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PubMed2026

Polygenic risk score for neurodevelopmental disorders and cognitive impairment at long-term follow-up of first-episode psychosis.

BACKGROUND: One of the most outstanding contributions to the understanding of the etiopathogenesis of schizophrenia spectrum disorders (SSD) was the neurodevelopmental hypothesis. SSD and neurodevelopmental disorders (NDD) share pathogenetic mechanisms and overlapping clinical and cognitive impairment features. METHODS: We investigated whether polygenic risk scores (PRSs) for NDD are associated with cognitive performance in patients with first-episode psychosis (FEP). The sample comprised 127 patients with FEP who were followed up for a mean of 20.9 years. Cognitive examination was performed using the MoCA test at follow-up. Pearson coefficient correlations and multiple regression analyses were performed to examine the contribution of the three PRSs for rare neurodevelopmental conditions (PRSNDD), attention-deficit hyperactivity disorder (PRSADHD) and autism spectrum disorder (PRSASD) to cognitive impairment after allowing for the effect of covariates. Furthermore, we examined the interconnections between the PRS for NDD and cognitive impairment using network analysis (NA), including core premorbid variables. RESULTS: PRSNDD showed significant associations with impairment on visuospatial/executive, attention, and language MoCA subtests, after allowing for the influence of covariates. PRSNDD and PRSADHD, but not PRSASD, were significantly associated with worse performance on the total MoCA score. Moreover, in the network analysis, the relationships between PRSs for NDD and cognitive impairment were highly interconnected with premorbid variables and PRSs for schizophrenia and educational attainment. CONCLUSIONS: These results provide evidence for a possible direct genetic effect on cognitive performance for the PRS of common genetic variations related to neurodevelopment and attention deficit hyperactivity disorder in patients with FEP.

Cognitive impairment↗

PubMed2026

Cross-Ancestry and Phenome-Wide Associations of Cancer-Specific Polygenic Risk Scores.

PURPOSE: Genome-wide association studies have identified many common variants associated at low effect sizes with various cancers. Summing the effects of these variants into polygenic risk scores (PRS) can improve cancer risk prediction. However, cross-cancer and cross-phenotype pleiotropic associations of cancer-specific PRS are limited. METHODS: Using logistic regression models, we tested the association of 13 cancer-specific PRS with curated phenotypes representing the same 13 cancers and 340 cancer and cardiometabolic phecodes in 560,287 individuals (114,255 African ancestry [AFR] and 446,032 European ancestry [EUR]) from the Million Veteran Program. Models were stratified by ancestry and used age, principal components, and cancer-specific PRS per standard deviation as independent variables, and correction was applied for multiple comparisons. RESULTS: All 13 cancer-specific PRS were significantly associated with their respective cancers among EUR individuals with odds ratios per standard deviation of PRS (odds ratio [OR]) 1.05-1.70. Among AFR individuals, the effect sizes of the cancer PRS were lower, with OR 1.01-1.48, and cancer-specific PRS were significantly associated with their respective cancers for five of 13 cancers (bladder, breast in female patients, colorectal, prostate, and thyroid). In cancer-cancer pleiotropy studies, only the renal cancer-specific PRS was significantly associated with skin cancer (OR = 1.04, P = 4.5 × 10-06) among EUR individuals. PheWAS demonstrated five positive pleotropic associations with cardiometabolic conditions (thyroid cancer PRS with thyroid goiter, oral cancer PRS with diabetes phenotypes, and hypothyroidism) and two negative associations (oral and lung cancer PRS separately with coronary artery disease). CONCLUSION: Cancer PRS have stronger associations per cancer among EUR versus AFR individuals. In contrast to PRS of other chronic diseases, the majority of cancer-related PRS are highly specific and pleiotropic associations with other cancers and cardiometabolic traits are uncommon.

Female↗

PubMed2026

Role of Polygenic Risk Scores in Predicting Cognitive Functioning after Mild Traumatic Brain Injury: A TRACK-TBI Study.

