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A systematic analysis of the contribution of genetics to multimorbidity and comparisons with primary care data

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journal contribution
posted on 2025-03-11, 12:15 authored by Olivia Murrin, Ninon Mounier, Bethany Voller, Linus Tata, Carlos Gallego-Moll, Albert Roso-Llorach, Lucía A Carrasco-Ribelles, Chris Fox, Louise M Allan, Ruby M Woodward, Xiaoran Liang, Jose M Valderas, Sara M Khalid, Frank DudbridgeFrank Dudbridge, Sally E Lamb, Mary Mancini, Leon Farmer, Kate Boddy, Jack Bowden, David Melzer, Timothy M Frayling, Jane AH Masoli, Luke C Pilling, Concepción Violán, João Delgado
<p dir="ltr">Background: Multimorbidity, the presence of two or more conditions in one person, is common but studies are often limited to observational data and single datasets. We address this gap by integrating large-scale primary-care and genetic data from multiple studies to interrogate multimorbidity patterns and producing digital resources to support future research. </p><p dir="ltr">Methods: We defined chronic, common, and heritable conditions in individuals aged ≥65 years, using two large primary-care databases [CPRD (UK) N = 2,425,014 and SIDIAP (Spain) N = 1,053,640], and estimated heritability using the same definitions in UK Biobank (N = 451,197). We used logistic regression to estimate the co-occurrence of pairs of conditions in the primary care data. Linkage disequilibrium score regression was used to estimate genetic similarity between pairs of conditions. Meta-analyses were conducted across databases, and up to three sources of genetic data, for each pair of conditions. We classified pairs of conditions as across or within-domain based on the international classification of disease. </p><p dir="ltr">Findings: We identified 72 chronic conditions, with 43.6% of 2546 pairs showing higher co-occurrence than chance in primary care and evidence of shared genetics. Many across-domain pairs exhibited substantial shared genetics (e.g., iron deficiency anaemia and peripheral arterial disease: genetic correlation Rg = 0.45 [95% Confidence Intervals 0.27:0.64]). 33 pairs displayed negative genetic correlations, such as skin cancer and rheumatoid arthritis (Rg = −0.14 [−0.21:−0.06]), due to potential adverse drug effects. Discordance between genetic and primary care data was also observed, e.g., abdominal aortic aneurysm and bladder cancer co-occurred in primary care but were not genetically correlated (Odds-Ratio = 2.23 [2.09:2.37], Rg = 0.04 [−0.20:0.28]) and schizophrenia and fibromyalgia were less likely to co-occur together in primary care but were positively genetically correlated (OR = 0.84 [0.75:0.94], Rg = 0.20 [0.11:0.29]). </p><p dir="ltr">Interpretation: Most pairs of chronic conditions show evidence of shared genetics, and co-occurrence in primary care, suggesting shared mechanisms. The identified patterns of shared genetics, negative correlations and discordance between genetic and observational data provide a foundation for future multimorbidity research. </p><p dir="ltr"><br></p>

Funding

Genetic Evaluation of Multimorbidity towards INdividualisation of Interventions (GEMINI)

UK Research and Innovation

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History

Author affiliation

College of Life Sciences Population Health Sciences

Version

  • VoR (Version of Record)

Published in

eBioMedicine

Volume

113

Pagination

105584 - 105584

Publisher

Elsevier BV

issn

2352-3964

eissn

2352-3964

Acceptance date

2025-01-20

Copyright date

2025

Available date

2025-03-07

Spatial coverage

Netherlands

Language

en

Deposited by

Professor Frank Dudbridge

Deposit date

2025-02-28

Data Access Statement

We cannot make individual-level data available. Researchers can apply to UK Biobank (https://www.ukbiobank.ac.uk/enable-your-research/), CPRD (https://www.cprd.com/research-applications), and SIDIAP (https://www.sidiap.org/index.php/en/solicituds-en). We have made our diagnostic code lists, code and results available on our GitHub (https://github.com/GEMINI-multimorbidity/) site and Shiny website (https://gemini-multimorbidity.shinyapps.io/atlas/). GWAS summary statistics will be available following acceptance at the GWAS Catalog (https://www.ebi.ac.uk/gwas/home).

Rights Retention Statement

  • Yes

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