Literature DB >> 27543620

Comparison of Collection Methods for Fecal Samples for Discovery Metabolomics in Epidemiologic Studies.

Erikka Loftfield1, Emily Vogtmann2, Joshua N Sampson3, Steven C Moore2, Heidi Nelson4,5, Rob Knight6,7, Nicholas Chia4,5,8, Rashmi Sinha2.   

Abstract

BACKGROUND: The gut metabolome may be associated with the incidence and progression of numerous diseases. The composition of the gut metabolome can be captured by measuring metabolite levels in the feces. However, there are little data describing the effect of fecal sample collection methods on metabolomic measures.
METHODS: We collected fecal samples from 18 volunteers using four methods: no solution, 95% ethanol, fecal occult blood test (FOBT) cards, and fecal immunochemical test (FIT). One set of samples was frozen after collection (day 0), and for 95% ethanol, FOBT, and FIT, a second set was frozen after 96 hours at room temperature. We evaluated (i) technical reproducibility within sample replicates, (ii) stability after 96 hours at room temperature for 95% ethanol, FOBT, and FIT, and (iii) concordance of metabolite measures with the putative "gold standard," day 0 samples without solution.
RESULTS: Intraclass correlation coefficients (ICC) estimating technical reproducibility were high for replicate samples for each collection method. ICCs estimating stability at room temperature were high for 95% ethanol and FOBT (median ICC > 0.87) but not FIT (median ICC = 0.52). Similarly, Spearman correlation coefficients (rs) estimating metabolite concordance with the "gold standard" were higher for 95% ethanol (median rs = 0.82) and FOBT (median rs = 0.70) than for FIT (median rs = 0.40).
CONCLUSIONS: Metabolomic measurements appear reproducible and stable in fecal samples collected with 95% ethanol or FOBT. Concordance with the "gold standard" is highest with 95% ethanol and acceptable with FOBT. IMPACT: Future epidemiologic studies should collect feces using 95% ethanol or FOBT if interested in studying fecal metabolomics. Cancer Epidemiol Biomarkers Prev; 25(11); 1483-90. ©2016 AACR. ©2016 American Association for Cancer Research.

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Year:  2016        PMID: 27543620      PMCID: PMC5093035          DOI: 10.1158/1055-9965.EPI-16-0409

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  40 in total

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