title: Metabolic profiling and the metabolome-wide association study: significance level for biomarker identification.
abstract: High throughput metabolic profiling via the metabolome-wide association study (MWAS) is a powerful new approach to identify biomarkers of disease risk, but there are methodological challenges: high dimensionality, high level of collinearity, the existence of peak overlap within metabolic spectral data, multiple testing, and selection of a suitable significance threshold. We define the metabolome-wide significance level (MWSL) as the threshold required to control the family wise error rate through a permutation approach. We used 1H NMR spectroscopic profiles of 24 h urinary collections from the INTERMAP study. Our results show that the MWSL primarily depends on sample size and spectral resolution. The MWSL estimates can be used to guide selection of discriminatory biomarkers in MWA studies. In a simulation study, we compare statistical performance of the MWSL approach to two variants of orthogonal partial least-squares (OPLS) method with respect to statistical power, false positive rate and correspondence of ranking of the most significant spectral variables. Our results show that the MWSL approach as estimated by the univariate t test is not outperformed by OPLS and offers a fast and simple method to detect disease-related discriminatory features in human NMR urinary metabolic profiles.
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London W2 1PG, United Kingdom.
authors.forename: Marc
authors.initials: M
authors.lastname: Chadeau-Hyam
authors.forename: Timothy M D
authors.initials: TM
authors.lastname: Ebbels
authors.forename: Ian J
authors.initials: IJ
authors.lastname: Brown
authors.forename: Queenie
authors.initials: Q
authors.lastname: Chan
authors.forename: Jeremiah
authors.initials: J
authors.lastname: Stamler
authors.forename: Chiang Ching
authors.initials: CC
authors.lastname: Huang
authors.forename: Martha L
authors.initials: ML
authors.lastname: Daviglus
authors.forename: Hirotsugu
authors.initials: H
authors.lastname: Ueshima
authors.forename: Liancheng
authors.initials: L
authors.lastname: Zhao
authors.forename: Elaine
authors.initials: E
authors.lastname: Holmes
authors.forename: Jeremy K
authors.initials: JK
authors.lastname: Nicholson
authors.forename: Paul
authors.initials: P
authors.lastname: Elliott
authors.forename: Maria
authors.initials: M
authors.lastname: De Iorio
mesh_terms: D015415:Biomarkers / Q000737:chemistry / Q000378:metabolism* / Q000652:urine; D016000:Cluster Analysis; D003198:Computer Simulation; D057166:High-Throughput Screening Assays / Q000379:methods*; D006801:Humans; D016018:Least-Squares Analysis; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*; D008954:Models, Biological; D019906:Nuclear Magnetic Resonance, Biomolecular; D012372:ROC Curve; D012016:Reference Values; D014556:Urine / Q000737:chemistry
chemical_list: D015415:Biomarkers