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PubMed2026

Nonuniform Association of Genetic Risk Scores for Intraocular Pressure.

IMPORTANCE: Elevated intraocular pressure (IOP) is a risk factor for primary open-angle glaucoma, and genetic risk scores hold promise as a tool for screening for ocular hypertension. However, genetic risk scores for IOP have a nonuniform association across the range of IOP, which reduces their accuracy. OBJECTIVE: To test the hypothesis that nonuniform behavior of genetic risk scores for IOP is associated with a specific type of genetic interaction. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional, post hoc genetic association studies were performed using linear and quantile regression in a sample of UK Biobank participants. Data were analyzed from January to September 2025. EXPOSURES: Ninety-eight genetic variants associated with IOP. MAIN OUTCOMES AND MEASURES: Tests were carried out for 98 genetic variants associated with IOP (P < 5.0 ×10-8) to examine (1) dominant or recessive genetic effects, (2) genotype × genotype interactions, (3) genotype × age interactions, and (4) genotype × sex interactions. RESULTS: A total of 98 235 participants (mean [SD] age, 58.1 [7.9] years; 52 168 female [53.1%]) were included in this analysis. More variants exhibited genotype × age interactions than expected by chance (14 of the 98 variants associated with IOP had at least nominal evidence of an interaction with age; P = 3.76 ×10-4). For 12 of these 14 variants, age increased rather than decreased the magnitude of the IOP vs genotype association. However, integrating age interactions into the genetic risk score construction process did not yield improved accuracy (incremental noninteraction model, R2 = 4.05; 95% CI, 3.82-4.31 and interaction model, R2 = 4.04; 95% CI, 3.80-4.27). There was little support for other types of genetic interaction. CONCLUSIONS AND RELEVANCE: In the current work, findings show minimal evidence that nonadditive allelic effects, genotype × genotype interactions, and genotype × sex interactions contributed to the nonuniform association of genetic variants with IOP across quantiles of IOP. Although a genetic risk score for IOP was more accurate in older vs younger individuals, efforts to account for genotype × age interactions in genetic risk score construction did not improve accuracy. These findings suggest other factors, such as gene-environment interactions, contribute to the nonuniform relationship of genetic variants with IOP.

Humans↗

PubMed2026

Genetic risk scores, perceived neighborhood disorder, and sleep duration.

STUDY OBJECTIVES: Most studies of neighborhood context and sleep health emphasize direct effects and fail to account for the role of genetics. In this paper, we draw on the socioecological model to examine the interplay of genetics, neighborhood context, and sleep health. We specifically examine the independent and joint effects of genetic risk scores (GRS) and perceived neighborhood disorder on sleep duration. METHODS: We combine genomic and cross-sectional survey data from the All of Us Research Program, a non-probability sample of 22 575 adults of European ancestry living in the United States. We use the sleep duration-increasing risk allele count for 78 genome-wide single nucleotide polymorphisms (SNPs) to construct weighted genetic risk scores. Our analyses include an index of perceived neighborhood disorder and an objective measure of sleep duration based on wrist actigraphy. RESULTS: Genetic risk scores are inversely associated with neighborhood disorder, positively associated with continuous sleep duration, and inversely associated with the odds of short sleep. Neighborhood disorder is inversely associated with continuous sleep duration and positively associated with the odds of short and long sleep. The association between genetic risk scores and sleep duration (continuous and categorical) is invariant across levels of neighborhood disorder. CONCLUSIONS: Our analyses confirm the independent direct effects of genetic risk scores and neighborhood disorder on sleep duration. Our findings extend the socioecological model by assessing the role of genetics in the study of neighborhood context and sleep health. Although we observed a gene-environment correlation between genetic risk scores and perceived neighborhood disorder, there was little indication of genetic confounding and no evidence of gene-environment interaction.

Humans↗

PubMed2005

Generating genetic risk scores from intermediate phenotypes for use in association studies of clinically significant endpoints.

