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PubMed2005

Expression quantitative trait loci analysis of 13 genes in the rat prostate.

Differential expression of mRNA among animal strains is one of the mechanisms for their diversity. cDNA microarray analysis of the prostates of BUF/Nac (BUF) and ACI/N (ACI) rats, which show different susceptibility to prostate cancers, found 195 differentially expressed genes. To identify loci that control differential expression of 13 genes with diverse expression levels, their expression levels were measured by quantitative RT-PCR in 89 backcross rats, and expression quantitative trait locus (eQTL) analysis was performed. Nine genes [Aldh1a1, Aldr1, Bmp6, Cdkn1a (p21), Cntn6, Ghr, Jund, Nupr1, and RT1-M3] were controlled by cis-acting loci. Cdkn1a, a cell cycle regulator and a candidate for a prostate cancer susceptibility gene, was mapped to its own locus and had polymorphisms, including a 119-bp insertion in the 5' upstream region in BUF rats. Four genes (Kclr, Pbsn, Psat1, and Ptn) were controlled by trans-acting loci. Pbsn, a prostate-specific gene on chromosome X, was controlled by a QTL on chromosome 8. Depending upon which gene that we selected from the genes widely used for normalization (Actb, Gapd, or Ppia), different QTL were mapped for Kclr, Psat1, and Ptn. Normalization using Actb most appropriately explained the expression levels in a congenic strain for chromosome 3. eQTL analysis with precise measurement of expression levels and appropriate normalization was shown to be effective for mapping loci that control gene expression in vivo.

Animals↗

PubMed2026

Integrated bioinformatics analyses for GSDMB in carcinogenesis and progression of bladder cancer.

BACKGROUND: Emerging evidence suggests that pyroptosis influences the development of various diseases. Gasdermin B (GSDMB), an intracellular protein that executes pyroptosis, has recently attracted attention for its potential role in tumor biology. However, its specific function in bladder cancer (BLCA) remains unclear. Therefore, this study aimed to investigate the potential role of GSDMB in the carcinogenesis and prognosis of BLCA patients. METHODS: Mendelian randomization (MR) studies were conducted to examine relationships between the expression of GSDMB and BLCA with expression quantitative trait loci (eQTL) data. Then, GSDMB mRNA expression data and clinical characteristics of BLCA patients were retrieved from The Cancer Genome Atlas (TCGA) database. Cox regression was used to explore the relationship between GSDMB mRNA expression and patients' survival. Additionally, the correlation between GSDMB and the immune microenvironment, tumor mutational burden (TMB), tumor microenvironment (TME), and drug sensitivity in BLCA was examined. RESULTS: According to MR analysis based on eQTLs, GSDMB mRNA expression has positive causal effects on bladder carcinogenesis and the need for bladder surgery (P<0.05). The analyses of TCGA demonstrated an increased expression of GSDMB in BLCA tissues, correlating with improved patient survival. Additionally, elevated GSDMB mRNA expression was identified as an independent protective prognostic factor for BLCA, and it was associated with immune cell infiltration, TMB, TME score, and drug sensitivity. CONCLUSIONS: Elevated mRNA expression of GSDMB has a causal link to a higher risk of BLCA and the likelihood of bladder surgery, but also indicates a better prognosis. Thus, GSDMB exhibits dual effects and might serve as a potential biomarker for predicting onset and progression of BLCA. Nevertheless, further investigation of pathogenesis and mechanisms underlying GSDMB is warranted.

Bladder cancer (BLCA)↗

PubMed2026

Multi-omics Mendelian Randomization Prioritizes Neutrophil Extracellular Trap-related Genes Associated with Atrial Fibrillation Risk.

