Search Results (32)

Major depressive disorder (MDD) is one of the most common diseases, affecting millions of people worldwide. Existing antidepressants do not allow sustainable remission to be achieved in many cases, probably due to insufficient understanding of the etiopathogenesis of MDD. The aim of this study was to identify the key genes, pathways, and master regulators associated with MDD based on a combination of genomic and transcriptomic data analyses. We performed a transcriptome-wide association study (TWAS) to identify the increase and decrease in transcription of particular genes that can be associated with MDD risk, the results of which were used to perform a pathway enrichment analysis that elucidated the pathways and processes associated with MDD. Besides changes in the metabolism of neurotransmitters, the association of some other processes with MDD was revealed, including changes in phospholipid and glycan metabolism, chromatin remodeling, RNA processing and splicing, and cell–extracellular matrix interaction. The transcriptomic analysis performed for brain regions mostly confirmed genome-level findings. The gene expression changes in the brain related to MDD were mostly sex-specific, and the transcription of many genes was changed in the opposite direction in males and females. Finally, master regulators were found, which are the proteins responsible for the transcriptional regulation of the revealed genes and represent the most important proteins contributing to MDD development. Full article

As the laying cycle is prolonged, the egg albumen quality exhibits a declining trend. A Haugh unit (HU) is a standard measure of the albumen quality, which reflects viscosity and freshness. During the late laying period, the HU not only decreased significantly, but also exhibited greater variability among individuals. The magnum, as the primary site of albumen synthesis, plays a central role in this process; however, the mechanisms by which it regulates the albumen quality remain unclear. To address this, we obtained genomic and transcriptomic data from 254 individuals, along with single-cell RNA sequencing (scRNA-seq) data of the magnum tissue. Genome-wide association studies (GWAS) across five laying stages (66, 72, 80, 90, and 100 weeks of age) identified 77 HU-associated single-nucleotide polymorphisms (SNPs). Expression quantitative trait locus (eQTL) mapping linked these variants to the expression of 12 genes in magnum tissue. In addition, transcriptomic analysis using linear regression and random forest models identified 259 genes that significantly correlated with the HU. Single-cell RNA sequencing further revealed two key cell types, plasma cells and a subset of epithelial cells, marked by ADAMTSL1 and OVAL, which are functionally relevant to the HU. Through integrated Transcriptome-Wide Association Study (TWAS) and Summary-data-based Mendelian Randomization (SMR) analyses, we identified four robust regulators of the albumen quality: CISD1, NQO2, SLC22A23, and CMTM6. These genes are functionally involved in mitochondrial function, antioxidant defense, and membrane transport. Overall, our findings uncovered the genetic and cellular mechanisms underlying age-related decline in the albumen quality and identified potential targets for improving the egg quality in aging flocks. Full article

Background/Objectives: The anti-Müllerian hormone (AMH) is a key biomarker of the ovarian reserve, correlating with ovarian follicle count, fertility outcomes, and menopause timing. Understanding its genetic determinants has broad implications for female reproductive health. However, prior genome-wide association studies (GWASs) have focused exclusively on women of European ancestry, limiting insights into diverse populations. Methods: We conducted a GWAS to identify genetic loci associated with circulating AMH levels in a sample of 1185 Samoan women from two independently recruited samples. Using a Cox mixed-effects model we accounted for AMH levels below detectable limits and meta-analysed the summary statistics using a fixed-effect model. To prioritize variants and genes, we used FUMA and performed colocalization and transcriptome-wide association analysis (TWAS). We also assessed whether any previously reported loci were replicated in our GWAS. Results: We identified eleven genome-wide suggestive loci, with the strongest signal at ARID3A (19-946163-G-C; p = 2.32 × 10⁻⁷) and replicated rs10093345 near EIF4EBP1. The gene-based testing revealed ARID3A and R3HDM4 as significant genes. Integrating GWAS results with expression quantitative trait loci via TWAS, we detected seven transcriptome-wide significant genes. The lead variant in ARID3A is in high linkage disequilibrium (r² = 0.79) with the known age-at-menopause variant 19-950694-G-A. Nearby KISS1R is a biologically plausible candidate gene that encodes the kisspeptin receptor, a regulator of ovarian follicle development linked to AMH levels. Conclusions: This study expands our understandings of AMH genetics by focusing on Samoan women. While these findings may be particularly relevant to Pacific Islanders, they hold broader implications for reproductive phenotypes such as the ovarian reserve, menopause timing, and polycystic ovary syndrome. Full article

