A description of large-scale metabolomics studies: increasing value by combining metabolomics with genome-wide SNP genotyping and transcriptional profiling

被引：22

作者：

Homuth, Georg ^{[1
]}

Teumer, Alexander ^{[1
]}

Voelker, Uwe ^{[1
]}

Nauck, Matthias ^{[2
]}

机构：

[1] Univ Med Greifswald, Interfaculty Inst Genet & Funct Genom, Dept Funct Genom, D-17487 Greifswald, Germany

[2] Univ Med Greifswald, Inst Clin Chem & Lab Med, D-17487 Greifswald, Germany

来源：

JOURNAL OF ENDOCRINOLOGY | 2012年 / 215卷 / 01期

关键词：

KIDNEY-FUNCTION; ASSOCIATION; LOCI; DISEASE; EXPRESSION; RISK;

D O I：

10.1530/JOE-12-0144

中图分类号：

R5 [内科学];

学科分类号：

100201 [内科学];

摘要：

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 nongenetic factors. Metabolic traits can be related to genetic polymorphisms in genome-wide association studies, enabling the identification of underlying genetic factors, as well as to specific phenotypes, resulting in the identification of metabolome signatures primarily caused by nongenetic 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 give an outlook on future developments. Journal of Endocrinology (2012) 215, 17-28

引用

页码：17 / 28

页数：12

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