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Endogenous fine-mapping and prioritization of functional regulatory elements in complex genetic loci.

Most genetic loci linked to polygenic traits are in non-coding regions, with complex regulation and linkage disequilibrium (LD), complicating causal variant and gene prioritization. We used multiplexed single-cell CRISPR interference and activation perturbations to investigate cis-regulatory element (CRE) and gene expression relationships within tight LD in the endogenous chromatin context. We demonstrated the prevalence of multiple causality in perfect LD (pLD) for independent expression quantitative trait loci (eQTLs) and uncovered fine-grained genetic effects on gene expression within pLD, which are difficult to decipher using traditional eQTL fine-mapping or existing computational methods. We found that over one-third of the causal CREs lack classical epigenetic markers prior to perturbation, and we functionally validated one of these hidden regulatory mechanisms. Leveraging Multiome single-cell epigenetic and sequence perturbations, we highlighted the regulatory plasticity of the human genome. Our study will guide the exploration of missing causal mechanisms underlying molecular trait regulation and disease development.

Humans

Mining of important genetic loci and evaluation of genetic effects for growth traits in Baicheng You Chicken.

The Baicheng You Chicken is a precious indigenous breed in Xinjiang, China, prized for its strong disease and stress resistance and superior meat quality. However, the lack of scientific breeding and conservation has led to poor production performance, particularly in growth traits. In this study, we collected phenotypic and whole-genome resequencing data from 1,535 18-week-old Baicheng You Chickens (180 males and 1,355 females). After stringent quality control (SNP call rate > 95%, minor allele frequency > 1%), we constructed the breed's first comprehensive SNP-based genome-wide variation map, which comprised 2,020,743 high-quality SNPs across the genome. The filtered SNPs had high mapping quality (99.73% mapped to the bGalGal1.mat.broiler.GRCg7b reference genome, Q30 = 93.26%) and a reasonable Ti/Tv ratio (2.596), guaranteeing the reliability of subsequent analyses. We estimated genetic effects (SNP-based heritability and phenotypic variance explained (PVE) by individual loci) via the restricted maximum likelihood (REML) method, and performed a genome-wide association study (GWAS) using a mixed linear model (MLM) - with sex as a fixed effect and principal components to correct for population stratification - to identify significant loci and their effect sizes (Beta). All eight growth traits showed moderate to high heritability: body weight (BW) had the highest heritability (0.86±0.11), while chest width (CW, 0.41±0.08) and body slanting length (BSL, 0.43±0.09) were the lowest; keel length (KL), chest girth (CG), pelvic width (PW), chest depth (CD) and shank length (SL) had heritabilities of 0.50±0.09, 0.46±0.09, 0.54±0.09, 0.67±0.10 and 0.74±0.10, respectively. GWAS identified 145 significant SNPs, with a maximum Beta value of 0.39 and PVE ranging from 1.25% to 6.25%. We annotated 22 candidate genes, with TAPT1, IGF2BP1, ADGRB3, LDB2, NCAPG and LCORL as key candidates. These quantifiable genetic markers and effect estimates provide direct targets for marker-assisted selection (MAS) and valuable resources for future genomic selection (GS) programs, offering a practical approach to improve the breed's slow growth while preserving its unique meat quality.

Baicheng You Chicken

Polycystic Ovary Syndrome Physiologic Pathways Implicated Through Clustering of Genetic Loci.

