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Results for “shared genetic architecture”

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PubMed2026

A single-cell study of transcription and RNA splicing in MDD and ALC.

Major depressive disorder (MDD) and problematic alcohol use (ALC) commonly co-occur, yet the extent, genomic distribution, and biological context of their shared genetic architecture remain incompletely understood. Here, we integrated genome-wide and local genetic architecture analyses with tissue, spatial, single-cell, and multi-omics analyses to characterize the shared genetic basis of MDD and ALC. Across methods, the two phenotypes showed a consistent positive genetic correlation (rg = 0.380-0.582). MiXeR estimated that they shared approximately 5479 variants with non-zero additive genetic effects, with the shared component accounting for a larger proportion of the polygenic architecture of ALC than of MDD. Local analyses further indicated that shared genetic covariance was concentrated in a limited number of genomic segments. At the tissue and cellular levels, genetic signals were primarily associated with central nervous system tissues and neuronal lineages, with additional support for oligodendrocyte-related populations; the two phenotypes also differed in the distribution and within-cell-type heterogeneity of disease-relevance scores. Multi-omics integration prioritized MED19 and ACO2 as candidate genes and highlighted processes related to mitochondrial energy metabolism and synaptic function. These findings refine the genomic, tissue, and cellular context of the shared genetic architecture of MDD and ALC and provide prioritized genomic regions, cell types, and candidate genes for validation in independent populations and functional studies.

Major Depressive Disorder↗

PubMed2025

A genome-wide analysis of the shared genetic risk architecture of complex neurological and psychiatric disorders.

Although neurological and psychiatric disorders have historically been considered to reflect distinct pathogenic entities, recent findings suggest shared pathophysiological mechanisms. However, the extent to which these heritable disorders share genetic influences remains unclear. Here we performed a comprehensive analysis of genome-wide association study data, involving nearly 1 million cases across ten neurological diseases and ten psychiatric disorders, to compare their common genetic signal and biological associations. Using complementary statistical tools, we demonstrate that a large set of common genetic variants impacts the risk of multiple neurological and psychiatric disorders, even in the absence of genetic correlations. Furthermore, genome-wide association studies on psychiatric disorders consistently implicate neuronal biology, whereas neurological diseases are associated with diverse neurobiological processes. Together, this study elucidates the genetic relationship between complex neurological and psychiatric disorders, indicating a larger degree of genetic pleiotropy than previously recognized. The findings have implications for disease classification, precision medicine and clinical practice.

Humans↗

PubMed2026

Genetic insights into the relationship between age at menarche and mental health-related phenotypes.

BACKGROUND: Multiple observational studies have reported associations between age at menarche (AAM) and mental health problems, yet their shared genetic architecture remains poorly characterized. METHODS: We leveraged genome-wide association study summary statistics for AAM and 15 mental health-related phenotypes. We conducted a multi-method integrative analysis encompassing linkage disequilibrium score regression, pleiotropic analysis under the composite null hypothesis, functional mapping and annotation, multi-marker analysis of genomic annotation, pathway enrichment, and bidirectional two-sample Mendelian randomization (MR) to explore shared genetic architecture and potential causal relationships. RESULTS: Our study identified significant genetic correlations between AAM and eight mental health-related phenotypes (miserableness, fed-up feelings, nervous feelings, ever thought that life is not worth living, ever self-harmed, depression, ever smoker, and age started smoking in former smokers). A total of 155 pleiotropic loci, 18 colocalized loci (e.g., 6q16.3), and 203 pleiotropic genes (e.g., LIN28B) were identified. These genes are expressed in multiple regions, including the cerebral cortex and hypothalamus, and are involved in various biological processes and signaling pathways. Additionally, MR analysis revealed causal associations between AAM and 5 mental health-related phenotypes (mood swings, miserableness, fed-up feelings, and age at which smokers started smoking in former/current smokers). CONCLUSIONS: Our study revealed extensive genetic associations between AAM and mental health-related phenotypes, and further explored the potential causal relationships between them. These findings enhance our understanding of the relationship from a genetic perspective and establish a foundation for future research to explore the biological pathways and environmental interactions contributing to these associations.

