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Investigating sources of variability in metabolomic data in the EPIC study: the Principal Component Partial R-square (PC-PR2) method
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2014 (English)In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 10, no 6, 1074-1083 p.Article in journal (Refereed) Published
Abstract [en]

The key goal of metabolomic studies is to identify relevant individual biomarkers or composite metabolic patterns associated with particular disease status or patho-physiological conditions. There are currently very few approaches to evaluate the variability of metabolomic data in terms of characteristics of individuals or aspects pertaining to technical processing. To address this issue, a method was developed to identify and quantify the contribution of relevant sources of variation in metabolomic data prior to investigation of etiological hypotheses. The Principal Component Partial R-square (PC-PR2) method combines features of principal component and of multivariable linear regression analyses. Within the European Prospective Investigation into Cancer and nutrition (EPIC), metabolic profiles were determined by H-1 NMR analysis on 807 serum samples originating from a nested liver cancer case-control study. PC-PR2 was used to quantify the variability of metabolomic profiles in terms of study subjects age, sex, body mass index, country of origin, smoking status, diabetes and fasting status, as well as factors related to sample processing. PC-PR2 enables the evaluation of important sources of variations in metabolomic studies within large-scale epidemiological investigations.

Place, publisher, year, edition, pages
Springer, 2014. Vol. 10, no 6, 1074-1083 p.
Keyword [en]
Metabolomics, Principal component analysis, Nuclear magnetic resonance, Epidemiology, Systematic variation, European prospective investigation on cancer and nutrition
National Category
Endocrinology and Diabetes
URN: urn:nbn:se:umu:diva-97210DOI: 10.1007/s11306-014-0647-9ISI: 000344555300005OAI: diva2:773267
Available from: 2014-12-18 Created: 2014-12-12 Last updated: 2014-12-18Bibliographically approved

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Johansson, Mattias
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Department of Biobank Research
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