Lifestyle Modifies the Diabetes-Related Metabolic Risk, Conditional on Individual Genetic Differences.

GxE interaction lifestyle metabolic disease precision medicine type 2 diabetes

Journal

Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621

Informations de publication

Date de publication:
2022
Historique:
received: 17 08 2021
accepted: 10 01 2022
entrez: 31 3 2022
pubmed: 1 4 2022
medline: 1 4 2022
Statut: epublish

Résumé

Metabolic syndrome is a group of heritable metabolic traits that are highly associated with type 2 diabetes (T2DM). Classical interventions to T2DM include individual self-management of environmental risk factors, such as improving diet quality, increasing physical activity, and reducing smoking and alcohol consumption, which decreases the risk of developing metabolic syndrome. However, it is poorly understood how the phenotypes of diabetes-related metabolic traits change with respect to lifestyle modifications at the individual level. In the analysis, we used 12 diabetes-related metabolic traits and eight lifestyle covariates from the UK Biobank comprising 288,837 white British participants genotyped for 1,133,273 genome-wide single nucleotide polymorphisms. We found 16 GxE interactions. Modulation of genetic effects by physical activity was seen for four traits (glucose, HbA1c, C-reactive protein, systolic blood pressure) and by alcohol and smoking for three (BMI, glucose, waist-hip ratio and BMI and diastolic and systolic blood pressure, respectively). We also found a number of significant phenotypic modulations by the lifestyle covariates, which were not attributed to the genetic effects in the model. Overall, modulation in the metabolic risk in response to the level of lifestyle covariates was clearly observed, and its direction and magnitude were varied depending on individual differences. We also showed that the metabolic risk inferred by our model was notably higher in T2DM prospective cases than controls. Our findings highlight the importance of individual genetic differences in the prevention and management of diabetes and suggest that the one-size-fits-all approach may not benefit all.

Identifiants

pubmed: 35356427
doi: 10.3389/fgene.2022.759309
pii: 759309
pmc: PMC8959634
doi:

Types de publication

Journal Article

Langues

eng

Pagination

759309

Subventions

Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom

Informations de copyright

Copyright © 2022 Shin, Zhou, Tan, Hyppönen, Benyamin and Lee.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Jisu Shin (J)

Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, Australia.
UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia.
National Cancer Center, Goyang-si, South Korea.

Xuan Zhou (X)

Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, Australia.
UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia.

Joanne T M Tan (JTM)

Vascular Research Centre, Heart and Vascular Health Program, Lifelong Health Theme, South Australian Health and Medical Research Institute, Adelaide, SA, Australia.
Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia.

Elina Hyppönen (E)

Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, Australia.
UniSA Clinical and Health Sciences, University of South Australia, Adelaide, SA, Australia.
South Australian Health and Medical Research Institute, Adelaide, SA, Australia.

Beben Benyamin (B)

Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, Australia.
UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia.
South Australian Health and Medical Research Institute, Adelaide, SA, Australia.

S Hong Lee (SH)

Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, Australia.
UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia.
South Australian Health and Medical Research Institute, Adelaide, SA, Australia.

Classifications MeSH