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Widespread recessive effects on common diseases in a cohort of 44,000 British Pakistanis and Bangladeshis with high autozygosity

medrxiv(2024)

Wellcome Sanger Institute | Broad Institute | Blizard Institute

Cited 0|Views42
Abstract
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 44,190 genotyped individuals, using two imputation panels: a set of 4,982 whole-exome-sequences from within the cohort, and the TOPMed-r2 panel. We performed association testing with 898 diseases from electronic health records. We identified 185 independent loci that reached standard genome-wide significance (p<5×10−8) under the recessive model and had p-values more significant than under the additive model. 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<5.5×10−12). 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 PNPLA3 (rs66812091) and non-alcoholic fatty liver disease, a previously reported additive association. We present novel evidence suggesting that the association is recessive instead (OR=1.3, recessive p=2×10−12, additive p=2×10−11, dominance deviation p=3×10−2, 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. ![Figure][1] ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This research was funded in part by Wellcome (grant no. 220540/Z/20/A, Wellcome Sanger Institute Quinquennial Review 2021–2026). For the purpose of open access, the authors have applied a CC–BY public copyright licence to any author accepted manuscript version arising from this submission. Genes & Health is/has recently been core–funded by Wellcome (WT102627, WT210561), the Medical Research Council (UK) (M009017, MR/X009777/1, MR/X009920/1), Higher Education Funding Council for England Catalyst, Barts Charity (845/1796), Health Data Research UK (for London substantive site), and research delivery support from the NHS National Institute for Health Research Clinical Research Network (North Thames). Genes & Health is/has recently been funded by Alnylam Pharmaceuticals, Genomics PLC; and a Life Sciences Industry Consortium of Astra Zeneca PLC, Bristol–Myers Squibb Company, GlaxoSmithKline Research and Development Limited, Maze Therapeutics Inc, Merck Sharp & Dohme LLC, Novo Nordisk A/S, Pfizer Inc, Takeda Development Centre Americas Inc. T. H. Heng is supported by the Agency for Science, Technology, and Research (A∗STAR) National Science Scholarship. The FinnGen project is funded by two grants from Business Finland (HUS 4685/31/2016 and UH 4386/31/2016) and the following industry partners: AbbVie Inc., AstraZeneca UK Ltd, Biogen MA Inc., Bristol Myers Squibb (and Celgene Corporation & Celgene International II Sarl), Genentech Inc., Merck Sharp & Dohme LCC, Pfizer Inc., GlaxoSmithKline Intellectual Property Development Ltd., Sanofi US Services Inc., Maze Therapeutics Inc., Janssen Biotech Inc, Novartis Pharma AG, and Boehringer Ingelheim International GmbH. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The London South East NRES Committee of the Health Research Authority gave ethical approval for the G&H work (14/LO/1240, dated 16 September 2014). The Coordinating Ethics Committee of the Hospital District of Helsinki and Uusimaa (HUS) gave ethical approval for the FinnGen work (Nr HUS/990/2017). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes G&H data is available for analysis in a secure Trusted Research Environment. Application can be made to the G&H executive: Information on how to access FinnGen data can be found here: Software used in the data analysis are publicly available and have been cited. Code written to run these algorithms is available upon reasonable request to the authors. [1]: pending:yes
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要点】:该研究在44,190名英国巴基斯坦和孟加拉裔个体中发现了185个与常见疾病相关的隐性基因位点,突显了非欧洲血统人群中隐性效应对常见疾病的影响,拓宽了遗传关联研究的视野。

方法】:研究者使用队列内4,982个全外显子序列和TOPMed-r2面板对个体进行变异体推断,并通过电子健康记录进行898种疾病的关联测试。

实验】:研究在FinnGen项目中得到验证,发现了一个新的保护性隐性关联,即SGLT4基因变异与高血压有关,为常见疾病的隐性效应提供了新的证据。使用的数据集包括G&H数据集和FinnGen数据集。