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  • 1
    Abstract: AIM OF THE STUDY: A vast majority of human malignancies are associated with ageing, and age is a strong predictor of cancer risk. Recently, DNA methylation-based marker of ageing, known as 'epigenetic clock', has been linked with cancer risk factors. This study aimed to evaluate whether the epigenetic clock is associated with breast cancer risk susceptibility and to identify potential epigenetics-based biomarkers for risk stratification. METHODS: Here, we profiled DNA methylation changes in a nested case-control study embedded in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (n = 960) using the Illumina HumanMethylation 450K BeadChip arrays and used the Horvath age estimation method to calculate epigenetic age for these samples. Intrinsic epigenetic age acceleration (IEAA) was estimated as the residuals by regressing epigenetic age on chronological age. RESULTS: We observed an association between IEAA and breast cancer risk (OR, 1.04; 95% CI, 1.007-1.076, P = 0.016). One unit increase in IEAA was associated with a 4% increased odds of developing breast cancer (OR, 1.04; 95% CI, 1.007-1.076). Stratified analysis based on menopausal status revealed that IEAA was associated with development of postmenopausal breast cancers (OR, 1.07; 95% CI, 1.020-1.11, P = 0.003). In addition, methylome-wide analyses revealed that a higher mean DNA methylation at cytosine-phosphate-guanine (CpG) islands was associated with increased risk of breast cancer development (OR per 1 SD = 1.20; 95 %CI: 1.03-1.40, P = 0.02) whereas mean methylation levels at non-island CpGs were indistinguishable between cancer cases and controls. CONCLUSION: Epigenetic age acceleration and CpG island methylation have a weak, but statistically significant, association with breast cancer susceptibility.
    Type of Publication: Journal article published
    PubMed ID: 28259012
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  • 2
    Keywords: LUNG-CANCER ; DISEASE ; ENZYMES ; CLEAVAGE ; BETA-CAROTENE ; SINGLE NUCLEOTIDE POLYMORPHISMS ; VITAMIN-A ; pooled analysis ; MENDELIAN RANDOMIZATION ; 15,15-MONOOXYGENASE
    Abstract: BACKGROUND: Dietary and circulating carotenoids have been inversely associated with breast cancer risk, but observed associations may be due to confounding. Single-nucleotide polymorphisms (SNPs) in beta-carotene 15,15'-monooxygenase 1 (BCMO1), a gene encoding the enzyme involved in the first step of synthesizing vitamin A from dietary carotenoids, have been associated with circulating carotenoid concentrations and may serve as unconfounded surrogates for those biomarkers. We determined associations between variants in BCMO1 and breast cancer risk in a large cohort consortium. METHODS: We used unconditional logistic regression to test four SNPs in BCMO1 for associations with breast cancer risk in 9,226 cases and 10,420 controls from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also tested weighted multi-SNP scores composed of the two SNPs with strong, confirmed associations with circulating carotenoid concentrations. RESULTS: Neither the individual SNPs nor the weighted multi-SNP scores were associated with breast cancer risk [OR (95% confidence interval) comparing extreme quintiles of weighted multi-SNP scores = 1.04 (0.94-1.16) for beta-carotene, 1.08 (0.98-1.20) for alpha-carotene, 1.04 (0.94-1.16) for beta-cryptoxanthin, 0.95 (0.87-1.05) for lutein/zeaxanthin, and 0.92 (0.83-1.02) for retinol]. Furthermore, no associations were observed when stratifying by estrogen receptor status, but power was limited. CONCLUSIONS: Our results do not support an association between SNPs associated with circulating carotenoid concentrations and breast cancer risk. Impact: Future studies will need additional genetic surrogates and/or sample sizes at least three times larger to contribute evidence of a causal link between carotenoids and breast cancer. Cancer Epidemiol Biomarkers Prev; 22(5); 927-36. (c)2013 AACR.
