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Results for “Expression quantitative trait locus”

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At least 19 recordsLinked to original sources
PubMed2026

Integration of Genome-Wide Association Studies With Single-Cell and Bulk Expression Quantitative Trait Locus to Identify Stroke Susceptibility Genes.

BACKGROUND: Previous studies have integrated genome-wide association studies with expression quantitative trait locus (eQTL) data from bulk tissues to identify stroke susceptibility genes. However, eQTL data exhibit high cell-type specificity, and genetic variants may have distinct effects across stroke subtypes. METHODS: We applied the summary-data-based Mendelian randomization (MR) method to integrate eQTL data from 7 brain cell types with genome-wide association studies data for 5 stroke phenotypes (stroke, ischemic stroke, cardioembolic stroke, large artery stroke, and small vessel stroke). Results were compared with summary-data-based MR using eQTL data from 49 tissues in the Genotype-Tissue Expression project. Robustness of significant single-cell summary-data-based MR associations was assessed via MR and colocalization analyses. Further evaluations included single-cell RNA-seq differential expression, protein-protein interaction, druggability, and phenome-wide association studies. RESULTS: Single-cell summary-data-based MR identified many novel significant genes not detected using bulk tissue eQTL data. Validated associations revealed 2 stroke risk genes (LRCH1, ICA1L), 3 stroke protective genes (AHI1, LYRM9, CENPQ), 2 large artery stroke risk genes (LIPA, ELL), and 1 ischemic stroke protective gene (CENPQ). Single-cell RNA-seq showed significantly increased LIPA expression in mouse stroke samples compared with controls. Protein-protein interaction and druggability analyses, along with phenome-wide association studies, prioritized LIPA and LRCH1 as potential therapeutic targets for stroke while indicating possible adverse effects. CONCLUSIONS: Integrating single-cell eQTL with stroke-subtype genome-wide association studies uncovers novel cell-type-specific causal genes and highlights promising therapeutic targets, advancing understanding of stroke pathogenesis.

Genome-Wide Association Study↗
PubMed2026

Single-cell expression quantitative trait locus Mendelian randomization reveals immune cell-specific causal regulatory networks and actionable targets in polycystic ovary syndrome.

ObjectiveTo systematically investigate whether the pathogenesis of polycystic ovary syndrome (PCOS) is causally related to dysregulated gene expression in specific immune cell subsets, and to evaluate the potential of these causal genes as actionable drug targets.MethodsThis study employed a two-sample Mendelian randomization (MR) framework using publicly available genome-wide association study (GWAS) summary statistics. The participant data included 797 PCOS cases and 140,558 controls (no direct patient recruitment was involved). Instrumental variables were derived from high-resolution immune cell-specific single-cell expression quantitative trait locus (sc-eQTL) data (OneK1K project) across 14 immune cell types. Primary analyses utilized the inverse-variance weighted (IVW) method. Shared causal variants were validated using Bayesian colocalization. Phenome-wide association analysis (PheWAS), external transcriptomic dataset validation (GSE8157), and DrugBank database screening were conducted for pleiotropy assessment and drug repositioning.ResultsMR analysis revealed genome-wide significant causal associations for GLIPR1 in non-classical monocytes (Mono NC) and XBP1 in CD4+ effector memory T cells (CD4 ET) with PCOS risk. Higher GLIPR1 expression was associated with a decreased PCOS risk (OR = 0.669, P = 4.34×10-6), whereas higher XBP1 expression was associated with an increased risk (OR = 1.406, P = 9.53×10-8). Colocalization analysis confirmed that GLIPR1 shares a causal variant with PCOS (PP.H4 = 96.73%). PheWAS and external validation confirmed the safety profile and significant upregulation (P = 0.03) of GLIPR1. Drug repositioning identified SOT-107, a Phase III protein therapy drug, as a potential interacting agent for GLIPR1.ConclusionsThis sc-eQTL MR study reveals immune cell-specific causal regulatory networks in PCOS. GLIPR1 in non-classical monocytes represents a high-confidence protective target, while XBP1 provides suggestive evidence for immune-mediated pathogenesis. The candidate drug SOT-107 highlights theoretical repositioning opportunities, though rigorous preclinical validation remains required.

