Next Article in Journal
The Mitochondrial Genome of Linichthys laticeps (Cypriniformes: Cyprinidae): Characterization and Phylogeny
Next Article in Special Issue
Alternative Genetic Diagnoses in Axenfeld–Rieger Syndrome Spectrum
Previous Article in Journal
Genetic Diversity of Merozoite Surface Antigens in Global Babesia bovis Populations
Previous Article in Special Issue
Co-Occurrence of Germline Genomic Variants and Copy Number Variations in Hereditary Breast and Colorectal Cancer Patients
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

The Human Microbiome and Its Role in Musculoskeletal Disorders

1
Department of Orthopedic Surgery, Rush University Medical Center, Chicago, IL 60612, USA
2
International Spine Research and Innovation Initiative, Rush University Medical Center, Chicago, IL 60612, USA
3
Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China
4
Department of Microbial Pathogens and Immunity, Rush University Medical Center, Chicago, IL 60612, USA
5
Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA
6
Department of Twin Research, King’s College London, London WC2R 2LS, UK
*
Author to whom correspondence should be addressed.
Genes 2023, 14(10), 1937; https://doi.org/10.3390/genes14101937
Submission received: 18 September 2023 / Revised: 6 October 2023 / Accepted: 9 October 2023 / Published: 14 October 2023
(This article belongs to the Special Issue Feature Papers in Human Genomics and Genetic Diseases 2023)

Abstract

:
Musculoskeletal diseases (MSDs) are characterized as injuries and illnesses that affect the musculoskeletal system. MSDs affect every population worldwide and are associated with substantial global burden. Variations in the makeup of the gut microbiota may be related to chronic MSDs. There is growing interest in exploring potential connections between chronic MSDs and variations in the composition of gut microbiota. The human microbiota is a complex community consisting of viruses, archaea, bacteria, and eukaryotes, both inside and outside of the human body. These microorganisms play crucial roles in influencing human physiology, impacting metabolic and immunological systems in health and disease. Different body areas host specific types of microorganisms, with facultative anaerobes dominating the gastrointestinal tract (able to thrive with or without oxygen), while strict aerobes prevail in the nasal cavity, respiratory tract, and skin surfaces (requiring oxygen for development). Together with the immune system, these bacteria have coevolved throughout time, forming complex biological relationships. Changes in the microbial ecology of the gut may have a big impact on health and can help illnesses develop. These changes are frequently impacted by lifestyle choices and underlying medical disorders. The potential for safety, expenses, and efficacy of microbiota-based medicines, even with occasional delivery, has attracted interest. They are, therefore, a desirable candidate for treating MSDs that are chronic and that may have variable progression patterns. As such, the following is a narrative review to address the role of the human microbiome as it relates to MSDs.

1. Introduction

A collection of microorganisms, such as bacteria and fungi, that live on the surface of the host body or within is known as the human microbiota [1]. Microbial cells that inhabit the human body, including the mucosal and skin environments, outnumber our somatic cells and carry significantly more genes than our human genome [2]. The human body contains 500–1000 bacterial species at any given moment, although the number of unique genotypes (subspecies) may be larger in magnitude [3]. Millions of genes make up each bacterial strain’s genome, giving them much greater genetic variety and flexibility than the human genome. There is a large inter-individual variability in the composition of the microbiota. People can have vastly different collections of microorganisms, yet very little is known as to what governs such variability. Importantly, although it remains uncertain how intra- or inter-individual microbial diversity affects an individual’s well-being, health preservation, or disease inception and progression, changes in the microbiome and how it interacts with the gastrointestinal, nervous, immune, and endocrine systems are well recognized and are associated with a number of illnesses, including major depressive disorder, cancer, and inflammatory bowel disease [4,5].
The study of the human microbiome has now reached a key juncture. In the United States, the prevalence of many noncommunicable or chronic diseases has risen in recent decades, owing to longer lifespans and altered lifestyle (e.g., diet, activity levels, etc.). Changes in diet (e.g., fiber content, processed foods, etc.), sanitation (e.g., chlorinated water and filtered), and antibiotic use have significantly altered the gut’s microbial population in the United States during the last 100 years [6]. These findings have led to the premise that changes in the gut microbiota, secondary to lifestyle changes, are a significant factor associated with variations in the prevalence of different diseases over time [7,8,9]. Recent advances in sequencing technology have facilitated the conduction of systematic and comprehensive research on the human microbiome [10]. DNA-based taxonomy allows for identification of microbial communities at species level, whereas microbial metatranscriptomics and metagenomics can investigate the actively transcribed microbial genes and microbial genomes, respectively [11,12,13,14]. Direct and indirect crosstalk between the gut microbiota and the host immune system is now better understood as an adaptive evolutionary process between both microbial communities and mammalian species [15,16].
The efficacy of lifestyle treatments aimed at reducing the effects of aging on the musculoskeletal system or the onset of illness can be significantly influenced by the gut microbiota and their metabolites. Studies have noted that gut microbiota are associated and have implications with various musculoskeletal disorders (MSDs), such as osteoporosis [17,18,19,20], sarcopenia [21], osteoarthritis [22], and rheumatoid arthritis [15] (Table 1 and Table 2). MSDs are recognized as one of the most common workplace health concerns, significantly impacting working professionals’ quality of life [23].
Currently, little is known about the interplay between the human microbiome and MSDs. The current narrative review evaluates emerging data on the role of the human microbiome in relation to MSDs. To our knowledge, a singular and comprehensive review on the role of the microbiome upon MSDs has not, to date, been addressed. Risk factors between many musculoskeletal conditions tend to overlap, suggesting crosstalk of these mechanisms. This crosstalk provides cause and reason to believe that a review of the microbiome in relationship to MSDs in this depth and coverage is needed and would provide a starting point for discussion and future research. This review is targeted to clinicians (e.g., orthopaedists, rheumatologists, physiatrists, physical therapists, etc.) and basic science researchers interested in the topic of microbiome and MSDs.

2. Human Microbiome

Microbiota is a term used to describe the microorganisms that live in a certain environment [38], while the “microbiome” is a collection of genomes from those microorganisms. The human microbiota is composed of approximately 10 to 100 trillion symbiotic microbial cells residing within each person, predominantly bacteria in the gut. The human microbiome is made up of the genes that comprise the genetic material of such microbial cells [39]. Multiple microbiome projects have been developed globally to better understand the roles of these symbiotic microorganisms and their effects on human health [40,41]. The study of the human microbiome has now reached a key juncture. The field is moving away from descriptive analyses and towards mechanistic and interventional studies [42]. These developments have also sparked a boom in translational research and significant expenditures in both academic and corporate research, including that of so-called “big pharma”. A revolution in customized medicine has sparked this organized endeavour in clinical microbiome research. Cancer genome sequencing is one instance of customized medicine since it enables quick identification of a patient’s unique treatment plan that will provide beneficial results. Our ability to define the microbiome quickly and consistently may provide a platform for the development of new diagnostic biomarkers and non-invasive treatments as well as refined predictive outcome modeling of patient care [43].

3. Microbiome in Health and Disease

Since the inception of the study of the human microbiome back in the 17th century, its potential significance in health and disease has gained attention in the scientific community, yet there is still so much to explore. The current cutting-edge sequencing methods allow for the investigation of microbiota composition and its potential impact on the human body. Over 100 trillion prokaryotic cells have been found to support human biological activities. Each individual is carrying 3 to 6 pounds of bacteria and other microbes at all times, with approximately 3 million protein-coding genes [44]. There are various microbial niches that are in harmony with the normal physiologic processes of the human body [45]. The host’s homeostasis is significantly influenced by the gut microbiota. [46]. Human physiology, fat storage, immune system development, behavior, digestion, angiogenesis regulation, detoxification, and development processes all depend on the gut microbiome [47,48]. Enzymes essential for the breakdown of otherwise indigestible food components and the production of vitamins are encoded by some microbes in the gut microbiome [49,50]. Actinobacteria, Firmicutes and Bacteroidetes are the most prevalent microbiota phyla in a healthy gut, while Verrucomicrobia, Proteobacteria, Fusobacteria, and Cyanobacteria are frequently absent [41,51]. There have also been reports of Eucarya (mostly yeasts), methanogenic archaea (particularly Methanobrevibacter smithii) and numerous phages in a healthful gut microbiome [52].
Multiple factors can affect the microbiota. While the microbiota content varies greatly from one individual to the next [41], the microbiota is a highly dynamic ecosystem that can be altered by a variety of circumstances, such as pharmaceutical treatments, illness [53], age, travel [54], hormonal cycles [55] and diet [56]. Furthermore, according to He et al. [57] microbial patterns vary across geographical regions. Within the same geographical region, ethnicity plays the largest role in explaining inter-individual differences in microbiome composition [58]. The gut microbiota can have a major impact on health and become disrupted during certain pathological conditions. Environmental factors can also disrupt gut microbial communities in genetically vulnerable individuals, resulting in dysregulation of the host’s innate and adaptive immune systems, resulting in the emergence of different illnesses [45]. The interplay between the immune system and the altered gut microbiota has been shown to affect the etiology of various diseases in recent years, including cancer, inflammatory bowel syndrome, metabolic syndrome and nonalcoholic fatty liver disease [59,60,61,62,63] and many autoimmune diseases (e.g., rheumatoid arthritis, multiple sclerosis, autoimmune hepatitis, spondyloarthritis and type 1 diabetes) [64,65,66,67,68,69]. The gut microbiota is highly organized, and it has a wide range of protective, structural, metabolic, and immunological effects both within the gut and across the body [70]. Metabolites contributed by gut microbiota and their respective functions are illustrated in Table 3.
Many gut microbiota metabolite end-products have critical roles in immunological processes, host metabolic balance and neurology, highlighting the extended genome’s basic involvement in human disease [71]. The most compelling representations of the role of gut bacterial metabolites in cardiometabolic illnesses come from comprehensive studies of choline and methylamine metabolism in humans and animal models [72]. Bile acids are steroid molecules that are generated in the liver from cholesterol and then processed by the gut microbiota into secondary bile acids [71].
Table 3. Metabolites by the gut microbiota and their respective functions. Adapted from Kho and Lal [73].
Table 3. Metabolites by the gut microbiota and their respective functions. Adapted from Kho and Lal [73].
MetabolitesFunctions
Polyamines,
e.g., putrescine, spermidine, and spermine [74,75,76,77,78]
  • Maintain a high rate of intestinal epithelial cell proliferation.
  • Dysregulated polyamine metabolism may promote the growth of cancer.
  • Promote the production of intercellular junction proteins (occludin, zonula occludens-1 (ZO-1), and E-cadherin) to improve intestinal barrier integrity and function.
  • Spermine suppresses pro-inflammatory M1 macrophage activation and promotes intestinal and systemic adaptive immune system development.
Vitamins,
e.g., thiamine (B1), riboflavin (B2), pantothenic acid (B5), niacin (B3), pyridoxine (B6), folate (B11–B9) biotin (B7), cobalamin (B12), and menaquinone (K2) [79,80]
  • The creation of red blood cells, the generation of energy, and the role of cofactors in many metabolic processes.
  • DNA methylation, repair, and replication, which controls cell division.
  • The creation of vitamins, amino acids, and nucleotides. Enhance immune functioning.
Phenolic derivatives,
e.g., 4-OH phenyl acetic acid, equol, urolithins, enterolactone, enterodiol, 8-prenylnaringenin, 2-(3,4-dihydroxyphenyl) acetic acid, 3-(4-hydroxyphenyl) propionic acid, and 5-(3,4-dihydroxyphenyl) valeric acid [81,82,83]
  • Antimicrobial effects: suppressing harmful bacteria, affecting the makeup of the gut microbiota, and maintaining intestinal health.
  • Protective effect against oxidative stress.
  • Estrogen-modulating effect. λ platelet aggregation inhibition effect.
  • The anti-inflammatory and cancer-prevention properties of urolithin are present.
Choline metabolites,
e.g., betaine and choline, and trimethylamine N-oxide (TMAO) [84,85]
  • Alter glucose homeostasis and lipid metabolism.
  • Cause cardiovascular disease and non-alcoholic fatty liver disease.
Bile acid metabolites, e.g., lithocholic acid (LCA) and deoxycholic acid (DCA) [86]
  • Exhibit antimicrobial activities.
  • Activate host nuclear receptors and cell signaling pathways; regulate bile acid, cholesterol, glucose, lipid, and energy metabolism.
Indole derivatives, e.g., indole, indoxyl sulfate, and indole-3-propionic acid (IPA) [87,88,89]
  • IPA functions as a potent antioxidant, a blocker of amyloid-beta fibril production, and a cytoprotective agent against a range of oxidants.
  • Pregnane X receptor (PXR), a xenobiotic sensor, is how IPA controls the intestinal barrier function. Through the PXR, IPA lowers intestinal inflammation (by downregulating the pro-inflammatory cytokines TNF-) and regulates intestinal permeability and mucosal integrity (by upregulating junctional protein-coding mRNAs).
  • The uremic toxin indoxyl sulfate, which builds up in the blood of people with compromised excretion systems.
Short-chain fatty acids (SCFAs), e.g., acetate, butyrate, propionate, hexanoate, and valerate [89,90,91]
  • Control host metabolic pathways by signaling from G-protein-coupled receptors GPR41 or GPR43: energy homeostasis; glucagon-like peptide 1 (GLP-1) synthesis; upregulation of leptin production. Improve insulin sensitivity and glucose tolerance. Strong histone deacetylase (HDAC) inhibitor controls the proliferation of intestinal cells. Intestinal gluconeogenesis, lipogenesis, and inhibition of fasting-induced adipose tissue in the intestinal epithelium (factor FIAF). Immunomodulatory impact, dendritic cell activation, and gut immunity.

4. Microbiome and Musculoskeletal Development

An aberrant or malfunctioning microbiota has been linked to a variety of illnesses and problems not related to the gut. There is growing evidence that altered gut microbiome is highly related to certain MSDs. Changes in the microbiota provide plausible potential mechanisms for generating inflammation, modifying the immune response, and affecting host metabolism, all of which may modulate the development of MSDs and frailty. Studies in this field are challenging to carry out and require thorough planning to eliminate confounding variables such host genetics, nutrition, age, and the sickness itself, all of which alter the composition of the gut microbiome [92]. When compared to adults, children have dramatically different gut flora [93]. Despite the fact that fewer bacterial species dominate the infant’s gut microbiota, a variety of variables have a role in its growth throughout the first year of life [94].

