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Approved Research

Identifying risk factors of complex diseases: observational and genetic associations

Principal Investigator: Dr Xiaoyan Huang
Approved Research ID: 73684
Approval date: February 8th 2022

Lay summary

Causality is the core issue of scientific research. In traditional observational research, confounding and reverse causality often interfere with research results; randomized controlled trials are often restricted by ethical concerns, costs, noncompliance with intervention, and external validity. Mendelian randomization studies use genetic variation as an instrumental variable for exposure factors, providing a new and effective way for causal inference. This project is based on the database of UK Biobank (general population, about 500,000 cases), comprehensively using a variety of Mendelian randomization designs and analysis methods to carry out several genetic epidemiological research topics in the field of major chronic diseases, and verify the research hypothesis of causal inference which are unclear in the traditional study design. Results or our study are expected to identify the causes and risk factors of common major chronic diseases, and provide more reliable evidence for future treatment target selection, new drug development, intervention strategy formulation, and conduction of randomized controlled trials.