| 311. |
- Li, Kuanrong, et al.
(författare)
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Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts
- 2018
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Ingår i: Breast Cancer Research. - : BioMed Central. - 1465-5411 .- 1465-542X. ; 20
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Few published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction.METHODS: We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women's Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention.RESULTS: Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10- 6 for ModelER+ and 3.0 × 10- 6 for ModelGail.CONCLUSIONS: Modeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.
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| 312. |
- Li, Sherly X., et al.
(författare)
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Interaction between genes and macronutrient intake on the risk of developing type 2 diabetes : systematic review and findings from European Prospective Investigation into Cancer (EPIC)-InterAct
- 2017
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Ingår i: American Journal of Clinical Nutrition. - : American society for nutrition. - 0002-9165 .- 1938-3207. ; 106:1, s. 263-275
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Forskningsöversikt (refereegranskat)abstract
- Background: Gene-diet interactions have been reported to contribute to the development of type 2 diabetes (T2D). However, to our knowledge, few examples have been consistently replicated to date. Objective: We aimed to identify existing evidence for genemacronutrient interactions and T2D and to examine the reported interactions in a large-scale study. Design: We systematically reviewed studies reporting genemacronutrient interactions and T2D. We searched the MEDLINE, Human Genome Epidemiology Network, and WHO International Clinical Trials Registry Platform electronic databases to identify studies published up to October 2015. Eligibility criteria included assessment of macronutrient quantity (e.g., total carbohydrate) or indicators of quality (e. g., dietary fiber) by use of self-report or objective biomarkers of intake. Interactions identified in the review were subsequently examined in the EPIC (European Prospective Investigation into Cancer)-InterAct case-cohort study (n = 21,148, with 9403 T2D cases; 8 European countries). Prentice-weighted Cox regression was used to estimate countryspecific HRs, 95% CIs, and P-interaction values, which were then pooled by random-effects meta-analysis. A primary model was fitted by using the same covariates as reported in the published studies, and a second model adjusted for additional covariates and estimated the effects of isocaloric macronutrient substitution. Results: Thirteen observational studies met the eligibility criteria (n < 1700 cases). Eight unique interactions were reported to be significant between macronutrients [carbohydrate, fat, saturated fat, dietary fiber, and glycemic load derived from self-report of dietary intake and circulating n-3 (v-3) polyunsaturated fatty acids] and genetic variants in or near transcription factor 7-like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) (P-interaction, 0.05). We found no evidence of interaction when we tried to replicate previously reported interactions. In addition, no interactions were detected in models with additional covariates. Conclusions: Eight gene-macronutrient interactions were identified for the risk of T2D from the literature. These interactions were not replicated in the EPIC-InterAct study, which mirrored the analyses undertaken in the original reports. Our findings highlight the importance of independent replication of reported interactions.
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| 313. |
- Li, Sherly X, et al.
(författare)
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Interplay between genetic predisposition, macronutrient intake and type 2 diabetes incidence: analysis within EPIC-InterAct across eight European countries.
- 2018
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 61:6, s. 1325-1332
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Tidskriftsartikel (refereegranskat)abstract
- Gene-macronutrient interactions may contribute to the development of type 2 diabetes but research evidence to date is inconclusive. We aimed to increase our understanding of the aetiology of type 2 diabetes by investigating potential interactions between genes and macronutrient intake and their association with the incidence of type 2 diabetes.We investigated the influence of interactions between genetic risk scores (GRSs) for type 2 diabetes, insulin resistance and BMI and macronutrient intake on the development of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a prospective case-cohort study across eight European countries (N=21,900 with 9742 incident type 2 diabetes cases). Macronutrient intake was estimated from diets reported in questionnaires, including proportion of energy derived from total carbohydrate, protein, fat, plant and animal protein, saturated, monounsaturated and polyunsaturated fat and dietary fibre. Using multivariable-adjusted Cox regression, we estimated country-specific interaction results on the multiplicative scale, using random-effects meta-analysis. Secondary analysis used isocaloric macronutrient substitution.No interactions were identified between any of the three GRSs and any macronutrient intake, with low-to-moderate heterogeneity between countries (I2 range 0-51.6%). Results were similar using isocaloric macronutrient substitution analyses and when weighted and unweighted GRSs and individual SNPs were examined.Genetic susceptibility to type 2 diabetes, insulin resistance and BMI did not modify the association between macronutrient intake and incident type 2 diabetes. This suggests that macronutrient intake recommendations to prevent type 2 diabetes do not need to account for differences in genetic predisposition to these three metabolic conditions.
