Metabolomics profiling reveals novel markers for leukocyte telomere length.

Author: Zierer J1,2, Kastenmüller G1,2, Suhre K2,3, Gieger C4,5,6, Codd V7, Tsai PC1, Bell J1, Peters A5, Strauch K8, Schulz H9,10, Weidinger S11, Mohney RP12, Samani NJ7,13, Spector T1, Mangino M1,14, Menni C1.
1Department of Twin Research and Genetic Epidemiology, King's College London, London, UK. 2Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany. 3Department of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Doha, Qatar. 4Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. 5Institute of Epidemiologie II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. 6German Center for Diabetes Research, Neuherberg, Germany. 7Department of Cardiovascular Sciences, University of Leicester, Leicester, UK. 8Institute of Genetic Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany. 9Institute of Epidemiology I, Helmholtz Zentrum München, Neuherberg, Germany. 10Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research, Munich, Germany. 11Department of Dermatology, Venereology and Allergy, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany. 12Metabolon, Inc., Durham, NC 27713, USA. 13National Institute for Health Research (NIHR) Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, UK. 14National Institute for Health Research (NIHR) Biomedical Research Centre at Guy's and St. Thomas' Foundation Trust, London, UK.
Conference/Journal: Aging (Albany NY).
Date published: 2016 Jan 20
Other: Word Count: 223

Leukocyte telomere length (LTL) is considered one of the most predictive markers of biological aging. The aim of this study was to identify novel pathways regulating LTL using a metabolomics approach. To this end, we tested associations between 280 blood metabolites and LTL in 3511 females from TwinsUK and replicated our results in the KORA cohort. We furthermore tested significant metabolites for associations with several aging-related phenotypes, gene expression markers and epigenetic markers to investigate potential underlying pathways. Five metabolites were associated with LTL: Two lysolipids, 1-stearoylglycerophosphoinositol (P=1.6×10-5) and 1-palmitoylglycerophosphoinositol (P=1.6×10-5), were found to be negatively associated with LTL and positively associated with phospholipase A2 expression levels suggesting an involvement of fatty acid metabolism and particularly membrane composition in biological aging. Moreover, two gamma-glutamyl amino acids, gamma-glutamyltyrosine (P=2.5×10-6) and gamma-glutamylphenylalanine (P=1.7×10-5), were negatively correlated with LTL. Both are products of the glutathione cycle and markers for increased oxidative stress. Metabolites were also correlated with functional measures of aging, i.e. higher blood pressure and HDL cholesterol levels and poorer lung, liver and kidney function. Our results suggest an involvement of altered fatty acid metabolism and increased oxidative stress in human biological aging, reflected by LTL and age-related phenotypes of vital organ systems.
biological aging; glutathione; metabolomics; oxidative stress; telomere length
PMID: 26797767 [PubMed - as supplied by publisher] Free full text