ArticleClinical epigenetics2018
Identifying and correcting epigenetics measurements for systematic sources of variation.
Article in Clinical epigenetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Disease classification for whole-blood DNA methylation: Meta-analysis, missing values imputation, and XAI.GigaScience · 2022Pooled it
- Hypertensive Disorders of Pregnancy and DNA Methylation in Newborns.Hypertension (Dallas, Tex. : 1979) · 2019Pooled it
- Lifestyle change accelerates epigenetic ageing in King penguins.Nature communications · 2026Article
- Novel epigenetic marks of insulin resistance trajectories in a longitudinal study of childhood obesity.Cardiovascular diabetology · 2026Article
- Identification of key biomarkers and potential therapeutic drugs in nasopharyngeal carcinoma based on comprehensive bioinformatics analysis.Discover oncology · 2025Article
- Breaking rules: the complex relationship between DNA methylation and X-chromosome inactivation in the human placenta.Biology of sex differences · 2025Article
- Critical review of aging clocks and factors that may influence the pace of aging.Frontiers in aging · 2024Review
- Waterpipe and cigarette epigenome analysis reveals markers implicated in addiction and smoking type inference.Environment international · 2023Article
- Article
- DNA methylation of insulin signaling pathways is associated with HOMA2-IR in primary myoblasts from older adults.Skeletal muscle · 2023Article
- Global endometrial DNA methylation analysis reveals insights into mQTL regulation and associated endometriosis disease risk and endometrial function.Communications biology · 2023Article
- Differences in white blood cell proportions between schizophrenia cases and controls are influenced by medication and variations in time of day.Translational psychiatry · 2023Article
- Buffy coat signatures of breast cancer risk in a prospective cohort study.Clinical epigenetics · 2023Article
- Effects of prenatal exposure to (es)citalopram and maternal depression during pregnancy on DNA methylation and child neurodevelopment.Translational psychiatry · 2023Article
- Calculating detection limits and uncertainty of reference-based deconvolution of whole-blood DNA methylation data.Epigenomics · 2023Article
- Longitudinal Epigenome-Wide Analysis of Kidney Transplant Recipients Pretransplant and Posttransplant.Kidney international reports · 2023Article
- DNA methylation signatures of Alzheimer's disease neuropathology in the cortex are primarily driven by variation in non-neuronal cell-types.Nature communications · 2022Article
- Cutaneous and acral melanoma cross-OMICs reveals prognostic cancer drivers associated with pathobiology and ultraviolet exposure.Nature communications · 2022Article
- Metabolic Signatures of Healthy Lifestyle Patterns and Colorectal Cancer Risk in a European Cohort.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2022Article
- Novel Biomarkers of Habitual Alcohol Intake and Associations With Risk of Pancreatic and Liver Cancers and Liver Disease Mortality.Journal of the National Cancer Institute · 2021Article
Corrections and comments
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Authors and funding
21 authors.
Funding
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 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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