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

EarlyCause consortium

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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.

Original languageEnglish
Article numbere1010508
JournalPlos Genetics
Issue number6
Publication statusPublished - 30 Jun 2023

Bibliographical note

Funding Information:
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 848158 (EarlyCause). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We are grateful to the UK Biobank and all its voluntary participants. We also thank all 23andMe research participants who made this study possible.

Data Availability:
To access summary statistics for psycho-cardiometabolic multimorbidity, a data transfer agreement is required with 23andMe ([email protected]) before making a request to the University of Bath Research Data Archive (https://doi.org/10.15125/BATH-01179). Further information regarding access to 23andMe is available at: https://research.23andme.com/collaborate/. Summary statistics for the top 10,000 SNPs generated during this study are available from the University of Bath Research Data Archive: https://doi.org/10.15125/BATH-01179. Summary statistics for coronary artery disease can be obtained from: http://www.cardiogramplusc4d.org. Summary statistics for type 2 diabetes can be obtained from: http://diagram-consortium.org/downloads.html. To access summary statistics for depression, a data transfer agreement is required from 23andMe ([email protected]) before a request is made to David Howard ([email protected]), as described in: https://www.nature.com/articles/s41593-018-0326-7. UK Biobank data can be accessed via an application process outlined here: https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access. Code underlying our analyses can be found on GitHub: https://github.com/VilteBaltra/Psycho-cardiometabolic-multimorbidity.


  • Humans
  • Diabetes Mellitus, Type 2/epidemiology
  • Genome-Wide Association Study
  • Multimorbidity
  • Risk Factors
  • Coronary Artery Disease/epidemiology
  • Mendelian Randomization Analysis
  • Polymorphism, Single Nucleotide/genetics


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