Design and Analysis of Metabolomics Studies in Epidemiologic Research: A Primer on -Omic Technologies

被引:148
作者
Tzoulaki, Ioanna [1 ,2 ]
Ebbels, Timothy M. D. [3 ]
Valdes, Ana [4 ]
Elliott, Paul [1 ,2 ]
Ioannidis, John P. A. [5 ,6 ,7 ,8 ]
机构
[1] Univ London Imperial Coll Sci Technol & Med, Dept Epidemiol & Biostat, London, England
[2] Univ London Imperial Coll Sci Technol & Med, MRC PHE Ctr Environm & Hlth, London, England
[3] Univ London Imperial Coll Sci Technol & Med, Dept Surg & Canc, London, England
[4] City Hosp Nottingham, Fac Med & Hlth Sci, Nottingham, England
[5] Stanford Univ, Sch Med, Stanford Prevent Res Ctr, Dept Med, Stanford, CA 94305 USA
[6] Univ Sch Med, Dept Hlth Res & Policy, Stanford, CA USA
[7] Stanford Univ, Dept Stat, Sch Humanities & Sci, Stanford, CA 94305 USA
[8] Meta Res Innovat Ctr Stanford, Stanford, CA USA
关键词
metabolic profiling; metabolome-wide association studies; metabolomics; MASS-SPECTROMETRY DATA; LIQUID-CHROMATOGRAPHY; VALIDATION PRACTICES; IMPROVED PREDICTION; BIOMARKERS; RISK; IDENTIFICATION; METABONOMICS; ASSOCIATION; REGRESSION;
D O I
10.1093/aje/kwu143
中图分类号
R1 [预防医学、卫生学];
学科分类号
100235 [预防医学];
摘要
Metabolomics is the field of "-omics" research concerned with the comprehensive characterization of the small low-molecular-weight metabolites in biological samples. In epidemiology, it represents an emerging technology and an unprecedented opportunity to measure environmental and other exposures with improved precision and far less measurement error than with standard epidemiologic methods. Advances in the application of metabolomics in large-scale epidemiologic research are now being realized through a combination of improved sample preparation and handling, automated laboratory and processing methods, and reduction in costs. The number of epidemiologic studies that use metabolic profiling is still limited, but it is fast gaining popularity in this area. In the present article, we present a roadmap for metabolomic analyses in epidemiologic studies and discuss the various challenges these data pose to large-scale studies. We discuss the steps of data preprocessing, univariate and multivariate data analysis, correction for multiplicity of comparisons with correlated data, and finally the steps of cross-validation and external validation. As data from metabolomic studies accumulate in epidemiology, there is a need for large-scale replication and synthesis of findings, increased availability of raw data, and a focus on good study design, all of which will highlight the potential clinical impact of metabolomics in this field.
引用
收藏
页码:129 / 139
页数:11
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