Female↗
PubMed2026

Exploring genomic regions regulating the liver transcriptome and energy homeostasis in pigs.

In pigs, energy homeostasis has an impact on meat quality and health. In a Duroc pig population, 30 quantitative trait locus (QTL) regions associated with fatty acid (FA) composition in adipose tissue, plasma, liver and muscle were previously identified. Mapping of expression quantitative trait locus (eQTL) regions will provide a molecular hypothesis for genotype-phenotype interactions and may allow the identification of shared causal variants, key to increasing our understanding of the genetic regulation of FA composition and energy homeostasis. However, gene expression is impacted by environmental factors, while individual-level allelic imbalance (AI) can be more reliable and can be surveyed via allelic-specific expression (ASE) analysis. Furthermore, treatment of ASE as a quantitative trait allows the identification of allele-specific expression quantitative trait loci (aseQTLs), which are variants whose heterozygosity is linked to the AI of a nearby single-nucleotide polymorphism (SNP), pointing to regulatory elements. In this study, liver was selected as a key metabolic hub with an important role in the regulation of energy homeostasis, and 310 liver RNA sequencing samples were analysed using a combination of (1) eQTL mapping, (2) ASE analysis, and (3) aseQTL mapping methods. A total of 2 188 eQTL regions were identified, mostly cis-eQTL regions (73.17%). ASE analysis reported 1 964 ASE SNPs, associated with 633 genes. Finally, aseQTL mapping reported 64 172 aseQTL, associated with the AI of 31 genes. Colocalisation analysis combined with ASE analysis showed that the expression of FADS1 and FADS2 genes is associated with the polyunsaturated FA composition in several tissues, where microRNA regulation may be present. Finally, in the DGAT2 gene, annotated in a QTL region associated with multiple FAs in adipose tissue, ASE revealed allelic imbalance in the 3' untranslated region (UTR) of this gene. Allelic differential expression can be caused by a 13-bp insertion affecting messenger RNA stability, previously described, exemplifying how allelic imbalance is caused by a post-transcriptional regulatory mechanism undetectable by eQTL mapping. Furthermore, aseQTLs were associated with this gene, linked to a previously identified copy number variant not yet associated with DGAT2 expression. These results demonstrate how ASE analysis and aseQTL mapping can complement eQTL mapping, as they resolved a complex region affected by allelic heterogeneity, a main confounding effect of QTL mapping. In conclusion, the combination of eQTL mapping, ASE analysis and aseQTL mapping allowed the characterisation of the regulation of liver gene expression, improving our understanding of the genetic determinism of energy homeostasis.

Allele-specific expression↗
PubMed2026

Multi-Ancestry Genome-Wide Association with Fine-Mapping Identifies Novel Loci for Pigment Dispersion Syndrome and Pigmentary Glaucoma.

PURPOSE: Pigment dispersion syndrome and pigmentary glaucoma are important causes of ocular hypertension and glaucomatous optic neuropathy, yet their genetic determinants remain incompletely defined, particularly across diverse ancestries. This study aimed to use a large multi-ancestry cohort from the All of Us Research Program to investigate the genetic basis of pigment dispersion syndrome and pigmentary glaucoma. DESIGN: Case-control study. PARTICIPANTS: In total, 572 cases and 37 808 controls with array genotyping and 537 cases and 35 493 controls with whole-genome sequencing. METHODS: Using electronic health record phenotyping in the All of Us Research Program, we performed multi-ancestry genome-wide association analyses using both array-based data and whole-genome sequencing-based data, comparing patients with pigment dispersion syndrome or pigmentary glaucoma to those without either condition. We also performed Firth penalized regression and Fisher analyses, and we performed principal component analyses to assess effect sizes across genetic ancestries. We applied statistical fine-mapping, examined for cross-trait overlap, and assessed expression quantitative trait locus associations for lead variants. MAIN OUTCOME MEASURES: P values and odds ratios of lead loci from genome-wide association analyses; size of credible sets determined from fine-mapping; allele frequency of lead variants in cases, controls, and the general population; expression quantitative trait loci effect size and P values linking lead variants to gene expression. RESULTS: We identified 4 loci reaching genome-wide significance across analyses, including signals near EPHA7 (which mediates cell-cell signaling), within TYR (involved in melanin synthesis and replicated from prior studies), within LINC01138, and near OTX2. Statistical fine-mapping refined 3 of these loci to single-variant 95% credible sets and narrowed the TYR locus to small credible sets, prioritizing possible causal variants. Effect estimates were broadly consistent across genetic ancestry clusters. Lead variants showed regulatory evidence in expression quantitative trait locus, including reduced EPHA7 expression. CONCLUSIONS: These findings implicate both melanogenesis and cell-cell adhesion and signaling pathways in pigment dispersion syndrome and pigmentary glaucoma. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Genome-wide association study↗
PubMed2025