CONTEXT: Polycystic ovary syndrome (PCOS) is a heterogeneous disorder, with disease loci identified from genome-wide association studies (GWAS) having largely unknown relationships to disease pathogenesis. OBJECTIVE: This work aimed to group PCOS GWAS loci into genetic clusters associated with disease pathophysiology. METHODS: Cluster analysis was performed for 60 PCOS-associated genetic variants and 49 traits using GWAS summary statistics. Cluster-specific PCOS partitioned polygenic scores (pPS) were generated and tested for association with clinical phenotypes in the Mass General Brigham Biobank (MGBB, N = 62 252). Associations with clinical outcomes (type 2 diabetes [T2D], coronary artery disease [CAD], and female reproductive traits) were assessed using both GWAS-based pPS (DIAMANTE, N = 898,130, CARDIOGRAM/UKBB, N = 547 261) and individual-level pPS in MGBB. RESULTS: Four PCOS genetic clusters were identified with top loci indicated as following: (i) cluster 1/obesity/insulin resistance (FTO); (ii) cluster 2/hormonal/menstrual cycle changes (FSHB); (iii) cluster 3/blood markers/inflammation (ATXN2/SH2B3); (iv) cluster 4/metabolic changes (MAF, SLC38A11). Cluster pPS were associated with distinct clinical traits: Cluster 1 with increased body mass index (P = 6.6 × 10-29); cluster 2 with increased age of menarche (P = 1.5 × 10-4); cluster 3 with multiple decreased blood markers, including mean platelet volume (P = 3.1 ×10-5); and cluster 4 with increased alkaline phosphatase (P = .007). PCOS genetic clusters GWAS-pPSs were also associated with disease outcomes: cluster 1 pPS with increased T2D (odds ratio [OR] 1.07; P = 7.3 × 10-50), with replication in MGBB all participants (OR 1.09, P = 2.7 × 10-7) and females only (OR 1.11, 4.8 × 10-5). CONCLUSION: Distinct genetic backgrounds in individuals with PCOS may underlie clinical heterogeneity and disease outcomes.

Humans

Genome-Wide Association Analyses of Bitter Food Preferences Link Genetic Loci to Sensory and Metabolic Pathways.

BACKGROUND: Genetic variation is implicated in individual preferences for bitter-tasting foods. However, previous studies have focused on candidate genes and limited varieties of bitter-tasting foods and have treated food preference scale responses as continuous data. OBJECTIVES: The present investigation aimed to identify genetic variants associated with preferences for bitter-tasting foods using ordinal multinomial regression models in genome-wide association studies (GWAS). In addition, post-GWAS functional annotation and mapping, genetic correlations, and associations with dietary intake were examined. METHODS: Food preference and genome-wide genotyping data were used from the UK Biobank (n = 125,578). Preference data from Likert scale rankings (from 1 to 9) for 12 individual foods were analyzed using ordinal multinomial regression GWAS. In addition, 1 composite continuous variable was created for preference for cruciferous vegetables as a group and analyzed using a linear mixed-model GWAS to enable the calculation of a polygenic score (PGS) for cruciferous vegetable preference. Convergent validity of GWAS results was assessed with dietary intake data for the same food items in the CARTaGENE cohort (n = 8176). Post-GWAS gene-level and pathway-level association analyses were conducted in MAGMA (Multimarker Analysis of GenoMic Annotation). RESULTS: Forty-six single-nucleotide polymorphisms (SNPs) were identified for preferences for 11 bitter-tasting foods at a genome-wide significance level (P < 7.14 &#xd7; 10-9). Gene-set analysis for enrichment identified pathways related to caffeine metabolism and bitter taste perception for preference of coffee without sugar and grapefruit, respectively. Genes with higher expression in brain tissues showed stronger genetic associations with cruciferous vegetable preference. The PGS for cruciferous vegetable preference was weakly correlated with intake (r = 0.05, P < 0.0001), but individual SNPs were not associated with intake in a consistent manner. CONCLUSIONS: Genetic variation contributes to preferences for bitter-tasting foods among adults, and some links with food intake are detectable. Nevertheless, effect sizes are small and inconsistent, reflecting the multifactorial complexity of food intake.

bitter taste

Novel Genetic Loci in Early-Onset Gout Derived From Whole-Genome Sequencing of an Adolescent Gout Cohort.

