease. Ann. Neurol. 2007, 62, 145–153. [Google Scholar] [CrossRef] [PubMed]
  389. Collins, L.M.; Williams-Gray, C.H. The genetic basis of cognitive impairment and dementia in Parkinson’s disease. Front. Psychiatry 2016, 7, 89. [Google Scholar] [CrossRef] [PubMed]
  390. Desplats, P.; Spencer, B.; Coffee, E.; Patel, P.; Michael, S.; Patrick, C.; Adame, A.; Rockenstein, E.; Masliah, E. Alpha-synuclein sequesters Dnmt1 from the nucleus: A novel mechanism for epigenetic alterations in Lewy body diseases. J. Biol. Chem. 2011, 286, 9031–9037. [Google Scholar] [CrossRef] [PubMed]
  391. Hu, C.W.; Tseng, C.W.; Chien, C.W.; Huang, H.C.; Ku, W.C.; Lee, S.J.; Chen, Y.J.; Juan, H.F. Quantitative proteomics reveals diverse roles of miR-148a from gastric cancer progression to neurological development. J. Proteome Res. 2013, 12, 3993–4004. [Google Scholar] [CrossRef] [PubMed]
  392. Zoncu, R.; Efeyan, A.; Sabatini, D.M. mTOR: From growth signal integration to cancer, diabetes and ageing. Nat. Rev. Mol. Cell Biol. 2011, 12, 21–35. [Google Scholar] [CrossRef] [PubMed]
  393. Dazert, E.; Hall, M.N. mTOR signaling in disease. Curr. Opin. Cell Biol. 2011, 23, 744–755. [Google Scholar] [CrossRef] [PubMed]
  394. Melnik, B.C.; John, S.M.; Carrera-Bastos, P.; Cordain, L. The impact of cow’s milk-mediated mTORC1-signaling in the initiation and progression of prostate cancer. Nutr. Metab. (Lond.) 2012, 9, 74. [Google Scholar] [CrossRef] [PubMed]
  395. Oddo, S. The role of mTOR signaling in Alzheimer disease. Front. Biosci. (Schol. Ed.) 2012, 4, 941–952. [Google Scholar] [CrossRef] [PubMed]
  396. Cornu, M.; Albert, V.; Hall, M.N. mTOR in aging, metabolism, and cancer. Curr. Opin. Genet. Dev. 2013, 23, 53–62. [Google Scholar] [CrossRef] [PubMed]
  397. Perl, A. mTOR activation is a biomarker and a central pathway to autoimmune disorders, cancer, obesity, and aging. Ann. N. Y. Acad. Sci. 2015, 1346, 33–44. [Google Scholar] [CrossRef] [PubMed]
  398. Steelman, L.S.; Martelli, A.M.; Cocco, L.; Libra, M.; Nicoletti, F.; Abrams, S.L.; McCubrey, J.A. The therapeutic potential of mTOR inhibitors in breast cancer. Br. J. Clin. Pharmacol. 2016, 82, 1189–1212. [Google Scholar] [CrossRef] [PubMed]
  399. Melnik, B.C.; Schmitz, G. Metformin: An inhibitor of mTORC1 signaling. J. Endocrinol. Diabetes Obes. 2014, 2, 1029. [Google Scholar]
  400. Zhong, T.; Men, Y.; Lu, L.; Geng, T.; Zhou, J.; Mitsuhashi, A.; Shozu, M.; Maihle, N.J.; Carmichael, G.G.; Taylor, H.S.; et al. Metformin alters DNA methylation genome-wide via the H19/SAHH axis. Oncogene 2016. [Google Scholar] [CrossRef] [PubMed]
  401. Tehlivets, O.; Malanovic, N.; Visram, M.; Pavkov-Keller, T.; Keller, W. S-adenosyl-l-homocysteine hydrolase and methylation disorders: Yeast as a model system. Biochim. Biophys. Acta 2013, 1832, 204–215. [Google Scholar] [CrossRef] [PubMed]
  402. Zhou, J.; Yang, L.; Zhong, T.; Mueller, M.; Men, Y.; Zhang, N.; Xie, J.; Giang, K.; Chung, H.; Sun, X.; et al. H19 lncRNA alters DNA methylation genome wide by regulating S-adenosylhomocysteine hydrolase. Nat. Commun. 2015, 6, 10221. [Google Scholar] [CrossRef] [PubMed]
  403. Saha, A.; Blando, J.; Tremmel, L.; DiGiovanni, J. Effect of metformin, rapamycin, and their combination on growth and progression of prostate tumors in HiMyc mice. Cancer Prev. Res. (Phila.) 2015, 8, 597–606. [Google Scholar] [CrossRef] [PubMed]