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| 314. |
- Lin, Crystal, et al.
(författare)
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Pre-diagnostic circulating insulin-like growth factor-I and bladder cancer risk in the European Prospective Investigation into Cancer and Nutrition
- 2018
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Ingår i: International Journal of Cancer. - : WILEY. - 0020-7136 .- 1097-0215. ; 143:10, s. 2351-2358
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Tidskriftsartikel (refereegranskat)abstract
- Previous in vitro and case–control studies have found an association between the insulin‐like growth factor (IGF)‐axis and bladder cancer risk. Circulating concentrations of IGF‐I have also been found to be associated with an increased risk of several cancer types; however, the relationship between pre‐diagnostic circulating IGF‐I concentrations and bladder cancer has never been studied prospectively. We investigated the association of pre‐diagnostic plasma concentrations of IGF‐I with risk of overall bladder cancer and urothelial cell carcinoma (UCC) in a case–control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. A total of 843 men and women diagnosed with bladder cancer between 1992 and 2005 were matched with 843 controls by recruitment centre, sex, age at recruitment, date of blood collection, duration of follow‐up, time of day and fasting status at blood collection using an incidence density sampling protocol. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using conditional logistic regression with adjustment for smoking status. No association was found between pre‐diagnostic circulating IGF‐I concentration and overall bladder cancer risk (adjusted OR for highest versus lowest fourth: 0.91, 95% CI: 0.66–1.24, ptrend = 0.40) or UCC (n of cases = 776; 0.91, 0.65–1.26, ptrend = 0.40). There was no significant evidence of heterogeneity in the association of IGF‐I with bladder cancer risk by tumour aggressiveness, sex, smoking status, or by time between blood collection and diagnosis (pheterogeneity > 0.05 for all). This first prospective study indicates no evidence of an association between plasma IGF‐I concentrations and bladder cancer risk.
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| 315. |
- Lindstrom, Sara, et al.
(författare)
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Characterizing Associations and SNP-Environment Interactions for GWAS-Identified Prostate Cancer Risk Markers-Results from BPC3
- 2011
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:2
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with prostate cancer risk. However, whether these associations can be consistently replicated, vary with disease aggressiveness (tumor stage and grade) and/or interact with non-genetic potential risk factors or other SNPs is unknown. We therefore genotyped 39 SNPs from regions identified by several prostate cancer GWAS in 10,501 prostate cancer cases and 10,831 controls from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). We replicated 36 out of 39 SNPs (P-values ranging from 0.01 to 10(-28)). Two SNPs located near KLK3 associated with PSA levels showed differential association with Gleason grade (rs2735839, P = 0.0001 and rs266849, P = 0.0004; case-only test), where the alleles associated with decreasing PSA levels were inversely associated with low-grade (as defined by Gleason grade,8) tumors but positively associated with high-grade tumors. No other SNP showed differential associations according to disease stage or grade. We observed no effect modification by SNP for association with age at diagnosis, family history of prostate cancer, diabetes, BMI, height, smoking or alcohol intake. Moreover, we found no evidence of pair-wise SNP-SNP interactions. While these SNPs represent new independent risk factors for prostate cancer, we saw little evidence for effect modification by other SNPs or by the environmental factors examined.
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| 316. |
- Lindström, Sara, et al.
