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De Santana Villasboas Arruda, A.L. ; Hartley, A.* ; Katsoula, G. ; Smith, G.D.* ; Morris, A.P.* ; Zeggini, E.

Genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis.

Am. J. Hum. Genet. 110, 1304-1318 (2023)
Publ. Version/Full Text DOI PMC
Open Access Gold (Paid Option)
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Multimorbidity is a rising public health challenge with important implications for health management and policy. The most common multimorbidity pattern is the combination of cardiometabolic and osteoarticular diseases. Here, we study the genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis. We find genome-wide genetic correlation between the two diseases and robust evidence for association-signal colocalization at 18 genomic regions. We integrate multi-omics and functional information to resolve the colocalizing signals and identify high-confidence effector genes, including FTO and IRX3, which provide proof-of-concept insights into the epidemiologic link between obesity and both diseases. We find enrichment for lipid metabolism and skeletal formation pathways for signals underpinning the knee and hip osteoarthritis comorbidities with type 2 diabetes, respectively. Causal inference analysis identifies complex effects of tissue-specific gene expression on comorbidity outcomes. Our findings provide insights into the biological basis for the type 2 diabetes-osteoarthritis disease co-occurrence.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Mendelian Randomization ; Colocalization Analysis ; Multimorbidity ; Osteoarthritis ; Statistical Genetics ; Type 2 Diabetes; Body-mass Index; Mendelian Randomization; Association; Identification; Metabolism; Expression; Arthritis; Variants; Pathways; Resource
ISSN (print) / ISBN 0002-9297
e-ISSN 1537-6605
Quellenangaben Volume: 110, Issue: 8, Pages: 1304-1318 Article Number: , Supplement: ,
Publisher Elsevier
Publishing Place New York, NY
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Translational Genomics (ITG)