Longitudinal profiling of metabolic ageing trends in two population cohorts of young adults

Author:

Mäkinen Ville-Petteri123ORCID,Karsikas Mari345,Kettunen Johannes3456,Lehtimäki Terho7,Kähönen Mika8ORCID,Viikari Jorma910,Perola Markus61112ORCID,Salomaa Veikko6ORCID,Järvelin Marjo-Riitta5131415,Raitakari Olli T161718,Ala-Korpela Mika34519ORCID

Affiliation:

1. Computational and Systems Biology Program, Precision Medicine Theme, South Australian Health and Medical Research Institute , Adelaide, Australia

2. Australian Centre for Precision Health, University of South Australia , Adelaide, Australia

3. Computational Medicine, Faculty of Medicine, University of Oulu , Oulu, Finland

4. Biocenter Oulu , Oulu, Finland

5. Center for Life Course Health Research, Faculty of Medicine, University of Oulu , Oulu, Finland

6. Department of Public Health and Welfare, Finnish Institute for Health and Welfare , Helsinki, Finland

7. Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University , Tampere, Finland

8. Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University , Tampere, Finland

9. Department of Medicine, University of Turku , Turku, Finland

10. Division of Medicine, Turku University Hospital , Turku, Finland

11. Institute for Molecular Medicine (FIMM), University of Helsinki , Helsinki, Finland

12. Estonian Genome Center, University of Tartu , Tartu, Estonia

13. Unit of Primary Health Care, Oulu University Hospital, OYS , Oulu, Finland

14. Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London , London, UK

15. Department of Life Sciences, College of Health and Life Sciences, Brunel University London , UK

16. Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku , Turku, Finland

17. Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital , Turku, Finland

18. Centre for Population Health Research, University of Turku and Turku University Hospital

19. NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland , Kuopio, Finland

Abstract

Abstract Background Quantification of metabolic changes over the human life course is essential to understanding ageing processes. Yet longitudinal metabolomics data are rare and long gaps between visits can introduce biases that mask true trends. We introduce new ways to process quantitative time-series population data and elucidate metabolic ageing trends in two large cohorts. Methods Eligible participants included 1672 individuals from the Cardiovascular Risk in Young Finns Study and 3117 from the Northern Finland Birth Cohort 1966. Up to three time points (ages 24–49 years) were analysed by nuclear magnetic resonance metabolomics and clinical biochemistry (236 measures). Temporal trends were quantified as median change per decade. Sample quality was verified by consistency of shared biomarkers between metabolomics and clinical assays. Batch effects between visits were mitigated by a new algorithm introduced in this report. The results below satisfy multiple testing threshold of P < 0.0006. Results Women gained more weight than men (+6.5% vs +5.0%) but showed milder metabolic changes overall. Temporal sex differences were observed for C-reactive protein (women +5.1%, men +21.1%), glycine (women +5.2%, men +1.9%) and phenylalanine (women +0.6%, men +3.5%). In 566 individuals with ≥+3% weight gain vs 561 with weight change ≤−3%, divergent patterns were observed for insulin (+24% vs −10%), very-low-density-lipoprotein triglycerides (+32% vs −6%), high-density-lipoprotein2 cholesterol (−6.5% vs +4.7%), isoleucine (+5.7% vs −6.0%) and C-reactive protein (+25% vs −22%). Conclusion We report absolute and proportional trends for 236 metabolic measures as new reference material for overall age-associated and specific weight-driven changes in real-world populations.

Funder

Academy of Finland

Novo Nordisk foundation

Oulu Health and Wellfare Center, Social Insurance Institution of Finland

Competitive State Research Financing of the Expert Responsibility area of Kuopio

ERDF European Regional Development Fund

Social Insurance Institution of Finland

Kuopio, Tampere and Turku University Hospitals

Juho Vainio Foundation

Paavo Nurmi Foundation

Finnish Foundation for Cardiovascular Research

Finnish Cultural Foundation

The Sigrid Juselius Foundation

Tampere Tuberculosis Foundation

Emil Aaltonen Foundation

Yrjö Jahnsson Foundation

Signe and Ane Gyllenberg Foundation

Diabetes Research Foundation of Finnish Diabetes Association

European Union’s Horizon 2020

European Research Council

Tampere University Hospital Supporting Foundation and Finnish Society of Clinical Chemistry

Publisher

Oxford University Press (OUP)

Subject

General Medicine,Epidemiology

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