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Constructing a consensus serum metabolome

Chi, Y.; Mitchell, J.; Thapa, M.; Zheng, S.; Frohock, Z.; Li, Y.; Smirnov, A.; Du, X.; Li, S.

2025-05-11 biochemistry
10.1101/2025.05.07.652782 bioRxiv
Show 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. HighlightsO_LIA reference of human biochemistry linked to observation frequency C_LIO_LIMajor gaps revealed in current databases and experimental methods C_LIO_LIEnabling cross-laboratory, cross-platform data alignment C_LIO_LIAccelerated and cumulative metabolite annotation C_LI

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.