| Title: | Exploring disease-causing traits for drug repurposing in critically ill COVID-19 patients: A causal inference approach |
| Journal: | iScience |
| Published: | 12 Oct 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37965141/ |
| DOI: | https://doi.org/10.1016/j.isci.2023.108185 |
| Citations: | 1 (1 in last 2 years) as of 8 Aug 2024 |
Publication 9392
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Abstract
Despite recent development of vaccines to prevent SARS-CoV-2 infection, treatment of critically ill COVID-19 patients remains an important goal. In principle, genome-wide association studies (GWASs) provide a shortcut to the clinical evidence needed to repurpose existing drugs; however, genes identified frequently lack a causal disease link. We report an alternative method for finding drug repurposing targets, focusing on disease-causing traits beyond immediate disease genetics. Sixty blood cell types and biochemistries, and body mass index, were screened on a cohort of critically ill COVID-19 cases and controls that exhibited mild symptoms after infection, yielding high neutrophil cell count as a possible causal trait for critical illness. Our methodology identified CDK6 and janus kinase (JAK) inhibitors as treatment targets that were validated in an ex vivo neutrophil extracellular trap (NET) formation assay. Our methodology demonstrates the increased power for drug target identification by leveraging large disease-causing trait datasets.</p>
10 Authors
- Hannes A. Baukmann
- Justin L. Cope
- Colin Bannard
- Alexander R.E.C. Schwinges
- Margaretha R.J. Lamparter
- Sarah Groves
- Charles N.J. Ravarani
- Borko Amulic
- Joern E. Klinger
- Marco F. Schmidt
1 Application
| Application ID | Title |
|---|---|
| 36226 | Validation and improvement of our Machine Learning approach to analyze interactions in your genotyping/imputation data for better Familial Hypercholesterolemia diagnostics |
Enabling scientific discoveries that improve human health