Patients with traumatic brain injury (TBI) and Glasgow Coma Scale scores of 13-15 (historically called mild TBI [mTBI]) commonly experience changes in cognitive functioning, including processing speed, memory, and executive functioning. In a prospective sample (N = 523) of individuals of European descent who had been treated in a U.S. level 1 trauma center for mTBI, we examined the prognostic value of four polygenic risk scores (PRS) for cognitive outcomes at 6-months postinjury. To estimate the impact of mTBI on cognition, primary cognitive outcomes were scaled as z-scores reflecting changes in performance relative to predicted preinjury performance. The PRS examined were previously developed and validated to predict cognition-related outcomes of educational attainment (Education-PRS), intelligence (Intelligence-PRS), and Alzheimer's disease (AD-mild traumatic brain injury (APOE)-PRS and AD + APOE-PRS). Both the Education-PRS and Intelligence-PRS displayed bivariate associations with all four cognitive outcomes (β = 0.19-0.32), whereas neither Alzheimer's disease PRS was significantly associated with any outcome. After controlling for other factors known to predict cognitive outcomes of TBI (e.g., sex, education, mTBI severity defined by a combination of Glasgow Coma Scale scores and the presence/absence of acute intracranial findings on clinical neuroimaging), the Education-PRS and Intelligence-PRS remained independently predictive of verbal episodic memory (β = 0.10-0.16), whereas their associations with processing speed and executive functioning were mostly nonsignificant and were mediated through educational attainment. Looking across primary z-score and secondary raw score outcomes, cognitive outcomes 6 months post-mTBI were good on average, and PRS made small independent contributions to outcome prediction. The mediation model findings may support theories of cognitive reserve, which propose that individuals with stronger preinjury cognitive processing abilities (often estimated by educational history) can better compensate for TBI. Moreover, findings indicate that PRS may contribute modestly to multivariable models predicting cognitive function after TBI.

Humans↗

PubMed2025

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

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

Humans↗

PubMed2025

A multi-ancestry polygenic risk score for Alzheimer disease is associated with cognitive decline, hippocampal atrophy and neuropathological hallmarks in diverse populations.

Alzheimer disease (AD) has a strong genetic basis, yet previously derived polygenic risk scores (PRS) are heavily weighted by the APOE locus and perform inconsistently across diverse ancestries. We developed an APOE-independent multi-ancestry AD PRS using genome-wide association study summary statistics from cohorts in the United States, Europe and East Asia that were applied to European ancestry (EA), African American (AA), Caribbean Hispanic (CH), and East Asian cohorts from the Alzheimer's Disease Genetics Consortium. PRS performance was evaluated in the multi-ancestry Alzheimer's Disease Sequencing Project (ADSP) dataset and validated in several additional multi-ancestry cohorts. The PRS was significantly associated with AD in the ADSP EA, AA, CH, and Native American Hispanic groups with adjusted odds ratios (ORs) between 1.14 and 1.52 per standard deviation of the PRS. PRS performance was validated in the replication cohorts (ORs 1.21-1.65). The PRS was also associated with poorer memory, executive function, and language performance; greater AD-related neuropathological burden (including CERAD, Braak stage, and Thal phase scores); reduced hippocampal volume; lower CSF Aβ42; and elevated total tau and phosphorylated tau (p-tau), with stronger p-tau associations observed in women. Longitudinal analyses revealed that individuals in the highest PRS decile exhibited the steepest cognitive decline, particularly among those who progressed to AD. Our findings demonstrate the utility of an ancestry-aware and APOE-independent PRS for advancing understanding of the genetic basis of AD across diverse populations. Associations observed with early biological and cognitive changes and potential sex-specific differences support the incorporation of a PRS in clinical trials and personalized intervention and prevention strategies.

Journal Article↗

PubMed2025

Polygenic Risk Scores and HLA Class II Variants are Biomarkers of Corticosteroid Response in Childhood Nephrotic Syndrome.

