alexa Metabolomics in epidemiology: sources of variability in metabolite measurements and implications.
Chemical Engineering

Chemical Engineering

Journal of Analytical & Bioanalytical Techniques

Author(s): Sampson JN, Boca SM, Shu XO, StolzenbergSolomon RZ, Matthews CE,

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Abstract BACKGROUND: Metabolite levels within an individual vary over time. This within-individual variability, coupled with technical variability, reduces the power for epidemiologic studies to detect associations with disease. Here, the authors assess the variability of a large subset of metabolites and evaluate the implications for epidemiologic studies. METHODS: Using liquid chromatography/mass spectrometry (LC/MS) and gas chromatography-mass spectroscopy (GC/MS) platforms, 385 metabolites were measured in 60 women at baseline and year-one of the Shanghai Physical Activity Study, and observed patterns were confirmed in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening study. RESULTS: Although the authors found high technical reliability (median intraclass correlation = 0.8), reliability over time within an individual was low. Taken together, variability in the assay and variability within the individual accounted for the majority of variability for 64\% of metabolites. Given this, a metabolite would need, on average, a relative risk of 3 (comparing upper and lower quartiles of "usual" levels) or 2 (comparing quartiles of observed levels) to be detected in 38\%, 74\%, and 97\% of studies including 500, 1,000, and 5,000 individuals. Age, gender, and fasting status factors, which are often of less interest in epidemiologic studies, were associated with 30\%, 67\%, and 34\% of metabolites, respectively, but the associations were weak and explained only a small proportion of the total metabolite variability. CONCLUSION: Metabolomics will require large, but feasible, sample sizes to detect the moderate effect sizes typical for epidemiologic studies. IMPACT: We offer guidelines for determining the sample sizes needed to conduct metabolomic studies in epidemiology.
This article was published in Cancer Epidemiol Biomarkers Prev and referenced in Journal of Analytical & Bioanalytical Techniques

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