5. Gut Microbiota and Bone Health

Over the last two decades, inflammatory bowel diseases have been associated with a loss of bone mass, implying that the intestinal and skeletal systems are linked. Recently, it was shown that the microbiomes of people with osteoporosis were much more varied than those of healthy controls, particularly in terms of Firmicutes abundance [17]. In a study postmenopausal woman with osteoporosis and osteopenia were shown to have altered microbiome [30]. Furthermore, a clinical trial demonstrated that replenishing the microbiota with probiotic medication reduced bone loss in older people with low bone mineral density [95]. Conversely, a recent study showed that probiotics reduced femoral neck bone mineral density, but hip bone mineral density was unaffected [18].
Mice’s osteocalcin and bone strength have decreased owing to antibiotic-induced microbiota depletion, which has been related to decreased vitamin K2 levels [32]. Given the connection between the stomach and the bones, the medical world has recently become interested in probiotics, which reintroduce beneficial bacteria strains. Probiotics like the bacterial strain Lactobacillus rhamnosus GG and VSL#3, have been shown to improve bone health by repairing intestinal permeability and restoring the gut microbiota in animal research [34]. In estrogen-deficient mice, Lactobacillus reuteri was demonstrated to protect against bone loss when given as a supplement [96,97].
Disruption of gut homeostasis can induce an inflammatory immunological phenotype that affects bone metabolism. Increases in TH17 cells that release the interleukin IL-17 in the bone marrow (BM) can promote bone breakdown by facilitating the differentiation of osteoclasts (OCs) in the BM [98,99]. Yu et al. [100] examined how intestinal immune cells affected bone remodeling in hyperparathyroid mouse models. They discovered that parathyroid hormones enhanced the number of gut TH17 cells in mice with segmented filamentous bacteria in their microbiomes. These TH17 cells moved into the BM after egressing from the stomach and into circulation, causing bone degradation [100]. To demonstrate intestinal TH17 cell egress, they used an FTY720 antagonist to block the sphingosine 1 phosphate (S1P) receptor-1, which limits lymphocyte egress from the mesenteric lymph nodes, resulting in a BM TH17 cells decrease and bone loss [100]. They also found that the chemoattractant CCL20, which guides TH17 cells into the BM, was elevated in the BM, demonstrating the relevance of TH17 cell migration into the BM [100]. Although the quantity of intestinal TH17 cells was unaffected by the administration of neutralizing anti-CCL20 antibody, it prevented the decreases in bone loss and the increase in TH17 cells in the BM.

6. Osteoporosis

An increase in the risk of bone fracture is associated with osteoporosis, which is defined by a decline in bone strength, a measure of bone density and quality [101]. Increased inflammatory markers in plasma, such as high-sensitivity C-reactive protein (CRP), increase bone resorption, bone loss and may increased risk of fracture [102,103,104,105]. Osteoclasts, which are produced from hematopoietic stem cells, are highly specialized motile migratory bone resorptive cells. Because osteoclasts are the most important bone resorbing cells, local activation of their activity is required to prevent alveolar bone loss [106]. Mineral bioavailability from the diet is influenced by probiotics. Human studies have found that adolescents and postmenopausal women benefit from probiotics because they boost calcium absorption [107,108]. Compared to those who took placebo pills, adolescents who were given a mix of inulin-type fructans with short and long chains demonstrated considerable increase in bone density and mineral content throughout the body in the bone [109]. The flora of the distal colon ferments fructans in the intestinal tract rather than having them degraded by enzymes in the small intestine. A substance that favorably affects mineral absorption is fructans. Fructans have been found to improve the absorption of a number of minerals, including calcium and iron. [110]. Alterations in calcium absorption, according to the authors, were most likely to blame; however, changes in gut microbiota composition and immune response could also have played a role [111,112]. In adolescent girls, the administration of galacto-oligosaccharides (GOS) on calcium absorption and the intestinal microbiota was studied [112]. In a dose-dependent manner, beneficial fecal bifidobacteria numbers increased considerably. Calcium absorption increased as well, although no direct relationship with dose was observed. A different study found enhanced calcium absorption and an increase in microbiota in teenagers who consumed a soluble maize fiber diet compared to similar controls who ate normal diet; however, no changes in indicators of bone turnover were observed. These results suggest that among adolescents who eat less calcium than is advised, a moderate daily dosage of SCF, a well-tolerated prebiotic fiber, enhances short-term Ca absorption [113].

7. Rheumatoid Arthritis

The autoimmune disease rheumatoid arthritis (RA) affects the synovium and cartilage and is commonly accompanied with bone erosions. The prevalence of RA is rising, as is the age at which it first appears, partly due to population ageing [97,98]. Despite shorter symptomatology at presentation, older patients frequently have greater disease severity [114]. However, the reasons for this phenomenon have not been elucidated. Intestinal microbiota components [115] affect the host immunity, especially the effector T-cell development, which may influence autoimmune disease susceptibility, such as RA [116]. The gut microbiota is also known to alter with age [117]. Seropositive RA is characterized by antibodies against citrullinated proteins (ACPAs), which have been found to be harmful. According to the CIA model, Porphyromonas can hasten the course of RA in animals [118,119]. Genetic changes in the microbiota may help mitigate genetic risk [31,120]. Prevotella spp were shown to relate to the RA genotype in absence of RA, including people with high risk factor of having RA [120]. Autoantigenic citrullinated peptides secreted by oral microbiome were demonstrated to be elevated in RA patients [121]. However, in adjuvant-induced arthritis in rats, L. casei (ATCC334) bacteria was shown to restore bone loss indicating this to be a potential candidate for probiotics for treating RA [122].

8. Sarcopenia

A broad, progressive skeletal muscle condition known as sarcopenia causes loss of muscular mass and function [123]. It occurs with advancing age, and causes decreased strength, eventually leading to physical decline, incapability to carry out daily tasks, loss of independence, higher risk of falls, and an increased chance of death [124]. Sarcopenia makes recovering from bone and joint diseases more difficult, including orthopaedic surgery. Various medical conditions (e.g., cancer, malnutrition, chronic infection, and chronic heart failure) can cause muscle wasting. Inflammation and a poor nutritional state are also believed to be shared mechanisms [125]. Higher blood interleukin-6 (IL-6) and CRP levels were observed to enhance the likelihood of muscular strength loss over a 3-year period in a prospective investigation involving over 1000 participants [126].
In sarcopenic obesity, the microbiome may also play a role [127]. Increased adiposity, fat redistribution, persistent muscle fat infiltration and low-grade inflammation are all symptoms of this sarcopenia type, which has no universal diagnostic criteria [128]. The function of the gut microbiota in obesity has been studied extensively [127]. When compared to normal-weight and age-matched controls, overweight individuals have a less diverse microbiome, which could contribute to weight gain and increased inflammation in muscle [128]. Based on a study by Kang et al. [127] whereby 60 healthy and 27 sarcopenic individuals were compared, 16S rRNA sequencing data of fecal microbiota revealed reduction in microbial diversity for those with sarcopenia. More specifically, the study noted an increased abundance of Lactobacillus but a decreased abundance of Fusicantenibacter, Lachnospira, Eubacterium, Roseburia, and Lachnoclostridium in sarcopenic subjects.

9. Osteoarthritis

The classic view of osteoarthritis was that it was a non-inflammatory arthropathy characterized by cartilage and bone remodeling. On the other hand, several studies have consistently demonstrated inflammation throughout the whole illness phase [129,130]. Streptococcus species within the gastrointestinal microbiome has shown to trigger endotoxin release leading to local inflammation in the knee joint with resulting pain [131]. Indeed, the synovium and chondrocytes create chemokines, cytokines and other inflammatory mediators have been detected in the synovial fluid of OA joints [129,130]. Furthermore, bacterial DNA has been found in the synovial fluid and synovial tissue of OA joints from polymerase chain reaction (PCR) tests, suggesting the potential that living bacteria are present in the joint as the illness progresses [127,132,133]. Investigations employing sequence-based microbiota assays are essential since a significant portion of gut bacteria is currently unculturable. For 12 weeks, participants in these earlier research received either 3000 mg/day of an oral glucosamine sulphate (GS) supplement or 3000 mg/day of a whole green-lipped mussel (GLM) extract. However, since these tests are digested in the colon by gut bacteria, considerable disagreement existed concerning their efficacy. The discrepancy could be due to differences in baseline microbiota between studies and individuals [22].

10. Intervertebral Disc Degeneration

Disc degeneration (DD), which causes low back pain, is the most disabling ailment in the world and well known potential risk factor [134,135,136,137,138,139]. Inflammation has been identified as the final common pathway leading to DD, but the mechanisms that cause it remain unknown [28,140]. Although environmental, genetic, and mechanical factors have all been implicated, subclinical infection and bacteria-induced inflammation are of particular interest [26,141,142,143,144]. Bacterial presence has been found in DD, but it has been suggested that it could be contamination rather than infection [25,29]. The existence of a unique disc biome in human intervertebral discs and disc dysbiosis in degenerative discs have been shown utilizing advanced omics technologies [27,145]. A comparative analysis of gut microbiota in 36 obese or overweight individuals with or without back pain have revealed direct correlation with altered gut microbiota and back pain, which may be attributed to increased inflammation [146]. More specifically, genera Adlercreutzia, Roseburia, Uncl. Christensenellaceae were observed abundantly in obese or overweight individuals with back pain. However, treating a mouse model for lumbar disc herniation with Lactobacillus paracasei S16 has been shown to reduce the inflammatory response [36]. Such an approach has also altered the gut microbiota and serum metabolites. Further research is required to examine the interactions between bacterial inflammation and dysbiosis and their role in DD in the setting of pain and non-painful states, potentially opening the possibility for new avenues of understanding the pathomechanisms of symptomatic degenerated discs, the development of more targeted novel treatments and more refined predictive outcomes.

11. Modic Changes

Modic changes (MC) are subchondral vertebral bone marrow non-neoplastic lesions observed on magnetic resonance imaging (MRI) [136,147,148,149,150]. These lesions involve both the vertebrae and the endplate of the adjacent disc and are related to DD. MC (especially MC type 1 [MC-1]) is thought to be related to low back pain (LBP) [151,152,153]. The prevalence of MC increases with age [136,154]; however, such lesions are more common among individuals with lumbar disc herniation and chronic LBP (approximately 45%) as compared to the general population (around 5% [155,156]). There are three types of MCs, which are determined based on T1- and T2-weighted MRIs. The MC-1 indicates inflammatory changes or edema in the vertebral bone marrow; MC-2 represents the replacement of normal haemopoietic bone marrow by yellow lipid marrow; and MC-3 indicates subchondral bone sclerosis and has low prevalence. Of the three types of MCs, MC-1 is associated with a higher prevalence of chronic LBP [157,158]. Although multiple factors (e.g., biomechanical changes or degeneration) have been proposed to be related to the development of MCs, some animal and human studies indicated that MCs might be attributed to low-virulent intra-discal infection [141,142,159,160,161]. For instance, Chen et al. [162] showed that the inoculation of human-derived Propionibacterium acnes into the L5, L6, and L7 intervertebral discs of rabbits caused gradual disc degeneration, adjacent endplate disruption, and MC. Although the mechanisms underlying P. acnes inducing MC are uncertain, it has been hypothesized that P. acnes secreted propionic acid may dissolve fatty bone marrow and may result in MC. It has also been hypothesized that the presence of P. acnes induces monocytes to create pro-inflammatory cytokines (such TNF- and IL-1) [162]. that are responsible for edema of subchondral bone marrow and potential damage of the endplates [163].
Human randomized controlled trials were conducted to evaluate the use of 90 or 100 days of Amoxicillin-clavulanate or Amoxicillin alone in improving the symptoms or MC in patients with chronic LBP and concomitant MC [162,164,165,166]. They found that antibiotics were significantly more effective than placebo in improving pain or disability immediately after the treatment or at the one-year follow-up in patients with MC-1. However, there were inconsistent findings regarding the clinical significance of these findings. Nonetheless, these studies underscore that perhaps bacterial infection may be related to spine health and that more targeted, precision-based and imaging approaches with respect to various structural spine phenotypes are needed.

12. Scoliosis

Scoliosis is the most common rotational malformation of the spine, affecting about 1 to 4 percent of adolescents worldwide [167]. Cardiovascular risk, respiratory failure and death are associated with severe scoliosis [168]. The etiology of scoliosis remains uncertain but is believed to be multifactorial [167]. For example, central nervous system difficulties, genetic factors, skeletal spinal growth, bone metabolism abnormalities, metabolic pathways, biomechanics, proprioceptive deficits, and other factors have all been postulated as possible explanations for its pathophysiology [169,170]. Clinical symptoms and pathological abnormalities of scoliosis suggest that metabolic dysfunction and biochemical variables may be involved in its development [171,172,173]. Recent research reveals that the gut microbiota plays a significant role in regulating metabolic and biochemical processes that support bone production and skeletal development [37,174]. Recent observations in the distinct gut microbiota profiles in patients with scoliosis as compared to non-scoliotic controls have led to the development of a novel hypothesis [175]. Specifically, the changes in plasma proteins and the amount of fecal Prevotella were found to be positively associated with the Cobb angles of patients with scoliosis [175]. However, there is insufficient evidence to substantiate the direct involvement of gut microbiome on the onset or progression of scoliosis. Future research should investigate the gut microbiota profiles of patients with rapid progressive scoliosis to improve our understanding regarding the pathophysiology or progression of scoliosis.

13. Microbiome and Inflammatory Conditions

13.1. Septic Arthritis

Most commonly, Neisseria gonorrhoeae and Staphylococcus aureus (S. aureus) cause septic arthritis in individuals of all ages [176,177,178]. The most common cause of bloodstream infections globally is S. aureus [179]. However, due to a continuous extension from a nearby soft tissue infection, S. aureus can also result in septic arthritis. After minor trauma or in medical settings when a central venous catheter or peripheral intravenous device is used, bloodstream infections brought on by S. aureus are frequent [180]. Numerous virulence traits of S. aureus enable it to penetrate the joint space and evade human defenses, leading to symptomatic infection. These include protein A, collagen-binding protein, clumping factors A and B, and bone sialoprotein-binding protein, which all have similar mechanisms of action involving extracellular matrix adhesion and cause osteomyelitis and septic arthritis [181]. S. aureus, however, is regarded as a human commensal since up to 30% of asymptomatic individuals have it in their noses. Methicillin-resistant S. aureus (MRSA) septic arthritis is a prominent subgroup of S. aureus septic arthritis [182]. According to a systematic analysis, children under the age of two and African Americans are more commonly affected by CA-MRSA bone and joint infections [183]. Although the causes are unknown, they could have something to do with access to care or unusual presentations of bone and joint infections in very young infants [174]. A patient with septic arthritis of the hip or knee who worked in a medical facility was more likely to get MRSA than methicillin-sensitive S. aureus, according to studies [184].

13.2. Osteomyelitis

Osteomyelitis is a type of bone inflammation and infection. When a bacterial or fungal infection enters bone through the circulation or surrounding tissue, it is known as osteomyelitis. Osteomyelitis can appear suddenly or gradually [185]. In the United States, it is estimated that 2 to 5 per 10,000 persons have osteomyelitis regardless of age [186]. Children are more likely to get long bone infections involving the arms or legs. However, older persons are more likely to develop osteomyelitis [187,188]; however, anyone at any age can get it because they have more health problems that raise the risk of infection, such as diabetes, lower immunity or orthopaedic problems that necessitate surgery. Osteomyelitis can be “hematogenous”, meaning it originated from the bloodstream to the bone, or “non-hematogenous”, meaning it is not transmitted from the bloodstream [189]. If bacteria enter the body through intravenous therapy, it is more likely to develop hematogenous osteomyelitis, especially in children. Trauma, such as a fracture or an open wound, can cause non-hematogenous osteomyelitis, which is the most common cause of non-hematogenous osteomyelitis in children. Surgical procedures (especially those involving prosthetic materials like metal pins, screws, or plates, which can harbor fungi or bacteria) may increase the risk of osteomyelitis [190]. Although the study of the role of the microbiome in the development of osteomyelitis is currently in its infancy, recent research has established early foundations as it relates to bone health of the foot, jaw and other regions related to MSDs [191,192].

