Expression Quantitative Trait Loci Research Articles

Haplotype-aware modeling of cis-regulatory effects highlights the gaps remaining in eQTL data

Expression Quantitative Trait Loci (eQTLs) are critical to understanding the mechanisms underlying disease-associated genomic loci. Nearly all protein-coding genes in the human genome have been associated with one or more eQTLs. Here we introduce a multi-variant generalization of allelic Fold Change (aFC), aFC-n, to enable quantification of the cis-regulatory effects in multi-eQTL genes under the assumption that all eQTLs are known and conditionally independent. Applying aFC-n to 458,465 eQTLs in the Genotype-Tissue Expression (GTEx) project data, we demonstrate significant improvements in accuracy over the original model in estimating the eQTL effect sizes and in predicting genetically regulated gene expression over the current tools. We characterize some of the empirical properties of the eQTL data and use this framework to assess the current state of eQTL data in terms of characterizing cis-regulatory landscape in individual genomes. Notably, we show that 77.4% of the genes with an allelic imbalance in a sample show 0.5 log2 fold or more of residual imbalance after accounting for the eQTL data underlining the remaining gap in characterizing regulatory landscape in individual genomes. We further contrast this gap across tissue types, and ancestry backgrounds to identify its correlates and guide future studies.

Single Nucleotide Polymorphisms [SNPs] in the Shadows: Uncovering their Function in Non-Coding Region of Esophageal Cancer.

Esophageal cancer is a complex disease influenced by genetic and environmental factors. Single nucleotide polymorphisms [SNPs] in non-coding regions of the genome have emerged as crucial contributors to esophageal cancer susceptibility. This review provides a comprehensive overview of the role of SNPs in non-coding regions and their association with esophageal cancer. The accumulation of SNPs in the genome has been implicated in esophageal cancer risk. Various studies have identified specific locations in the genome where SNPs are more likely to occur, suggesting a location-specific response. Chromatin conformational studies have shed light on the localization of SNPs and their impact on gene transcription, posttranscriptional modifications, gene expression regulation, and histone modification. Furthermore, miRNA-related SNPs have been found to play a significant role in esophageal squamous cell carcinoma [ESCC]. These SNPs can affect miRNA binding sites, thereby altering target gene regulation and contributing to ESCC development. Additionally, the risk of ESCC has been linked to base excision repair, suggesting that SNPs in this pathway may influence disease susceptibility. Somatic DNA segment alterations and modified expression quantitative trait loci [eQTL] have also been associated with ESCC. These alterations can lead to disrupted gene expression and cellular processes, ultimately contributing to cancer development and progression. Moreover, SNPs have been found to be associated with the long non-coding RNA HOTAIR, which plays a crucial role in ESCC pathogenesis. This review concludes with a discussion of the current and future perspectives in the field of SNPs in non-coding regions and their relevance to esophageal cancer. Understanding the functional implications of these SNPs may lead to the identification of novel therapeutic targets and the development of personalized approaches for esophageal cancer prevention and treatment.

Identification of potential crucial genes and therapeutic targets for epilepsy

BackgroundEpilepsy, a central neurological disorder, has a complex genetic architecture. There is some evidence suggesting that genetic factors play a role in both the occurrence of epilepsy and its treatment. However, the genetic determinants of epilepsy are largely unknown. This study aimed to identify potential therapeutic targets for epilepsy.MethodsDifferentially expressed genes (DEGs) were extracted from the expression profiles of GSE44031 and GSE1834. Gene co-expression analysis was used to confirm the regulatory relationship between newly discovered epilepsy candidate genes and known epilepsy genes. Expression quantitative trait loci analysis was conducted to determine if epilepsy risk single-nucleotide polymorphisms regulate DEGs’ expression in human brain tissue. Finally, protein–protein interaction analysis and drug–gene interaction analysis were performed to assess the role of DEGs in epilepsy treatment.ResultsThe study found that the protein tyrosine phosphatase receptor-type O gene (PTPRO) and the growth arrest and DNA damage inducible alpha gene (GADD45A) were significantly upregulated in epileptic rats compared to controls in both datasets. Gene co-expression analysis revealed that PTPRO was co-expressed with RBP4, NDN, PAK3, FOXG1, IDS, and IDS, and GADD45A was co-expressed with LRRK2 in human brain tissue. Expression quantitative trait loci analysis suggested that epilepsy risk single-nucleotide polymorphisms could be responsible for the altered PTPRO and GADD45A expression in human brain tissue. Moreover, the protein encoded by GADD45A had a direct interaction with approved antiepileptic drug targets, and GADD45A interacts with genistein and cisplatin.ConclusionsThe results of this study highlight PTPRO and GADD45A as potential genes for the diagnosis and treatment of epilepsy.

