Dataset Information

Reference Standardization for Quantification and Harmonization of Large-Scale Metabolomics.

ABSTRACT: Reference standardization was developed to address quantification and harmonization challenges for high-resolution metabolomics (HRM) data collected across different studies or analytical methods. Reference standardization relies on the concurrent analysis of calibrated pooled reference samples at predefined intervals and enables a single-step batch correction and quantification for high-throughput metabolomics. Here, we provide quantitative measures of approximately 200 metabolites for each of three pooled reference materials (220 metabolites for Qstd3, 211 metabolites for CHEAR, 204 metabolites for NIST1950) and show application of this approach for quantification supports harmonization of metabolomics data collected from 3677 human samples in 17 separate studies analyzed by two complementary HRM methods over a 17-month period. The results establish reference standardization as a method suitable for harmonizing large-scale metabolomics data and extending capabilities to quantify large numbers of known and unidentified metabolites detected by high-resolution mass spectrometry methods.

SUBMITTER: Liu KH

PROVIDER: S-EPMC7887762 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Reference Standardization for Quantification and Harmonization of Large-Scale Metabolomics.

Liu Ken H KH Nellis Mary M Uppal Karan K Ma Chunyu C Tran ViLinh V Liang Yongliang Y Walker Douglas I DI Jones Dean P DP

Analytical chemistry 20200615 13

Reference standardization was developed to address quantification and harmonization challenges for high-resolution metabolomics (HRM) data collected across different studies or analytical methods. Reference standardization relies on the concurrent analysis of calibrated pooled reference samples at predefined intervals and enables a single-step batch correction and quantification for high-throughput metabolomics. Here, we provide quantitative measures of approximately 200 metabolites for each of ...[more]

PMID: 32490663

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Project description:The exposome is the cumulative measure of environmental influences and associated biological responses throughout the lifespan, including exposures from the environment, diet, behavior, and endogenous processes. A major challenge for exposome research lies in the development of robust and affordable analytic procedures to measure the broad range of exposures and associated biologic impacts occurring over a lifetime. Biomonitoring is an established approach to evaluate internal body burden of environmental exposures, but use of biomonitoring for exposome research is often limited by the high costs associated with quantification of individual chemicals. High-resolution metabolomics (HRM) uses ultra-high resolution mass spectrometry with minimal sample preparation to support high-throughput relative quantification of thousands of environmental, dietary, and microbial chemicals. HRM also measures metabolites in most endogenous metabolic pathways, thereby providing simultaneous measurement of biologic responses to environmental exposures. The present research examined quantification strategies to enhance the usefulness of HRM data for cumulative exposome research. The results provide a simple reference standardization protocol in which individual chemical concentrations in unknown samples are estimated by comparison to a concurrently analyzed, pooled reference sample with known chemical concentrations. The approach was tested using blinded analyses of amino acids in human samples and was found to be comparable to independent laboratory results based on surrogate standardization or internal standardization. Quantification was reproducible over a 13-month period and extrapolated to thousands of chemicals. The results show that reference standardization protocol provides an effective strategy that will enhance data collection for cumulative exposome research. In principle, the approach can be extended to other types of mass spectrometry and other analytical methods.

Project description:BackgroundThere are presently hundreds of online databases hosting millions of chemical compounds and associated data. As a result of the number of cheminformatics software tools that can be used to produce the data, subtle differences between the various cheminformatics platforms, as well as the naivety of the software users, there are a myriad of issues that can exist with chemical structure representations online. In order to help facilitate validation and standardization of chemical structure datasets from various sources we have delivered a freely available internet-based platform to the community for the processing of chemical compound datasets.ResultsThe chemical validation and standardization platform (CVSP) both validates and standardizes chemical structure representations according to sets of systematic rules. The chemical validation algorithms detect issues with submitted molecular representations using pre-defined or user-defined dictionary-based molecular patterns that are chemically suspicious or potentially requiring manual review. Each identified issue is assigned one of three levels of severity - Information, Warning, and Error - in order to conveniently inform the user of the need to browse and review subsets of their data. The validation process includes validation of atoms and bonds (e.g., making aware of query atoms and bonds), valences, and stereo. The standard form of submission of collections of data, the SDF file, allows the user to map the data fields to predefined CVSP fields for the purpose of cross-validating associated SMILES and InChIs with the connection tables contained within the SDF file. This platform has been applied to the analysis of a large number of data sets prepared for deposition to our ChemSpider database and in preparation of data for the Open PHACTS project. In this work we review the results of the automated validation of the DrugBank dataset, a popular drug and drug target database utilized by the community, and ChEMBL 17 data set. CVSP web site is located at http://cvsp.chemspider.com/.ConclusionA platform for the validation and standardization of chemical structure representations of various formats has been developed and made available to the community to assist and encourage the processing of chemical structure files to produce more homogeneous compound representations for exchange and interchange between online databases. While the CVSP platform is designed with flexibility inherent to the rules that can be used for processing the data we have produced a recommended rule set based on our own experiences with the large data sets such as DrugBank, ChEMBL, and data sets from ChemSpider.

Dataset Information

Reference Standardization for Quantification and Harmonization of Large-Scale Metabolomics.

Publications

Reference Standardization for Quantification and Harmonization of Large-Scale Metabolomics.

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