13.3. Post-Operative Infection

Surgical site infection (SSI) and periprosthetic joint infection are major problems following orthopedic surgery. SSI have been reported to occur in 1.4 to 5.5% of cases following ankle surgery, and 0.7 to 12% of cases following spine surgery [193]. Because of the high morbidity and mortality associated with SSI, prevention is a main area of focus. Multiple risk factors, such as smoking, open fracture, obesity, alcohol abuse, and diabetes, have been identified; however, evidence suggests the carriage of S. aureus, a bacterial strain that is part of the normal microflora commonly found in the anterior section of the nostrils, could play a role [194]. A clinical investigation comparing over 1000 patients prophylactically treated with mupirocin to a historical control found that it might lower the infection rate in orthopedic surgery [195]. In a cohort of 18 patients who got SSI after orthopedic surgery, another clinical investigation discovered that high nasal carriage of S. aureus was the only substantial independent risk factor for developing S. aureus-related SSI [196,197]. However, their later randomized, double-blind, placebo-controlled experiment discovered that using Mupirocin nasal ointment did not shorten hospital stays or SSI caused by S. aureus. The gut microbiota may be involved in periprosthetic joint infection, according to animal studies. For instance, in mice, a higher percentage of those treated with oral antibiotics for disturbed gut flora developed periprosthetic joint infection [33]. The scientists hypothesized that the mice with altered gut microbiota had a suppressed immunological response to the illness. It is necessary to do further animal and clinical research to determine how the gut microbiome’s health affects the emergence of periprosthetic joint infection and SSI.

13.4. Discitis

Discitis is a bacterial infection of the intervertebral disc resulting from direct injection or hematogenous seeding. Identification of a causal pathogen, when possible, is crucial for guiding the therapy protocols [198,199]. Although polymicrobial infection can occur, most cases involve a single pathogen [200]. S. aureus is the most common isolated pyogenic pathogen [201,202,203,204]. The MRSA infection rate ranges from 10 to 40%, notably in nosocomial acquired isolates [202,205,206]. Coagulase-negative staphylococci, such as S. epidermidis (5 to 29%), and Streptococcus genus, have also been noted (5 to 20%) [202,205,207]. Escherichia coli (7 to 33%) is the most often grown gram-negative bacillus, which is commonly seen in immunocompromised patients [208], followed by Pseudomonas (4 to 12%) [205,207,209]. In IV drug abusers, the most common bacteria are Pseudomonas species, S. aureus, and S. epidermidis. Patients with infected endocarditis are likely to be caused by S. viridans and Group D streptococci.

13.5. Ankylosing Spondylitis

Ankylosing spondylitis (AS) is a chronic inflammatory, autoimmune condition with a complicated pathophysiology involving specific genetic markers and distinct environmental triggers, such as gut dysbiosis [24]. Metagenomic profiling of these microbiota clearly shows microbiota perturbation and AS-enriched species are shown to trigger autoimmunity due to molecular mimicry [210]. The interaction between the antigen HLA-B27 and bacterial cells, for example, can result in HLA-B27 misfolding within the endoplasmic reticulum within the bacteria leading to inactive proteins [211,212]. The production of pro-inflammatory mediators, as well as the phenomenon of autophagy, are both caused by this unfolded response [213]. Furthermore, since there is a biochemical similarity between HLA-B27-presented bacterial peptides and different self-peptides, it could lead to a cross-immune responses [211,214]. Furthermore, according to Chen et al. [215], the gut microbiota is restored in AS patients after adalimumab treatment, and this gut microbiome functions as possible biomarkers to assess the therapeutic medication.

13.6. Fibromyalgia and Chronic Pain

Fibromyalgia is a chronic widespread pain with both somatic and psychological symptoms [216]. Although the causes of fibromyalgia are unclear, oxidative stress, neuroinflammation, proteomics, genetics, hormonal changes, and various types of bacterial infections have been suggested to be related to fibromyalgia [217,218,219]. It is known that fibromyalgia is closely related to irritable bowel syndrome through shared genetic factors [220]. Furthermore, Marc et al. [221], revealed that people with fibromyalgia had less diversity of fecal microbes than age-matched healthy controls. A recent systematic review by Wang et al. [222] found that the composition and metabolism of gastrointestinal microbiota were associated with fibromyalgia. However, it should be noted that potential confounders may exist, such as use of drugs (e.g., non-steroidal anti-inflammatory drugs [NSAIDs]) that may affect intestinal permeability in the included studies, that may complicate the interpretation of results. Collectively, given the potential association between fibromyalgia and gut microbiota and the paucity of relevant research, future prospective studies should adopt novel technology and standardized procedures, as well as address the limitations of prior studies in order to determine the causal relation between gut health and fibromyalgia.
Although multiple factors will affect the development or maintenance of chronic pain, it is not uncommon for patients with musculoskeletal pain to take high-dose paracetamol (>2 g per day) or NSAIDs [223]. These medications can adversely affect the gastrointestinal environment and physiology, which may lead to gut dysbiosis (i.e. bacterial imbalance). Gut dysbiosis heightens the permeability of enterocyte to bacterial endotoxins, resulting in gastrointestinal dysfunction (leaky gut) [70]. Gastrointestinal microbiota can affect the mucosal defense mechanisms (i.e., competing for mucosal colonization and metabolic substrates for the synthesis of regulatory factors) and immune system of the host. The gastrointestinal tract is constantly subjected to both internal and external challenges that can interfere the intestinal homeostasis. Toxins from adverse bacterial activity or diet, gut dysbiosis following medications or infections can disrupt the enterocyte’s barrier function, causing translocation of toxins or bacteria-derived gene products (e.g., lipopolysaccharides) across the inflamed, permeable epithelia and resulting in systemic inflammation and endotoxaemia [224]. Prolonged pro-inflammatory responses in the extra-intestinal environment will increase the risk of chronic inflammation and body pain. If this problem is not addressed timely, it may lead to chronic pain.

14. Potential Therapeutics Related to the Microbiome

The metabolism of several drugs often used to treat musculoskeletal disorders is mostly regulated by the microbes in the gut, which has emerged as a hub for the development of novel therapeutics. First, the gut microbiome has an impact on popular analgesic drugs, which are still a mainstay of symptomatic treatment [225]. Furthermore, because p-Cresol is a tyrosine metabolite, dietary tyrosine alteration may further increase paracetamol toxicity. Second, the bacterially produced enzyme b-glucuronidase influences the stomach and intestinal toxicity of NSAIDs. Inhibitors of this bacterial enzyme decreased the number of NSAID-induced ulcers in mice [225].
Since this system’s alteration might have significant effects, especially in older people who are more susceptible to gastrointestinal bleeding, human trials proving this adjustment are urgently needed. For example, evidence from clinical trials investigating the use of epimedium-derived phytoestrogen flavonoids (EPFs) to support bone health noted a significant decrease in bone mineral density loss in late postmenopausal females in comparison to placebo participants [226]. The trial’s authors made a concentrated effort to standardize the diets of the volunteers, which may have lessened variation in the patients’ microbiota. Rats’ gut microorganisms substantially metabolize epimedii, hence the effectiveness may vary depending on the host microbiota [227]. A more recent Chinese multicenter trial indicated a significant effect after just 6 months, however the diet was not consistent throughout the study [228]. More study is required to determine if this medication is effective when used with a Western host microbiome and diet. Though this will only have an impact on therapy if absorption is postponed until the colon, in vitro models have demonstrated that some drugs used to treat bone and joint problems are digested by the gut flora. Some drugs, such the osteoporosis treatment strontium, are affected by food, especially alginates [229], which are subsequently digested by specialized bacteria, resulting in a complex interaction between the host-specific diet, medication, and microbiota profile. The severe bisphosphonate side effect of osteonecrosis of the jaw has been linked to changes in the oral microbiota in early epidemiological studies, but new data suggests that the connection is not causative but rather reflects changes in systemic immunity [230].

15. Future Directions

The next critical stages in comprehending the function of the microbiome are preclinical investigations that more precisely pinpoint the mechanisms linking the microbiome to the health of musculoskeletal tissues. Future clinical studies should examine the potential efficacy of microbiome-based therapies for various MSDs, and measure gut microbiota in these patient populations. Once a more complete understanding of the mechanisms relating the gut microbiome to musculoskeletal tissues is attained, appropriate microbiome-based interventions, such as fecal microbiota transplantation or and prebiotics, can be determined for various patients. In addition, with the evolving understanding of deep analytics and artificial intelligence solutions as well as integrative and multi-omics approaches, a deeper understanding of an individual’s microbiome profile may be possible and lend to more personalized patient care approaches. In fact, such platforms can further contribute to novel preventative measures, unique diagnostics, and informative predictive modeling as they pertain to MSD.

16. Conclusions

The gut microbiome is now widely acknowledged in the scientific community as a contributor to the onset of illness and a prospective target for therapeutic treatments and prognostic prediction. Despite being well acknowledged in other medical fields, the gut microbiome has only just begun to be recognized as a factor in musculoskeletal health. With the explosion of deep phenotyping and analytics, and the understanding of the integration of various omics approaches, the microbiome is an emerging research area that may lead to a paradigm shift in the spectrum of personalized care for patients with different MSDs. As such, this will ultimately improve patient care, decrease healthcare costs and lead to a more productive society.

Author Contributions

D.S. conceived the study, provided administrative support, and supervised the project. K.A. provided the initial draft. All authors contributed to the literature review, writing, and editing of the paper. All authors have read and agreed to the published version of the manuscript.

Funding

National Institutes of Health, National Institute of Arthritis and Musculoskeletal and Skin Diseases, Grant # R21AR079679; and The Thomas J. Coogan, Chair of Immunology Endowment (LA).

Institutional Review Board Statement

Institutional Review Board approval was not needed for this broad narrative review.

Informed Consent Statement

Informed consent was not required.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors have no financial or competing interest to disclose in relation to this work.

