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Updated: May 6, 2026

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS

Published on: March 14, 2013

Constructing a consensus serum metabolome.

Yuanye Chi¹, Joshua M Mitchell¹, Maheshwor Thapa¹

¹The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA.

Biorxiv : the Preprint Server for Biology

|July 14, 2025

Summary

This summary is machine-generated.

Researchers created a consensus serum metabolome (CSM) from millions of mass spectrometry spectra. This comprehensive human blood chemistry survey improves data alignment and metabolomics annotation quality.

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Last Updated: May 6, 2026

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS

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Published on: March 14, 2013

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Area of Science:

Biomedical applications
Metabolomics
Mass spectrometry

Background:

Blood analysis is crucial in biomedical research.
Compiling a reference metabolome is challenging due to technical hurdles.
Existing metabolomics data is abundant but lacks standardization.

Purpose of the Study:

To assemble a comprehensive consensus serum metabolome (CSM).
To address limitations in current metabolomics databases and annotation.
To facilitate community-level data alignment and improve scientific investigations.

Main Methods:

Utilized novel data structures and tools.
Processed over 100,000 mass spectrometry acquisitions.
Analyzed more than 200 million spectra to build the CSM.

Main Results:

Successfully assembled a consensus serum metabolome (CSM).
Revealed the frequency-dependent nature of metabolome and exposome.
Identified significant gaps between CSM and existing databases.
Demonstrated improved annotation quality for LC-MS metabolomics.

Conclusions:

The CSM provides a vital reference for human blood chemistry.
CSM enhances data alignment and annotation accuracy in metabolomics.
This resource is critical for future biomedical and scientific investigations.