BACKGROUND: Neutrophil extracellular traps (NETs) participate in thrombosis, inflammation, and cardiovascular remodeling, yet whether NET-related genes (NRGs) are associated with atrial fibrillation (AF) risk across multiple molecular layers remains unclear. This study used a multiomics Mendelian randomization framework to prioritize NRGs supported by methylation, expression, and protein quantitative trait loci (QTL) data. METHODS: Genome-wide significant cis instruments (P < 5 × 10-8) were obtained for 90 methylation QTLs (mQTLs), 100 expression QTLs (eQTLs), and 38 protein QTLs (pQTLs) mapped to 137 literature- curated NRG entries. Summary-data-based Mendelian randomization (SMR) coupled with the heterogeneity in dependent instruments (HEIDI) test was applied using whole-blood mQTL data (n = 1,980), eQTLGen blood eQTL data (n = 31,684), and deCODE plasma pQTL data (n = 35,559). AF outcome data were obtained from a meta-analysis including 60,620 cases and 970,216 controls of European ancestry. RESULTS: At the methylation level, 21 CpG-feature associations across 13 genes remained significant after HEIDI filtering and false discovery rate (FDR) correction. Expression-level analysis identified eight significant gene-AF associations, whereas protein-level analysis identified seven significant features representing five unique proteins. Cross-omics integration prioritized C3, MAPK3, and STAT3 as Tier 1 genes, CTSC, LPAR3, and THBD as Tier 2 genes, and fourteen additional genes as Tier 3 candidates. C3 showed risk-increasing protein-level associations together with multiple significant CpG signals, whereas MAPK3 and STAT3 showed directionally protective expression/protein or methylation/protein patterns. DISCUSSION: The cross-omics convergence on C3, MAPK3, and STAT3 is consistent with complement activation, immune-fibrotic signaling, and cytokine-regulatory pathways implicated in AF biology, but the findings should be interpreted as genetic prioritization rather than definitive intervention-ready causality. CpG-level heterogeneity at the C3 locus and the blood/plasma origin of the QTL resources further support a cautious interpretation. Modest colocalization support and the unresolved possibility of pQTL sample overlap further support this cautious, hypothesis-generating interpretation. CONCLUSION: Multi-omics SMR prioritizes C3, MAPK3, and STAT3 as the most consistently supported NET-related genes associated with AF risk. These findings provide a framework for atrialtissue replication and mechanistic validation of NET-related pathways in AF.

Atrial fibrillation↗

PubMed2026

Potential mitochondria-associated pathogenic genes in sepsis: a multi-omics Mendelian randomization study.

BACKGROUND: Mitochondrial dysfunction has been implicated in the pathophysiology of sepsis. However, human genetic evidence linking mitochondria-related genes to sepsis susceptibility remains limited. This study aimed to identify mitochondria-related genes associated with sepsis risk using a multi-omics Mendelian randomization framework. METHODS: Summary-data-based Mendelian randomization (SMR) was applied using sepsis genome-wide association study (GWAS) summary statistics from the UK Biobank and FinnGen databases. Expression, methylation, single-cell, and protein quantitative trait loci (QTLs) were used as genetic instruments. Colocalization analyses were conducted to evaluate whether SMR associations were driven by shared genetic variants. Expression of prioritized candidate genes was further examined in clinical septic samples, and correlations with disease severity (SOFA scores) were assessed. RESULTS: SMR analysis prioritized 13 mitochondria-related genes associated with sepsis risk. Immune cell-specific eQTL analysis suggested that genetically predicted SURF1 expression in memory B cells and naïve T cells was associated with sepsis risk. Differential expression of 12 candidate genes was confirmed in septic patients by qPCR, and PPOX expression showed a negative correlation with SOFA scores. Integration of mQTL and eQTL data supported a regulatory relationship between methylation at cg06661924 and AK4 expression. Increased genetically predicted AK4 expression was associated with higher sepsis risk (OR = 1.21, 95% CI 1.02-1.42). Protein-level analysis identified DUT as a potential sepsis-associated candidate, with consistent evidence across streptococcal and pneumococcal septicemia subtypes. Subtype analyses also suggested heterogeneous genetic signals across different sepsis subtypes. CONCLUSION: This study prioritized several mitochondria-related genes associated with sepsis susceptibility based on human genetic evidence. These findings provide candidate targets for further mechanistic and translational investigation.