While previous results of genetic association studies for common, complex diseases (eg., coronary artery disease, CAD) have been disappointing, examination of multiple related genes within a physiologic pathway may provide improved resolution. This paper describes a method of calculating a genetic risk score (GRS) for a clinical endpoint by integrating data from many candidate genes and multiple intermediate phenotypes (IPs). First, the association of all single nucleotide polymorphisms (SNPs) to an IP is determined and regression beta-coefficients are used to calculate an IP-specific GRS for each individual, repeating this analysis for every IP. Next, the IPs are assessed by a second regression as predictors of the clinical endpoint. Each IP's individual GRS is then weighted by the regression beta-coefficients from the second step, creating a single, composite GRS. As an example, 3,172 patients undergoing coronary angiography were evaluated for 3 SNPs from the cholesterol metabolism pathway. Although these data provide only a preliminary example, the GRS method detected significant differences in CAD by GRS group, whereas separate genotypes did not. These results illustrate the potential of the GRS methodology for multigenic risk evaluation and suggest that such approaches deserve further examination in common, complex diseases such as CAD.

Coronary Disease↗

PubMed2025

Interaction of genetics risk score and fatty acids quality indices on healthy and unhealthy obesity phenotype.

BACKGROUND: The growth in obesity and rates of abdominal obesity in developing countries is due to the dietary transition, meaning a shift from traditional, fiber-rich diets to Westernized diets high in processed foods, sugars, and unhealthy fats. Environmental changes, such as improving the quality of dietary fat consumed, may be useful in preventing or mitigating the obesity or unhealthy obesity phenotype in individuals with a genetic predisposition, although this has not yet been confirmed. Therefore, in this study, we investigated how dietary fat quality indices with metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUO) based on the Karelis criterion interact with genetic susceptibility in Iranian female adults. METHODS: In the current cross-sectional study, 279 women with overweight or obesity participated. Dietary intake was assessed using a 147-item food frequency questionnaire and dietary fat quality was assessed using the cholesterol-saturated fat index (CSI) and the ratio of omega-6/omega-3 (N6/N3) essential fatty acids. Three single nucleotide polymorphisms-MC4R (rs17782313), CAV-1 (rs3807992), and Cry-1(rs2287161) were genotyped by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique and were combined to produce the genetic risk score (GRS). Body composition was evaluated using a multi-frequency bioelectrical impedance analyzer. Participants were divided into MHO or MUO phenotypes after the metabolic risk assessment based on the Karelis criteria. RESULTS: We found significant interactions between GRS and N6/N3 in the adjusted model controlling for confounding factors (age, body mass index, energy, and physical activity) (β = 2.26, 95% CI: 0.008 to 4.52, P = 0.049). In addition, we discovered marginally significant interactions between GRS and N6/N3 in crude (β = 1.92, 95% CI: -0.06 to 3.91, P = 0.058) and adjusted (age and energy) (β = 2.00, 95% CI: -0.05 to 4.05, P = 0.057) models on the MUH obesity phenotype. However, no significant interactions between GRS and CSI were shown in both crude and adjusted models. CONCLUSION: This study highlights the importance of personalized nutrition and recommends further study of widely varying fat intake based on the findings on gene-N6/N3 PUFA interactions.

Humans↗

PubMed1984

Easy calculations of lod scores and genetic risks on small computers.

A computer program that calculates lod scores and genetic risks for a wide variety of both qualitative and quantitative genetic traits is discussed. An illustration is given of the joint use of a genetic marker, affection status, and quantitative information in counseling situations regarding Duchenne muscular dystrophy.

Computers↗

PubMed2025

A comprehensive evaluation of candidate genetic polymorphisms in a large histologically characterized MASLD cohort using a novel framework.