Association of the pri-miR-34b/c rs4938723 T > C polymorphism with hepatoblastoma susceptibility in Eastern Chinese children: A five-center case-control study.

BACKGROUND: Hepatoblastoma is the most prevalent liver cancer affecting children, and its intricate causes are closely linked to genetic variations. This study interrogated the influence of the miR-34b/c rs4938723 T > C polymorphism in hepatoblastoma predisposition in a Han Chinese children study population, comprising 193 cases and 773 controls from East China. METHODS: Genotyping was performed via the TaqMan technique. The association between this genetic variant and hepatoblastoma susceptibility was determined via logistic regression models adjusted for age and sex. RESULTS: Our results show that the TC genotype of the miR-34b/c rs4938723 polymorphism is associated with a significantly reduced risk of hepatoblastoma under a heterozygous model (adjusted OR = 0.59, 95% CI = 0.41-0.84, P = 0.003), whereas the CC genotype is associated with an increased risk under a recessive model (adjusted OR = 1.79, 95% CI = 1.17-2.73, P = 0.008). Further stratified analysis revealed that the TC/CC genotypes were linked to a lower risk of hepatoblastoma in girls and those with advanced clinical stages (III + IV). Furthermore, we identified the miR-34b/c rs4938723 polymorphism as an expression quantitative trait locus that affects the expression of nearby genes. The CC genotype was related to a decrease in LAYN expression in the colon, brain, and lung and decreased PPP2R1B expression in the testis. These findings suggest that miR-34b/c rs4938723 T > C has the potential to modify hepatoblastoma predisposition through its regulatory effects on gene expression. CONCLUSIONS: This study provides evidence for the association between the miR-34b/c rs4938723 polymorphism and hepatoblastoma risk in Chinese Han children from East China, suggesting that this polymorphism may have potential as a biomarker for predicting hepatoblastoma susceptibility in this specific population.

Child↗
PubMed2024

Genetic variants reduced POPs-related colorectal cancer risk via altering miRNA binding affinity and m6A modification.

Exposure to persistent organic pollutants (POPs) may contribute to colorectal cancer risk, but the underlying mechanisms of crucial POPs exposure remain unclear. Hence, we systematically investigated the associations among POPs exposure, genetics and epigenetics and their effects on colorectal cancer. A case-control study was conducted in the Chinese population for detecting POPs levels. We measured the concentrations of 24 POPs in the plasma using gas chromatography-tandem mass spectrometry (GC-MS/MS) and evaluated the clinical significance of POPs by calculating the area under the receiver operating characteristic curve (AUC). To assess the associations between candidate genetic variants and colorectal cancer risk, unconditional logistic regression was used. Compared with healthy control individuals, individuals with colorectal cancer exhibited higher concentrations of the majority of POPs. Exposure to PCB153 was positively associated with colorectal cancer risk, and PCB153 demonstrated superior accuracy (AUC=0.72) for predicting colorectal cancer compared to other analytes. On PCB153-related genes, the rs67734009 C allele was significantly associated with reduced colorectal cancer risk and lower plasma levels of PCB153. Moreover, rs67734009 exhibited an expression quantitative trait locus (eQTL) effect on ESR1, of which the expression level was negatively related to PCB153 concentration. Mechanistically, the risk allele of rs67734009 increased ESR1 expression via miR-3492 binding and m6A modification. Collectively, this study sheds light on potential genetic and epigenetic mechanisms linking PCB153 exposure and colorectal cancer risk, thereby providing insight into the accurate protection against POPs exposure.