OBJECTIVE: Mechanisms underlying the adolescent-onset and early-onset gout are unclear. This study aimed to discover variants associated with early-onset gout. METHODS: We conducted whole-genome sequencing in a discovery adolescent-onset gout cohort of 905 individuals (gout onset 12 to 19 years) to discover common and low-frequency single-nucleotide variants (SNVs) associated with gout. Candidate common SNVs were genotyped in an early-onset gout cohort of 2,834 individuals (gout onset &#x2264;30 years old), and meta-analysis was performed with the discovery and replication cohorts to identify loci associated with early-onset gout. Transcriptome and epigenomic analyses, quantitative real-time polymerase chain reaction and RNA sequencing in human peripheral blood leukocytes, and knock-down experiments in human THP-1 macrophage cells investigated the regulation and function of candidate gene RCOR1. RESULTS: In addition to ABCG2, a urate transporter previously linked to pediatric-onset and early-onset gout, we identified two novel loci (Pmeta < 5.0 &#xd7; 10-8): rs12887440 (RCOR1) and rs35213808 (FSTL5-MIR4454). Additionally, we found associations at ABCG2 and SLC22A12 that were driven by low-frequency SNVs. SNVs in RCOR1 were linked to elevated blood leukocyte messenger RNA levels. THP-1 macrophage culture studies revealed the potential of decreased RCOR1 to suppress gouty inflammation. CONCLUSION: This is the first comprehensive genetic characterization of adolescent-onset gout. The identified risk loci of early-onset gout mediate inflammatory responsiveness to crystals that could mediate gouty arthritis. This study will contribute to risk prediction and therapeutic interventions to prevent adolescent-onset gout.

Humans

Dual genetic loci and flavonoid metabolism orchestrate fruiting body coloration in Flammulina filiformis: a multi-omic roadmap for fungal pigmentation.

BACKGROUND: The fruiting bodies of macrofungi exhibit diverse coloration, traditionally attributed to melanin and carotenoid biosynthesis. This study is the first to reveal that flavonoids, rather than these classical pigments, are the predominant contributors to yellow pigmentation in the Flammulina filiformis. OBJECTIVE: To uncover the genetic basis and key regulatory genes involved in pigment formation in F. filiformis fruiting bodies, and to establish a model framework for studying color genetics in macrofungi. METHODS: Metabolomic profiling was conducted on yellow and white F. filiformis fruiting bodies to identify key pigment components. A segregating population was constructed, followed by integrated multi-omics analyses-including bulk segregant analysis (BSA), genome-wide association study (GWAS), and transcriptomics-to map regulatory loci and candidate genes. Functional roles were validated via genetic transformation and protein structural modeling. RESULTS: Flavonoid accumulation was identified as the biochemical hallmark of pigmented fruiting bodies. Genetic analysis revealed a dual regulatory mechanism: a qualitative locus governing pigmentation presence and a quantitative trait determining color intensity. Combined BSA and GWAS pinpointed a major locus, Ffcrs, within a recombination-suppressed region. Transcriptomic analysis identified two key regulators, Ffakr (a transcriptional activator) and Ffpal (encoding phenylalanine ammonia-lyase). Functional verification via transformation, structural modeling, and metabolite profiling in transgenic lines confirmed their essential roles in flavonoid biosynthesis and pigmentation. CONCLUSION: This study uncovers a flavonoid-based pigmentation mechanism in F. filiformis and elucidates a complex genetic architecture shaped by both qualitative and quantitative loci, providing a new paradigm for understanding pigment formation in macrofungi. The identified regulatory factors establish a molecular foundation for the precise manipulation of economically important pigmentation traits in edible mushroom.

Flavonoids

Genome-wide association study reveals two novel genetic loci associated with chronic lung allograft dysfunction.

