SEARCH · Search PubMed

Results for “shared genetic etiology”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2026

Multi-ancestry multi-trait analysis reveals shared genetics across major psychiatric disorders and Alzheimer's disease.

The clinical overlap between major psychiatric disorders (MPDs) and Alzheimer's disease (AD) implicates complex shared etiology. Previous studies demonstrated that both diseases are genetically complex and highly heritable, suggesting that more endeavors are necessary to be made from the very bottom to understand their genetic basis. With the advance of post-genomic analysis, multi-ancestry meta-analysis allows the generalizability of the genetic architecture across different populations to uncover ancestry-specific variants, while multi-trait analysis enables the discovery of the co-colocalized risk genomic regions across diseases. Therefore, in this study, we leveraged published GWAS summary statistics from European, East Asian, Hispanic and African American populations to report schizophrenia, major depressive disorders, and Alzheimer's disease risk loci and further fine-mapping to credible sets with >95% PP inclusion of the causal variant. We distilled 2871 potential traits from publicly available and found 134 traits significantly genetically correlated with both MPDs and AD using batch LD score regression. We then prioritized the identified loci from multi-ancestry results for cross-trait colocalization analysis to assess shared genetic etiology and further nominated 2 colocalized loci across both conditions, including rs2532240 and rs6504163. In the end, we finalized our analysis by validation and functional inference of the underlying susceptibility genes as well as putative mechanisms using evidence from multiple resources, including FIVEx, Open Targets, and scQTLbase.

Humans↗

PubMed2026

Cellular transcriptomic signatures underpinning the heterogeneity of depression in Alzheimer's disease.

INTRODUCTION: Late-onset Alzheimer's disease (LOAD) and major depressive disorder (MDD) share genetic etiologies. Here, we investigated brain transcriptomic landscapes to gain insights into shared and divergent molecular and biological etiologies across LOAD and MDD. METHODS: Brain single-nucleus RNA sequencing (snRNA-seq) datasets from cognitively normal older and young individuals and LOAD patients stratified by comorbid MDD were analyzed to identify differential expressed genes (DEGs). Using cell type-specific DEGs we performed biological pathway and intercellular-communication networks analyses. We investigated shared DEGs across MDD and LOAD cohorts and sex-specific DEGs. Results were validated by comparison with four transcriptomic and proteomic studies of MDD and depression. RESULTS: MDD-associated dysregulated genes and pathways were shared between LOAD and cognitive-normal individuals, including JUNB and DUSP1 in glutamatergic neurons, and PRAM1 and SNX9 in microglia. DEGs shared between the MDD and LOAD cohorts included HSPA1A and NDUFB7 in glutamatergic neurons. Sex interaction analysis identified numerous new DEGs in the MDD cohorts, whereas there were ≈5 to 10 times more DEGs in female than in male individuals. LOAD and MDD common microglial pathways included neuronal injury, stress, peroxisome proliferator-activated receptor (PPAR) signaling and interferon alpha/beta signaling. DISCUSSION: LOAD and MDD exhibited common molecular profiles, dysregulated pathways, and cellular communication changes. MDD develops earlier in life, thus, our findings provide a window into early molecular and biological processes preceding LOAD-onset.

Humans↗

PubMed2025

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↗

PubMed2026

Genetic evidence that advanced COVID-19 accelerates longitudinal brain atrophy: A Mendelian randomization study.

