Background Multimorbidity, the presence of two or more conditions in one person, is increasingly prevalent. Yet shared biological mechanisms of specific pairs of conditions often remain poorly understood. We address this gap by integrating large-scale primary care and genetic data to elucidate potential causes of multimorbidity. Methods We defined chronic, common, and heritable conditions in individuals aged ≥65 years, using two large representative healthcare 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 models 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 healthcare databases, and up to three sources of genetic data, for each condition pair. We classified pairs of conditions as across or within-domain based on the international classification of disease. Findings We identified N=72 chronic conditions, with 43.6% of 2546 pairs showing higher co-occurrence than expected and evidence of shared genetics. Notably, across-domain pairs like iron deficiency anaemia and peripheral arterial disease exhibited substantial shared genetics (genetic correlation Rg=0.45[95% Confidence Intervals 0.27:0.64]). N=33 pairs displayed negative genetic correlations, such as skin cancer and rheumatoid arthritis (Rg=-0.14[-0.21:-0.06]), indicating potential protective mechanisms. Discordance between genetic and primary care data was also observed, e.g., abdominal aortic aneurysm and bladder cancer co-occurred 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 but were positively genetically correlated (OR=0.84[0.75:0.94], Rg=0.20[0.11:0.29]). Interpretation Most pairs of chronic conditions show evidence of shared genetics and co-occurrence in primary care, suggesting shared mechanisms. The identified shared mechanisms, negative correlations and discordance between genetic and observational data provide a foundation for future research on prevention and treatment of multimorbidity. Funding UK Medical Research Council [MR/W014548/1].

ARL is now an employee of AstraZeneca and has interests in the company. The work undertaken here was prior to his appointment. SK's group has received funding support from Amgen BioPharma outside of this work. JB is a part time employee of Novo Nordisk Research Centre Oxford, limited, unrelated to this work. TF has consulted for several pharmaceutical companies. All other authors have no disclosures to declare.

This work was supported by the UK Medical Research Council [grant number MR/W014548/1]. This study was supported by the National Institute for Health and Care Research (NIHR) Exeter Biomedical Research Centre (BRC), the NIHR Leicester BRC, the NIHR Oxford BRC, the NIHR Peninsula Applied Research Collaboration, and the NIHR HealthTech Research Centre. KB is partly funded by the NIHR Applied Research Collaboration South-West Peninsula. JM is funded by an NIHR Advanced Fellowship (NIHR302270). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. CV acknowledges research funding by a "Contratos para la intensificacion de la actividad investigadora en el Sistema Nacional de Salud" contract (INT23/00040) from the Spanish Ministry of Science and Innovation.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

This study was approved by the relevant ethics committees: SIDIAP Scientific and Ethical Committees (19/518-P) on 18/12/2019. The SIDIAP database is based on opt-out presumed consent. If a patient decides to opt out, their routine data would be excluded of the database. CPRD ISAC committee protocol number 23_003109. The Northwest Multi-Centre Research Ethics Committee approved the collection and use of UK Biobank data for health-related research (Research Ethics Committee reference 11/NW/0382). UKB was granted under Application Number 9072.

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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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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).