Integrating genetic regulation and single-cell expression with GWAS prioritizes causal genes and cell types for glaucoma

Primary open-angle glaucoma (POAG), characterized by retinal ganglion cell death, is a leading cause of irreversible blindness worldwide. However, its molecular and cellular causes are not well understood. Elevated intraocular pressure (IOP) is a major risk factor, but many patients have normal IOP. Colocalization and Mendelian randomization analysis of >240 POAG and IOP genome-wide association study (GWAS) loci and overlapping expression and splicing quantitative trait loci (e/sQTLs) in 49 GTEx tissues and retina prioritizes causal genes for 60% of loci. These genes are enriched in pathways implicated in extracellular matrix organization, cell adhesion, and vascular development. Analysis of single-nucleus RNA-seq of glaucoma-relevant eye tissues reveals that the POAG and IOP colocalizing genes and genome-wide associations are enriched in specific cell types in the aqueous outflow pathways, retina, optic nerve head, peripapillary sclera, and choroid. This study nominates IOP-dependent and independent regulatory mechanisms, genes, and cell types that may contribute to POAG pathogenesis.

Multi-tissue transcriptome analysis to identify candidate genes associated with weight regulation in Hanwoo cattle.

While genetic markers related to meat production traits have been identified in many other cattle breeds, research on weight in Hanwoo cattle (Korean native cattle) is still insufficient. In this study, we performed expression quantitative trait loci (eQTL) analysis and differential gene expression analysis to detect candidate genes influencing the weight characteristics of 32 castrated Hanwoo cattle across 22 tissues and, we identified variants that affect gene expression levels. In total, we identified a total of 3,298 differentially expressed genes, among which we discovered key genes such as UBD, RGS2, FASN, and SCD that have functions related to adipogenesis, body weight, obesity, and lipid metabolism. Gene-set enrichment analysis revealed that candidate genes in adipose tissue are involved in metabolic pathways linked to obesity-related traits, adipose metabolism, and lipid metabolism. Additionally, we found that decreased expression of TRIM31 contributes to weight gain which can be explained by the associated candidate cis-eQTL genotypes for TRIM31 and their effect on differential gene expression between the lower and higher weight groups. Our findings revealed candidate genes associated with the weight of Hanwoo cattle and perhaps can provide comprehensive insights into the association of weight with various tissues beyond adipose tissue and muscle, indicating the potential for expanding the focus of livestock trait research.

Associations between genetic variants in sphingolipid metabolism pathway genes and hepatitis B virus-related hepatocellular carcinoma survival.

Although the sphingolipid metabolism pathway is known to play a significant role in tumor progression, there have been few studies on how genetic variants in the sphingolipid metabolism pathway genes affect the survival of patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). We utilized available genotyping data to conduct multivariate Cox proportional hazards regression model analysis, examining the associations of 12,188 single nucleotide polymorphisms (SNPs) in 86 sphingolipid metabolism pathway genes on the survival of 866 HBV-HCC patients, and the model was also used in additive interaction analysis. We used bioinformatics functional prediction and expression quantitative trait locus (eQTL) analysis to explore the potential functions of SNPs and to evaluate the association of SNPs with the corresponding mRNA expression, respectively. We also used the online database TIMER2.0 (http://timer.comp-genomics.org/) to analyze the relationship between the corresponding mRNA expression levels and immune cell infiltration. Our study found that GBA2 rs1570247 G>A was significantly associated with elevated survival of HBV-HCC patients [(hazards ratio (HR)=0.74, 95% confidence interval (CI)=0.64-0.86, P<0.001)]. And on an additive scale, a synergistic effect was observed between the GG genotype of rs1570247 and advanced BCLC stage. Among HBV-HCC patients with advanced BCLC stage, those carrying the GBA2 rs1570247 GG genotype exhibited a significantly elevated risk of mortality (HR=3.32, 95%CI=2.45-4.50). Further functional prediction and eQTL analysis revealed that rs1570247 were located in the 5' untranslated region of the GBA2, the A allele of SNP rs1570247 was associated with higher mRNA expression levels of GBA2 in normal liver tissues (P=0.009). Moreover, we observed a positive correlation between GBA2 mRNA expression and the infiltration level of B lymphocytes cell (R=0.331, P<0.001), while a negative correlation was noted between GBA2 mRNA expression and the infiltration level of macrophage M2 in HCC (R=-0.383, P<0.001). Our findings suggest that GBA2 rs1570247 G>A in sphingolipid metabolism pathway may be a key factor for survival of HBV-HCC patients by regulating the expression of corresponding genes and affecting the infiltration level of immune cells.

