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PubMed2026

Genetic Contributors to Postoperative Delirium and Their Implications for Dementia Outcomes.

BACKGROUND: Postoperative delirium (POD) is a perioperative neurocognitive disorder that substantially impairs patient recovery. Unfortunately, its genetic risk profile and relationship with subsequent dementia remain unclear. This study aimed to elucidate genetic contributors to POD identified via Hospital Episode Statistics codes and to examine its association with subsequent dementia. METHODS: The study included 230,179 noncardiac and 21,254 cardiac surgery subjects from the UK Biobank, defining POD using delirium codes from the International Classification of Diseases (10th revision) recorded within the first 7 postoperative days. Genome-wide association studies were performed in the noncardiac and cardiac cohorts and their prespecified subgroups, followed by functional annotation, gene prioritization and drug-target analyses. Associations between POD and subsequent dementia were estimated using Cox models. RESULTS: In the noncardiac cohort, one genome-wide significant locus was identified at the APOE region, with rs429358 as the lead variant ( P = 5.00 × 10 -28 ). Integrative gene prioritization analyses highlighted multiple genes within this locus. Exploratory drug-target analyses suggested potential subgroup-specific drug-target enrichment. In the cardiac cohort, no genome-wide significant signals were detected. POD was associated with all-cause dementia after both noncardiac (hazard ratio, 6.45; 95% CI, 5.45 to 7.63) and cardiac (hazard ratio, 2.95; 95% CI, 1.71 to 5.08) surgeries. CONCLUSIONS: This study demonstrates APOE as a genetic risk locus for International Classification of Diseases-coded POD in the noncardiac surgery setting and confirms an association between POD and subsequent dementia.

Humans↗

PubMed2026

HLA and non-HLA genetic analyses reveal suggestive variants associated with statin-induced liver injury.

BACKGROUND: Statins are widely prescribed for cardiovascular risk reduction and are generally well tolerated. However, they can cause drug-induced liver injury (DILI), and the genetic factors contributing to statin-DILI remain poorly understood. METHODS: HLA association and genome-wide association (GWAS) studies were conducted to identify genetic variants associated with statin-DILI. High-confidence cases (n=71) were identified from the Drug-Induced Liver Injury Network (DILIN) and compared with statin-exposed controls without liver injury (n=551) from the Indiana Biobank. Association testing was performed across ancestries and within ancestry, adjusting for age, sex, and three principal components of genotypes. Top variants were further evaluated in non-statin DILI cases and unexposed controls. In addition, we investigated the frequency of candidate variants among a comprehensive list of pharmacogenetic variants related to statins. RESULTS: HLA-DQA1*03:01 was significantly associated with increased risk of statin-DILI (OR=3.49, 95% CI 2.21-5.51, p-value=1.27×10-7), with enrichment observed across multiple ancestry groups, particularly non-Hispanic Black and Hispanic individuals. From the GWAS, three loci showed suggestive associations (p-value <5×10-06) with statin-DILI, including rs35197737 in RGS1 (OR=5.03, 95% CI 1.11-3.66, p=1.14×10-7), rs75629598 in FRMD4A (OR=4.4, 95% CI=2.33-8.12, p=3.97×10-6), and rs7658630 in the intergenic region on chromosome 4 (OR=4.86, 95% CI 2.66-8.85, p=2.68×10-7). No pharmacogenetic variants revealed statistical significance. CONCLUSION: We identified HLA and non-HLA genetic variants associated with statin DILI. Future studies with larger sample sizes should confirm these observations.

Humans↗

PubMed2024

A functional genomic framework to elucidate novel causal metabolic dysfunction-associated fatty liver disease genes.