Genome-Wide Association Study↗

PubMed2026

Shared genetic basis and spatial cellular atlas of psoriasis and metabolic syndrome.

BACKGROUND: Psoriasis (PS) and metabolic syndrome (MetS) frequently co-occur. Characterizing their shared genetic architecture and spatially enriched cellular populations may clarify the context of their co-occurrence and generate hypotheses for functional validation. METHODS: We integrated genome-wide association study (GWAS) summary statistics for PS, MetS, and five related components with spatially resolved single-cell transcriptomic data. Global and local genetic correlations were assessed using linkage disequilibrium score regression, genetic covariance analysis, high-definition likelihood, and local analysis of variant association. A bivariate causal mixture model quantified polygenic overlap. Conditional/conjunctional false discovery rate and composite-null pleiotropy analyses identified shared susceptibility loci. Finally, gsMap evaluated trait-associated enrichment across annotated embryonic tissues at single-cell resolution. RESULTS: Genetic approaches identified significant genome-wide correlations and polygenic sharing between PS, MetS, and its components. Local and cross-trait analyses identified region-specific signals and cross-validated shared loci. gsMap revealed trait-specific tissue enrichment. PS showed the strongest enrichment in the epidermis (pCauchy = 1.0573 × 10  - ⁴), adipose tissue (pCauchy = 1.5366 × 10 - ⁴), and liver (pCauchy = 1.0167 × 10 - ³). Across MetS, FBG, HDL-C, hypertension, and TG, enriched regions mainly involved the liver, adipose tissue, and epidermis. WC enrichment was predominantly observed in adipose tissue (pCauchy = 1.7823 × 10 - ⁴), with no significant liver or epidermal enrichment. CONCLUSION: Integrating GWAS with single-cell transcriptomic and spatial information characterized shared genetic architecture between PS and MetS-related phenotypes and their spatial enrichment patterns. These findings provide a framework for generating testable hypotheses about comorbidity biology and guiding future functional and clinical validation.

Psoriasis↗

PubMed2024

Multivariate genetic architecture reveals testosterone-driven sexual antagonism in contemporary humans.

Sex difference (SD) is ubiquitous in humans despite shared genetic architecture (SGA) between the sexes. A univariate approach, i.e., studying SD in single traits by estimating genetic correlation, does not provide a complete biological overview, because traits are not independent and are genetically correlated. The multivariate genetic architecture between the sexes can be summarized by estimating the additive genetic (co)variance across shared traits, which, apart from the cross-trait and cross-sex covariances, also includes the cross-sex-cross-trait covariances, e.g., between height in males and weight in females. Using such a multivariate approach, we investigated SD in the genetic architecture of 12 anthropometric, fat depositional, and sex-hormonal phenotypes. We uncovered sexual antagonism (SA) in the cross-sex-cross-trait covariances in humans, most prominently between testosterone and the anthropometric traits - a trend similar to phenotypic correlations. 27% of such cross-sex-cross-trait covariances were of opposite sign, contributing to asymmetry in the SGA. Intriguingly, using multivariate evolutionary simulations, we observed that the SGA acts as a genetic constraint to the evolution of SD in humans only when selection is sexually antagonistic and not concordant. Remarkably, we found that the lifetime reproductive success in both the sexes shows a positive genetic correlation with anthropometric traits, but not with testosterone. Moreover, we demonstrated that genetic variance is depleted along multivariate trait combinations in both the sexes but in different directions, suggesting absolute genetic constraint to evolution. Our results indicate that testosterone drives SA in contemporary humans and emphasize the necessity and significance of using a multivariate framework in studying SD.

Humans↗

PubMed2026

Genomic Structural Equation Modeling Identifies a Shared Inflammatory Genetic Dimension Across Inflammatory Arthritis Phenotypes and Biomarkers.