Humans↗

PubMed2026

Integrated multi-omics identification of m6A-SNP-related diagnostic biomarkers in amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) lacks reliable and minimally invasive biomarkers for early diagnosis. m6A-associated single-nucleotide polymorphisms (m6A-SNPs) may influence RNA methylation and gene expression, offering opportunities to identify clinically relevant diagnostic markers. METHODS: We integrated eQTLGen cis-eQTL data, RMVar m6A-SNP annotations, and ALS transcriptomic datasets to identify m6A-SNP-related genes. Random Forest and LASSO regression were combined to screen robust diagnostic markers. A nomogram was constructed and validated using independent cohorts. Immune infiltration, predicted m6A modification sites, and potential RBP-SNP interactions were assessed. Peripheral blood samples from ALS patients were used for exploratory validation of gene expression and global m6A levels. RESULTS: We identified 109 ALS-associated m6A-SNP-related genes with cis-eQTL signals and narrowed these to seven candidate diagnostic markers (TMED5, OXR1, BRI3, FEM1C, SUZ12, EIF2AK4, and TJAP1). The seven-gene model outperformed the individual markers in the training cohort and retained moderate discrimination in the independent validation cohort. ALS samples showed differences in inferred immune-cell composition, including monocytes, neutrophils, and T-cell subsets. The selected SNP loci were located near predicted m6A sites and annotated RBP-binding regions. Exploratory clinical validation showed significant upregulation of FEM1C and SUZ12 at both mRNA and protein levels, accompanied by reduced global m6A modification. CONCLUSIONS: Through multi-omics integration and exploratory clinical validation, this study identifies m6A-SNP-related candidate markers associated with ALS. The findings support further evaluation of m6A-related signatures for ALS discrimination and molecular characterization, while larger independent cohorts and additional calibration are required before clinical application.

Humans↗

PubMed2026

Multi-trait GWAS identifies pleiotropic loci shared between early pregnancy bleeding and psychiatric traits.

INTRODUCTION: Early pregnancy bleeding is a common pregnancy complication, yet its genetic basis and potential links with psychiatric traits remain poorly understood. This study aimed to characterize the shared genetic architecture between early pregnancy bleeding and reproductive, psychiatric, and cardiometabolic traits. METHODS: We integrated linkage disequilibrium score regression (LDSC), local genetic correlation analysis (LAVA), and multi-trait genome-wide association analysis (MTAG). LDSC was used to estimate genome-wide genetic correlations, including sex-stratified analyses. LAVA was applied to identify genomic regions contributing to local genetic sharing. Guided by these correlation patterns, MTAG was performed to improve locus discovery, followed by cis-eQTL analysis using GTEx v8 to explore potential regulatory mechanisms. RESULTS: LDSC revealed significant positive genetic correlations between early pregnancy bleeding and reproductive traits, including endometriosis, miscarriage, and uterine fibroids. Strong positive correlations were also observed with several psychiatric disorders, including major depressive disorder, post-traumatic stress disorder, and attention deficit hyperactivity disorder. Sex-stratified analyses suggested stronger genetic correlations with emotional reactivity-related traits in females, whereas social and behavioral traits were more prominent in males. LAVA localized these shared signals to specific genomic regions and identified pleiotropic hotspots at 8q21 near RUNX1T1 and 9p21 near CDKN2A/B. MTAG identified two novel loci, 15q15.1 marked by rs45457497 and 11q13.1 marked by rs2452681. Cis-eQTL analysis showed that the lead variant at 15q15.1 regulates RMDN3 expression across multiple brain regions, while the 11q13.1 locus regulates PACS1, GAL3ST3, and SF3B2 expression in brain tissues and the pituitary. DISCUSSION: These findings position early pregnancy bleeding as a multifactorial trait shaped by shared reproductive, psychiatric, neuroendocrine, and stress-related biology. The implication of RMDN3, which encodes a mitochondrial outer membrane protein involved in ER-mitochondria tethering and calcium homeostasis, suggests a potential molecular link between neuroendocrine stress pathways, psychiatric susceptibility, and reproductive vulnerability.