BACKGROUND AND AIMS: Metabolic dysfunction-associated fatty liver disease (MASLD) is the most prevalent chronic liver pathology in western countries, with serious public health consequences. Efforts to identify causal genes for MASLD have been hampered by the relative paucity of human data from gold standard magnetic resonance quantification of hepatic fat. To overcome insufficient sample size, genome-wide association studies using MASLD surrogate phenotypes have been used, but only a small number of loci have been identified to date. In this study, we combined genome-wide association studies of MASLD composite surrogate phenotypes with genetic colocalization studies followed by functional in vitro screens to identify bona fide causal genes for MASLD. APPROACH AND RESULTS: We used the UK Biobank to explore the associations of our novel MASLD score, and genetic colocalization to prioritize putative causal genes for in vitro validation. We created a functional genomic framework to study MASLD genes in vitro using CRISPRi. Our data identify VKORC1 , TNKS , LYPLAL1 , and GPAM as regulators of lipid accumulation in hepatocytes and suggest the involvement of VKORC1 in the lipid storage related to the development of MASLD. CONCLUSIONS: Complementary genetic and genomic approaches are useful for the identification of MASLD genes. Our data supports VKORC1 as a bona fide MASLD gene. We have established a functional genomic framework to study at scale putative novel MASLD genes from human genetic association studies.

Humans↗

PubMed2026

The association of cardiovascular health with new-onset pulmonary hypertension and the mediating role of proteomic signatures.

BACKGROUND: The cardiovascular health (CVH) metrics have been reported to play an important role in the development of noncommunicable chronic diseases, yet its link to pulmonary hypertension (PH) risk and the underlying biological mechanisms remain unclear. This study aimed to investigate the association of CVH with PH risk and elucidate the mediating role of plasma proteomic signatures. METHODS: A total of 279 220 participants without PH at enrollment of the UK Biobank were included. Cox regression was used to quantify the association between CVH and incident PH. Proteome-wide association analysis, mediation analysis, and functional enrichment analysis were conducted to identify protein mediators. Key hub proteins were further validated at the transcriptional level through quantitative polymerase chain reaction (qPCR) in an animal model of PH, as well as at the protein level, and by macrophage-specific knockdown of interleukin (IL)-6 and CCL4 to evaluate its impact on rat pulmonary artery smooth muscle cell (PASMC) migration and proliferation. RESULTS: Over a median 13.2-year follow-up, 1325 PH cases occurred. Compared to the lowest CVH, participants with moderate and high CVH had 59% [hazard ratio (HR): 0.41; 95% confidence interval (CI): 0.33-0.49] and 82% (HR: 0.18; 95% CI: 0.14-0.23) lower risk, respectively. Proteomic analyses revealed that this association was significantly mediated by a distinct plasma protein signature. Pathway enrichment analysis indicates that proteins are significantly enriched in inflammatory/immune pathways, and key hub proteins were identified as participating in the central mechanism pathway. In the lung tissue of PH rat models, the mRNA and protein expression levels of IL-6 and C-C motif chemokine ligand 4 (CCL4) were significantly elevated. Furthermore, functional assays demonstrated that knockdown of IL-6 or CCL4 in macrophages significantly attenuated the migration and proliferation of rat PASMCs in vitro. CONCLUSION: High CVH level, defined by Life's Essential 8 (LE8), is significantly linked to a reduced risk of developing PH. This protective effect is primarily mediated by a proteomic signature, revealing the role of signaling pathways such as cytokine-cytokine receptor interaction in the prevention of PH.

Hypertension, Pulmonary↗

PubMed2025

Dietary patterns and risk of ischemic stroke: A two-sample Mendelian randomization study.