BACKGROUND: Inflammatory arthritis (IA), including rheumatoid arthritis (RA), psoriatic arthritis (PsA) and gout, shares systemic inflammatory features indexed by C-reactive protein (CRP) and interleukin-6 (IL-6), yet the extent of their common genetic basis remains unclear. AIMS: We aimed to delineate the shared genetic architecture across IA phenotypes and inflammatory biomarkers. MATERIALS AND METHODS: We applied genomic structural equation modelling (Genomic SEM) to GWAS summary statistics for RA, PsA, gout, CRP and IL-6, fitted a single common factor, and performed multivariate GWAS followed by fine-mapping, transcriptome-wide association, gene-based analysis, pathway enrichment, and cell-type and spatial mapping. RESULTS: A single common factor was fitted (CFI = 0.990, SRMR = 0.045). The multivariate GWAS identified 56 genome-wide significant SNPs across 10 independent lead loci, including one novel signal. Fine-mapping prioritized high-confidence variants near PTPN22, the CRP gene cluster and a urate-associated locus. Gene-level analyses converged on DCLRE1B, PTPN22, IL6R, NLRP3 and HNF1A, with pathway enrichment implicating inflammasome assembly and metabolic-inflammatory overlap. Cell-type enrichment highlighted myeloid populations, and spatial mapping localized signals to lung, kidney, mucosal epithelium and gastrointestinal tissues. DISCUSSION: These results delineate a shared inflammatory genetic dimension across IA phenotypes and biomarkers, anchored in immune, inflammasome, cytokine-receptor and metabolic pathways. CONCLUSION: Together, these findings provide a valuable framework for prioritizing candidate genes and cellular contexts for future investigation.

TWAS↗

PubMed2026

Unraveling causal links between chronic rhinosinusitis and peripheral artery diseases: insights from genetic correlations through genome-wide association studies.

OBJECTIVES: Chronic Rhinosinusitis (CRS) shares epidemiological links with Cardiovascular Diseases (CVDs), however, their shared genetic basis remains unclear. We hypothesized that pleiotropic genetic variants underlie CRS-CVDs links via distinct biological pathways. METHODS: Using large-scale GWAS data from European-ancestry individuals, we assessed global and local genetic correlations. We applied Genomic Structural Equation Modeling (Genomic SEM) to dissect shared genetic architecture, performed bidirectional Mendelian Randomization (MR) to infer causality, and conducted cis-eQTL colocalization to identify shared genetic signals. Finally, in vitro endothelial models (HUVECs) validated the functional dynamics of candidate genes under CRS-mimicking inflammatory stress. RESULTS: CRS showed significant genetic correlations with multiple CVDs. Genomic SEM revealed a latent factor structuring shared genetic risk through three pathways: artery diseases, myocardial diseases, and heart failure. Local genetic correlations identified significant local genetic correlations specifically between CRS and Peripheral Atherosclerosis (PAS)/Peripheral Artery Disease (PAD) specifically within the chr6: 31.57‒33.24 Mb locus. MR demonstrated causal effects of CRS on PAD (OR = 1.23, p = 0.022) and PAS (OR = 1.21, p = 0.011), but not vice versa. Genetically predicted HLA-DRB1, APOM, and COL11A2 expression conferred protection, while HLA-DQA2 increased risk. Crucially, in vitro validation corroborated these pathogenic trajectories, inflammatory stress significantly downregulated the protective APOM and upregulated the risk-associated HLA-DQA2 alongside pro-atherogenic VCAM-1, while HLA-DRB1 exhibited a compensatory upregulation (p < 0.05). CONCLUSION: CRS shares global genetic liability with CVDs, structured through three primary etiological pathways. Causal effects of CRS on peripheral artery diseases are mediated by immune and lipid-related genes within the chr6 locus, revealing divergent pleiotropic mechanisms. Our integrated genetic and in vitro evidence provides a mechanistic framework wherein chronic mucosal inflammation contributes to systemic endothelial vulnerability, thereby highlighting candidate targets for mechanism-directed therapy.

