Published in

Oxford University Press, International Journal of Epidemiology, 6(51), p. 1970-1983, 2022

DOI: 10.1093/ije/dyac062

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

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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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.