Coronavirus disease 2019 (COVID-19) was reported to persist long-term in the brain and leave several long-term neurologic sequelae. However, the causal relationship between COVID-19 and brain aging is still unknown. The genome-wide association study (GWAS) data on COVID-19 phenotypes (susceptibility, hospitalization, and severity), involving a total of 5,779,391 participants, were collected from the COVID-19 Host Genetics Initiative. In addition, GWAS data on longitudinal changes in 15 brain structures, assessed via magnetic resonance imaging across the lifespan, were sourced from the ENIGMA Consortium and involved 15,640 participants. Two-sample Mendelian randomization was conducted to infer the causal relationship between COVID-19 and longitudinal brain changes. Multi-trait GWAS meta-analysis, colocalization, and fine-mapping analyses were performed to identify shared genetic etiologies. H3K27me3 ChIP-seq was used to evaluate the regulatory effect of colocalized loci. Two-step Mendelian randomization was applied to explore potential mediating mechanisms across multi-omics layers, including proteomics, metabolomics, and immunomics. Our results showed that COVID-19 hospitalization (β = -262.405, P = .041) and severity (β = -177.676, P = .049) were genetically associated with atrophied volume of total brain during longitudinal change. This suggests that individuals with advanced COVID-19 may be more susceptible to accelerated global brain aging. Caudate was genetically affected by all COVID-19 phenotypes. Seven variants were shared between advanced COVID-19 and global brain aging. rs117169628 was colocalized between advanced COVID-19 and global brain aging, and exerted an inhibitory effect on CDH15 expression, further strengthening the causality. Six metabolites, 1 protein, and 1 immune trait were identified as potential mediators. Our study indicates that advanced COVID-19 might be genetically associated with accelerated brain aging. Brain health should be paid more attention in long COVID-19.

Humans↗

PubMed2026

Shared genetic architecture and cellular convergence between female reproductive disorders and pulmonary function: a genome-wide cross-trait analysis.

Female reproductive disorders (FRDs), including polycystic ovary syndrome, endometriosis, uterine leiomyomata, and infertility, have been epidemiologically associated with impaired pulmonary function. However, it remains unclear whether this cross-organ link reflects shared genetic etiology and, if so, which cellular mechanisms mediate it. We performed a systematic genome-wide cross-trait analysis of three FRDs and lung function traits (FEV₁, FVC, FEV₁/FVC) using GWAS summary statistics from individuals of European ancestry, integrating genetic correlation, bidirectional causal inference, pleiotropy mapping, and single-cell enrichment analyses. We identified significant negative genetic correlations between FRDs and lung volume traits, most prominently for FVC (rg range: - 0.077 to - 0.178). Bidirectional causal analyses indicated that FRDs have a detrimental effect on lung volume, with higher FRD genetic liability associated with reduced lung volume. Cross-trait meta-analysis identified 17 pleiotropic variants across 11 loci, with the 19q13.2 (LTBP4) and 12q13.13 (HOXC6/HOXC9) loci showing strong evidence of shared causal variants. Critically, single-cell analyses revealed that shared genetic risk converged on mesenchymal lineages across organs, specifically alveolar adventitial fibroblasts in the lung and stromal/smooth muscle cells in the endometrium. Transcriptome-wide analyses further nominated the estrogen-responsive gene RERG as a convergent gene linking these conditions with lung function. Our study revealed a shared genetic architecture between female reproductive disorders and lung function traits, providing a basis for further mechanistic investigations and potential clinical evaluation. Furthermore, our findings suggest that shared fibroproliferative and hormone-responsive pathways may offer insights into the biological mechanisms underlying these conditions.

Female↗

PubMed2025

Distinguishing specific from broad genetic associations between external correlates and common factors.

MOTIVATION: Within the genomic structural equation modelling (genomic SEM) framework, common factors are often used to index shared genetic etiology across constellations of genome-wide associations studies (GWASs) phenotypes. A standard common pathway model, in which a genetic association is estimated between an external GWAS phenotype and a common factor, assumes that all genetic associations between the external GWAS phenotype and the individual indicator phenotypes are mediated through the factor. This assumption can be tested using the QTrait statistic, which compares the common pathway model to an independent pathways model that allows for direct genetic associations between the external GWAS phenotype and the individual indicators of the factor. However, QTrait is not designed to identify either the magnitude or the source of this heterogeneity. RESULTS: We expand upon the QTrait approach by describing an effect size index that quantifies the degree to which the common pathways model is violated, and we provide a systematic approach for empirically identifying specific direct pathways between an external trait and indicator traits. Our method comprises a series of omnibus tests and outlying indicator detection algorithms indexing the heterogeneity of associations between the genetic component of external traits and the individual indicators of common factors. We provide a set of automated functions which we apply to investigate the patterns of genetic associations across a set of external correlates with respect to indicators of general cognitive ability and case-control and proxy GWAS indices of Alzheimer's disease. AVAILABILITY AND IMPLEMENTATION: The Genomic SEM R package and the QTrait function is available at https://github.com/GenomicSEM/GenomicSEM. The QTrait function tutorial is available at https://github.com/GenomicSEM/GenomicSEM/wiki/8.-Tutorials. To ensure reproducibility of the analyses presented in this manuscript, the exact version of the QTrait function used, along with input data and scripts, has been archived on Zenodo (DOI: https://doi.org/10.5281/zenodo.17186083).