Diet and nutrition critically influence the development and outcomes of ischemic stroke (IS). However, observational studies often yield inconsistent findings due to confounding and measurement error. Mendelian randomization (MR) provides an alternative approach to strengthen causal inference. We conducted a 2-sample MR analysis to evaluate the causal associations between 22 dietary factors and IS risk. Genetic instruments for dietary exposures were derived from the UK Biobank genome-wide association study, and outcome data were obtained from the MEGASTROKE consortium. Inverse-variance weighted analysis served as the primary method, complemented by sensitivity analyses. Consumption of oily fish (β = -0.402, P = .022), cheese (β = -0.364, P = .001), dried fruit (β = -0.710, P = .0002), weekly red wine (β = -0.507, P = .024), and calcium supplements (β = -3.994, P = .015) was associated with reduced risk of IS. Conversely, dietary patterns characterized by high-sugar or high-protein intake showed suggestive associations with increased IS risk, although these did not remain significant after multiple-comparison correction. This 2-sample MR study provides evidence that specific dietary factors, including oily fish, cheese, dried fruit, red wine, and calcium, may reduce IS risk, while high-sugar and high-protein diets may confer increased risk. These findings underscore the importance of dietary management in stroke prevention and highlight the need for further studies to validate the role of potentially harmful dietary patterns.

Humans↗

PubMed2025

Causal relationship between albumin, total protein, and colorectal cancer risk: A 2-sample Mendelian randomization study.

Albumin (ALB) and total protein (TP) are vital constituents of the blood, and their levels and roles in the risk of colorectal cancer (CRC) are of significance. Previous observational studies have reported correlations among ALB, TP, and CRC. However, the existence of a causal relationship between ALB and CRC in European populations has not been adequately investigated and the causal link between TP and CRC remains unexplored. To address these gaps, we applied Mendelian randomization (MR) to investigate the potential causal relationship between ALB, TP, and CRC. Two-sample MR analysis was used to investigate whether there was a causal relationship between ALB, TP, and CRC. Our exposure data were extracted from genome-wide association study (GWAS) databases sourced from the UK Biobank, containing 315,268 and 314,921 Europeans participants for ALB and TP analyses, respectively. Single nucleotide polymorphisms that were significantly associated with ALB and TP were assessed using GWAS datasets. Our data were derived from the FinnGen Consortium CRC GWAS, which contained 6509 CRC cases and 28,7137 controls. Causal inference between ALB, TP, and CRC was performed using 3 MR methods: inverse variance weighting (IVW), MR-Egger, and weighted median. The IVW analysis showed no significant causal association between ALB and CRC (OR = 1.04, 95% CI = 0.89-1.21, P = .65). In contrast, the IVW analysis for TP and CRC showed a significant causal association (OR = 0.78, 95% CI = 0.66-0.92, P = .003), suggesting a reduced risk of CRC. Through a 2-sample MR study investigating the causal relationship between ALB, TP, and CRC in a European population, our findings revealed a significant causal relationship between TP and a reduced risk of CRC.

Humans↗

PubMed2026

Association between 1400 blood metabolites and the risk of ankylosing spondylitis: A 2-stage, 2-sample Mendelian randomization study.

Human blood metabolites have been closely linked to ankylosing spondylitis (AS) in observational studies, yet direct causal evidence remains limited. This study aims to use Mendelian randomization (MR) to pinpoint causal metabolites associated with AS and to predict potential side effects of metabolite interventions. Genetic instruments for exposure were sourced from a genome-wide association study of 1400 blood metabolites, while genome-wide association study data for AS outcomes were derived from the FinnGen cohort. The primary MR analysis was conducted using the inverse variance weighted method. Supplemental analyses were conducted using weighted median, MR-Egger, simple mode, and weighted mode methods, while sensitivity analyses were performed to evaluate heterogeneity and pleiotropy. A replication analysis using an additional the UK Biobank cohort was also performed to determine metabolites associated with AS. The Steiger test and linkage disequilibrium score regression were used to further strengthen causal inference. Lastly, a phenome-wide Mendelian randomization analysis was performed to investigate the potential on-target side effects of metabolite interventions. After comprehensive analyses, 3 metabolites (the 2'-deoxyuridine levels, the hate to mannose ratio, and the Uridine to 2'-deoxyuridine ratio) were identified as being genetically associated with AS. The phenome-wide Mendelian randomization analysis revealed that the hate to mannose ratio might have deleterious effects on 4 other diseases, while no significant associations were found for the 2'-deoxyuridine levels or the uridine to 2'-deoxyuridine ratio with other diseases. This systematic MR analysis unveiled the potential role of the 2'-deoxyuridine levels, hate to mannose ratio and uridine to 2'-deoxyuridine ratio as the causal mediator in the development of AS. Considering the advantages and disadvantages, 2'-deoxyuridine appears as the most promising prospective therapeutic target for the prevention of AS.

