American journal of human genetics最新文献

{"title":"Complexity within simplicity: Exploring the multifactorial nature of sickle cell disease.","authors":"Athena Starlard-Davenport","doi":"10.1016/j.ajhg.2025.05.008","DOIUrl":"10.1016/j.ajhg.2025.05.008","url":null,"abstract":"<p><p>Sickle cell disease, though monogenic, exhibits complex clinical variability driven by genetic, epigenetic, and environmental factors. This commentary highlights advances in precision therapies and underscores the urgent need for equitable access, global collaboration, and personalized approaches to address the significant health disparities impacting individuals with sickle cell disease worldwide.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"1499-1503"},"PeriodicalIF":8.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12256871/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144245916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping chromatin interactions at melanoma susceptibility loci uncovers distant cis-regulatory gene targets.","authors":"Rohit Thakur, Mai Xu, Hayley Sowards, Joshuah Yon, Lea Jessop, Timothy Myers, Tongwu Zhang, Raj Chari, Erping Long, Thomas Rehling, Rebecca Hennessey, Karen Funderburk, Jinhu Yin, Mitchell J Machiela, Matthew E Johnson, Andrew D Wells, Alessandra Chesi, Struan F A Grant, Mark M Iles, Maria Teresa Landi, Matthew H Law, Jiyeon Choi, Kevin M Brown","doi":"10.1016/j.ajhg.2025.04.015","DOIUrl":"10.1016/j.ajhg.2025.04.015","url":null,"abstract":"<p><p>Genome-wide association studies (GWASs) of melanoma risk have identified 68 independent signals at 54 loci. For most loci, specific functional variants and their respective target genes remain to be established. Capture-HiC is an assay that links fine-mapped risk variants to candidate target genes by comprehensively mapping chromatin interactions. We performed a melanoma GWAS region-focused capture-HiC assay in human primary melanocytes to identify physical interactions between fine-mapped risk variants and potential causal melanoma-susceptibility genes. Overall, chromatin-interaction data alone nominated potential causal genes for 61 of the 68 melanoma risk signals, identifying many candidates beyond those reported by previous studies. We further integrated these data with epigenomic (chromatin state, accessibility), gene expression (expression quantitative trait locus [eQTL]/transcriptome-wide association study [TWAS]), DNA methylation (methylation QTL [meQTL]/methylome-wide association study [MWAS]), and massively parallel reporter assay (MPRA) data generated from melanoma-relevant cell types to prioritize potentially cis-regulatory variants and their respective candidate gene targets. From the set of fine-mapped variants across these loci, we identified 140 prioritized credible causal variants linked to 195 candidate genes at 42 risk signals. In addition, we developed an integrative scoring system to facilitate candidate gene prioritization, integrating melanocyte and melanoma datasets. Notably, at several GWAS risk signals, we observed long-range chromatin connections (500 kb to >1 Mb) with distant candidate target genes. We validated several such cis-regulatory interactions using CRISPR inhibition, providing evidence for known cancer driver genes MDM4 and CBL, as well as the SRY-box transcription factor SOX4, as likely melanoma risk genes.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"1625-1648"},"PeriodicalIF":8.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12256899/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144132107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recurrent de novo variants in the spliceosomal factor CRNKL1 are associated with severe microcephaly and pontocerebellar hypoplasia with seizures.","authors":"Sankalita Ray Das, Rosie Sullivan, Mischa S G Ruegg, Julia Horsfield, Jordan Doran, Gemma Poke, Nathalie de Vries, Sarah Duerinckx, Damien Lederer, Muzhirah Haniffa, Wee-Teik Keng, Gaik-Siew Ch'ng, David A Parry, Andrew P Jackson, Masamune Sakamoto, Naomichi Matsumoto, Noriko Miyake, Shin Nabatame, Hidetoshi Taniguchi, Emma Wakeling, Katrin Õunap, Pilvi Ilves, Ghayda Mirzaa, Andrew Timms, Emily Pao, Kimberly A Aldinger, William Dobyns, Axel Bohring, Beate Behre, Daniel G Calame, James R Lupski, Juan M Pascual, Marc Abramowicz, Gregory Gimenez, Louise S Bicknell","doi":"10.1016/j.ajhg.2025.05.013","DOIUrl":"10.1016/j.ajhg.2025.05.013","url":null,"abstract":"<p><p>Splicing is a complex process that is required to create the transcriptomic diversity needed for specialized functions in higher eukaryotes. The spliceosome contains more than 100 proteins and RNA molecules, which coordinate