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


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.

SUBMITTER: Sampson JN 

PROVIDER: S-EPMC3617076 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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

Sampson Joshua N JN   Boca Simina M SM   Shu Xiao Ou XO   Stolzenberg-Solomon Rachael Z RZ   Matthews Charles E CE   Hsing Ann W AW   Tan Yu Ting YT   Ji Bu-Tian BT   Chow Wong-Ho WH   Cai Qiuyin Q   Liu Da Ke DK   Yang Gong G   Xiang Yong Bing YB   Zheng Wei W   Sinha Rashmi R   Cross Amanda J AJ   Moore Steven C SC  

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20130208 4


<h4>Background</h4>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.<h4>Methods</h4>Using liquid chromatography/mass spectrometry (LC/MS) and gas chromatography-mass spectroscopy (GC/MS) platforms, 385 metabolit  ...[more]

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2017-09-13 | GSE100768 | GEO