Longitudinal profiling of metabolic ageing trends in two population cohorts of young adults
Mäkinen, Ville-Petteri; Karsikas, Mari; Kettunen, Johannes; Lehtimäki, Terho; Kähönen, Mika; Viikari, Jorma; Perola, Markus; Salomaa, Veikko; Järvelin, Marjo-Riitta; Raitakari, Olli T; Ala-Korpela, Mika (2022-04-20)
Mäkinen, Ville-Petteri
Karsikas, Mari
Kettunen, Johannes
Lehtimäki, Terho
Kähönen, Mika
Viikari, Jorma
Perola, Markus
Salomaa, Veikko
Järvelin, Marjo-Riitta
Raitakari, Olli T
Ala-Korpela, Mika
Oxford University Press
20.04.2022
Ville-Petteri Mäkinen, Mari Karsikas, Johannes Kettunen, Terho Lehtimäki, Mika Kähönen, Jorma Viikari, Markus Perola, Veikko Salomaa, Marjo-Riitta Järvelin, Olli T Raitakari, Mika Ala-Korpela, Longitudinal profiling of metabolic ageing trends in two population cohorts of young adults, International Journal of Epidemiology, Volume 51, Issue 6, December 2022, Pages 1970–1983, https://doi.org/10.1093/ije/dyac062
https://rightsstatements.org/vocab/InC/1.0/
© The Author(s) 2022; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.
https://rightsstatements.org/vocab/InC/1.0/
© The Author(s) 2022; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.
https://rightsstatements.org/vocab/InC/1.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202401101160
https://urn.fi/URN:NBN:fi:oulu-202401101160
Tiivistelmä
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.
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.
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