BACKGROUND: There is a substantial heritable component to metabolic dysfunction-associated steatotic liver disease (MASLD), and several genetic variants that promote MASLD development or associate with its severity have been reported. These associations vary in terms of their effect size and degree of replication. METHODS: We developed a framework to classify previously identified MASLD genetic polymorphisms into 4 tiers based on effect size and extent of replication in the literature. We tested the association between "tier 1" single-nucleotide polymorphisms (OR ≥1.5, replicated in >2 independent studies) and biopsy measures of MASLD severity in a large, well-characterized histologic cohort of MASLD patients (n=3094). RESULTS: Across 19 "tier 1" variants reflecting 11 genetic loci, only those in the PNPLA3-SAMM50-PARVB locus showed significant associations with biopsy-proven fibrosis severity and NAFLD activity score; the highest risk was for the rs738409 p.I148M variant in PNPLA3. A genetic risk score based on "tier 1" variants, as well as a previously developed genetic risk score based on variants in PNPLA3, TM6SF2, and HSD17B13, were both associated with fibrosis and NAFLD activity score, but these results were driven entirely by PNPLA3 rs738409. CONCLUSIONS: Our study provides a framework to prioritize evaluation of genetic polymorphisms for future replication efforts and demonstrates that in a large case-only cohort, histologic severity of MASLD is only robustly associated with the presence of variation in PNPLA3 among known candidate genes. These findings may have implications for patient risk stratification based on the presence of PNPLA3 rs738409.

Humans↗

PubMed2026

Decoding Primary Open-Angle Glaucoma: A Multi-Omics Approach to Identify Druggable Effector Genes.

PURPOSE: Genomewide association studies (GWAS) have identified numerous primary open angle glaucoma (POAG) risk loci, yet most reside in non-coding regions with unclear function. Mapping these loci to effector genes can elucidate disease mechanisms, identify functionally conserved variants, improve cross-ancestry risk prediction by reducing population-specific noise, and uncover shared therapeutic targets. METHODS: Here, we integrate European POAG GWAS with six types of multi-omics molecular Quantitative Trait Locis (xQTLs) using multi-trait colocalization to identify candidate effector variants and evaluate their cross-population relevance using genetic risk score (GRS) analysis, and their therapeutic potential through drug target prioritization. RESULTS: We identified 25 POAG effector variants colocalized with at least one xQTLs. In non-European populations, effector variants showed stronger effect size correlations with Europeans than non-colocalized variants (Pearson r2 = African 0.85 vs. 0.71; East Asian 0.81 vs. 0.69; and Latin American 0.91 vs. 0.75). Effector variants also had smaller allele frequency variations across populations (average interquartile range [IQR] = 0.15 vs. 0.20). The genetic risk score based on effector variants performed comparably to the genome-wide significant single-nucleotide polymorphism (SNP)-based GRS in non-European populations. Drug prioritization identified zinc, copper, sunitinib, probucol, and astemizole as potential common therapeutic agents for POAG and its subtypes. CONCLUSIONS: Our findings offer deeper insight into the molecular mechanisms underlying glaucoma and effector variants for developing more robust GRS models and broadly effective therapeutic strategies for POAG.

Humans↗

PubMed2026

Association of PCSK9 and CCL22 gene polymorphisms with myocardial infarction in a South Indian population.

Myocardial infarction (MI) remains a major global cause of morbidity and mortality, with a particularly high burden among individuals with type 2 diabetes mellitus (T2DM). Host genetic factors play a significant role in modulating individual susceptibility to MI by influencing lipid metabolism and immune-mediated inflammatory pathways. The proprotein convertase subtilisin/kexin type 9 (PCSK9) gene is a key regulator of cholesterol homeostasis, while C-C motif chemokine ligand 22 (CCL22) is involved in immune cell recruitment and vascular inflammation. In this study, we investigated the association of PCSK9 rs505151 and rs11591147 and CCL22 rs4359426 polymorphisms with MI risk in a South Indian population. This case-control study included 400 participants categorized into controls (n = 100), MI (n = 100), T2DM (n = 100), and MI with T2DM (n = 100). Significant differences in clinical and biochemical parameters, including lipid indices and cardiometabolic risk markers, were observed between groups (p < 0.05). Genetic analysis revealed a significant association between the PCSK9 rs505151 variant and MI susceptibility across allelic and genotypic distributions, with significant effects under dominant and recessive inheritance models. Multivariable logistic regression confirmed that the rs505151 risk genotype was independently associated with MI after adjustment for age, sex, body mass index, and smoking status. In contrast, PCSK9 rs11591147 was rare and showed no significant association. The CCL22 rs4359426 polymorphism showed limited evidence of association with MI, with a significant effect observed only under the dominant inheritance model. Furthermore, combined analysis using a genetic risk score suggested that cumulative genetic burden involving PCSK9 and CCL22 variants was associated with an increased risk of MI. Overall, our findings suggest that genetic variation in lipid-regulatory and immune-related pathways may contribute to MI susceptibility in South Indians. Further studies are warranted to validate these associations and clarify their biological and clinical relevance.

