Thursday, November 27, 2008

GWAS of metabolite profiles

This is great, and somewhat appropriate for Thanksgiving.

An important issue in deciphering the genetic basis for traits is appropriate phenotype definition. In this study, they look at the association between metabolic by-products in individuals and their genetic profile. These metabolites represent a better phenotype since they are more proximal to the genetic/biochemical pathways that happen within cells, compared to the clinically assessed symptoms of a "disease." Not only does this give us a more appropriate and well-defined phenotype, it's also a phenotype that can be measured on a continuous scale.

The subjects are from Germany and they briefly dismiss the possibility of population stratification: "Also, recent experimental assessment has found little population stratification to exist within and across Germany [33]". Ironically, the latest European genetic structure study, see my last blog post, showed some stratification within Germany - granted, probably not too big of a deal for this study, but it's just funny

Blood samples were obtained in the morning after overnight fasting. In the future, I can imagine collecting samples after feeding of some sugary or fatty meal to get even better measures of metabolic variation.

Genetics Meets Metabolomics: A Genome-Wide Association Study of Metabolite Profiles in Human Serum.
Gieger C, Geistlinger L, Altmaier E, Hrabe´ de Angelis M, Kronenberg F, et al.
PLoS Genet (2008)4(11): e1000282. doi:10.1371/journal.pgen.1000282
Abstract: The rapidly evolving field of metabolomics aims at comprehensive measurement of ideally all endogenous metabolites in a cell or body fluid. It thereby provides a functional readout of the physiological state of the human body. Genetic variants that associate with changes in the homeostasis of key lipids, carbohydrates, or amino acids are not only expected to display much larger effect sizes due to their direct involvement in metabolite conversion modification, but should also provide access to the biochemical context of such variations, in particular when enzyme coding genes are concerned. To test this hypothesis, we conducted what is, to the best of our knowledge, the first GWA study with metabolomics based on the quantitative measurement of 363 metabolites in serum of 284 male participants of the KORA study. We found associations of frequent single nucleotide polymorphisms (SNPs) with considerable differences in the metabolic homeostasis of the human body, explaining up to 12% of the observed variance. Using ratios of certain metabolite concentrations as a proxy for enzymatic activity, up to 28% of the variance can be explained (p-values 10216 to 10221). We identified four genetic variants in genes coding for enzymes (FADS1, LIPC, SCAD, MCAD) where the corresponding metabolic phenotype (metabotype) clearly matches the biochemical pathways in which these enzymes are active. Our results suggest that common genetic polymorphisms induce major differentiations in the metabolic make-up of the human population. This may lead to a novel approach to personalized health care based on a combination of genotyping and metabolic characterization. These genetically determined metabotypes may subscribe the risk for a certain medical phenotype, the response to a given drug treatment, or the reaction to a nutritional intervention or environmental challenge.

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