Baltramonaityte, Vilte, Pingault, Jean-Baptiste, Cecil, Charlotte A. M., Choudhary, Priyanka, Järvelin, Marjo-Riitta, Penninx, Brenda W. J. H., Felix, Janine, Sebert, Sylvain, Milaneschi, Yuri, and Walton, Esther
Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity (Neffective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately genetically correlated with T2D (rg = 0.39, P = 2e-34) and weakly correlated with depression (rg = 0.13, P = 3e-6). Depression was weakly correlated with T2D (rg = 0.15, P = 4e-15). The latent multimorbidity factor explained the largest proportion of variance in T2D (45%), followed by CAD (35%) and depression (5%). We identified 11 independent SNPs associated with multimorbidity and 18 putative multimorbidity-associated genes. We observed enrichment in immune and inflammatory pathways. A greater polygenic risk score for multimorbidity in the UK Biobank (N = 306,734) was associated with the co-occurrence of CAD, T2D and depression (OR per standard deviation = 1.91, 95% CI = 1.74–2.10, relative to the healthy group), validating this latent multimorbidity factor. Mendelian randomization analyses suggested potentially causal effects of BMI, body fat percentage, LDL cholesterol, total cholesterol, fasting insulin, income, insomnia, and childhood maltreatment. These findings advance our understanding of multimorbidity suggesting common genetic pathways. Author summary: While observational research has shown a substantial degree of overlap between depression, coronary artery disease and type 2 diabetes, few studies have attempted to identify genetic variants associated with multimorbidity between these conditions. Here, we explore the shared genetic architecture of depression, coronary artery disease and type 2 diabetes (i.e., psycho-cardiometabolic diseases) and examine common genetic variants associated with the co-occurrence of these conditions. Employing a novel method for performing multivariate genome-wide association studies, we show that there are 11 independent genetic variants across nine distinct genomic risk loci associated with psycho-cardiometabolic multimorbidity. We observe enrichment in immune and inflammation-related pathways and identify 18 multimorbidity-associated genes. We show that the polygenic risk score developed based on our multimorbidity genome-wide association study is predictive of the co-occurrence of depression, coronary artery disease and type 2 diabetes in an independent sample. Lastly, we identify eight potentially causal risk factors for multimorbidity. These results advance our understanding of the shared genetic influences in psycho-cardiometabolic diseases. [ABSTRACT FROM AUTHOR]