Humans↗

PubMed2025

Genetic liability to meniscus degeneration and its comorbidity patterns: a phenome-wide association study in the UK Biobank.

Meniscus degeneration is a common knee pathology causing pain, disability, and osteoarthritis. While mechanical factors are established, the contribution of inherited genetic liability to its systemic disease patterns remains unclear. We applied a polygenic risk score (PRS) for meniscus degeneration, derived from FinnGen genome-wide association study (GWAS) results to 323,999 UK Biobank participants and conducted a phenome-wide association study (PRS-PheWAS) across 962 clinical phenotypes. The PRS-PheWAS revealed significant associations beyond musculoskeletal traits, extending to metabolic, cardiovascular, psychiatric, and gastrointestinal domains, indicating broad shared genetic architecture. To support these findings, linkage disequilibrium score regression confirmed strong genetic correlations with osteoarthritis and related arthropathies, and genotype-tissue expression (GTEx) analysis highlighted tissue-specific expression of lead genes (e.g., GDF5, SOX5, BMP6) in connective and metabolic tissues. The results demonstrate that genetic liability to meniscus degeneration extends beyond the knee, sharing pathways with systemic conditions. This systemic genetic architecture underscores the need for integrative management approaches that combine orthopedic care with metabolic and lifestyle interventions.

Journal Article↗

PubMed2026

Suicidality phenotypes reflect both shared and distinct genetic factors.

Suicidality phenotypes, including suicidal ideation (SI), non-fatal suicide attempt (SA), and suicide death (SD), are heritable and exhibit both shared and phenotype-specific genetic influences. Using genomic structural equation modelling, we estimated the shared genetic architecture across GWAS of SI (176,147 cases, 1,010,300 controls), SA (53,919 cases, 1,063,988 controls), and SD (7,584 cases, 652,070 controls) and conducted a multivariate GWAS of a latent suicidality factor capturing their shared liability. This analysis identified 36 genome-wide significant loci, including seven not previously reported in any suicidality GWAS. Follow-up analyses identified residual genetic variance specific to each phenotype, including three SD-specific genomic risk loci. Conditioning suicidality phenotypes on genetic liability to psychiatric disorders revealed significant residual genetic variance across SI, SA, SD, and the suicidality common factor. Together, these results suggest that suicidality reflects both shared genetic liability and phenotype-specific contributions.

Journal Article↗

PubMed2026

Genomic relationship between polyendocrine metabolic ovarian syndrome and bipolar disorder.

Women with bipolar disorder (BIP) have a higher risk of developing polyendocrine metabolic ovarian syndrome (PMOS). Shared genetic architecture may underlie this comorbidity. Valproate, a mood-stabilizer commonly used to treat BIP, increases the risk of PMOS. Still, the mechanism underlying PMOS in BIP remains unknown. Here, we aimed to identify genetic variants shared between BIP and PMOS, as well as their interaction with valproate. We used the results of large-scale genome-wide association studies of BIP (41,510 cases and 354,340 controls), and PMOS (3609 cases and 229,788 controls). Using conditional false discovery rate, we discovered genetic variants jointly associated with BIP and PMOS. Gene mapping of identified variants was performed using the Open Targets platforms. We analyzed the tissue-specific expression, interaction with valproate, and involvement in biological pathways of the mapped genes. We identified two loci shared between BIP and PMOS. Among the 10 genes mapped to the locus on chromosome 8:11,444,837-11,463,015, GATA4, NEIL2, and FDFT1 showed expression profiles suggesting their role in the observed comorbidity. Mapped to the locus on chromosome 12:2499,849-2514,270, CACNA1C, FKBP4, DCP1B, and ITFG2 are expressed in both the ovaries and the brain. Valproate interacts with CACNA1C, and CACNA1C is part of biological pathways that also include other genes interacting with valproate. We identified shared genetic underpinnings of BIP and PMOS and highlighted genes that may potentially contribute to the biological mechanisms underlying their comorbidity and to a hypothesized role of valproate in these mechanisms.

