Investigating the Association Between Body Fat and Depression via Mendelian Randomization

Abstract

Obesity and depression are major public health concerns that are both associated with substantial morbidity and mortality. There is a considerable body of literature linking obesity to the development of depression. Recent studies using Mendelian Randomization indicate that this relationship is causal. Most studies of the obesity-depression association have used body mass index as a measure of obesity. Body mass index is defined as weight (measured in kilograms) divided by the square of height (meters) and therefore does not distinguish between the contributions of fat and non-fat to body weight. To better understand the obesity-depression association, we conduct a Mendelian Randomization study of the relationship between fat mass, non-fat mass, height, and depression, using genome-wide association study results from the UK Biobank (n=332,000) and the Psychiatric Genomics Consortium (n=480,000). Our findings suggest that both fat mass and height (short stature) are causal risk factors for depression, while non-fat mass is not. These results represent important new knowledge on the role of anthropometric measures in the etiology of depression. They also suggest that reducing fat mass will decrease the risk of depression, which lends further support to public health measures aimed at reducing the obesity epidemic.