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Large-scale non-targeted metabolomic profiling in three human population-based studies
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. (Molekylär epidemiologi)ORCID iD: 0000-0003-2071-5866
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
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2016 (English)In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 12, 4Article in journal (Refereed) Published
Abstract [en]

Non-targeted metabolomic profiling is used to simultaneously assess a large part of the metabolome in a biological sample. Here, we describe both the analytical and computational methods used to analyze a large UPLC–Q-TOF MS-based metabolomic profiling effort using plasma and serum samples from participants in three Swedish population-based studies of middle-aged and older human subjects: TwinGene, ULSAM and PIVUS. At present, more than 200 metabolites have been manually annotated in more than 3600 participants using an in-house library of standards and publically available spectral databases. Data available at the metabolights repository include individual raw unprocessed data, processed data, basic demographic variables and spectra of annotated metabolites. Additional phenotypical and genetic data is available upon request to cohort steering committees. These studies represent a unique resource to explore and evaluate how metabolic variability across individuals affects human diseases.

Place, publisher, year, edition, pages
2016. Vol. 12, 4
Keyword [en]
Metabolomics Epidemiology Annotation
National Category
Medical and Health Sciences Endocrinology and Diabetes
Identifiers
URN: urn:nbn:se:uu:diva-274799DOI: 10.1007/s11306-015-0893-5ISI: 000367426600004OAI: oai:DiVA.org:uu-274799DiVA: diva2:897657
Funder
Knut and Alice Wallenberg FoundationEU, European Research Council, 335395Swedish Diabetes Association, 2013-024Swedish Heart Lung Foundation, 20120197Swedish Research Council, 2012-1397
Note

Ganna and Fall equal contributions as first author

Available from: 2016-01-26 Created: 2016-01-26 Last updated: 2017-11-30

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Fall, ToveSalihovic, SamiraStenemo, MarkusLind, LarsIngelsson, Erik

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