Female↗

PubMed2025

Genomic relationship between polycystic ovary syndrome and bipolar disorder.

Women with bipolar disorder (BIP) have a higher risk of developing polycystic ovary syndrome (PCOS). Shared genetic architecture may underlie this comorbidity. Valproate, a mood-stabilizer commonly used to treat BIP, increases the risk of PCOS. Still, the mechanism underlying PCOS in BIP remains unknown. Here, we aimed to identify genetic variants shared between BIP and PCOS, as well as their interaction with valproate. We used the results of large-scale genome-wide association studies of BIP (41,510 cases and 354,340 controls), and PCOS (3,609 cases and 229,788 controls). Using conditional false discovery rate, we discovered genetic variants jointly associated with BIP and PCOS. Gene mapping of identified variants was performed using the Open Targets platforms. We analyzed the tissue-specific expression, interaction with valproate, and involvement in biological pathways of the mapped genes. We identified two loci shared between BIP and PCOS. Among the 10 genes mapped to the locus on chromosome 8:11455262, GATA4, NEIL2, and FDFT1 showed expression profiles suggesting their role in the observed comorbidity. Mapped to the locus on chromosome 12:2499849, CACNA1C, FKBP4, DCP1B, and ITFG2 are expressed in both the ovaries and the brain. CACNA1C expression is affected by valproate, and CACNA1C plays a role in biological pathways involving other valproate-affected genes. We identified shared genetic underpinnings of BIP and PCOS, and implicated genes which may explain the biological mechanisms of the comorbidity between these disorders and a potential mechanism for the role of valproate.

bipolar disorder↗

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↗

PubMed2025

Polygenic Associations between Motor Behaviour, Neuromotor Traits, and Active Music Engagement in Four Cohorts.

Phenotypic investigations have shown that actively engaging with music, i.e., playing a musical instrument or singing may be protective of motor decline in aging. For example, music training associated with enhanced sensorimotor skills accompanied by changes in brain structure and function. Although it is possible that the benefits of active music engagement "transfer" to benefits in the motor domain, it is also possible that the genetic architecture of motor behaviour and the motor system structure may influence active music engagement. This study investigated whether polygenic scores (PGS) for five behavioural motor traits, 12 neuromotor structural brain traits, and seven rates of change in brain structure traits trained from existing discovery genome-wide association studies (GWAS) predict active music engagement outcomes in four independent cohorts of unrelated individuals of European ancestry: the Canadian Longitudinal Study on Aging (CLSA; N=22,198), Wisconsin Longitudinal Study (WLS; N=4,605), Vanderbilt's BioVU Repository (BioVU; N=6,150), and Vanderbilt's Online Musicality study (OM; N=1,559). Results were meta-analyzed for each PGS main effect across outcomes and cohorts, revealing that PGS for a faster walking pace was associated with higher amounts of active music engagement. Within CLSA, a higher PGS for walking pace was associated with greater odds of engaging with music. Findings suggest a shared genetic architecture between motor function and active music engagement. Future intervention-based research should consider the genetic underpinnings of motor behavior when evaluating the effects of music engagement on motor function across the lifespan.

BioVU↗

PubMed2025

Genetic pleiotropy underlying obesity and autoimmune disorders: a large-scale cross-trait gwas analysis in European ancestry populations.

