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Updated: May 13, 2025

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
Published on: May 27, 2014
A Reproducibility Crisis for Clinical Metabolomics Studies
Darcy Cochran1,2, Mai NourEldein1,2, Dominika Bezdekova1
1Department of Chemistry, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588-0304, USA.
Abstract:
Cancer is a leading cause of world-wide death and a major subject of clinical studies focused on the identification of new diagnostic tools. An in-depth meta-analysis of 244 clinical metabolomics studies of human serum samples highlights a reproducibility crisis. A total of 2,206 unique metabolites were reported as statistically significant across the 244 studies, but 72% (1,582) of these metabolites were identified by only one study. Further analysis shows a random disparate disagreement in reported directions of metabolite concentration changes when detected by multiple studies. Statistical models revealed that 1,867 of the 2,206 metabolites (85%) are simply statistical noise. Only 3 to 12% of these metabolites reach the threshold of statistical significance for a specific cancer type. Our findings demonstrate the absence of a detectable metabolic response to cancer and provide evidence of a serious need by the metabolomics community to establish widely accepted best practices to improve future outcomes.
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