Systematic identification of genotype-dependent enhancer variants in eosinophilic esophagitis

Eosinophilic esophagitis (EoE) is a rare atopic disorder associated with esophageal dysfunction, including difficulty swallowing, food impaction, and inflammation, that develops in a small subset of people with food allergies. Genome-wide association studies (GWASs) have identified 9 independent EoE risk loci reaching genome-wide significance (p<5×10-8) and 27 additional loci of suggestive significance (5×10-8<p<1×10-5). In the current study, we perform linkage disequilibrium (LD) expansion of these loci to nominate a set of 531 variants that are potentially causal. To systematically interrogate the gene regulatory activity of these variants, we designed a massively parallel reporter assay (MPRA) containing the alleles of each variant within their genomic sequence context cloned into a GFP reporter library. Analysis of reporter gene expression in TE-7, HaCaT, and Jurkat cells revealed cell-type-specific gene regulation. We identify 32 allelic enhancer variants, representing 6 genome-wide significant EoE loci and 7 suggestive EoE loci, that regulate reporter gene expression in a genotype-dependent manner in at least one cellular context. By annotating these variants with expression quantitative trait loci (eQTL) and chromatin looping data in related tissues and cell types, we identify putative target genes affected by genetic variation in individuals with EoE. Transcription factor enrichment analyses reveal possible roles for cell-type-specific regulators, including GATA3. Our approach reduces the large set of EoE-associated variants to a set of 32 with allelic regulatory activity, providing functional insights into the effects of genetic variation in this disease.

Signatures of Co-evolution and Co-regulation in the CYP3A and CYP4F Genes in Humans.

Cytochromes P450 (CYP450) are hemoproteins generally involved in the detoxification of the body of xenobiotic molecules. They participate in the metabolism of many drugs and genetic polymorphisms in humans have been found to impact drug responses and metabolic functions. In this study, we investigate the genetic diversity of CYP450 genes. We found that two clusters, CYP3A and CYP4F, are notably differentiated across human populations with evidence for selective pressures acting on both clusters: we found signals of recent positive selection in CYP3A and CYP4F genes and signals of balancing selection in CYP4F genes. Furthermore, an extensive amount of unusual linkage disequilibrium is detected in this latter cluster, indicating co-evolution signatures among CYP4F genes. Several of the selective signals uncovered co-localize with expression quantitative trait loci (eQTL), which could suggest epistasis acting on co-regulation in these gene families. In particular, we detected a potential co-regulation event between CYP3A5 and CYP3A43, a gene whose function remains poorly characterized. We further identified a causal relationship between CYP3A5 expression and reticulocyte count through Mendelian randomization analyses, potentially involving a regulatory region displaying a selective signal specific to African populations. Our findings linking natural selection and gene expression in CYP3A and CYP4F subfamilies are of importance in understanding population differences in metabolism of nutrients and drugs.

Lung Cancer in Ever- and Never-Smokers: Findings from Multi-Population GWAS Studies.

Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer. We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer. Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10-8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior. We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies. Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.