Humans↗

PubMed2026

Waist-to-height ratio as a practical indicator for screening pediatric metabolic dysfunction-associated steatotic liver disease in diverse populations and genetic backgrounds.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading chronic liver disease in children and adolescents; this parallels the global obesity epidemic. The contribution of genetic susceptibility to pediatric MASLD, and its interaction with anthropometric and biochemical indices used for non-invasive screening remains poorly understood. We aimed to evaluate waist-to-height ratio (WHtR) as a simple, equitable, and scalable tool for early identification of pediatric MASLD and relate this to genetic risk. METHODS: We combined school-based data from 1010 Chinese children with analyses of the Global Burden of Disease, the 1000 Genomes Project, and the US National Health and Nutrition Examination Survey (NHANES). Thirteen MASLD-related single-nucleotide polymorphisms (SNPs) were genotyped to construct a genetic risk score (GRS). We examined global epidemiological patterns, quantified inter-population allele divergence, and assessed how GRS modifies cutoffs and performance of nine anthropometric and biochemical indices. RESULTS: Genetic analysis revealed minimal frequency divergence across most ancestries (mean Fixation index < 0.05), except for the African ancestry where there was moderate divergence. Higher GRS were associated with lower cutoffs across indices. When GRS Z-score increased from -3 to 3, visceral adiposity index showed the sharpest changes (Z-score decreased from 1.5 to -1.8), while BFP (1.2 to 0.1) and WHtR (1.5 to 0.1) showed gradual change. Furthermore, incorporating GRS into the base anthropometric models yielded only marginal improvements in overall screening performance [area under the receiver operating characteristic curve (AUC) and Youden Index]. Validation in NHANES showed WHtR ≥ 0.48 retained high discrimination (AUC > 0.87) across most genetic variants. CONCLUSIONS: This study suggests that WHtR is a consistent and practical tool for screening pediatric patients with MASLD across diverse populations. While genetic variation may influence optimal thresholds, WHtR ≥ 0.48 appears broadly applicable, supporting its potential use as a frontline screening metric in diverse settings.

Humans↗

PubMed2026

B cell pathways implicate shared genetic architecture between schizophrenia and immune-mediated diseases.

BACKGROUND: Schizophrenia and immune-mediated diseases are globally prevalent and highly heritable conditions that frequently co-occur, posing major public health burdens. However, their shared genetic architecture remains poorly understood. METHODS: We applied the bivariate causal mixture model (MiXeR) to investigate the polygenic overlap between schizophrenia and eight common immune-mediated diseases, using genome-wide association study summary statistics comprising 2,489 to 67,323 cases and 9,066 to 497,622 controls. Shared loci were identified through conditional/conjunctional false discovery rate (cond/conjFDR), local genetic correlation (LAVA), and colocalization analyses. Subsequently, gene mapping, functional annotation, expression-trait association, and drug-gene interaction analyses were performed to explore shared genes and enriched pathways, and genetic risk scores (GRS) from the UK Biobank were used to validate the findings. RESULTS: MiXeR estimated substantial polygenic overlap between schizophrenia and immune-mediated diseases, and conjFDR identified 133 shared loci, with eight prioritized through local genetic correlation and colocalization signals. These eight loci were mapped to 85 protein-coding genes enriched in pathways essential for B cell function. Among them, S-PrediXcan analyses identified 14 genes whose expression in brain tissues or blood was associated with both diseases. These genes also interact with immunomodulatory or antihypertensive drugs. Additionally, 11 of the 14 genes were linked to innate immunity and/or cognitive traits. Using UK Biobank data, we further confirmed that overall, shared gene, and B cell activation and receptor signaling pathway–specific genetic risk for schizophrenia is associated with immune-mediated disease susceptibility. CONCLUSIONS: These findings underscore the shared genetic architecture of schizophrenia and immune-mediated diseases, advancing insights at the interface of psychiatric genetics and immunology.