Background: Obesity significantly impacts disease burden, with waist-to-hip ratio (WHR) as a key obesity indicator, but the genetic and biological pathways underlying WHR, particularly its sex-specific differences, remain poorly understood. Methods: This study explored WHR’s sexual dimorphism and its links to complex traits using cross-sectional surveys and genetic data from Giant and UK Biobank (UKB). We analyzed WHR heritability, performed tissue-specific transcriptome-wide association studies (TWAS) using FUSION, and conducted genetic correlation analyses with linkage disequilibrium score regression (LDSC) and Local Analysis of [co]Variant Association (LAVA). Polygenic scores (PGS) for WHR were constructed using the clumping and thresholding method (CT), and associations with complex traits were assessed via logistic or linear models. Results: The genetic analysis showed sex-specific heritability for WHR, with TWAS identifying female-specific (e.g., CCDC92) and male-specific (e.g., UQCC1) genes. Global genetic correlation analysis revealed sex-specific associations between WHR and 23 traits, while local analysis identified eight sex-specific loci across five diseases. Regression analysis highlighted sex-specific associations for 70 traits with WHR and 45 traits with WHR PGS, with stronger effects in females. Predictive models also performed better in females. Conclusions: This study underscores WHR’s sexual dimorphism and its distinct associations with complex traits, offering insights into sex-specific biological differences, health management, and clinical advancements. Full article

Background/Objectives: Diabetic kidney disease (DKD) is a common diabetic complication, driven by a multifactorial pathogenesis that includes various genetic components. However, the precise causative genes and their underlying biological pathways remain poorly understood. Methods: We performed a cross-tissue transcriptome-wide association study (TWAS) of DKD using expression quantitative trait loci (eQTL) data from 49 tissues in the Genotype—Tissue Expression (GTEx) version 8 (v8) resource. Five complementary analytical frameworks—sparse canonical correlation analysis (sCCA), functional summary-based imputation (FUSION), fine-mapping of causal gene sets (FOCUS), summary-data-based Mendelian randomization (SMR), and multi-marker analysis of genomic annotation (MAGMA)—were integrated to nominate candidate genes. Causal inference was refined using Mendelian randomization (MR), and biological significance was evaluated through pathway enrichment, protein interaction networks, and druggability profiling. Results: We identified 23 candidate genes associated with DKD risk, of which 13 were supported by MR analysis. Among these, 10 represent previously unreported susceptibility genes. Notably, four genes—HLA-DRB1, HLA-DRB5, NOTCH4, and CYP21A2—encode potentially druggable proteins, with HLA-DRB5 and CYP21A2 both qualifying as novel susceptibility genes and therapeutic targets. These genes converge on immune modulation, steroid biosynthesis, DNA repair, and transcriptional regulation—processes central to DKD pathogenesis. Conclusions: Our study represents the first systematic cross-tissue TWAS of DKD, revealing a prioritized set of genetically and functionally supported susceptibility genes. The identification of druggable targets among these genes provides critical insight into the mechanistic underpinnings of DKD and highlights their potential for future therapeutic development. These findings enhance our understanding of DKD pathophysiology and offer a foundation for precision medicine strategies in nephrology. Full article