INTRODUCTION: Nephrotic syndrome (NS), a common glomerular disease in children, is classified based on response to corticosteroid therapy as either steroid-sensitive nephrotic syndrome (SSNS), or steroid-resistant nephrotic syndrome (SRNS). However, there are currently no reliable predictors of therapy response at initial clinical presentation. METHODS: We conducted genome-wide association studies, developed polygenic risk scores (PRS) for therapy response and analyzed classical HLA alleles in 1,997 (994 discovery and 1,003 replication/validation cohorts) previously unstudied children with NS and 3,558 ancestry-matched controls. RESULTS: A significant association with HLA loci defined by variants in HLA-DQB1, HLA-DRB1, and HLA-DQA1 were found for SSNS (but not SRNS), along with a second immune-related SSNS locus: CLEC16A. A PRS that discriminates between SSNS and SRNS was validated in two independent cohorts. The HLA haplotype HLA- DRB1*07:01~DQA1*02:01~DQB1*02:02 was associated with ~4 times the risk of developing SSNS. A model incorporating HLA haplotype, PRS score, and age at onset of the disease was the best predictor of steroid responsiveness with an AUC of 0.68-0.70 and an overall classification accuracy of SSNS versus SRNS of 67-71%. CONCLUSIONS: Our findings confirm that SSNS (unlike SRNS) is an immune-mediated HLA-associated disorder. The PRS for therapy response and HLA haplotype can serve as biomarkers and provide a foundation for more accurate diagnoses and tailored and individualized treatment.

HLA haplotype↗

PubMed2026

Kv11.1 (hERG) Protein Interaction Networks Connect Endocytic Trafficking to Polygenic Influences on Cardiac Repolarization.

Polygenic scores (PGS) capture the combined effect of many common genetic variants on quantitative traits and disease risk, yet their functional consequences at the protein level remain poorly defined. Here, we integrated quantitative and interaction proteomics to resolve how polygenic liability for cardiac repolarization manifests in human cells. We studied human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from donors with extreme PGS for QT interval duration, a clinically relevant electrophysiologic trait associated with arrhythmia risk. Global quantitative proteomics revealed increased abundance of mitochondrial proteins in high-PGS cardiomyocytes. To define protein network-level effects on a key repolarizing ion channel, we performed multiplexed affinity purification-mass spectrometry (AP-MS) of Kv11.1. While mitochondrial changes did not directly explain Kv11.1-associated complexes, interactome analysis revealed increased association of Kv11.1 with myosin motor proteins and endosomal recycling machinery in high-PGS cells. These findings suggest altered channel trafficking dynamics of Kv11.1, distinct from the trafficking defects observed in monogenic Kv11.1 variants. Together, these data show that integrating global and interaction proteomics can resolve how polygenic variation reshapes protein networks. Future work using these methods could connect genomic risk to subcellular remodeling and our work provides a generalizable framework to probe the proteomic basis of complex traits. SIGNIFICANCE STATEMENT: Polygenic scores (PGS) predict disease risk, but how biological pathways are influenced by these common variants remains difficult to define. We generated human induced pluripotent stem cells from individuals with extreme high- and low- PGS for QT interval, a key electrocardiographic measure linked to arrhythmia risk. By combining global proteomics and interactomics for a common ion channel involved in regulating the QT interval (Kv11.1) we found potential mechanisms that are influenced by common genetic traits in patients. Our work provides an approach to connect polygenic scores to pathway-level molecular mechanisms in human cells and a general framework for uncovering how complex genetic architecture drives disease-relevant biology.

AP-MS↗

PubMed2026

Two Genomes, one Outcome: Stratifying Donor and Recipient Polygenic Risk Score to Improve Kidney Allograft Longevity.