References

  1. Arumugam, M.; Raes, J.; Pelletier, E.; Le Paslier, D.; Yamada, T.; Mende, D.R.; Fernandes, G.R.; Tap, J.; Bruls, T.; Batto, J.M.; et al. Enterotypes of the human gut microbiome. Nature 2011, 473, 174–180. [Google Scholar] [CrossRef]
  2. Sender, R.; Fuchs, S.; Milo, R. Are We Really Vastly Outnumbered? Revisiting the Ratio of Bacterial to Host Cells in Humans. Cell 2016, 164, 337–340. [Google Scholar] [CrossRef]
  3. Locey, K.J.; Lennon, J.T. Scaling laws predict global microbial diversity. Proc. Natl. Acad. Sci. USA 2016, 113, 5970–5975. [Google Scholar] [CrossRef]
  4. Wang, B.; Yao, M.; Lv, L.; Ling, Z.; Li, L. The Human Microbiota in Health and Disease. Engineering 2017, 3, 71–82. [Google Scholar] [CrossRef]
  5. Zheng, P.; Zeng, B.; Zhou, C.; Liu, M.; Fang, Z.; Xu, X.; Zeng, L.; Chen, J.; Fan, S.; Du, X.; et al. Gut microbiome remodeling induces depressive-like behaviors through a pathway mediated by the host’s metabolism. Mol. Psychiatry 2016, 21, 786–796. [Google Scholar] [CrossRef]
  6. Conlon, M.A.; Bird, A.R. The impact of diet and lifestyle on gut microbiota and human health. Nutrients 2014, 7, 17–44. [Google Scholar] [CrossRef]
  7. Sonnenburg, E.D.; Sonnenburg, J.L. The ancestral and industrialized gut microbiota and implications for human health. Nat. Rev. Microbiol. 2019, 17, 383–390. [Google Scholar] [CrossRef]
  8. Blaser, M.J. Antibiotic use and its consequences for the normal microbiome. Science 2016, 352, 544–545. [Google Scholar] [CrossRef]
  9. Bello, M.G.D.; Knight, R.; Gilbert, J.A.; Blaser, M.J. Preserving microbial diversity. Science 2018, 362, 33–34. [Google Scholar] [CrossRef]
  10. Costello, M.E.; Robinson, P.C.; Benham, H.; Brown, M.A. The intestinal microbiome in human disease and how it relates to arthritis and spondyloarthritis. Best Pract. Res. Clin. Rheumatol. 2015, 29, 202–212. [Google Scholar] [CrossRef]
  11. Goodrich, J.K.; Di Rienzi, S.C.; Poole, A.C.; Koren, O.; Walters, W.A.; Caporaso, J.G.; Knight, R.; Ley, R.E. Conducting a microbiome study. Cell 2014, 158, 250–262. [Google Scholar] [CrossRef]
  12. Sharpton, T.J. An introduction to the analysis of shotgun metagenomic data. Front. Plant Sci. 2014, 5, 209. [Google Scholar] [CrossRef]
  13. Hiergeist, A.; Gläsner, J.; Reischl, U.; Gessner, A. Analyses of Intestinal Microbiota: Culture versus Sequencing. ILAR J. 2015, 56, 228–240. [Google Scholar] [CrossRef]
  14. Coit, P.; Sawalha, A.H. The human microbiome in rheumatic autoimmune diseases: A comprehensive review. Clin. Immunol. 2016, 170, 70–79. [Google Scholar] [CrossRef]
  15. Scher, J.U.; Littman, D.R.; Abramson, S.B. Microbiome in Inflammatory Arthritis and Human Rheumatic Diseases. Arthritis Rheumatol. 2016, 68, 35–45. [Google Scholar] [CrossRef]
  16. Caminer, A.C.; Haberman, R.; Scher, J.U. Human microbiome, infections, and rheumatic disease. Clin. Rheumatol. 2017, 36, 2645–2653. [Google Scholar] [CrossRef]
  17. Das, M.; Cronin, O.; Keohane, D.M.; Cormac, E.M.; Nugent, H.; Nugent, M.; Molloy, C.; O’Toole, P.W.; Shanahan, F.; Molloy, M.G.; et al. Gut microbiota alterations associated with reduced bone mineral density in older adults. Rheumatology 2019, 58, 2295–2304. [Google Scholar] [CrossRef]
  18. Nilsson, A.G.; Sundh, D.; Bäckhed, F.; Lorentzon, M. Lactobacillus reuteri reduces bone loss in older women with low bone mineral density: A randomized, placebo-controlled, double-blind, clinical trial. J. Intern. Med. 2018, 284, 307–317. [Google Scholar] [CrossRef]
  19. Wang, J.; Wang, Y.; Gao, W.; Wang, B.; Zhao, H.; Zeng, Y.; Ji, Y.; Hao, D. Diversity analysis of gut microbiota in osteoporosis and osteopenia patients. PeerJ 2017, 5, e3450. [Google Scholar] [CrossRef]
  20. Xu, Z.; Xie, Z.; Sun, J.; Huang, S.; Chen, Y.; Li, C.; Sun, X.; Xia, B.; Tian, L.; Guo, C.; et al. Gut Microbiome Reveals Specific Dysbiosis in Primary Osteoporosis. Front. Cell Infect. Microbiol. 2020, 10, 160. [Google Scholar] [CrossRef]
  21. Liu, C.; Cheung, W.H.; Li, J.; Chow, S.K.; Yu, J.; Wong, S.H.; Ip, M.; Sung, J.J.Y.; Wong, R.M.Y. Understanding the gut microbiota and sarcopenia: A systematic review. J. Cachexia Sarcopenia Muscle 2021, 12, 1393–1407. [Google Scholar] [CrossRef]
  22. Coulson, S.; Butt, H.; Vecchio, P.; Gramotnev, H.; Vitetta, L. Green-lipped mussel extract (Perna canaliculus) and glucosamine sulphate in patients with knee osteoarthritis: Therapeutic efficacy and effects on gastrointestinal microbiota profiles. Inflammopharmacology 2013, 21, 79–90. [Google Scholar] [CrossRef]
  23. Cardoso, J.; Ribeiro, I.; Araújo, T.; Carvalho, F.; Reis, E. Prevalência de dor musculoesquelética em professores. Rev. Bras. De Epidemiol. 2009, 12, 604–614. [Google Scholar] [CrossRef]
  24. Cardoneanu, A.; Cozma, S.; Rezus, C.; Petrariu, F.; Burlui, A.M.; Rezus, E. Characteristics of the intestinal microbiome in ankylosing spondylitis. Exp. Ther. Med. 2021, 22, 676. [Google Scholar] [CrossRef]
  25. Fritzell, P.; Welinder-Olsson, C.; Jonsson, B.; Melhus, A.; Andersson, S.G.E.; Bergstrom, T.; Tropp, H.; Gerdhem, P.; Hagg, O.; Laestander, H.; et al. Bacteria: Back pain, leg pain and Modic sign-a surgical multicentre comparative study. Eur. Spine J. 2019, 28, 2981–2989. [Google Scholar] [CrossRef]
  26. Rajasekaran, S.; Tangavel, C.; Aiyer, S.N.; Nayagam, S.M.; Raveendran, M.; Demonte, N.L.; Subbaiah, P.; Kanna, R.; Shetty, A.P.; Dharmalingam, K. ISSLS PRIZE IN CLINICAL SCIENCE 2017: Is infection the possible initiator of disc disease? An insight from proteomic analysis. Eur. Spine J. 2017, 26, 1384–1400. [Google Scholar] [CrossRef]
  27. Rajasekaran, S.; Soundararajan, D.C.R.; Tangavel, C.; Muthurajan, R.; Sri Vijay Anand, K.S.; Matchado, M.S.; Nayagam, S.M.; Shetty, A.P.; Kanna, R.M.; Dharmalingam, K. Human intervertebral discs harbour a unique microbiome and dysbiosis determines health and disease. Eur. Spine J. 2020, 29, 1621–1640. [Google Scholar] [CrossRef]
  28. Rajasekaran, S.; Tangavel, C.; Sri Vijay Anand, K.S.; Soundararajan, D.C.R.; Nayagam, S.M.; Matchado, M.S.; Raveendran, M.; Shetty, A.P.; Kanna, R.M.; Dharmalingam, K. Inflammaging determines health and disease in lumbar discs-evidence from differing proteomic signatures of healthy, aging, and degenerating discs. Spine J. 2020, 20, 48–59. [Google Scholar] [CrossRef]
  29. Rao, P.J.; Maharaj, M.; Chau, C.; Taylor, P.; Phan, K.; Choy, W.J.; Scherman, D.; Mews, P.; Scholsem, M.; Coughlan, M.; et al. Degenerate-disc infection study with contaminant control (DISC): A multicenter prospective case-control trial. Spine J. 2020, 20, 1544–1553. [Google Scholar] [CrossRef]
  30. Rettedal, E.A.; Ilesanmi-Oyelere, B.L.; Roy, N.C.; Coad, J.; Kruger, M.C. The Gut Microbiome Is Altered in Postmenopausal Women With Osteoporosis and Osteopenia. JBMR Plus 2020, 5, e10452. [Google Scholar] [CrossRef]
  31. Scher, J.U.; Sczesnak, A.; Longman, R.S.; Segata, N.; Ubeda, C.; Bielski, C.; Rostron, T.; Cerundolo, V.; Pamer, E.G.; Abramson, S.B.; et al. Expansion of intestinal Prevotella copri correlates with enhanced susceptibility to arthritis. eLife 2013, 2, e01202. [Google Scholar] [CrossRef]
  32. Guss, J.D.; Taylor, E.; Rouse, Z.; Roubert, S.; Higgins, C.H.; Thomas, C.J.; Baker, S.P.; Vashishth, D.; Donnelly, E.; Shea, M.K.; et al. The microbial metagenome and bone tissue composition in mice with microbiome-induced reductions in bone strength. Bone 2019, 127, 146–154. [Google Scholar] [CrossRef] [PubMed]
  33. Hernandez, C.J.; Yang, X.; Ji, G.; Niu, Y.; Sethuraman, A.S.; Koressel, J.; Shirley, M.; Fields, M.W.; Chyou, S.; Li, T.M.; et al. Disruption of the Gut Microbiome Increases the Risk of Periprosthetic Joint Infection in Mice. Clin. Orthop. Relat. Res. 2019, 477, 2588–2598. [Google Scholar] [CrossRef] [PubMed]
  34. Li, J.Y.; Chassaing, B.; Tyagi, A.M.; Vaccaro, C.; Luo, T.; Adams, J.; Darby, T.M.; Weitzmann, M.N.; Mulle, J.G.; Gewirtz, A.T.; et al. Sex steroid deficiency-associated bone loss is microbiota dependent and prevented by probiotics. J. Clin. Investig. 2016, 126, 2049–2063. [Google Scholar] [CrossRef] [PubMed]
  35. Sjögren, K.; Engdahl, C.; Henning, P.; Lerner, U.H.; Tremaroli, V.; Lagerquist, M.K.; Ohlsson, C. The gut microbiota regulates bone mass in mice. J. Bone Miner. Res. 2012, 27, 1357–1367. [Google Scholar] [CrossRef]
  36. Wang, Z.; Wu, H.; Chen, Y.; Chen, H.; Wang, X.; Yuan, W. Lactobacillus paracasei S16 Alleviates Lumbar Disc Herniation by Modulating Inflammation Response and Gut Microbiota. Front. Nutr. 2021, 8, 701644. [Google Scholar] [CrossRef]
  37. Yan, J.; Herzog, J.W.; Tsang, K.; Brennan, C.A.; Bower, M.A.; Garrett, W.S.; Sartor, B.R.; Aliprantis, A.O.; Charles, J.F. Gut microbiota induce IGF-1 and promote bone formation and growth. Proc. Natl. Acad. Sci. USA 2016, 113, E7554–E7563. [Google Scholar] [CrossRef]
  38. Reis Ferreira, M.; Andreyev, H.J.N.; Mohammed, K.; Truelove, L.; Gowan, S.M.; Li, J.; Gulliford, S.L.; Marchesi, J.R.; Dearnaley, D.P. Microbiota- and Radiotherapy-Induced Gastrointestinal Side-Effects (MARS) Study: A Large Pilot Study of the Microbiome in Acute and Late-Radiation Enteropathy. Clin. Cancer Res. 2019, 25, 6487–6500. [Google Scholar] [CrossRef]
  39. Turnbaugh, P.J.; Ley, R.E.; Hamady, M.; Fraser-Liggett, C.M.; Knight, R.; Gordon, J.I. The human microbiome project. Nature 2007, 449, 804–810. [Google Scholar] [CrossRef]
  40. Peterson, J.; Garges, S.; Giovanni, M.; McInnes, P.; Wang, L.; Schloss, J.A.; Bonazzi, V.; McEwen, J.E.; Wetterstrand, K.A.; Deal, C.; et al. The NIH Human Microbiome Project. Genome Res. 2009, 19, 2317–2323. [Google Scholar] [CrossRef]
  41. Qin, J.; Li, R.; Raes, J.; Arumugam, M.; Burgdorf, K.S.; Manichanh, C.; Nielsen, T.; Pons, N.; Levenez, F.; Yamada, T.; et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 2010, 464, 59–65. [Google Scholar] [CrossRef] [PubMed]
  42. Gilbert, J.; Quinn, R.; Debelius, J.; Xu, Z.; Morton, J.; Garg, N.; Jansson, J.; Dorrestein, P.; Knight, R. Microbiome-wide association studies link dynamic microbial consortia to disease. Nature 2016, 535, 94–103. [Google Scholar] [CrossRef] [PubMed]
  43. Gilbert, J.A.; Blaser, M.J.; Caporaso, J.G.; Jansson, J.K.; Lynch, S.V.; Knight, R. Current understanding of the human microbiome. Nat. Med. 2018, 24, 392–400. [Google Scholar] [CrossRef]
  44. Voreades, N.; Kozil, A.; Weir, T.L. Diet and the development of the human intestinal microbiome. Front. Microbiol. 2014, 5, 494. [Google Scholar] [CrossRef] [PubMed]
  45. Quigley, E.M. Gut bacteria in health and disease. Gastroenterol. Hepatol. 2013, 9, 560–569. [Google Scholar]
  46. Debré, P. Challenges set by the microbiota. Biol. Aujourdhui 2017, 211, 19–28. [Google Scholar] [CrossRef] [PubMed]
  47. Sekirov, I.; Russell, S.L.; Antunes, L.C.; Finlay, B.B. Gut microbiota in health and disease. Physiol. Rev. 2010, 90, 859–904. [Google Scholar] [CrossRef]
  48. Cryan, J.F.; O’Mahony, S.M. The microbiome-gut-brain axis: From bowel to behavior. Neurogastroenterol. Motil. 2011, 23, 187–192. [Google Scholar] [CrossRef]
  49. Flint, H.J.; Scott, K.P.; Duncan, S.H.; Louis, P.; Forano, E. Microbial degradation of complex carbohydrates in the gut. Gut Microbes 2012, 3, 289–306. [Google Scholar] [CrossRef]
  50. Lynch, S.V.; Pedersen, O. The Human Intestinal Microbiome in Health and Disease. N. Engl. J. Med. 2016, 375, 2369–2379. [Google Scholar] [CrossRef]
  51. Eckburg, P.B.; Bik, E.M.; Bernstein, C.N.; Purdom, E.; Dethlefsen, L.; Sargent, M.; Gill, S.R.; Nelson, K.E.; Relman, D.A. Diversity of the human intestinal microbial flora. Science 2005, 308, 1635–1638. [Google Scholar] [CrossRef] [PubMed]
  52. Reyes, A.; Haynes, M.; Hanson, N.; Angly, F.E.; Heath, A.C.; Rohwer, F.; Gordon, J.I. Viruses in the faecal microbiota of monozygotic twins and their mothers. Nature 2010, 466, 334–338. [Google Scholar] [CrossRef] [PubMed]
  53. Pérez-Cobas, A.E.; Gosalbes, M.J.; Friedrichs, A.; Knecht, H.; Artacho, A.; Eismann, K.; Otto, W.; Rojo, D.; Bargiela, R.; von Bergen, M.; et al. Gut microbiota disturbance during antibiotic therapy: A multi-omic approach. Gut 2013, 62, 1591–1601. [Google Scholar] [CrossRef] [PubMed]
  54. Yatsunenko, T.; Rey, F.E.; Manary, M.J.; Trehan, I.; Dominguez-Bello, M.G.; Contreras, M.; Magris, M.; Hidalgo, G.; Baldassano, R.N.; Anokhin, A.P.; et al. Human gut microbiome viewed across age and geography. Nature 2012, 486, 222–227. [Google Scholar] [CrossRef] [PubMed]
  55. Koren, O.; Goodrich, J.K.; Cullender, T.C.; Spor, A.; Laitinen, K.; Bäckhed, H.K.; Gonzalez, A.; Werner, J.J.; Angenent, L.T.; Knight, R.; et al. Host remodeling of the gut microbiome and metabolic changes during pregnancy. Cell 2012, 150, 470–480. [Google Scholar] [CrossRef]