Humans↗

PubMed2026

Genetically predicted childhood traits and parental health and risk of pediatric psychiatric disorders: A 2-sample Mendelian randomization study.

The etiology of pediatric psychiatric disorders is complex, involving intergenerational influences and a child's own developmental health. We aimed to investigate the potential effects of genetically predicted childhood traits (childhood obesity, absence epilepsy, intelligence) and parental health traits (longevity, Alzheimer disease, severe depression) on the risk of several childhood and adolescent psychiatric disorders. We employed a 2-sample Mendelian randomization (MR) design using summary statistics from large-scale genome-wide association studies. Data for parental health exposures were primarily from the UK Biobank. Data for childhood trait exposures were from various consortia. Data for outcomes - conduct disorder, mixed conduct and emotional disorders, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and broader behavioral/emotional and social disorders - were sourced from FinnGen and the Psychiatric Genomics Consortium, among others. We used the inverse-variance weighted method for the primary analysis, with MR-Egger, weighted median, and weighted mode as additional analyses. To test the robustness of the results, we conducted sensitivity analyses using MR-Egger regression, Cochran Q test for heterogeneity, the MR-pleiotropy residual sum and outlier test, and a leave-one-out analysis. Genetic liability for childhood obesity was associated with an increased risk of ASD (odds ratio = 1.06, P = .016) and ADHD (odds ratio = 1.09, P = .026), even though these associations did not withstand multiple testing correction. No other robust, statistically significant causal associations were identified. Sensitivity analyses showed limited evidence of bias from horizontal pleiotropy for the main findings. Our findings provide MR evidence supporting potential links from genetic liability for childhood obesity to increased risks of ASD and ADHD. These results highlight the importance of considering a child's early-life health trajectory in the etiology of pediatric psychiatric disorders.

Humans↗

PubMed2026

Genetically predicted lower FLT3L levels increase the risk of hypertrophic cardiomyopathy partly mediated by phosphate: Evidence from a 2-step Mendelian randomization analysis.

We performed a 2-step Mendelian randomization (MR) study to investigate the associations of Fms-related tyrosine kinase 3 ligand (FLT3L) and phosphate levels with the risk of hypertrophic cardiomyopathy (HCM). Genetic instruments for 75 circulating inflammatory factors were obtained from the NHGRI-EBI GWAS Catalog, while summary statistics for circulating phosphate and HCM were derived from the UK Biobank and FinnGen, respectively. Univariable MR analysis using the inverse-variance weighted method indicated that genetically predicted higher phosphate levels were associated with an increased risk of HCM (OR = 1.36, P = 4.82 × 10-2). Among the inflammatory markers, FLT3L emerged as a significant candidate and showed inverse associations with phosphate levels (β = -0.05, P = 1.70 × 10-9) and HCM (OR = 0.79, P = 4.10 × 10-2). Bidirectional MR analyses did not support a causal effect of phosphate on FLT3L. Mediation analysis suggested that phosphate levels accounted for an estimated 12.05% of the total effect of FLT3L on HCM. Genetic liability to lower FLT3L levels is associated with a higher risk of HCM, and this relationship may be partially mediated through circulating phosphate levels.

Humans↗

PubMed2026

Genetically proxied circulating PD-1/PD-L1 levels and broadly defined myocarditis: A bidirectional Mendelian randomization study with exploratory lipidomic analyses.