Kidney transplantation outcomes arise from complex interactions among donor organ quality, recipient susceptibility, and immunologic compatibility, yet conventional clinical risk models explain only a modest fraction of outcome variability. Polygenic risk scores (PRS) offer a promising framework to enhance transplant risk assessment by integrating genome-wide genetic information from both donor and recipient into biologically informed models. This narrative review examines the mechanistic basis for PRS application in kidney transplantation and variant clustering approaches that link polygenic signals to specific biological pathways underlying alloimmunity, fibrosis, and metabolic dysfunction. We compare current PRS construction methodologies, highlighting their respective strengths and limitations in transplant cohorts. Transplant PRS are distinguished from single-genome disease models by their capacity to capture dual-genome interactions, simultaneously quantifying inherited donor organ liability and recipient genetic susceptibility within an integrated framework. This dual-genome architecture requires novel risk stratification paradigms in which combined donor-recipient polygenic profiles inform pretransplant decision-making in ways that neither genome alone can achieve. However, current PRS contribute only incremental variance beyond established clinical predictors, and critical limitations persist, including European ancestry bias, small cohort sizes, incomplete replication, and undefined clinical actionability thresholds. We critically evaluate these implementation barriers and outline future directions for integrating dual-genome PRS with clinical, molecular, and environmental data. The longer-term goal is to advance precision kidney transplantation through applications such as donor selection, immunosuppression tailoring, and individualized posttransplant surveillance. Realizing this potential will require validation in adequately powered, ancestry diverse, prospective transplant cohorts.

Journal Article↗

PubMed2025

Polygenic risk scores for rheumatoid arthritis and idiopathic pulmonary fibrosis and associations with RA, interstitial lung abnormalities, and quantitative interstitial abnormalities among smokers.

OBJECTIVE: Genome-wide association studies (GWAS) facilitate construction of polygenic risk scores (PRSs) for rheumatoid arthritis (RA) and idiopathic pulmonary fibrosis (IPF). We investigated associations of RA and IPF PRSs with RA and high-resolution chest computed tomography (HRCT) parenchymal lung abnormalities. METHODS: Participants in COPDGene, a prospective multicenter cohort of current/former smokers, had chest HRCT at study enrollment. Using genome-wide genotyping, RA and IPF PRSs were constructed using GWAS summary statistics. HRCT imaging underwent visual inspection for interstitial lung abnormalities (ILA) and quantitative CT (QCT) analysis using a machine-learning algorithm that quantified percentage of normal lung, interstitial abnormalities, and emphysema. RA was identified through self-report and DMARD use. We investigated associations of RA and IPF PRSs with RA, ILA, and QCT features using multivariable logistic and linear regression. RESULTS: We analyzed 9,230 COPDGene participants (mean age 59.6 years, 46.4 % female, 67.2 % non-Hispanic White, 32.8 % Black/African American). In non-Hispanic White participants, RA PRS was associated with RA diagnosis (OR 1.32 per unit, 95 %CI 1.18-1.49) but not ILA or QCT features. Among non-Hispanic White participants, IPF PRS was associated with ILA (OR 1.88 per unit, 95 %CI 1.52-2.32) and quantitative interstitial abnormalities (adjusted β=+0.50 % per unit, p = 7.3 × 10-8) but not RA. There were no statistically significant associations among Black/African American participants. CONCLUSIONS: RA and IPF PRSs were associated with their intended phenotypes among non-Hispanic White participants but performed poorly among Black/African American participants. PRS may have future application to risk stratify for RA diagnosis among patients with ILD or for ILD among patients with RA.

