RELIC: a novel dye-bias correction method for Illumina Methylation BeadChip

Xu, Zongli; Langie, Sabine A. S.; Boever, Patrick De; Taylor, Jack A.; Niu, Liang

doi:10.1186/s12864-016-3426-3

Cited by 101 publications

(76 citation statements)

References 14 publications

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“…The ENmix R package was used to preprocess raw DNA methylation data in order to improve data quality (https://bioconductor.org/packages/release/ bioc/html/ENmix.html). Briefly, we used the ENmix method to reduce background noise [43]; the RELIC method to correct fluorescent dye-bias [44]; and quantile inter-array normalization on the methylation intensity values and RCP method to reduce Infinium I and II probe design bias [45]. We excluded 5 samples due to data quality issue: 3 samples with >0.05% low quality methylation values (detection p > 1 x 10 −6 or number of beads <3) or with an average bisulfite intensity of <4000, and 2 samples with missing phenotype data.…”

Section: Resultsmentioning

confidence: 99%

Hormone therapy use and breast tissue DNA methylation: analysis of epigenome wide data from the normal breast study

Harlid

Kirk

et al. 2019

Epigenetics

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Hormone therapy (HT) is associated with increased risk of breast cancer, strongly dependent on type, duration, and recency of use. HT use could affect cancer risk by changing breast tissue transcriptional programs. We hypothesize that these changes are preceded by changes in DNA methylation. To explore this hypothesis we used histologically normal-appearing breast tissue from the Normal Breast Study (NBS). DNA methylation β-values were obtained using the Illumina HumanMethylation 450 BeadChips for 90 samples including all NBS-participants who used HT within 5 y before surgery. Data were analyzed using the reference-free cell mixture method. Cancer Genome Atlas (TCGA) mRNA-Seq data were used to assess correlation between DNA methylation and gene expression. We identified 527 CpG sites in 403 genes that were associated with ever using HT at genome wide significance (FDR q < 0.05), of these, 68 sites were also significantly associated with duration of use or recency of use. Twelve sites reached significance in all analyses one of which was cg01382688 in ARHGEF4 (p < 1.2x10 −7). Mutations in ARHGEF4 have been reported in breast tumors, but this is the first report of possible breast cancer-related DNA methylation changes. In addition, 22 genes included more than one significant CpG site and a majority of these sites were significantly correlated with gene expression. Although based on small numbers, these findings support the hypothesis that HT is associated with epigenetic alterations in breast tissue, and identifies genes with altered DNA methylation states which could be linked to breast cancer development.

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Section: Resultsmentioning

confidence: 99%

Hormone therapy use and breast tissue DNA methylation: analysis of epigenome wide data from the normal breast study

Harlid

Kirk

et al. 2019

Epigenetics

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“…The DNA processing procedures have been described elsewhere. 44 quantile normalization to make overall array fluorescence intensity distribution comparable between arrays, and reducing Infinium I and II probe design bias using the regression on correlated probes method. 45 We excluded 102 samples after quality control (61 cases and 41 noncases).…”