Humans↗
PubMed2025

Association of AGER genetic variants with chronic obstructive pulmonary disease susceptibility in Southern Chinese Han populations.

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) remains a leading cause of disability and mortality among elderly populations. Studies indicate that AGER plays a critical regulatory role in the pathogenesis of respiratory disorders. However, the genetic variations in AGER to COPD susceptibility remain incompletely understood. This study employs a case-control design to investigate associations between AGER genetic variants and COPD risk in the Southern Chinese Han population. METHODS: This study enrolled 270 COPD patients and 271 healthy controls. AGER single-nucleotide polymorphisms (SNPs) were analysed using the MassARRAY iPLEX platform. Logistic regression models evaluated associations between AGER polymorphisms and COPD susceptibility, with false discovery rate (FDR) correction applied to mitigate multiple testing errors. SNP-SNP interactions were investigated through multifactor dimensionality reduction (MDR) analysis. Expression quantitative trait locus (eQTL) data from the GTEx database were further analysed to assess regulatory relationships between SNPs and AGER gene expression levels. RESULTS: This study showed that rs3134941 (G allele, OR = 0.21, 95% CI = 0.10-0.41, p (FDR) = 0.001) and rs3131300 (G allele, OR = 0.32, 95% CI = 0.20-0.49, p (FDR) = 0.0001) were significantly associated with a reduced susceptibility to COPD. MDR indicated that rs3131300 was the optimal predictive model for COPD risk. Additionally, initial mechanistic investigations utilizing the GTEx database identify rs3134941 (C > G) and rs3131300 (A > G) as significant expression quantitative trait loci for AGER mRNA in cell-cultured fibroblasts and whole blood. CONCLUSION: Our study demonstrated that AGER genetic variants might play a protective role in the progression of COPD.

Aged↗
PubMed2026

FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies.

Transcriptome-wide association studies (TWAS) integrate genome wide association studies with expression quantitative trait locus reference panels to identify genes associated with traits of interest. However, linkage disequilibrium and correlated gene expression can induce spurious TWAS signals, motivating fine mapping methods to prioritize putatively causal genes within associated loci. The rapid growth of large-scale phenomic resources (e.g. electronic health records (EHRs)) has shifted genetic studies from single-trait analyses to phenome-wide investigations that jointly evaluate many closely related phenotypes. We introduce FM-GPT (Fine-mapping of causal Genes for Phenome-wide Transcriptome-wide association studies), a novel Bayesian fine mapping method for prioritizing causal genes across multiple correlated phenotypes with potentially mixed outcome types (e.g., binary, count or continuous) in phenome-wide TWAS. FM-GPT performs gene-guided dimension reduction of the phenotypes and reveals pleiotropic or phenotype-specific effects of the identified genes. In simulations, FM-GPT identified true causal genes more accurately than other fine mapping methods while controlling false positives. We applied FM-GPT to two applications using data from UK Biobank: a brain-wide genetic analysis of MRI data derived regional cortical thickness measures and a phenome-wide genetic analysis of clinical phenotypes derived from EHR data. FM-GPT greatly narrowed down the set size of putatively causal genes and identified: 1. genes with pleiotropic effects on regional cortical thickness across the cerebral cortex, including five genes BCAS3, LRRC37A, NOS2P3, ARL17B and UBB on chromosome 17 regulating neuronal morphology and cortical organization; and 2. genes that influence multiple medical conditions across the circulatory, metabolic, digestive, respiratory and genitourinary systems, revealing two major axes of variation among these conditions that point to a potential trade-off in gene regulation between immune and metabolic functions. These results highlight FM-GPT's power to disentangle complex gene-phenotype relationships in large-scale phenome-wide studies, uncovering shared biological mechanisms across diverse human traits and advancing translational and comorbidity research.

