TY - JOUR
T1 - Effects of smoking and smoking cessation on human serum metabolite profile
T2 - Results from the KORA cohort study
AU - Xu, Tao
AU - Holzapfel, Christina
AU - Dong, Xiao
AU - Bader, Erik
AU - Yu, Zhonghao
AU - Prehn, Cornelia
AU - Perstorfer, Katrin
AU - Jaremek, Marta
AU - Roemisch-Margl, Werner
AU - Rathmann, Wolfgang
AU - Li, Yixue
AU - Wichmann, H. Erich
AU - Wallaschofski, Henri
AU - Ladwig, Karl H.
AU - Theis, Fabian
AU - Suhre, Karsten
AU - Adamski, Jerzy
AU - Illig, Thomas
AU - Peters, Annette
AU - Wang-Sattler, Rui
N1 - Funding Information:
We express our appreciation to all KORA study participants for donating their blood and time. We thank the field staff in Augsburg who conducted the KORA studies. The KORA research platform and the KORA Augsburg studies were initiated and financed by the Helmholtz Zentrum München, which is funded by the German Federal Ministry of Education, Science, Research and Technology and by the State of Bavaria. The KORA study group consists of A. Peters (speaker), J. Heinrich, R. Holle, R. Leidl, C. Meisinger, K. Strauch and their co-workers, who are responsible for the design and conduct of the KORA studies. We thank Julia Scarpa, Katharina Sckell and Arsin Sabunchi for metabolomics measurements performed at the Helmholtz Zentrum München, Genome Analysis Centre, Metabolomics Core Facility. This study was supported in part by a grant from the German Federal Ministry of Education and Research (BMBF) to the German Centre for Diabetes Research (DZD e.V.) and this work was partly supported by the BMBF project ‘Metabolomics of ageing’ (FKZ: 01DO12030) and EU FP7 grant HEALTH-2009-2.2.1-3/242114 (Project OPTiMiSE).
PY - 2013/3/4
Y1 - 2013/3/4
N2 - Background: Metabolomics helps to identify links between environmental exposures and intermediate biomarkers of disturbed pathways. We previously reported variations in phosphatidylcholines in male smokers compared with non-smokers in a cross-sectional pilot study with a small sample size, but knowledge of the reversibility of smoking effects on metabolite profiles is limited. Here, we extend our metabolomics study with a large prospective study including female smokers and quitters.Methods: Using targeted metabolomics approach, we quantified 140 metabolite concentrations for 1,241 fasting serum samples in the population-based Cooperative Health Research in the Region of Augsburg (KORA) human cohort at two time points: baseline survey conducted between 1999 and 2001 and follow-up after seven years. Metabolite profiles were compared among groups of current smokers, former smokers and never smokers, and were further assessed for their reversibility after smoking cessation. Changes in metabolite concentrations from baseline to the follow-up were investigated in a longitudinal analysis comparing current smokers, never smokers and smoking quitters, who were current smokers at baseline but former smokers by the time of follow-up. In addition, we constructed protein-metabolite networks with smoking-related genes and metabolites.Results: We identified 21 smoking-related metabolites in the baseline investigation (18 in men and six in women, with three overlaps) enriched in amino acid and lipid pathways, which were significantly different between current smokers and never smokers. Moreover, 19 out of the 21 metabolites were found to be reversible in former smokers. In the follow-up study, 13 reversible metabolites in men were measured, of which 10 were confirmed to be reversible in male quitters. Protein-metabolite networks are proposed to explain the consistent reversibility of smoking effects on metabolites.Conclusions: We showed that smoking-related changes in human serum metabolites are reversible after smoking cessation, consistent with the known cardiovascular risk reduction. The metabolites identified may serve as potential biomarkers to evaluate the status of smoking cessation and characterize smoking-related diseases.
AB - Background: Metabolomics helps to identify links between environmental exposures and intermediate biomarkers of disturbed pathways. We previously reported variations in phosphatidylcholines in male smokers compared with non-smokers in a cross-sectional pilot study with a small sample size, but knowledge of the reversibility of smoking effects on metabolite profiles is limited. Here, we extend our metabolomics study with a large prospective study including female smokers and quitters.Methods: Using targeted metabolomics approach, we quantified 140 metabolite concentrations for 1,241 fasting serum samples in the population-based Cooperative Health Research in the Region of Augsburg (KORA) human cohort at two time points: baseline survey conducted between 1999 and 2001 and follow-up after seven years. Metabolite profiles were compared among groups of current smokers, former smokers and never smokers, and were further assessed for their reversibility after smoking cessation. Changes in metabolite concentrations from baseline to the follow-up were investigated in a longitudinal analysis comparing current smokers, never smokers and smoking quitters, who were current smokers at baseline but former smokers by the time of follow-up. In addition, we constructed protein-metabolite networks with smoking-related genes and metabolites.Results: We identified 21 smoking-related metabolites in the baseline investigation (18 in men and six in women, with three overlaps) enriched in amino acid and lipid pathways, which were significantly different between current smokers and never smokers. Moreover, 19 out of the 21 metabolites were found to be reversible in former smokers. In the follow-up study, 13 reversible metabolites in men were measured, of which 10 were confirmed to be reversible in male quitters. Protein-metabolite networks are proposed to explain the consistent reversibility of smoking effects on metabolites.Conclusions: We showed that smoking-related changes in human serum metabolites are reversible after smoking cessation, consistent with the known cardiovascular risk reduction. The metabolites identified may serve as potential biomarkers to evaluate the status of smoking cessation and characterize smoking-related diseases.
KW - Metabolic network
KW - Metabolomics
KW - Molecular epidemiology
KW - Smoking
KW - Smoking cessation
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UR - http://www.scopus.com/inward/citedby.url?scp=84874417316&partnerID=8YFLogxK
U2 - 10.1186/1741-7015-11-60
DO - 10.1186/1741-7015-11-60
M3 - Article
C2 - 23497222
AN - SCOPUS:84874417316
SN - 1741-7015
VL - 11
JO - BMC Medicine
JF - BMC Medicine
IS - 1
M1 - 60
ER -
