Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19

VA Million Veteran Program COVID-19 Science Initiative, Liam Gaziano, Claudia Giambartolomei, Alexandre C. Pereira, Anna Gaulton, Daniel C. Posner, Sonja A. Swanson, Yuk Lam Ho, Sudha K. Iyengar, Nicole M. Kosik, Marijana Vujkovic, David R. Gagnon, A. Patrícia Bento, Inigo Barrio-Hernandez, Lars Rönnblom, Niklas Hagberg, Christian Lundtoft, Claudia Langenberg, Maik Pietzner, Dennis ValentineStefano Gustincich, Gian Gaetano Tartaglia, Elias Allara, Praveen Surendran, Stephen Burgess, Jing Hua Zhao, James E. Peters, Bram P. Prins, Emanuele Di Angelantonio, Poornima Devineni, Yunling Shi, Kristine E. Lynch, Scott L. DuVall, Helene Garcon, Lauren O. Thomann, Jin J. Zhou, Bryan R. Gorman, Jennifer E. Huffman, Christopher J. O’Donnell, Philip S. Tsao, Jean C. Beckham, Saiju Pyarajan, Sumitra Muralidhar, Grant D. Huang, Rachel Ramoni, Pedro Beltrao, John Danesh, Adriana M. Hung, Kyong Mi Chang, Yan V. Sun, Jacob Joseph

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Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10−6; IFNAR2, P = 9.8 × 10−11 and IL-10RB, P = 2.3 × 10−14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.

Original languageEnglish
Pages (from-to)668-676
Number of pages9
JournalNature Medicine
Issue number4
Publication statusPublished - 9 Apr 2021

Bibliographical note

Funding Information:
We are grateful to the Host Genetic Initiative for making their data publicly available (full acknowledgements can be found at This research is based on data from the MVP, Office of Research and Development, VA and was supported by award no. MVP035. This research was also supported by additional Department of Veterans Affairs awards grant no. MVP001. This publication does not represent the views of the Department of Veteran Affairs or the US Government. Full acknowledgements for the VA MVP COVID-19 Science Initiative can be found in Supplementary Methods. C.G. has received funding from the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie grant agreement no. 754490, MINDED project. A.G., P.B. and A.R.L. are funded by the Member States of the European Molecular Biology Laboratory. I.B.-H. received funding from Open Targets (grant agreement OTAR-044). The Fenland study59 is funded by the Medical Research Council (MC_UU_12015/1); we are grateful to all the volunteers and to the General Practitioners and practice staff for assistance with recruitment; we thank the Fenland Study Investigators, Fenland Study Co-ordination team and the Epidemiology Field, Data and Laboratory teams; we further acknowledge support for genomics from the Medical Research Council (MC_PC_13046); proteomic measurements were supported and governed by a collaboration agreement between the University of Cambridge and Somalogic. J.E.P. is supported by UK Research and Innovation Fellowship at Health Data Research UK (MR/S004068/2). L.R., N.H. and C.L. are supported by the Swedish Research Council. E.A. was supported by the EU/EFPIA Innovative Medicines Initiative Joint Undertaking BigData@Heart grant no. 116074 and by the British Heart Foundation Programme grant RG/18/13/33946. We thank A. Wood for feedback on statistical analyses used in the paper. We thank the INTERVAL Study investigators, co-ordination team and the epidemiology field, data and laboratory teams, who were supported by core funding from the UK Medical Research Council (MR/L003120/1), the British Heart Foundation (RG/13/13/30194; RG/18/13/33946), the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (BRC-1215-20014) (the views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care) and the NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR BTRU-2014-10024). This work was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, the Engineering and Physical Sciences Research Council, the Economic and Social Research Council, the Department of Health and Social Care (England), the Chief Scientist Office of the Scottish Government Health and Social Care Directorates, the Health and Social Care Research and Development Division (Welsh Government), the Public Health Agency (Northern Ireland), the British Heart Foundation and Wellcome. J.D. holds a British Heart Foundation Professorship and an NIHR Senior Investigator Award.

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.


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