Bayesian fine mapping↗
PubMed2026

The bioinformatics approach to identifying pathogenic variants for colorectal cancer (CRC).

Colorectal cancer (CRC) is the third most prevalent cancer globally, accounting for 9.6% of newly diagnosed cases and 9.3% of cancer-related deaths. It develops from the uncontrolled proliferation of glandular cells in the colon and rectum and is categorized into three primary types: sporadic, hereditary, and colitis-associated. While genetic susceptibility is a key factor in CRC pathogenesis, identifying high-impact pathogenic variants remains a significant challenge. This study integrates bioinformatics and population genetics approaches to identify CRC-associated single-nucleotide polymorphisms (SNPs) with potential clinical significance. CRC-associated SNPs were extracted from the Genome-Wide Association Studies (GWAS) Catalog, functionally annotated via HaploReg, and validated via Ensembl. In addition, expression quantitative trait locus (eQTL) data from the GTEx database were used to assess the effects of these variants on gene expression across human tissues. Our analysis identified three high-priority SNPs (rs9379084, rs3184504, and rs11557154) associated with the RREB1, ATXN2, SH2B3, and DCAF12 genes, which exhibited marked allele frequency differences among populations. These findings suggest potential biomarkers for CRC risk assessment and highlight the importance of genetic screening across diverse populations.

Bioinformatics↗
PubMed2026

Genetic evidence and cross-species functional characterization implicate CNN2 in age-related macular degeneration susceptibility.

Age-related macular degeneration (AMD) is a leading cause of irreversible visual impairment in the aging population globally. Although genome-wide association studies (GWAS) have identified many AMD susceptibility loci, the genes and mechanisms underlying many of these associations remain unresolved. Here, we integrated expression quantitative trait locus (eQTL) data with AMD GWAS to prioritize nine putative genes. Through in vivo screening in zebrafish, we demonstrated that the downregulation of cnn2 and sarm1 expression led to ocular structural abnormalities and visual functional impairment. Subsequent mouse model studies confirmed that Cnn2 deficiency affected photoreceptor structure and function, impaired contrast sensitivity, and caused abnormalities in cone cell immunostaining. Given that CNN2 is predominantly expressed in endothelial cells, we propose that endothelial dysfunction may cascade to impair photoreceptor function. Collectively, through in silico prioritization and cross-species functional characterization, we identify CNN2 as a candidate susceptibility gene in AMD pathogenesis, providing vital underlying mechanistic insights.

Animals↗
PubMed2026

Integrative TWAS and multi-omics analyses prioritize HSPE1 as a candidate risk gene for bipolar disorder with immune cell-specific regulatory evidence.

BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder associated with substantial disability. Although genome-wide association studies have identified multiple BD-associated loci, the underlying genes and mechanisms remain incompletely understood. METHODS: We integrated a European-ancestry BD genome-wide association dataset with cross-tissue and tissue-specific transcriptome-wide association studies (TWAS) and complementary gene-based analysis. Candidate genes were further evaluated using differential expression analysis, consensus clustering, immune infiltration analysis, machine learning, summary-data-based Mendelian randomization, Mendelian randomization using single-cell expression quantitative trait locus data, single-nucleus transcriptomics, phenome-wide association analysis, and virtual screening. RESULTS: The integrative analyses prioritized 37 candidate genes. Peripheral-blood differential-expression analysis identified 14 genes that remained significant after FDR correction, and their expression profiles separated BD samples into two expression-defined clusters. Machine-learning analysis selected UNC50, LMAN2L, LYG2, HSPE1, and KANSL3 for an exploratory classification nomogram. SMR associated genetically predicted higher HSPE1 expression with increased BD risk in two blood eQTL datasets. Cell-type-specific analyses indicated HSPE1-related associations in T-cell and natural killer cell subsets, while single-nucleus analysis descriptively showed higher HSPE1 expression in medial thalamic T cells from BD samples. PheWAS identified no genome-wide significant associations for HSPE1, whereas virtual screening identified candidate compounds with favorable predicted docking scores against the HSPE1 structure. CONCLUSION: This integrative multi-omics study identified HSPE1 as a candidate BD risk gene with immune-cell-related regulatory evidence, providing insight into BD pathogenesis and supporting functional validation.