Background: Multiple myeloma (MM) is a hematological malignancy originating from the plasma cells present in the bone marrow. Despite significant therapeutic advancements, relapse and drug resistance remain major clinical challenges, highlighting the urgent need for novel therapeutic targets. Methods: To identify potential druggable genes associated with MM, we performed Mendelian randomization (MR) analysis. Causal candidates were further validated using a single-tissue transcriptome-wide association study (TWAS), and colocalization analysis was conducted to assess shared genetic signals between gene expression and disease risk. Potential off-target effects were assessed through an MR phenome-wide association study (MR-PheWAS). Additionally, molecular docking and functional assays were used to evaluate candidate drug efficacy. Results: The MR analysis identified nine druggable genes (FDR < 0.05), among which Orosomucoid 1 (ORM1) and Oviductal Glycoprotein 1 (OVGP1) were supported by both TWAS and colocalization evidence (PPH4 > 0.75). Experimental validation demonstrated the significant downregulation of ORM1 and OVGP1 in MM cells (p < 0.05). Pregnenolone and irinotecan, identified as agonists of ORM1 and OVGP1, respectively, significantly inhibited MM cell viability, while upregulating their expression (p < 0.05). Conclusions: Our study highlights ORM1 and OVGP1 as novel therapeutic targets for MM. The efficacy of pregnenolone and irinotecan in suppressing MM cell growth suggests their potential for clinical application. These findings provide insights into MM pathogenesis and offer a promising strategy for overcoming drug resistance. Full article

Crohn’s disease (CD) is a chronic inflammatory disorder with potential progression to stricturing (B2) or penetrating (B3) phenotypes, leading to significant complications. Early identification of patients at risk for these complications is critical for personalized management. This study aimed to develop a predictive model using clinical data and a Korean-specific transcriptome-wide association study (TWAS) to forecast early progression in CD patients. A retrospective analysis of 430 Korean CD patients from 15 hospitals was conducted. Genotyping was performed using the Korea Biobank Array, and gene expression predictions were derived from a TWAS model based on terminal ileum data. Logistic regression models incorporating clinical and gene expression data predicted progression to B2 or B3 within 24 months of diagnosis. Among the cohort, 13.9% (60 patients) progressed to B2 and 16.9% (73 patients) to B3. The combined model achieved mean area under the curve (AUC) values of 0.788 for B2 and 0.785 for B3 progression. Key predictive genes for B2 included CCDC154, FAM189A2, and TAS2R19, while PUS7, CCDC146, and MLXIP were linked to B3 progression. This integrative model provides a robust approach for identifying high-risk CD patients, potentially enabling early, targeted interventions to reduce disease progression and associated complications. Full article

Genetic variants increase the risk of neurocognitive disorders in later life, including vascular dementia (VaD) and Alzheimer’s disease (AD), but the precise relationships between genetic risk factors and underlying disease etiologies are not well understood. Transcriptome-wide association studies (TWASs) can be leveraged to better characterize the genes and biological pathways underlying genetic influences on disease. To date, almost all existing TWASs on VaD and AD have been conducted using expression studies from individuals of a single genetic ancestry, primarily European. Using the joint likelihood-based inference framework in Multi-ancEstry TRanscriptOme-wide analysis (METRO), we leveraged gene expression data from European ancestry (EA) and African ancestry (AA) samples to identify genes associated with general cognitive function, white matter hyperintensity (WMH), and AD. Regions were fine-mapped using Fine-mapping Of CaUsal gene Sets (FOCUS). We identified 266, 23, 69, and 2 genes associated with general cognitive function, WMH, AD (using EA GWAS summary statistics), and AD (using AA GWAS), respectively (Bonferroni-corrected alpha = p < 2.9 × 10⁻⁶), some of which had been previously identified. Enrichment analysis showed that many of the identified genes were in pathways related to innate immunity, vascular dysfunction, and neuroinflammation. Further, the downregulation of ICA1L was associated with a higher WMH and with AD, indicating its potential contribution to overlapping AD and VaD neuropathology. To our knowledge, our study is the first TWAS on cognitive function and neurocognitive disorders that used expression mapping studies for multiple ancestries. This work may expand the benefits of TWASs beyond a single ancestry group and help to identify gene targets for pharmaceuticals or preventative treatments for dementia. Full article