(författare)
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A large study of androgen receptor germline variants and their relation to sex hormone levels and prostate cancer risk : Results from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium
- 2010
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Ingår i: Journal of Clinical Endocrinology and Metabolism. - : The Endocrine Society. - 0021-972X .- 1945-7197. ; 95:9, s. E121-E127
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Tidskriftsartikel (refereegranskat)abstract
- Background: Androgens are key regulators of prostate gland maintenance and prostate cancer growth, and androgen deprivation therapy has been the mainstay of treatment for advanced prostate cancer for many years. A long-standing hypothesis has been that inherited variation in the androgen receptor (AR) gene plays a role in prostate cancer initiation. However, studies to date have been inconclusive and often suffered from small sample sizes. Objective and Methods: We investigated the association of AR sequence variants with circulating sex hormone levels and prostate cancer risk in 6058 prostate cancer cases and 6725 controls of Caucasian origin within the Breast and Prostate Cancer Cohort Consortium. We genotyped a highly polymorphic CAG microsatellite in exon 1 and six haplotype tagging single nucleotide polymorphisms and tested each genetic variant for association with prostate cancer risk and with sex steroid levels. Results: We observed no association between AR genetic variants and prostate cancer risk. However, there was a strong association between longer CAG repeats and higher levels of testosterone (P = 4.73 × 10−5) and estradiol (P = 0.0002), although the amount of variance explained was small (0.4 and 0.7%, respectively). Conclusions: This study is the largest to date investigating AR sequence variants, sex steroid levels, and prostate cancer risk. Although we observed no association between AR sequence variants and prostate cancer risk, our results support earlier findings of a relation between the number of CAG repeats and circulating levels of testosterone and estradiol.
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| 317. |
- Linseisen, Jakob, et al.
(författare)
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Consumption of meat and fish and risk of lung cancer: results from the European Prospective Investigation into Cancer and Nutrition
- 2011
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Ingår i: Cancer Causes and Control. - : Springer Science and Business Media LLC. - 1573-7225 .- 0957-5243. ; 22:6, s. 909-918
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Tidskriftsartikel (refereegranskat)abstract
- Evidence from case-control studies, but less so from cohort studies, suggests a positive association between meat intake and risk of lung cancer. Therefore, this association was evaluated in the frame of the European Prospective Investigation into Cancer and Nutrition, EPIC. Data from 478,021 participants, recruited from 10 European countries, who completed a dietary questionnaire in 1992-2000 were evaluated; 1,822 incident primary lung cancer cases were included in the present evaluation. Relative risk estimates were calculated for categories of meat intake using multi-variably adjusted Cox proportional hazard models. In addition, the continuous intake variables were calibrated by means of 24-h diet recall data to account for part of the measurement error. There were no consistent associations between meat consumption and the risk of lung cancer. Neither red meat (RR = 1.06, 95% CI 0.89-1.27 per 50 g intake/day; calibrated model) nor processed meat (RR = 1.13, 95% CI 0.95-1.34 per 50 g/day; calibrated model) was significantly related to an increased risk of lung cancer. Also, consumption of white meat and fish was not associated with the risk of lung cancer. These findings do not support the hypothesis that a high intake of red and processed meat is a risk factor for lung cancer.
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| 318. |
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| 319. |
- Linseisen, Jakob, et al.
(författare)
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Fruit and vegetable consumption and lung cancer risk: Updated information from the European Prospective Investigation into Cancer and Nutrition (EPIC)
- 2007
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Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 121:5, s. 1103-1114
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Tidskriftsartikel (refereegranskat)abstract
- The association of fruit and vegetable consumption and lung cancer incidence was evaluated using the most recent data from the European Prospective Investigation into Cancer and Nutrition (EPIC), applying a refined statistical approach (calibration) to account for measurement error potentially introduced by using food frequency questionnaire data. Between 1992 and 2000, detailed information on diet and life-style of 478,590 individuals participating in EPIC was collected. During a median follow-up of 6.4 years, 1,126 lung cancer cases were observed. Multivariate Cox proportional hazard models were applied for statistical evaluation. In the whole study population, fruit consumption was significantly inversely associated with lung cancer risk while no association was found for vegetable consumption. In current smokers, however, lung cancer risk significantly decreased with higher vegetable consumption; this association became more pronounced after calibration, the hazard ratio (HR) being 0.78 (95% CI 0.620.98) per 100 g increase in daily vegetable consumption. In comparison, the HR per 100 g fruit was 0.92 (0.85-0.99) in the entire cohort and 0.90 (0.81-0.99) in smokers. Exclusion of cases diagnosed during the first 2 years of follow-up strengthened these associations, the HR being 0.71 (0.55-0.94) for vegetables (smokers) and 0.86 (0.78-0.95) for fruit (entire cohort). Cancer incidence decreased with higher consumption of apples and pears (entire cohort) as well as root vegetables (smokers). In addition to an overall inverse association with fruit intake, the results of this evaluation add evidence for a significant inverse association of vegetable consumption and lung cancer incidence in smokers. (C) 2007 Wiley-Liss, Inc.