  56. David, L.A.; Maurice, C.F.; Carmody, R.N.; Gootenberg, D.B.; Button, J.E.; Wolfe, B.E.; Ling, A.V.; Devlin, A.S.; Varma, Y.; Fischbach, M.A.; et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 2014, 505, 559–563. [Google Scholar] [CrossRef]
  57. He, Y.; Wu, W.; Zheng, H.M.; Li, P.; McDonald, D.; Sheng, H.F.; Chen, M.X.; Chen, Z.H.; Ji, G.Y.; Zheng, Z.D.; et al. Author Correction: Regional variation limits applications of healthy gut microbiome reference ranges and disease models. Nat. Med. 2018, 24, 1940. [Google Scholar] [CrossRef]
  58. Deschasaux, M.; Bouter, K.E.; Prodan, A.; Levin, E.; Groen, A.K.; Herrema, H.; Tremaroli, V.; Bakker, G.J.; Attaye, I.; Pinto-Sietsma, S.J.; et al. Depicting the composition of gut microbiota in a population with varied ethnic origins but shared geography. Nat. Med. 2018, 24, 1526–1531. [Google Scholar] [CrossRef]
  59. Fasano, A.; Shea-Donohue, T. Mechanisms of disease: The role of intestinal barrier function in the pathogenesis of gastrointestinal autoimmune diseases. Nat. Clin. Pract. Gastroenterol. Hepatol. 2005, 2, 416–422. [Google Scholar] [CrossRef]
  60. Nougayrède, J.P.; Homburg, S.; Taieb, F.; Boury, M.; Brzuszkiewicz, E.; Gottschalk, G.; Buchrieser, C.; Hacker, J.; Dobrindt, U.; Oswald, E. Escherichia coli induces DNA double-strand breaks in eukaryotic cells. Science 2006, 313, 848–851. [Google Scholar] [CrossRef]
  61. Serban, D.E. Microbiota in Inflammatory Bowel Disease Pathogenesis and Therapy: Is It All About Diet? Nutr. Clin. Pract. 2015, 30, 760–779. [Google Scholar] [CrossRef] [PubMed]
  62. Dabke, K.; Hendrick, G.; Devkota, S. The gut microbiome and metabolic syndrome. J. Clin. Investig. 2019, 129, 4050–4057. [Google Scholar] [CrossRef] [PubMed]
  63. Vallianou, N.; Christodoulatos, G.S.; Karampela, I.; Tsilingiris, D.; Magkos, F.; Stratigou, T.; Kounatidis, D.; Dalamaga, M. Understanding the Role of the Gut Microbiome and Microbial Metabolites in Non-Alcoholic Fatty Liver Disease: Current Evidence and Perspectives. Biomolecules 2021, 12, 56. [Google Scholar] [CrossRef]
  64. Singh, B.; Qin, N.; Reid, G. Microbiome Regulation of Autoimmune, Gut and Liver Associated Diseases. Inflamm. Allergy Drug Targets 2015, 14, 84–93. [Google Scholar] [CrossRef]
  65. Gioia, C.; Lucchino, B.; Tarsitano, M.G.; Iannuccelli, C.; Di Franco, M. Dietary Habits and Nutrition in Rheumatoid Arthritis: Can. Diet. Influence Disease Development and Clinical Manifestations? Nutrients 2020, 12, 1456. [Google Scholar] [CrossRef] [PubMed]
  66. Mowry, E.M.; Glenn, J.D. The Dynamics of the Gut Microbiome in Multiple Sclerosis in Relation to Disease. Neurol. Clin. 2018, 36, 185–196. [Google Scholar] [CrossRef] [PubMed]
  67. Wei, Y.; Li, Y.; Yan, L.; Sun, C.; Miao, Q.; Wang, Q.; Xiao, X.; Lian, M.; Li, B.; Chen, Y.; et al. Alterations of gut microbiome in autoimmune hepatitis. Gut 2020, 69, 569–577. [Google Scholar] [CrossRef]
  68. Manasson, J.; Shen, N.; Garcia Ferrer, H.R.; Ubeda, C.; Iraheta, I.; Heguy, A.; Von Feldt, J.M.; Espinoza, L.R.; Garcia Kutzbach, A.; Segal, L.N.; et al. Gut Microbiota Perturbations in Reactive Arthritis and Postinfectious Spondyloarthritis. Arthritis Rheumatol. 2018, 70, 242–254. [Google Scholar] [CrossRef]
  69. Bibbò, S.; Dore, M.P.; Pes, G.M.; Delitala, G.; Delitala, A.P. Is there a role for gut microbiota in type 1 diabetes pathogenesis? Ann. Med. 2017, 49, 11–22. [Google Scholar] [CrossRef]
  70. Vitetta, L.; Coulson, S.; Linnane, A.W.; Butt, H. The gastrointestinal microbiome and musculoskeletal diseases: A beneficial role for probiotics and prebiotics. Pathogens 2013, 2, 606–626. [Google Scholar] [CrossRef]
  71. Brial, F.; Le Lay, A.; Dumas, M.E.; Gauguier, D. Implication of gut microbiota metabolites in cardiovascular and metabolic diseases. Cell. Mol. Life Sci. 2018, 75, 3977–3990. [Google Scholar] [CrossRef]
  72. Bennett, B.J.; de Aguiar Vallim, T.Q.; Wang, Z.; Shih, D.M.; Meng, Y.; Gregory, J.; Allayee, H.; Lee, R.; Graham, M.; Crooke, R.; et al. Trimethylamine-N-oxide, a metabolite associated with atherosclerosis, exhibits complex genetic and dietary regulation. Cell Metab. 2013, 17, 49–60. [Google Scholar] [CrossRef] [PubMed]
  73. Kho, Z.Y.; Lal, S.K. The Human Gut Microbiome—A Potential Controller of Wellness and Disease. Front. Microbiol. 2018, 9, 1835. [Google Scholar] [CrossRef] [PubMed]
  74. Guo, X.; Rao, J.N.; Liu, L.; Zou, T.T.; Turner, D.J.; Bass, B.L.; Wang, J.Y. Regulation of adherens junctions and epithelial paracellular permeability: A novel function for polyamines. Am. J. Physiol. Cell Physiol. 2003, 285, C1174–C1187. [Google Scholar] [CrossRef] [PubMed]
  75. Guo, X.; Rao, J.N.; Liu, L.; Zou, T.; Keledjian, K.M.; Boneva, D.; Marasa, B.S.; Wang, J.Y. Polyamines are necessary for synthesis and stability of occludin protein in intestinal epithelial cells. Am. J. Physiol. Gastrointest. Liver Physiol. 2005, 288, G1159–G1169. [Google Scholar] [CrossRef]
  76. Pérez-Cano, F.J.; González-Castro, A.; Castellote, C.; Franch, A.; Castell, M. Influence of breast milk polyamines on suckling rat immune system maturation. Dev. Comp. Immunol. 2010, 34, 210–218. [Google Scholar] [CrossRef]
  77. Johnson, C.H.; Dejea, C.M.; Edler, D.; Hoang, L.T.; Santidrian, A.F.; Felding, B.H.; Ivanisevic, J.; Cho, K.; Wick, E.C.; Hechenbleikner, E.M.; et al. Metabolism links bacterial biofilms and colon carcinogenesis. Cell Metab. 2015, 21, 891–897. [Google Scholar] [CrossRef]
  78. Rooks, M.G.; Garrett, W.S. Gut microbiota, metabolites and host immunity. Nat. Rev. Immunol. 2016, 16, 341–352. [Google Scholar] [CrossRef]
  79. Nicholson, J.K.; Holmes, E.; Kinross, J.; Burcelin, R.; Gibson, G.; Jia, W.; Pettersson, S. Host-gut microbiota metabolic interactions. Science 2012, 336, 1262–1267. [Google Scholar] [CrossRef]
  80. Lerner, A.; Neidhöfer, S.; Matthias, T. The Gut Microbiome Feelings of the Brain: A Perspective for Non-Microbiologists. Microorganisms 2017, 5, 66. [Google Scholar] [CrossRef]
  81. Selma, M.V.; Espín, J.C.; Tomás-Barberán, F.A. Interaction between phenolics and gut microbiota: Role in human health. J. Agric. Food Chem. 2009, 57, 6485–6501. [Google Scholar] [CrossRef] [PubMed]
  82. Larrosa, M.; González-Sarrías, A.; García-Conesa, M.T.; Tomás-Barberán, F.A.; Espín, J.C. Urolithins, ellagic acid-derived metabolites produced by human colonic microflora, exhibit estrogenic and antiestrogenic activities. J. Agric. Food Chem. 2006, 54, 1611–1620. [Google Scholar] [CrossRef] [PubMed]
  83. Larrosa, M.; González-Sarrías, A.; Yáñez-Gascón, M.J.; Selma, M.V.; Azorín-Ortuño, M.; Toti, S.; Tomás-Barberán, F.; Dolara, P.; Espín, J.C. Anti-inflammatory properties of a pomegranate extract and its metabolite urolithin-A in a colitis rat model and the effect of colon inflammation on phenolic metabolism. J. Nutr. Biochem. 2010, 21, 717–725. [Google Scholar] [CrossRef] [PubMed]
  84. Dumas, M.E.; Barton, R.H.; Toye, A.; Cloarec, O.; Blancher, C.; Rothwell, A.; Fearnside, J.; Tatoud, R.; Blanc, V.; Lindon, J.C.; et al. Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice. Proc. Natl. Acad. Sci. USA 2006, 103, 12511–12516. [Google Scholar] [CrossRef] [PubMed]
  85. Wang, Z.; Klipfell, E.; Bennett, B.J.; Koeth, R.; Levison, B.S.; Dugar, B.; Feldstein, A.E.; Britt, E.B.; Fu, X.; Chung, Y.M.; et al. Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature 2011, 472, 57–63. [Google Scholar] [CrossRef] [PubMed]
  86. Hylemon, P.B.; Zhou, H.; Pandak, W.M.; Ren, S.; Gil, G.; Dent, P. Bile acids as regulatory molecules. J. Lipid Res. 2009, 50, 1509–1520. [Google Scholar] [CrossRef]
  87. Deguchi, T.; Ohtsuki, S.; Otagiri, M.; Takanaga, H.; Asaba, H.; Mori, S.; Terasaki, T. Major role of organic anion transporter 3 in the transport of indoxyl sulfate in the kidney. Kidney Int. 2002, 61, 1760–1768. [Google Scholar] [CrossRef]
  88. Wikoff, W.R.; Anfora, A.T.; Liu, J.; Schultz, P.G.; Lesley, S.A.; Peters, E.C.; Siuzdak, G. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proc. Natl. Acad. Sci. USA 2009, 106, 3698–3703. [Google Scholar] [CrossRef]
  89. Venkatesh, M.; Mukherjee, S.; Wang, H.; Li, H.; Sun, K.; Benechet, A.P.; Qiu, Z.; Maher, L.; Redinbo, M.R.; Phillips, R.S.; et al. Symbiotic bacterial metabolites regulate gastrointestinal barrier function via the xenobiotic sensor PXR and Toll-like receptor 4. Immunity 2014, 41, 296–310. [Google Scholar] [CrossRef]
  90. Tolhurst, G.; Heffron, H.; Lam, Y.S.; Parker, H.E.; Habib, A.M.; Diakogiannaki, E.; Cameron, J.; Grosse, J.; Reimann, F.; Gribble, F.M. Short-chain fatty acids stimulate glucagon-like peptide-1 secretion via the G-protein-coupled receptor FFAR2. Diabetes 2012, 61, 364–371. [Google Scholar] [CrossRef]
  91. Galus, M.; Jeyaranjaan, J.; Smith, E.; Li, H.; Metcalfe, C.; Wilson, J.Y. Chronic effects of exposure to a pharmaceutical mixture and municipal wastewater in zebrafish. Aquat. Toxicol. 2013, 132, 212–222. [Google Scholar] [CrossRef]
  92. Steves, C.J.; Bird, S.; Williams, F.M.; Spector, T.D. The Microbiome and Musculoskeletal Conditions of Aging: A Review of Evidence for Impact and Potential Therapeutics. J. Bone Miner. Res. 2016, 31, 261–269. [Google Scholar] [CrossRef] [PubMed]
  93. Derrien, M.; Alvarez, A.-S.; de Vos, W.M. The Gut Microbiota in the First Decade of Life. Trends Microbiol. 2019, 27, 997–1010. [Google Scholar] [CrossRef]
  94. Matamoros, S.; Gras-Leguen, C.; Le Vacon, F.; Potel, G.; de La Cochetiere, M.F. Development of intestinal microbiota in infants and its impact on health. Trends Microbiol. 2013, 21, 167–173. [Google Scholar] [CrossRef] [PubMed]
  95. Jansson, P.-A.; Curiac, D.; Ahrén, I.; Hansson, F.; Martinsson Niskanen, T.; Sjögren, K.; Ohlsson, C. Probiotic treatment using a mix of three Lactobacillus strains for lumbar spine bone loss in postmenopausal women: A randomised, double-blind, placebo-controlled, multicentre trial. Lancet Rheumatol. 2019, 1, e154–e162. [Google Scholar] [CrossRef]
  96. Martin-Millan, M.; Almeida, M.; Ambrogini, E.; Han, L.; Zhao, H.; Weinstein, R.S.; Jilka, R.L.; O’Brien, C.A.; Manolagas, S.C. The estrogen receptor-α in osteoclasts mediates the protective effects of estrogens on cancellous but not cortical bone. Mol. Endocrinol. 2010, 24, 323–334. [Google Scholar] [CrossRef] [PubMed]
  97. Nakamura, T.; Imai, Y.; Matsumoto, T.; Sato, S.; Takeuchi, K.; Igarashi, K.; Harada, Y.; Azuma, Y.; Krust, A.; Yamamoto, Y.; et al. Estrogen prevents bone loss via estrogen receptor α and induction of Fas ligand in osteoclasts. Cell 2007, 130, 811–823. [Google Scholar] [CrossRef]
  98. Sato, K.; Suematsu, A.; Okamoto, K.; Yamaguchi, A.; Morishita, Y.; Kadono, Y.; Tanaka, S.; Kodama, T.; Akira, S.; Iwakura, Y.; et al. Th17 functions as an osteoclastogenic helper T cell subset that links T cell activation and bone destruction. J. Exp. Med. 2006, 203, 2673–2682. [Google Scholar] [CrossRef]
  99. Takayanagi, H.; Ogasawara, K.; Hida, S.; Chiba, T.; Murata, S.; Sato, K.; Takaoka, A.; Yokochi, T.; Oda, H.; Tanaka, K.; et al. T-cell-mediated regulation of osteoclastogenesis by signalling cross-talk between RANKL and IFN-γ. Nature 2000, 408, 600–605. [Google Scholar] [CrossRef]
  100. Yu, M.; Malik Tyagi, A.; Li, J.Y.; Adams, J.; Denning, T.L.; Weitzmann, M.N.; Jones, R.M.; Pacifici, R. PTH induces bone loss via microbial-dependent expansion of intestinal TNF+ T cells and Th17 cells. Nat. Commun. 2020, 11, 468. [Google Scholar] [CrossRef]
  101. Lorentzon, M.; Cummings, S.R. Osteoporosis: The evolution of a diagnosis. J. Intern. Med. 2015, 277, 650–661. [Google Scholar] [CrossRef] [PubMed]
  102. Pasco, J.A.; Kotowicz, M.A.; Henry, M.J.; Nicholson, G.C.; Spilsbury, H.J.; Box, J.D.; Schneider, H.G. High-sensitivity C-reactive protein and fracture risk in elderly women. JAMA 2006, 296, 1353–1355. [Google Scholar] [CrossRef] [PubMed]
  103. Ding, C.; Parameswaran, V.; Udayan, R.; Burgess, J.; Jones, G. Circulating levels of inflammatory markers predict change in bone mineral density and resorption in older adults: A longitudinal study. J. Clin. Endocrinol. Metab. 2008, 93, 1952–1958. [Google Scholar] [CrossRef]
  104. Schett, G.; Kiechl, S.; Weger, S.; Pederiva, A.; Mayr, A.; Petrangeli, M.; Oberhollenzer, F.; Lorenzini, R.; Redlich, K.; Axmann, R.; et al. High-sensitivity C-reactive protein and risk of nontraumatic fractures in the Bruneck study. Arch. Intern. Med. 2006, 166, 2495–2501. [Google Scholar] [CrossRef]
  105. Koh, J.M.; Khang, Y.H.; Jung, C.H.; Bae, S.; Kim, D.J.; Chung, Y.E.; Kim, G.S. Higher circulating hsCRP levels are associated with lower bone mineral density in healthy pre- and postmenopausal women: Evidence for a link between systemic inflammation and osteoporosis. Osteoporos. Int. 2005, 16, 1263–1271. [Google Scholar] [CrossRef] [PubMed]
  106. Hienz, S.A.; Paliwal, S.; Ivanovski, S. Mechanisms of Bone Resorption in Periodontitis. J. Immunol. Res. 2015, 2015, 615486. [Google Scholar] [CrossRef]