RMDN3↗

PubMed2026

Multistage Genetic, Transcriptomic, and Single-Cell Evidence Prioritizes MAP1LC3A among Ferroptosis-Related Genes in Glioblastoma.

Glioblastoma (GBM) remains a highly aggressive malignancy, and the contribution of ferroptosis-related genes to disease susceptibility remains incompletely understood. A genetically anchored, multistage framework was applied to prioritize ferroptosis-related genes associated with GBM. Among 483 genes curated from FerrDb V2, 315 had candidate cis-expression quantitative trait loci (cis-eQTLs) in eQTLGen, 250 retained at least three independent instruments after linkage disequilibrium clumping, and 226 yielded valid inverse-variance weighted (IVW) Mendelian randomization estimates using a GBM genome-wide association study comprising 6,183 cases and 18,169 controls. Thirty-four genes met the exploratory discovery criteria of P < 0.05 and a Benjamini-Hochberg false discovery rate (BH-FDR) < 0.20, with directionally concordant Bayesian weighted Mendelian randomization (BWMR) estimates. Replication-stage Mendelian randomization using GTEx V10 whole-blood cis-eQTLs supported four genes: ATG7, RPTOR, MAP1LC3A, and CHMP6. Evaluation across three independent tumor-control transcriptomic cohorts demonstrated that MAP1LC3A was consistently downregulated in tumor tissue and showed a significant random-effects pooled estimate (log₂ fold change, -1.273; 95% confidence interval, -1.625 to -0.920; false discovery rate = 0.016), whereas the other three genes lacked comparable cross-cohort statistical support. Single-cell virtual knockout analysis was subsequently performed in a patient-balanced subset of 2,400 malignant cells selected from 4,916 eligible cells across 20 adult IDH-wild-type GBM tumors. Across five independently seeded runs, 3, 15, 4, and 7 robust downstream genes were identified for ATG7, RPTOR, MAP1LC3A, and CHMP6, respectively. The resulting consensus sets comprised 17 unique genes, with RND3 shared across all four targets. Gene Ontology analysis indicated enrichment of cell-adhesion and cell-surface processes, whereas no KEGG or Reactome pathways remained significant after multiple-testing correction. Collectively, these findings prioritize MAP1LC3A for future experimental investigation while distinguishing genetic association, tumor-expression concordance, and computational perturbation from definitive evidence of causality or mechanism.

Humans↗

PubMed2026

Disentangling adiposity-related and non-adiposity-related genetic pathways for type 2 diabetes.

OBJECTIVE: To identify circulating proteins associated with type 2 diabetes (T2D) risk through pathways not fully explained by body mass index (BMI), and to assess therapeutic actionability. RESEARCH DESIGN AND METHODS: We applied GWAS-by-subtraction within a genomic structural equation model to European ancestry summary statistics for T2D (74,124 cases, 824,006 controls) and BMI (n = 681,275), partitioning T2D liability into BMI-related and BMI-subtracted components. We then performed proteome-wide Mendelian randomization (MR) using cis-protein quantitative trait loci from four plasma proteomics cohorts: ARIC, deCODE, Fenland, and the UK Biobank Pharma Proteomics Project. Prioritized proteins passed sensitivity analyses with alternative MR methods and were supported by colocalization evidence. Tissue-resolution regulatory support was assessed using cis-eQTL colocalization across GTEx and pancreatic islet, subcutaneous adipose, and whole-blood resources. Actionability was evaluated using the druggable genome and Open Targets. RESULTS: GWAS-by-subtraction attenuated the genetic correlation between BMI and BMI-subtracted T2D from 0.54 (SE 0.02) to 0.35 (SE 0.02). Proteome-wide MR prioritized 29 proteins for BMI-subtracted T2D. Thirteen showed eQTL colocalization in at least one tissue, implicating liver and intermediary metabolism (GCDH, NOTCH2), pancreatic islet biology (CTRB2, MANBA), adipose and Wnt signaling (RSPO3, GALNT3), and whole blood regulatory signals (PAM, SNUPN). Sixteen proteins were classified within druggable-genome Tiers 1-3, and five had existing Open Targets compounds. CONCLUSIONS: Integrating GWAS-by-subtraction, proteome-wide MR, and colocalization nominated 29 proteins associated with T2D liability not fully explained by BMI. These findings highlight genetically supported targets for follow-up studies of T2D therapies that complement weight-centered approaches.