Associations of MMP9 polymorphism with the risk of severe pneumonia in a Southern Chinese children population

BackgroundSevere pneumonia frequently causes irreversible sequelae and represents a major health burden for children under the age of 5. Matrix Metallopeptidase 9 (MMP9) is a zinc-dependent endopeptidase that is involved in various cellular processes. The correlation between MMP9 and the risk of severe childhood pneumonia remains unclear.MethodsHere we assemble a case–control cohort to study the association of genetic variants in MMP9 gene with severe childhood pneumonia susceptibility in a Southern Chinese population (1034 cases and 8426 controls).ResultsOur results indicate that the allele G in rs3918262 SNP was significantly associated with an increased risk of severe pneumonia. Bioinformatic analyses by expression quantitative trait loci (eQTL), RegulomeDB and FORGEdb database analysis showed that rs3918262 SNP has potential regulatory effect on translational efficiency and protein level of MMP9 gene. Furthermore, MMP9 concentrations were significantly up-regulated in the bronchoalveolar lavages (BALs) of children with severe pneumonia.ConclusionIn summary, our findings suggest that MMP9 is a novel predisposing gene for childhood pneumonia.

Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

BackgroundGut microbiota alterations have been implicated in sepsis and related infectious diseases, but the causal relationship and underlying mechanisms remain unclear.MethodsWe evaluated the association between gut microbiota composition and sepsis using two-sample Mendelian randomization (MR) analysis based on published genome-wide association study (GWAS) summary statistics. Sensitivity analyses were conducted to validate the robustness of the results. Reverse MR analysis and integration of GWAS and expression quantitative trait loci (eQTL) data were performed to identify potential genes and therapeutic targets.ResultsOur analysis identified 11 causal bacterial taxa associated with sepsis, with increased abundance of six taxa showing positive causal relationships. Ten taxa had causal effects on the 28-day survival outcome of septic patients, with increased abundance of six taxa showing positive associations. Sensitivity analyses confirmed the robustness of these associations. Reverse MR analysis did not provide evidence of reverse causality. Integration of GWAS and eQTL data revealed 76 genes passing the summary data-based Mendelian randomization (SMR) test. Differential expression of these genes was observed between sepsis patients and healthy individuals. These genes represent potential therapeutic targets for sepsis. Molecular docking analysis predicted potential drug-target interactions, further supporting their therapeutic potential.ConclusionOur study provides insights for the development of personalized treatment strategies for sepsis and offers preliminary candidate targets and drugs for future drug development.

Identification of eQTLs using different sets of single nucleotide polymorphisms associated with carcass and body composition traits in pigs

BackgroundMapping expression quantitative trait loci (eQTLs) in skeletal muscle tissue in pigs is crucial for understanding the relationship between genetic variation and phenotypic expression of carcass traits in meat animals. Therefore, the primary objective of this study was to evaluate the impact of different sets of single nucleotide polymorphisms (SNP), including scenarios removing SNPs pruned for linkage disequilibrium (LD) and SNPs derived from SNP chip arrays and RNA-seq data from liver, brain, and skeletal muscle tissues, on the identification of eQTLs in the Longissimus lumborum tissue, associated with carcass and body composition traits in Large White pigs. The SNPs identified from muscle mRNA were combined with SNPs identified in the brain and liver tissue transcriptomes, as well as SNPs from the GGP Porcine 50 K SNP chip array. Cis- and trans-eQTLs were identified based on the skeletal muscle gene expression level, followed by functional genomic analyses and statistical associations with carcass and body composition traits in Large White pigs.ResultsThe number of cis- and trans-eQTLs identified across different sets of SNPs (scenarios) ranged from 261 to 2,539 and from 29 to 13,721, respectively. Furthermore, 6,180 genes were modulated by eQTLs in at least one of the scenarios evaluated. The eQTLs identified were not significantly associated with carcass and body composition traits but were significantly enriched for many traits in the “Meat and Carcass” type QTL. The scenarios with the highest number of cis- (n = 304) and trans- (n = 5,993) modulated genes were the unpruned and LD-pruned SNP set scenarios identified from the muscle transcriptome. These genes include 84 transcription factor coding genes.ConclusionsAfter LD pruning, the set of SNPs identified based on the transcriptome of the skeletal muscle tissue of pigs resulted in the highest number of genes modulated by eQTLs. Most eQTLs are of the trans type and are associated with genes influencing complex traits in pigs, such as transcription factors and enhancers. Furthermore, the incorporation of SNPs from other genomic regions to the set of SNPs identified in the porcine skeletal muscle transcriptome contributed to the identification of eQTLs that had not been identified based on the porcine skeletal muscle transcriptome alone.

Genome-Wide Identification and Expression Analyses of the FAR1/FHY3 Gene Family Provide Insight into Inflorescence Development in Maize.

