Human serum metabolic profiles are age dependent

Abstract

Summary 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, αcorr = 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.

Effects of Metformin on Metabolite Profiles and LDL Cholesterol in Patients With Type 2 Diabetes

“…The levels of metabolites depend on multiple modifiable factors, such as lifestyle and environment (9)(10)(11)(13)(14)(15)(16). We therefore considered a number of confounding effects, e.g., physiological parameters (age, sex, BMI, and systolic BP), lifestyle (physical activity, alcohol intake, and smoking), glucose levels (HbA 1c and fasting glucose), lipid levels (HDL-C and triglycerides), and medication usage (statins, b-blockers, ACE inhibitors, and ARBs).…”

“…The assay procedures were previously described in detail (27). For KORA S4 and F4, identical qualitycontrol procedures (9,13), which are explained in details in our previous publications, were used. In KORA F4, 131 metabolites of the initially targeted 163 metabolites passed all quality-control criteria: hexose (H1), 24 acylcarnitines, 14 amino acids, 13 sphingomyelines, 34 phosphatidylcholines (PCs), diacyl (aa), 37 PCs acyl-alkyl (ae), and 8 lysoPCs.…”

“…Metabolomic studies have detected metabolite profile changes during the development of T2D (9)(10)(11)(12) and identified concentration differences caused by various physiological and environmental factors such as age (13), sex (14), smoking status (15), and alcohol consumption (16). Several metabolomic studies attempted to unravel the physiological effects of metformin (17)(18)(19)(20)(21).…”

Demographic and clinical variables affecting mid‐ to late‐life trajectories of plasma ceramide and dihydroceramide species

“…Thus, the homeostasis of ceramide metabolism may be critical in regulating lifespan and age‐associated diseases (Cutler & Mattson, 2001; Rao et al ., 2007). Indeed, it has been increasingly recognized, from the cellular to human level, that perturbations in ceramide metabolism are associated with longevity (Yu et al ., 2012; Gonzalez‐Covarrubias et al ., 2013; Cutler et al ., 2014; Huang et al ., 2014) and the development and progression of many age‐related diseases including cancer (Alberg et al ., 2013), atherosclerosis (Ichi et al ., 2006), insulin resistance and diabetes (Holland et al ., 2007; Holland & Summers, 2008; Boon et al ., 2013), Alzheimer's disease (Mielke et al ., 2012), and Parkinson's disease (Mielke et al ., 2013). …”

Integration of ‘omics’ data in aging research: from biomarkers to systems biology

“…Yu et al . (2012) analysed 131 targeted metabolites in 2162 individuals from the KORA study, while we analysed 280 untargeted metabolites in 6055 twins from the TwinsUK cohort (Menni et al ., 2013b). Both studies identified half of the analysed metabolites to be associated with chronological age.…”