Journal Article↗

PubMed2026

Genetic evidence prioritizes circulating proteins for heart failure beyond shared BMI-related genetic liability.

BACKGROUND: Heart failure (HF) and body mass index (BMI) share substantial genetic architecture, which may lead genetically informed target discovery to preferentially identify adiposity-related pathways. We sought to identify circulating proteins associated with HF beyond this shared genetic component. METHODS: We applied GWAS-by-subtraction to overall HF, nonischemic HF, and nonischemic HF with reduced or preserved ejection fraction to derive BMI-related and BMI-subtracted HF components. We then performed proteome-wide cis-pQTL Mendelian randomization and colocalization using four independent proteomic cohorts, followed by tissue-specific eQTL colocalization, cardiac transcriptomic annotation, and druggability assessment. RESULTS: Compared with the original HF phenotypes, the BMI-subtracted components showed attenuated genetic correlations with BMI (0.045-0.147) while retaining 28 independent loci for overall HF and nine for nonischemic HF. Across 19,930 protein-HF tests, 11 associations involving nine proteins were prioritized by the Mendelian randomization and colocalization analyses. For example, a 1-SD increase in genetically predicted CELSR2 abundance was associated with lower overall HF risk (odds ratio, 0.96 [95% CI, 0.94-0.98]; P=8.6×10-7), whereas a 1-SD increase in genetically predicted CSF3 abundance was associated with higher nonischemic HF risk (odds ratio, 1.32 [95% CI, 1.18-1.48]; P=2.0×10-6). CELSR2 and TMEM106B colocalized with cis-eQTLs in failing left ventricular myocardium, and DAG1 showed cardiomyocyte enrichment with concordant downregulation in failing hearts. CONCLUSIONS: We identified nine circulating proteins associated with HF beyond the genetic component shared with BMI. These findings extend the range of genetically supported pathways implicated in HF and nominate candidate proteins for further mechanistic and therapeutic investigation.

Genetics↗

PubMed2025

Genome-Wide Association Analyses of HPV16 and HPV18 Seropositivity Identify Susceptibility Loci for Cervical Cancer.

Infection by high-risk human papillomavirus is known to exacerbate cervical cancer development. The host immune response is crucial in disease regression. Large-scale genetic association studies for cervical cancer have identified few susceptibility variants, mainly at the human leukocyte antigen locus on chromosome 6. We hypothesized that the host immune response modifies cervical cancer risk and performed three genome-wide association analyses for HPV16, HPV18 and HPV16/18 seropositivity in 7814, 7924, and 7924 samples from the UK Biobank, followed by validation genotyping in the German Cervigen case-control series of cervical cancer and dysplasia. In GWAS analyses, we identified two loci associated with HPV16 seropositivity (6p21.32 and 15q26.2), two loci associated with HPV18 seropositivity (5q31.2 and 14q24.3), and one locus for HPV16 and/or HPV18 seropositivity (at 6p21.32). MAGMA gene-based analysis identified HLA-DQA1 and HLA-DQB1 as genome-wide significant (GWS) genes. In validation genotyping, the genome-wide significant lead variant at 6p21.32, rs9272293 associated with overall cervical disease (OR = 0.86, p = 0.004, 95% CI = 0.78-0.95, n = 3710) and HPV16 positive invasive cancer (OR = 0.73, p = 0.005, 95% CI = 0.59-0.91, n = 1431). This variant was found to be a robust eQTL for HLA-DRB1, HLA-DQB1-AS1, C4B, HLA-DRB5, HLA-DRB6, HLA-DQB1, and HLA-DPB1 in a series of cervical epithelial tissue samples. We additionally genotyped twenty-four HPV seropositivity variants below the GWS threshold out of which eleven variants were found to be associated with cervical disease in our cohort, suggesting that further seropositivity variants may determine cervical disease outcome. Our study identifies novel genomic risk loci that associate with HPV type-specific cervical cancer and dysplasia risk and provides evidence for candidate genes at one of the risk loci.

