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Ageing Investigation Using Two-Time-Point Metabolomics Data from KORA and CARLA Studies

Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
Institute of Medical Epidemiology, Biometry and Informatics, Martin-Luther University Halle-Wittenberg, 06108 Halle, Germany
German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
Research Unit of Molecular Endocrinology and Metabolism, Helmholtz Zentrum München, 85764 Neuherberg, Germany
Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117593, Singapore
Institute for Medical Informatics, Biometrics and Epidemiology, Ludwig-Maximilians-Universität München, 81377 München, Germany
Author to whom correspondence should be addressed.
Metabolites 2019, 9(3), 44;
Received: 13 December 2018 / Revised: 26 February 2019 / Accepted: 28 February 2019 / Published: 5 March 2019
(This article belongs to the Special Issue Metabolomics of Complex Traits)
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Ageing, one of the largest risk factors for many complex diseases, is highly interconnected to metabolic processes. Investigating the changes in metabolite concentration during ageing among healthy individuals offers us unique insights to healthy ageing. We aim to identify ageing-associated metabolites that are independent from chronological age to deepen our understanding of the long-term changes in metabolites upon ageing. Sex-stratified longitudinal analyses were performed using fasting serum samples of 590 healthy KORA individuals (317 women and 273 men) who participated in both baseline (KORA S4) and seven-year follow-up (KORA F4) studies. Replication was conducted using serum samples of 386 healthy CARLA participants (195 women and 191 men) in both baseline (CARLA-0) and four-year follow-up (CARLA-1) studies. Generalized estimation equation models were performed on each metabolite to identify ageing-associated metabolites after adjusting for baseline chronological age, body mass index, physical activity, smoking status, alcohol intake and systolic blood pressure. Literature researches were conducted to understand their biochemical relevance. Out of 122 metabolites analysed, we identified and replicated five (C18, arginine, ornithine, serine and tyrosine) and four (arginine, ornithine, PC aa C36:3 and PC ae C40:5) significant metabolites in women and men respectively. Arginine decreased, while ornithine increased in both sexes. These metabolites are involved in several ageing processes: apoptosis, mitochondrial dysfunction, inflammation, lipid metabolism, autophagy and oxidative stress resistance. The study reveals several significant ageing-associated metabolite changes with two-time-point measurements on healthy individuals. Larger studies are required to confirm our findings. View Full-Text
Keywords: ageing; chronological age; targeted metabolomics; longitudinal study; amino acids ageing; chronological age; targeted metabolomics; longitudinal study; amino acids

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Chak, C.M.; Lacruz, M.E.; Adam, J.; Brandmaier, S.; Covic, M.; Huang, J.; Meisinger, C.; Tiller, D.; Prehn, C.; Adamski, J.; Berger, U.; Gieger, C.; Peters, A.; Kluttig, A.; Wang-Sattler, R. Ageing Investigation Using Two-Time-Point Metabolomics Data from KORA and CARLA Studies. Metabolites 2019, 9, 44.

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