| Title: | The combined impact of persistent infections and human genetic variation on C-reactive protein levels |
| Journal: | BMC Medicine |
| Published: | 1 Nov 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36320076/ |
| DOI: | https://doi.org/10.1186/s12916-022-02607-7 |
| URL: | https://bmcmedicine.biomedcentral.com/counter/pdf/10.1186/s12916-022-02607-7 |
Publication 10640
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Abstract
Multiple human pathogens establish chronic, sometimes life-long infections. Even if they are often latent, these infections can trigger some degree of local or systemic immune response, resulting in chronic low-grade inflammation. There remains an incomplete understanding of the potential contribution of both persistent infections and human genetic variation on chronic low-grade inflammation. We searched for potential associations between seropositivity for 13 persistent pathogens and the plasma levels of the inflammatory biomarker C-reactive protein (CRP), using data collected in the context of the UK Biobank and the CoLaus|PsyCoLaus Study, two large population-based cohorts. We performed backward stepwise regression starting with the following potential predictors: serostatus for each pathogen, polygenic risk score for CRP, and demographic and clinical factors known to be associated with CRP. We found evidence for an association between Chlamydia trachomatis (P-value = 5.04e − 3) and Helicobacter pylori (P-value = 8.63e − 4) seropositivity and higher plasma levels of CRP. We also found an association between pathogen burden and CRP levels (P-value = 4.12e − 4). These results improve our understanding of the relationship between persistent infections and chronic inflammation, an important determinant of long-term morbidity in humans.</p>
9 Authors
- Flavia Hodel
- Olivier Naret
- Clara Bonnet
- Nicole Brenner
- Noemi Bender
- Tim Waterboer
- Pedro Marques-Vidal
- Peter Vollenweider
- Jacques Fellay
1 Application
| Application ID | Title |
|---|---|
| 50085 | Human genomics of humoral immunity and chronic inflammation: searching for predictors of complex diseases. |
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