BACKGROUND: Chronic lung allograft dysfunction (CLAD) leads to declining respiratory function and high mortality, representing the main barrier to long-term survival in lung transplantation (LT). We performed the first genome-wide association study (GWAS) investigating donor's and recipient's genetic factors associated with CLAD. METHOD: We genotyped 392 donor-recipient pairs from the multicentric Cohort in Lung Transplantation. We tested 4.5 million SNPs for association with CLAD using multivariable logistic regression models corrected for age, sex, initial disease and genetic ancestry. Three levels of explanatory variables were separately considered to conduct GWAS: donors-only, recipients-only, and donor-recipient mismatches. We also ran HLA-centric analyses using the same models. RESULTS: Our analysis confirmed the deleterious impact of HLA allelic and epitopic mismatches on CLAD risk, mostly driven by class I HLA (p=0.004). No significant associations with CLAD were found for donors' genotypes or donor-recipient non-HLA mismatches. We highlighted two independent recipient's loci associated with CLAD, including one protective signal (0.39 in CLAD vs 0.66 in non-CLAD recipients, p-value=5.05&#xd7;10-7, q-value=0.017, OR=0.35) encompassing the PLXDC2 gene, and one risk signal (0.66 in CLAD vs 0.38 in non-CLAD recipients, p-value=9.86&#xd7;10-7, q-value=0.017, OR=2.83) encompassing the ZNF518A/BLNK genes. These non-coding SNPs are putative regulatory variants of gene expression. Importantly, our single-cell RNA-sequencing showed a down-regulation of PLXDC2 in fibroblasts and lung epithelium in CLAD vs healthy controls. CONCLUSION: This first LT GWAS revealed two candidate loci from the recipient's genome, both biologically relevant for CLAD pathogenesis. Our study calls for larger LT genomic initiatives to increase power for signal discovery.

Humans

New Genetic Loci Implicated in Cardiac Morphology and Function Using Three-Dimensional Population Phenotyping.

BACKGROUND: Cardiac remodeling occurs in the mature heart and is a cascade of adaptations in response to stress, which are primed in early life. A key question remains as to the processes that regulate the geometry and motion of the heart and how it adapts to stress. METHODS: We performed spatially resolved phenotyping using machine learning-based analysis of cardiac magnetic resonance imaging in 47&#x2009;549 UK Biobank participants. We analyzed 16 left ventricular spatial phenotypes, including regional myocardial wall thickness and systolic strain in both circumferential and radial directions. In up to 40&#x2009;058 participants, genetic associations across the allele frequency spectrum were assessed using genome-wide association studies with imputed genotype participants, and exome-wide association studies and gene-based burden tests using whole-exome sequencing data. We integrated transcriptomic data from the GTEx project and used pathway enrichment analyses to further interpret the biological relevance of identified loci. To investigate causal relationships, we conducted Mendelian randomization analyses to evaluate the effects of blood pressure on regional cardiac traits and the effects of these traits on cardiomyopathy risk. RESULTS: We found 42 loci associated with cardiac structure and contractility, many of which reveal patterns of spatial organization in the heart. Whole-exome sequencing revealed 3 additional variants not captured by the genome-wide association study, including a missense variant in CSRP3 (minor allele frequency 0.5%). The majority of newly discovered loci are found in cardiomyopathy-associated genes, suggesting that they regulate spatially distinct patterns of remodeling in the left ventricle in an adult population. Our causal analysis also found regional modulation of blood pressure on cardiac wall thickness and strain. CONCLUSIONS: These findings provide a comprehensive description of the pathways that orchestrate heart development and cardiac remodeling. These data highlight the role that cardiomyopathy-associated genes have on the regulation of spatial adaptations in those without known disease.

Humans

Genome-wide association and selective sweep analyses reveal genetic loci for teat number trait in pigs.

Teat number is a key reproductive trait for the commercial pig industry, as an optimum number enhances weaned piglet survival rate. This study aimed to identify single nucleotide polymorphisms (SNPs) and genomic regions that are associated with teat number in the Large White sow. A total of 1000 French Large White sows were used in an analysis of total, left/right, and maximum unilateral teat number. Environmental factor, Spearman correlation, genome-wide association study (GWAS), linkage disequilibrium, and selective sweep analyses were conducted, with validation performed in a population of 1145 Landrace pigs. Genetic statistics showed that this population's teat number had moderate-low genomic heritability (h2&#xa0;=&#xa0;0.17-0.21) and weak negative correlation with weaned piglet litter weight. Parity and season affected teat development. GWAS identified 17 candidate SNPs on SSC 4, 7, and 17. Combined with selective sweep analysis, two key regions on SSC 7 were found, with four teat number-related SNPs, annotated to VRTN, DIO2, NRXN3. These candidate genes are associated with thoracic vertebrae development, hormone regulation during the early stage of teat formation, and nervous system development. These five SNPs showed similar results in the Landrace pig validation population; non-mutant homozygotes had 0.25-1.15 more teats than mutant ones in both populations. This study contributes to the identification of key variant loci associated with teat number-related traits in sows, thereby providing reliable molecular markers and a theoretical basis for marker-assisted selection of sow reproductive performance.

