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Approved Research

Evaluation of causal risk factors for autoimmune diseases: evidence from epidemiological studies, phenome-wide Mendelian randomisation study

Principal Investigator: Professor Dong-qing Ye
Approved Research ID: 62663
Approval date: July 27th 2020

Lay summary

Autoimmune diseases (ADs) are a heterogeneous group of disorders where the body attack and destroy itself, which bring a heavy burden to society and are often debilitating and disabling for affected individuals. Recent large-scale genome-wide association studies (GWASs) have made it possible to understand the genetic architecture of common ADs, such as rheumatoid arthritis, multiple sclerosis, ankylosing spondylitis, gout, inflammatory bowel disease.

Given that relatively lower disease concordance rates between monozygotic twins, environmental exposures including cigarette smoke, sex hormone and dietary factors are also important in the pathogenesis of ADs. However, few risk factors have been robustly validated in epidemiological studies. In this project, we aimed to systematically explore potentially environmental exposures and genetic factors of ADs, and to compare these identified risk factors from previous observation studies and GWASs. By now, no studies have investigated the applicability of a combination of genetic with non-genetic factors and compared them in different populations. Our project therefore seeks to develop risk prediction models containing both genetic and non-genetic risk factors to identify individuals with higher risk of ADs and evaluate the utility and effectiveness in prediction of ADs risk.

To address these issues, we plan to perform a prospective observational study, a phenome-wide mendelian randomization association study and genome-wide associated studies using data from the UK Biobank, our group and other public available datasets. We also develop risk prediction models containing both genetic and non-genetic risk factors to identify individuals with higher risk of ADs and evaluate the utility and effectiveness in prediction of ADs risk. All efforts are expected to be finished in the next 36 months. Our research is expected to expanding our understanding of ADs pathogenesis and may guide individual for risk stratification more accurately for improving prevention and treatment of ADs.