this dynamic process. Despite the ubiquity of splicing, pathogenic variants in spliceosomal components often cause a tissue-specific phenotype, hinting at further complexities that are not yet fully understood. We have identified a cohort of ten families with de novo missense variants in a spliceosomal component, CRNKL1, where nine individuals harbor one of two missense variants that both affect the same amino acid, Arg267. All affected individuals share a common and specific phenotype: profound pre- and post-natal microcephaly, with pontocerebellar hypoplasia, seizures, and severe intellectual disability. Microinjection of mRNA encoding mutant Crnkl1 into a zebrafish model caused a severe lack of brain development accompanied by a significant reduction in proliferating cells and widespread cellular stress, as indicated by p53 staining. RNA sequencing analysis of injected zebrafish embryos showed broad transcriptomic changes, with altered expression of neuronal and cell cycle genes. Taking these results together, we have identified CRNKL1 as a disease-associated gene and demonstrate the requirement for this protein in brain development. Our findings contribute to a growing disease cluster, where associated components act at the same spliceosomal stage and cause a severe neurological phenotype, suggesting a more intricate role for these spliceosomal subcomplexes than previously thought.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"112 7","pages":"1722-1732"},"PeriodicalIF":8.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12256911/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144939350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring depression treatment response by using polygenic risk scoring across diverse populations","authors":"Sandra Lapinska, Aditya Pimplaskar, Zhuozheng Shi, Yi Ding, Clara Frydman-Gani, Kangcheng Hou, Vidhya Venkateswaran, Kristin Boulier, Loes M. Olde Loohuis, Bogdan Pasaniuc","doi":"10.1016/j.ajhg.2025.06.003","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.06.003","url":null,"abstract":"Treatment-resistant depression (TRD), usually defined as limited or no response to at least two antidepressants, occurs in approximately one-third of individuals diagnosed with major depressive disorder (MDD). Studies of individuals of European ancestry highlight a genetic overlap between TRD and MDD. We analyzed two large and diverse biobanks, the UCLA ATLAS Community Health Study (ATLAS) and the All of Us Research Program (AoU), to test for associations between a polygenic score for major depression (MDD-PGS) and TRD. Compared to treatment responders, TRD individuals have higher MDD-PGS across all ancestries. MDD-PGS was significantly associated with response to selective serotonin reuptake inhibitors in individuals of European and Hispanic/Latin American genetic ancestries in both biobanks. In AoU, a decreased MDD-PGS was observed in response to tricyclics or serotonin modulators in individuals of European American ancestry and in response to serotonin and norepinephrine reuptake inhibitors in individuals of African American ancestry. ATLAS found that MDD-PGS showed lower odds of responding to atypical agents than did TRD in MDD-affected individuals belonging to the Hispanic/Latin American group, MDD-PGS was associated with atypical agents. Overall, by leveraging larger sample sizes from two diverse biobanks, we provide new insights into antidepressant response and treatment specificity for MDD in individuals of diverse genetic ancestries.","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"274 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144504023","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":"Genomic rare variant mechanisms for congenital cardiac laterality defect: A digenic model approach","authors":"Archana Rai, Jonathan Klonowski, Bo Yuan, Karen J. Coveler, Zain Dardas, Iman Egab, Jiaoyang Xu, Philip J. Lupo, A.J. Agopian, Dennis Kostka, Cecilia W. Lo, S. Stephen Yi, Bruce D. Gelb, Christine E. Seidman, Eric Boerwinkle, Jennifer E. Posey, Richard A. Gibbs, James R. Lupski, Shaine A. Morris, Zeynep Coban-Akdemir","doi":"10.1016/j.ajhg.2025.05.014","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.05.014","url":null,"abstract":"Laterality defects are defined by perturbations in the usual left-right asymmetry of organs. The genetic etiology that underlies congenital heart disease (CHD) is often unknown (less than 40%), so we used a digenic model approach for the identification of contributing variants in known laterality-defect-associated genes (<ce:italic>n</ce:italic> = 115) in the exome/genome sequencing (ES/GS) data from individuals with