Genome-Wide Association Study↗

PubMed2026

Elucidating shared genetic signals between type 2 diabetes and three neurodegenerative dementia phenotypes.

Type 2 diabetes (T2D) and dementia frequently co-occur, yet the biological mechanisms underlying this comorbidity remain incompletely understood. Here, we systematically investigate shared genetic signals between T2D and three forms of neurodegenerative dementia (Alzheimer disease, Lewy body dementia, and sporadic frontotemporal dementia) using large-scale genome-wide association studies of clinically diagnosed individuals. We identify five genomic regions harboring shared association signals between T2D and at least one dementia subtype. Among these, the APOE locus was common to all dementia subtypes, whereas the remaining four loci (GBA, CRY2/PEX16/MAPK8IP1, INO80E, and NSF) were each shared exclusively between T2D and one dementia subtype. Integrating multi-omics data across several disease-relevant tissues and orthogonal lines of functional evidence, we prioritize 26 candidate genes through which these shared genetic loci potentially mediate their effect. Pathway enrichment highlights lipid and lipoprotein regulatory biology as a central shared axis. Mendelian randomization analyses using genetically regulated gene expression in relevant tissues indicate pleiotropic mechanisms with divergent phenotypic consequences. Our findings identify shared genetic loci between T2D and neurodegenerative dementia, revealing systemic metabolic-neurodegenerative trade-offs and highlighting key genes that underpin the comorbidity, providing a framework for improved understanding of age-related multi-morbidity.

Alzheimer disease↗

PubMed2026

Multivariate, Multi-Omic Analysis in 799,429 Individuals Identifies 134 Loci Associated with Somatoform Traits.

INTRODUCTION: Somatoform traits (e.g., health anxiety, somatic preoccupation, and bodily distress symptoms) are prevalent and pose challenges to clinical practice. Understanding their genetic basis could improve diagnostic and therapeutic approaches. METHODS: Using available summary statistics, we conducted a multivariate genome-wide association study (GWAS) and multi-omic analysis of four somatoform traits - fatigue, irritable bowel syndrome, pain intensity, and health satisfaction - in 799,429 individuals genetically similar to European reference panels. RESULTS: The GWAS identified 134 loci associated with a somatoform common factor, including 44 loci not significant in the input GWAS and 8 novel loci for somatoform traits. Novel loci were mechanistically informative, mapping to the DNM1 gene and the protocadherin gene cluster (PCDHA1-4), which are involved in nociceptor sensitization and synaptogenesis, respectively. Gene-property analyses highlighted an enrichment of genes involved in synaptic transmission and enriched expression in 11 brain tissues and the pituitary. Across two brain transcriptomic datasets, we identified 16 high-confidence genes whose expression in enriched tissues was associated with somatoform traits. There was substantial polygenic overlap (76-83%) between the somatoform and externalizing, internalizing, and general psychopathology factors. Somatoform polygenic scores were associated with obesity, type 2 diabetes, and tobacco use disorder in independent biobanks. Drug repurposing analyses suggested potential therapeutic targets, including MEK inhibitors, while Mendelian randomization analyses indicated potentially protective effects of gut microbiota. DISCUSSION: Consistent with emerging medical and genetic knowledge, somatoform traits have a shared etiology and considerable polygenic overlap with psychopathology. The biological insights from drug repurposing and Mendelian randomization analyses could provide promising avenues for treatment development.

Genetics↗

PubMed2025

Shared genetic risk and causal associations between Post-traumatic stress disorder and migraine with antithrombotic agents and other medications.

