Notes
Human polyomaviruses are widespread in humans and can cause severe disease in immunocompromised individuals. To identify human genetic determinants of the humoral immune response against polyomaviruses, we performed genome-wide association studies and meta-analyses of qualitative and quantitative immunoglobulin G responses against BK polyomavirus (BKPyV), JC polyomavirus (JCPyV), Merkel cellpolyomavirus (MCPyV), WU polyomavirus (WUPyV), and human polyomavirus 6 (HPyV6) in 15,660 individuals of European ancestry from three independent studies. We observed significant associations for all tested viruses: JCPyV, HPyV6, and MCPyV associated with human leukocyte antigen class II variation, BKPyV and JCPyV with variants in FUT2, responsible for secretor status, MCPyV with variants in STING1, involved in interferon induction, and WUPyV with a functional variant in MUC1, previously associated with risk for gastric cancer. These results provide insights into the genetic control of a family of very prevalent human viruses, highlighting genes and pathways that play a modulating role in human humoral immunity.
Application 50085
Human genomics of humoral immunity and chronic inflammation: searching for predictors of complex diseases.
We propose to harness the power of large-scale genomic analysis to understand the interactions between human genetic variants, persistent infections, chronic inflammation and complex human diseases of major public health importance.
Combing data collected in the context of the UK Biobank cohort and the Swiss CoLaus cohort, this study aims to identify the major genomic determinants of humoral immune responses against multiple persistent human pathogens. A GWAS strategy will also be used to describe the influence of human genetic factors on the plasma levels of inflammatory biomarkers (e.g. CRP), which are correlated with certain persistent infections. Genetic risk scores will be built to summarize the combined effect of associated variants on infectious and inflammatory phenotypes. Finally, we will develop statistical models to explore the respective and combined influences of genetic variation, persistent infections and low-grade inflammation on complex human diseases (coronary artery disease and neurodegenerative disorders). These analyses have the potential to elucidate important pathogenic mechanisms. From a translational perspective, outcomes of this project could thus include novel disease biomarkers, better prediction models, or innovative targets for diagnostic or therapeutic development.
Lead investigator: | Professor Jacques Fellay |
Lead institution: | Ecole Polytechnique Federale de Lausanne (EPFL) |