Animals

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&#x2009;=&#x2009;1.618, 95% CI: 1.199-2.182) and protein (OR&#x2009;=&#x2009;4.432, 95% CI: 1.783-11.018) levels. Colocalization supported a shared causal variant (PPH4&#x2009;>&#x2009;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

Genome-Wide Association Analyses Identify Distinct Genetic Architectures for Extreme Early-Onset and Late-Onset T2D.

AIMS: Type 2 diabetes (T2D) is a heterogeneous disorder with substantial variation in age at onset (AAO). This study aimed to characterize the distinct genetic architectures and biological mechanisms underlying extreme AAO-defined T2D subtypes. MATERIALS AND METHODS: Using 74&#x2009;795 European-ancestry participants from the UK Biobank, we performed genome-wide association studies (GWAS) of relatively early-onset T2D (eoT2D; AAO <&#x2009;55&#x2009;years) and late-onset T2D (loT2D; AAO &#x2265;&#x2009;70&#x2009;years). We investigated subtype-specific genetic loci, SNP-based heritability, genetic correlations, Mendelian randomization (MR)-based relationships, polygenic risk scores (PRS) and phenome-wide association studies (PheWAS). Single-cell transcriptomic data from human pancreatic tissues were further used to evaluate cell-type-specific expression patterns of candidate genes. RESULTS: SNP-based heritability was substantially higher for eoT2D than loT2D (11.2% vs. 6.4%), with eoT2D displaying distinct genetic loci related to &#x3b2;-cell function and insulin regulation, including SLC30A8 and IRS1. By contrast, loT2D showed a comparatively lipid-related genetic profile, featuring APOE-associated signals and expression patterns in immune-related cell populations. Linkage disequilibrium score regression (LDSC) and MR analyses further underscored this divergence: eoT2D exhibited broader genetic overlap with cardiometabolic traits, whereas loT2D showed stronger relationships with traditional metabolic risk factors. Finally, subtype-specific PRSs improved risk discrimination beyond conventional covariates, although their clinical utility warrants further evaluation. CONCLUSIONS: Extreme AAO-defined T2D subtypes exhibit partially distinct genetic architectures, highlighting AAO as an important dimension of T2D heterogeneity and providing a framework for future age-stratified genetic risk assessment.

Type 2 diabetes

Integrative cross-tissue transcriptome-wide association and metabolomic analysis reveals novel genetic risk loci for aortic aneurysm.

BACKGROUND: Aortic aneurysm (AA) is a life-threatening cardiovascular condition with a strong genetic component, however, its molecular mechanisms remain poorly understood. Although genome-wide association studies (GWAS) have identified numerous risk loci, most prior studies have investigated genetic and metabolic factors separately, leaving the causal pathways from genetic variants to disease largely unexplored. METHODS: We established an integrative framework combining cross-tissue transcriptome-wide association studies (TWAS) with metabolomic mediation analysis. First, we integrated GWAS data from FinnGen R12 with multi-tissue expression quantitative trait loci (eQTL) data from Genotype-Tissue Expression Project (GTEx) V8, then performed cross-tissue TWAS using the Unified Test for MOlecular SignaTures (UTMOST) and single-tissue validation with the Functional Summary-based Imputation (FUSION) to prioritize susceptibility genes. Second, we applied Mendelian randomization (MR), colocalization, and Fine-mapping Of CaUsal gene Sets (FOCUS) to assess causality and identify high-confidence genes. Third, we performed metabolite mediation analysis to uncover metabolic pathways linking genetic variants to disease risk. Finally, we validated key findings in mouse models of thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA) using Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction (RT-qPCR) and Western blotting. RESULTS: We identified multiple novel susceptibility genes for AA and its subtypes. Key genes included ADH family members (ADH1A, ADH1B, ADH4, ADH6) and ZNF827, which showed cross-subtype associations with strong colocalization evidence in vascular tissues. Metabolite mediation analysis revealed significant pathways involving N-acetylphenylalanine and methionine sulfoxide. Functional enrichment revealed distinct biological mechanisms: AA and AAA were primarily associated with metabolic pathways, whereas TAA-related genes were enriched in developmental and contractile processes. PheWAS indicated no significant off-target associations. Critically, experimental validation in mouse models confirmed significant upregulation of ZNF827 in TAA and ADH6 in AAA at both mRNA and protein levels, corroborating the genetic predictions. CONCLUSION: This integrated cross-omics analysis identifies novel genetic loci and, crucially, uncovers specific nutrient-related metabolic pathways that mediate genetic risk. These findings provide a mechanistic basis for future nutritional and metabolic intervention studies in AA and its subtypes.