  404. Pérez-Revuelta, B.I.; Hettich, M.M.; Ciociaro, A.; Rotermund, C.; Kahle, P.J.; Krauss, S.; Di Monte, D.A. Metformin lowers Ser-129 phosphorylated α-synuclein levels via mTOR-dependent protein phosphatase 2A activation. Cell Death Dis. 2014, 5, e1209. [Google Scholar] [CrossRef] [PubMed]
  405. Kickstein, E.; Krauss, S.; Thornhill, P.; Rutschow, D.; Zeller, R.; Sharkey, J.; Williamson, R.; Fuchs, M.; Köhler, A.; Glossmann, H.; et al. Biguanide metformin acts on tau phosphorylation via mTOR/protein phosphatase 2A (PP2A) signaling. Proc. Natl. Acad. Sci. USA 2010, 107, 21830–21835. [Google Scholar] [CrossRef] [PubMed]
  406. Rotllan, N.; Price, N.; Pati, P.; Goedeke, L.; Fernández-Hernando, C. microRNAs in lipoprotein metabolism and cardiometabolic disorders. Atherosclerosis 2016, 246, 352–360. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Working model of exosomal transfer of lactation-specific miRNAs that target DNA methyltransferases (DNMT) of the milk recipient. Mammary gland epithelial cells (MEC) secrete DNMT-targeting miRNAs via exosomes, which are taken up by (1) intestinal epithelial cells (IEC) and (2) vascular endothelial cells (VEC) via endocytosis; (3) Especially during the postnatal period, which is associated with high interstinal permeability, milk exosomes may travel along IEC intercellular spaces. After entry into the systemic circulation, milk exosomes may reduce DNA methylation of peripheral target cells.
Figure 1. Working model of exosomal transfer of lactation-specific miRNAs that target DNA methyltransferases (DNMT) of the milk recipient. Mammary gland epithelial cells (MEC) secrete DNMT-targeting miRNAs via exosomes, which are taken up by (1) intestinal epithelial cells (IEC) and (2) vascular endothelial cells (VEC) via endocytosis; (3) Especially during the postnatal period, which is associated with high interstinal permeability, milk exosomes may travel along IEC intercellular spaces. After entry into the systemic circulation, milk exosomes may reduce DNA methylation of peripheral target cells.
Diseases 05 00012 g001
Figure 2. Working model of milk-mediated epigenetic regulation. Milk exosome-derived DNMT-targeting miRNAs enhance DNA promoter demethylation of critical CpG islets involved in the upregulation of gene expression of pivotal transcription factors (NRF2, SREBP1, FOXP3, NR4A3) and key metabolic regulators (INS, IGF1, CAV1, GLUT1, LCT) and the RNA m6A demethylase FTO. Milk-derived DNMT-targeting miRNAs may thus play a fundamental role in epigenetic enhancement of transcription and translation (see list of abbreviations).
Figure 2. Working model of milk-mediated epigenetic regulation. Milk exosome-derived DNMT-targeting miRNAs enhance DNA promoter demethylation of critical CpG islets involved in the upregulation of gene expression of pivotal transcription factors (NRF2, SREBP1, FOXP3, NR4A3) and key metabolic regulators (INS, IGF1, CAV1, GLUT1, LCT) and the RNA m6A demethylase FTO. Milk-derived DNMT-targeting miRNAs may thus play a fundamental role in epigenetic enhancement of transcription and translation (see list of abbreviations).