BACKGROUND: Obesity and autoimmune disorders represent a significant comorbidity burden, yet their shared genetic architecture is not fully understood. Elucidating the pleiotropic genetic basis underlying both conditions is crucial for unraveling the mechanisms driving their co-occurrence and advancing therapeutic strategies. METHODS: We conducted a large-scale cross-trait analysis integrating genome-wide association study (GWAS) summary data for obesity and 17 autoimmune diseases. Genetic correlations were assessed using LD score regression and high-definition likelihood. Cross-trait pleiotropic analysis was performed using Stratified Pleiotropic Locus Mapping (PLACO) to identify shared loci, followed by Bayesian colocalization to confirm shared causal variants. Gene-level and tissue-specific heritability analyses were conducted, and drug targets were prioritized via summary-based Mendelian randomization (SMR). Finally, immune co-localization and bidirectional Mendelian randomization were employed to elucidate immunological mechanisms and causal relationships. RESULTS: Our analysis identified eight autoimmune diseases with significant genetic correlations to obesity. We discovered 10,324 pleiotropic SNPs, which mapped to 52 independent risk loci, with nine loci confirmed as shared causal variants by colocalization. Gene-level analysis revealed 133 unique pleiotropic genes, including CLN3, SH2B1, and MMEL1, enriched in pathways of hematopoietic cell differentiation and immune homeostasis. Tissue-specific heritability was most prominent in the spleen, whole blood, and EBV-transformed lymphocytes. Immuno-co-localization implicated six IgD+ CD38- %B cell-related traits as key pathological conduits. Bidirectional Mendelian randomization established a causal role of obesity in hypothyroidism, psoriasis, and multiple sclerosis, while revealing an inverse causal association of type 1 diabetes with obesity risk. CONCLUSIONS: This study demonstrates a robust shared genetic foundation between obesity and multiple autoimmune diseases, pinpointing specific pleiotropic loci, genes, and immune cell subsets. Our findings provide a mechanistic framework for their comorbidity and highlight potential targets for therapeutic intervention.

Humans↗

PubMed2026

Genetic evidence links hypertension to accelerated brain aging.

Hypertension affects one-third of adults and is a major comorbidity of neurocognitive disorders. The causal relationship, shared genetic architecture, and upstream mechanisms linking hypertension to brain aging remain unclear. Hypertension GWAS datasets from MVP and FinnGen R12 were meta-analyzed as the exposure, and a European-ancestry brain age gap (BAG) GWAS derived from the UK Biobank and LIFE-Adult cohorts was used as the outcome. MR and GSMR assessed causality. LDSC, HDL, and S-LDSC estimated genetic correlation. Four TWAS methods (MAGMA, FUSION, JTI-PrediXcan, FOCUS) mapped associations to genes, followed by SMR for causal validation and PoPS for prioritization. GSMAP with spatial transcriptomics characterized regional and cell-type enrichment. Hypertension and brain aging were genetically correlated, and MR and GSMR analyses suggested a causal effect of hypertension on increased brain age gap. TWAS identified 15 shared Hypertension-BAG genes, 10 supported by SMR. PoPS prioritized TRIM47 as the core gene. Shared signals were enriched in meninges, fiber tracts, cortical layer 1, and CA1 stratum lacunosum/radiatum, with cell-type enrichment in meninges, smooth muscle cells, oligodendrocytes, and astrocyte subtypes. Hypertension is genetically correlated with, and shows evidence of a causal effect on, accelerated brain aging. TRIM47 is a core gene bridging hypertension and BAG. GSMAP-based spatial enrichment provides a hypothesis-generating framework for understanding vascular, meningeal, and myelin-related pathways linking hypertension to increased brain age gap.

Humans↗

PubMed2026

Genetic interconnections between personality-related phenotypes and psychiatric disorders.

