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BIOCRATES’ Metabolomics Expertise Provides New Insight into Functional Genomics
News

BIOCRATES’ Metabolomics Expertise Provides New Insight into Functional Genomics

BIOCRATES’ Metabolomics Expertise Provides New Insight into Functional Genomics
News

BIOCRATES’ Metabolomics Expertise Provides New Insight into Functional Genomics

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Researchers at the Helmholtz Zentrum Munchen - German Research Center for Environmental Health recently used Biocrates’ metabolomics expertise in research linking the genetic make-up of an individual to differences in their metabolism. This was the first time that genomics and metabolomics data have been combined in a large, population-based study. The patients’ “metabotypes” were determined and new light was shed into the “black box” of functional genomics. The data combination techniques used in this study can be used in future studies to lower costs or increase statistical significance. The Helmholz Zentrum München team was able to identify genetic variants in many genes responsible for enzymes which perform important tasks in the body’s metabolism of amino acids, lipids, and carbohydrates. BIOCRATES Life Sciences AG identified and quantified metabolites in each participant’s blood samples, and the Ludwig-Maximilians Universitat Munchen (LMU) and Helmholtz Zentrum Munchen teams worked to overlay this data with genetic data. The teams detected major differences in metabolite concentrations and enzyme activities in individuals with different gene variants, confirming that genetic factors influence our metabolism. This combination of metabolomics data and genetic data brings two distinct benefits for scientific and biological understanding: 1) the combined data either increases the significance of the findings for the same cohort size or enables studies to obtain significant hits and findings from smaller cohort sizes, reducing study costs dramatically; 2) the combined data increases biochemical plausibility and can verify mere statistical correlations through mechanistic insight, thus making functional genomics truly “functional.” The results of this study can provide the basis for identifying genetically-induced variations in metabolism. They also show how these variations can predict risks of certain medical phenotypes or possible reactions to medical treatment, nutritional or environmental influences. Future studies can use these results to assess the effects of disease, therapies, diets, and environment on a patient’s physiology. In essence, the study shows that “personalized” metabolism demands “personalized” medicine and nutrition.
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