Cross-sectional metabolic subgroups and 10-year follow-up of cardiometabolic multimorbidity in the UK Biobank.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
21 05 2022
Historique:
received: 13 01 2022
accepted: 29 04 2022
entrez: 21 5 2022
pubmed: 22 5 2022
medline: 25 5 2022
Statut: epublish

Résumé

We assigned 329,908 UK Biobank participants into six subgroups based on a self-organizing map of 51 biochemical measures (blinded for clinical outcomes). The subgroup with the most favorable metabolic traits was chosen as the reference. Hazard ratios (HR) for incident disease were modeled by Cox regression. Enrichment ratios (ER) of incident multi-morbidity versus randomly expected co-occurrence were evaluated by permutation tests; ER is like HR but captures co-occurrence rather than event frequency. The subgroup with high urinary excretion without kidney stress (HR = 1.24) and the subgroup with the highest apolipoprotein B and blood pressure (HR = 1.52) were associated with ischemic heart disease (IHD). The subgroup with kidney stress, high adiposity and inflammation was associated with IHD (HR = 2.11), cancer (HR = 1.29), dementia (HR = 1.70) and mortality (HR = 2.12). The subgroup with high liver enzymes and triglycerides was at risk of diabetes (HR = 15.6). Multimorbidity was enriched in metabolically favorable subgroups (3.4 ≤ ER ≤ 4.0) despite lower disease burden overall; the relative risk of co-occurring disease was higher in the absence of obvious metabolic dysfunction. These results provide synergistic insight into metabolic health and its associations with cardiovascular disease in a large population sample.

Identifiants

pubmed: 35597771
doi: 10.1038/s41598-022-12198-1
pii: 10.1038/s41598-022-12198-1
pmc: PMC9124207
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

8590

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

© 2022. The Author(s).

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Auteurs

Anwar Mulugeta (A)

Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, Australia.

Elina Hyppönen (E)

Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, Australia.

Mika Ala-Korpela (M)

Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.
Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.
NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland.

Ville-Petteri Mäkinen (VP)

Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, Australia. ville-petteri.makinen@sahmri.com.
Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland. ville-petteri.makinen@sahmri.com.
Computational and Systems Biology Program, Precision Medicine Theme, South Australian Health and Medical Research Institute, Adelaide, Australia. ville-petteri.makinen@sahmri.com.

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