Sources of Variability in Metabolite Measurements from Urinary Samples

Qian Xiao, Steven C Moore, Simina M Boca, Charles E Matthews, Nathaniel Rothman, Rachael Z Stolzenberg-Solomon, Rashmi Sinha, Amanda J Cross and Joshua N Sampson

PLOS ONE, 2014, vol. 9, issue 5, 1-8

Abstract: Background: The application of metabolomics in epidemiological studies would potentially allow researchers to identify biomarkers associated with exposures and diseases. However, within-individual variability of metabolite levels caused by temporal variation of metabolites, together with technical variability introduced by laboratory procedures, may reduce the study power to detect such associations. We assessed the sources of variability of metabolites from urine samples and the implications for designing epidemiologic studies. Methods: We measured 539 metabolites in urine samples from the Navy Colon Adenoma Study using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectroscopy (GC-MS). The study collected 2–3 samples per person from 17 male subjects (age 38–70) over 2–10 days. We estimated between-individual, within-individual, and technical variability and calculated expected study power with a specific focus on large case-control and nested case-control studies. Results: Overall technical reliability was high (median intraclass correlation = 0.92), and for 72% of the metabolites, the majority of total variance can be attributed to between-individual variability. Age, gender and body mass index explained only a small proportion of the total metabolite variability. For a relative risk (comparing upper and lower quartiles of “usual” levels) of 1.5, we estimated that a study with 500, 1,000, and 5,000 individuals could detect 1.0%, 4.5% and 75% of the metabolite associations. Conclusions: The use of metabolomics in urine samples from epidemiological studies would require large sample sizes to detect associations with moderate effect sizes.

Date: 2014
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0095749 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 95749&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0095749

DOI: 10.1371/journal.pone.0095749

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone (plosone@plos.org).