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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)
Verlagsversion DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
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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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Mendelian Randomization ; Colocalization Analysis ; Multimorbidity ; Osteoarthritis ; Statistical Genetics ; Type 2 Diabetes; Body-mass Index; Mendelian Randomization; Association; Identification; Metabolism; Expression; Arthritis; Variants; Pathways; Resource
Sprache englisch
Veröffentlichungsjahr 2023
HGF-Berichtsjahr 2023
ISSN (print) / ISBN 0002-9297
e-ISSN 1537-6605
Zeitschrift American Journal of Human Genetics, The
Quellenangaben Band: 110, Heft: 8, Seiten: 1304-1318 Artikelnummer: , Supplement: ,
Verlag Elsevier
Verlagsort New York, NY
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Translational Genomics (ITG)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Genetics and Epidemiology
Enabling and Novel Technologies
PSP-Element(e) G-506700-001
G-506701-001
DOI 10.1016/j.ajhg.2023.06.010
WOS ID 001052700800001
Scopus ID 85166585096
PubMed ID 37433298
Erfassungsdatum 2023-10-06
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