Humans↗

PubMed2026

Hypertrophic cardiomyopathy: a genome-wide association meta-analysis and polygenic risk score.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is a heritable trait with marked variability in expression and outcomes. Our aims were to discover new genetic loci associated with HCM and to test the effect of a new polygenic risk score (PRS) on incidence, phenotype and outcomes stratified by genotype status. METHODS: A discovery genome-wide association study (GWAS) was performed on 2284 HCM cases and 4525 controls. Two fixed-effects meta-analyses combined our discovery GWAS with single-trait and multi-trait results from a published study. Discovered loci underwent comprehensive bioinformatic analysis including functional and druggability annotations. A PRS using loci from the two meta-analyses was evaluated for association with HCM diagnosis in 411 213 individuals from UK Biobank (UKBB); imaging phenotypes in individuals without HCM; a composite endpoint (including all-cause mortality and transplantation); and sudden cardiac death (SCD) in 1756 HCM cases. PRS analyses were stratified by genotype status. RESULTS: Three loci were found in the discovery GWAS (BAG3, FHOD3 and novel locus PPP1R3A). In the meta-analyses, 70 unique loci were identified, four novel (MYPN, YWHAE, NOS1AP and OBSCN). Bioinformatic analyses identified NOS1AP as a candidate HCM gene. A new PRS was significantly associated with HCM diagnosis (HR=3.19, 95% CI 2.46 to 4.14 for top 5% vs lower 95%; HR=1.88, 95% CI 1.72 to 2.06 per SD increase). Significant associations were found between PRS and greater left ventricular (LV) wall thickness and higher LV ejection fraction in UKBB participants without HCM. Genotype-negative HCM cases in the top 20% of the PRS distribution had an increased risk of SCD (HR=2.72, 95% CI 1.03 to 7.17). CONCLUSIONS: We report novel HCM loci. A new PRS predicted the risk of HCM development and associated imaging characteristics in the UKBB and outcomes in an HCM cohort.

Cardiomyopathies↗

PubMed2026

Polygenic risk scores associate with asthma phenotypes and proteomic analyses implicate IL1R1 in two family-based studies.

Despite its high prevalence and the discovery of hundreds of genetic associations, the genetic determinants and heterogeneous manifestations of asthma remain incompletely understood. Incorporating polygenic risk scores (PRS) into asthma research offers a powerful approach to quantify inherited susceptibility, refine risk profiles, and advance mechanistic understanding of disease development. For this study, we leveraged whole-genome sequencing (WGS) data from two family-based cohorts of childhood asthma - the Genetics of Asthma in Costa Rica Study (GACRS) and the Childhood Asthma Management Program (CAMP) - to examine the transmission profiles of externally derived asthma PRS and their associations with clinical phenotypes in children with asthma. To further elucidate molecular mechanisms, we integrated large-scale external genome-wide association study (GWAS) summary statistics and genetic prediction models of protein abundance in a two-step proteome-wide association study (PWAS) of asthma. Our findings provide robust evidence supporting the validity of externally derived asthma PRS (asthma PRS association p-value p = 10-24 [GACRS and CAMP trios combined] for the Global Biobank Meta-analysis Initiative [GBMI]) and reveal consistent associations with spirometry measures and atopy markers across both studies, as 13 of 21 traits (62%) were significantly associated with the GBMI-PRS in the meta-analysis after multiple-testing correction. Moreover, the results of the integrative proteomic analysis implicate IL-1 signaling in the etiology of asthma, reinforcing the candidacy of IL1R1 antagonists for drug repurposing.

Journal Article↗

PubMed2026

Evaluation of population-specific polygenic risk scores for blood lipids: insights from Taiwanese cohorts and multiancestry meta-analysis.

BACKGROUND: Blood lipids are heritable risk factors for cardiovascular disease (CVD), a leading cause of mortality worldwide. However, the genetic architecture of lipid traits and the performance of polygenic risk scores (PRSs) remain underexplored in East Asian (EAS) populations, including Taiwanese Han individuals. METHODS: We conducted genome-wide association studies and PRS analyses for five lipid traits: total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, and the ratio of low-density lipoprotein cholesterol to total cholesterol. Lipid profile data were obtained from the China Medical University Hospital cohort. PRSs were evaluated on the basis of their correlations with measured lipid levels. To evaluate trans-ancestry PRS transferability, localized models were systematically compared against models derived from discovery-stage GWAS meta-analyses incorporating five ancestry groups from the Global Lipids Genetics Consortium. The performance of the PRS models in predicting lipid-related diseases was evaluated through receiver operating characteristic curve analyses. RESULTS: The population-specific PRS models explained 11%-40% of the variance in lipid levels within the target cohort. Models leveraging global multiancestry GWAS meta-analysis weights revealed limited predictive performance (r 2 = 0.04-0.19), whereas analyses incorporating EAS-specific data yielded higher correlations (r 2 = 0.13-0.30), although these correlations did not exceed those derived from the hospital-based cohort alone. When combined with age and sex, the PRS models demonstrated strong predictive performance for coronary artery disease, atherosclerosis, and ischemic stroke, with area under the curve values of 0.910, 0.926, and 0.854, respectively. CONCLUSION: Population-specific PRS models derived from a Taiwanese population outperformed meta-analysis-derived frameworks in predicting lipid levels and demonstrated substantial potential for predicting CVD risk, indicating the importance of ancestry-matched genetic studies in precision medicine.

