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Sökning: WFRF:(Byrnes Graham) > (2015-2019) > Johansson Mattias

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1.
  • Brenner, Darren R., et al. (författare)
  • Inflammatory Cytokines and Lung Cancer Risk in 3 Prospective Studies
  • 2017
  • Ingår i: American Journal of Epidemiology. - : OXFORD UNIV PRESS INC. - 0002-9262 .- 1476-6256. ; 185:2, s. 86-95
  • Tidskriftsartikel (refereegranskat)abstract
    • To further investigate the role of inflammation in lung carcinogenesis, we evaluated associations between proinflammatory cytokines and lung cancer risk. We conducted a case-control study nested within 3 prospective cohort studies-the Melbourne Collaborative Cohort Study (1990-1994), the Malm Diet and Cancer Study (1991-1996), and the Northern Sweden Health and Disease Study (initiated in 1985)-involving 807 incident lung cancer cases and 807 smoking-matched controls. Conditional logistic regression models adjusting for serum cotinine concentrations were used to estimate odds ratios for lung cancer risk associated with concentrations of interleukin (IL)-1 beta, IL-2, IL-6, IL-8, IL-10, IL-12, interferon., tumor necrosis factor a, and granulocyte-macrophage colony-stimulating factor. We observed a higher lung cancer risk for participants with elevated concentrations of IL-6 and IL-8. These associations seemed to be stronger among former smokers (for fourth quartile vs. first quartile, odds ratio (OR) = 2.70, 95% confidence interval (CI): 1.55, 4.70) and current smokers (OR = 1.99, 95% CI: 1.15, 3.44) for IL-6 and among former smokers (OR = 2.83, 95% CI: 1.18, 6.75) and current smokers (OR = 1.30, 95% CI: 0.69, 2.44) for IL-8. No notable associations were observed among never smokers. Risk associations with IL-6 and IL-8 were observed for blood samples taken close to diagnosis (< 5 years) as well as more than 15 years postdiagnosis.
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2.
  • Assi, Nada, et al. (författare)
  • A statistical framework to model the meeting-in-the-middle principle using metabolomic data : application to hepatocellular carcinoma in the EPIC study
  • 2015
  • Ingår i: Mutagenesis. - : Oxford University Press (OUP). - 0267-8357 .- 1464-3804. ; 30:6, s. 743-753
  • 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.
  • Delahaye-Sourdeix, Manon, et al. (författare)
  • The 12p13.33/RAD52 locus and genetic susceptibility to squamous cell cancers of upper aerodigestive tract
  • 2015
  • Ingår i: PLOS ONE. - : Public library science. - 1932-6203. ; 10:3
  • Tidskriftsartikel (refereegranskat)abstract
    • Genetic variants located within the 12p13.33/RAD52 locus have been associated with lung squamous cell carcinoma (LUSC). Here, within 5,947 UADT cancers and 7,789 controls from 9 different studies, we found rs10849605, a common intronic variant in RAD52, to be also associated with upper aerodigestive tract (UADT) squamous cell carcinoma cases (OR = 1.09, 95% CI: 1.04-1.15, p = 6x10(-4)). We additionally identified rs10849605 as a RAD52 cis-eQTL inUADT(p = 1x10(-3)) and LUSC (p = 9x10(-4)) tumours, with the UADT/LUSC risk allele correlated with increased RAD52 expression levels. The 12p13.33 locus, encompassing rs10849605/RAD52, was identified as a significant somatic focal copy number amplification in UADT(n = 374, q-value = 0.075) and LUSC (n = 464, q-value = 0.007) tumors and correlated with higher RAD52 tumor expression levels (p = 6x10(-48) and p = 3x10(-29) in UADT and LUSC, respectively). In combination, these results implicate increased RAD52 expression in both genetic susceptibility and tumorigenesis of UADT and LUSC tumors.
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4.