  107. Griffin, I.J.; Davila, P.M.; Abrams, S.A. Non-digestible oligosaccharides and calcium absorption in girls with adequate calcium intakes. Br. J. Nutr. 2002, 87 (Suppl. S2), S187–S191. [Google Scholar] [CrossRef]
  108. van den Heuvel, E.G.; Muys, T.; van Dokkum, W.; Schaafsma, G. Oligofructose stimulates calcium absorption in adolescents. Am. J. Clin. Nutr. 1999, 69, 544–548. [Google Scholar] [CrossRef]
  109. Whisner, C.M.; Castillo, L.F. Prebiotics, Bone and Mineral Metabolism. Calcif. Tissue Int. 2018, 102, 443–479. [Google Scholar] [CrossRef]
  110. Costa, G.; Vasconcelos, Q.; Abreu, G.; Albuquerque, A.; Vilarejo, J.; Aragao, G. Changes in nutrient absorption in children and adolescents caused by fructans, especially fructooligosaccharides and inulin. Arch. Pediatr. 2020, 27, 166–169. [Google Scholar] [CrossRef]
  111. Ohlsson, C.; Sjogren, K. Effects of the gut microbiota on bone mass. Trends Endocrinol. Metab. 2015, 26, 69–74. [Google Scholar] [CrossRef]
  112. Abrams, S.A.; Griffin, I.J.; Hawthorne, K.M.; Liang, L.; Gunn, S.K.; Darlington, G.; Ellis, K.J. A combination of prebiotic short- and long-chain inulin-type fructans enhances calcium absorption and bone mineralization in young adolescents. Am. J. Clin. Nutr. 2005, 82, 471–476. [Google Scholar] [CrossRef] [PubMed]
  113. Whisner, C.M.; Martin, B.R.; Nakatsu, C.H.; McCabe, G.P.; McCabe, L.D.; Peacock, M.; Weaver, C.M. Soluble maize fibre affects short-term calcium absorption in adolescent boys and girls: A randomised controlled trial using dual stable isotopic tracers. Br. J. Nutr. 2014, 112, 446–456. [Google Scholar] [CrossRef] [PubMed]
  114. Mangnus, L.; van Steenbergen, H.W.; Lindqvist, E.; Brouwer, E.; Reijnierse, M.; Huizinga, T.W.; Gregersen, P.K.; Berglin, E.; Rantapaa-Dahlqvist, S.; van der Heijde, D.; et al. Studies on ageing and the severity of radiographic joint damage in rheumatoid arthritis. Arthritis Res. Ther. 2015, 17, 222. [Google Scholar] [CrossRef] [PubMed]
  115. Ivanov, I.I.; Atarashi, K.; Manel, N.; Brodie, E.L.; Shima, T.; Karaoz, U.; Wei, D.; Goldfarb, K.C.; Santee, C.A.; Lynch, S.V.; et al. Induction of intestinal Th17 cells by segmented filamentous bacteria. Cell 2009, 139, 485–498. [Google Scholar] [CrossRef]
  116. McLean, M.H.; Dieguez, D.; Jr Miller, L.M.; Young, H.A. Does the microbiota play a role in the pathogenesis of autoimmune diseases? Gut 2015, 64, 332–341. [Google Scholar] [CrossRef]
  117. Biagi, E.; Candela, M.; Fairweather-Tait, S.; Franceschi, C.; Brigidi, P. Aging of the human metaorganism: The microbial counterpart. Age (Dordr) 2012, 34, 247–267. [Google Scholar] [CrossRef]
  118. de Aquino, S.G.; Abdollahi-Roodsaz, S.; Koenders, M.I.; van de Loo, F.A.; Pruijn, G.J.; Marijnissen, R.J.; Walgreen, B.; Helsen, M.M.; van den Bersselaar, L.A.; de Molon, R.S.; et al. Periodontal pathogens directly promote autoimmune experimental arthritis by inducing a TLR2- and IL-1-driven Th17 response. J. Immunol. 2014, 192, 4103–4111. [Google Scholar] [CrossRef]
  119. Marchesan, J.T.; Gerow, E.A.; Schaff, R.; Taut, A.D.; Shin, S.Y.; Sugai, J.; Brand, D.; Burberry, A.; Jorns, J.; Lundy, S.K.; et al. Porphyromonas gingivalis oral infection exacerbates the development and severity of collagen-induced arthritis. Arthritis Res. Ther. 2013, 15, R186. [Google Scholar] [CrossRef]
  120. Wells, P.M.; Adebayo, A.S.; Bowyer, R.C.E.; Freidin, M.B.; Finckh, A.; Strowig, T.; Lesker, T.R.; Alpizar-Rodriguez, D.; Gilbert, B.; Kirkham, B.; et al. Associations between gut microbiota and genetic risk for rheumatoid arthritis in the absence of disease: A cross-sectional study. Lancet Rheumatol. 2020, 2, e418–e427. [Google Scholar] [CrossRef]
  121. Lopez-Oliva, I.; Paropkari, A.D.; Saraswat, S.; Serban, S.; Yonel, Z.; Sharma, P.; de Pablo, P.; Raza, K.; Filer, A.; Chapple, I.; et al. Dysbiotic Subgingival Microbial Communities in Periodontally Healthy Patients With Rheumatoid Arthritis. Arthritis Rheumatol. 2018, 70, 1008–1013. [Google Scholar] [CrossRef] [PubMed]
  122. Pan, H.; Guo, R.; Ju, Y.; Wang, Q.; Zhu, J.; Xie, Y.; Zheng, Y.; Li, T.; Liu, Z.; Lu, L.; et al. A single bacterium restores the microbiome dysbiosis to protect bones from destruction in a rat model of rheumatoid arthritis. Microbiome 2019, 7, 107. [Google Scholar] [CrossRef] [PubMed]
  123. Santilli, V.; Bernetti, A.; Mangone, M.; Paoloni, M. Clinical definition of sarcopenia. Clin. Cases Miner. Bone Metab. 2014, 11, 177–180. [Google Scholar] [CrossRef] [PubMed]
  124. Cruz-Jentoft, A.J.; Baeyens, J.P.; Bauer, J.M.; Boirie, Y.; Cederholm, T.; Landi, F.; Martin, F.C.; Michel, J.P.; Rolland, Y.; Schneider, S.M.; et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010, 39, 412–423. [Google Scholar] [CrossRef]
  125. Bindels, L.B.; Delzenne, N.M. Muscle wasting: The gut microbiota as a new therapeutic target? Int. J. Biochem. Cell. Biol. 2013, 45, 2186–2190. [Google Scholar] [CrossRef]
  126. Schaap, L.A.; Pluijm, S.M.; Deeg, D.J.; Visser, M. Inflammatory markers and loss of muscle mass (sarcopenia) and strength. Am. J. Med. 2006, 119, 526.e9–526.e17. [Google Scholar] [CrossRef]
  127. Kang, L.; Li, P.; Wang, D.; Wang, T.; Hao, D.; Qu, X. Alterations in intestinal microbiota diversity, composition, and function in patients with sarcopenia. Sci. Rep. 2021, 11, 4628. [Google Scholar] [CrossRef]
  128. Inglis, J.E.; Ilich, J.Z. The Microbiome and Osteosarcopenic Obesity in Older Individuals in Long-Term Care Facilities. Curr. Osteoporos. Rep. 2015, 13, 358–362. [Google Scholar] [CrossRef]
  129. Goldring, M.B.; Otero, M. Inflammation in osteoarthritis. Curr. Opin. Rheumatol. 2011, 23, 471–478. [Google Scholar] [CrossRef]
  130. Benito, M.J.; Veale, D.J.; FitzGerald, O.; van den Berg, W.B.; Bresnihan, B. Synovial tissue inflammation in early and late osteoarthritis. Ann. Rheum. Dis. 2005, 64, 1263–1267. [Google Scholar] [CrossRef]
  131. Boer, C.G.; Radjabzadeh, D.; Medina-Gomez, C.; Garmaeva, S.; Schiphof, D.; Arp, P.; Koet, T.; Kurilshikov, A.; Fu, J.; Ikram, M.A.; et al. Intestinal microbiome composition and its relation to joint pain and inflammation. Nat. Commun. 2019, 10, 4881. [Google Scholar] [CrossRef] [PubMed]
  132. Siala, M.; Gdoura, R.; Fourati, H.; Rihl, M.; Jaulhac, B.; Younes, M.; Sibilia, J.; Baklouti, S.; Bargaoui, N.; Sellami, S.; et al. Broad-range PCR, cloning and sequencing of the full 16S rRNA gene for detection of bacterial DNA in synovial fluid samples of Tunisian patients with reactive and undifferentiated arthritis. Arthritis Res. Ther. 2009, 11, R102. [Google Scholar] [CrossRef] [PubMed]
  133. Olmez, N.; Wang, G.F.; Li, Y.; Zhang, H.; Schumacher, H.R. Chlamydial nucleic acids in synovium in osteoarthritis: What are the implications? J. Rheumatol. 2001, 28, 1874–1880. [Google Scholar] [PubMed]
  134. Diseases, G.B.D.; Injuries, C. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. Lancet 2020, 396, 1204–1222. [Google Scholar] [CrossRef]
  135. Chou, D.; Samartzis, D.; Bellabarba, C.; Patel, A.; Luk, K.D.; Kisser, J.M.; Skelly, A.C. Degenerative magnetic resonance imaging changes in patients with chronic low back pain: A systematic review. Spine 2011, 36 (Suppl. S21), S43–S53. [Google Scholar] [CrossRef]
  136. Mallow, G.M.; Zepeda, D.; Kuzel, T.G.; Barajas, J.N.; Aboushaala, K.; Nolte, M.T.; Espinoza-Orias, A.; Oh, C.; Colman, M.; Kogan, M.; et al. ISSLS PRIZE in Clinical Science 2022: Epidemiology, risk factors and clinical impact of juvenile Modic changes in paediatric patients with low back pain. Eur. Spine J. 2022, 31, 1069–1079. [Google Scholar] [CrossRef]
  137. Rudisill, S.S.; Hornung, A.L.; Kia, C.; Mallow, G.M.; Aboushaala, K.; Lim, P.; Martin, J.; Wong, A.Y.L.; Toro, S.; Kozaki, T.; et al. Obesity in children with low back pain: Implications with imaging phenotypes and opioid use. Spine J. 2023, 23, 945–953. [Google Scholar] [CrossRef]
  138. Wan, Z.Y.; Zhang, J.; Shan, H.; Liu, T.F.; Song, F.; Samartzis, D.; Wang, H.Q. Epidemiology of Lumbar Degenerative Phenotypes of Children and Adolescents: A Large-Scale Imaging Study. Glob. Spine J. 2023, 13, 599–608. [Google Scholar] [CrossRef]
  139. Zehra, U.; Tryfonidou, M.; Iatridis, J.C.; Illien-Junger, S.; Mwale, F.; Samartzis, D. Mechanisms and clinical implications of intervertebral disc calcification. Nat. Rev. Rheumatol. 2022, 18, 352–362. [Google Scholar] [CrossRef]
  140. Sadowska, A.; Touli, E.; Hitzl, W.; Greutert, H.; Ferguson, S.J.; Wuertz-Kozak, K.; Hausmann, O.N. Inflammaging in cervical and lumbar degenerated intervertebral discs: Analysis of proinflammatory cytokine and TRP channel expression. Eur. Spine J. 2018, 27, 564–577. [Google Scholar] [CrossRef]
  141. Capoor, M.N.; Birkenmaier, C.; Wang, J.C.; McDowell, A.; Ahmed, F.S.; Bruggemann, H.; Coscia, E.; Davies, D.G.; Ohrt-Nissen, S.; Raz, A.; et al. A review of microscopy-based evidence for the association of Propionibacterium acnes biofilms in degenerative disc disease and other diseased human tissue. Eur. Spine J. 2019, 28, 2951–2971. [Google Scholar] [CrossRef] [PubMed]
  142. Ohrt-Nissen, S.; Fritz, B.G.; Walbom, J.; Kragh, K.N.; Bjarnsholt, T.; Dahl, B.; Manniche, C. Bacterial biofilms: A possible mechanism for chronic infection in patients with lumbar disc herniation—A prospective proof-of-concept study using fluorescence in situ hybridization. APMIS 2018, 126, 440–447. [Google Scholar] [CrossRef] [PubMed]
  143. Urquhart, D.M.; Zheng, Y.; Cheng, A.C.; Rosenfeld, J.V.; Chan, P.; Liew, S.; Hussain, S.M.; Cicuttini, F.M. Could low grade bacterial infection contribute to low back pain? A systematic review. BMC Med. 2015, 13, 13. [Google Scholar] [CrossRef] [PubMed]
  144. Lin, Y.; Tang, G.; Jiao, Y.; Yuan, Y.; Zheng, Y.; Chen, Y.; Xiao, J.; Li, C.; Chen, Z.; Cao, P. Propionibacterium acnes Induces Intervertebral Disc Degeneration by Promoting iNOS/NO and COX-2/PGE(2) Activation via the ROS-Dependent NF-kappaB Pathway. Oxid. Med. Cell. Longev. 2018, 2018, 3692752. [Google Scholar] [CrossRef] [PubMed]
  145. De la Fuente, M. The Role of the Microbiota-Gut-Brain Axis in the Health and Illness Condition: A Focus on Alzheimer’s Disease. J. Alzheimers Dis. 2021, 81, 1345–1360. [Google Scholar] [CrossRef] [PubMed]
  146. Dekker Nitert, M.; Mousa, A.; Barrett, H.L.; Naderpoor, N.; de Courten, B. Altered Gut Microbiota Composition Is Associated With Back Pain in Overweight and Obese Individuals. Front. Endocrinol. 2020, 11, 605. [Google Scholar] [CrossRef]
  147. Tamai, H.; Teraguchi, M.; Hashizume, H.; Oka, H.; Cheung, J.P.Y.; Samartzis, D.; Muraki, S.; Akune, T.; Kawaguchi, H.; Nakamura, K.; et al. A Prospective, 3-year Longitudinal Study of Modic Changes of the Lumbar Spine in a Population-based Cohort: The Wakayama Spine Study. Spine 2022, 47, 490–497. [Google Scholar] [CrossRef]
  148. Teraguchi, M.; Hashizume, H.; Oka, H.; Cheung, J.P.Y.; Samartzis, D.; Tamai, H.; Muraki, S.; Akune, T.; Tanaka, S.; Yoshida, M.; et al. Detailed Subphenotyping of Lumbar Modic Changes and Their Association with Low Back Pain in a Large Population-Based Study: The Wakayama Spine Study. Pain Ther. 2022, 11, 57–71. [Google Scholar] [CrossRef]
  149. Udby, P.M.; Modic, M.; Elmose, S.; Carreon, L.Y.; Andersen, M.O.; Karppinen, J.; Samartzis, D. The Clinical Significance of the Modic Changes Grading Score. Glob. Spine J. 2022, 21925682221123012. [Google Scholar] [CrossRef]
  150. Udby, P.M.; Samartzis, D.; Carreon, L.Y.; Andersen, M.O.; Karppinen, J.; Modic, M. A definition and clinical grading of Modic changes. J. Orthop. Res. 2022, 40, 301–307. [Google Scholar] [CrossRef]
  151. McGrath, S.; Zhao, X.; Steele, R.; Thombs, B.D.; Benedetti, A.; Collaboration, D.E.S.D. Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. Stat. Methods Med. Res. 2020, 29, 2520–2537. [Google Scholar] [CrossRef]
  152. Riley, R.D.; Higgins, J.P.; Deeks, J.J. Interpretation of random effects meta-analyses. BMJ 2011, 342, d549. [Google Scholar] [CrossRef] [PubMed]
  153. Higgins, J.P.; Thompson, S.G. Quantifying heterogeneity in a meta-analysis. Stat. Med. 2002, 21, 1539–1558. [Google Scholar] [CrossRef] [PubMed]
  154. Mok, F.P.; Samartzis, D.; Karppinen, J.; Fong, D.Y.; Luk, K.D.; Cheung, K.M. Modic changes of the lumbar spine: Prevalence, risk factors, and association with disc degeneration and low back pain in a large-scale population-based cohort. Spine J. 2016, 16, 32–41. [Google Scholar] [CrossRef] [PubMed]
  155. Grant, R.; Lovecchio, F.; Samartzis, D.; Louie, P.K.; Germscheid, N.; An, H.S.; Cheung, J.P.Y.; Chutkan, N.; Mallow, G.M.; Neva, M.H.; et al. Telemedicine in spine surgery: Global perspectives and practices. Glob. Spine J. 2023, 13, 1200–1211. [Google Scholar]
