{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,10,4]],"date-time":"2026-10-04T02:53:38Z","timestamp":1791082418059,"version":"4.1.0"},"posted":{"date-parts":[[2024,12,20]]},"group-title":"Genetics","reference-count":79,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T00:00:00Z","timestamp":1734652800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,9,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>The global pandemic caused by the SARS-CoV-2 virus provided an unprecedented opportunity to investigate genetic factors influencing the disease severity of the viral infection. Despite a plethora of recent research on both SARS-CoV-2 and COVID-19, few have taken a systems biology approach to address individual-level variation, especially based on non-European populations.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We analyzed multi-omics data generated at three timepoints from 184 Korean COVID-19 patients with mild or severe symptoms, composed of whole genome sequencing, blood-based single-cell RNA-sequencing (2.15M cells), 195 cytokine profiles, and human leukocyte antigen (HLA) allele data. Expression quantitative trait loci (eQTLs) were called and their biological implications were evaluated.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    We identified disease severity interacting eQTLs (\n                    <jats:italic>n<\/jats:italic>\n                    = 404) and disease progression interacting eQTLs (\n                    <jats:italic>n<\/jats:italic>\n                    = 972) for various cell types. We elucidated a complex regulatory mechanism involving\n                    <jats:italic>HLA<\/jats:italic>\n                    genes and their targets, and identified genetic determinants of cytokine levels. Finally, we show how regulation of interaction-eQTLs (ieQTLs) is established by upstream transcription factors (TFs), illustrating complex regulation of the\n                    <jats:italic>IGFBP7<\/jats:italic>\n                    ieQTL, which is potentially important in conferring differential severity. Our COVID-eQTLs were independently validated against a large-scale single-cell PBMC eQTL dataset (1M-scBloodNL), providing robust cross-dataset replication across cell types.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>This study illuminates an efficient molecular interrogation framework that can be applied toward understanding infectious disease progression in individuals of different genotypes.<\/jats:p>\n                <\/jats:sec>","DOI":"10.1101\/2024.12.18.629144","type":"posted-content","created":{"date-parts":[[2024,12,22]],"date-time":"2024-12-22T03:30:16Z","timestamp":1734838216000},"source":"Crossref","is-referenced-by-count":2,"title":["Integrated analysis of COVID-19 multi-omics data for eQTLs reveals genetic mechanisms underlying disease severity"],"prefix":"10.64898","author":[{"given":"Jeongha","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eun Young","family":"Jeon","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liyang","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Data Science, Dartmouth Cancer Center, Dartmouth College, Hanover, NH, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanna","family":"Durante","sequence":"additional","affiliation":[{"name":"Department of Biomedical Data Science, Dartmouth Cancer Center, Dartmouth College, Hanover, NH, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hye-Yeong","family":"Jo","sequence":"additional","affiliation":[{"name":"Division of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sang Cheol","family":"Kim","sequence":"additional","affiliation":[{"name":"Division of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Woong-Yang","family":"Park","sequence":"additional","affiliation":[{"name":"Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Republic of Korea"},{"name":"Geninus Inc, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyun-Young","family":"Park","sequence":"additional","affiliation":[{"name":"Division of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siming","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Biomedical Data Science, Dartmouth Cancer Center, Dartmouth College, Hanover, NH, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9195-1455","authenticated-orcid":false,"given":"Murim","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026100319250616000_2024.12.18.629144v3.1","doi-asserted-by":"publisher","DOI":"10.1038\/s41576-020-00297-6"},{"key":"2026100319250616000_2024.12.18.629144v3.2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2918-0"},{"key":"2026100319250616000_2024.12.18.629144v3.3","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2700-3"},{"key":"2026100319250616000_2024.12.18.629144v3.4","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30566-3"},{"key":"2026100319250616000_2024.12.18.629144v3.5","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.m1985"},{"key":"2026100319250616000_2024.12.18.629144v3.6","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06355-3"},{"key":"2026100319250616000_2024.12.18.629144v3.7","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-022-04447-0"},{"key":"2026100319250616000_2024.12.18.629144v3.8","unstructured":"Zhang Q , Bastard P , Liu Z , Le Pen J , Moncada-Velez M , Chen J , et al. 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