| 1. |
- Agogo, George O., et al.
(författare)
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A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data
- 2016
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Ingår i: BMC Medical Research Methodology. - : Springer Science and Business Media LLC. - 1471-2288. ; 16
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Tidskriftsartikel (refereegranskat)abstract
- Background: Measurement error in self-reported dietary intakes is known to bias the association between dietary intake and a health outcome of interest such as risk of a disease. The association can be distorted further by mismeasured confounders, leading to invalid results and conclusions. It is, however, difficult to adjust for the bias in the association when there is no internal validation data. Methods: We proposed a method to adjust for the bias in the diet-disease association (hereafter, association), due to measurement error in dietary intake and a mismeasured confounder, when there is no internal validation data. The method combines prior information on the validity of the self-report instrument with the observed data to adjust for the bias in the association. We compared the proposed method with the method that ignores the confounder effect, and with the method that ignores measurement errors completely. We assessed the sensitivity of the estimates to various magnitudes of measurement error, error correlations and uncertainty in the literature-reported validation data. We applied the methods to fruits and vegetables (FV) intakes, cigarette smoking (confounder) and all-cause mortality data from the European Prospective Investigation into Cancer and Nutrition study. Results: Using the proposed method resulted in about four times increase in the strength of association between FV intake and mortality. For weakly correlated errors, measurement error in the confounder minimally affected the hazard ratio estimate for FV intake. The effect was more pronounced for strong error correlations. Conclusions: The proposed method permits sensitivity analysis on measurement error structures and accounts for uncertainties in the reported validity coefficients. The method is useful in assessing the direction and quantifying the magnitude of bias in the association due to measurement errors in the confounders.
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| 2. |
- 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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| 3. |
- Assi, Nada, et al.
(författare)
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Are Metabolic Signatures Mediating the Relationship between Lifestyle Factors and Hepatocellular Carcinoma Risk? Results from a Nested Case–Control Study in EPIC
- 2018
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 27:5, s. 531-540
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Tidskriftsartikel (refereegranskat)abstract
- Background: The "meeting-in-the-middle" (MITM) is a principle to identify exposure biomarkers that are also predictors of disease. The MITM statistical framework was applied in a nested case-control study of hepatocellular carcinoma (HCC) within European Prospective Investigation into Cancer and Nutrition (EPIC), where healthy lifestyle index (HLI) variables were related to targeted serum metabolites.Methods: Lifestyle and targeted metabolomic data were available from 147 incident HCC cases and 147 matched controls. Partial least squares analysis related 7 lifestyle variables from a modified HLI to a set of 132 serum-measured metabolites and a liver function score. Mediation analysis evaluated whether metabolic profiles mediated the relationship between each lifestyle exposure and HCC risk.Results: Exposure-related metabolic signatures were identified. Particularly, the body mass index (BMI)-associated metabolic component was positively related to glutamic acid, tyrosine, PC aaC38:3, and liver function score and negatively to lysoPC aC17:0 and aC18:2. The lifetime alcohol-specific signature had negative loadings on sphingomyelins (SM C16:1, C18:1, SM(OH) C14:1, C16:1 and C22:2). Both exposures were associated with increased HCC with total effects (TE) = 1.23 (95% confidence interval = 0.93-1.62) and 1.40 (1.14-1.72), respectively, for BMI and alcohol consumption. Both metabolic signatures mediated the association between BMI and lifetime alcohol consumption and HCC with natural indirect effects, respectively, equal to 1.56 (1.24-1.96) and 1.09 (1.03-1.15), accounting for a proportion mediated of 100% and 24%.Conclusions: In a refined MITM framework, relevant metabolic signatures were identified as mediators in the relationship between lifestyle exposures and HCC risk.Impact: The understanding of the biological basis for the relationship between modifiable exposures and cancer would pave avenues for clinical and public health interventions on metabolic mediators.
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| 4. |
- Assi, Nada, et al.