Post-traumatic stress disorder (PTSD) is a psychiatric disorder that frequently co-occurs with pain disorders including migraine. There are proposed biological, genetic and environmental factors associated with both PTSD and migraine suggesting shared etiology. Genome-Wide Association Studies (GWAS) have been used to identify genomic risk loci associated with various disorders and to investigate genetic overlap between traits. There is a significant genetic correlation between PTSD and migraine with no evidence of a causal relationship that could be attributed to pleiotropy. Cross-disorder genetic analyses were applied to investigate the genetic overlap and causal associations using GWAS summary statistics of PTSD (n = 214408), migraine (n = 873341) and 23 medication use traits (n = 78808-305913) including anti-depressants, anti-migraine preparations and beta-blocking agents. Across the entire genome, anti-thrombotic agents had a significant and negative genetic correlation with PTSD (rG = -0.2, P FDR = 0.032) and a positive genetic correlation with migraine (rG = 0.26, P FDR = 2.23 x 10-8). PTSD showed significant genetic correlation with 11 other medication use traits including beta blocking agents (rG = -0.11, P FDR = 0.034). Of the 2495 genomic regions tested, PTSD showed significant local genetic correlation with 12 medication use traits at 43 loci; while migraine showed significant genetic correlation with only anti-inflammatory agents and anti-rheumatic products at locus 12:57522282-57607142 (DAB1) (P < 2 x 10-5). The genetic liability to PTSD had a causal effect on increased risk of using pain medication such as opioids (β ivw = 0.59, P = 5.21 x 10-5) while the genetic liability to migraine had a causal effect on the increased risk of using anti-thrombotic agents (β ivw = 0.59, P = 1.69 x 10-7). The genes in the genomic regions shared between PTSD and medication use traits were enriched in neural-related pathways such as neuron development, neurogenesis and protein kinase activity. These results provide further insight into the genetically controlled biological and environmental factors underlying the shared etiology between PTSD and migraine. The identified biomarkers can be used as a basis for investigation as potential drug targets for both disorders. These findings are significant for drug re-purposing and treatment of PTSD and migraine using monotherapy.

GWAS↗

PubMed1979

Notes on the genetics of congenital glaucoma.

Relying on the analysis of 81 non-Gypsy families with congenital glaucoma from the entire territory of Slovakia, the authors discuss the share of the genetic component in the etiology of the disease. The characteristics of the families of this series resembled those of comparable series as far as the percentage of familial occurrence, the percentage of bilateral occurrence (73.56%), the percentage of parental consanguinity (4.87%) and in the prevalence of males with a ratio of 1.55:1 are concerned. The incidence of the disease in Slovakia varies around 1 per 22,000 live-born infants. In the non-Gypsy population of Slovakia, the authors assume a multifactorial etiology.

Consanguinity↗

PubMed2025

Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders.

BACKGROUND: The intricate shared genetic architecture underlying allergic disorders-including allergic asthma, atopic dermatitis, contact dermatitis, allergic rhinitis, allergic conjunctivitis, allergic urticaria, anaphylaxis, and eosinophilic esophagitis-remains incompletely characterized. METHODS: Our study employed genomic structural equation modeling (Genomic SEM) to define the common factor representing the shared genetic architecture of allergic disorders. Coupled with diverse post-GWAS analytical methods, we aimed to discover susceptible loci and investigate genetic associations with external traits. Furthermore, we explored enriched genetic pathways, cellular layers, and genomic elements, and investigated putative plasma protein biomarkers. Polygenic risk score (PRS) analyses, leveraging our integrated GWAS data, were conducted to assess chromosomal-level risk associations for allergic disorders. RESULTS: A well-fitted genomic SEM integrated GWAS data, revealing the shared genetic architecture of allergic disorders. We identified a total of 2038 genome-wide significant SNP loci (p < 5e-8), including 31 previously unreported loci. Fine-mapping of variants and gene sets pinpointed 2 causal variants and 31 candidate susceptible genes. Genetic correlation analyses further illuminated the shared genetic architecture underlying multiple traits, notably psychiatric disorders. Preliminary findings identified four putative causal plasma protein biomarkers. CONCLUSION: Notably, this study presents the first comprehensive genetic characterization of allergic disorders through a GWAS analysis of an unmeasured composite phenotype, providing novel insights into shared etiological pathways across these conditions.

Humans↗

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↗

PubMed2026

Schizophrenia and bipolar disorder: a comparative analysis of genetic and brain network connectivity.