As transcription factors derived from transposase, FAR-RED IMPAIRED RESPONSE1 (FAR1) and its homolog FHY3 play crucial roles in the regulation of light signaling and various stress responses by coordinating the expression of downstream target genes. Despite the extensive investigation of the FAR1/FHY3 family in Arabidopsis thaliana and other species, a comprehensive examination of these genes in maize has not been conducted thus far. In this study, we employed a genomic mining approach to identify 16 ZmFAR1 genes in the maize inbred line B73, which were further classified into five subgroups based on their phylogenetic relationships. The present study characterized the predicted polypeptide sequences, molecular weights, isoelectric points, chromosomal distribution, gene structure, conserved motifs, subcellular localizations, phylogenetic relationships, and cis-regulatory elements of all members belonging to the ZmFAR1 family. Furthermore, the tissue-specific expression of the 16 ZmFAR1 genes was analyzed using RNA-seq, and their expression patterns under far-red light conditions were validated in the ear and tassel through qRT-qPCR. The observed highly temporal and spatial expression patterns of these ZmFAR1 genes were likely associated with their specific functional capabilities under different light conditions. Further analysis revealed that six ZmFAR1 genes (ZmFAR1-1, ZmFAR1-10, ZmFAR1-11, ZmFAR1-12, ZmFAR1-14, and ZmFAR1-15) exhibited a response to simulated shading treatment and actively contributed to the development of maize ears. Through the integration of expression quantitative trait loci (eQTL) analyses and population genetics, we identified the presence of potential causal variations in ZmFAR1-14 and ZmFAR1-9, which play a crucial role in regulating the kernel row number and kernel volume weight, respectively. In summary, this study represents the initial identification and characterization of ZmFAR1 family members in maize, uncovering the functional variation in candidate regulatory genes associated with the improvement of significant agronomic traits during modern maize breeding.

PTGES2 and RNASET2 identified as novel potential biomarkers and therapeutic targets for basal cell carcinoma: insights from proteome-wide mendelian randomization, colocalization, and MR-PheWAS analyses.

Basal cell carcinoma (BCC) is the most common skin cancer, lacking reliable biomarkers or therapeutic targets for effective treatment. Genome-wide association studies (GWAS) can aid in identifying drug targets, repurposing existing drugs, predicting clinical trial side effects, and reclassifying patients in clinical utility. Hence, the present study investigates the association between plasma proteins and skin cancer to identify effective biomarkers and therapeutic targets for BCC. Proteome-wide mendelian randomization was performed using inverse-variance-weight and Wald Ratio methods, leveraging 1Mb cis protein quantitative trait loci (cis-pQTLs) in the UK Biobank Pharma Proteomics Project (UKB-PPP) and the deCODE Health Study, to determine the causal relationship between plasma proteins and skin cancer and its subtypes in the FinnGen R10 study and the SAIGE database of Lee lab. Significant association with skin cancer and its subtypes was defined as a false discovery rate (FDR) < 0.05. pQTL to GWAS colocalization analysis was executed using a Bayesian model to evaluate five exclusive hypotheses. Strong colocalization evidence was defined as a posterior probability for shared causal variants (PP.H4) of ≥0.85. Mendelian randomization-Phenome-wide association studies (MR-PheWAS) were used to evaluate potential biomarkers and therapeutic targets for skin cancer and its subtypes within a phenome-wide human disease category. PTGES2, RNASET2, SF3B4, STX8, ENO2, and HS3ST3B1 (besides RNASET2, five other plasma proteins were previously unknown in expression quantitative trait loci (eQTL) and methylation quantitative trait loci (mQTL)) were significantly associated with BCC after FDR correction in the UKB-PPP and deCODE studies. Reverse MR showed no association between BCC and these proteins. PTGES2 and RNASET2 exhibited strong evidence of colocalization with BCC based on a posterior probability PP.H4 >0.92. Furthermore, MR-PheWAS analysis showed that BCC was the most significant phenotype associated with PTGES2 and RNASET2 among 2,408 phenotypes in the FinnGen R10 study. Therefore, PTGES2 and RNASET2 are highlighted as effective biomarkers and therapeutic targets for BCC within the phenome-wide human disease category. The study identifies PTGES2 and RNASET2 plasma proteins as novel, reliable biomarkers and therapeutic targets for BCC, suggesting more effective clinical application strategies for patients.