MAGMA

Dissecting the shared genetic architecture of schizophrenia with ventricular subregion volumes.

Schizophrenia is characterized by cerebral ventricular enlargement as an early and consistent structural anomaly. While genetic factors significantly influence both schizophrenia and cerebral ventricular enlargement, the shared genetic etiology between them requires further investigation. Using summary statistics from recent large genome-wide association studies on schizophrenia and 9 ventricular subregion volumes phenotypes. Gaussian causal mixture modeling was applied to characterize the genetic architecture and overlap between schizophrenia and ventricular subregion volumes phenotypes. Local genetic correlation was investigated with Local Analysis of Variant Association. The conjunctional false discovery rate framework was used to identify the specific shared genetic loci, annotated with FUMA. Gaussian causal mixture modeling estimated schizophrenia to be more polygenic more polygenic (9574 trait-influencing variants) than ventricular subregion volumes phenotypes (157-1267 trait-influencing variants). Conjunctional false discovery rate analysis identified 42 shared genetic loci, 17 loci were identified as novel for both schizophrenia and the ventricular subregion volumes phenotypes. Local Analysis of Variant Association revealed that 11 distinct loci demonstrated significant differences, among which 4 loci were situated in the Major Histocompatibility Complex region. Annotated genes in shared loci were enriched in molecular signaling pathways involved in inflammation and the brain structure. The shared loci between them were annotated and enriched in Major Histocompatibility Complex and inflammation-related pathways, highlighting new opportunities for future investigation.

Schizophrenia

Consensus meta-analysis of genome-wide association studies for Alzheimer's disease and related dementias.

To better characterize the genetic architecture underlying Alzheimer's disease (AD) and related dementias (ADRD), we performed a meta-analysis of European-ancestry genome-wide association studies in 128,681 cases or proxy cases of ADRD and 849,833 (proxy) controls. We identified 91 genetic loci associated with ADRD risk, of which 16 are new and 56 are specifically detected in clinically diagnosed AD cases. We also provide a list of 18 loci (15 new) requiring further external validation. A polygenic score combining the effects of ADRD loci other than APOE was primarily associated with AD rather than non-AD pathology. Individuals in the tenth decile of the score exhibited a twofold increased risk of presenting with Braak neurofibrillary tangles stage of >4 and moderate-to-severe neuritic amyloid plaque pathology at death compared to individuals in the median score group. In conclusion, our study validated a large number of loci associated with the risk of clinically diagnosed AD, while further investigations are required to confirm the impact of the other loci on AD clinical diagnosis and of each locus on AD pathology.

Humans

Large-scale pleiotropic analysis across cancers reveals shared genetic mechanisms and identifies novel functional genes.

