Acid metabolism, insulin sensitivity, mitochondrial function as well as blood cell
Acid metabolism, insulin sensitivity, mitochondrial function as well as blood cell development and function. Keywords: Metabolomics, Transcriptomics, Weight change, Obesity, Molecular epidemiology, Bioinformatics* Correspondence: [email protected] Equal contributors 1 Institute of Epidemiology II, Helmholtz Zentrum M chen, German Research Center for Environmental Health, Neuherberg, Germany 2 Research Unit of Molecular Epidemiology, Helmholtz Zentrum M chen, German Research Center for Environmental Health, Neuherberg, Germany Full list of author information is available at the end of the article?2015 Wahl et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Wahl et al. BMC Medicine (2015) 13:Page 2 ofBackground With an estimated 671 million obese individuals worldwide in 2013 [1], obesity has reached epidemic proportions. Considering the manifold health problems associated with excess body weight, including Mdivi-1 web cardiovascular disease and type 2 diabetes, obesity PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/26104484 poses a serious public health problem [2]. Understanding the mechanisms by which excess body weight contributes to cardiometabolic risk is a prerequisite for advances in therapeutic approaches. Despite extensive research, however, the complex molecular basis of body weight-related metabolic perturbations is not fully understood. Advances in the field of high-throughput omics technologies, including metabolomics and transcriptomics, offer the opportunity to simultaneously measure hundreds or thousands of molecules, for example, metabolites and gene transcripts, thereby allowing a deeper characterization of obesity-related pathomechanisms on a molecular level [3]. In recent years, a number of crosssectional efforts suggested a relationship between PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/26100631 obesity and the human blood metabolome (for example, [4-6]) and transcriptome (for example, [7,8]), which extend to different tissues such as adipose tissue [9]. In addition, weight loss upon behavioral intervention was associated with changes in the blood metabolome [5,10], suggesting that the observed obesity-related molecular signatures are at least in part reversible. However, the effect of long-term body weight change on the human blood metabolome and transcriptome in the general population ?rather than under clinical settings ?is less well explored. Few prospective studies have investigated the association of body weight change with concentrations of a larger set of metabolites in healthy subjects and these are restricted to a panel of lipoprotein subclasses [11,12]. In addition, although multiomic approaches have been fruitful in different applications to enhance the understanding of complex molecular pathways (for example, [13-15]), the potential of integrating multiple omics techniques has rarely been used in the study of weight change-associated metabolic effects in humans [5]. Here, we used data from Cooperative Health Research in the Region of Augsburg (KORA) S4/F4, which constitutes a large phenotypically and molecularly well-characterized population-based cohort. We aimed to charact.