clinically diagnosed laterality defects. The unsolved ES/GS data were analyzed from three CHD cohorts: Baylor College of Medicine-Genomics Research to Elucidate the Genetics of Rare Diseases (BCM-GREGoR; <ce:italic>n</ce:italic>= 251 proband ES), Gabriella Miller Kids First Pediatric Research Program (Kids First; <ce:italic>n</ce:italic> = 158 trio GS), and Pediatric Cardiac Genomics Consortium (PCGC; <ce:italic>n</ce:italic> = 163 trio ES). <ce:italic>trans</ce:italic>-heterozygous digenic variants were identified in 2.8% (inherited digenic variants in 0.4%), 8.2%, and 13.5% of individuals, respectively; this was significantly higher than in 602 control trios provided by the 1000 Genomes Project (<ce:italic>p =</ce:italic> 0.001, 1.4e−07, and 8.9e−13, respectively). <ce:italic>trans</ce:italic>-heterozygous digenic variants were also identified in 0.4% and 1.4% of individuals with non-laterality CHD in Kids First and PCGC datasets, respectively, which was not statistically significant as compared to control trios (<ce:italic>p</ce:italic> = 1 and 0.059, respectively). Altogether, in laterality cohorts, 23% of digenic pairs were in the same structural complex of motile cilia. Out of 39 unique digenic pairs in laterality CHD, 29 are more likely to be potential digenic hits as predicted by the DiGePred tool. These findings provide further evidence that digenic epistatic interactions can contribute to the complex genetics of laterality defects.","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"25 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144335447","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":"Applying multimodal AI to physiological waveforms improves genetic prediction of cardiovascular traits","authors":"Yuchen Zhou, Justin Khasentino, Taedong Yun, Mahantesh I. Biradar, Jacqueline Shreibati, Dongbing Lai, Tae-Hwi Schwantes-An, Robert Luben, Zachary R. McCaw, Jorgen Engmann, Rui Providencia, Amand Floriaan Schmidt, Patricia B. Munroe, Howard Yang, Andrew Carroll, Anthony P. Khawaja, Cory Y. McLean, Babak Behsaz, Farhad Hormozdiari","doi":"10.1016/j.ajhg.2025.05.015","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.05.015","url":null,"abstract":"Electronic health records, biobanks, and wearable biosensors enable the collection of multiple health modalities from many individuals. Access to multimodal health data provides a unique opportunity for genetic studies of complex traits because different modalities relevant to a single physiological system (e.g., circulatory system) encode complementary and overlapping information. We propose a multimodal deep learning method, multimodal representation learning for genetic discovery on low-dimensional embeddings (M-REGLE), for discovering genetic associations from a joint representation of complementary electrophysiological waveform modalities. M-REGLE jointly learns a lower representation (i.e., latent factors) of multimodal physiological waveforms using a convolutional variational autoencoder, performs genome-wide association studies (GWASs) on each latent factor, then combines the results to study the genetics of the underlying system. To validate the advantages of M-REGLE and multimodal learning, we apply it to common cardiovascular modalities (photoplethysmogram [PPG] and electrocardiogram [ECG]) and compare its results to unimodal learning methods in which representations are learned from each data modality separately but are statistically combined for downstream genetic comparison. M-REGLE identifies 19.3% more loci on the 12-lead ECG dataset, 13.0% more loci on the ECG lead I + PPG dataset, and its genetic risk score significantly outperforms the unimodal risk score at predicting cardiac phenotypes, such as atrial fibrillation (Afib), in multiple biobanks.","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"101 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144335469","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":"CADET: Enhanced transcriptome-wide association analyses in admixed samples using eQTL summary data","authors":"S. Taylor Head, Qile Dai, Joellen Schildkraut, David J. Cutler, Jingjing Yang, Michael P. Epstein","doi":"10.1016/j.ajhg.2025.05.010","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.05.010","url":null,"abstract":"A transcriptome-wide association study (TWAS) is a popular statistical method for identifying genes whose genetically regulated expression (GReX) component is associated with a trait of interest. Most TWAS approaches fundamentally assume that the training dataset (used to fit the gene expression prediction model) and target genome-wide association study (GWAS) dataset are from the