Objective: To unveil the efficacy and ferroptosis-related mechanisms of Atractylodes Macrocephala Koidz (AMK) against Alzheimer’s disease (AD), which is the most widespread neurodegenerative disease. Methods: Gene set variation analysis (GSVA) scores were used to investigate the relationship between ferroptosis and AD. Logistic regression with seven feature selections and a deep learning model were utilized to identify potential targets of AMK based on transcriptomic data from multiple tissues. A transcriptome-wide association study (TWAS), summary-data-based mendelian randomization (SMR), and mendelian randomization (MR) were utilized to validate the causal relationship between target genes and AD risk. A single-gene gene set enrichment analysis (GSEA) was employed to investigate the biological pathways associated with the target genes. Three molecular docking strategies and a molecular dynamics simulation were employed to verify the binding domains interacting with AMK. Furthermore, the anti-AD effects of AMK were validated in a zebrafish AD model by testing behavior responses, apoptosis, and the deposition of beta-amyloid (Aβ) in the brain. Ultimately, real-time qPCR was used to verify the ferroptosis-related targets, which was identified via multi-omics. Results: Ferroptosis is an important pathogenic mechanism of AD, as suggested by the GSVA scores. AMK may exert its anti-AD activity through targets genes identified in the brain (ATP5MC3, GOT1, SAT1, EGFR, and MAPK9) and blood (G6PD, PGD, ALOX5, HMOX1, and ULK1). EGFR and HMOX1 were further confirmed as target genes mediating the anti-AD activity of AMK through TWAS, SMR, and MR analyses. The GSEA results indicated that EGFR may be involved in oxidative phosphorylation-related pathways, while HMOX1 may be associated with lysosome and phagosome pathways. The results of three molecular docking strategies and molecular dynamics simulations implied that the kinase domain of EGFR and the catalytic domain of HMOX1 played pivotal roles in the interaction between AMK and the targets. In a zebrafish model, AD-like symptoms including motor slowness and delayed responses, neuronal apoptosis, and plaque deposition in the brain, were significantly improved after AMK treatment. Accordingly, AMK reversed the abnormal expression of egfra and hmox1a, two core targets genes involved in ferroptosis. Conclusions: AMK significantly alleviated AD-like symptoms through the modulation of EGFR and HMOX1, which might reduce lipid peroxidation, thereby suppressing ferroptosis. This study provided evidence supporting the efficacy and therapeutic targets associated with ferroptosis in AMK-treated AD, which aid in the development of therapeutic interventions. Full article

Endometriosis (EMT) is a common gynecological disease with a strong genetic component, while its precise etiology remains elusive. This study aims to integrate transcriptome-wide association study (TWAS), Mendelian randomization (MR), and bioinformatics analyses to reveal novel putatively causal genes and potential mechanisms. We obtained summary-level data of the Genotype-Tissue Expression Project (GTEx), v8 expression quantitative loci (eQTL) data, and the genome-wide association study (GWAS) data of EMT and its subtypes from the R11 release results of the FinnGen consortium for analysis. GWAS data of modifiable risk factors were collected from IEU Open GWAS. Cross-tissue TWAS analyses were performed using the unified test for molecular signature (UTMOST), while functional summary-based imputation (FUSION) was employed for single-tissue TWAS analyses. Furthermore, we also conducted multi-marker analysis of genomic annotation (MAGMA) analyses to validate the significant associations. Subsequent Mendelian randomization (MR) and colocalization analysis elucidated the causal associations between the identified genes across various tissues and EMT. To further delve into mechanisms, two-sample network MR analyses were conducted. At last, bioinformatics analyses were employed to enhance our understanding of the functional implications and expression patterns of these identified genes. For EMT, 22 significant gene signals were identified by UTMOST, 615 by FUSION, and 354 by MAGMA. Ultimately, six genes, including CISD2, EFRB, GREB1, IMMT, SULT1E1, and UBE2D3, were identified as candidate susceptibility genes for EMT. Through similar procedures, we identified GREB1, IL1A, and SULT1E1 for EMT of the ovary, and we identified GREB1 for EMT of the pelvic peritoneum, EMT of rectovaginal septum and vagina, and deep EMT. In MR analyses, the expression of IMMT in 21 tissues, EFR3B in the adrenal gland, CISD2 in 17 tissues, and UBE2D3 in 7 tissues demonstrated causal relationships with EMT risk. In addition, CISD2, IMMT, and UBE2D3, across different tissues, exhibited strong colocalization with EMT (PPH4 > 0.7). Two-sample network MR analyses revealed that CISD2, EFR3B, and UBE2D3 could potentially regulate the levels of blood lipids and hip circumference so as to influence the risk of EMT. Furthermore, bioinformatics analyses confirmed our findings and delved into the biological functions of the identified genes. Our study unveiled seven novel candidate genes whose predicted expression was associated with the risk of EMT, providing new insights into the underlying genetic framework of EMT. These findings will facilitate a deeper comprehension of the tissue-specific transcriptional regulatory mechanisms associated with EMT, paving the way for optimizing the management and treatment of EMT. Full article