  156. Storheim, K.; Espeland, A.; Grovle, L.; Skouen, J.S.; Assmus, J.; Anke, A.; Froholdt, A.; Pedersen, L.M.; Haugen, A.J.; Fors, T.; et al. Antibiotic treatment In patients with chronic low back pain and Modic changes (the AIM study): Study protocol for a randomised controlled trial. Trials 2017, 18, 596. [Google Scholar] [CrossRef]
  157. Saukkonen, J.; Maatta, J.; Oura, P.; Kyllonen, E.; Tervonen, O.; Niinimaki, J.; Auvinen, J.; Karppinen, J. Association Between Modic Changes and Low Back Pain in Middle Age: A Northern Finland Birth Cohort Study. Spine 2020, 45, 1360–1367. [Google Scholar] [CrossRef]
  158. Määttä, J.H.; Wadge, S.; MacGregor, A.; Karppinen, J.; Williams, F.M. ISSLS Prize Winner: Vertebral Endplate (Modic) Change is an Independent Risk Factor for Episodes of Severe and Disabling Low Back Pain. Spine 2015, 40, 1187–1193. [Google Scholar] [CrossRef]
  159. Capoor, M.N.; Ruzicka, F.; Schmitz, J.E.; James, G.A.; Machackova, T.; Jancalek, R.; Smrcka, M.; Lipina, R.; Ahmed, F.S.; Alamin, T.F.; et al. Propionibacterium acnes biofilm is present in intervertebral discs of patients undergoing microdiscectomy. PLoS ONE 2017, 12, e0174518. [Google Scholar] [CrossRef]
  160. Chen, Z.; Zheng, Y.; Yuan, Y.; Jiao, Y.; Xiao, J.; Zhou, Z.; Cao, P. Modic Changes and Disc Degeneration Caused by Inoculation of Propionibacterium acnes inside Intervertebral Discs of Rabbits: A Pilot Study. Biomed. Res. Int. 2016, 2016, 9612437. [Google Scholar] [CrossRef]
  161. Dudli, S.; Liebenberg, E.; Magnitsky, S.; Miller, S.; Demir-Deviren, S.; Lotz, J.C. Propionibacterium acnes infected intervertebral discs cause vertebral bone marrow lesions consistent with Modic changes. J. Orthop. Res. 2016, 34, 1447–1455. [Google Scholar] [CrossRef]
  162. Albert, H.B.; Sorensen, J.S.; Christensen, B.S.; Manniche, C. Antibiotic treatment in patients with chronic low back pain and vertebral bone edema (Modic type 1 changes): A double-blind randomized clinical controlled trial of efficacy. Eur. Spine J. 2013, 22, 697–707. [Google Scholar] [CrossRef]
  163. Farrar, M.D.; Ingham, E. Acne: Inflammation. Clin. Dermatol. 2004, 22, 380–384. [Google Scholar] [CrossRef] [PubMed]
  164. Albert, H.B.; Manniche, C.; Sorensen, J.S.; Deleuran, B.W. Antibiotic treatment in patients with low-back pain associated with Modic changes Type 1 (bone oedema): A pilot study. Br. J. Sports Med. 2008, 42, 969–973. [Google Scholar] [CrossRef] [PubMed]
  165. Braten, L.C.H.; Gjefsen, E.; Gervin, K.; Pripp, A.H.; Skouen, J.S.; Schistad, E.; Pedersen, L.M.; Wigemyr, M.; Selmer, K.K.; Aass, H.C.D.; et al. Cytokine Patterns as Predictors of Antibiotic Treatment Effect in Chronic Low Back Pain with Modic Changes: Subgroup Analyses of a Randomized Trial (AIM Study). J. Pain Res. 2023, 16, 1713–1724. [Google Scholar] [CrossRef]
  166. Braten, L.C.H.; Rolfsen, M.P.; Espeland, A.; Wigemyr, M.; Assmus, J.; Froholdt, A.; Haugen, A.J.; Marchand, G.H.; Kristoffersen, P.M.; Lutro, O.; et al. Efficacy of antibiotic treatment in patients with chronic low back pain and Modic changes (the AIM study): Double blind, randomised, placebo controlled, multicentre trial. BMJ 2019, 367, l5654. [Google Scholar] [CrossRef]
  167. Cheng, J.C.; Castelein, R.M.; Chu, W.C.; Danielsson, A.J.; Dobbs, M.B.; Grivas, T.B.; Gurnett, C.A.; Luk, K.D.; Moreau, A.; Newton, P.O.; et al. Adolescent idiopathic scoliosis. Nat. Rev. Dis. Primers 2015, 1, 15030. [Google Scholar] [CrossRef] [PubMed]
  168. Weinstein, S.L.; Dolan, L.A.; Spratt, K.F.; Peterson, K.K.; Spoonamore, M.J.; Ponseti, I.V. Health and function of patients with untreated idiopathic scoliosis: A 50-year natural history study. JAMA 2003, 289, 559–567. [Google Scholar] [CrossRef]
  169. Lau, K.K.L.; Law, K.K.P.; Kwan, K.Y.H.; Cheung, J.P.Y.; Cheung, K.M.C.; Wong, A.Y.L. Timely Revisit of Proprioceptive Deficits in Adolescent Idiopathic Scoliosis: A Systematic Review and Meta-Analysis. Glob. Spine J. 2022, 12, 1852–1861. [Google Scholar] [CrossRef]
  170. Wang, W.J.; Yeung, H.Y.; Chu, W.C.; Tang, N.L.; Lee, K.M.; Qiu, Y.; Burwell, R.G.; Cheng, J.C. Top theories for the etiopathogenesis of adolescent idiopathic scoliosis. J. Pediatr. Orthop. 2011, 31 (Suppl. S1), S14–S27. [Google Scholar] [CrossRef]
  171. Sun, Z.J.; Jia, H.M.; Qiu, G.X.; Zhou, C.; Guo, S.; Zhang, J.G.; Shen, J.X.; Zhao, Y.; Zou, Z.M. Identification of candidate diagnostic biomarkers for adolescent idiopathic scoliosis using UPLC/QTOF-MS analysis: A first report of lipid metabolism profiles. Sci. Rep. 2016, 6, 22274. [Google Scholar] [CrossRef]
  172. Lombardi, G.; Akoume, M.Y.; Colombini, A.; Moreau, A.; Banfi, G. Biochemistry of adolescent idiopathic scoliosis. Adv. Clin. Chem. 2011, 54, 165–182. [Google Scholar] [CrossRef]
  173. Wang, Y.J.; Yu, H.G.; Zhou, Z.H.; Guo, Q.; Wang, L.J.; Zhang, H.Q. Leptin Receptor Metabolism Disorder in Primary Chondrocytes from Adolescent Idiopathic Scoliosis Girls. Int. J. Mol. Sci. 2016, 17, 1160. [Google Scholar] [CrossRef]
  174. Yan, J.; Charles, J.F. Gut Microbiome and Bone: To Build, Destroy, or Both? Curr. Osteoporos. Rep. 2017, 15, 376–384. [Google Scholar] [CrossRef]
  175. Shen, N.; Chen, N.; Zhou, X.; Zhao, B.; Huang, R.; Liang, J.; Yang, X.; Chen, M.; Song, Y.; Du, Q. Alterations of the gut microbiome and plasma proteome in Chinese patients with adolescent idiopathic scoliosis. Bone 2019, 120, 364–370. [Google Scholar] [CrossRef] [PubMed]
  176. Goldenberg, D.L. Septic arthritis. Lancet 1998, 351, 197–202. [Google Scholar] [CrossRef] [PubMed]
  177. Ross, J.J.; Davidson, L. Methicillin-resistant Staphylococcus aureus septic arthritis: An emerging clinical syndrome. Rheumatology 2005, 44, 1197–1198. [Google Scholar] [CrossRef] [PubMed]
  178. Li, R.; Hatcher, J.D. Gonococcal Arthritis; StatPearls: Treasure Island, FL, USA, 2022. [Google Scholar]
  179. Antimicrobial Resistance, C. Global burden of bacterial antimicrobial resistance in 2019: A systematic analysis. Lancet 2022, 399, 629–655. [Google Scholar] [CrossRef]
  180. Bonnal, C.; Birgand, G.; Lolom, I.; Diamantis, S.; Dumortier, C.; L’Heriteau, F.; Armand-Lefevre, L.; Lucet, J.C. Staphylococcus aureus healthcare associated bacteraemia: An indicator of catheter related infections. Med. Mal. Infect. 2015, 45, 84–88. [Google Scholar] [CrossRef]
  181. Ferry, T.; Perpoint, T.; Vandenesch, F.; Etienne, J. Virulence determinants in Staphylococcus aureus and their involvement in clinical syndromes. Curr. Infect. Dis. Rep. 2005, 7, 420–428. [Google Scholar] [CrossRef] [PubMed]
  182. Peterson, T.C.; Pearson, C.; Zekaj, M.; Hudson, I.; Fakhouri, G.; Vaidya, R. Septic arthritis in intravenous drug abusers: A historical comparison of habits and pathogens. J. Emerg. Med. 2014, 47, 723–728. [Google Scholar] [CrossRef]
  183. Vardakas, K.Z.; Kontopidis, I.; Gkegkes, I.D.; Rafailidis, P.I.; Falagas, M.E. Incidence, characteristics, and outcomes of patients with bone and joint infections due to community-associated methicillin-resistant Staphylococcus aureus: A systematic review. Eur. J. Clin. Microbiol. Infect. Dis. 2013, 32, 711–721. [Google Scholar] [CrossRef] [PubMed]
  184. Helito, C.P.; Zanon, B.B.; Miyahara Hde, S.; Pecora, J.R.; Lima, A.L.; Oliveira, P.R.; Vicente, J.R.; Demange, M.K.; Camanho, G.L. Clinical and epidemiological differences between septic arthritis of the knee and hip caused by oxacillin-sensitive and -resistant S. aureus. Clinics 2015, 70, 30–33. [Google Scholar] [CrossRef] [PubMed]
  185. Mohanty, N.; Misra, S.; Sahoo, S.; Mishra, S.; Vasudevan, V.; Subramanian, K. Rhinomaxillary Mucormycosis Masquerading as Chronic Osteomyelitis: A Series of Four Rare Cases with Review of Literature. J. Indian Acad. Oral Med. Radiol. 2012, 24, 315–323. [Google Scholar] [CrossRef]
  186. Kremers, H.M.; Nwojo, M.E.; Ransom, J.E.; Wood-Wentz, C.M.; Melton, L.J., 3rd; Huddleston, P.M., 3rd. Trends in the epidemiology of osteomyelitis: A population-based study, 1969 to 2009. J. Bone Jt. Surgery. Am. 2015, 97, 837–845. [Google Scholar] [CrossRef]
  187. Cunha, B. Osteomyelitis in Elderly Patients. Clin. Infect. Dis. 2002, 35, 287–293. [Google Scholar] [CrossRef]
  188. Romanò, C.L.; Logoluso, N.; Elia, A.; Romanò, D. Osteomyelitis in elderly patients. BMC Geriatr. 2010, 10, L15. [Google Scholar] [CrossRef]
  189. Rana, A.; Rabbani, N.U.A.; Wood, S.; McCorkle, C.; Gilkerson, C. A Complicated Case of Vertebral Osteomyelitis by Serratia Marcescens. Cureus 2020, 12, e9002. [Google Scholar] [CrossRef]
  190. Mauffrey, C.; Bailey, J.R.; Bowles, R.J.; Price, C.; Hasson, D.; Hak, D.J.; Stahel, P.F. Acute management of open fractures: Proposal of a new multidisciplinary algorithm. Orthopedics 2012, 35, 877–881. [Google Scholar] [CrossRef]
  191. Zeus, M.; Janssen, S.; Laws, H.J.; Fischer, U.; Borkhardt, A.; Oommen, P.T. Results from a pilot study on the oral microbiome in children and adolescents with chronic nonbacterial osteomyelitis. Z. Für Rheumatol. 2023, 82, 123–133. [Google Scholar] [CrossRef]
  192. Johani, K.; Fritz, B.G.; Bjarnsholt, T.; Lipsky, B.A.; Jensen, S.O.; Yang, M.; Dean, A.; Hu, H.; Vickery, K.; Malone, M. Understanding the microbiome of diabetic foot osteomyelitis: Insights from molecular and microscopic approaches. Clin. Microbiol. Infect. 2019, 25, 332–339. [Google Scholar] [CrossRef] [PubMed]
  193. Meng, J.; Zhu, Y.; Li, Y.; Sun, T.; Zhang, F.; Qin, S.; Zhao, H. Incidence and risk factors for surgical site infection following elective foot and ankle surgery: A retrospective study. J. Orthop. Surg. Res. 2020, 15, 449. [Google Scholar] [CrossRef] [PubMed]
  194. Deng, H.; Chan, A.K.; Ammanuel, S.; Chan, A.Y.; Oh, T.; Skrehot, H.C.; Edwards, S.; Kondapavulur, S.; Nichols, A.D.; Liu, C.; et al. Risk factors for deep surgical site infection following thoracolumbar spinal surgery. J. Neurosurg. Spine 2019, 32, 292–301. [Google Scholar] [CrossRef] [PubMed]
  195. Gernaat-van der Sluis, A.J.; Hoogenboom-Verdegaal, A.M.; Edixhoven, P.J.; Spies-van Rooijen, N.H. Prophylactic mupirocin could reduce orthopedic wound infections. 1,044 patients treated with mupirocin compared with 1,260 historical controls. Acta Orthop. Scand. 1998, 69, 412–414. [Google Scholar] [CrossRef]
  196. Kalmeijer, M.D.; van Nieuwland-Bollen, E.; Bogaers-Hofman, D.; de Baere, G.A. Nasal carriage of Staphylococcus aureus is a major risk factor for surgical-site infections in orthopedic surgery. Infect. Control Hosp. Epidemiol. 2000, 21, 319–323. [Google Scholar] [CrossRef]
  197. Nakamura, M.; Shimakawa, T.; Nakano, S.; Chikawa, T.; Yoshioka, S.; Kashima, M.; Toki, S.; Sairyo, K. Screening for nasal carriage of Staphylococcus aureus among patients scheduled to undergo orthopedic surgery: Incidence of surgical site infection by nasal carriage. J. Orthop. Sci. 2017, 22, 778–782. [Google Scholar] [CrossRef]
  198. Kapsalaki, E.; Gatselis, N.; Stefos, A.; Makaritsis, K.; Vassiou, A.; Fezoulidis, I.; Dalekos, G.N. Spontaneous spondylodiscitis: Presentation, risk factors, diagnosis, management, and outcome. Int. J. Infect. Dis. 2009, 13, 564–569. [Google Scholar] [CrossRef]
  199. Kim, C.J.; Song, K.H.; Jeon, J.H.; Park, W.B.; Park, S.W.; Kim, H.B.; Oh, M.D.; Choe, K.W.; Kim, N.J. A comparative study of pyogenic and tuberculous spondylodiscitis. Spine 2010, 35, E1096–E1100. [Google Scholar] [CrossRef]
  200. Tali, E.T. Spinal infections. Eur. J. Radiol. 2004, 50, 120–133. [Google Scholar] [CrossRef]
  201. Cottle, L.; Riordan, T. Infectious spondylodiscitis. J. Infect. 2008, 56, 401–412. [Google Scholar] [CrossRef]
  202. Jimenez-Mejias, M.E.; de Dios Colmenero, J.; Sanchez-Lora, F.J.; Palomino-Nicas, J.; Reguera, J.M.; Garcia de la Heras, J.; Garcia-Ordonez, M.A.; Pachon, J. Postoperative spondylodiskitis: Etiology, clinical findings, prognosis, and comparison with nonoperative pyogenic spondylodiskitis. Clin. Infect. Dis. 1999, 29, 339–345. [Google Scholar] [CrossRef] [PubMed]
  203. Hopkinson, N.; Stevenson, J.; Benjamin, S. A case ascertainment study of septic discitis: Clinical, microbiological and radiological features. QJM 2001, 94, 465–470. [Google Scholar] [CrossRef] [PubMed]
  204. Boody, B.S.; Jenkins, T.J.; Maslak, J.; Hsu, W.K.; Patel, A.A. Vertebral Osteomyelitis and Spinal Epidural Abscess: An Evidence-based Review. J. Spinal Disord. Tech. 2015, 28, E316–E327. [Google Scholar] [CrossRef]
  205. Gouliouris, T.; Aliyu, S.H.; Brown, N.M. Spondylodiscitis: Update on diagnosis and management. J. Antimicrob. Chemother. 2010, 65 (Suppl. S3), iii11–iii24. [Google Scholar] [CrossRef] [PubMed]
  206. Al-Nammari, S.S.; Lucas, J.D.; Lam, K.S. Hematogenous methicillin-resistant Staphylococcus aureus spondylodiscitis. Spine 2007, 32, 2480–2486. [Google Scholar] [CrossRef]
