Uncovering cell-type-specific immunomodulatory variants and molecular phenotypes in COVID-19 using structurally resolved protein networks
Immunomodulatory variants that lead to the loss or gain of specific protein interactions often manifest only as organismal phenotypes in infectious disease. Here, we propose a network-based approach to integrate genetic variation with a structurally resolved human protein interactome network to prioritize immunomodulatory variants in COVID-19. We find that, in addition to variants that pass genome-wide significance thresholds, variants at the interface of specific protein-protein interactions, even though they do not meet genome-wide thresholds, are equally immunomodulatory. The integration of these variants with single-cell epigenomic and transcriptomic data prioritizes myeloid and T cell subsets as the most affected by these variants across both the peripheral blood and the lung compartments. Of particular interest is a common coding variant that disrupts the OAS1-PRMT6 interaction and affects downstream interferon signaling. Critically, our framework is generalizable across infectious disease contexts and can be used to implicate immunomodulatory variants that do not meet genome-wide significance thresholds.
Authors
- Reinhard Hinterleitner (ORCID: https://orcid.org/0000-0002-6518-108X)
- Munesh Kumar Harioudh (ORCID: https://orcid.org/0000-0003-2921-8604)
- Prabal Chhibbar (ORCID: https://orcid.org/0000-0003-1666-5050)
- Harinder Singh (ORCID: https://orcid.org/0000-0002-6330-8526)
- Donghui Yang (ORCID: https://orcid.org/0000-0002-1516-9875)
- Saumendra N. Sarkar (ORCID: https://orcid.org/0000-0002-2850-6121)
- Daniel J. McGrail (ORCID: https://orcid.org/0000-0002-6669-6069)
- Nidhi Sahni (ORCID: https://orcid.org/0000-0002-9155-5882)
- S. Stephen Yi (ORCID: https://orcid.org/0000-0003-0047-8103)
- Jishnu Das (ORCID: https://orcid.org/0000-0002-5747-064X)
- Yi‐Nan Gong (ORCID: https://orcid.org/0000-0002-3643-4682)
- P. Roy
Institutions
- Livestrong Foundation (US)
- Cleveland Clinic (US)
- The University of Texas MD Anderson Cancer Center (US)
- University of Pittsburgh (US)
- Baylor College of Medicine (US)
- Cleveland Clinic Lerner College of Medicine (US)
- Quantitative BioSciences (US)
- The University of Texas at Austin (US)
Publication Details
- Journal
- Cell Reports
- Published
- 2024-11-01
- DOI
- https://doi.org/10.1016/j.celrep.2024.114930
- Citations
- 2
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.47
Funders
- Cancer Prevention and Research Institute of Texas
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases
- University of Pittsburgh
- National Institutes of Health
- National Human Genome Research Institute
- National Institute of General Medical Sciences
- National Institute of Allergy and Infectious Diseases