A transcriptome-wide association study (TWAS) was conducted on genome-wide association study (GWAS) summary statistics of malignant melanoma of skin (UK Biobank dataset) and The Cancer Genome Atlas-Skin Cutaneous Melanoma (TCGA-SKCM) gene expression weights to identify melanoma susceptibility genes. The GWAS included 2465 cases and 449,799 controls, while the gene expression testing was conducted on 103 cases. Afterward, a gene enrichment analysis was applied to identify significant TWAS associations. The melanoma’s gene–microRNA (miRNA) regulatory network was constructed from the TWAS genes and their corresponding miRNAs. At last, a disease enrichment analysis was conducted on the corresponding miRNAs. The TWAS detected 27 genes associated with melanoma with p-values less than 0.05 (the top three genes are LOC389458 (RBAK), C16orf73 (MEIOB), and EIF3CL). After the joint/conditional test, one gene (AMIGO1) was dropped, resulting in 26 significant genes. The Gene Ontology (GO) biological process associated the extended gene set (76 genes) with protein K11-linked ubiquitination and regulation of cell cycle phase transition. K11-linked ubiquitin chains regulate cell division. Interestingly, the extended gene set was related to different skin cancer subtypes. Moreover, the enriched pathways were nsp1 from SARS-CoV-2 that inhibit translation initiation in the host cell, cell cycle, translation factors, and DNA repair pathways full network. The gene-miRNA regulatory network identified 10 hotspot genes with the top three: TP53, BRCA1, and MDM2; and four hotspot miRNAs: mir-16, mir-15a, mir-125b, and mir-146a. Melanoma was among the top ten diseases associated with the corresponding (106) miRNAs. Our results shed light on melanoma pathogenesis and biologically significant molecular interactions. Full article

Genome-wide association studies (GWAS) significantly enhance our ability to identify trait-associated genomic variants by considering the host genome. Moreover, the hologenome refers to the host organism’s collective genetic material and its associated microbiome. In this study, we utilized the hologenome framework, called Hologenome-wide association studies (HWAS), to dissect the architecture of complex traits, including milk yield, methane emissions, rumen physiology in cattle, and gut microbial composition in pigs. We employed four statistical models: (1) GWAS, (2) Microbial GWAS (M-GWAS), (3) HWAS-CG (hologenome interaction estimated using COvariance between Random Effects Genome-based restricted maximum likelihood (CORE-GREML)), and (4) HWAS-H (hologenome interaction estimated using the Hadamard product method). We applied Bonferroni correction to interpret the significant associations in the complex traits. The GWAS and M-GWAS detected one and sixteen significant SNPs for milk yield traits, respectively, whereas the HWAS-CG and HWAS-H each identified eight SNPs. Moreover, HWAS-CG revealed four, and the remaining models identified three SNPs each for methane emissions traits. The GWAS and HWAS-CG detected one and three SNPs for rumen physiology traits, respectively. For the pigs’ gut microbial composition traits, the GWAS, M-GWAS, HWAS-CG, and HWAS-H identified 14, 16, 13, and 12 SNPs, respectively. We further explored these associations through SNP annotation and by analyzing biological processes and functional pathways. Additionally, we integrated our GWA results with expression quantitative trait locus (eQTL) data using transcriptome-wide association studies (TWAS) and summary-based Mendelian randomization (SMR) methods for a more comprehensive understanding of SNP-trait associations. Our study revealed hologenomic variability in agriculturally important traits, enhancing our understanding of host-microbiome interactions. Full article

