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Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality

Authors: Nakanishi, Tomoko; Pigazzini, Sara; Degenhardt, Frauke; Cordioli, Mattia; Butler-Laporte, Guillaume; Maya-Miles, Douglas; Nafria Jimenez, Beatriz; +42 Authors

Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality

Abstract

AG has received support by NordForsk Nordic Trial Alliance (NTA) grant, by Academy of Finland Fellow grant N. 323116 and the Academy of Finland for PREDICT consortium N. 340541. The Richards research group is supported by the Canadian Institutes of Health Research (CIHR) (365825 and 409511), the Lady Davis Institute of the Jewish General Hospital, the Canadian Foundation for Innovation (CFI), the NIH Foundation, Cancer Research UK, Genome Quebec, the Public Health Agency of Canada, the McGill Interdisciplinary Initiative in Infection and Immunity and the Fonds de Recherche Quebec Sante (FRQS). TN is supported by a research fellowship of the Japan Society for the Promotion of Science for Young Scientists. GBL is supported by a CIHR scholarship and a joint FRQS and Quebec Ministry of Health and Social Services scholarship. JBR is supported by an FRQS Clinical Research Scholarship. Support from Calcul Quebec and Compute Canada is acknowledged. TwinsUK is funded by the Welcome Trust, the Medical Research Council, the European Union, the National Institute for Health Research-funded BioResource and the Clinical Research Facility and Biomedical Research Centre based at Guy's and St. Thomas' NHS Foundation Trust in partnership with King's College London. The Biobanque Quebec COVID19 is funded by FRQS, Genome Quebec and the Public Health Agency of Canada, the McGill Interdisciplinary Initiative in Infection and Immunity and the Fonds de Recherche Quebec Sante. These funding agencies had no role in the design, implementation or interpretation of this study. The COVID19-Host(a)ge study received infrastructure support from the DFG Cluster of Excellence 2167 Precision Medicine in Chronic Inflammation (PMI) (DFG Grant: EXC2167). The COVID19-Host(a)ge study was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). Genotyping in COVID19-Host(a)ge was supported by a philantropic donation from Stein Erik Hagen. The COVID GWAs, Premed COVID-19 study (COVID19-Host(a)ge_3) was supported by Grupo de Trabajo en Medicina Personalizada contra el COVID-19 de Andalucia and also by the Instituto de Salud Carlos III (CIBERehd and CIBERER). Funding comes from COVID-19-GWAS, COVID-PREMED initiatives. Both of them are supported by Consejeria de Salud y Familias of the Andalusian Government. DMM is currently funded by the the Andalussian government (Proyectos Estrategicos-Fondos Feder PE-0451-2018). The Columbia University Biobank was supported by Columbia University and the National Center for Advancing Translational Sciences, NIH, through Grant Number UL1TR001873. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or Columbia University. The SPGRX study was supported by the Consejeria de Economia, Conocimiento, Empresas y Universidad #CV20-10150. The GEN-COVID study was funded by: the MIUR grant Dipartimenti di Eccellenza 2018-2020 to the Department of Medical Biotechnologies University of Siena, Italy; the Intesa San Paolo 2020 charity fund dedicated to the project NB/2020/0119; and philanthropic donations to the Department of Medical Biotechnologies, University of Siena for the COVID-19 host genetics research project (D.L n.18 of March 17, 2020). Part of this research project is also funded by Tuscany Region Bando Ricerca COVID-19 Toscana grant to the Azienda Ospedaliero Universitaria Senese (CUP I49C20000280002). Authors are grateful to: the CINECA consortium for providing computational resources; the Network for Italian Genomes (NIG) (http://www.nig.cineca.it) for its support; the COVID-19 Host Genetics Initiative (https://www.covid19hg.org/); the Genetic Biobank of Siena, member of BBMRI-IT, Telethon Network of Genetic Biobanks (project no. GTB18001), EuroBioBank, and RD-Connect, for managing specimens. Genetics against coronavirus (GENIUS), Humanitas University (COVID19-Host(a)ge_4) was supported by Ricerca Corrente (Italian Ministry of Health), intramural funding (Fondazione Humanitas per la Ricerca). The generous contribution of Banca Intesa San Paolo and of the Dolce&Gabbana Fashion Firm is gratefully acknowledged. Data acquisition and sample processing was supported by COVID-19 Biobank, Fondazione IRCCS Ca Granda Milano; LV group was supported by MyFirst Grant AIRC n.16888, Ricerca Finalizzata Ministero della Salute RF-2016-02364358, Ricerca corrente Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, the European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- Liver Investigation: Testing Marker Utility in Steatohepatitis, Programme Photonics under grant agreement 101016726 for the project REVEAL: Neuronal microscopy for cell behavioural examination and manipulation, Fondazione Patrimonio Ca' Granda Liver Bible PR-0361. DP was supported by Ricerca corrente Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, CV PREVITAL Strategie di prevenzione primaria nella popolazione Italiana Ministero della Salute, and Associazione Italiana per la Prevenzione dell'Epatite Virale (COPEV). Genetic modifiers for COVID-19 related illness (BeLCovid_1) was supported by the Fonds Erasme. The Host genetics and immune response in SARS-Cov-2 infection (BelCovid_2) study was supported by grants from Fondation Leon Fredericq and from Fonds de la Recherche Scientifique (FNRS). The INMUNGEN-CoV2 study was funded by the Consejo Superior de Investigaciones Cientificas. KUL is supported by the German Research Foundation (LU 1944/3-1) SweCovid is funded by the SciLifeLab/KAW national COVID-19 research program project grant to Michael Hultstrom (KAW 2020.0182) and the Swedish Research Council to Robert Frithiof (2014-02569 and 2014-07606). HZ is supported by Jeansson Stiftelser, Magnus Bergvalls Stiftelse. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. Genotyping for the COMRI cohort was performed and funded by the Genotyping Laboratory of Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki, Helsinki, Finland.