Diseases 05 00012 g002
Figure 3. Working model of milk-mediated epigenetic actication of fat mass- and obesity-associated protein (FTO) expression modifying the epitranscriptome. Milk-derived DNMT-targeting miRNAs reduce methylation critical DNA CpG islets thereby increasing FTO gene expression. The RNA m6A demethylase FTO erases m6A marks on mRNAs, thereby enhancing FTO-dependent mRNA transcription and mRNA splice variant production such as adipogenic short form of RNX1T1. The mRNAs of ghrelin and dopamine receptor 3 (DRD3) are targets of FTO-mediated upregulation. Resulting hyperphagia and feeding rewards support milk intake for infant growth requirements. Via epigenetic upregulation of FTO expression milk regulates the m6A-controlled epitranscriptome.
Figure 3. Working model of milk-mediated epigenetic actication of fat mass- and obesity-associated protein (FTO) expression modifying the epitranscriptome. Milk-derived DNMT-targeting miRNAs reduce methylation critical DNA CpG islets thereby increasing FTO gene expression. The RNA m6A demethylase FTO erases m6A marks on mRNAs, thereby enhancing FTO-dependent mRNA transcription and mRNA splice variant production such as adipogenic short form of RNX1T1. The mRNAs of ghrelin and dopamine receptor 3 (DRD3) are targets of FTO-mediated upregulation. Resulting hyperphagia and feeding rewards support milk intake for infant growth requirements. Via epigenetic upregulation of FTO expression milk regulates the m6A-controlled epitranscriptome.
Diseases 05 00012 g003
Figure 4. Comparison of milk-miRNA-mediated epigenetic signaling to the human milk recipient. (1) Artifical formula contains only neglectible amounts of bovine miRNAs, which may have an insufficient effect on postnatal epigenetic programming, thus increasing the risk for diseases of civilization; (2) Breastfeeding provides the appropriate epigenetic signaling, which is under control of the human lactation genome, thus reducing the risk for diseases of civilization; (3) Persistent cow milk consumption results in adipogenic, diabetogenic, neurodegenerative, and cancerogenic miRNA signaling; (4) Upregulation of dairy lactation performance increases the burden of milk-derived epigenetic signaling exaggerating the risk of diseases of civilization.
Figure 4. Comparison of milk-miRNA-mediated epigenetic signaling to the human milk recipient. (1) Artifical formula contains only neglectible amounts of bovine miRNAs, which may have an insufficient effect on postnatal epigenetic programming, thus increasing the risk for diseases of civilization; (2) Breastfeeding provides the appropriate epigenetic signaling, which is under control of the human lactation genome, thus reducing the risk for diseases of civilization; (3) Persistent cow milk consumption results in adipogenic, diabetogenic, neurodegenerative, and cancerogenic miRNA signaling; (4) Upregulation of dairy lactation performance increases the burden of milk-derived epigenetic signaling exaggerating the risk of diseases of civilization.
Diseases 05 00012 g004
Table 1. Evidence for milk exosome miRNA transfer into the systemic circulation.
Table 1. Evidence for milk exosome miRNA transfer into the systemic circulation.
The majority of milk exosomes is secreted by mammary epithelial cells[14]
Milk exsomes resist intestinal degradation[38,40,43,61,62,66]
Milk exosomes are taken up by intestinal epithelial cells[75,76,77]
Milk exosomes are taken up by vascular endothelial cells[78]
Increased serum levels of milk-derived miRNAs during lactation[41,46]
Dose-dependent increase of miRNA-29b and miRNA-200c in the serum of cow’s milk consumers[79]
Increase of miRNA-29b and miRNA-200c in peripheral blood mononuclear cells of human volunteers 6 h after commercial milk intake[79]
Increased expression of RUNX2, a regulatory target of miRNA-29b, in PBMCs of healthy humans after cow’s milk consumption[79]
Detection of bovine milk exosomes in murine splenocytes[75]
Predicted role of milk miRNAs in organismal development and organ maturation[17,80,81]
Table 2. High complementarity of seed sequences between human and bovine DNMT-targeting miRNAs.
