American journal of human genetics最新文献

{"title":"Haplotype analysis reveals pleiotropic disease associations in the HLA region.","authors":"Courtney J Smith, Satu Strausz, Jeffrey P Spence, Hanna M Ollila, Jonathan K Pritchard","doi":"10.1016/j.ajhg.2025.06.011","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.06.011","url":null,"abstract":"<p><p>The human leukocyte antigen (HLA) region plays an important role in human health through its involvement in immune cell recognition and maturation. While genetic variation in the HLA region is associated with many diseases, the pleiotropic patterns of these associations have not been systematically investigated. Here, we developed a haplotype approach to investigate disease associations phenome wide for 412,181 Finnish individuals and 2,459 diseases. Across the 1,035 diseases with a genome-wide association study association, we found a 17-fold average per-SNP enrichment of hits in the HLA region. Altogether, we identified 7,649 HLA associations across 647 diseases, including 1,750 associations uncovered by haplotype analysis. We found that some haplotypes show both risk-increasing and protective associations across different diseases, while others consistently increase risk across diseases, indicating a complex pleiotropic landscape involving a range of diseases. This study highlights the extensive impact of HLA variation on disease risk and underscores the importance of classical and non-classical genes as well as non-coding variation.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":""},"PeriodicalIF":8.1,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extracting and calibrating evidence of variant pathogenicity from population biobank data.","authors":"Vineel Bhat, Tian Yu, Lara Brown, Vikas Pejaver, Matthew Lebo, Steven Harrison, Christopher A Cassa","doi":"10.1016/j.ajhg.2025.06.012","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.06.012","url":null,"abstract":"<p><p>Genomic medicine requires a robust evidence base of variant phenotypic impacts, which remains incomplete even in extensively studied genes with monogenic disease associations. Here, we evaluated the broad potential of using population cohort data to identify evidence that can be used in variant assessment. Across 41 genes related to 18 clinically actionable monogenic phenotypes, we calculated variant-level odds ratios of disease enrichment using data from 469,803 UK Biobank participants. We found significant differences in odds ratio values between ClinVar-labeled pathogenic and benign variants in 11 phenotypes, spanning both common and rare disorders. To facilitate clinical translation, we calibrated the strength of evidence provided by variant-level odds ratios to align with American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) interpretation guidelines (PS4 criterion) and found that odds ratios may reach \"moderate,\" \"strong,\" or \"very strong\" evidence, varying by phenotype and gene. Overall, we found that 2.6% (N = 12,350) of participants harbor a rare variant of uncertain significance (VUS) with at least moderate evidence of pathogenicity-an indication of potentially unrecognized disease risk. Finally, by incorporating computational and functional data alongside population-based odds ratios, we identified variants that met the criteria for clinical reclassification. Notably, using this approach, we identified that 12.4% of rare VUSs in LDLR seen in participants meet diagnostic criteria to be classified as likely pathogenic, demonstrating its potential to scale the reclassification of VUSs.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":""},"PeriodicalIF":8.1,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144607165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient Mendelian randomization analysis with self-adaptive determination of sample structure and multiple pleiotropic effects.","authors":"Liye Zhang, Lu Liu, Jiadong Ji, Ran Yan, Ping Guo, Weiming Gong, Fuzhong Xue, Xiang Zhou, Zhongshang Yuan","doi":"10.1016/j.ajhg.2025.06.002","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.06.002","url":null,"abstract":"<p><p>Mendelian randomization (MR) has emerged as a highly valuable tool for inferring the causal effects of exposures on outcomes in observational studies using genetic variants, typically single-nucleotide polymorphisms (SNPs), as instrumental variables (IVs). Standard MR typically involves three steps: inputs of genome-wide association studies (GWASs) for both exposure and outcome, determination of IVs, and inference of causal effects. However, existing methods fail to simultaneously account for characteristics of GWAS data, uncertainty surrounding the validity of SNPs as IVs, and efficiency of estimating and testing the causal effect. Here, we developed