Background There is considerable variability in COVID-19 outcomes amongst younger adults—and some of this variation may be due to genetic predisposition. We characterized the clinical implications of the major genetic risk factor for COVID-19 severity, and its age-dependent effect, using individual-level data in a large international multi-centre consortium. Method The major common COVID-19 genetic risk factor is a chromosome 3 locus, tagged by the marker rs10490770. We combined individual level data for 13,424 COVID-19 positive patients (N=6,689 hospitalized) from 17 cohorts in nine countries to assess the association of this genetic marker with mortality, COVID-19-related complications and laboratory values. We next examined if the magnitude of these associations varied by age and were independent from known clinical COVID-19 risk factors. Findings We found that rs10490770 risk allele carriers experienced an increased risk of all-cause mortality (hazard ratio [HR] 1·4, 95% confidence interval [CI] 1·2–1·6) and COVID-19 related mortality (HR 1·5, 95%CI 1·3–1·8). Risk allele carriers had increased odds of several COVID-19 complications: severe respiratory failure (odds ratio [OR] 2·0, 95%CI 1·6-2·6), venous thromboembolism (OR 1·7, 95%CI 1·2-2·4), and hepatic injury (OR 1·6, 95%CI 1·2-2·0). Risk allele carriers ≤ 60 years had higher odds of death or severe respiratory failure (OR 2·6, 95%CI 1·8-3·9) compared to those > 60 years OR 1·5 (95%CI 1·3-1·9, interaction p-value=0·04). Amongst individuals ≤ 60 years who died or experienced severe respiratory COVID-19 outcome, we found that 31·8% (95%CI 27·6-36·2) were risk variant carriers, compared to 13·9% (95%CI 12·6-15·2%) of those not experiencing these outcomes. Prediction of death or severe respiratory failure among those ≤ 60 years improved when including the risk allele (AUC 0·82 vs 0·84, p=0·016) and the prediction ability of rs10490770 risk allele was similar to, or better than, most established clinical risk factors. Interpretation The major common COVID-19 risk locus on chromosome 3 is associated with increased risks of morbidity and mortality—and these are more pronounced amongst individuals ≤ 60 years. The effect on COVID-19 severity was similar to, or larger than most established risk factors, suggesting potential implications for clinical risk management.

No

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Spain
Subjects by Vocabulary

Microsoft Academic Graph classification: Coronavirus disease 2019 (COVID-19) business.industry Hazard ratio Age dependent Odds ratio Confidence interval Medicine Respiratory system Genetic risk factor business Venous thromboembolism Demography

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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AKA| A privacy-aware approach to identify individuals at high risk for cardiometabolic diseases using nation-wide registries and genetic information., AKA| Prediction tools and early mitigation measures in crisis preparedness: case COVID-19 / Consortium: PREDICT, EC| REVEAL
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REVEAL
Neuronal microscopy for cell behavioural examination and manipulation
  • Funder: European Commission (EC)
  • Project Code: 101016726
  • Funding stream: H2020 | RIA
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NIH| Predictive utility of polygenic risk scores for chronic kidney disease.
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  • Funder: National Institutes of Health (NIH)
  • Project Code: 1K25DK128563-01
  • Funding stream: NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
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