Humans↗
PubMed2025

Identification of novel type 1 and type 2 diabetes genes by co-localization of human islet eQTL and GWAS variants with colocRedRibbon.

Over 1,000 genetic variants have been associated with diabetes by genome-wide association studies (GWASs), but for most, their functional impact is unknown; only 7% alter gene expression in pancreatic islets in expression quantitative trait locus (eQTL) studies. To fill this gap, we developed a co-localization pipeline, colocRedRibbon, that prefilters eQTLs by the direction of effect on gene expression and shortlists overlapping eQTL and GWAS variants prior to co-localization. Applying colocRedRibbon to recent diabetes and glycemic trait GWASs, we identified 292 co-localizing gene regions, including 24 co-localizations for type 1 diabetes and 268 for type 2 diabetes and glycemic traits, representing a 4-fold increase. A low-frequency type 2 diabetes protective variant increases islet MYO5C expression, and a type 1 diabetes protective variant increases FUT2 expression. These novel co-localizations advance the understanding of diabetes genetics and its impact on human islet biology. colocRedRibbon has broad applicability to co-localize GWASs and various QTLs.

Humans↗
PubMed2026

Integrative genomic and transcriptomic analysis of hypertension in a Taiwanese population.

OBJECTIVES: Hypertension is highly prevalent in Asian populations and represents a major cardiovascular risk factor. However, most genome-wide association studies (GWASs) and transcriptome-wide association studies (TWASs) have focused primarily on Caucasian cohorts. This study aimed to identify genetic loci and gene expression signatures associated with hypertension in an Asian population. METHODS: We analyzed 10 739 hypertensive patients and 49 668 controls from the Taiwan Biobank, testing 4 512 191 genome-wide single nucleotide polymorphisms (SNPs). Integrated GWAS, TWAS, and expression quantitative trait locus (eQTL) analyses were conducted to characterize genetic risk. Additionally, a polygenic risk score (PRS) was constructed using a split-sample design to evaluate genetic risk stratification. RESULTS: We identified 14 loci significantly associated with hypertension, including a novel locus at 5p13.1. eQTL analysis linked this locus to DAB2 expression in whole blood. TWAS detected 55 hypertension-associated genes, with 20 (36%) overlapping GWAS loci. Several novel genes outside GWAS loci, including FBXL15, KCNIP2, and CRIP3, were highly significant and implicated in vascular biology and hypertension mechanisms. PRS analysis effectively differentiated hypertension risk, with individuals in the top 10% showing a > 3.5-fold increased risk compared to the bottom 10%. CONCLUSIONS: Our findings provide new insights into the genetic and transcriptomic landscape of hypertension in Asians. The identification of novel loci and genes advances understanding of disease biology and may guide precision medicine approaches for risk prediction and therapeutic development.

Female↗
PubMed2026

Overlapping genetic etiology of pediatric and adult germ cell tumors.