same ancestrally homogeneous population. If this assumption is violated, studies have shown a marked negative impact on expression prediction accuracy as well as reduced power of the downstream gene-trait association test. These issues pose a particular problem for admixed individuals whose genomes represent a mosaic of multiple continental ancestral segments. To resolve these issues, we present CADET, which enables powerful TWAS of admixed cohorts leveraging the local-ancestry (LA) information of the cohort along with summary-level expression quantitative trait locus (eQTL) data from reference panels of different ancestral groups. CADET combines multiple polygenic risk score models based on the summary-level eQTL reference data to predict LA-aware GReX components in admixed target samples. Using simulated data, we compare the imputation accuracy, power, and type I error rate of our proposed LA-aware approach to LA-unaware methods for performing TWASs. We show that CADET performs optimally in nearly all settings regardless of whether the genetic architecture of gene expression is dependent or independent of ancestry. We further illustrate CADET by performing a TWAS of 29 common blood biochemistry phenotypes within an admixed cohort from the UK Biobank and identify 18 hits unique to our LA-aware strategy, with the majority of hits supported by existing GWAS findings.","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"11 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289888","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":"Weighing the evidence on costs and benefits of polygenic risk-based approaches in clinical practice: A systematic review of economic evaluations","authors":"Leonardo Maria Siena, Valentina Baccolini, Marianna Riccio, Annalisa Rosso, Giuseppe Migliara, Antonio Sciurti, Claudia Isonne, Jessica Iera, Francesco Pierri, Carolina Marzuillo, Corrado De Vito, Giuseppe La Torre, Paolo Villari","doi":"10.1016/j.ajhg.2025.05.012","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.05.012","url":null,"abstract":"Polygenic risk scores (PRSs) represent a promising innovation in the context of precision health, but their benefits for patients and healthcare systems remain unclear. This systematic review examined the methods used to quantify the costs and benefits of PRS-based approaches across different healthcare contexts, summarizing current evidence and identifying challenges. A systematic search of three databases was conducted, and full economic evaluations related to any intervention based on polygenic risk stratification strategies were included (PROSPERO CRD42023442780). Quality was assessed using the Quality of Health Economic Studies instrument. Studies were grouped into three categories (cancer, cardiovascular disease, and other diseases), and key methodological features and characteristics were extracted. A total of 24 cost-utility analyses of generally high quality were included: 16 studies focused on cancer, five on cardiovascular disease, and three on other diseases. Studies on cancer mainly aimed to optimize screening programs, while in the other fields, PRSs were mostly used to refine eligibility for preventive therapies. Analyses were robust, but they mostly relied on hypothetical cohorts, had limited generalizability, paid insufficient attention to implementation aspects—including the delivery model—and considered only clinical benefits. Despite a positive trend toward cost effectiveness following PRS implementation, several challenges remain. These include the limited use of real-world data, issues of representativeness, and gaps in accounting for implementation costs, as well as long-term health and non-health benefits. Further research and pilot studies are needed to evaluate both the costs and benefits of PRS applications across diverse populations for multiple health outcomes simultaneously.","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"20 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289889","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":"A data model for population descriptors in genomic research","authors":"Alyna T. Khan, Clement Adebamowo, Stephanie M. Fullerton, Jibril Hirbo, Iain R. Konigsberg, Peter Kraft, Iman Martin, Sarah C. Nelson, Michèle Ramsay, Genevieve L. Wojcik, Sally N. Adebamowo, Matthew P. Conomos, Burcu F. Darst, Micah R. Hysong, Yun Li, Alicia R. Martin, Rasika A. Mathias, Stephen S. Rich, Lori C. Sakoda, Daniel R. Schrider, Jayati Sharma, Johanna L. Smith, Quan Sun, Yuji Zhang, Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium, Stephanie M. Gogarten","doi":"10.1016/j.ajhg.2025.05.011","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.05.011","url":null,"abstract":"Population