Schizophrenia↗

PubMed2026

GWAS Meta-analysis Identifies Novel Associated Loci and Points to Causal Tissues in Central Serous Chorioretinopathy.

OBJECTIVE: To define CSC genetic architecture and identify implicated ocular tissues, cell types, genes, and circulating proteins. DATA SOURCES: Genome-wide data were assembled from FinnGen, All of Us, Mass General Brigham Biobank, Million Veteran Program, and a Dutch chronic CSC cohort. Serum protein quantitative trait loci, human single-cell ocular atlases, and UK Biobank macular optical coherence tomography (OCT) imaging were used for downstream analyses. STUDY SELECTION: Five European-ancestry cohorts with genome-wide data and cohort-specific CSC case-control definitions were included, comprising 2,584 cases and 1,044,455 controls. Variants present in at least 2 cohorts were meta-analyzed. DATA EXTRACTION AND SYNTHESIS: Cohort-level GWASs were adjusted for age, age squared, sex, genotyping array or batch, and 10 genetic principal components, then combined using fixed-effects inverse-variance meta-analysis. Post-GWAS analyses included gene prioritization, colocalization, Mendelian randomization, single-cell disease-relevance scoring, and testing of a CSC genetic risk score in UK Biobank OCT images. MAIN OUTCOMES AND MEASURES: Genome-wide significant CSC loci, effector genes and proteins, tissue and cell-type enrichment, and CSC-relevant OCT abnormalities. RESULTS: Across 11,068,938 variants, 10 loci reached genome-wide significance (P < 5 × 10-8), including 3 novel loci near TGFB1, LINC00551, and LOC105375630 and 7 replicated loci near CFH, CD46, NOTCH4, PREX1, PTPRB, GATA5, and TNFRSF10A. Integrative analyses prioritized 10 candidate effector genes. Colocalization and Mendelian randomization implicated circulating TNFRSF10A, TGFB1, and CASP10 levels. Single-cell analyses localized genetic risk to sclera (P = 2.0 × 10-4) and vascular endothelial cells (P = 4.0 × 10-4), with fibroblast enrichment. In UK Biobank, OCT abnormalities were more frequent in the top vs bottom 1% of CSC genetic risk (18 of 109 [16.5%] vs 8 of 134 [6.0%]; odds ratio, 4.05; 95% CI, 1.65-10.87; P = .002). CONCLUSIONS AND RELEVANCE: In this GWAS meta-analysis, CSC susceptibility localized predominantly to scleral and vascular biology rather than primary retinal pigment epithelial dysfunction. These findings support CSC as a sclerovascular disorder and nominate complement regulation, endothelial signaling, and extracellular matrix pathways for future study.

Journal Article↗

PubMed2006

A direct assessment of genetic contribution to the incidence of coronary infarct in the general population Greek EPIC cohort.

To estimate the fraction of the incidence of coronary infarct attributable to the combined action of common genetic polymorphisms likely to be related to this condition, we conducted a case-control study nested within the Greek component of the European Prospective Investigation into Cancer and Nutrition. A total of 202 cases with a new, medically confirmed coronary infarct and 197 controls who had not developed an infarct by the time the corresponding case was diagnosed, were identified. A simple a priori score, relying on a total of 11 genetic polymorphisms was developed. Each polymorphism contributed 1 unit if the subject was homozygous for the high-risk allele, 0.5 units if the subject was heterozygous and 0 units if the subject was homozygous for the low-risk allele. Cases were over-represented in the presumed high genetic risk score values (chi square for trend = 10.18; p = 0.0014). The odds ratio to develop coronary infarct was 1.55 (95% confidence interval: 1.02-2.37) for score > or = 3.0, and 2.02 (1.31-3.11) for score > or = 3.5. In both instances the population fraction of the disease attributable to genetic predisposition exceeded 22%. Assuming a prior probability of at least 0.10 for the score to be predictive of coronary infarct risk, our findings are more likely than not to be truly positive. Our results, based on a simple score integrating the additive impact of 11 genetic polymorphisms, indicate that genetic predisposition accounts for a considerable fraction of the incidence of coronary infarct in the community.