LDL-C/TC ratio↗

PubMed2025

Evaluation of Multiple Breast Cancer Polygenic Risk Score Panels in Women of Latin American Heritage.

BACKGROUND: A substantial portion of the genetic predisposition for breast cancer is explained by multiple common genetic variants of relatively small effect. A subset of these variants, which have been identified mostly in individuals of European (EUR) and Asian ancestries, have been combined to construct a polygenic risk score (PRS) to predict breast cancer risk, but the prediction accuracy of existing PRSs in Hispanic/Latinx individuals (H/L) remain relatively low. We assessed the performance of several existing PRS panels with and without addition of H/L-specific variants among self-reported H/L women. METHODS: PRS performance was evaluated using multivariable logistic regression and the area under the ROC curve. RESULTS: Both EUR and Asian PRSs performed worse in H/L samples compared with original reports. The best EUR PRS performed better than the best Asian PRS in pooled H/L samples. EUR PRSs had decreased performance with increasing Indigenous American (IA) ancestry, while Asian PRSs had increased performance with increasing IA ancestry. The addition of two H/L SNPs increased performance for all PRSs, most notably in the samples with high IA ancestry, and did not impact the performance of PRSs in individuals with lower IA ancestry. CONCLUSIONS: A single PRS that incorporates risk variants relevant to the multiple ancestral components of individuals from Latin America, instead of a set of ancestry-specific panels, could be used in clinical practice. IMPACT: The results highlight the importance of population-specific discovery and suggest a straightforward approach to integrate ancestry-specific variants into PRSs for clinical application.

Adult↗

PubMed2026

Parental longevity and polygenic longevity scores in relation to ageing-related factors in a population of 70-year-olds followed over six years: The Gothenburg H70 Birth Cohort Study.

As societies age, a deeper understanding of ageing-related factors that contribute to longevity is needed. We therefore investigated possible longevity factors (social, medical, and biological) in relation to parental longevity (PL) and polygenic longevity scores (PGLSs). We examined 1126 70-year-olds from the Swedish population-based Gothenburg H70 Birth Cohort study in 2014-2016 (response rate 72%), with follow-up in 2019-2022 (response rate 77.6%). Comprehensive examinations included self-reported information on parents' ages, socioeconomic factors, mental, cardiovascular, and neurological health, anthropometry, laboratory data, and genotyping to construct two continuous PGLSs variables (with and without the APOE locus). PL groups were categorised as high if both parents survived to age 85 (17.2%); medium if one parent had survived (43.3%), and low if neither parent had survived to age 85 (39.4%). Higher PL and higher PGLSs were related to less hypertension, higher educational level, better childhood, and current socioeconomic status. In addition, higher PL was associated with higher MMSE score, total cholesterol, HDL-cholesterol (HDL-c) and LDL-cholesterol (LDL-c), lower BMI, homocysteine and inflammatory markers (IL-6, CRP) levels, and less smoking, whereas higher PGLSs was related to less myocardial infarction. At follow-up, high-PL was associated with less increase in plasma pTau217. PGLSs were mainly related to socioeconomic and cardiovascular factors, while individuals with long-lived parents, in addition, had several other characteristics of longevity, such as less inflammation, homocysteine, and markers of dementia. PL may be a proxy for biological ageing and used as a screening for ageing-related disorders in the context of prevention.