descriptors used in genetic studies have broad social and translational implications. There are no globally agreed-upon definitions or usages of common population descriptors (e.g., race, ethnicity, nationality, and tribe), many of which are applied <ce:italic>ad hoc</ce:italic> and/or derived from political or bureaucratic conventions. Recent recommendations have encouraged the retention of as much granularity in population descriptors as possible during data preparation, analysis, and interpretation of research results. However, genomic research infrastructures (i.e., current practices, resources, and workflows in genomic research) often lack systematic and flexible organization, structure, and harmonization of multifaceted and detailed population descriptor data. This can lead to loss of information, barriers to international collaboration, and potential issues in clinical translation. Here, we describe a data model, developed by the NIH-funded Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium, that organizes and retains detailed population descriptor data for future research use. The model supports a versatile, traceable, and reproducible harmonization system that offers multiple benefits over existing data structures. This data model affords researchers the flexibility to thoughtfully choose and scientifically justify their choice of population descriptors. It avoids the conflation of social identities with biological categories and guards against harmful typological inferences. Genomic research tools of this kind will be crucial for producing scientifically robust findings that minimize potential harms of descriptor misuse while maximizing benefits for diverse communities.","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"87 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289907","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":"Widespread recessive effects on common diseases in a cohort of 44,000 British Pakistanis and Bangladeshis with high autozygosity.","authors":"Teng Hiang Heng, Klaudia Walter, Qin Qin Huang, Juha Karjalainen, Mark J Daly, Henrike O Heyne, Daniel S Malawsky, Georgios Kalantzis, Sarah Finer, David A van Heel, Hilary C Martin","doi":"10.1016/j.ajhg.2025.03.020","DOIUrl":"10.1016/j.ajhg.2025.03.020","url":null,"abstract":"<p><p>Genetic association studies have focused on testing additive models in cohorts with European ancestry. Little is known about recessive effects on common diseases, specifically for non-European ancestry. Genes & Health is a cohort of British Pakistani and Bangladeshi individuals with elevated rates of consanguinity and endogamy, making it suitable to study recessive effects. We imputed variants into a genotyped dataset (n = 44,190) by using two reference panels: a set of 4,982 whole-exome sequences from within the cohort and the Trans-Omics for Precision Medicine (TOPMed-r2) panel. We performed association testing with 898 diseases from electronic health records. 185 independent loci reached genome-wide significance (p < 5 × 10^-8) under the recessive model, with p values lower than under the additive model, and >40% of these were novel. 140 loci demonstrated nominally significant (p < 0.05) dominance deviation p values, confirming a recessive association pattern. Sixteen loci in three clusters were significant at a Bonferroni threshold, accounting for multiple phenotypes tested (p < 5.4 × 10^-12). In FinnGen, we replicated 44% of the expected number of Bonferroni-significant loci we were powered to replicate, at least one from each cluster, including an intronic variant in patatin-like phospholipase domain-containing protein 3 (PNPLA3; rs66812091) and non-alcoholic fatty liver disease, a previously reported additive association. We present evidence suggesting that the association is recessive instead (odds ratio [OR] = 1.3, recessive p = 2 × 10^-12, additive p = 2 × 10^-11, dominance deviation p = 3 × 10^-2, and FinnGen recessive OR = 1.3 and p = 6 × 10^-12). We identified a novel protective recessive association between a missense variant in SGLT4 (rs61746559), a sodium-glucose transporter with a possible role in the renin-angiotensin-aldosterone system, and hypertension (OR = 0.2, p = 3 × 10^-8, dominance deviation p = 7 × 10^-6). These results motivate interrogating recessive effects on common diseases more widely.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"1316-1329"},"PeriodicalIF":8.1,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12256797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143956606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}