Pleiotropic genetic loci have been increasingly reported in cancer, and identifying genetic variants with pleiotropic associations can reveal shared biological pathways influencing multiple cancers. Using summary statistics from genome-wide association studies for 37 cancer types (N&#x2009;=&#x2009;433&#xa0;836), we identified extensive genome-wide and local genetic correlations among cancers. Through pairwise pleiotropic analysis, we identified 75&#xa0;243 significant pleiotropic single nucleotide polymorphisms (SNPs) across 372 cancer pairs, among which 3472 were lead SNPs with potential regulatory functions. Using FUMA and MAGMA, we identified 2527 pleiotropic risk loci and 4272 candidate pleiotropic genes. Notably, genes such as TERT (5p15.33), POU5F1B (8q24.21), and FANCA (16q24.3) exhibited widespread pleiotropy across multiple cancer types. Pathway enrichment analysis highlighted the critical roles of pigment synthesis, metabolism, and apoptosis in skin-related cancers, while cross-cancer enrichment analysis emphasized pathways related to apoptosis, chromatin structure, and intermediate filaments. We also identified 33 novel functional genes harboring previously unreported cancer risk variants. Drug-gene interaction analysis revealed several repositionable FDA-approved drugs. Importantly, drug sensitivity assays demonstrated that bosutinib and cobimetinib exhibited promising therapeutic potential in breast cancer cell lines. Finally, we developed the PleioCancer database (https://gonglab.hzau.edu.cn/PleioCancer/), providing a comprehensive resource for cancer pleiotropy research. These findings have important implications for carcinogenesis cancer, prevention and treatment.

Humans

Genome-to-genome analysis reveals associations between human and mycobacterial genetic variation in tuberculosis patients from Tanzania.

The risk and prognosis of tuberculosis (TB) are influenced by a complex interplay between human and bacterial genetic factors. While previous genomic studies have largely examined human and bacterial genomes separately, we adopted an integrated approach to uncover host-pathogen interactions. We leveraged paired human and Mycobacterium tuberculosis (M.tb) genomic data from 1000 adult TB patients from Tanzania and used a "genome-to-genome" approach to search for associations between human and M.tb genetic variants and to identify interacting genetic loci. Our analyses revealed two significant host-pathogen genetic associations. The first significant association (p&#x2009;=&#x2009;4.7e-11) links a human intronic variant in PRDM15 (rs12151990), a gene involved in apoptosis regulation, with an M.tb variant in Rv2348c (I101M), which encodes a T cell-stimulating antigen. The second significant association (p&#x2009;=&#x2009;6.3e-11) connects a human intergenic variant near TIMM21 and FBXO15 (rs75769176) - also associated with TB severity (p&#x2009;=&#x2009;0.04) - with an M.tb variant in FixA (T67M). While FBXO15 is involved in the regulation of antigen processing and TIMM21 affects mitochondrial function, FixA's role remains undefined due to limited functional characterization. Additionally, we observed that a group of M.tb T cell epitope variants were significantly associated with HLA-DRB1 variation, suggesting that, despite their rarity, certain epitopes may still be subjected to immune selective pressure. Together, these findings identify previously unknown sites of genomic conflicts between humans and M.tb, advancing our understanding of how this pathogen evades selection pressure and persist in human populations.

Humans

Gut fungi are associated with human genetic variation and disease risk.

Human genetic determinants of the gut mycobiome remain uninvestigated despite decades of research highlighting tripartite relationships between gut bacteria, genetic background, and disease. Here, we present the first genome-wide association study on the number and types of human genetic loci influencing gut fungi relative abundance. We detect 148 fungi-associated variants (FAVs) across 7 chromosomes that statistically associate with 9 fungal taxa. Of these FAVs, several occur in the protein-coding genes PTPRC, ANAPC10, NAV2, and CDH13. Additional FAVs link to tissue-specific gene expression as fungi-associated expression quantitative trait loci. Notably, the relative abundance of gut yeast Kazachstania associates with genetic variation in CDH13 encoding T-cadherin, a protein linked to cardiovascular disease. Kazachstania forms a causal relationship with cardiovascular disease risk in a mendelian two-sample randomization analysis. These findings establish previously unrecognized connections between human genetics, gut fungi, and chronic disease, broadening the paradigm of human-microbe interactions in the gut to the mycobiome.

Humans