  207. Hadjipavlou, A.G.; Mader, J.T.; Necessary, J.T.; Muffoletto, A.J. Hematogenous pyogenic spinal infections and their surgical management. Spine 2000, 25, 1668–1679. [Google Scholar] [CrossRef]
  208. Di Martino, A.; Papapietro, N.; Lanotte, A.; Russo, F.; Vadala, G.; Denaro, V. Spondylodiscitis: Standards of current treatment. Curr. Med. Res. Opin. 2012, 28, 689–699. [Google Scholar] [CrossRef]
  209. D’Agostino, C.; Scorzolini, L.; Massetti, A.P.; Carnevalini, M.; d’Ettorre, G.; Venditti, M.; Vullo, V.; Orsi, G.B. A seven-year prospective study on spondylodiscitis: Epidemiological and microbiological features. Infection 2010, 38, 102–107. [Google Scholar] [CrossRef]
  210. Zhou, C.; Zhao, H.; Xiao, X.-Y.; Chen, B.-D.; Guo, R.-J.; Wang, Q.; Chen, H.; Zhao, L.-D.; Zhang, C.-C.; Jiao, Y.-H.; et al. Metagenomic profiling of the pro-inflammatory gut microbiota in ankylosing spondylitis. J. Autoimmun. 2020, 107, 102360. [Google Scholar] [CrossRef]
  211. Zhang, L.; Hu, Y.; Xu, Y.; Li, P.; Ma, H.; Li, X.; Li, M. The correlation between intestinal dysbiosis and the development of ankylosing spondylitis. Microb. Pathog. 2019, 132, 188–192. [Google Scholar] [CrossRef]
  212. Turner, M.J.; Sowders, D.P.; DeLay, M.L.; Mohapatra, R.; Bai, S.; Smith, J.A.; Brandewie, J.R.; Taurog, J.D.; Colbert, R.A. HLA-B27 misfolding in transgenic rats is associated with activation of the unfolded protein response. J. Immunol. 2005, 175, 2438–2448. [Google Scholar] [CrossRef] [PubMed]
  213. Ciccia, F.; Accardo-Palumbo, A.; Rizzo, A.; Guggino, G.; Raimondo, S.; Giardina, A.; Cannizzaro, A.; Colbert, R.A.; Alessandro, R.; Triolo, G. Evidence that autophagy, but not the unfolded protein response, regulates the expression of IL-23 in the gut of patients with ankylosing spondylitis and subclinical gut inflammation. Ann. Rheum. Dis. 2014, 73, 1566–1574. [Google Scholar] [CrossRef] [PubMed]
  214. Ciccia, F.; Rizzo, A.; Triolo, G. Subclinical gut inflammation in ankylosing spondylitis. Curr. Opin. Rheumatol. 2016, 28, 89–96. [Google Scholar] [CrossRef] [PubMed]
  215. Chen, Z.; Zheng, X.; Wu, X.; Wu, J.; Li, X.; Wei, Q.; Zhang, X.; Fang, L.; Jin, O.; Gu, J. Adalimumab Therapy Restores the Gut Microbiota in Patients With Ankylosing Spondylitis. Front. Immunol. 2021, 12, 700570. [Google Scholar] [CrossRef] [PubMed]
  216. Minerbi, A.; Gonzalez, E.; Brereton, N.J.B.; Anjarkouchian, A.; Dewar, K.; Fitzcharles, M.-A.; Chevalier, S.; Shir, Y. Altered microbiome composition in individuals with fibromyalgia. Pain 2019, 160, 2589–2602. [Google Scholar] [CrossRef] [PubMed]
  217. Cassisi, G.; Sarzi-Puttini, P.; Cazzola, M. Chronic widespread pain and fibromyalgia: Could there be some relationships with infections and vaccinations? Clin. Exp. Rheumatol. 2011, 29 (Suppl. S69), S118–S126. [Google Scholar]
  218. Giacomelli, C.; Sernissi, F.; Rossi, A.; Bombardieri, S.; Bazzichi, L. Biomarkers in fibromyalgia: A review. Curr. Biomark. Find. 2014, 4, 35. [Google Scholar] [CrossRef]
  219. Albrecht, D.S.; Forsberg, A.; Sandström, A.; Bergan, C.; Kadetoff, D.; Protsenko, E.; Lampa, J.; Lee, Y.C.; Höglund, C.O.; Catana, C.; et al. Brain glial activation in fibromyalgia—A multi-site positron emission tomography investigation. Brain Behav. Immun. 2019, 75, 72–83. [Google Scholar] [CrossRef]
  220. Kendler, K.S.; Rosmalen, J.G.M.; Ohlsson, H.; Sundquist, J.; Sundquist, K. A distinctive profile of family genetic risk scores in a Swedish national sample of cases of fibromyalgia, irritable bowel syndrome, and chronic fatigue syndrome compared to rheumatoid arthritis and major depression. Psychol. Med. 2022, 53, 3879–3886. [Google Scholar] [CrossRef]
  221. Clos-Garcia, M.; Andres-Marin, N.; Fernandez-Eulate, G.; Abecia, L.; Lavin, J.L.; van Liempd, S.; Cabrera, D.; Royo, F.; Valero, A.; Errazquin, N.; et al. Gut microbiome and serum metabolome analyses identify molecular biomarkers and altered glutamate metabolism in fibromyalgia. EBioMedicine 2019, 46, 499–511. [Google Scholar] [CrossRef]
  222. Wang, Y.; Wei, J.; Zhang, W.; Doherty, M.; Zhang, Y.; Xie, H.; Li, W.; Wang, N.; Lei, G.; Zeng, C. Gut dysbiosis in rheumatic diseases: A systematic review and meta-analysis of 92 observational studies. EBioMedicine 2022, 80, 104055. [Google Scholar] [CrossRef] [PubMed]
  223. Zhou, Z.; Hui, E.S.; Kranz, G.S.; Chang, J.R.; de Luca, K.; Pinto, S.M.; Chan, W.W.; Yau, S.Y.; Chau, B.K.; Samartzis, D.; et al. Potential mechanisms underlying the accelerated cognitive decline in people with chronic low back pain: A scoping review. Ageing Res. Rev. 2022, 82, 101767. [Google Scholar] [CrossRef] [PubMed]
  224. Stecher, B.; Maier, L.; Hardt, W.-D. ‘Blooming’ in the gut: How dysbiosis might contribute to pathogen evolution. Nat. Rev. Microbiol. 2013, 11, 277–284. [Google Scholar] [CrossRef]
  225. Clayton, T.A.; Baker, D.; Lindon, J.C.; Everett, J.R.; Nicholson, J.K. Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism. Proc. Natl. Acad. Sci. USA 2009, 106, 14728–14733. [Google Scholar] [CrossRef] [PubMed]
  226. Zhang, G.; Qin, L.; Shi, Y. Epimedium-derived phytoestrogen flavonoids exert beneficial effect on preventing bone loss in late postmenopausal women: A 24-month randomized, double-blind and placebo-controlled trial. J. Bone Miner. Res. 2007, 22, 1072–1079. [Google Scholar] [CrossRef] [PubMed]
  227. Zhou, J.; Ma, Y.H.; Zhou, Z.; Chen, Y.; Wang, Y.; Gao, X. Intestinal Absorption and Metabolism of Epimedium Flavonoids in Osteoporosis Rats. Drug Metab. Dispos. 2015, 43, 1590–1600. [Google Scholar] [CrossRef] [PubMed]
  228. Zhu, H.M.; Qin, L.; Garnero, P.; Genant, H.K.; Zhang, G.; Dai, K.; Yao, X.; Gu, G.; Hao, Y.; Li, Z.; et al. The first multicenter and randomized clinical trial of herbal Fufang for treatment of postmenopausal osteoporosis. Osteoporos. Int. 2012, 23, 1317–1327. [Google Scholar] [CrossRef]
  229. Höllriegl, V.; Röhmuss, M.; Oeh, U.; Roth, P. Strontium biokinetics in humans: Influence of alginate on the uptake of ingested strontium. Health Phys. 2004, 86, 193–196. [Google Scholar] [CrossRef]
  230. Kalyan, S.; Wang, J.; Quabius, E.S.; Huck, J.; Wiltfang, J.; Baines, J.F.; Kabelitz, D. Systemic immunity shapes the oral microbiome and susceptibility to bisphosphonate-associated osteonecrosis of the jaw. J. Transl. Med. 2015, 13, 212. [Google Scholar] [CrossRef]
Table 1. Microbiome and musculoskeletal disorders in human studies.
Table 1. Microbiome and musculoskeletal disorders in human studies.
AuthorPopulation SizePopulation CharacteristicsMales:FemalesMicrobeMusculoskeletal DisorderFindings
Cardoneanu et al. (2021) [24]6032 healthy controls, 28 ankylosing spondylitis29:31Several microbesAnkylosing SpondylitisDecreased intestinal bacterial diversity ankylosing spondylitis patients compared to control
Das et al. (2019) [17]181Older adults13:17Several microbesOsteoporosisDifferent gut microbiota profiles were found to be associated with osteopenic, osteoporotic, and normal bone mass density
Fritzell et al. (2019) [25]6040 adults with lumbar disc herniation/lower back pain, 20 control patients with scoliosis30:30Cutibacterium acnesDegenerative discC. acnes found in discs and vertebrae during surgery for disc herniation
Nilsson et al. (2018) [18]90Elderly women between the ages of 75 and 80 who have diminished bone mineral density0:90Lactobacillus
reuteri
OsteoporosisL. reuteri reduces total bone mass density compared to the placebo
Rajasekaran et al. (2017) [26]2215-disc herniations, 5-
degenerate, 2-normal in MRI
15:7Propionibacterium acnesProteome in intervertebral discsSpecific bacterial and host defense proteins were present in intervertebral discs
Rajasekaran et al. (2019) [27]6 control discs, 5 degenerated
discs
Group A (young 2nd–4th decades), Group B (aging. 5th–7th decade), Group C (degenerative discs)4:7---Degenerative DiscUnique proteome signatures of bacteria in discs of young, aging, and degenerative discs
Rajasekaran et al. (2020) [28]248- brain-dead but living organ donors had healthy MRI discs, 8 had herniated discs, 8-disc degeneration15:9Several microbesDegenerative discDistinct microbiome profiles in patients with healthy disc, disc herniations, and degenerative disc
Rao et al. (2020) [29]812NANACutibacterium acnesDegenerative discThe research did not reveal any distinction in actual infection rates between the groups with non-degenerative and degenerative discs
Rettedal et al. (2020) [30]86All postmenopausal women: 18 osteoporosis, 42 osteopenia, 26 healthy controls0:86BacteroidesOsteoporosisBacteroides taxa were more abundant in both osteopenia and osteoporosis
Scher et al. (2013) [31]114Rheumatoid Arthritis11:33Prevotella copriRheumatoid ArthritisP. copri in stool is correlated with new onset untreated.
rheumatoid arthritis
Scher et al. (2016) [15]58Rheumatoid Arthritis, Sarcoidosis, Control43:25PseudonocardiaRheumatoid Arthritis, SarcoidosisThe composition of gut microbiota in individuals with rheumatoid arthritis and sarcoidosis was significantly decreased and is less varied in comparison to individuals without health issues
Wang et al. (2017) [19]186 adults with primary osteoporosis, 6 with primary osteopenia, and 6 normal controls3:15Firmicutes and BacteroidetesOsteoporosisOsteoporosis individuals contained an increased proportion of Firmicutes phyla but decreased proportion of Bacteroidetes compared to the control
Xu et al. (2020) [20]9648 primary osteoporosis patients and 48 healthy37:59Faecalibacterium and dialisterOsteoporosisIncrease in abundance of Faecalibacterium and dialister in patients with primary Osteoporosis
Table 2. Microbiome and musculoskeletal disorders in animal studies.
Table 2. Microbiome and musculoskeletal disorders in animal studies.
AuthorSample SizeInterventionMSK DisorderResult
Guss et al. (2019) [32]6–7 mice per group, 2 groupsOral antibiotics vs. untreatedOsteoporosisThe decrease in microbiota synthesized vitamin K from the antibiotics led to a decrease in bone matrix quality
Guss et al. (2019) [32]10–11 mice group 2 groupsToll-le mceptor-5 deficient miceOsteoarthritisGut microbiome may influence cartilage pathology
Hemandez et al. (2019) [33]82 (40 modified microbiome, 42 untreated)A tibial implant made of titanium, along with the introduction of Staphylococcus aureus in the synovial space.Periprosthetic joint infectionGut microbiota may influence susceptibility to periprosthetic joint infection The composition of gut microbiota could impact one’s vulnerability to periprosthetic joint infection
Li et al. (2016) [34]10 mice per group 2 groupsControl vs. ProbioticsOsteoporosisThe microbiota within the gut lumen and heightened gut permeability contribute to the initiation of inflammatory pathways that are essential in causing bone loss in mice lacking sex steroids
Sjogren et al. (2012) [35]485 miceGerm free mice vs conventionally raised miceOsteoporosisIn mice, the gut microbiota manages bone density by decreasing the production of inflammatory cytokines in both bone and bone marrow.
Wang et al. (2021) [36]12 mice per group, 4 groupsControl, Control + L. paracasei S16 probiotic, Lumbar Doc Herniation (LDH), LDH+ L. paracasei S16 probioticsLumbar Disc Herniation (Low Back Pain)L. paracasei S16 has the potential to alleviate LDH symptoms through the reduction of inflammation, modifications in gut microbiota, and alterations in serum metabolite
Yan et al. (2016) [37]6 miceControl vs. AntibioticsOsteoporosisThe gut microbiota negatively impacts bone health, likely through IGF-1 mediation, causing a net anabolic deficit
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Aboushaala, K.; Wong, A.Y.L.; Barajas, J.N.; Lim, P.; Al-Harthi, L.; Chee, A.; Forsyth, C.B.; Oh, C.-d.; Toro, S.J.; Williams, F.M.K.; et al. The Human Microbiome and Its Role in Musculoskeletal Disorders. Genes 2023, 14, 1937. https://doi.org/10.3390/genes14101937

AMA Style

Aboushaala K, Wong AYL, Barajas JN, Lim P, Al-Harthi L, Chee A, Forsyth CB, Oh C-d, Toro SJ, Williams FMK, et al. The Human Microbiome and Its Role in Musculoskeletal Disorders. Genes. 2023; 14(10):1937. https://doi.org/10.3390/genes14101937

Chicago/Turabian Style

Aboushaala, Khaled, Arnold Y. L. Wong, Juan Nicolas Barajas, Perry Lim, Lena Al-Harthi, Ana Chee, Christopher B. Forsyth, Chun-do Oh, Sheila J. Toro, Frances M. K. Williams, and et al. 2023. "The Human Microbiome and Its Role in Musculoskeletal Disorders" Genes 14, no. 10: 1937. https://doi.org/10.3390/genes14101937

APA Style

Aboushaala, K., Wong, A. Y. L., Barajas, J. N., Lim, P., Al-Harthi, L., Chee, A., Forsyth, C. B., Oh, C. -d., Toro, S. J., Williams, F. M. K., An, H. S., & Samartzis, D. (2023). The Human Microbiome and Its Role in Musculoskeletal Disorders. Genes, 14(10), 1937. https://doi.org/10.3390/genes14101937

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop