Stratified randomization controls better for batch effects in 450K methylation analysis: a cautionary tale

Buhule, Olive D.; Minster, Ryan L.; Hawley, Nicola L.; Medvedovic, Mario; Sun, Guoqiang; Viali, Satupaitea; Deka, Ranjan; McGarvey, Stephen T.; Weeks, Daniel E.

doi:10.3389/fgene.2014.00354

Cited by 44 publications

(46 citation statements)

References 32 publications

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“…Methylation values ranged from zero (for a fully unmethylated CpG site) to one (for a fully methylated CpG site). As others have found that the differences between plates or chips are often the largest source of technical variation [12,13], all pairs of placenta and cord blood (from the same individual) were arrayed on the same chip with a randomized position (row and column).…”

Section: Dna Methylation Profilingmentioning

confidence: 99%

Epigenome-Wide Cross-Tissue Predictive Modeling and Comparison of Cord Blood and Placental Methylation in a Birth Cohort

et al. 2017

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Aim:We compared predictive modeling approaches to estimate placental methylation using cord blood methylation. Materials & methods: We performed locus-specific methylation prediction using both linear regression and support vector machine models with 174 matched pairs of 450k arrays. Results: At most CpG sites, both approaches gave poor predictions in spite of a misleading improvement in array-wide correlation. CpG islands and gene promoters, but not enhancers, were the genomic contexts where the correlation between measured and predicted placental methylation levels achieved higher values. We provide a list of 714 sites where both models achieved an R 2 ≥0.75. Conclusion: The present study indicates the need for caution in interpreting cross-tissue predictions. Few methylation sites can be predicted between cord blood and placenta.

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Section: Dna Methylation Profilingmentioning

confidence: 99%

Epigenome-Wide Cross-Tissue Predictive Modeling and Comparison of Cord Blood and Placental Methylation in a Birth Cohort

et al. 2017

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“…Blood samples were collected blinded to the outcome, as well were DNA extraction and DNAm measurements. Batch effects are omnipresent and numerous for the 450K platform [24], but our careful sample allocation scheme ensured that they were not associated with the outcome or the matching factors.…”

Section: Discussionmentioning

confidence: 99%

Epigenome-wide discovery and evaluation of leukocyte DNA methylation markers for the detection of colorectal cancer in a screening setting

Heiss

Brenner

2017

Clin Epigenet

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Background: Colorectal cancer (CRC) is the third most common cancer worldwide. If detected at an early stage, prognosis is good. Despite increasing evidence for the benefits of implemented screening programs, such as screening colonoscopy, compliance is rather low. Hence there is demand for non-invasive tests for the early detection of CRC with high acceptance in population-wide screening. The objective of this study was to identify and evaluate leukocyte DNA methylation patterns as a potential biomarker for early detection of CRC. Methods: Blood samples of patients scheduled for a screening colonoscopy were collected before the procedure. Additionally, blood samples from CRC cases recruited in a clinical setting were collected. DNA was extracted from leukocytes, and DNA methylation was measured with the Infinium 450K BeadChip. In total, 46 CRC cases and 140 controls from the screening setting and 93 CRC cases from the clinical setting were measured. Results: An epigenome-wide discovery revealed two CpG sites in the promoter region of KIAA1549L that were significantly differentially methylated between cases and controls. A third marker in the body region of BCL2 was discovered in a candidate approach testing biomarkers reported in the literature. Logistic regression models built on these three markers yielded an optimism-corrected c-statistic of 0.69 in the screening setting and 0.73 in the clinical setting. Conclusions: Although diagnostic performance of the DNA methylation signature identified in this first epigenomewide association study of leukocyte DNA methylation with CRC in a screening setting is not competitive with established screening tests, the identified markers may contribute to multimarker panels for early detection of CRC.

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“…We also considered microarray batch effects by stratified randomization of samples across chips. This approach was implemented to protect against spurious findings and represents a more optimal approach than common computational corrections for batch effects such as ComBat (32). The standardized intervention and relatively brief time period between sampling are also important factors to consider in this study.…”

Section: Discussionmentioning

confidence: 99%

Postprandial alterations in whole-blood DNA methylation are mediated by changes in white blood cell composition

Rask‐Andersen

Bringeland

Nilsson

et al. 2016

The American Journal of Clinical Nutrition

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Background: DNA methylation is an essential nuclear process associated with genomic functions such as transcription factor binding and the regulation of gene expression. DNA methylation patterns can also serve as potential biomarkers for disease progression and response to therapy. However, the full dynamics of DNA methylation across daily physiologic events have not been fully elucidated. Objective: We sought to study how ingesting a standardized meal acutely affects peripheral blood DNA methylation. Design: We performed an observational study in healthy men (n = 26) on DNA methylation and gene expression in whole blood before and 160 min after the ingestion of a standardized meal. Cytosinephosphate-guanine (CpG) methylation was assayed on the HumanMethylation450k microarray, and gene expression was measured with the Human Gene 2.1 ST Array. Results: Differential methylation after food intake was detected in 13% of the analyzed probes (63,207 CpG probes) at a 5% false discovery rate (FDR). This effect was driven by changes in leukocyte fractions as estimated from comparisons against methylation datasets generated from sorted leukocytes. When methylation values were adjusted for estimated leukocyte fractions, 541 probes were observed to be altered in the postprandial state (5% FDR). Conclusions: Apparent alterations in DNA methylation 160 min after meal ingestion mainly reflect changes in the estimated leukocyte population in whole blood. These results have major methodologic implications for genome-wide methylation studies because they highlight the strong underlying effects of changes in leukocyte fractions on CpG methylation patterns as well as the potential importance of meal-standardized sampling procedures for future investigations when alterations in white blood cell fractions are unavailable. This trial was registered at clinicaltrials.gov as LSF008786.Am J Clin Nutr 2016;104:518-25.

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Stratified randomization controls better for batch effects in 450K methylation analysis: a cautionary tale

Cited by 44 publications

References 32 publications

Epigenome-Wide Cross-Tissue Predictive Modeling and Comparison of Cord Blood and Placental Methylation in a Birth Cohort

Epigenome-Wide Cross-Tissue Predictive Modeling and Comparison of Cord Blood and Placental Methylation in a Birth Cohort

Epigenome-wide discovery and evaluation of leukocyte DNA methylation markers for the detection of colorectal cancer in a screening setting

Postprandial alterations in whole-blood DNA methylation are mediated by changes in white blood cell composition

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