A multivariate genome-wide association study of psycho-cardiometabolic multimorbidity

Abstract

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.

Fig 1. A Common Factor Model for Psycho-Cardiometabolic Multimorbidity.

Unstandardized coefficients (SE) on the left and standardized coefficients (SE) on the right for the genetically defined common factor of multimorbidity. The model uses unit variance identification for the latent factor. All paths are significant at P < 2e-13. MM, multimorbidity; CAD, coronary artery disease; T2D, type 2 diabetes; MD, major depression; U, residual variance.

Fig 2. Manhattan and LocusZoom Plots of the Multivariate GWAS of Psycho-Cardiometabolic Multimorbidity.

(A) A Manhattan plot displaying the results for the multivariate GWAS of psycho-cardiometabolic multimorbidity obtained using Genomic SEM (with Diagonally Weighted Least Squares estimation). The y axis depicts–log10(P) values for variants associated with multimorbidity. The dashed, horizontal grey line denotes the genome-wide significance threshold at P = 5e-8. Points above the grey line represent genome-wide significant hits. The black diamonds represent independent hits. The grey stars represent independent SNPs with evidence for heterogeneous effects (Q_SNP P < 5e−8 and directionally discordant univariate effect estimates). (B, C, D) Regional plots centered on three top variants (rs10789340, rs2043539 and rs2004910, respectively) that have comparable univariate estimates across coronary artery disease, type 2 diabetes and depression. Coding genes are shown in the panel below. The blue line represents the recombination rate.

Fig 3. Out-of-Sample Prediction for Phenotypic Psycho-Cardiometabolic Multimorbidity or Single Diseases using Polygenic Risk Scores.

(A) Multimorbidity polygenic risk score across groups of individuals with no, any one, two or three diseases. (B) Four polygenic risk scores for MD, CAD, T2D, and multimorbidity across groups of individuals with no, any one, two or three diseases. MD, major depression; CAD, coronary artery disease; T2D, type 2 diabetes; MM, multimorbidity; PRS, polygenic risk score.

Fig 4. Scatter plots of Two-Sample Mendelian Randomization results.

Scatter plots showing SNP effects of body mass index (A), body fat percentage (B), LDL cholesterol (C), total cholesterol (D), fasting insulin (E), income (F), insomnia (G), and childhood maltreatment (H) on psycho-cardiometabolic multimorbidity. The slopes represent estimates from the primary (inverse variance weighted) and sensitivity analyses (MR-Egger, simple mode, weighted median, weighted mode). MR, Mendelian randomization; LDL, low-density lipoprotein; SNP, single nucleotide polymorphism.