Myocarditis is an inflammatory myocardial disease with potentially severe outcomes. Programmed cell death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1) regulate immune tolerance, but the association between lifelong genetically proxied circulating PD-1/PD-L1 levels and broadly defined myocarditis remains uncertain. We investigated these associations and explored related plasma lipid species. We conducted bidirectional 2-sample Mendelian randomization using proteomic genome-wide association data from the UK Biobank Pharma Proteomics Project and INTERVAL. FinnGen Release 10 was the primary broadly defined myocarditis outcome, and an independent myocarditis genome-wide association study (GCST90018882) provided outcome-level validation. Complementary estimators, heterogeneity and pleiotropy diagnostics, influence analyses, MR-RAPS, and supportive meta-analyses were performed. Associations with 179 plasma lipid species were examined in exploratory analyses. Higher genetically proxied circulating PD-L1 was inversely associated with broadly defined myocarditis in UKB-PPP (odds ratio [OR] 0.834, 95% confidence interval [CI] 0.698-0.995; P = .0441), and the independent INTERVAL analysis yielded a concordant inverse estimate (OR 0.619, 95% CI: 0.434-0.883; P = .0083); no clear association was observed for PD-1. The MR-RAPS estimate retained the inverse direction; estimates against the independent broadly defined myocarditis dataset were also inverse, and supportive meta-analyses across protein and outcome sources yielded inverse pooled estimates. Reverse MR did not support effects of broadly defined myocarditis liability on circulating PD-1 or PD-L1. Exploratory lipid analyses identified nominal associations requiring confirmation. Higher genetically proxied circulating PD-L1 may be associated with a lower risk of broadly defined myocarditis, supporting further investigation of PD-L1-related immune regulation. These findings do not directly estimate the effects of pharmacologic PD-1/PD-L1 blockade. The lipid findings are hypothesis-generating.

Myocarditis↗

PubMed2023

Evaluating the impact of modeling choices on the performance of integrated genetic and clinical models.

The value of genetic information for improving the performance of clinical risk prediction models has yielded variable conclusions. Many methodological decisions have the potential to contribute to differential results across studies. Here, we performed multiple modeling experiments integrating clinical and demographic data from electronic health records (EHR) and genetic data to understand which decision points may affect performance. Clinical data in the form of structured diagnostic codes, medications, procedural codes, and demographics were extracted from two large independent health systems and polygenic risk scores (PRS) were generated across all patients with genetic data in the corresponding biobanks. Crohn's disease was used as the model phenotype based on its substantial genetic component, established EHR-based definition, and sufficient prevalence for model training and testing. We investigated the impact of PRS integration method, as well as choices regarding training sample, model complexity, and performance metrics. Overall, our results show that including PRS resulted in higher performance by some metrics but the gain in performance was only robust when combined with demographic data alone. Improvements were inconsistent or negligible after including additional clinical information. The impact of genetic information on performance also varied by PRS integration method, with a small improvement in some cases from combining PRS with the output of a clinical model (late-fusion) compared to its inclusion an additional feature (early-fusion). The effects of other modeling decisions varied between institutions though performance increased with more compute-intensive models such as random forest. This work highlights the importance of considering methodological decision points in interpreting the impact on prediction performance when including PRS information in clinical models.

Preprint↗

PubMed2023

Pervasive correlations between causal disease effects of proximal SNPs vary with functional annotations and implicate stabilizing selection.

The genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a new method, LD SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs, depending on their allele frequencies, LD, and functional annotations; LDSPEC produced robust estimates in simulations across various genetic architectures. We applied LDSPEC to 70 diseases and complex traits from the UK Biobank (average N=306K), meta-analyzing results across diseases/traits. We detected significantly nonzero effect correlations for proximal SNP pairs (e.g., -0.37±0.09 for low-frequency positive-LD 0-100bp SNP pairs) that decayed with distance (e.g., -0.07±0.01 for low-frequency positive-LD 1-10kb), varied with allele frequency (e.g., -0.15±0.04 for common positive-LD 0-100bp), and varied with LD between SNPs (e.g., +0.12±0.05 for common negative-LD 0-100bp) (because we consider derived alleles, positive-LD and negative-LD SNP pairs may yield very different results). We further determined that SNP pairs with shared functions had stronger effect correlations that spanned longer genomic distances, e.g., -0.37±0.08 for low-frequency positive-LD same-gene promoter SNP pairs (average genomic distance of 47kb (due to alternative splicing)) and -0.32±0.04 for low-frequency positive-LD H3K27ac 0-1kb SNP pairs. Consequently, SNP-heritability estimates were substantially smaller than estimates of the sum of causal effect size variances across all SNPs (ratio of 0.87±0.02 across diseases/traits), particularly for certain functional annotations (e.g., 0.78±0.01 for common Super enhancer SNPs)-even though these quantities are widely assumed to be equal. We recapitulated our findings via forward simulations with an evolutionary model involving stabilizing selection, implicating the action of linkage masking, whereby haplotypes containing linked SNPs with opposite effects on disease have reduced effects on fitness and escape negative selection.

Journal Article↗

PubMed2025

Identifying independent causal cell types for human diseases and risk variants.

The SNP-heritability of human diseases is extremely enriched in candidate regulatory elements (cREs) from disease-relevant cell types. Critical next steps are to understand whether these enrichments are driven by multiple causal cell types and whether individual variants impact disease risk via a single or multiple of cell types. Here, we propose CT-FM and CT-FM-SNP, 2 methods accounting for cREs shared across cell types to identify independent sets of causal cell types for a trait and its candidate causal variants, respectively. We applied CT-FM to 63 GWAS summary statistics (average N = 417K) using 924 cRE annotations, primarily from ENCODE4. CT-FM inferred 79 sets of causal cell types, with corresponding SNP-annotations explaining 39.0 ± 1.8% of trait SNP-heritability. It identified 14 traits with independent causal cell types, uncovering previously unexplored cellular mechanisms in height, schizophrenia and autoimmune diseases. We applied CT-FM-SNP to 39 UK Biobank traits and predicted high-confidence causal cell types for 3,091 candidate causal non-coding SNPs-trait pairs. Our results suggest that most SNPs affect a phenotype via a single set of cell types, whereas pleiotropic SNPs might target different cell types depending on the phenotype context. Altogether, CT-FM and CT-FM-SNP shed light on how genetic variants act collectively and individually at the cellular level to affect disease risk.

Journal Article↗

PubMed2025

Automated Deep Learning-Based Detection of Early Atherosclerotic Plaques in Carotid Ultrasound Imaging.

BACKGROUND: Carotid plaque presence is associated with cardiovascular risk, even among asymptomatic individuals. While deep learning has shown promise for carotid plaque phenotyping in patients with advanced atherosclerosis, its application in population-based settings of asymptomatic individuals remains unexplored. METHODS: We developed a YOLOv8-based model for plaque detection using carotid ultrasound images from 19,499 participants of the population-based UK Biobank (UKB) and fine-tuned it for external validation in the BiDirect study (N = 2,105). Cox regression was used to estimate the impact of plaque presence and count on major cardiovascular events. To explore the genetic architecture of carotid atherosclerosis, we conducted a genome-wide association study (GWAS) meta-analysis of the UKB and CHARGE cohorts. Mendelian randomization (MR) assessed the effect of genetic predisposition to vascular risk factors on carotid atherosclerosis. RESULTS: Our model demonstrated high performance with accuracy, sensitivity, and specificity exceeding 85%, enabling identification of carotid plaques in 45% of the UKB population (aged 47-83 years). In the external BiDirect cohort, a fine-tuned model achieved 86% accuracy, 78% sensitivity, and 90% specificity. Plaque presence and count were associated with risk of major adverse cardiovascular events (MACE) over a follow-up of up to seven years, improving risk reclassification beyond the Pooled Cohort Equations. A GWAS meta-analysis of carotid plaques uncovered two novel genomic loci, with downstream analyses implicating targets of investigational drugs in advanced clinical development. Observational and MR analyses showed associations between smoking, LDL cholesterol, hypertension, and odds of carotid atherosclerosis. CONCLUSIONS: Our model offers a scalable solution for early carotid plaque detection, potentially enabling automated screening in asymptomatic individuals and improving plaque phenotyping in population-based cohorts. This approach could advance large-scale atherosclerosis research.

atherosclerosis↗

PubMed2025

Comorbidity alters the genetic relationship between anxiety disorders and major depression.