BACKGROUND: Personality-related phenotypes are genetically correlated with psychiatric disorders, but whether these relationships reflect shared genetic loci and differ across individual phenotypes remains unclear. We investigated their shared genetic architecture at the level of specific phenotype-disorder pairs. METHODS: We analyzed genome-wide association study summary statistics for 13 personality-related phenotypes and eight psychiatric disorders in populations of European ancestry. Genetic correlations were evaluated separately for 104 phenotype-disorder pairs using linkage disequilibrium score regression and high-definition likelihood. For pairs supported by both methods, MTAG and CPASSOC were applied separately to identify pleiotropic signals, followed by linkage disequilibrium clumping, Bayesian colocalization, gene prioritization, functional enrichment and bidirectional two-sample Mendelian randomization analyses. No composite personality or psychiatric-disorder phenotype was constructed. RESULTS: Among the 104 evaluated pairs, 77 showed significant positive genetic correlations in both analyses. Joint screening of MTAG and CPASSOC results identified pleiotropic signals in 61 pairs, comprising 1088 independent lead SNV-pair associations and 776 unique SNVs. Bayesian colocalization supported 351 signals across 42 pairs and 284 unique lead SNVs. MAGMA identified 1293 unique genes, of which 379 were prioritized by PoPS and 151 were further supported by SMR. These genes were enriched in brain tissues and biological processes involving nervous system development, synaptic organization and intercellular connectivity. Inverse-variance weighted Mendelian randomization identified 41 forward and 32 reverse associations after false-discovery-rate correction, including 21 pairs with bidirectional evidence. CONCLUSION: These item-resolved analyses identify widespread but heterogeneous genetic sharing between personality-related phenotypes and psychiatric disorders. The findings provide a pair-specific map of shared loci and prioritized genes, while the Mendelian randomization results should be interpreted cautiously because of residual heterogeneity and potential horizontal pleiotropy. Further validation in diverse populations and functional studies is required.

Colocalization↗

PubMed2025

Polygenic Susceptibility in Peripartum, Alcohol-Induced, and Cancer Therapy-Related Cardiomyopathies.

IMPORTANCE: Rare monogenic variants linked to nonischemic dilated cardiomyopathy (DCM) are enriched among individuals with secondary cardiomyopathies, such as peripartum (PPCM), alcohol-induced (ACM), and cancer therapy-related (CCM) cardiomyopathies. However, it remains unclear whether a polygenic predisposition to DCM also contributes to these conditions. OBJECTIVE: To assess the association of a DCM polygenic score with PPCM, ACM, and CCM, and to evaluate the contributions of monogenic and polygenic susceptibilities to these secondary cardiomyopathies. DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective genetic association analysis of data from the Mass General Brigham (MGB) Biobank (n = 42 137, 2008-2025), with replication in the UK Biobank (n = 295 160, 2005-2010), FinnGen (n = 417 950, 2017-2025), and the Veterans Affairs Million Veteran Program (n = 516 066, 2011-2025). In MGB Biobank, medical records were reviewed to ascertain secondary cardiomyopathy cases and antecedent clinical risk factors. EXPOSURES: DCM polygenic risk score and DCM monogenic variants. MAIN OUTCOMES AND MEASURES: The primary outcomes were the association of the DCM polygenic risk score with PPCM, ACM, and CCM and the prevalence of monogenic variants and a high polygenic score among individuals with cardiomyopathy. RESULTS: The mean (SD) age in the MGB Biobank was 55.7 (17.0) years at enrollment, and 24 551 (58.3%) were female. Across the 4 study cohorts, 3414 individuals with secondary cardiomyopathy were identified, including 70 with PPCM, 2281 with ACM, and 1063 with CCM. The DCM polygenic score was associated with PPCM (odds ratio [OR], 1.82 per SD; 95% CI, 1.43-2.30), ACM (OR, 1.56; 95% CI,1.34-1.82), and CCM (OR, 1.64; 95% CI,1.24-2.15) (all with P < .001). Monogenic variants were enriched but present in 7 of 113 individuals with medical record-reviewed cardiomyopathy in MGB, while 66 had a high polygenic score, which conferred an approximately 3-fold increased odds of cardiomyopathy. Most individuals with cardiomyopathy lacked antecedent clinical risk factors. CONCLUSIONS AND RELEVANCE: In this cohort study, individuals with PPCM, ACM, and CCM were enriched for monogenic DCM variants and a high DCM polygenic score, suggesting a shared genetic susceptibility influenced by distinct environmental precipitants. These findings support a shared genetic architecture between secondary cardiomyopathies and DCM, although additional work with larger numbers of individuals with cardiomyopathy is needed to confirm these findings.

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↗