BACKGROUND: Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions with overlapping clinical presentations, genetic risk factors, and brain network dysfunction. Whether alterations in large-scale intrinsic brain networks reflect shared or disorder-specific genetic influences remains poorly understood. Clarifying this distinction is essential for refining etiological models and improving diagnostic precision. METHODS: Genome-wide inferred statistics (GWIS) were applied to decompose the genetic architecture of SCZ and BD into shared and unique components. Using resting-state network (RSN) data from the UK Biobank, functional connectivity (FC) and structural connectivity (SC) were extracted as neuroimaging phenotypes. Causal inference approaches were subsequently employed to infer potential directional relationships between brain network connectivity and each disorder. RESULTS: Analyses revealed both common and distinct patterns of brain network connectivity associated with SCZ and BD. Notably, SC within the default mode network (DMN) exhibited opposing effects across the two disorders, suggesting divergent structural underpinnings despite clinical overlap. Additionally, SC within the limbic network (LN) and frontotemporal control network demonstrated potential causal relationships with both conditions, implicating these circuits astransdiagnostic neural substrates. CONCLUSION: These findings illuminate the shared and disorder-specific genetic and neural architecture underlying SCZ and BD. Integrating genome-wide genetic methods with large-scale neuroimaging data offers a powerful framework for disentangling psychiatric comorbidity and may inform more targeted diagnostic criteria and individualized treatment strategies.

Humans↗

PubMed2026

Genomic basis of developmental defects of enamel and sex-specific effects.

We conducted a multi-ancestry genome-wide association study (GWAS) of developmental defects of enamel (DDE) in the primary dentition among 6,061 U.S. preschool-aged children (3-5 years). We investigated four DDE phenotypes (demarcated opacities, diffuse opacities, hypoplastic defects, and a combined DDE trait) leveraging main-effect models, joint gene-sex interaction testing (2df), and sex-stratified analyses. SNP-based heritability for the combined DDE trait was estimated at 20%, with concordance analyses robustly supporting a genetic etiology. We identified 39 unique genome-wide significant loci (P<5×10 ), with five surpassing a study-wide Bonferroni-corrected statistical significance criterion (P<1.25×10 9), including Y RNA and ALDH1A1. The main-effect GWAS identified 20 loci, including HBS1L and MYB, genes regulating hematopoiesis with plausible roles in amelogenesis. Joint test and sex-stratified analyses revealed 19 additional loci, including ALDH1A1, TENM2, and DLGAP2, demonstrating sex-specific heterogeneity. Nineteen loci exhibited sex-specific differences after Bonferroni correction (P<2x10-3), including genes involved in retinoic acid signaling (ALDH1A1), odontogenesis (TENM2), and neurodevelopment (DLGAP2, CDH10). Pathway enrichment highlighted ectodermal and synapse organization networks, suggesting shared etiological mechanisms between DDE and systemic conditions like neurofibromatosis and autism spectrum disorder. Notably, no locus generalized in an external GWAS of permanent dentition DDE, underscoring fundamental biological differences in the genetic architectures governing primary versus permanent enamel formation. Crucially, a comprehensive cross-trait pleiotropy lookup against early childhood caries (ECC) revealed no shared genetic architecture, supporting the notion that the established clinical and epidemiological association between DDE and ECC is likely driven by structural defects increasing caries lesion susceptibility rather than genetic pleiotropy. By integrating gene-sex interaction testing, this study offers novel insights into the complex, sexually dimorphic genetic etiology of DDE and augments the biological evidence base that can support the development of precision pediatric dentistry.

developmental defects of enamel↗

PubMed2026

Cross-Ancestry Proteogenomic Analyses Identified New Therapeutic Insights for Ischemic Heart Disease.

