title: Human serum metabolic profiles are age dependent.
abstract: Understanding the complexity of aging is of utmost importance. This can now be addressed by the novel and powerful approach of metabolomics. However, to date, only a few metabolic studies based on large samples are available. Here, we provide novel and specific information on age-related metabolite concentration changes in human homeostasis. We report results from two population-based studies: the KORA F4 study from Germany as a discovery cohort, with 1038 female and 1124 male participants (32-81 years), and the TwinsUK study as replication, with 724 female participants. Targeted metabolomics of fasting serum samples quantified 131 metabolites by FIA-MS/MS. Among these, 71/34 metabolites were significantly associated with age in women/men (BMI adjusted). We further identified a set of 13 independent metabolites in women (with P values ranging from 4.6 × 10(-04) to 7.8 × 10(-42) , α(corr) = 0.004). Eleven of these 13 metabolites were replicated in the TwinsUK study, including seven metabolite concentrations that increased with age (C0, C10:1, C12:1, C18:1, SM C16:1, SM C18:1, and PC aa C28:1), while histidine decreased. These results indicate that metabolic profiles are age dependent and might reflect different aging processes, such as incomplete mitochondrial fatty acid oxidation. The use of metabolomics will increase our understanding of aging networks and may lead to discoveries that help enhance healthy aging.
authors: Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
authors: Zhonghao
authors: Z
authors: Yu
authors: Guangju
authors: G
authors: Zhai
authors: Paula
authors: P
authors: Singmann
authors: Ying
authors: Y
authors: He
authors: Tao
authors: T
authors: Xu
authors: Cornelia
authors: C
authors: Prehn
authors: Werner
authors: W
authors: Römisch-Margl
authors: Eva
authors: E
authors: Lattka
authors: Christian
authors: C
authors: Gieger
authors: Nicole
authors: N
authors: Soranzo
authors: Joachim
authors: J
authors: Heinrich
authors: Marie
authors: M
authors: Standl
authors: Elisabeth
authors: E
authors: Thiering
authors: Kirstin
authors: K
authors: Mittelstraß
authors: Heinz-Erich
authors: HE
authors: Wichmann
authors: Annette
authors: A
authors: Peters
authors: Karsten
authors: K
authors: Suhre
authors: Yixue
authors: Y
authors: Li
authors: Jerzy
authors: J
authors: Adamski
authors: Tim D
authors: TD
authors: Spector
authors: Thomas
authors: T
authors: Illig
authors: Rui
authors: R
authors: Wang-Sattler
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000097:blood*; D015415:Biomarkers / Q000097:blood*; D015992:Body Mass Index; D005227:Fatty Acids / Q000378:metabolism; D005260:Female; D017022:Flow Injection Analysis; D006801:Humans; D008297:Male; D055442:Metabolome / Q000502:physiology*; D055432:Metabolomics; D008875:Middle Aged; D015999:Multivariate Analysis; D010084:Oxidation-Reduction; D012737:Sex Factors; D053719:Tandem Mass Spectrometry
chemical_list: D015415:Biomarkers; D005227:Fatty Acids