| 1. |
- Assi, Nada, et al.
(författare)
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A statistical framework to model the meeting-in-the-middle principle using metabolomic data : application to hepatocellular carcinoma in the EPIC study
- 2015
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Ingår i: Mutagenesis. - : Oxford University Press (OUP). - 0267-8357 .- 1464-3804. ; 30:6, s. 743-753
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Tidskriftsartikel (refereegranskat)abstract
- Metabolomics is a potentially powerful tool for identification of biomarkers associated with lifestyle exposures and risk of various diseases. This is the rationale of the 'meeting-in-the-middle' concept, for which an analytical framework was developed in this study. In a nested case-control study on hepatocellular carcinoma (HCC) within the European Prospective Investigation into Cancer and nutrition (EPIC), serum H-1 nuclear magnetic resonance (NMR) spectra (800 MHz) were acquired for 114 cases and 222 matched controls. Through partial least square (PLS) analysis, 21 lifestyle variables (the 'predictors', including information on diet, anthropometry and clinical characteristics) were linked to a set of 285 metabolic variables (the 'responses'). The three resulting scores were related to HCC risk by means of conditional logistic regressions. The first PLS factor was not associated with HCC risk. The second PLS metabolomic factor was positively associated with tyrosine and glucose, and was related to a significantly increased HCC risk with OR = 1.11 (95% CI: 1.02, 1.22, P = 0.02) for a 1SD change in the responses score, and a similar association was found for the corresponding lifestyle component of the factor. The third PLS lifestyle factor was associated with lifetime alcohol consumption, hepatitis and smoking, and had negative loadings on vegetables intake. Its metabolomic counterpart displayed positive loadings on ethanol, glutamate and phenylalanine. These factors were positively and statistically significantly associated with HCC risk, with 1.37 (1.05, 1.79, P = 0.02) and 1.22 (1.04, 1.44, P = 0.01), respectively. Evidence of mediation was found in both the second and third PLS factors, where the metabolomic signals mediated the relation between the lifestyle component and HCC outcome. This study devised a way to bridge lifestyle variables to HCC risk through NMR metabolomics data. This implementation of the 'meeting-in-the-middle' approach finds natural applications in settings characterised by high-dimensional data, increasingly frequent in the omics generation.
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| 2. |
- Fages, Anne, et al.
(författare)
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Investigating sources of variability in metabolomic data in the EPIC study : the Principal Component Partial R-square (PC-PR2) method
- 2014
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Ingår i: Metabolomics. - : Springer. - 1573-3882 .- 1573-3890. ; 10:6, s. 1074-1083
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 3. |
- Fages, Anne, et al.
(författare)
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Metabolomic profiles of hepatocellular carcinoma in a European prospective cohort.
- 2015
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Ingår i: BMC Medicine. - : Springer Science and Business Media LLC. - 1741-7015. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is difficult to diagnose and has limited treatment options with a low survival rate. Aside from a few key risk factors, such as hepatitis, high alcohol consumption, smoking, obesity, and diabetes, there is incomplete etiologic understanding of the disease and little progress in identification of early risk biomarkers.
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