BACKGROUND: Germ cell tumors are heterogeneous neoplasms arising from primordial germ cells. Although genome-wide association studies have identified numerous susceptibility loci for adult testicular germ cell tumors, the heritable basis of pediatric testicular germ cell tumors and germ cell tumors that arise outside the testes remain poorly understood. METHODS: We conducted a multi-ancestry genome-wide association study of pediatric germ cell tumors, including 1927 cases from the Germ Cell Tumor Epidemiology Study and 10 601 controls. Cases were diagnosed with testicular (n = 678), ovarian (n = 441), intracranial (n = 435), and extragonadal (n = 373) germ cell tumor between the ages of 0 and 19 years. RESULTS: We identified 4 loci reaching genome-wide significance, including variants near BAK1 (chr 6: rs3831846), SPRY4 (chr 5: rs12515244), DMRT1 (chromosome [chr] 9: rs10815910), and DEPTOR (chr 8: rs13277786). Additional genome-wide statistically significant associations were identified in subgroup analyses, including 6 loci for intracranial germ cell tumors (rs2758612 [PMF1/BGLAP], rs9854760 [PLCL2], rs6851498 [KIT], rs11816992 on chromosome 10, rs3830273 [TFAM], and rs13054014 [LZTR1]), 1 locus for testicular germ cell tumor (rs1907702 [KITLG]), and 1 locus for males (rs4610628 [MAD1L1]). After Bonferroni correction, 18 of 78 previously reported testicular germ cell tumor loci were significantly associated with germ cell tumor overall or in at least 1 subgroup with a particularly strong correlation between testicular germ cell tumor and intracranial germ cell tumor effect estimates (rho = 0.63, P = 5.5 × 10-10). Expression quantitative trait locus (QTL) analyses identified candidate genes in the regions identified on chromosome 6 (BAK1, LINC003366, and ITPR3) and chromosome 8 (DEPTOR and RP11-760H22.2). CONCLUSIONS: Our data support a role for germline genetic variation in the development of germ cell tumors in locations outside the testes and highlight shared genetic architecture across age group and tumor location.

Humans↗
PubMed2026

Shared genetic architecture of smoking dependence and Crohn's disease: A cross-trait analysis of GWAS summary statistics.

INTRODUCTION: Smoking dependence (SD) and Crohn's disease (CD) are epidemiologically associated, but whether this relationship reflects shared genetic susceptibility remains unclear. METHODS: We conducted a cross-trait genetic analysis of SD and CD using publicly available genome-wide association study (GWAS) summary statistics from European-ancestry populations. Genome-wide genetic correlation was estimated using linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL). Pleiotropic variants were identified using PLACO and mapped to genomic loci using FUMA. Regional signal sharing was assessed by Bayesian colocalization. Functional analyses included stratified LDSC, Multi-marker Analysis of GenoMic Annotation (MAGMA), GTEx tissue analysis, and Metascape. Expression-linked candidate genes were prioritized using expression quantitative trait locus (eQTL)-based summary-data-based Mendelian randomization (SMR) with heterogeneity in dependent instruments (HEIDI) testing. Genetically informed spatial mapping of cells for complex traits (gsMap) was used for spatial mapping. RESULTS: SD and CD showed positive genetic correlation by LDSC (rg=0.2090, p=0.0008) and HDL (rg=0.3817, p=0.00106). PLACO identified 81 genome-wide significant pleiotropic SNPs, which were mapped by FUMA to three loci at 1p31.3, 5p13.1, and 12q12, represented by rs11209031, rs1395152, and rs17467116, respectively. MAGMA identified 22 FDR-significant genes, four of which remained Bonferroni significant: LRRK2, TNFRSF6B, ZGPAT, and RP4-583P15.15. Cross-trait tissue analysis showed significant enrichment of the shared genetic signal in whole blood and small intestine, while gene-set analysis highlighted inflammatory response (pbon=1.86×10-5) and T-helper 17 cell differentiation (pbon=7.37×10-4). SMR/HEIDI analysis further prioritized RPS6KB1 as a shared expression-linked candidate. Spatial mapping revealed a prominent signal in the embryonic gastrointestinal tract and gene-specific regional patterns involving LRRK2 and SLC2A13 in the adult mouse brain. CONCLUSIONS: SD and CD showed measurable shared genetic susceptibility, with convergent evidence from pleiotropic loci, immune-inflammatory pathway enrichment, tissue-level associations, and spatial transcriptomic mapping.

Crohn's disease↗
PubMed2025

Integrative omics of the genetic basis for wheat WUE and drought resilience reveal the function of TaMYB7-A1.

