Abstract
Background: Multimorbidity, also known as multiple long-term conditions, is a major public health concern. Internalising and CardioMetabolic MultiMorbidity (ICM-MM) is a common form of mental-physical health multimorbidity, yet its genetic predisposition is largely unknown. We examined the polygenic nature of ICM-MM by assessing single trait-specific polygenic risk scores (PRSTRAIT) and whether combining them could increase the proportion of variance in liability to ICM-MM explained by genetic variation. Methods: We developed PRSTRAIT using PRS-CS and summary statistics from the largest trait-specific GWAS excluding UK Biobank (UKB). We evaluated PRSTRAIT on ICM-MM risk in 206 452 UKB participants (n = 39 311 (19.0%) with ICM-MM) using logistic regression adjusted for gender and 10 genetic principal components, defining ICM-MM as lifetime occurrence of: ≥1 internalising (depression, anxiety, somatoform disorder) traits AND ≥ 1 cardiometabolic traits (type 2 diabetes, obesity, hypertension, dyslipidemia, chronic kidney disease). We used elastic net regression in a 50% training sample to generate ICM-MM-PRSTRAIT: a weighted combination of PRSTRAIT targeting ICM-MM. Results: The strongest associations were between ICM-MM and PRSTRAIT for depression and type 2 diabetes—both odds ratios (OR) 1.18, [95% confidence interval (CI) 1.17–1.20] per standard deviation increase in PRSTRAIT. ICM-MM-PRSTRAIT retained five PRSTRAIT, with stronger associations (OR = 1.31, [95%CI 1.29–1.34]) than any PRSTRAIT in the testing sample. Discussion: Combining several PRS explains more variance in ICM-MM liability than single-trait PRSs alone. ICM-MM-PRSTRAIT is a measure of genetic risk that could be used to examine premorbid stages of ICM-MM in external and youth cohorts, supporting awareness of earlier presentation and potentially avoidance or intervention.
Funding Information
  • Tackling Multimorbidity at Scale Strategic Priorities Fund programme (MR/W014416/1)
  • Medical Research Council
  • National Institute for Health and Care Research
  • Engineering and Physical Sciences Research Council
  • Wellcome Trust GW4-CAT Clinical Doctoral Fellowship (222849/Z/21/Z)

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