MR method with self-adaptive determination of sample structure and multiple pleiotropic effects (MAPLE), a method for effective MR analysis. MAPLE utilizes correlated SNPs, self-adaptively accounts for the sample structure and the uncertainty that these correlated SNPs may exhibit multiple pleiotropic effects, and relies on a maximum-likelihood framework to infer the causal effects and obtain calibrated p values. We illustrate the advantage of MAPLE through comprehensively realistic simulations, where MAPLE, compared with another eight MR methods, shows calibrated type I error control and reduces false positives while being more powerful. In three types of lipid-trait-centric MR analyses in UK Biobank, MAPLE produces the most accurate causal-effect estimates in positive-control analyses evaluating the causal effect of each lipid trait on itself; reduces the false positives by 12.5% on average compared with existing methods in negative-control analyses investigating the causal effects of lipid traits on hair color and skin color; and highlights the causal effects of physical activity, alcohol, and smoking on lipid profiles in factor-screening analyses involving 412 trait pairs.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":""},"PeriodicalIF":8.1,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data sharing in the PRIMED Consortium: Design, implementation, and recommendations for future policymaking.","authors":"Johanna L Smith, Quenna Wong, Whitney Hornsby, Matthew P Conomos, Benjamin D Heavner, Iftikhar J Kullo, Bruce M Psaty, Stephen S Rich, Adrienne M Stilp, Bamidele Tayo, Yuji Zhang, Pradeep Natarajan, Sarah C Nelson","doi":"10.1016/j.ajhg.2025.06.004","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.06.004","url":null,"abstract":"<p><p>Sharing diverse genomic and other biomedical datasets is critical to advancing scientific discoveries and their equitable translation to improve human health. However, data sharing remains challenging in the context of legacy datasets, evolving policies, multi-institutional consortium science, and international stakeholders. The NIH-funded Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium was established to improve the performance of polygenic risk estimates for a broad range of health and disease outcomes with global impacts. Improving polygenic risk score performance across genetically diverse populations requires access to large, diverse cohorts. We report on the design and implementation of data-sharing policies and procedures developed in PRIMED to aggregate and analyze data from multiple heterogeneous sources while adhering to pre-existing data-sharing policies for each integrated dataset and respecting participant preferences and informed consent. Specifically, we describe two primary data-sharing mechanisms-coordinated dbGaP applications and a Consortium Data Sharing Agreement-and provide alternatives when individual-level data cannot be shared within the Consortium (e.g., federated analyses). We also describe technical implementation of Consortium data sharing in the NHGRI Analysis Visualization and Informatics Lab-space (AnVIL) cloud platform to share derived individual-level data, genomic summary results, and methods workflows with appropriate permissions. As a consortium making secondary use of pre-existing data sources, we also discuss challenges and propose solutions for release of individual- and summary-level data products to the broader scientific community. We make recommendations for ongoing and future policymaking with the goal of informing future consortia and other research activities.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":""},"PeriodicalIF":8.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144590267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Public preferences for the value and implementation of genomic newborn screening: Insights from two discrete choice experiments in Australia.","authors":"Riccarda Peters, Stephanie Best, Fiona Lynch, Danya F Vears, Lilian Downie, Alison D Archibald, Sebastian Lunke, Zornitza Stark, Ilias Goranitis","doi":"10.1016/j.ajhg.2025.05.001","DOIUrl":"10.1016/j.ajhg.2025.05.001","url":null,"abstract":"<p><p>Integrating genomic sequencing into newborn screening (NBS) has transformative potential for the identification and management of genetic conditions. Using discrete choice experiment surveys, we elicited the preferences, values, and priorities of 2,509 members of the Australian public about the value (n = 1,504) and implementation (n = 1,005) of genomic NBS (gNBS). The Australian public demonstrated positive preference for gNBS, with 90% of respondents indicating an interest in gNBS results. Cost of screening was the most important attribute in people's decision about uptake of gNBS. Enabling