Shared genetic loci between depression and cardiometabolic traits

Author summaryStudies have found associations between depression and both cardiovascular disease risk factors and worse cardiovascular disease prognosis. It is unknown if shared genetic factors contribute to these associations. We applied novel statistical tools for polygenic architectures to investigate if there are common genes for depression, coronary artery disease and cardiovascular risk factors (body mass index, blood pressure, lipids, type 2 diabetes and c-reactive protein). We used the statistical methods the bivariate causal mixture model (MiXeR) and the conditional/conjunctional false discovery rate (pleioFDR) to quantify genome-wide overlap and to identify shared genetic variants. We found extensive genetic overlap. Depression shared 68% of genetic variants with body mass index and 14% and with systolic blood pressure. We also identified 79 unique genomic variants associated with depression and coronary artery disease or the risk factors. Variants associated with increased risk for depression also increased the risk of coronary artery disease, some of the lipids and c-reactive protein levels, while there was a mixed pattern of direction for the other risk factors. Further analyses identified shared genetic variants found in metabolism of alpha-linolenic pathway for type 2 diabetes. Epidemiological and clinical studies have found associations between depression and cardiovascular disease risk factors, and coronary artery disease patients with depression have worse prognosis. The genetic relationship between depression and these cardiovascular phenotypes is not known. We here investigated overlap at the genome-wide level and in individual loci between depression, coronary artery disease and cardiovascular risk factors. We used the bivariate causal mixture model (MiXeR) to quantify genome-wide polygenic overlap and the conditional/conjunctional false discovery rate (pleioFDR) method to identify shared loci, based on genome-wide association study summary statistics on depression (n = 450,619), coronary artery disease (n = 502,713) and nine cardiovascular risk factors (n = 204,402-776,078). Genetic loci were functionally annotated using FUnctional Mapping and Annotation (FUMA). Of 13.9K variants influencing depression, 9.5K (SD 1.0K) were shared with body-mass index. Of 4.4K variants influencing systolic blood pressure, 2K were shared with depression. ConjFDR identified 79 unique loci associated with depression and coronary artery disease or cardiovascular risk factors. Six genomic loci were associated jointly with depression and coronary artery disease, 69 with blood pressure, 49 with lipids, 9 with type 2 diabetes and 8 with c-reactive protein at conjFDR < 0.05. Loci associated with increased risk for depression were also associated with increased risk of coronary artery disease and higher total cholesterol, low-density lipoprotein and c-reactive protein levels, while there was a mixed pattern of effect direction for the other risk factors. Functional analyses of the shared loci implicated metabolism of alpha-linolenic acid pathway for type 2 diabetes. Our results showed polygenic overlap between depression, coronary artery disease and several cardiovascular risk factors and suggest molecular mechanisms underlying the association between depression and increased cardiovascular disease risk.