(författare)
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Metabolic signature of healthy lifestyle and its relation with risk of hepatocellular carcinoma in a large European cohort
- 2018
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Ingår i: American Journal of Clinical Nutrition. - : American Society for Nutrition. - 0002-9165 .- 1938-3207. ; 108:1, s. 117-126
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Tidskriftsartikel (refereegranskat)abstract
- Background: Studies using metabolomic data have identified metabolites from several compound classes that are associated with disease-related lifestyle factors.Objective: In this study, we identified metabolic signatures reflecting lifestyle patterns and related them to the risk of hepatocellular carcinoma (HCC) in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.Design: Within a nested case-control study of 147 incident HCC cases and 147 matched controls, partial least squares (PLS) analysis related 7 modified healthy lifestyle index (HLI) variables (diet, BMI, physical activity, lifetime alcohol, smoking, diabetes, and hepatitis) to 132 targeted serum-measured metabolites and a liver function score. The association between the resulting PLS scores and HCC risk was examined in multivariable conditional logistic regression models, where ORs and 95% CIs were computed.Results: The lifestyle component's PLS score was negatively associated with lifetime alcohol, BMI, smoking, and diabetes, and positively associated with physical activity. Its metabolic counterpart was positively related to the metabolites sphingomyelin (SM) (OH) C14:1, C16:1, and C22:2, and negatively related to glutamate, hexoses, and the diacyl-phosphatidylcholine PC aaC32:1. The lifestyle and metabolomics components were inversely associated with HCC risk, with the ORs for a 1-SD increase in scores equal to 0.53 (95% CI: 0.38, 0.74) and 0.28 (0.18, 0.43), and the associated AUCs equal to 0.64 (0.57, 0.70) and 0.74 (0.69, 0.80), respectively.Conclusions: This study identified a metabolic signature reflecting a healthy lifestyle pattern which was inversely associated with HCC risk. The metabolic profile displayed a stronger association with HCC than did the modified HLI derived from questionnaire data. Measuring a specific panel of metabolites may identify strata of the population at higher risk for HCC and can add substantial discrimination compared with questionnaire data. This trial was registered at clinicaltrials.gov as NCT03356535.
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| 5. |
- Bamia, Christina, et al.
(författare)
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Coffee, tea and decaffeinated coffee in relation to hepatocellular carcinoma in a European population: Multicentre, prospective cohort study
- 2015
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Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 136, s. 1899-1908
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Tidskriftsartikel (refereegranskat)abstract
- © 2014 UICC. Inverse associations of coffee and/or tea in relation to hepatocellular carcinoma (HCC) risk have been consistently identified in studies conducted mostly in Asia where consumption patterns of such beverages differ from Europe. In the European Prospective Investigation into Cancer and nutrition (EPIC), we identified 201 HCC cases among 486,799 men/women, after a median follow-up of 11 years. We calculated adjusted hazard ratios (HRs) for HCC incidence in relation to quintiles/categories of coffee/tea intakes. We found that increased coffee and tea intakes were consistently associated with lower HCC risk. The inverse associations were substantial, monotonic and statistically significant. Coffee consumers in the highest compared to the lowest quintile had lower HCC risk by 72% [HR: 0.28; 95% confidence intervals (CIs): 0.16-0.50, p-trend < 0.001]. The corresponding association of tea with HCC risk was 0.41 (95% CI: 0.22-0.78, p-trend50.003). There was no compelling evidence of heterogeneity of these associations across strata of important HCC risk factors, including hepatitis B or hepatitis C status (available in a nested case-control study). The inverse, monotonic associations of coffee intake with HCC were apparent for caffeinated (p-trend50.009), but not decaffeinated (p-trend50.45) coffee for which, however, data were available for a fraction of subjects. Results from this multicentre, European cohort study strengthen the existing evidence regarding the inverse association between coffee/tea and HCC risk. Given the apparent lack of heterogeneity of these associations by HCC risk factors and that coffee/tea are universal exposures, our results could have important implications for high HCC risk subjects.
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| 6. |
- Carayol, Marion, et al.
(författare)
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Blood Metabolic Signatures of Body Mass Index : A Targeted Metabolomics Study in the EPIC Cohort
- 2017
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 16:9, s. 3137-3146
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Tidskriftsartikel (refereegranskat)abstract
- Metabolomics is now widely used to characterize metabolic phenotypes associated with lifestyle risk factors such as obesity. The objective of the present study was to explore the associations of body mass index (BMI) with 145 metabolites measured in blood samples in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolites were measured in blood from 392 men from the Oxford (UK) cohort (EPIC-Oxford) and in 327 control subjects who were part of a nested case-control study on hepatobiliary carcinomas (EPIC-Hepatobiliary). Measured metabolites included amino acids, acylcarnitines, hexoses, biogenic amines, phosphatidylcholines, and sphingomyelins. Linear regression models controlled for potential confounders and multiple testing were run to evaluate the associations of metabolite concentrations with BMI. 40 and 45 individual metabolites showed significant differences according to BMI variations, in the EPIC-Oxford and EPIC-Hepatobiliary subcohorts, respectively. Twenty two individual metabolites (kynurenine, one sphingomyelin, glutamate and 19 phosphatidylcholines) were associated with BMI in both subcohorts. The present findings provide additional knowledge on blood metabolic signatures of BMI in European adults, which may help identify mechanisms mediating the relationship of BMI with obesity-related diseases.
