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A Network Medicine Approach to Investigation and Population-based Validation of Disease Manifestations and Drug Repurposing for COVID-19.
Zhou, Yadi; Hou, Yuan; Shen, Jiayu; Kallianpur, Asha; Zein, Joe; Culver, Daniel A; Farha, Samar; Comhair, Suzy; Fiocchi, Claudio; Gack, Michaela U; Mehra, Reena; Stappenbeck, Thaddeus; Chan, Timothy; Eng, Charis; Jung, Jae U; Jehi, Lara; Erzurum, Serpil; Cheng, Feixiong.
  • Zhou Y; Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Hou Y; Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Shen J; Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Kallianpur A; Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Zein J; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA.
  • Culver DA; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA.
  • Farha S; Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Comhair S; Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Fiocchi C; Department of Pulmonary Medicine, Respiratory Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Gack MU; Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Mehra R; Department of Pulmonary Medicine, Respiratory Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Stappenbeck T; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA.
  • Chan T; Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Eng C; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA.
  • Jung JU; Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Jehi L; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA.
  • Erzurum S; Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Cheng F; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA.
ChemRxiv ; 2020 Jul 02.
Article in English | MEDLINE | ID: covidwho-1027422
Preprint
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ABSTRACT
The global Coronavirus Disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to unprecedented social and economic consequences. The risk of morbidity and mortality due to COVID-19 increases dramatically in the presence of co-existing medical conditions while the underlying mechanisms remain unclear. Furthermore, there are no proven effective therapies for COVID-19. This study aims to identify SARS-CoV-2 pathogenesis, diseases manifestations, and COVID-19 therapies using network medicine methodologies along with clinical and multi-omics observations. We incorporate SARS-CoV-2 virus-host protein-protein interactions, transcriptomics, and proteomics into the human interactome. Network proximity measure revealed underlying pathogenesis for broad COVID-19-associated manifestations. Multi-modal analyses of single-cell RNA-sequencing data showed that co-expression of ACE2 and TMPRSS2 was elevated in absorptive enterocytes from the inflamed ileal tissues of Crohn's disease patients compared to uninflamed tissues, revealing shared pathobiology by COVID-19 and inflammatory bowel disease. Integrative analyses of metabolomics and transcriptomics (bulk and single-cell) data from asthma patients indicated that COVID-19 shared intermediate inflammatory endophenotypes with asthma (including IRAK3 and ADRB2). To prioritize potential treatment, we combined network-based prediction and propensity score (PS) matching observational study of 18,118 patients from a COVID-19 registry. We identified that melatonin (odds ratio (OR) = 0.36, 95% confidence interval (CI) 0.22-0.59) was associated with 64% reduced likelihood of a positive laboratory test result for SARS-CoV-2. Using PS-matching user active comparator design, melatonin was associated with 54% reduced likelihood of SARS-CoV-2 positive test result compared to angiotensin II receptor blockers or angiotensin-converting enzyme inhibitors (OR = 0.46, 95% CI 0.24-0.86).

Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Year: 2020 Document Type: Article Affiliation country: Chemrxiv.12579137.v1

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Year: 2020 Document Type: Article Affiliation country: Chemrxiv.12579137.v1