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J Inherit Metab Dis. 2018 May;41(3):329-336. doi: 10.1007/s10545-018-0137-8. Epub 2018 Apr 16.

The role of the Human Metabolome Database in inborn errors of metabolism.

Author information

1
Departments of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E8, Canada.
2
Departments of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E8, Canada. dwishart@ualberta.ca.
3
Computing Science, University of Alberta, Edmonton, AB, T6G 2E8, Canada. dwishart@ualberta.ca.
4
National Institute for Nanotechnology, 11421 Saskatchewan Drive, Edmonton, AB, T6G 2M9, Canada. dwishart@ualberta.ca.

Abstract

Metabolomics holds considerable promise to advance our understanding of human disease, including our understanding of inborn errors of metabolism (IEM). The application of metabolomics in IEM research has already led to the discovery of several novel IEMs and the identification of novel IEM biomarkers. However, with hundreds of known IEMs and more than 700 associated IEM metabolites, it is becoming increasingly challenging for clinical researchers to keep track of IEMs, their associated metabolites, and their corresponding metabolic mechanisms. Furthermore, when using metabolomics to assist in IEM biomarker discovery or even in IEM diagnosis, it is becoming much more difficult to properly identify metabolites from the complex NMR and MS spectra collected from IEM patients. To that end, comprehensive, open access metabolite databases that provide up-to-date referential information about metabolites, metabolic pathways, normal/abnormal metabolite concentrations, and reference NMR or MS spectra for compound identification are essential. Over the last few years, a number of compound databases, including the Human Metabolome Database (HMDB), have been developed to address these challenges. First described in 2007, the HMDB is now the world's largest and most comprehensive metabolomic resource for human metabolic studies. The latest release of the HMDB contains 114,100 metabolite entries (with 247 being relevant to IEMs), thousands of metabolite concentrations (with 600 being relevant to IEMs), and ~33,000 metabolic and disease-associated pathways (with 202 being relevant to IEMs). Here we provide a summary of the HMDB and offer some guidance on how it can be used in metabolomic studies of IEMs.

KEYWORDS:

Databases; Human Metabolome Database; bioinformatics; inborn errors of metabolism; metabolomics

PMID:
29663269
DOI:
10.1007/s10545-018-0137-8

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