Identification of atrial fibrillation-related genes through transcriptome data analysis and Mendelian randomization.

Atrial fibrillation (AF) is a common persistent arrhythmia characterized by rapid and chaotic atrial electrical activity, potentially leading to severe complications such as thromboembolism, heart failure, and stroke, significantly affecting patient quality of life and safety. As the global population ages, the prevalence of AF is on the rise, placing considerable strains on individuals and healthcare systems. This study utilizes bioinformatics and Mendelian Randomization (MR) to analyze transcriptome data and genome-wide association study (GWAS) summary statistics, aiming to identify biomarkers causally associated with AF and explore their potential pathogenic pathways. We obtained AF microarray datasets GSE41177 and GSE79768 from the Gene Expression Omnibus (GEO) database, merged them, and corrected for batch effects to pinpoint differentially expressed genes (DEGs). We gathered exposure data from expression quantitative trait loci (eQTL) and outcome data from AF GWAS through the IEU Open GWAS database. We employed inverse variance weighting (IVW), MR-Egger, weighted median, and weighted model approaches for MR analysis to assess exposure-outcome causality. IVW was the primary method, supplemented by other techniques. The robustness of our results was evaluated using Cochran's Q test, MR-Egger intercept, MR-PRESSO, and leave-one-out sensitivity analysis. A "Veen" diagram visualized the overlap of DEGs with significant eQTL genes from MR analysis, referred to as common genes (CGs). Additional analyses, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and immune cell infiltration studies, were conducted on these intersecting genes to reveal their roles in AF pathogenesis. The combined dataset revealed 355 differentially expressed genes (DEGs), with 228 showing significant upregulation and 127 downregulated. Mendelian randomization (MR) analysis identified that the autocrine motility factor receptor (AMFR) [IVW: OR = 0.977; 95% CI, 0.956-0.998; P = 0.030], leucine aminopeptidase 3 (LAP3) [IVW: OR = 0.967; 95% CI, 0.934-0.997; P = 0.048], Rab acceptor 1 (RABAC1) [IVW: OR = 0.928; 95% CI, 0.875-0.985; P = 0.015], and tryptase beta 2 (TPSB2) [IVW: OR = 0.971; 95% CI, 0.943-0.999; P = 0.049] are associated with a reduced risk of atrial fibrillation (AF). Conversely, GTPase-activating SH3 domain-binding protein 2 (G3BP2) [IVW: OR = 1.030; 95% CI, 1.004-1.056; P = 0.024], integrin subunit beta 2 (ITGB2) [IVW: OR = 1.050; 95% CI, 1.017-1.084; P = 0.003], glutaminyl-peptide cyclotransferase (QPCT) [IVW: OR = 1.080; 95% CI, 1.010-0.997; P = 1.154], and tripartite motif containing 22 (TRIM22) [IVW: OR = 1.048; 95% CI, 1.003-1.095; P = 0.035] are positively associated with AF risk. Sensitivity analyses indicated a lack of heterogeneity or horizontal pleiotropy (P > 0.05), and leave-one-out analysis did not reveal any single nucleotide polymorphisms (SNPs) impacting the MR results significantly. GO and KEGG analyses showed that CG is involved in processes such as protein polyubiquitination, neutrophil degranulation, specific and tertiary granule formation, protein-macromolecule adaptor activity, molecular adaptor activity, and the SREBP signaling pathway, all significantly enriched. The analysis of immune cell infiltration demonstrated associations of CG with various immune cells, including plasma cells, CD8T cells, resting memory CD4T cells, regulatory T cells (Tregs), gamma delta T cells, activated NK cells, activated mast cells, and neutrophils. By integrating bioinformatics and MR approaches, genes such as AMFR, G3BP2, ITGB2, LAP3, QPCT, RABAC1, TPSB2, and TRIM22 are identified as causally linked to AF, enhancing our understanding of its molecular foundations. This strategy may facilitate the development of more precise biomarkers and therapeutic targets for AF diagnosis and treatment.

NPC1 is required for postnatal islet β cell differentiation by maintaining mitochondria turnover.