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| 320. |
- Lotta, Luca A., et al.
(författare)
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Association between low-density lipoprotein cholesterol-lowering genetic variants and risk of type 2 diabetes : A meta-analysis
- 2016
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Ingår i: JAMA: The Journal of the American Medical Association. - : American Medical Association (AMA). - 0098-7484 .- 1538-3598. ; 316:13, s. 1383-1391
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Tidskriftsartikel (refereegranskat)abstract
- IMPORTANCE Low-density lipoprotein cholesterol (LDL-C)-lowering alleles in or near NPC1L1 or HMGCR, encoding the respective molecular targets of ezetimibe and statins, have previously been used as proxies to study the efficacy of these lipid-lowering drugs. Alleles near HMGCR are associated with a higher risk of type 2 diabetes, similar to the increased incidence of new-onset diabetes associated with statin treatment in randomized clinical trials. It is unknown whether alleles near NPC1L1 are associated with the risk of type 2 diabetes. OBJECTIVE To investigate whether LDL-C-lowering alleles in or near NPC1L1 and other genes encoding current or prospective molecular targets of lipid-lowering therapy (ie, HMGCR, PCSK9, ABCG5/G8, LDLR) are associated with the risk of type 2 diabetes. DESIGN, SETTING, AND PARTICIPANTS The associations with type 2 diabetes and coronary artery disease of LDL-C-lowering genetic variants were investigated in meta-analyses of genetic association studies. Meta-analyses included 50 775 individuals with type 2 diabetes and 270 269 controls and 60 801 individuals with coronary artery disease and 123 504 controls. Data collection took place in Europe and the United States between 1991 and 2016. EXPOSURES Low-density lipoprotein cholesterol-lowering alleles in or near NPC1L1, HMGCR, PCSK9, ABCG5/G8, and LDLR. MAIN OUTCOMES AND MEASURES Odds ratios (ORs) for type 2 diabetes and coronary artery disease. RESULTS Low-density lipoprotein cholesterol-lowering genetic variants at NPC1L1 were inversely associated with coronary artery disease (OR for a genetically predicted 1-mmol/L [38.7-mg/dL] reduction in LDL-C of 0.61 [95%CI, 0.42-0.88]; P = .008) and directly associated with type 2 diabetes (OR for a genetically predicted 1-mmol/L reduction in LDL-C of 2.42 [95%CI, 1.70-3.43]; P .001). For PCSK9 genetic variants, the OR for type 2 diabetes per 1-mmol/L genetically predicted reduction in LDL-C was 1.19 (95%CI, 1.02-1.38; P = .03). For a given reduction in LDL-C, genetic variants were associated with a similar reduction in coronary artery disease risk (I2 = 0%for heterogeneity in genetic associations; P = .93). However, associations with type 2 diabetes were heterogeneous (I2 = 77.2%; P = .002), indicating gene-specific associations with metabolic risk of LDL-C-lowering alleles. CONCLUSIONS AND RELEVANCE In thismeta-analysis, exposure to LDL-C-lowering genetic variants in or near NPC1L1 and other geneswas associated with a higher risk of type 2 diabetes. These data provide insights into potential adverse effects of LDL-C-lowering therapy.
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