  • Freisling, Heinz, et al. (författare)
  • Main nutrient patterns are associated with prospective weight change in adults from 10 European countries
  • 2016
  • Ingår i: European Journal of Nutrition. - : Springer. - 1436-6207 .- 1436-6215. ; 55:6, s. 2093-2104
  • Tidskriftsartikel (refereegranskat)abstract
    • PURPOSE: Various food patterns have been associated with weight change in adults, but it is unknown which combinations of nutrients may account for such observations. We investigated associations between main nutrient patterns and prospective weight change in adults.METHODS: This study includes 235,880 participants, 25-70 years old, recruited between 1992 and 2000 in 10 European countries. Intakes of 23 nutrients were estimated from country-specific validated dietary questionnaires using the harmonized EPIC Nutrient DataBase. Four nutrient patterns, explaining 67 % of the total variance of nutrient intakes, were previously identified from principal component analysis. Body weight was measured at recruitment and self-reported 5 years later. The relationship between nutrient patterns and annual weight change was examined separately for men and women using linear mixed models with random effect according to center controlling for confounders.RESULTS: Mean weight gain was 460 g/year (SD 950) and 420 g/year (SD 940) for men and women, respectively. The annual differences in weight gain per one SD increase in the pattern scores were as follows: principal component (PC) 1, characterized by nutrients from plant food sources, was inversely associated with weight gain in men (-22 g/year; 95 % CI -33 to -10) and women (-18 g/year; 95 % CI -26 to -11). In contrast, PC4, characterized by protein, vitamin B2, phosphorus, and calcium, was associated with a weight gain of +41 g/year (95 % CI +2 to +80) and +88 g/year (95 % CI +36 to +140) in men and women, respectively. Associations with PC2, a pattern driven by many micro-nutrients, and with PC3, a pattern driven by vitamin D, were less consistent and/or non-significant.CONCLUSIONS: We identified two main nutrient patterns that are associated with moderate but significant long-term differences in weight gain in adults.
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5.
  • Guida, Florence, et al. (författare)
  • Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins
  • 2018
  • Ingår i: JAMA Oncology. - : American Medical Association (AMA). - 2374-2437 .- 2374-2445. ; 4:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Importance  There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases.Objective  To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a traditional risk prediction model and current US screening criteria.Design, Setting, and Participants  Prediagnostic samples from 108 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and samples from 216 smoking-matched controls from the Carotene and Retinol Efficacy Trial (CARET) cohort were used to develop a biomarker risk score based on 4 proteins (cancer antigen 125 [CA125], carcinoembryonic antigen [CEA], cytokeratin-19 fragment [CYFRA 21-1], and the precursor form of surfactant protein B [Pro-SFTPB]). The biomarker score was subsequently validated blindly using absolute risk estimates among 63 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and 90 matched controls from 2 large European population-based cohorts, the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Northern Sweden Health and Disease Study (NSHDS).Main Outcomes and Measures  Model validity in discriminating between future lung cancer cases and controls. Discrimination estimates were weighted to reflect the background populations of EPIC and NSHDS validation studies (area under the receiver-operating characteristics curve [AUC], sensitivity, and specificity).Results  In the validation study of 63 ever-smoking patients with lung cancer and 90 matched controls (mean [SD] age, 57.7 [8.7] years; 68.6% men) from EPIC and NSHDS, an integrated risk prediction model that combined smoking exposure with the biomarker score yielded an AUC of 0.83 (95% CI, 0.76-0.90) compared with 0.73 (95% CI, 0.64-0.82) for a model based on smoking exposure alone (P = .003 for difference in AUC). At an overall specificity of 0.83, based on the US Preventive Services Task Force screening criteria, the sensitivity of the integrated risk prediction (biomarker) model was 0.63 compared with 0.43 for the smoking model. Conversely, at an overall sensitivity of 0.42, based on the US Preventive Services Task Force screening criteria, the integrated risk prediction model yielded a specificity of 0.95 compared with 0.86 for the smoking model.Conclusions and Relevance  This study provided a proof of principle in showing that a panel of circulating protein biomarkers may improve lung cancer risk assessment and may be used to define eligibility for computed tomography screening.
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