Rationale: NPC1 is a protein localized on the lysosome membrane regulating intracellular cholesterol transportation and maintaining normal lysosome function. GWAS studies have found that NPC1 variants in T2D was a pancreatic islet expression quantitative trait locus, suggesting a potential role of NPC1 in T2D islet pathophysiology. Methods: Two-week-old Npc1-/- mice and wild type littermates were employed to examine pancreatic β cell morphology and functional changes induced by loss of Npc1. Single cell RNA sequencing was conducted on primary islets. Npc1-/- Min6 cell line was generated using CRISPR/Cas9 gene editing. Seahorse XF24 was used to analyze primary islet and Min6 cell mitochondria respiration. Ultra-high-resolution cell imaging with Lattice SIM2 and electron microscope imaging were used to observe mitochondria and lysosome in primary islet β and Min6 cells. Mitophagy Dye and mt-Keima were used to measure β cell mitophagy. Results: In Npc1-/- mice, we found that β cell survival and pancreatic β cell mass expansion as well as islet glucose induced insulin secretion in 2-week-old mice were reduced. Npc1 loss retarded postnatal β cell differentiation and growth as well as impaired mitochondria oxidative phosphorylation (OXPHOS) function to increase mitochondrial superoxide production, which might be attributed to impaired autophagy flux particularly mitochondria autophagy (mitophagy) induced by dysfunctional lysosome in Npc1 null β cells. Conclusion: Our study revealed that NPC1 played an important role in maintaining normal lysosome function and mitochondria turnover, which ensured establishment of sufficient mitochondria OXPHOS for islet β cells differentiation and maturation.

Identification of an Allele-Specific Transcription Factor Binding Interaction that May Regulate PLA2G2A Gene Expression.

The secreted phospholipase A2 (sPLA2) isoform, sPLA2-IIA, has been implicated in a variety of diseases and conditions, including bacteremia, cardiovascular disease, COVID-19, sepsis, adult respiratory distress syndrome, and certain cancers. Given its significant role in these conditions, understanding the regulatory mechanisms impacting its levels is crucial. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs), including rs11573156, that are associated with circulating levels of sPLA2-IIA. The work in the manuscript leveraged 4 publicly available datasets to investigate the mechanism by which rs11573156 influences sPLA2-IIA levels via bioinformatics and modeling analysis. Through genotype-tissue expression (GTEx), 234 expression quantitative trait loci (eQTLs) were identified for the gene that encodes for sPLA2-IIA, PLA2G2A. SNP2TFBS was used to ascertain the binding affinities between transcription factors (TFs) to both the reference and alternative alleles of identified eQTL SNPs. Subsequently, candidate TF-SNP interactions were cross-referenced with the ChIP-seq results in matched tissues from ENCODE. SP1-rs11573156 emerged as the significant TF-SNP pair in the liver. Further analysis revealed that the upregulation of PLA2G2A transcript levels through the rs11573156 variant was likely affected by tissue SP1 protein levels. Using an ordinary differential equation based on Michaelis-Menten kinetic assumptions, we modeled the dependence of PLA2G2A transcription on SP1 protein levels, incorporating the SNP influence. Collectively, our analysis strongly suggests that the difference in the binding dynamics of SP1 to different rs11573156 alleles may underlie the allele-specific PLA2G2A expression in different tissues, a mechanistic model that awaits future direct experimental validation. This mechanism likely contributes to the variation in circulating sPLA2-IIA protein levels in the human population, with implications for a wide range of human diseases.

Multi-omics Mendelian randomization integrating GWAS, eQTL, and mQTL data identified genes associated with breast cancer.

