| 1. |
- Allione, Alessandra, et al.
(författare)
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Blood cell DNA methylation biomarkers in preclinical malignant pleural mesothelioma : the EPIC prospective cohort
- 2022
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Ingår i: International Journal of Cancer. - : John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 152:4, s. 725-737
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Tidskriftsartikel (refereegranskat)abstract
- Malignant pleural mesothelioma (MPM) is a rare and aggressive cancer mainly caused by asbestos exposure. Specific and sensitive noninvasive biomarkers may facilitate and enhance screening programs for the early detection of cancer. We investigated DNA methylation (DNAm) profiles in MPM prediagnostic blood samples in a case-control study nested in the European Prospective Investigation into Cancer and nutrition (EPIC) cohort, aiming to characterise DNAm biomarkers associated with MPM. From the EPIC cohort, we included samples from 135 participants who developed MPM during 20 years of follow-up and from 135 matched, cancer-free, controls. For the discovery phase we selected EPIC participants who developed MPM within 5 years from enrolment (n = 36) with matched controls. We identified nine differentially methylated CpGs, selected by 10-fold cross-validation and correlation analyses: cg25755428 (MRI1), cg20389709 (KLF11), cg23870316, cg13862711 (LHX6), cg06417478 (HOOK2), cg00667948, cg01879420 (AMD1), cg25317025 (RPL17) and cg06205333 (RAP1A). Receiver operating characteristic (ROC) analysis showed that the model including baseline characteristics (age, sex and PC1wbc) along with the nine MPM-related CpGs has a better predictive value for MPM occurrence than the baseline model alone, maintaining some performance also at more than 5 years before diagnosis (area under the curve [AUC] < 5 years = 0.89; AUC 5-10 years = 0.80; AUC >10 years = 0.75; baseline AUC range = 0.63-0.67). DNAm changes as noninvasive biomarkers in prediagnostic blood samples of MPM cases were investigated for the first time. Their application can improve the identification of asbestos-exposed individuals at higher MPM risk to possibly adopt more intensive monitoring for early disease identification.
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| 2. |
- Perrier, Flavie, et al.
(författare)
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Identifying and correcting epigenetics measurements for systematic sources of variation
- 2018
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Ingår i: Clinical Epigenetics. - London : BioMed Central. - 1868-7083 .- 1868-7075. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Background: Methylation measures quantified by microarray techniques can be affected by systematic variation due to the technical processing of samples, which may compromise the accuracy of the measurement process and contribute to bias the estimate of the association under investigation. The quantification of the contribution of the systematic source of variation is challenging in datasets characterized by hundreds of thousands of features.In this study, we introduce a method previously developed for the analysis of metabolomics data to evaluate the performance of existing normalizing techniques to correct for unwanted variation. Illumina Infinium HumanMethylation450K was used to acquire methylation levels in over 421,000 CpG sites for 902 study participants of a case-control study on breast cancer nested within the EPIC cohort. The principal component partial R-square (PC-PR2) analysis was used to identify and quantify the variability attributable to potential systematic sources of variation. Three correcting techniques, namely ComBat, surrogate variables analysis (SVA) and a linear regression model to compute residuals were applied. The impact of each correcting method on the association between smoking status and DNA methylation levels was evaluated, and results were compared with findings from a large meta-analysis.Results: A sizeable proportion of systematic variability due to variables expressing 'batch' and 'sample position' within 'chip' was identified, with values of the partial R-2 statistics equal to 9.5 and 11.4% of total variation, respectively. After application of ComBat or the residuals' methods, the contribution was 1.3 and 0.2%, respectively. The SVA technique resulted in a reduced variability due to 'batch' (1.3%) and 'sample position' (0.6%), and in a diminished variability attributable to 'chip' within a batch (0.9%). After ComBat or the residuals' corrections, a larger number of significant sites (k = 600 and k = 427, respectively) were associated to smoking status than the SVA correction (k = 96).Conclusions: The three correction methods removed systematic variation in DNA methylation data, as assessed by the PC-PR2, which lent itself as a useful tool to explore variability in large dimension data. SVA produced more conservative findings than ComBat in the association between smoking and DNA methylation.
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| 3. |
- Reiling, Erwin, et al.
(författare)
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Codon 72 polymorphism (rs1042522) of TP53 is associated with changes in diastolic blood pressure over time
- 2012
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Ingår i: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1476-5438 .- 1018-4813. ; 20:6, s. 696-700
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Tidskriftsartikel (refereegranskat)abstract
- p53 is involved in stress response, metabolism and cardiovascular functioning. The C-allele of rs1042522 in the gene encoding for p53 is associated with longevity and cancer. In this study, we aimed to investigate the association of rs1042522 with changes in blood pressure, BMI and waist circumference using a longitudinal approach. Rs1042522 was analyzed in two longitudinal studies; the Doetinchem Cohort Study (DCS) and the Botnia Prospective Study (BPS). Changes in quantitative traits over time were investigated according to rs1042522 genotypes. An association between rs1042522 and changes in diastolic blood pressure (DBP) in the DCS over time was observed (P=0.004). Furthermore, a borderline significant association was detected with changes in waist circumference over time (P=0.03). These findings were also observed in the BPS (P=0.02 and P=0.05). The C/C-genotype (Pro/Pro) showed the most moderate time-related increase for the studied endpoints. Furthermore, data from the BPS suggested that the C/C-genotype protects against increases in glucose levels over time at 30 and 60 min during oral glucose tolerance test (P=0.01 and P=0.02). In conclusion, we found an association between the C/C-genotype of rs1042522 and changes in DBP and waist circumference over time. This might contribute to the longevity phenotype observed for the same genotype by others. European Journal of Human Genetics (2012) 20, 696-700; doi:10.1038/ejhg.2011.240; published online 21 December 2011
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