Adult↗

PubMed2025

Plasma inflammatory proteome profiles identify MASLD among children with overweight or obesity.

BACKGROUND & AIMS: Pediatric metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly prevalent among children with overweight or obesity, yet its early diagnosis remains a major clinical challenge. This study aimed to identify circulating inflammatory proteins associated with MASLD and to develop a proteomic risk score (ProScore) to improve diagnostic accuracy. METHODS: In this cross-sectional study of 161 children (median age 8.5 years) with overweight or obesity, MASLD was assessed by vibration-controlled transient elastography, with 42 cases identified. Plasma concentrations of 92 inflammation-related proteins were quantified using a high-throughput proximity extension assay. The ProScore was compared with eleven conventional anthropometric/metabolic indices (WHtR, METS-IR, SPISE, PNFI, VAI, LAP, TyG, TyG-ALT, TyG-WC, TyG-WHtR, and TyG-BMI) and a genetic risk score (GRS). Six machine learning algorithms were employed and diagnostic performance was assessed using area under the curve (AUC) with fivefold cross-validation. RESULTS: Fifteen proteins were significantly associated with MASLD. A six-protein panel (FGF-21, CDCP1, CD244, OPG, Flt3L, MCP-1) achieved the highest diagnostic accuracy (AUC = 0.84), exceeding that of all conventional indices (AUC = 0.65-0.78; all P < 0.05). ProScore performance remained robust in school-based validation (AUC = 0.83), with no substantial improvement when combined with conventional indices. Diagnostic accuracy was higher in children with lower GRS (AUC = 0.92) than in those with higher GRS (AUC = 0.80; P = 0.003). CONCLUSIONS: A proteomic signature of systemic inflammation provides accurate, non-invasive identification of MASLD in at-risk children, outperforming conventional metabolic and genetic tools, and may have utility in clinical and public health settings.

Humans↗

PubMed2025

Assessing individual genetic susceptibility to metabolic syndrome: interpretable machine learning method.

BACKGROUND: Genome-wide association studies have provided profound insights into the genetic aetiology of metabolic syndrome (MetS). However, there is a lack of machine-learning (ML)-based predictive models to assess individual genetic susceptibility to MetS. This study utilized single-nucleotide polymorphisms (SNPs) as variables and employed ML-based genetic risk score (GRS) models to predict the occurrence of MetS, bringing it closer to clinical application. METHODS: Feature selection was performed using Least Absolute Shrinkage and Selection Operator. Six ML algorithms were employed to construct GRS models. A fivefold cross-validation was utilized to aid in the internal validation of models. The receiver operating characteristic (ROC) curve was used to select the better-performing GRS model. The SHapley Additive exPlanations (SHAP) was then applied to interpret the model. After extracting GRS, stratified analysis of BMI, age and gender was performed. Finally, these conventional risk factors and GRS were integrated through multivariate logistic regression to establish a combined model. RESULTS: A total of 17 SNPs were selected for analysis. Among the GRS models, the extreme gradient boosting (XGBoost) model demonstrated superior discriminative performance (AUC = 0.837). The XGBoost's optimal robustness was also validated through five-fold cross-validation (mean ROC-AUC = 0.706). The XGBoost-based SHAP algorithm not only elucidated the global effects of 17 SNPs across all samples, but also described the interaction between SNPs, providing a visual representation of how SNPs impact the prediction of MetS in an individual. There was a strong correlation between GRS and MetS risk, particularly observed among young individuals, males and overweight individuals. Furthermore, the model combining conventional risk factors and GRS exhibited excellent discriminative performance (AUC = 0.962) and outstanding robustness (mean ROC-AUC = 0.959). CONCLUSION: This study established a reliable XGBoost-based GRS model and a GRS prediction platform (https://metabolicsyndromeapps.shinyapps.io/geneticriskscore/) to assess individual genetic susceptibility to MetS. This model has high interpretability and can provide personalized reference for determining the necessity of primary prevention measures for MetS. Additionally, there may be interactions between traditional risk factors and GRS, and the integration of both in a comprehensive model is useful in the prediction of MetS occurrence.

