Genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis

Ana L Aruda; April E Hartley; Georgia  Katsoula; George Davey Smith; Andrew P Morris; Eleftheria Zeggini

doi:10.1016/j.ajhg.2023.06.010

Genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis

Ana L Aruda^*
, April E Hartley
, Georgia Katsoula
, George Davey Smith
, Andrew P Morris
, Eleftheria Zeggini^*

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

32 Citations (Scopus)

Abstract

Multimorbidity is a rising public health challenge with important implications for health management and policy. The most common multimorbidity pattern is for 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.

Original language	English
Pages (from-to)	1304-1318
Number of pages	15
Journal	American Journal of Human Genetics
Volume	110
Issue number	8
DOIs	https://doi.org/10.1016/j.ajhg.2023.06.010
Publication status	Published - 10 Jul 2023

Bibliographical note

Funding Information:
We thank Lorraine Southam and Konstantinos Hatzikotoulas for their input and support. We also thank the Genetics of Osteoarthritis (GO) and the DIAMANTE and the InsPIRE consortia for providing their data. E.Z. and A.L.A. conceived and designed the study and wrote the manuscript. A.L.A. and A.H. performed computation and statistical analyses and produced the figures. A.L.A. G.D.S. A.H. E.Z. and A.P.M. performed data interpretation. A.L.A. G.D.S. A.H. E.Z. G.K. and A.P.M. provided significant feedback on the methods, results, and manuscript. A.H. and G.D.S. work in a unit funded by the Medical Research Council (MRC) and the University of Bristol (MC_UU_00011/1, MC_UU_00011/3).

Funding Information:
A.H. and G.D.S. work in a unit funded by the Medical Research Council (MRC) and the University of Bristol (MC_UU_00011/1, MC_UU_00011/3).

Publisher Copyright:
© 2023 The Author(s)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Research Groups and Themes

Bristol Population Health Science Institute

Access to Document

10.1016/j.ajhg.2023.06.010Licence: CC BY

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Persistent link

IEU: MRC Integrative Epidemiology Unit Quinquennial renewal
Gaunt, L. F. (Principal Investigator) & Davey Smith, G. (Principal Investigator)
1/04/18 → 31/03/23
Project: Research

Cite this

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title = "Genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis",

abstract = "Multimorbidity is a rising public health challenge with important implications for health management and policy. The most common multimorbidity pattern is for 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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note = "Funding Information: We thank Lorraine Southam and Konstantinos Hatzikotoulas for their input and support. We also thank the Genetics of Osteoarthritis (GO) and the DIAMANTE and the InsPIRE consortia for providing their data. E.Z. and A.L.A. conceived and designed the study and wrote the manuscript. A.L.A. and A.H. performed computation and statistical analyses and produced the figures. A.L.A. G.D.S. A.H. E.Z. and A.P.M. performed data interpretation. A.L.A. G.D.S. A.H. E.Z. G.K. and A.P.M. provided significant feedback on the methods, results, and manuscript. A.H. and G.D.S. work in a unit funded by the Medical Research Council (MRC) and the University of Bristol (MC\_UU\_00011/1, MC\_UU\_00011/3). Funding Information: A.H. and G.D.S. work in a unit funded by the Medical Research Council (MRC) and the University of Bristol (MC\_UU\_00011/1, MC\_UU\_00011/3). Publisher Copyright: {\textcopyright} 2023 The Author(s)",

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AU - Aruda, Ana L

AU - Hartley, April E

AU - Katsoula, Georgia

AU - Davey Smith, George

AU - Morris, Andrew P

AU - Zeggini, Eleftheria

N1 - Funding Information: We thank Lorraine Southam and Konstantinos Hatzikotoulas for their input and support. We also thank the Genetics of Osteoarthritis (GO) and the DIAMANTE and the InsPIRE consortia for providing their data. E.Z. and A.L.A. conceived and designed the study and wrote the manuscript. A.L.A. and A.H. performed computation and statistical analyses and produced the figures. A.L.A. G.D.S. A.H. E.Z. and A.P.M. performed data interpretation. A.L.A. G.D.S. A.H. E.Z. G.K. and A.P.M. provided significant feedback on the methods, results, and manuscript. A.H. and G.D.S. work in a unit funded by the Medical Research Council (MRC) and the University of Bristol (MC_UU_00011/1, MC_UU_00011/3). Funding Information: A.H. and G.D.S. work in a unit funded by the Medical Research Council (MRC) and the University of Bristol (MC_UU_00011/1, MC_UU_00011/3). Publisher Copyright: © 2023 The Author(s)

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N2 - Multimorbidity is a rising public health challenge with important implications for health management and policy. The most common multimorbidity pattern is for 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.

AB - Multimorbidity is a rising public health challenge with important implications for health management and policy. The most common multimorbidity pattern is for 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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JO - American Journal of Human Genetics

JF - American Journal of Human Genetics

IS - 8

ER -

Genetic underpinning of the comorbidity between type 2 diabetes and osteoarthritis

Abstract

Bibliographical note

UN SDGs

Research Groups and Themes

Access to Document

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Projects

IEU: MRC Integrative Epidemiology Unit Quinquennial renewal

Cite this