BACKGROUND: Most drugs target proteins, and proteome-wide genetic analyses in diverse populations could discover potential novel and repurposed targets for improved prevention and treatment of ischemic heart disease (IHD) beyond statin therapy. OBJECTIVES: The purposes of this study were to use cis-acting single nucleotide polymorphisms (cis-pQTLs) identified for plasma proteins in East Asians and Europeans to discover and validate potential drug targets for IHD. METHODS: We measured plasma levels of 9,520 (Olink/SomaScan: 2,923/7,297) proteins in a case-cohort study of IHD (1,976 incident cases and 2,001 subcohort controls) in statin-free individuals in the prospective China Kadoorie Biobank (CKB). Genome-wide association studies identified 2,895 (Olink/SomaScan: 1,301/1,594) cis-pQTLs for these proteins in CKB. Two-sample Mendelian randomization (MR) and colocalization analyses assessed associations of all available cis-pQTLs for these proteins with IHD in East Asians (n = 29,319 cases), with further replication in Europeans (n = 181,522 cases) and comparison with findings in previous MR studies. RESULTS: In CKB observational analyses, a total of 959 (Olink/SomaScan: 426/533) proteins were associated at false discovery rate-corrected P < 0.05 with IHD after adjusting for major IHD risk factors. Two-sample MR analyses provided genetic support for 54 unique (Olink/SomaScan: 36/28) proteins in IHD etiology. Colocalization analyses confirmed shared gene-protein-IHD associations (posterior probability of hypothesis 4 [PPH4] ≥0.8) for 15 unique (Olink/SomaScan: 10/10) proteins, including 8 lipid-related, 3 inflammation-related, 1 blood pressure-related, and 3 alcohol-related proteins in East Asians. In Europeans, MR analyses of 12 non-alcohol-related proteins showed directionally concordant results for 8 proteins, with 5 having strong colocalization evidence of shared gene-protein-IHD associations (PPH4 ≥0.8), including 4 lipid-related (proprotein convertase subtilisin/kexin type 9, LPA, APOE, cadherin-1) and 1 systolic blood pressure-related (fibroblast growth factor 5) protein. However, 4 proteins showed directionally discordant MR results, including 2 lipid-related (APOA5, SORT1) and 1 inflammation-related (transforming growth factor beta 1) proteins with strong colocalization evidence of shared gene-protein-IHD associations (PPH4 ≥0.8). Comparison with previous MR studies revealed little consistency across studies in the number and identity of target proteins for IHD beyond well-established lipid-related (low-density lipoprotein cholesterol, lipoprotein(a), and triglycerides) or inflammation-related (interleukin-6) protein targets. CONCLUSIONS: The findings support a role for lipid-driven chronic inflammation in IHD etiology, and treatment strategies simultaneously targeting multiple lipid and inflammation pathways should be prioritized for further research to improve drug treatment of IHD beyond statin therapy.

Aged↗

PubMed2026

RBM20 Truncating Variants and Human Cardiomyopathy.

IMPORTANCE: Genetic diagnosis has become increasingly important to guide clinical decision-making for patients with dilated cardiomyopathy (DCM). Pathogenic or likely pathogenic (P/LP) missense variants in the gene RBM20 cause a highly penetrant arrhythmogenic DCM, but the role of RBM20 truncating variants (RBM20tvs) is unclear. OBJECTIVE: To assess the contribution of RBM20 variants to arrhythmogenic DCM. DESIGN, SETTING, AND PARTICIPANTS: In this cohort study, participants in the genome-first UK Biobank (UKB) and All of Us populations were evaluated to assess the etiologic fraction, natural history and penetrance of RBM20 variants. Retrospective data were collected from an international cohort of patients with DCM and RBM20 variants identified at centers of excellence for genetic heart disease and compared based on time to event. Study dates are not disclosed because the institutional review board did not authorize the sharing of this information. EXPOSURES: RBM20 variants were compared to known P/LP variants and variants of uncertain significance in RBM20 as well as titin truncating variants (TTNtvs). MAIN OUTCOMES AND MEASURES: Major ventricular arrhythmias, end-stage heart failure, and heart failure hospitalization as measured by medical record review (retrospective cohort) and diagnostic codes (UKB). RESULTS: Two main cohorts were studied for this project. In UK Biobank, a cohort of participants with RBM20tvs, RBM20 synonymous variants, and TTNtvs was studied. Of these 4249 participants, 1869 (44%) were male. The mean (SD) age at enrollment was 56 (8.2) years. In the RBM20 registry, of 179 patients, 105 (58.6%) were male, and the mean (SD) age at enrollment was 43.8 (19.1) years. A validation cohort from the All of Us biobank was also used. This consisted of 7002 participants, 4342 of whom (62.0%) were male, and the mean (SD) age was 52.7 (16.7) years. The etiologic fraction of RBM20 variants in arrhythmogenic DCM was 0.53 (95% CI, 0.32-0.67; P < .001). In genome-first biobanks, lifetime incidence of cardiomyopathy, heart failure, or major ventricular arrhythmia diagnosis was lower in participants with RBM20 variants than in those with TTNtvs (hazard ratio, 0.55; 95% CI, 0.36-0.84; P < .001). Patients with RBM20tvs and DCM presented to referral centers later in life than those with P/LP RBM20 and DCM (mean [SD], 53 [10] vs 34 [18] years; P < .001) and were less likely to have a family history of sudden cardiac arrest (2 of 10 [20%] vs 11 of 17 [65%]; P = .046) or cardiomyopathy (2 of 10 [20%] vs 14 of 18 [78%]; P < .001). There was no significant difference in age- and sex-adjusted incident major heart failure or arrhythmia events between patients with RBM20tv and DCM or those with P/LP RBM20 and DCM, though sex-adjusted lifetime hazard was reduced in those with RBM20tv and DCM (hazard ratio, 0.13; 95% CI, 0.03-0.56; P = .01). CONCLUSIONS AND RELEVANCE: This study found that RBM20 variants contributed to arrhythmogenic DCM phenotypes but conferred reduced lifetime disease penetrance compared to TTNtvs and milder disease severity alone than P/LP RBM20 variants. Their potential for additive interactions with other damaging variants should be considered in patients with DCM and their families.