Chronic kidney disease (CKD) presents a significant global health challenge, characterized by complex pathophysiology. This study utilized a multi-omic approach, integrating genomic data from the CKDGen consortium alongside transcriptomic, metabolomic, and proteomic data to elucidate the genetic underpinnings and identify therapeutic targets for CKD and kidney function. We employed a range of analytical methods including cross-tissue transcriptome-wide association studies (TWASs), Mendelian randomization (MR), summary-based MR (SMR), and molecular docking. These analyses collectively identified 146 cross-tissue genetic associations with CKD and kidney function. Key Golgi apparatus-related genes (GARGs) and 41 potential drug targets were highlighted, with MAP3K11 emerging as a significant gene from the TWAS and MR data, underscoring its potential as a therapeutic target. Capsaicin displayed promising drug–target interactions in molecular docking analyses. Additionally, metabolome- and proteome-wide MR (PWMR) analyses revealed 33 unique metabolites and critical inflammatory proteins such as FGF5 that are significantly linked to and colocalized with CKD and kidney function. These insights deepen our understanding of CKD pathogenesis and highlight novel targets for treatment and prevention. Full article

Meat color traits directly influence consumer acceptability and purchasing decisions. Nevertheless, there is a paucity of comprehensive investigation into the genetic mechanisms underlying meat color traits in pigs. Utilizing genome-wide association studies (GWAS) on five meat color traits and the detection of selection signatures in pig breeds exhibiting distinct meat color characteristics, we identified a promising candidate SNP, 6_69103754, exhibiting varying allele frequencies among pigs with different meat color characteristics. This SNP has the potential to affect the redness and chroma index values of pork. Moreover, transcriptome-wide association studies (TWAS) analysis revealed the expression of candidate genes associated with meat color traits in specific tissues. Notably, the largest number of candidate genes were observed from transcripts derived from adipose, liver, lung, spleen tissues, and macrophage cell type, indicating their crucial role in meat color development. Several shared genes associated with redness, yellowness, and chroma indices traits were identified, including RINL in adipose tissue, ENSSSCG00000034844 and ITIH1 in liver tissue, TPX2 and MFAP2 in lung tissue, and ZBTB17, FAM131C, KIFC3, NTPCR, and ENGSSSCG00000045605 in spleen tissue. Furthermore, single-cell enrichment analysis revealed a significant association between the immune system and meat color. This finding underscores the significance of the immune system associated with meat color. Overall, our study provides a comprehensive analysis of the genetic mechanisms underlying meat color traits, offering valuable insights for future breeding efforts aimed at improving meat quality. Full article

Identifying key causal genes is critical for unraveling the genetic basis of complex economic traits, yet it remains a formidable challenge. The advent of large-scale sequencing data and computational algorithms, such as transcriptome-wide association studies (TWASs), offers a promising avenue for identifying potential causal genes. In this study, we harnessed the power of TWAS to identify genes potentially responsible for milk production traits, including daily milk yield (MY), fat percentage (FP), and protein percentage (PP), within a cohort of 100 buffaloes. Our approach began by generating the genotype and expression profiles for these 100 buffaloes through whole-genome resequencing and RNA sequencing, respectively. Through comprehensive genome-wide association studies (GWAS), we pinpointed a total of seven and four single nucleotide polymorphisms (SNPs) significantly associated with MY and FP traits, respectively. By using TWAS, we identified 55, 71, and 101 genes as significant signals for MY, FP, and PP traits, respectively. To delve deeper, we conducted protein–protein interaction (PPI) analysis, revealing the categorization of these genes into distinct PPI networks. Interestingly, several TWAS-identified genes within the PPI network played a vital role in milk performance. These findings open new avenues for identifying potentially causal genes underlying important traits, thereby offering invaluable insights for genomics and breeding in buffalo populations. Full article