BACKGROUND: Comorbid anxiety disorders (ANX) and major depression (MD) have worse clinical outcomes than either disorder alone. Analysis of genomic data based on comorbidity status may reveal more precise biological pathways and causal relationships with potential clinical implications. We investigated the genetic relationship between ANX and MD with and without mutual comorbidity. METHODS: We leveraged data from UK Biobank to perform disorder-specific genome-wide association studies (GWAS) of ANX-only (n=189,422) and MD-only (n=194,339) and generate polygenic risk scores (PRS). The Norwegian Mother, Father, and Child Cohort (MoBa, n = 130,992) served to test the associations of PRS with diagnoses. MD and ANX GWAS, including comorbidities (MD-comorbid and ANX-comorbid), were used for comparison. Genetic correlations were compared by comorbidity status, and Mendelian randomization was employed to assess causal relationships. RESULTS: The MD-only PRS showed a stronger association with MD-only compared to ANX-only cases (Z=3.74; Padjusted=0.002); however, MD-comorbid PRS did not show a significant difference (Z=2.71; Padjusted=0.08). The genetic correlation between ANX-only and MD-only was 0.53, lower than between ANX-comorbid and MD-comorbid (0.90). ANX-only showed a causal relationship with MD-only (Padjusted=0.015), but not vice versa, and contrasted the bidirectional causal relationship (Padjusted=2.9e-12, and Padjusted=9.3e-06) when comorbidity was included. Gene sets of MD-comorbid, ANX-comorbid, and MD-only, but not of ANX-only, were enriched for immune regulation pathways such as interleukin production. CONCLUSIONS: ANX and MD show more distinct genetics when comorbid cases are excluded, and ANX may be causal for MD. Disorder-specific genetic studies help uncover more relevant biological mechanisms and guide tailored clinical interventions.

Journal Article↗

PubMed2025

Matching Heterogeneous Cohorts by Projected Principal Components Reveals Two Novel Alzheimer's Disease-Associated Genes in the Hispanic Population.

Alzheimer's disease (AD) is the most common form of dementia in elderly, affecting 6.9 million individuals in the United States. Some studies have suggested the prevalence of AD is greater in individuals who self-identify as Hispanic. Focused results are relevant for personalized and equitable clinical interventions. Ethnicity as a stratifying tool in genetic studies is often accompanied by genomic inflation due to heterogeneity. In this study, we report GWAS and meta-analyses conducted among NIAGADS subjects who self-identified as Hispanic and All of Us (AoU) sub-cohorts matched to that cohort, using projected genetically-derived principal components, with and without age and sex. In Hispanic NIAGADS subjects, we identified a common variant in PIEZO2 that was protective for AD with a p-value just beyond genome-wide significance (p = 5.4*10-8). Meta-analyses with genetically-matched AoU participants yielded three (two novel) genome-wide significant AD-associated loci based on rare lead variants: rs374043832 (RGS6/PSEN1), rs192423465 (ASPSCR1), and rs935208076 (GDAP2), which were also nominally significant in AoU sub-cohorts. We thus demonstrate an efficient way to select subjects from large heterogeneous biobank cohorts who are genetically similar to a smaller disease-specific cohort, yielding novel disease-relevant findings.

Journal Article↗

PubMed2025

Gene dosage architecture across complex traits.