APOE↗

PubMed2026

Assessing the comorbidity between asthma and depression through polygenic risk scoring and time-to-event models.

BACKGROUND: Patients with asthma have an increased risk of developing depression, affecting their quality of life. To date, the processes contributing to this comorbidity remain unclear. METHODS: We integrated two large genome-wide association studies (88,486 patients with asthma and 447,859 controls; 412,024 patients with depression and 1,587,577 controls) with cross-sectional and longitudinal information available from the All of Us Research Program (N = 87,167) through polygenic risk scoring (PRS), Cox proportional-hazards models, one-sample Mendelian randomization (MR), and gene-set and drug-repurposing analyses. RESULTS: We observed that depression PRS was associated with increased asthma risk (hazard ratio, HR = 1.13, 95% CI = 1.09-1.17), also when accounting for comorbidity status (HR = 1.08, 95% CI = 1.04-1.12). Conversely, the effect of asthma PRS was null after accounting for comorbidity status. One-sample MR analysis showed an effect of depression genetic liability on asthma, ranging from beta = 0.36 ± 0.03 when considering a linear relationship to beta = 3.21 ± 0.31 when considering possible nonlinear relationships. Conversely, the effect of asthma genetic risk on depression was null after accounting for potential confounders. The gene-set analyses showed that asthma and depression polygenic risks share biological processes, molecular functions, and cellular components related to the immune system and the lung-brain axis. CONCLUSIONS: Genetic predisposition contributes to asthma-depression comorbidity through direct effects and shared pathogenic processes. These findings highlight the potential to develop targeted interventions to prevent and treat the co-occurrence of respiratory and neuropsychiatric disorders.

Comorbidity↗

PubMed2025

Sparse polygenic risk score inference with the spike-and-slab LASSO.

MOTIVATION: Large-scale biobanks, with rich phenotypic and genomic data across hundreds of thousands of samples, provide ample opportunities to elucidate the genetics of complex traits and diseases. Consequently, there is growing demand for robust and scalable methods for disease risk prediction from genotype data. Inference in this setting is challenging due to the high-dimensionality of genomic data, especially when coupled with smaller sample sizes. Popular Polygenic Risk Score (PRS) inference methods address this challenge by adopting sparse Bayesian priors or penalized regression techniques, such as the Least Absolute Shrinkage and Selection Operator (LASSO). However, the former class of methods are not as scalable and do not produce exact sparsity, while the latter tends to over-shrink large coefficients. RESULTS: In this study, we present SSLPRS, a novel PRS method based on the Spike-and-Slab LASSO (SSL) prior, which offers a theoretical bridge between the two frameworks. We extend previous work to derive a coordinate-ascent inference algorithm that operates on GWAS summary statistics, which is orders-of-magnitude more efficient than corresponding individual-level-based implementations. To illustrate the statistical properties of the proposed model, we conducted experiments involving nine simulation configurations and nine quantitative phenotypes from the UK Biobank. Our results demonstrate that SSLPRS is competitive with state-of-the-art methods in terms of prediction accuracy and exhibits superior variable selection performance, especially in sparse genetic architectures. In simulations, this translates to upwards of 50% improvement in positive predictive value. In analysis of real phenotypes, we show that selected variants are highly enriched for meaningful genomic annotations and have better replication rates in larger meta-analyses. AVAILABILITY AND IMPLEMENTATION: SSLPRS is available in the open-source package https://github.com/li-lab-mcgill/penprs.

Multifactorial Inheritance↗

PubMed2025

Polygenic Risk Scores Predicting Estimated GFR Validated With Iohexol Clearance.