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| 7. |
- Carraro, Marco, et al.
(författare)
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Performance of in silico tools for the evaluation of p16INK4a (CDKN2A) variants in CAGI
- 2017
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 38:9, s. 1042-1050
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Tidskriftsartikel (refereegranskat)abstract
- Correct phenotypic interpretation of variants of unknown significance for cancer-associated genes is a diagnostic challenge as genetic screenings gain in popularity in the next-generation sequencing era. The Critical Assessment of Genome Interpretation (CAGI) experiment aims to test and define the state of the art of genotype-phenotype interpretation. Here, we present the assessment of the CAGI p16INK4a challenge. Participants were asked to predict the effect on cellular proliferation of 10 variants for the p16INK4a tumor suppressor, a cyclin-dependent kinase inhibitor encoded by the CDKN2A gene. Twenty-two pathogenicity predictors were assessed with a variety of accuracy measures for reliability in a medical context. Different assessment measures were combined in an overall ranking to provide more robust results. The R scripts used for assessment are publicly available from a GitHub repository for future use in similar assessment exercises. Despite a limited test-set size, our findings show a variety of results, with some methods performing significantly better. Methods combining different strategies frequently outperform simpler approaches. The best predictor, Yang&Zhou lab, uses a machine learning method combining an empirical energy function measuring protein stability with an evolutionary conservation term. The p16INK4a challenge highlights how subtle structural effects can neutralize otherwise deleterious variants.
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| 8. |
- Chajès, Véronique, et al.
(författare)
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Plasma Elaidic Acid Level as Biomarker of Industrial Trans Fatty Acids and Risk of Weight Change: Report from the EPIC Study.
- 2015
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 10:2
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Tidskriftsartikel (refereegranskat)abstract
- Few epidemiological studies have examined the association between dietary trans fatty acids and weight gain, and the evidence remains inconsistent. The main objective of the study was to investigate the prospective association between biomarker of industrial trans fatty acids and change in weight within the large study European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.
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| 9. |
- Daneshjou, Roxana, et al.
(författare)
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Working toward precision medicine : Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges
- 2017
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 38:9, s. 1182-1192
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Tidskriftsartikel (refereegranskat)abstract
- Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype-phenotype relationships.
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| 10. |
- Duarte-Salles, Talita, et al.
(författare)
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Dietary fat, fat subtypes and hepatocellular carcinoma in a large European cohort
- 2015
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Ingår i: International Journal of Cancer. - : Wiley-Blackwell. - 0020-7136 .- 1097-0215. ; 137:11, s. 2715-2728
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Tidskriftsartikel (refereegranskat)abstract
- The role of amount and type of dietary fat consumption in the etiology of hepatocellular carcinoma (HCC) is poorly understood, despite suggestive biological plausibility. The associations of total fat, fat subtypes and fat sources with HCC incidence were investigated in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, which includes 191 incident HCC cases diagnosed between 1992 and 2010. Diet was assessed by country-specific, validated dietary questionnaires. A single 24-hr diet recall from a cohort subsample was used for measurement error calibration. Hazard ratios (HR) and 95% confidence intervals (95% CI) were estimated from Cox proportional hazard models. Hepatitis B and C viruses (HBV/HCV) status and biomarkers of liver function were assessed separately in a nested case-control subset with available blood samples (HCC = 122). In multivariable calibrated models, there was a statistically significant inverse association between total fat intake and risk of HCC (per 10 g/day, HR = 0.80, 95% CI: 0.65-0.99), which was mainly driven by monounsaturated fats (per 5 g/day, HR = 0.71, 95% CI: 0.55-0.92) rather than polyunsaturated fats (per 5 g/day, HR = 0.92, 95% CI: 0.68-1.25). There was no association between saturated fats (HR = 1.08, 95% CI: 0.88-1.34) and HCC risk. The ratio of polyunsaturated/monounsaturated fats to saturated fats was not significantly associated with HCC risk (per 0.2 point, HR = 0.86, 95% CI: 0.73-1.01). Restriction of analyses to HBV/HCV free participants or adjustment for liver function did not substantially alter the findings. In this large prospective European cohort, higher consumption of monounsaturated fats is associated with lower HCC risk.
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