diagnosis in more newborns increases the utility of gNBS. To enable these diagnoses, the public is willing to accept less restrictive models of gNBS in terms of the types of conditions included. However, there is disutility associated with including conditions that have less effective (or no) treatments available and including conditions with reduced penetrance. A gNBS program yielding 10-50 additional diagnoses per 1,000 newborns screened relative to standard NBS was valued by the Australian public at AU$4,600-$5,700 (US$2,990-$3,700) per newborn screened. Most participants (65%) preferred an opt-in type of consent and expressed a preference to receive high-chance results in person from a genetics professional, although telehealth and phone options were acceptable. Our findings should inform economic evaluation and future implementation for gNBS in the Australian and other healthcare systems.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"1515-1527"},"PeriodicalIF":8.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144179739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-cell transcriptome-wide Mendelian randomization and colocalization analyses uncover cell-specific mechanisms in atherosclerotic cardiovascular disease.","authors":"Anushree Ray, Paulo Alabarse, Rainer Malik, Muralidharan Sargurupremraj, Jürgen Bernhagen, Martin Dichgans, Sebastian-Edgar Baumeister, Marios K Georgakis","doi":"10.1016/j.ajhg.2025.06.001","DOIUrl":"10.1016/j.ajhg.2025.06.001","url":null,"abstract":"<p><p>Genome-wide association studies (GWASs) have identified numerous genetic loci influencing human disease risk; however, linking these to causal genes remains challenging, limiting opportunities for drug target discovery. Transcriptome-wide association studies (TWASs) address this by linking variants to gene expression but typically rely on bulk RNA sequencing, limiting cell-specific resolution. Here, we present a single-cell TWAS pipeline combining cis-Mendelian randomization (MR) with colocalization analyses at the single-cell level. As a case study, we examined how genetically proxied gene expression in immune cells influences atherosclerotic cardiovascular disease (ASCVD) risk. We integrated single-cell expression quantitative trait loci (sc-eQTLs) for 14 immune cell types with GWASs for coronary artery disease, large artery atherosclerotic stroke, and peripheral artery disease. sc-cis-MR revealed 440 gene-outcome associations across cell types, 88% of which were missed by bulk TWASs, despite the considerably smaller sample size of the sc-eQTL dataset. Of these associations, 21 were replicated with external cis-eQTLs and colocalized with ASCVD GWAS signals. Expanding on previous evidence linking genetically proxied LIPA expression in whole blood to coronary artery disease, we found genetic variants influencing LIPA expression, particularly in monocytes, to drive associations with coronary artery disease, large artery atherosclerotic stroke, and subclinical atherosclerosis traits. A phenome-wide association study confirmed these findings without evidence of associations with unexpected clinical outcomes. scRNA sequencing and immunohistochemistry of human carotid plaques revealed high LIPA expression in plaque macrophages. Our pipeline enables the discovery of cell-specific expression patterns that drive genetic predisposition to human disease, potentially impacting target selection for cell-tailored therapeutics.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"1597-1609"},"PeriodicalIF":8.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144482849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic contributions to epigenetic-defined endotypes of allergic phenotypes in children.","authors":"Emma E Thompson, Xiaoyuan Zhong, Peter Carbonetto, Andréanne Morin, Jason Willwerscheid, Cynthia M Visness, Leonard B Bacharier, Meyer Kattan, George T O'Connor, Katherine Rivera-Spoljaric, Robert A Wood, Diane R Gold, Gurjit K Khurana Hershey, Christine C Johnson, Rachel L Miller, Christine M Seroogy, Edward M Zoratti, Peter J Gergen, Albert M Levin, Matthew C Altman, Tina Hartert, Matthew Stephens, Daniel J Jackson, James E Gern, Christopher G McKennan, Carole Ober","doi":"10.1016/j.ajhg.2025.05.006","DOIUrl":"10.1016/j.ajhg.2025.05.006","url":null,"abstract":"<p><p>Asthma is a common respiratory disease, with contributions from both genes and the environment and significant heterogeneity in underlying endotypes; yet, little is known about the relative contributions of each to these endotypes. To address this gap, we used nasal mucosal cell DNA methylation (DNAm) and gene expression and genotypes for 284 children in the Urban Environment and Childhood Asthma (URECA) birth cohort. Using an unbiased data-reduction approach and 37,256 CpGs on