Humans↗

PubMed2025

Exploring genetic mapping and co-expression patterns to illuminate significance of Tbx20 in cardiac biology.

The transcription factor Tbx20 is integral to heart development and plays a significant role in various cardiac diseases. Despite its established importance, the regulatory mechanisms and functional significance of Tbx20 remain incompletely understood. To elucidate these mechanisms, we initially conducted eQTL mapping to identify genetic loci associated with Tbx20 expression in heart tissue from BXD mice. Co-expression and enrichment analyses revealed pathways linked to Tbx20, including dilated cardiomyopathy, hypertrophic cardiomyopathy, and FoxO signaling. Additionally, protein-protein interaction studies identified essential cardiac proteins, such as Myl2 and Myl7, along with upstream regulators like Mef2c. To validate our bioinformatic findings, we performed quantitative reverse transcription polymerase chain reaction (qRT-PCR) to assess the relative mRNA expression levels of TBX20 and Mef2c in the heart tissues of BXD mice compared to their parental strains (B6 and D2). Our results demonstrated significant up-regulation of both TBX20 and Mef2c in the BXD group relative to the parental strains. Conversely, both genes were down-regulated in B6, D2, Control, and Treatment groups when compared to BXD mice. These findings confirm the predicted regulatory roles of TBX20 and Mef2c in cardiac development as suggested by our initial analyses.This study not only reinforces the critical role of Tbx20 in cardiac gene regulation but also highlights its potential as a therapeutic target for cardiovascular disorders. Further investigations into Tbx20 and its interactions will enhance our understanding of heart biology and contribute to the development of targeted therapies for heart diseases.

Animals↗

PubMed2026

Microglial PICALM: A novel genetic driver and therapeutic target in vascular dementia.

BACKGROUND: Vascular dementia (VaD) lacks well-defined genetic mechanisms. Cell-type-specific effects of GWAS loci remain unexplored. METHODS: We integrated single‑cell eQTL data (183 donors, eight cell types) with VaD GWAS (3624 cases, 475,484 controls) using Mendelian randomization and Bayesian colocalization, replicated in an independent cohort (2074 cases, 456,366 controls). Subtype, snRNA‑seq, cell‑cell communication, PheWAS, expression profiling, and drug prediction with BBB permeability assessment were performed. RESULTS: Microglial PICALM was the only robustly replicated signal (OR = 0.8334, p = 5.3 × 10⁻⁴; colocalization PP.H4 > 0.75). The effect was strongest in multiple infarctions dementia (OR = 0.7746). Exploratory snRNA-seq analysis (4 VaD vs. 4 controls; GSE282111) provided supporting evidence for microglial PICALM enrichment and downregulation (p < 0.001). PICALM‑high microglia showed enhanced neurovascular‑ and phagocytosis‑related communication (e.g., SPP1, GAS6, GRN). PheWAS revealed no pleiotropy. In silico drug repurposing prioritised three FDA-approved BBB-penetrant compounds (disopyramide, benzocaine, amantadine) as candidates warranting further mechanistic validation. CONCLUSIONS: Microglial PICALM is identified as a likely genetic determinant of VaD, especially in the multiple infarctions subtype. Upregulating PICALM may be associated with a neuroprotective microglial phenotype, highlighting PICALM as a candidate therapeutic target warranting further experimental validation.

Humans↗

PubMed2026

Multi-omic characterization of the Hispanic/Latino blood lipidome reveals an additional locus and attenuated genetic prediction.