Humans↗

PubMed2026

A Comprehensive Assessment of the Shared Genetic Architecture between Myopia and Open-Angle Glaucoma.

OBJECTIVE: Individuals with high myopia have an increased prevalence of open-angle glaucoma (OAG). We aim to clarify the possibly shared genetic architecture of myopia and OAG, in particular in high myopes with myopic macular degeneration (MMD), where OAG screening is highly challenging. DESIGN: Individual participant data meta-analysis of one-sample Mendelian randomization analyses and pleiotropic analysis under a composite null hypothesis. PARTICIPANTS: A total of 34 825 participants from 6 population-based cohort studies and 1 high myopia case-control study, including 708 OAG and 1953 high-myopia cases. METHODS: First, we calculated and validated genetic risk scores (GRSs) for OAG and myopia in each cohort. We subsequently meta-analyzed linear and logistic regression models for the association of a myopia GRS with OAG, intraocular pressure (IOP), and vertical cup-to-disc ratio (VCDR), and the association of an OAG-GRS with high myopia, axial length, and spherical equivalent. We stratified the analysis of OAG in different stages of axial elongation, and in high myopes with or without MMD. Pleiotropic analysis under a composite null hypothesis was applied to genome-wide association study summary statistics. MAIN OUTCOME MEASURES: Odds ratio (OR) of OAG and high myopia, and mean difference in IOP, VCDR, axial length, and spherical equivalent. RESULTS: One standard deviation (SD) increase in myopia GRS was associated with an OR (95% CI) of 1.18 (1.09, 1.28) for OAG, a beta (95% CI) of 0.04 (0.00, 0.08) mmHg in IOP, and of 0.005 (0.003, 0.007) in VCDR. The OAG-GRS was not significantly associated with high myopia compared to emmetropes, but a 1 SD increase was associated with a beta (95% CI) of 0.05 (0.01, 0.08) mm in axial length and of -0.05 (-0.10, -0.00) diopters in spherical equivalent. One SD increase in OAG-GRS had a substantially larger effect on OAG in high myopes with MMD, with an OR (95% CI) of 3.83 (1.89, 7.78) compared to 1.55 (1.24, 1.94) in emmetropes. Finally, we identified 95 independent pleiotropic single-nucleotide polymorphisms (SNPs). CONCLUSIONS: There is strong evidence for pleiotropy between myopia and OAG. Further research into the biological mechanisms of the identified pleiotropic SNPs is needed. An OAG-GRS might help to clinically estimate OAG risk, in particular in individuals with MMD. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Axial length↗

PubMed2025

Post-traumatic stress disorder and REM-sleep behavior disorder: exploring genetic associations and causal links.

OBJECTIVE: To explore potential genetic and/or causal associations between Post-Traumatic Stress Disorder and neurodegeneration-related isolated/idiopathic rapid-eye-movement sleep behavior disorder. METHODS: We conducted polygenic risk score, genetic correlation, and Mendelian randomization analyses using the latest genome-wide association studies summary statistics and individual genotyping data. Next, a blinded observer examined dopamine transporter imaging binding status-a marker of neurodegeneration-in patients with isolated/idiopathic rapid-eye movement sleep behavior disorder, with (N = 6) and without Post-Traumatic Stress Disorder (N = 32). RESULTS: Polygenic risk scores for Post-Traumatic Stress Disorder were associated with isolated/idiopathic rapid-eye-movement sleep behavior disorder, with each standard deviation increase linked to 14.7% higher odds (odds ratio = 1.15, 95% confidence interval: 1.04 to 1.26, p = 0.005). However, genetic correlation was weak, and Mendelian randomization did not support a potential causal relationship. The proportion of individuals with abnormal dopamine transporter imaging binding status was significantly higher in the Post-Traumatic Stress Disorder group compared to those without the disorder (p=0.01, X2 = 6.62). INTERPRETATION: Polygenic risk scores analysis identified an association between Post-Traumatic Stress Disorder and neurodegeneration-related isolated/idiopathic rapid-eye-movement sleep behavior disorder, consistent with the result from the small exploratory substudy. The lack of strong genetic correlation or causation may reflect limited sample size. Further research with larger and more diverse cohorts is crucial to clarify the genetic, biological and physiological mechanisms underlying this association.