a custom-content Asthma&Allergy array, empirical Bayesian factorization was implemented to identify three DNAm signatures that were associated with phenotypes reflecting allergic diseases (allergic asthma and allergic rhinitis), allergic sensitization (atopy) (specific and total immunoglobulin E), and/or type 2 inflammation (eosinophil count and fractional exhaled nitric oxide [FeNO]). These associations were replicated in the Infant Susceptibility to Pulmonary Infections and Asthma (INSPIRE) and the Children's Respiratory Environment Workgroup (CREW) cohorts. The genes that were correlated with each signature in URECA reflected three cardinal endotypes of asthma: inhibited immune response to microbes, impaired epithelial barrier integrity, and activated type 2 immune pathways. To estimate the genetic contributions to these signatures, we used a common set of genotypes available in the three cohorts. The joint SNP heritability of each signature was 0.21 (p = 0.037), 0.26 (p = 1.7 × 10^-8), and 0.17 (p = 7.7 × 10^-6), respectively. The heritabilities of the DNAm signatures suggest that genetic variation contributes significantly to epigenetic signatures of allergic phenotypes and that susceptibility to the development of specific endotypes of asthma is present at birth and is poised to mediate individual epigenetic responses to early-life environments.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"112 7","pages":"1610-1624"},"PeriodicalIF":8.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144564294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bi-allelic variants in POPDC2 cause an autosomal recessive syndrome presenting with cardiac conduction defects and hypertrophic cardiomyopathy.","authors":"Michele Nicastro, Alexa M C Vermeer, Pieter G Postema, Rafik Tadros, Forrest Z Bowling, Hildur M Aegisdottir, Vinicius Tragante, Lukas Mach, Alex V Postma, Elisabeth M Lodder, Karel van Duijvenboden, Rob Zwart, Leander Beekman, Lingshuang Wu, Sean J Jurgens, Paul A van der Zwaag, Mariëlle Alders, Mona Allouba, Yasmine Aguib, J Luis Santome, David de Una, Lorenzo Monserrat, Antonio M A Miranda, Kazumasa Kanemaru, James Cranley, Ingeborg E van Zeggeren, Eleonora M A Aronica, Michela Ripolone, Simona Zanotti, Gardar Sveinbjornsson, Erna V Ivarsdottir, Hilma Hólm, Daníel F Guðbjartsson, Ástrós Th Skúladóttir, Kári Stefánsson, Lincoln Nadauld, Kirk U Knowlton, Sisse Rye Ostrowski, Erik Sørensen, Ole Birger Vesterager Pedersen, Jonas Ghouse, Søren A Rand, Henning Bundgaard, Henrik Ullum, Christian Erikstrup, Bitten Aagaard, Mie Topholm Bruun, Mette Christiansen, Henrik K Jensen, Deanna Alexis Carere, Christopher T Cummings, Kristen Fishler, Pernille Mathiesen Tørring, Klaus Brusgaard, Trine Maxel Juul, Lotte Saaby, Bo Gregers Winkel, Jens Mogensen, Francesco Fortunato, Giacomo Pietro Comi, Dario Ronchi, J Peter van Tintelen, Michela Noseda, Michael V Airola, Imke Christiaans, Arthur A M Wilde, Ronald Wilders, Sally-Ann Clur, Arie O Verkerk, Connie R Bezzina, Najim Lahrouchi","doi":"10.1016/j.ajhg.2025.04.016","DOIUrl":"10.1016/j.ajhg.2025.04.016","url":null,"abstract":"<p><p>POPDC2 encodes the Popeye domain-containing protein 2, which has an important role in cardiac pacemaking and conduction, due in part to its cyclic AMP (cAMP)-dependent binding and regulation of TREK-1 potassium channels. Loss of Popdc2 in mice results in sinus pauses and bradycardia, and morpholino-mediated knockdown of popdc2 in zebrafish results in atrioventricular (AV) block. We identified bi-allelic variants in POPDC2 in four families with a phenotypic spectrum consisting of sinus node dysfunction, AV conduction defects, and hypertrophic cardiomyopathy. Using homology modeling, we show that the identified variants are predicted to diminish the ability of POPDC2 to bind cAMP. In in vitro electrophysiological studies, we demonstrated that, in contrast with wild-type POPDC2, variants found in affected individuals failed to increase TREK-1 current density. While muscle biopsy of an affected individual did not show clear myopathic disease, it showed significantly reduced abundance of both POPDC1 and POPDC2, suggesting that stability and/or membrane trafficking of the POPDC1-POPDC2 complex is impaired by pathogenic variants in either protein. Single-cell RNA sequencing from human hearts demonstrated that co-expression of POPDC1 and POPDC2 was most prevalent in AV node, AV node pacemaker, and AV bundle cells. Using population-level genetic data of more than 1 million individuals, we show that none of the familial variants were associated with clinical outcomes in heterozygous state, suggesting that heterozygous family members are unlikely to develop clinical manifestations and therefore might not necessitate clinical follow-up. Our findings provide evidence for bi-allelic variants in POPDC2 causing a Mendelian autosomal recessive cardiac syndrome.