Improving wheat drought resilience and water use efficiency (WUE) is critical for sustaining productivity under increasing water scarcity. Here, we integrate genome-wide association study (GWAS), expression quantitative trait locus (eQTL) mapping, population-transcriptome analysis, and summary-data-based mendelian randomization (SMR), followed by functional validation using indexed EMS mutants and transgenic lines, to systematically identify key WUE regulators. GWAS across water conditions in 228 accessions identifies 73 quantitative trait loci (QTLs) for WUE-traits. Transcriptome profiling of 110 diverse accessions reveals 28 drought-responsive modules. eQTL mapping uncovers 146,966 regulatory variants, including condition-specific hotspots associated with key drought-related pathways. Integrative analysis underscores 85 high-confidence candidate genes, notably TaMYB7-A1. Overexpression of TaMYB7-A1 enhances photosynthesis, WUE, root development, and grain yield under drought condition by activating TaPIP2;2-B1 (water transport), TaRD20-D1 (stomatal regulation), and TaABCB4-B1 (root growth), reflecting reduced water loss and improved physiological resilience. Our study presents a comprehensive regulatory map and robust targets for wheat drought adaptation and resilient cultivar breeding.

Triticum↗
PubMed2025

Saturating the eQTL map in Drosophila: Genome-wide patterns of cis and trans regulation of transcriptional variation in outbred populations.

Most genetic polymorphisms associated with complex traits are found in non-coding regions of the genome. Characterizing their effect presents a formidable challenge, and expression quantitative trait locus (eQTLs) mapping has been a key approach to do so. As comprehensive eQTL maps are available only for a few species, here we developed the Drosophila outbred synthetic population (Dros-OSP) and used it to characterize the landscape of transcriptional regulation in Drosophila melanogaster. We collected head and body transcriptomes and genomes from 1,286 outbred flies and mapped local and distant eQTLs for 98% of the genes. We characterized the network organization of the transcriptome across tissues and described the properties of local and distal eQTLs in terms of genetic diversity, heritability, connectivity, and pleiotropy. These results provide new insights into the genetic basis of transcriptional regulation in the fruit fly and offer a new mapping resource that will expand the possibilities currently available for the Drosophila community.

Animals↗
PubMed2025

Genetic Architecture of Idiopathic Inflammatory Myopathies From Meta-Analyses.

OBJECTIVE: Idiopathic inflammatory myopathies (IIMs, myositis) are rare systemic autoimmune disorders that lead to muscle inflammation, weakness, and extramuscular manifestations, with a strong genetic component influencing disease development and progression. Previous genome-wide association studies identified loci associated with IIMs. In this study, we imputed data from two prior genome-wide myositis studies and analyzed the largest myositis data set to date to identify novel risk loci and susceptibility genes associated with IIMs and its clinical subtypes. METHODS: We performed association analyses on 14,903 individuals (3,206 patients and 11,697 controls) with genotypes and imputed data from the Trans-Omics for Precision Medicine reference panel. Fine-mapping and expression quantitative trait locus colocalization analyses in myositis-relevant tissues indicated potential causal variants. Functional annotation and network analyses using the random walk with restart (RWR) algorithm explored underlying genetic networks and drug repurposing opportunities. RESULTS: Our analyses identified novel risk loci and susceptibility genes, such as FCRLA, NFKB1, IRF4, DCAKD, and ATXN2 in overall IIMs; NEMP2 in polymyositis; ACBC11 in dermatomyositis; and PSD3 in myositis with anti-histidyl-transfer RNA synthetase autoantibodies (anti-Jo-1). We also characterized effects of HLA region variants and the role of C4. Colocalization analyses suggested putative causal variants in DCAKD in skin and muscle, HCP5 in lung, and IRF4 in Epstein-Barr virus (EBV)-transformed lymphocytes, lung, and whole blood. RWR further prioritized additional candidate genes, including APP, CD74, CIITA, NR1H4, and TXNIP, for future investigation. CONCLUSION: Our study uncovers novel genetic regions contributing to IIMs, advancing our understanding of myositis pathogenesis and offering new insights for future research.

Humans↗