Untargeted Metabolome Quantitative Trait Locus Mapping Associates Variation in Urine Glycerate to Mutant Glycerate Kinase
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- 作者：Jean-Baptise Cazier ; Pamela J. Kaisaki ; Kar猫ne Argoud ; Benjamin J. Blaise ; Kirill Veselkov ; Timothy M. D. Ebbels ; Tsz Tsang ; Yulan Wang ; Marie-Th茅r猫se Bihoreau ; Steve C. Mitchell ; Elaine C. Holmes ; John C. Lindon ; James Scott ; Jeremy K. Nicholson ; Marc-Emmanuel Dumas ; Dominique Gauguier
- 刊名：Journal of Proteome Research
- 出版年：2012
- 出版时间：February 3, 2012
- 年：2012
- 卷：11
- 期：2
- 页码：631-642
- 全文大小：1056K
- 年卷期：v.11,no.2(February 3, 2012)
- ISSN：1535-3907
文摘
With successes of genome-wide association studies, molecular phenotyping systems are developed to identify genetically determined disease-associated biomarkers. Genetic studies of the human metabolome are emerging but exclusively apply targeted approaches, which restricts the analysis to a limited number of well-known metabolites. We have developed novel technical and statistical methods for systematic and automated quantification of untargeted NMR spectral data designed to perform robust and accurate quantitative trait locus (QTL) mapping of known and previously unreported molecular compounds of the metabolome. For each spectral peak, six summary statistics were calculated and independently tested for evidence of genetic linkage in a cohort of F2 (129S6xBALB/c) mice. The most significant evidence of linkages were obtained with NMR signals characterizing the glycerate (LOD10-42) at the mutant glycerate kinase locus, which demonstrate the power of metabolomics in quantitative genetics to identify the biological function of genetic variants. These results provide new insights into the resolution of the complex nature of metabolic regulations and novel analytical techniques that maximize the full utilization of metabolomic spectra in human genetics to discover mappable disease-associated biomarkers.