Section: Genomic Dna Processing and Immune Cell Deconvolutionmentioning

confidence: 99%

Prediagnostic Immune Cell Profiles and Breast Cancer

Kresovich

O’Brien

et al. 2020

JAMA Netw Open

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IMPORTANCE Higher overall leukocyte counts in women may be associated with increased risk of breast cancer, but the association of specific leukocyte subtypes with breast cancer risk remains unknown. OBJECTIVE To determine associations between circulating leukocyte subtypes and risk of breast cancer. DESIGN, SETTING, AND PARTICIPANTS Between 2003 and 2009, the Sister Study enrolled 50 884 women who had a sister previously diagnosed with breast cancer but were themselves breast cancer free. A case-cohort subsample was selected in July 2014 from the full Sister Study cohort. Blood samples were obtained at baseline, and women were followed up through October 2016. Data analysis was performed in April 2019. MAIN OUTCOMES AND MEASURES The main outcome was the development of breast cancer in women. Whole-blood DNA methylation was measured, and methylation values were deconvoluted using the Houseman method to estimate proportions of 6 leukocyte subtypes (B cells, natural killer cells, CD8 + and CD4 + T cells, monocytes, and granulocytes). Leukocyte subtype proportions were dichotomized at their population median value, and Cox proportional hazard models were used to estimate associations with breast cancer. RESULTS Among 2774 non-Hispanic white women included in the analysis (mean [SD] age at enrollment, 56.6 [8.8] years), 1295 women were randomly selected from the full cohort (of whom 91 developed breast cancer) along with an additional 1479 women who developed breast cancer during follow-up (mean [SD] time to diagnosis, 3.9 [2.2] years). Circulating proportions of B cells were positively associated with later breast cancer (hazard ratio [HR], 1.17; 95% CI, 1.01-1.36; P = .04). Among women who were premenopausal at blood collection, the association between B cells and breast cancer was significant (HR, 1.38; 95% CI, 1.05-1.82; P = .02), and an inverse association for circulating proportions of monocytes was found (HR, 0.75; 95% CI, 0.57-0.99; P = .05). Among all women, associations between leukocyte subtypes and breast cancer were time dependent: higher monocyte proportions were associated with decreased near-term risk (within 1 year of blood collection, HR, 0.62; 95% CI, 0.43-0.89; P = .01), whereas higher B cell proportions were associated with increased risk 4 or more years after blood collection (HR, 1.38; 95% CI, 1.15-1.67; P = .001). CONCLUSIONS AND RELEVANCE Circulating leukocyte profiles may be altered before clinical diagnoses of breast cancer and may be time-dependent markers for breast cancer risk, particularly among premenopausal women.

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“…We processed our data using functional normalization with the default of two principal components from control probes (16). We also adjusted for probe-type bias using RCP, a regression method approach that uses genomic proximity to adjust the distribution of type 2 probes (17). Last, we used the ComBat function from the sva package to adjust for sample plate (18).…”

Section: Epigenome-wide Dna Methylation Measurementsmentioning

confidence: 99%

Placental DNA Methylation Adaptation to Maternal Glycemic Response in Pregnancy

et al. 2018

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Maternal hyperglycemia during pregnancy is associated with excess fetal growth and adverse perinatal and developmental outcomes. Placental epigenetic maladaptation may underlie these associations. We performed an epigenome-wide association study (>850,000 CpG sites) of term placentas and prenatal maternal glycemic response 2-h post oral glucose challenge at 24-30 weeks of gestation among 448 mother-infant pairs. Maternal 2-h glycemia postload was strongly associated with lower DNA methylation of four CpG sites (false discovery rate [FDR] <0.05) within the phosphodiesterase 4B gene (). Additionally, three other individual CpG sites were differentially methylated relative to maternal glucose response within the ,, and genes (FDR <0.05). DNA methylation correlated with expression of its respective genes in placental tissue at three out of four independent identified loci: ( = 0.31, < 0.01), ( = -0.24, = 0.013), and ( = 0.32, < 0.001). In an independent replication cohort ( = 65-108 samples), results were consistent in direction but not significantly replicated among tested CpG sites in and Our study provides evidence that maternal glycemic response during pregnancy is associated with placental DNA methylation of key inflammatory genes whose expression levels are partially under epigenetic control.

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RELIC: a novel dye-bias correction method for Illumina Methylation BeadChip

Cited by 101 publications

References 14 publications

Hormone therapy use and breast tissue DNA methylation: analysis of epigenome wide data from the normal breast study

Hormone therapy use and breast tissue DNA methylation: analysis of epigenome wide data from the normal breast study

Prediagnostic Immune Cell Profiles and Breast Cancer

Placental DNA Methylation Adaptation to Maternal Glycemic Response in Pregnancy

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