While lipids have been extensively investigated, genetic regulation of the circulating lipidome in diverse populations remains poorly understood. We conducted a lipidome-wide genome-wide association study (GWAS) of 830 lipid species in 2,287 Hispanic/Latino participants and performed predictive modeling across omics layers. We identified 7,593 genome-wide significant SNPs mapping to 208 genes. Conditional analysis disentangled the long-range linkage disequilibrium artifacts from the pleiotropic FADS1/2/3 cluster. Separately, we discovered an association at the GPLD1 locus for a circulating ceramide. Colocalization revealed shared genetic architecture with conventional lipids alongside distinct, species-specific pathways. Incorporating Native/Indigenous American expression quantitative trait loci (eQTLs) within a multi-omic framework uncovered 62 likely regulatory genes missed by European-centric gene expression models. Finally, genetically regulated predictive models demonstrated performance declining from transcriptomics to proteomics to lipidomics, reflecting increased distance from gene action along the molecular cascade. Our study provides a genetic landscape of lipid metabolism in a highly burdened population and highlights the challenges in predicting lipid abundance.

Hispanic/Latino population↗

PubMed2026

Single-Cell Transcriptome-Wide Mendelian Randomization and Colocalization Uncover Potential Immunocytes-Related Therapeutic Targets for Obesity.

Weight-loss treatment is crucial for individuals with obesity to prevent various complications. The role of Immune cells in obesity has been recently recognized, whereas its translation into therapy requires identifying key target genes. We performed Mendelian randomization (MR) analysis to assess causal relationships between expression quantitative trait loci (eQTL) of 14 immune cells and obesity-related traits (obesity, body mass index and body fat percentage), and validated the results in colocalization analysis. For the putative causal genes identified by the MR and colocalization analyses, we conducted pathway enrichment, differential expressed gene (DEG) analysis and search of druggable evidence, and utilized a Tier system to prioritize drug targets for obesity. MR and colocalization evidence was observed for 1630 genes associated with one or more obesity-related traits, mainly expressed in CD4+ naive/central memory T cells and enriched in antigen processing and presentation pathways. Forty-one genes showed causal relationship with all three outcomes, among which 19 genes have not been reported for obesity previously. DEG analysis using single-cell RNA sequencing data of blood or adipose tissue indicated that the differential expression of UBE2Z in monocytes, ZCCHC7 in T cells, and FNBP4 in B cells between lean and obese individuals were consistent with the MR results. By searching drug-gene interaction databases, we found targeted drugs for PYGB and PRUNE1, and PYGB was the top gene ranked in the Tier system. This study provides evidence for the involvement of immune cells in obesity, and the potential cell-specific, immune-related targets for obesity treatment.

Obesity↗

PubMed2026

CHCHD10 Mitigates Alzheimer's Disease-Related Phenotypes in Association With Epigenetic Remodeling in Directly Reprogrammed Neurons.

Mitochondrial dysfunction and chromatin dysregulation are interconnected contributors to neuronal vulnerability in Alzheimer's disease (AD), yet the molecular mechanisms linking these processes remain poorly understood. CHCHD10, a mitochondrial intermembrane space protein, has been implicated in neurodegenerative disorders, but its role in AD has not been defined. Here, we identify CHCHD10 as a previously unrecognized modulator of neuronal epigenomic stability in AD. Using direct fibroblast-to-neuron reprogramming, which preserves patient-specific epigenetic signatures, we show that AD neurons recapitulate genome-wide hypomethylation patterns observed in postmortem AD cortex. CHCHD10 expression is significantly reduced in AD neurons and across multiple human brain datasets, including single-cell and bulk RNA sequencing, proteomics, and human cortical tissue analyses. Restoration of CHCHD10 in AD neurons reduces amyloid-β and insoluble tau accumulation while reversing AD-associated differentially methylated regions across CpG islands, promoters, and regulatory elements. CHCHD10-responsive methylation changes overlap with those observed in human AD brain regions and colocalize with significant AD loci and cortex-specific eQTL loci, including MAPT and ABCA7. Finally, we identify KATNAL2 as a CHCHD10-responsive effector whose loss enhances tau phosphorylation and seeding, whereas its restoration mitigates tau pathology. Together, these findings support a CHCHD10-associated neuroprotective pathway linking mitochondrial dysfunction, epigenomic instability, and tau pathology in AD.