    Type of Publication: Journal article published
    PubMed ID: 23515144
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  • 3
    Keywords: ASSOCIATION ; VARIANTS ; BREAST ; PERFORMANCE ; PREDICTION
    Abstract: Risk-prediction models need careful calibration to ensure they produce unbiased estimates of risk for subjects in the underlying population given their risk-factor profiles. As subjects with extreme high or low risk may be the most affected by knowledge of their risk estimates, checking the adequacy of risk models at the extremes of risk is very important for clinical applications. We propose a new approach to test model calibration targeted toward extremes of disease risk distribution where standard goodness-of-fit tests may lack power due to sparseness of data. We construct a test statistic based on model residuals summed over only those individuals who pass high and/or low risk thresholds and then maximize the test statistic over different risk thresholds. We derive an asymptotic distribution for the max-test statistic based on analytic derivation of the variance-covariance function of the underlying Gaussian process. The method is applied to a large case-control study of breast cancer to examine joint effects of common single nucleotide polymorphisms (SNPs) discovered through recent genome-wide association studies. The analysis clearly indicates a non-additive effect of the SNPs on the scale of absolute risk, but an excellent fit for the linear-logistic model even at the extremes of risks.
    Type of Publication: Journal article published
    PubMed ID: 25027274
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  • 4
    Keywords: carcinoma ; WOMEN ; PROSTATE-CANCER ; CLINICAL-SIGNIFICANCE ; susceptibility loci ; GENOME-WIDE ASSOCIATION ; CONFER SUSCEPTIBILITY ; COMMON VARIANTS ; COHORT CONSORTIUM ; IDENTIFIES 2
    Abstract: INTRODUCTION: Breast cancer in situ (BCIS) diagnoses, a precursor lesion for invasive breast cancer, comprise about 20 % of all breast cancers (BC) in countries with screening programs. Family history of BC is considered one of the strongest risk factors for BCIS. METHODS: To evaluate the association of BC susceptibility loci with BCIS risk, we genotyped 39 single nucleotide polymorphisms (SNPs), associated with risk of invasive BC, in 1317 BCIS cases, 10,645 invasive BC cases, and 14,006 healthy controls in the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3). Using unconditional logistic regression models adjusted for age and study, we estimated the association of SNPs with BCIS using two different comparison groups: healthy controls and invasive BC subjects to investigate whether BCIS and BC share a common genetic profile. RESULTS: We found that five SNPs (CDKN2BAS-rs1011970, FGFR2-rs3750817, FGFR2-rs2981582, TNRC9-rs3803662, 5p12-rs10941679) were significantly associated with BCIS risk (P value adjusted for multiple comparisons 〈0.0016). Comparing invasive BC and BCIS, the largest difference was for CDKN2BAS-rs1011970, which showed a positive association with BCIS (OR = 1.24, 95 % CI: 1.11-1.38, P = 1.27 x 10(-4)) and no association with invasive BC (OR = 1.03, 95 % CI: 0.99-1.07, P = 0.06), with a P value for case-case comparison of 0.006. Subgroup analyses investigating associations with ductal carcinoma in situ (DCIS) found similar associations, albeit less significant (OR = 1.25, 95 % CI: 1.09-1.42, P = 1.07 x 10(-3)). Additional risk analyses showed significant associations with invasive disease at the 0.05 level for 28 of the alleles and the OR estimates were consistent with those reported by other studies. CONCLUSIONS: Our study adds to the knowledge that several of the known BC susceptibility loci are risk factors for both BCIS and invasive BC, with the possible exception of rs1011970, a putatively functional SNP situated in the CDKN2BAS gene that may be a specific BCIS susceptibility locus.
    Type of Publication: Journal article published
    PubMed ID: 26070784
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  • 5
    Keywords: polymorphism ; TUMOR-SUPPRESSOR GENE ; mammographic density ; MULTIETHNIC COHORT ; BASE-LINE CHARACTERISTICS ; susceptibility loci ; GENOME-WIDE ASSOCIATION ; CONFER SUSCEPTIBILITY ; COMMON VARIANTS ; IDENTIFIES 2
    Abstract: The survival of breast cancer patients is largely influenced by tumor characteristics, such as TNM stage, tumor grade and hormone receptor status. However, there is growing evidence that inherited genetic variation might affect the disease prognosis and response to treatment. Several lines of evidence suggest that alleles influencing breast cancer risk might also be associated with breast cancer survival. We examined the associations between 35 breast cancer susceptibility loci and the disease over-all survival (OS) in 10,255 breast cancer patients from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) of which 1,379 died, including 754 of breast cancer. We also conducted a meta-analysis of almost 35,000 patients and 5,000 deaths, combining results from BPC3 and the Breast Cancer Association Consortium (BCAC) and performed in silico analyses of SNPs with significant associations. In BPC3, the C allele of LSP1-rs3817198 was significantly associated with improved OS (HRper-allele =0.70; 95% CI: 0.58-0.85; ptrend = 2.84 x 10-4 ; HRheterozygotes = 0.71; 95% CI: 0.55-0.92; HRhomozygotes = 0.48; 95% CI: 0.31-0.76; p2DF = 1.45 x 10-3 ). In silico, the C allele of LSP1-rs3817198 was predicted to increase expression of the tumor suppressor cyclin-dependent kinase inhibitor 1C (CDKN1C). In the meta-analysis, TNRC9-rs3803662 was significantly associated with increased death hazard (HRMETA =1.09; 95% CI: 1.04-1.15; ptrend = 6.6 x 10-4 ; HRheterozygotes = 0.96 95% CI: 0.90-1.03; HRhomozygotes = 1.21; 95% CI: 1.09-1.35; p2DF =1.25 x 10-4 ). In conclusion, we show that there is little overlap between the breast cancer risk single nucleotide polymorphisms (SNPs) identified so far and the SNPs associated with breast cancer prognosis, with the possible exceptions of LSP1-rs3817198 and TNRC9-rs3803662.
    Type of Publication: Journal article published
    PubMed ID: 25611573
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  • 6
    Abstract: AIMS/HYPOTHESIS: Studies on weight cycling and the risk of type 2 diabetes have revealed inconsistent results, possibly due to differences in the definition of weight fluctuations. Here, we investigated whether weight cycling during adulthood is related to diabetes risk in a large cohort study, using a complementary approach to define patterns of weight development. METHODS: Weight cycling, weight loss and weight gain were defined (1) a priori, using distinct categories, and (2) by functional principal component analysis (FPCA) to capture weight patterns in greater detail. Associations of weight cycling, weight loss and weight gain with the risk of type 2 diabetes were evaluated by Cox regression models. RESULTS: A priori defined weight cycling was associated with increased diabetes risk, compared with stable weight (HR 1.36 [95% CI 1.09, 1.68]). No significant association between FPCA-derived weight cycling and risk of diabetes was observed after adjustment for concurrent weight patterns (HR 1.19 [95% CI 0.89, 1.60]). Subgroup analyses showed that FPCA-derived weight cycling during net weight gain was associated with a higher risk of diabetes (HR 1.68 [95% CI 1.14, 2.48]). A priori defined weight gain (HR 2.08 [95% CI 1.60, 2.70]) was more clearly related to the risk of diabetes than FPCA-derived weight gain (HR 1.20 [95% CI 0.95, 1.51]), while no significant associations were observed for weight loss. CONCLUSIONS/INTERPRETATION: Overall, weight cycling may not be an independent risk factor for type 2 diabetes when accounting for concurrent patterns of weight development. However, weight cycling may pose a stronger risk of diabetes than non-cycling during net weight gain.
    Type of Publication: Journal article published
    PubMed ID: 26376796
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  • 7
    Abstract: DNA methylation changes are associated with cigarette smoking. We used the Illumina Infinium HumanMethylation450 array to determine whether methylation in DNA from pre-diagnostic, peripheral blood samples is associated with lung cancer risk. We used a case-control study nested within the EPIC-Italy cohort and a study within the MCCS cohort as discovery sets (a total of 552 case-control pairs). We validated the top signals in 429 case-control pairs from another 3 studies. We identified six CpGs for which hypomethylation was associated with lung cancer risk: cg05575921 in the AHRR gene (p-valuepooled = 4x10-17 ), cg03636183 in the F2RL3 gene (p-valuepooled = 2x10-13 ), cg21566642 and cg05951221 in 2q37.1 (p-valuepooled = 7x10-16 and 1x10-11 respectively), cg06126421 in 6p21.33 (p-valuepooled = 2x10-15 ) and cg23387569 in 12q14.1 (p-valuepooled = 5x10-7 ). For cg05951221 and cg23387569 the strength of association was virtually identical in never and current smokers. For all these CpGs except for cg23387569, the methylation levels were different across smoking categories in controls (p-valuesheterogeneity 〈/= 1.8 x10-7 ), were lowest for current smokers and increased with time since quitting for former smokers. We observed a gain in discrimination between cases and controls measured by the area under the ROC curve of at least 8% (p-values 〉/= 0.003) in former smokers by adding methylation at the 6 CpGs into risk prediction models including smoking status and number of pack-years. Our findings provide convincing evidence that smoking and possibly other factors lead to DNA methylation changes measurable in peripheral blood that may improve prediction of lung cancer risk. This article is protected by copyright. All rights reserved.