Humans↗

PubMed2026

The causal relationship between multiple cardiovascular diseases and glioblastoma: A Mendelian randomization study.

Observational studies suggest an association between glioblastoma (GBM) and cardiovascular diseases (CVDs), but a causal relationship remains unestablished. This study aimed to investigate the causal link between multiple CVDs and GBM risk. The inverse variance weighted method indicated that all 18 CVDs had significant causal associations with GBM (P < .05). Genetically predicted CVDs were uniformly associated with a lower risk of GBM (odds ratio < 1), identifying them as potential protective factors. Sensitivity analyses confirmed the absence of significant heterogeneity or horizontal pleiotropy, and the MR-Steiger test validated the correct causal direction. This Mendelian randomization (MR) study provides evidence that a range of CVDs are causally associated with a decreased risk of developing GBM. These findings suggest shared biological pathways and offer new insights for understanding GBM etiology. We conducted a 2-sample MR analysis using publicly available genome-wide association study data. GBM was the outcome, and 18 cardiovascular-related traits (including coronary artery disease, myocardial infarction, and venous thromboembolism) were exposures. Instrumental variables were single-nucleotide polymorphisms significantly associated with exposures (P < 5 × 10-8). The primary analysis used the inverse variance weighted method, supplemented with MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses, including Cochran Q test, MR-Egger intercept test, leave-one-out analysis, and MR-Steiger directionality test, were performed to ensure robustness.

Causality↗

PubMed2026

The first 25 years of the NICHD structural birth defects initiative.

Initiated by NICHD and crafted with clinicians and laboratory scientists, the Structural Birth Defects (SBD) Initiative has supported research into the clinical, genetic, biochemical, mechanistic, developmental, and environmental basis of human disorders with structural anomalies for 25 years. The SBD Initiative has supported and continues to fund research teams studying a broad spectrum of single gene (Mendelian) disorders along with defining loci and susceptibility genes in oligogenic phenotypes, including genetic and environmental risk modifiers. The Initiative required and currently convenes biennial meetings of SBD investigators to share data, exchange ideas and initiate collaborations. In alternate years, online trainee symposia provide a platform for medical fellows, postdoctoral fellows and graduate students to present their data, with the goal of attracting and retaining this future generation of investigators in SBD research. In addition to determining their etiology, the SBD Initiative has supported remarkable progress in developing a fundamental mechanistic understanding of this diverse group of phenotypes. Together, scientific progress has led to translational benefits that include 1) widespread diagnostic testing for families with these disorders, both within the United States and across the world, and 2) pharmacological treatments for affected individuals. This progress has fulfilled the promise of the vision of the architects of the program, which is reviewed in this article, and continues to drive the field forward.

Animals↗