Constructing a consensus serum metabolome

2025 · doi:10.1101/2025.05.07.652782
preprint OA: closed
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The study aims to construct a consensus serum metabolome reference to support metabolite annotation and cross-laboratory alignment, using a newly developed data structure and tooling. The authors assembled the consensus metabolome from more than 100,000 LC-MS mass spectrometry acquisitions comprising over 200 million spectra, and report a comprehensive survey of human blood chemistry that shows frequency-dependent patterns in the metabolome and exposome. A key finding is that substantial gaps remain between the consensus serum metabolome and current metabolomics databases, and that the new reference improves annotation quality and enables community-level data alignment. The paper’s limitation is that it is focused on serum LC-MS acquisitions and highlights discrepancies with existing databases and methods rather than directly addressing disease-specific outcomes. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Blood analysis is the most common in biomedical applications and a reference metabolome will be critical for effective annotation and for guiding scientific investigations. However, compiling such a reference is hindered by many technical challenges, despite the availability of large amount of metabolomics data today. Based on a new set of data structures and tools, we have assembled a consensus serum metabolome (CSM) from over 100,000 mass spectrometry acquisitions of more than 200 million spectra. This provides a comprehensive survey of human blood chemistry, revealing the frequency dependent nature of metabolome and exposome. Major gaps are found between CSM and the current databases. The CSM enables community-level data alignment and significantly improves annotation quality of LC-MS metabolomics. Highlights A reference of human biochemistry linked to observation frequency Major gaps revealed in current databases and experimental methods Enabling cross-laboratory, cross-platform data alignment Accelerated and cumulative metabolite annotation
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Abstract Blood analysis is the most common in biomedical applications and a reference metabolome will be critical for effective annotation and for guiding scientific investigations. However, compiling such a reference is hindered by many technical challenges, despite the availability of large amount of metabolomics data today. Based on a new set of data structures and tools, we have assembled a consensus serum metabolome (CSM) from over 100,000 mass spectrometry acquisitions of more than 200 million spectra. This provides a comprehensive survey of human blood chemistry, revealing the frequency dependent nature of metabolome and exposome. Major gaps are found between CSM and the current databases. The CSM enables community-level data alignment and significantly improves annotation quality of LC-MS metabolomics. Highlights A reference of human biochemistry linked to observation frequency Major gaps revealed in current databases and experimental methods Enabling cross-laboratory, cross-platform data alignment Accelerated and cumulative metabolite annotation Competing Interest Statement The authors have declared no competing interest.

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