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"1681-1698"},"PeriodicalIF":8.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144132106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward whole-genome inference of polygenic scores with fast and memory-efficient algorithms.","authors":"Shadi Zabad, Chirayu Anant Haryan, Simon Gravel, Sanchit Misra, Yue Li","doi":"10.1016/j.ajhg.2025.05.002","DOIUrl":"10.1016/j.ajhg.2025.05.002","url":null,"abstract":"<p><p>With improved whole-genome sequencing and variant imputation techniques, modern genome-wide association studies (GWASs) have enriched our understanding of the landscape of genetic associations for thousands of disease phenotypes. However, translating the marginal associations for millions of genetic variants to integrated polygenic risk scores (PRSs) that capture their joint effects on the phenotype remains a major challenge. Due to technical and statistical constraints, commonly used PRS methods in this setting either perform heuristic pruning and thresholding or overlook most genetic association signals by restricting inference to small variant sets, such as HapMap3. Here, we present a set of algorithmic improvements and compact data structures that enable scaling summary-statistics-based PRS inference to tens of millions of variants while avoiding numerical instabilities common in such high-dimensional settings. These enhancements consist of highly compressed linkage-disequilibrium (LD) matrix format, which integrates with streamlined and parallel coordinate-ascent updating schemes. When incorporated into our existing PRS method (VIPRS), the proposed algorithms yield over 50-fold reductions in storage requirements and lead to orders-of-magnitude improvements in runtime and memory efficiency. The updated VIPRS software can now perform variational Bayesian regression over 1.1 million HapMap3 variants in under a minute. Using this scalable implementation, we applied VIPRS to 75 of the most heritable, continuous phenotypes in the UK Biobank, leveraging marginal associations for up to 18 million bi-allelic variants. These experiments demonstrated that VIPRS is 1-2 orders of magnitude more efficient than popular baselines while being competitive with the best-performing methods in terms of prediction accuracy.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"1528-1546"},"PeriodicalIF":8.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144155380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging local ancestry and cross-ancestry genetic architecture to improve genetic prediction of complex traits in admixed populations.","authors":"Geyu Zhou,Israel Yolou,Yuhan Xie,Hongyu Zhao","doi":"10.1016/j.ajhg.2025.06.010","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.06.010","url":null,"abstract":"The broader application of polygenic risk score (PRS) is hindered by the limited transferability of PRS developed in Europeans to non-European populations. While many statistical methods have been developed to improve the performance of PRS in non-European populations, most of them focused on discrete genetic ancestry clusters and did not consider admixed individuals. Admixed individuals pose a unique challenge for PRS calculation due to the complexity of local ancestry and cross-ancestry effect sizes. Here, we present a statistical method called SDPR_admix for calculating PRS in admixed individuals. SDPR_admix characterizes the joint distribution of the effect sizes of a genetic variant with two ancestries to be both zero, ancestry enriched, or shared with correlation. SDPR_admix outperformed other methods in simulations and improved the prediction of real traits in European-African admixed individuals in UK Biobank when trained on the Population Architecture using Genomics and Epidemiology (PAGE) dataset (N = 13,000). Deployment of SDPR_admix on All of Us (N = 52,000) further increased the prediction accuracy by approximately 5-fold on average compared with training on PAGE. This enhancement was achieved with manageable computational time and cost, demonstrating the feasibility of training PRS models on large-scale All of Us data. We provided several examples demonstrating that both ancestral-enriched and shared effects, as included in the SDPR_admix prediction model, are helpful for improving polygenic prediction in admixed populations. We also applied SDPR_admix to construct PRS for admixed Americans with mixture of European and Amerindigenous ancestries and showed that SDPR_admix overall outperformed other methods.","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"109 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144594363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}