Prioritizing Observational Associations With Family History of Disease and Mendelian Randomization

Abstract

Elucidating the biological relevance of risk factors of chronic multifactorial disease is indispensable for identifying new putative intervention targets for disease prevention and therapeutic development. However, discovering novel associations in chronic disease and inferring causality is a challenge. There remains an unmet need for identifying associations between modifiable factors and phenotypes to uncover biological relevance in presence of confounding or reverse causality. One such tool is family history of disease, which reflects the effects of genetics and modifiable factors, including environment, and behavioral factors, and is a major risk factor for chronic disease, including type 2 diabetes and cardiovascular disease. Another tool is Mendelian randomization (MR), a statistical technique that leverages genetic variation for uncovering causal relationships between potentially modifiable exposures and outcomes. We propose to leverage family history of disease and MR to prioritize observational associations in chronic disease, thereby identifying potentially novel associations that may help elucidate the underlying biological (genetic and/or environmental) mechanisms by which risk factors cause disease.