Reproducibility of genetic risk factors identified for long COVID using combinatorial analysis across US and UK patient cohorts with diverse ancestries
These results demonstrate the reproducibility of long COVID disease signal found by combinatorial analysis, broadly validating the results of the original analysis. They provide compelling evidence for a much broader array of genetic associations with long COVID than previously identified through traditional GWAS studies. This strongly supports the hypothesis that genetic factors play a critical role in determining an individual's susceptibility to long COVID following recovery from acute SARS-CoV-2 infection. It also lends weight to the drug repurposing candidates identified in the original analysis. Together these results may help to stimulate much needed new precision medicine approaches to more effectively diagnose and treat the disease. This is also the first reproduction of long COVID genetic associations across multiple populations with substantially different ancestry distributions. Given the high reproducibility rate across diverse populations, these findings may have broader clinical application and promote better health equity. We hope that this will provide confidence to explore some of these mechanisms and drug targets and help advance research into novel ways to diagnose the disease and accelerate the discovery and selection of better therapeutic options, both in the form of newly discovered drugs and/or the immediate prioritization of coordinated investigations into the efficacy of repurposed drug candidates.
Authors
- Matthew Pearson (ORCID: https://orcid.org/0000-0001-7626-6719)
- Karolina Chocian
- Sayoni Das (ORCID: https://orcid.org/0000-0001-6256-5646)
- Steve Gardner (ORCID: https://orcid.org/0000-0002-5490-3358)
- Jason Sardell (ORCID: https://orcid.org/0000-0002-3791-2201)
- Keith Taylor (ORCID: https://orcid.org/0000-0003-2733-3457)
- Rishi K Gupta (ORCID: https://orcid.org/0000-0002-6257-1285)
- M. Strivens
- A Rochlin
Institutions
- Stamford Hospital (US)
- Valley Medical Center (US)
- BirdLife international (GB)
Publication Details
- Journal
- Journal of Translational Medicine
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1186/s12967-025-06535-x
- Citations
- 6
- Primary Topic
- Long-Term Effects of COVID-19
- Type
- article
- Field-Weighted Citation Impact
- 8.34
Funders
- National Institutes of Health