UNLABELLED: Copy number variants (CNVs) have large effects on complex traits, but they are rare and remain challenging to study. As a result, our understanding of biological functions linking gene dosage to complex traits remains limited, and whether these functions sensitive to gene dosage are similar to those underlying the effects of rare single nucleotide variants (SNVs) and common variants remains unknown. METHODS: We developed FunBurd, a functional burden analysis, to test the association of CNVs aggregated within functional gene sets. We applied this approach in 500,000 individuals from the UK Biobank to associate 43 complex traits with CNVs disrupting 172 gene sets across tissues and cell types. We compared CNV findings with those from common variants and LoF (Loss of Function) SNVs in the same cohort using the same functional gene sets. RESULTS: All 43 traits showed FDR significant associations with CNVs. Brain tissue and neuronal cell-types showed the highest levels of pleiotropy. Most of the functional gene set associations could, in part, be explained by genetic constraint, except for brain related processes. Shared genetic contributions between pairs of traits were concordant across types of variants, but on average 2-fold higher, for rare CNVs and SNVs compared to common variants.Functional enrichment across traits found limited overlap between CNVs and common variants. Moreover, the effects of deletions and duplications were negatively correlated for most traits.In conclusion, we present new methods to separate the contributions of genetic constraint and gene function to the associations of CNVs with complex traits. Overall, the functional convergence between different types of variants -even between deletions and duplications-remains limited.

Journal Article↗

PubMed2025

Associations of Genetic Liability to Six Psychiatric Disorders With Cardiometabolic Diseases.

IMPORTANCE: Individuals with psychiatric disorders have increased risk of cardiometabolic diseases (CMDs). Evaluating how psychiatric genetic liability relates to CMD may clarify mechanisms. OBJECTIVE: Identify genetic overlap between psychiatric disorders and CMDs independent of cross-disorder pleiotropy, BMI, and smoking. DESIGN SETTING AND PARTICIPANTS: Three Northern European cohorts (the Swedish Twin Registry, the Estonian Biobank, and the Norwegian Mother, Father and Child Cohort Study [MoBa]) totaling 355,159 individuals. Associations with CMDs were estimated as adjusted odds ratios (AORs) from logistic models mutually adjusted for all psychiatric PRSs and in models additionally adjusting for body mass index (BMI) and smoking. Cohort-specific AORs were pooled by inverse-variance weighting. MAIN OUTCOMES AND MEASURES: Exposures were PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), anxiety disorder, posttraumatic stress disorder (PTSD), bipolar disorder, and schizophrenia. Outcomes were diagnoses of CMDs (hyperlipidemia, obesity, type 2 diabetes, hypertensive diseases, arteriosclerosis, ischemic heart disease, heart failure, thromboembolic disease, cerebrovascular disease, and arrhythmias), ascertained from electronic health records. RESULTS: The MDD PRS was associated with increased risk of all CMDs across analyses (AORs ranged from 1.13 [95% CI, 1.10-1.15] for heart failure to 1.02 [95% CI, 1.00-1.05] for arrhythmias). The ADHD PRS was associated with increased risk of all CMDs (AOR ranged from 1.11 [95% CI, 1.09-1.12] for obesity to 1.02 [95% CI, 1.01-1.03] for hyperlipidemia), however associations where attenuated when adjusting for BMI and smoking (lifestyle adjusted AOR for obesity: 1.03 [95% CI, 1.02-1.05]). When not mutually adjusting for all psychiatric PRSs, anxiety disorder and PTSD PRSs were associated with all CMDs; these associations diminished after adjustment. The bipolar and schizophrenia PRSs were inversely associated with most CMDs (AOR for schizophrenia PRS and obesity, 0.93 [95% CI, 0.92-0.94]). CONCLUSIONS AND RELEVANCE: Associations between psychiatric PRSs and CMDs diverged: ADHD, MDD, anxiety disorder, and PTSD PRSs were positively associated with CMDs, whereas bipolar and schizophrenia PRSs were inversely associated. Genetic liability to MDD showed robust associations with CMDs independent of cross-disorder pleiotropy, BMI, and smoking status, whereas associations between the ADHD PRS and CMDs were largely attenuated after adjustment for BMI and smoking.

Journal Article↗