| Title: | A survey of pathogenic involvement in non-communicable human diseases |
| Journal: | Communications Medicine |
| Published: | 20 Jun 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40542146/ |
| DOI: | https://doi.org/10.1038/s43856-025-00956-x |
| URL: | https://www.nature.com/articles/s43856-025-00956-x.pdf |
Publication 16381
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
BackgroundMany relationships between pathogens and human disease are well-established. However, only a small fraction involve diseases considered non-communicable (NCDs). In this study, we sought to leverage the vast amount of newly available electronic health record data to identify potentially novel pathogen-NCD associations and find additional evidence supporting known associations.MethodsWe leverage data from The UK Biobank and TriNetX to perform a systematic survey across 20 pathogens and 426 diseases, primarily NCDs. To this end, we assess the association between disease status and infection history proxies using a logistic regression-based statistical approach.ResultsOur approach identifies 206 pathogen-disease pairs that replicate in both cohorts. We replicate many established relationships, including Helicobacter pylori, with several gastroenterological diseases and connections between Epstein-Barr virus and both multiple sclerosis and lupus. Overall, our approach identifies evidence of association for 15 pathogens and 96 distinct diseases, including a currently controversial link between human cytomegalovirus (CMV) and ulcerative colitis (UC). We validate the CMV-UC connection through two orthogonal analyses, revealing increased CMV gene expression in UC patients and enrichment for UC genetic risk signal near human genes that have altered expression upon CMV infection.ConclusionsCollectively, these results form a foundation for future investigations into mechanistic roles played by pathogens in the processes underlying NCDs. All results are easily accessible on our website, https://tf.cchmc.org/pathogen-disease.</p>
10 Authors
- Michael Lape
- Daniel Schnell
- Sreeja Parameswaran
- Kevin Ernst
- Shannon O'Connor
- Nathan Salomonis
- Lisa J. Martin
- Brett M. Harnett
- Leah C. Kottyan
- Matthew T. Weirauch
1 Application
| Application ID | Title |
|---|---|
| 47377 | Improved Polygenic Risk Score Calculation and Sub-classification of Disease by the Incorporation of Functional Data. |
Enabling scientific discoveries that improve human health