Journal Article↗

PubMed2026

Transcriptome-wide association analysis of Alzheimer's disease: construction and clinical validation of transcriptomic risk scores.

Early identification of individuals at high risk for Alzheimer's disease (AD) is crucial for disease prevention and intervention. This study aims to develop AD-specific transcriptomic risk scores (TRSs) through multi-tissue transcriptome-wide association study (TWAS) and to evaluate its clinical utility in AD diagnosis and risk prediction. Using GWAS summary statistics combined with expression quantitative trait loci (eQTL) data from 14 tissues, a multi-tissue TWAS approach was applied to identify AD-associated genes. Peripheral blood RNA expression data from the ADNI and GEO databases were used to construct the AD-specific TRSs. The associations of TRSs with AD pathological features and cognitive function were assessed in two independent cohorts. Furthermore, the diagnostic performance, differential diagnostic capability, and risk prediction efficiency of TRSs were evaluated. The TWAS identified 131 genes significantly associated with AD. The TRSs were significantly elevated in patients with AD and mild cognitive impairment (MCI) compared to cognitively normal (CN) individuals, and showed significant correlations with AD pathological markers and cognitive performance. When combined with APOE4 status, the TRSs demonstrated robust diagnostic ability for AD and MCI. When combined with age, the TRSs showed good diagnostic performance in distinguishing AD from frontotemporal dementia (FTD) (AUC = 0.86). Additionally, the TRSs effectively predicted the risk of progression to AD in non-AD individuals (HR = 1.74). The AD-specific TRSs developed in this study shows promising clinical utility in AD diagnosis, differential diagnosis, and risk prediction, providing valuable translational medical evidence for early screening and precision prevention of Alzheimer's disease.

Humans↗

PubMed2024

Genetic polymorphisms affecting telomere length and their association with cardiovascular disease in the Heinz-Nixdorf-Recall study.

Short telomeres are associated with cardiovascular disease (CVD). We aimed to investigate, if genetically determined telomere-length effects CVD-risk in the Heinz-Nixdorf-Recall study (HNRS) population. We selected 14 single-nucleotide polymorphisms (SNPs) associated with telomere-length (p<10-8) from the literature and after exclusion 9 SNPs were included in the analyses. Additionally, a genetic risk score (GRS) using these 9 SNPs was calculated. Incident CVD was defined as fatal and non-fatal myocardial infarction, stroke, and coronary death. We included 3874 HNRS participants with available genetic data and had no known history of CVD at baseline. Cox proportional-hazards regression was used to test the association between the SNPs/GRS and incident CVD-risk adjusting for common CVD risk-factors. The analyses were further stratified by CVD risk-factors. During follow-up (12.1±4.31 years), 466 participants experienced CVD-events. No association between SNPs/GRS and CVD was observed in the adjusted analyses. However, the GRS, rs10936599, rs2487999 and rs8105767 increase the CVD-risk in current smoker. Few SNPs (rs10936599, rs2487999, and rs7675998) showed an increased CVD-risk, whereas rs10936599, rs677228 and rs4387287 a decreased CVD-risk, in further strata. The results of our study suggest different effects of SNPs/GRS on CVD-risk depending on the CVD risk-factor strata, highlighting the importance of stratified analyses in CVD risk-factors.

Humans↗