Breast cancer (BC) remains a major disease posing a threat to women's health, but the underlying biological interpretation remains largely unknown. Here, we aimed to identify genes associated with breast cancer and analyze their pathophysiological mechanisms based on multi-omics Mendelian randomization (MR). Summary-data-based MR (SMR) was performed to estimate the causal effects of blood and breast mammary tissue expression quantitative trait loci (eQTLs) on BC. External validation analysis was used to validate the identified genes. Integration analyses BC GWAS summaries with eQTLs and DNA methylation QTLs (mQTLs) from the blood were conducted using SMR to prioritize putative blood genes and their regulatory elements associated with BC risk. Finally, two prior genes (ATG10 and RCCD1) from blood tissue reached significant levels in both BCAC (ATG10: ORBRCR = 0.91, PBRCR = 1.29 × 10-11; RCCD1: ORBRCR = 0.90, PBRCR = 3.72 × 10-15) and FinnGen cohorts (ATG10: ORFinnGen = 0.89, PFinnGen = 8.55 × 10-5; RCCD1: ORFinnGen = 0.89, PFinnGen = 2.38 × 10-8). Additionally, those two genes from breast tissues also replicated in both BCAC (ATG10: ORBRCR = 0.95, PBRCR = 1.02 × 10-9; RCCD1: ORBRCR = 0.87, PBRCR = 4.70 × 10-10) and FinnGen cohorts (ATG10: ORFinnGen = 0.93, PFinnGen = 2.38 × 10-4; RCCD1: ORFinnGen = 0.85, PFinnGen = 3.81 × 10-6). Sensitive analysis and external validation analysis validated those two identified genes. Multi-omics MR analysis showed that the SNP signals associated with ATG10 and RCCD1 were significant across the data from BC Genome-wide association study (GWAS), eQTL, and mQTL studies. In conclusion, we identified two priority genes that are potentially associated with BC. These findings improve our limited understanding of the mechanism of BC and shed light on the development of therapeutic agents for treating BC.

Exploring the Regulation and Function of Rpl3l in the Development of Early-Onset Dilated Cardiomyopathy and Congestive Heart Failure Using Systems Genetics Approach.

Cardiomyopathies, diseases affecting the myocardium, are common causes of congestive heart failure (CHF) and sudden cardiac death. Recently, biallelic variants in ribosomal protein L3-like (RPL3L) have been reported to be associated with severe neonatal dilated cardiomyopathy (DCM) and CHF. This study employs a systems genetics approach to gain understanding of the regulatory mechanisms underlying the role of RPL3L in DCM. Genetic correlation, expression quantitative trait loci (eQTL) mapping, differential expression analysis and comparative functional analysis were performed using cardiac gene expression data from the patients and murine genetic reference populations (GRPs) of BXD mice (recombinant inbred strains from a cross of C57BL/6J and DBA/2J mice). Additionally, immune infiltration analysis was performed to understand the relationship between DCM, immune cells and RPL3L expression. Systems genetics analysis identified high expression of Rpl3l mRNA, which ranged from 11.31 to 12.16 across murine GRPs of BXD mice, with an ~1.8-fold difference. Pathways such as "diabetic cardiomyopathy", "focal adhesion", "oxidative phosphorylation" and "DCM" were significantly associated with Rpl3l. eQTL mapping suggested Myl4 (Chr 11) and Sdha (Chr 13) as the upstream regulators of Rpl3l. The mRNA expression of Rpl3l, Myl4 and Sdha was significantly correlated with multiple echocardiography traits in BXD mice. Immune infiltration analysis revealed a significant association of RPL3L and SDHA with seven immune cells (CD4, CD8-naive T cell, CD8 T cell, macrophages, cytotoxic T cell, gamma delta T cell and exhausted T cell) that were also differentially infiltrated between heart samples obtained from DCM patients and normal individuals. RPL3L is highly expressed in the heart tissue of humans and mice. Expression of Rpl3l and its upstream regulators, Myl4 and Sdha, correlate with multiple cardiac function traits in murine GRPs of BXD mice, while RPL3L and SDHA correlate with immune cell infiltration in DCM patient hearts, suggesting important roles for RPL3L in DCM and CHF pathogenesis via immune inflammation, necessitating experimental validations of Myl4 and Sdha in Rpl3l regulation.

Genome-Wide Association Study Meta-Analysis Elucidates Genetic Structure and Identifies Candidate Genes of Teat Number Traits in Pigs.

The teat number is a pivotal reproductive trait that significantly influences the survival rate of piglets. A meta-analysis is a robust instrument, enhancing the universality of research findings and improving statistical power by increasing the sample size. This study aimed to identify universal candidate genes associated with teat number traits using a genome-wide association study (GWAS) meta-analysis with three breeds. We identified 21 chromosome threshold significant single-nucleotide polymorphisms (SNPs) associated with five teat number traits in single-breed and cross-breed meta-GWAS analyses. Using a co-localization analysis of expression quantitative trait loci and GWAS loci, we detected four unique genes that were co-localized with cross-breed GWAS loci associated with teat number traits. Through a meta-analysis and integrative analysis, we identified more reliable candidate genes associated with multiple-breed teat number traits. Our research provides new information for exploring the genetic mechanism affecting pig teat number for breeding selection and improvement.