Table 2. High complementarity of seed sequences between human and bovine DNMT-targeting miRNAs.
Human miRNAs Targeting DNMTsBovine miRNAs Targeting DNMTs
hsa-miRNA-148a-5p
6-aaaguucugagacacuccgacu-27
hsa-miRNA-148a-3p
44-ucagugcacuacagaacuuugu-65


bta-miRNA-148a-3p
44-ucagugcacuacagaacuuugu-65
hsa-miRNA-21-5p
8-uagcuuaucagacugauguuga-29
hsa-miRNA-21-3p
46-caacaccagucgaugggcugu-66
bta-miRNA-21-5p
8-uagcuuaucagacugauguugacu-31
bta-miRNA-21-3p
47-aacagcagucgaugggcugucu-68
hsa-miRNA-29b-1-5p
10-gcugguuucauauggugguuuaga-33
hsa-miRNA-29b-1-3p
51-uagcaccauuugaaaucaguguu-73


bta-miRNA-29-1-3p
51-uagcaccauuugaaaucaguguu-73
Table 3. Selected mRNAs upregulated via FTO-mediated m6A demethylation.
Table 3. Selected mRNAs upregulated via FTO-mediated m6A demethylation.
mRNAFunctionReferences
RUNX1T1Promotion of adipogenesis, mitotic clonal expansion increasing adipocyte numbers[152,247]
PPARγPromotion of adipogenesis[248]
CEBPαPromotion of adipogenesis[248]
PGC1αPromotion of adipogenesis[249]
GhrelinIncreased ghrelin mRNA and protein expression, increased orexigenic signaling[228]
Dopamine receptor 2 and 3Increased dopaminergic signaling potentially involved in feeding reward[239]
Table 4. Selected target mRNAs of miRNA-148a.
Table 4. Selected target mRNAs of miRNA-148a.
TargetReported Biological Effects of miRNA-148aReferences
DNMT1Reduced maintenance DNA methylation during cell division [118,244]
DNMT3BReduced de novo DNA methylation[121]
ABCA1Reduced reverse cholesterol transport, risk of dyslipidemia[106]
LDLRReduced hepatic uptake of LDL, risk of dyslipidemia [106]
CPT1AReduced mitochondrial fatty acid β-oxidation, risk of dyslipidemia[106]
MIG6Reduced inhibition of EGFR, increased cell proliferation[278]
ROCK1Reduced suppression of myogenesis, enhanced myogenesis[261]
Table 5. Genes with increased DNA CpG demethylation-dependent expression.
Table 5. Genes with increased DNA CpG demethylation-dependent expression.
GeneFunctionsReferences
FTOIncreased RNA m6A demethylation, resulting in increased transcription, generation of adipogenic splice variant (short form) of RUNX1T1[152,154,155,156]
INSIncreased insulin expression, activation of mTORC1, increased glucose uptake, anabolism[170]
IGF1Increased IGF-1 expression, activation of mTORC1, promotion of growth and GH signaling[174,175]
CAV1Stimulation of insulin- and IGF-1 receptor signal transduction, promotion of adipocyte differentiation[179]
FABP4Adipogenic differentiation[243]
LPLAdipogenic differentiation[243]
NRF2Increased expression of mTOR, RagD, promotion of mTORC1 signaling, promotion of osteogenesis[162,163,164,165,166]
NR4A3Promotion of myogenesis and FoxP3 expression[201,202,207,253]
FOXP3Increased FoxP3 expression, differentiation and stable expression of regulatory T cells, induction of immune tolerance, prevention of allergy[183,184,185,186,187]
APOEDecreased isotype-specific APOE methylation in brains of patients with Alzheimer’s disease[372]
SNCADecreased methylation at SNCA intron 1 in patients with Parkinson’s disease[383,384]
Diseases EISSN 2079-9721 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top