A description of large-scale metabolomics studies - Increasing value by combining metabolomics with genome-wide SNP genotyping and transcriptional profiling
- G Homuth, Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
- A Teumer, Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
- U Völker, Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
- M Nauck, Institute for Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- Correspondence: Georg Homuth, Email: georg.homuth{at}uni-greifswald.de
Abstract
The metabolome, defined as the reflection of metabolic dynamics derived from parameters measured primarily in easily accessible body fluids such as serum, plasma, and urine, can be considered as the OMICs data pool that is closest to the phenotype, because it integrates genetic influences as well as non-genetic factors. Metabolic traits can be related to genetic polymorphisms in GWAS, enabling the identification of underlying genetic factors, as well as to specific phenotypes, resulting in the identification of metabolome signatures caused primarily by non-genetic factors. Similarly, correlation of metabolome data with transcriptional or/and proteome profiles of blood cells also produces valuable data, by revealing associations between metabolic changes and mRNA and protein levels. In the last years, the progress in correlating genetic variation and metabolome profiles was most impressive. This review will therefore try to summarize the most important of these studies and to give an outlook on future developments.
- Received 24 April 2012
- Received in final form 6 July 2012
- Accepted 10 July 2012
- Accepted Preprint first posted online on 10 July 2012
