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Overlap in serum metabolic profiles between non-related diseases: implications for LC-MS metabolomics biomarker discovery
Umeå University, Faculty of Science and Technology, Department of Molecular Biology (Faculty of Science and Technology). Department of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden. (Anders Nordström)ORCID iD: 0000-0003-3676-817X
2016 (English)In: Biochemical and Biophysical Research Communications - BBRC, ISSN 0006-291X, E-ISSN 1090-2104, Vol. 478, no 3, 1472-1477 p.Article in journal (Refereed) Published
Abstract [en]

Untargeted metabolic profiling has generated large activity in the field of clinical biomarker discovery. Yet, no clinically approved metabolite biomarkers have emerged with failure in validation phases often being a reason. To investigate why, we have applied untargeted metabolic profiling in a retrospective cohort of serum samples representing non-related diseases. Age and gender matched samples from patients diagnosed with pneumonia, congestive heart failure, lymphoma and healthy controls were subject to comprehensive metabolic profiling using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). The metabolic profile of each diagnosis was compared to the healthy control group and significant metabolites were filtered out using t-test with FDR correction. Metabolites found to be significant between each disease and healthy controls were compared and analyzed for overlap. Results show that despite differences in etiology and clinical disease presentation, the fraction of metabolites with an overlap between two or more diseases was 61%. A majority of these metabolites can be associated with immune responses thus representing non-disease specific events. We show that metabolic serum profiles from patients representing non-related diseases display very similar metabolic differences when compared to healthy controls. Many of the metabolites discovered as disease specific in this study have further been associated with other diseases in the literature. Based on our findings we suggest non-related disease controls in metabolomics biomarker discovery studies to increase the chances of a successful validation and future clinical applications. 

Place, publisher, year, edition, pages
2016. Vol. 478, no 3, 1472-1477 p.
Keyword [en]
Metabolomics, Biomarker, LC-MS, Lymphoma, Heart failure, Pneumonia
National Category
Biological Sciences Biomedical Laboratory Science/Technology
Identifiers
URN: urn:nbn:se:umu:diva-128278DOI: 10.1016/j.bbrc.2016.08.155ISI: 000397715400072PubMedID: 27581198Scopus ID: 2-s2.0-84994052351OAI: oai:DiVA.org:umu-128278DiVA: diva2:1051094
Available from: 2016-12-01 Created: 2016-12-01 Last updated: 2017-04-18Bibliographically approved

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CiteExportLink to record
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Citation style
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