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We aimed to examine the association of kidney function\u2010related biomarkers and their genetic predisposition with the risk of developing severe COVID\u201019 in population\u2010based data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We analyzed data from UK Biobank to examine the prospective association of abnormal kidney function biomarkers with severe COVID\u201019, defined by laboratory\u2010confirmed COVID\u201019 hospitalizations. Using genotype data, we constructed polygenic risk scores (PRS) to represent an individual's overall genetic risk for these biomarkers. We also identified tipping points where the risk of severe COVID\u201019 began to increase significantly for each biomarker.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Of the 502,506 adults, 1650 (0.32%) were identified as severe COVID\u201019, before August 12, 2020. High levels of cystatin C (OR: 1.3; 95% CI: 1.2\u20131.5; FDR\u00a0=\u00a01.5\u2009\u00d7\u200910<jats:sup>\u22125<\/jats:sup>), serum creatinine (OR: 1.7; 95% CI: 1.3\u20132.1; <jats:italic>p<\/jats:italic>\u00a0=\u00a03.5\u2009\u00d7\u200910<jats:sup>\u22124<\/jats:sup>; FDR\u00a0=\u00a03.5\u2009\u00d7\u200910<jats:sup>\u22124<\/jats:sup>), microalbuminuria (OR: 1.4; 95% CI: 1.2\u20131.6; FDR\u00a0=\u00a04\u2009\u00d7\u200910<jats:sup>\u22124<\/jats:sup>), and UACR (urinary albumin creatinine ratio; OR: 1.4; 95% CI: 1.2\u20131.6; <jats:italic>p<\/jats:italic>\u00a0=\u00a03.5\u2009\u00d7\u200910<jats:sup>\u22124<\/jats:sup>; FDR\u00a0=\u00a03.5\u2009\u00d7\u200910<jats:sup>\u22124<\/jats:sup>) were found significantly associated with severe COVID\u201019. Individuals with top 10% of PRS for elevated cystatin C, urate, and microalbuminuria had 28% to 43% higher risks of severe COVID\u201019 than individuals with bottom 30% PRS (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.05). Tipping\u2010point analyses further supported that severe COVID\u201019 could occur even when the values of cystatin C, urate (male), and microalbuminuria were within their normal value ranges (OR &gt;1.1, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.05).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Findings from this study might point to new directions for clinicians and policymakers in optimizing risk\u2010stratification among patients based on polygenic risk estimation and tipping points of kidney function markers. Our results call for further investigation to develop a better strategy to prevent severe COVID\u201019 outcomes among patients with genetic predisposition to impaired kidney function. These findings could provide a new tool for clinicians and policymakers in the future especially if we need to live with COVID\u201019 for a long time.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mgg3.2047","type":"journal-article","created":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T07:55:09Z","timestamp":1663660509000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Impaired kidney function biomarkers and risk of severe <scp>COVID<\/scp>\u201019: Analysis of population\u2010based cohort data"],"prefix":"10.1002","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3184-9213","authenticated-orcid":false,"given":"Yifei","family":"Lin","sequence":"first","affiliation":[{"name":"West China Hospital Sichuan University  Chengdu China"},{"name":"Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology Harvard T.H. Chan School of Public Health  Boston Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baoshan","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology Dalian Maritime University  Dalian China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingxi","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Statistics Sun Yat\u2010sen University  Guangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxiang","family":"Chen","sequence":"additional","affiliation":[{"name":"Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology Harvard T.H. Chan School of Public Health  Boston Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Huang","sequence":"additional","affiliation":[{"name":"West China Hospital Sichuan University  Chengdu China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weimin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Respiratory and Critical Care Medicine\/Institute of Respiratory Health, Frontiers Science Center for Disease\u2010related Molecular Network\/Precision Medicine Research Center\/The Research Units of West China, Chinese Academy of Medical Sciences, West China Hospital Sichuan University  Chengdu China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueqing","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Nephrology Guangdong Provincial People's Hospital  Guangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8261-3174","authenticated-orcid":false,"given":"Liming","family":"Liang","sequence":"additional","affiliation":[{"name":"Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology Harvard T.H. 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