    Type of Publication: Journal article published
    PubMed ID: 27632354
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  • 8
    Abstract: BACKGROUND: -DNA methylation leaves a long-term signature of smoking exposure and is one potential mechanism by which tobacco exposure predisposes to adverse health outcomes, such as cancers, osteoporosis, lung, and cardiovascular disorders. METHODS AND RESULTS: -To comprehensively determine the association between cigarette smoking and DNA methylation, we conducted a meta-analysis of genome-wide DNA methylation assessed using the Illumina BeadChip 450K array on 15,907 blood derived DNA samples from participants in 16 cohorts (including 2,433 current, 6,518 former, and 6,956 never smokers). Comparing current versus never smokers, 2,623 CpG sites (CpGs), annotated to 1,405 genes, were statistically significantly differentially methylated at Bonferroni threshold of p〈1x10-7 (18,760 CpGs at False Discovery Rate (FDR)〈0.05). Genes annotated to these CpGs were enriched for associations with several smoking-related traits in genome-wide studies including pulmonary function, cancers, inflammatory diseases and heart disease. Comparing former versus never smokers, 185 of the CpGs that differed between current and never smokers were significant p〈1x10-7 (2,623 CpGs at FDR〈0.05), indicating a pattern of persistent altered methylation, with attenuation, after smoking cessation. Transcriptomic integration identified effects on gene expression at many differentially methylated CpGs. CONCLUSIONS: -Cigarette smoking has a broad impact on genome-wide methylation that, at many loci, persists many years after smoking cessation. Many of the differentially methylated genes were novel genes with respect to biologic effects of smoking, and might represent therapeutic targets for prevention or treatment of tobacco-related diseases. Methylation at these sites could also serve as sensitive and stable biomarkers of lifetime exposure to tobacco smoke.
    Type of Publication: Journal article published
    PubMed ID: 27651444
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  • 9
  • 10
    Keywords: TOBACCO-SMOKE ; BASE-LINE CHARACTERISTICS ; susceptibility loci ; GENOME-WIDE ASSOCIATION ; CONFER SUSCEPTIBILITY ; COMMON VARIANTS ; BRCA2 MUTATION CARRIERS ; LOW-PENETRANCE BREAST ; LEAD CONCENTRATION ; RISK VARIANT
    Abstract: We studied the interplay between 39 breast cancer (BC) risk SNPs and established BC risk (body mass index, height, age at menarche, parity, age at menopause, smoking, alcohol and family history of BC) and prognostic factors (TNM stage, tumor grade, tumor size, age at diagnosis, estrogen receptor status and progesterone receptor status) as joint determinants of BC risk. We used a nested case-control design within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3), with 16 285 BC cases and 19 376 controls. We performed stratified analyses for both the risk and prognostic factors, testing for heterogeneity for the risk factors, and case-case comparisons for differential associations of polymorphisms by subgroups of the prognostic factors. We analyzed multiplicative interactions between the SNPs and the risk factors. Finally, we also performed a meta-analysis of the interaction ORs from BPC3 and the Breast Cancer Association Consortium. After correction for multiple testing, no significant interaction between the SNPs and the established risk factors in the BPC3 study was found. The meta-analysis showed a suggestive interaction between smoking status and SLC4A7-rs4973768 (P-interaction = 8.84 x 10(-4)) which, although not significant after considering multiple comparison, has a plausible biological explanation. In conclusion, in this study of up to almost 79 000 women we can conclusively exclude any novel major interactions between genome-wide association studies hits and the epidemiologic risk factors taken into consideration, but we propose a suggestive interaction between smoking status and SLC4A7-rs4973768 that if further replicated could help our understanding in the etiology of BC.
    Type of Publication: Journal article published
    PubMed ID: 24895409
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