INTRODUCTION: Genome-wide association studies (GWAS) have identified hundreds of single nucleotide variants (SNVs) associated with estimated glomerular filtration rate (eGFR). eGFR has been used as a proxy phenotype because of the complexity and cost of measured GFR (mGFR) in large studies. Because eGFR is influenced by non-GFR factors, these GWAS results may be biased compared with a hypothetical study using mGFR. We aimed to investigate this by comparing aggregate measures of genetic effects on mGFR and eGFR. METHODS: We studied 1492 persons from the Renal Iohexol Clearance Survey (RENIS) cohort, a representative sample of the general population in Northern Norway without preexisting cardiovascular disease, kidney disease, or diabetes. We measured iohexol-clearance, and genotyping was performed with a microarray chip enriched for GFR-related SNVs. We compared the performance of 3 published polygenic risk scores (PGS) developed for creatinine-based eGFR (eGFRcr), narrow-sense heritability (h2) and the mean effect of SNVs on mGFR, eGFRcr, cystatin C-based eGFR (eGFRcys) and eGFRcr-cys. RESULTS: The performance of the PGS differed for mGFR and the 3 eGFRs, with best performance for prediction of eGFRcr (P < 0.05). However, when the beta coefficients of the SNVs in the 3 PGS were estimated in the RENIS-cohort, their magnitude was 11% to 46% greater for mGFR than for the 3 eGFR methods in 8 of 9 comparisons (P < 0.05). mGFR had higher h2 (0.47) than eGFRcr (0.21), eGFRcys (0.37), and eGFRcr-cys (0.42). CONCLUSIONS: SNVs with non-GFR effects on creatinine and cystatin-C influence GWAS results. The results of GWAS using eGFR should be validated using experimental and other more precise methods.

chronic kidney disease↗

PubMed2025

Genomic and Developmental Models to Predict Cognitive and Adaptive Outcomes in Autistic Children.

IMPORTANCE: Although early signs of autism are often observed between 18 and 36 months of age, there is considerable uncertainty regarding future development. Clinicians lack predictive tools to identify those who will later be diagnosed with co-occurring intellectual disability (ID). OBJECTIVE: To predict ID in children diagnosed with autism. DESIGN, SETTING, AND PARTICIPANTS: This prognostic study involved the development and validation of models integrating genetic variants and developmental milestones to predict ID. Models were trained, cross-validated, and tested for generalizability across 3 autism cohorts: Simons Foundation Powering Autism Research (SPARK), Simons Simplex Collection, and MSSNG. Autistic participants were assessed older than 6 years of age for ID. Study data were analyzed from January 2023 to July 2024. EXPOSURES: Ages at attaining early developmental milestones, occurrence of language regression, polygenic scores for cognitive ability and autism, rare copy number variants, de novo loss-of-function and missense variants impacting constrained genes. MAIN OUTCOMES AND MEASURES: The out-of-sample performance of predictive models was assessed using the area under the receiver operating characteristic curve (AUROC), positive predictive values (PPVs), and negative predictive values (NPVs). RESULTS: A total of 5633 autistic participants (4574 male [81.2%]) were included in this analysis. On average, participants were diagnosed with autism at 4 (IQR, 3-7) years of age and assessed for ID at 11 (8-14) years of age, with 1159 participants (20.6%) being diagnosed with ID. The model integrating all predictors yielded an AUROC of 0.653 (95% CI, 0.625-0.681), and this predictive performance was cross-validated and generalized across cohorts. This modest performance reflected that only a subset of individuals carried large-effect variants, high polygenic scores, or presented delayed milestones. However, combinations of genetic variants that are typically not considered clinically relevant by diagnostic laboratories achieved PPVs of 55% and correctly identified 10% of individuals developing ID. The addition of polygenic scores to developmental milestones specifically improved NPVs rather than PPVs. Notably, the ability to stratify ID probabilities using genetic variants was up to 2-fold higher in individuals with delayed milestones compared with those with typical development. CONCLUSIONS AND RELEVANCE: Results of this prognostic study suggest that the growing number of neurodevelopmental condition-associated variants cannot, in most cases, be used alone for predicting ID. However, models combining different classes of variants with developmental milestones provide clinically relevant individual-level predictions that could be useful for targeting early interventions.

Humans↗