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IL10RB as a key regulator of COVID-19 host susceptibility and severity
Georgios Voloudakis1, Gabriel Hoffman1, Sanan Venkatesh1
1Department of Psychiatry (G.V., S.V., K.D., J.V., W.Z., S.J., S.A., A.W.C., K.J.B., P.R.), Pamela Sklar Division of Psychiatric Genomics (G.V., G.H., S.V., K.D., J.V., W.Z., S.J., A.W.C., J. F.F., K.J.B., P.R.), Friedman Brain Institute (G.V., G.H., S.V., K.D., J.V., W.Z., S.J., S.A., J.F.F., K.J.B., P.R.), Department of Genetics and Genomic Science (G.V., G.H., S.V., K.D., J.V., W.Z., N.D.B., S.J., S.A., E.E.S., A.W.C., J.F.F., K.J.B., P.R.), Icahn Institute for Data Science and Genomic Technology (G.V., G.H., S.V., K.D., J.V., W.Z., N.D.B., S.J., S.A, E.E.S., A.W.C., J.F.F., K.J.B., P.R.), Nash Family Department of Neuroscience (K.D., S.A, A.W.C., K.J.B.), Department of Microbiology (D.H., B.R.T.), Virus Engineering Center for Therapeutics and Research (D.H., B.R.T.), Global Health and Emerging Pathogens Institute (D.H., B.R.T.), Mount Sinai Clinical Intelligence Center (N.D.B., A.W.C.), Department of Oncological Sciences (M.M.), Precision Immunology Institute (M.M.) and Tisch Cancer Institute (M.M.) of the Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; the Mental Illness Research, Education, and Clinical Center (VISN 2 South) of the James J. Peters VA Medical Center (G.V., S.V., P.R.), Bronx, NY 10468, USA; VA Informatics and Computing Infrastructure (K.M.L., J.B., J.A.L.), VA Salt Lake City Health Care System, Salt Lake City, UT; Department of Psychiatry (K.D., K.J.B.) of the Yale University, New Haven, CT 06511, USA; Division of Epidemiology (J.B., J.A.L.), University of Utah, Salt Lake City, UT 84108, USA; New York Genome Center (A.C.), New York, NY 10013, USA; Biostatistics Shared Resources (L.G.) and Department of Medicine (S.-W.L.), Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97229, USA; VA Boston Healthcare System (K.C.), Boston, MA, USA; Division of Aging (K.C.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Medicine (J.S.L., T.L.A.), Stanford University School of Medicine, Stanford, CA, 94304, USA; VA Palo Alto Health Care System (J.S.L., T.L.A.), Palo Alto, CA, 94304, USA; Department of Population and Quantitative Health Sciences (S.K.I), and Department of Genetics and Genome Sciences (S.K.I.), School of Medicine, Case Western Reserve University, Cleveland, OH 44106; VA Northeast Ohio Healthcare System (S.K.I.), Cleveland VA Medical Center, Cleveland, OH 44106; VA Portland Health Care System (S.-W.L.), Portland, OR 97239; Division of Infectious Diseases (R.S.), Department of Medicine, University of Wisconsin, Madison, WI; William S. Middleton Memorial Veterans Hospital (R.S.), Madison, WI 53705; and Sema4 (E.E.S.), Stamford, CT 06902, USA.
Background:
Recent efforts have identified genetic loci that are associated with coronavirus disease 2019 (COVID-19) infection rates and disease outcome severity. Translating these genetic findings into druggable genes and readily available compounds that reduce COVID-19 host susceptibility is a critical next step.
Methods:
We integrate COVID-19 genetic susceptibility variants, multi-tissue genetically regulated gene expression (GReX) and perturbargen signatures to identify candidate genes and compounds that reverse the predicted gene expression dysregulation associated with COVID-19 susceptibility. The top candidate gene is validated by testing both its GReX and observed blood transcriptome association with COVID-19 severity, as well as by in vitro perturbation to quantify effects on viral load and molecular pathway dysregulation. We validate the in silico drug repositioning analysis by examining whether the top candidate compounds decrease COVID-19 incidence based on epidemiological evidence.
Results:
We identify IL10RB as the top key regulator of COVID-19 host susceptibility. Predicted GReX up-regulation of IL10RB and higher IL10RB expression in COVID-19 patient blood is associated with worse COVID-19 outcomes. In vitro IL10RB overexpression is associated with increased viral load and activation of immune-related molecular pathways. Azathioprine and retinol are prioritized as candidate compounds to reduce the likelihood of testing positive for COVID-19.
Conclusions:
We establish an integrative data-driven approach for gene target prioritization. We identify and validate IL10RB as a suitable molecular target for modulation of COVID-19 host susceptibility. Finally, we provide evidence for a few readily available medications that would warrant further investigation as drug repositioning candidates.
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