Humans↗

PubMed2026

Integrating Genetics and Environment to Find Causal Mechanisms for Multiple Sclerosis.

Genome-wide association studies (GWAS) have identified hundreds of risk loci for multiple sclerosis (MS), but we have limited knowledge of the mechanisms through which genetic variants mediate risk. Similarly, epidemiological studies implicate numerous environmental risk factors in MS risk, but these cannot identify specific causal mechanisms. We review our current knowledge of genetic mechanisms in MS, including the critical role of expression quantitative trait locus (eQTL) mapping in translating genetic risk loci into causal mechanisms. Molecular and functional context has emerged as an important missing component of these studies, and we discuss how environmental risk factors can be modelled in a quantitative genetic context to identify disease mechanisms. In parallel, we highlight recent advances in which quantitative genetic methods establish a causal role for low vitamin D and obesity in MS, and to dissect the mechanisms through which these operate. As genetic, transcriptional, and epigenetic studies continue to expand, further mechanistic insights for MS are likely to come from the integration of genetic and environmental data.

Humans↗

PubMed2026

Integrative Multi-Omics Mendelian Randomization Analysis Identifies NIT2 as a Potential Metabolic Risk Gene in Hepatocellular Carcinoma.

BACKGROUND: Metabolic pathways are crucial in hepatocellular carcinoma (HCC) pathogenesis, but causal metabolic genes remain unclear. This study used Summary data-based Mendelian Randomization (SMR) and colocalization to identify metabolism-related genetic loci influencing HCC risk. METHODS: Differentially expressed genes in hepatic malignancy phenotype versus normal tissues from TCGA and GTEx were analyzed. Metabolism-related candidates were examined via SMR and colocalization using multi-omics data: methylation (mQTL), expression (eQTL), and protein (pQTL) quantitative trait loci. RESULTS: Multi-omics integration identified NIT2 as a key metabolic regulator for HCC. The cg13016775 locus of NIT2 was associated with elevated HCC risk at gene (OR = 1.618, 95% CI: 1.199-2.182) and protein (OR = 4.432, 95% CI: 1.783-11.018) levels. Colocalization supported a shared causal variant (PPH4 > 0.6), linking NIT2 to hepatocarcinogenesis via metabolic regulation. CONCLUSIONS: This study provides multi-omics evidence for NIT2 as a potential causal gene in HCC, enhancing understanding of metabolic contributions to HCC pathogenesis and highlighting integrative genomics for uncovering causal relationships.

Carcinoma, Hepatocellular↗

PubMed2005

Genetic mapping of QTLs controlling horticultural traits in diploid roses.

A segregating progeny set of 96 F1 diploid hybrids (2n = 2x = 14) between "Blush Noisette" (D10), one of the first seedlings from the original "Champneys' Pink Cluster", and Rosa wichurana (E15), was used to construct a genetic linkage map of the rose genome following a "pseudo-testcross" mapping strategy. A total of 133 markers (130 RAPD, one morphological and two microsatellites) were located on the 14 linkage groups (LGs) of the D10 and E15 maps, covering total map lengths of 388 and 260 cM, respectively. Due to the presence of common biparental markers the homology of four LGs between parental maps (D10-1/E15-1 to D10-4/E15-4) could be inferred. Four horticulturally interesting quantitative traits, flower size (FS), days to flowering (DF), leaf size (LS), and resistance to powdery mildew (PM) were analysed in the progeny in order to map quantitative trait loci (QTLs) controlling these traits. A total of 13 putative QTLs (LOD > 3.0) were identified, four for FS, two for flowering time, five for LS, and two for resistance to PM. Possible homologies between QTLs detected in the D10 and E15 maps could be established between Fs1 and Fs3, Fs2 and Fs4, and Ls1 and Ls3. Screening for pairwise epistatic interactions between loci revealed additional, epistatic QTLs (EQTLs) for DF and LS that were not detected in the original QTL analysis. The genetic maps developed in this study will be useful to add new markers and locate genes for important traits in the genus providing a practical resource for marker-assisted selection programs in roses.

Chromosome Mapping↗