methscore: a comprehensive R function for DNA methylation-based health predictors.

MOTIVATION: DNA methylation-based predictors of various biological metrics have been widely published and are becoming valuable tools in epidemiologic studies of epigenetics and personalized medicine. However, generating these predictors from original source software and web servers is complex and time consuming. Furthermore, different predictors were often derived based on data from different types of arrays, where array differences and batch effects can make predictors difficult to compare across studies. RESULTS: We integrate these published methods into a single R function to produce 158 previously published predictors for chronological age, biological age, exposures, lifestyle traits and serum protein levels using both classical and principal component-based methods. To mitigate batch and array differences, we also provide a modified RCP method (ref-RCP) that normalize input DNA methylation data to reference data prior to estimation. Evaluations in real datasets show that this approach improves estimate precision and comparability across studies. AVAILABILITY AND IMPLEMENTATION: The function was included in software package ENmix, and is freely available from Bioconductor website (https://www.bioconductor.org/packages/release/bioc/html/ENmix.html).

Trans-ancestry epigenome-wide association meta-analysis of DNA methylation with lifetime cannabis use.

Cannabis is widely used worldwide, yet its links to health outcomes are not fully understood. DNA methylation can serve as a mediator to link environmental exposures to health outcomes. We conducted an epigenome-wide association study (EWAS) of peripheral blood-based DNA methylation and lifetime cannabis use (ever vs. never) in a meta-analysis including 9436 participants (7795 European and 1641 African ancestry) from seven cohorts. Accounting for effects of cigarette smoking, our trans-ancestry EWAS meta-analysis revealed four CpG sites significantly associated with lifetime cannabis use at a false discovery rate of 0.05 [Formula: see text]: cg22572071 near gene ADGRF1, cg15280358 in ADAM12, cg00813162 in ACTN1, and cg01101459 near LINC01132. Additionally, our EWAS analysis in participants who never smoked cigarettes identified another epigenome-wide significant CpG site, cg14237301 annotated to APOBR. We used a leave-one-out approach to evaluate methylation scores constructed as a weighted sum of the significant CpGs. The best model can explain 3.79% of the variance in lifetime cannabis use. These findings unravel the DNA methylation changes associated with lifetime cannabis use that are independent of cigarette smoking and may serve as a starting point for further research on the mechanisms through which cannabis exposure impacts health outcomes.

In utero exposure to diethylstilbestrol and blood DNA methylation in adult women: Results from a meta-analysis of two cohort studies.

BACKGROUND: Prenatal exposure to diethylstilbestrol (DES) is associated with several adverse health outcomes. Animal studies have shown associations between prenatal DES exposure and DNA methylation. OBJECTIVE: The aim of this study was to explore blood DNA methylation in women exposed and unexposed to DES in utero. METHODS: Sixty women (40 exposed and 20 unexposed) in the National Cancer Institute's Combined DES Cohort Study and 199 women (99 exposed and 100 unexposed women) in the Sister Study Cohort were included in this analysis. Within each study, robust linear regression models were used to assess associations between DES exposure and blood DNA methylation. Study-specific associations were combined using fixed-effect meta-analysis with inverse variance weights. Our analysis focused on CpG sites located within nine candidate genes identified in animal models. We further explored whether in utero DES exposure was associated with age acceleration. RESULTS: Blood DNA methylation levels at 10 CpG sites in six of the nine candidate genes were statistically significantly associated with prenatal DES exposure (P < 0.05) in this meta-analysis. Genes included EGF, EMB, EGFR, WNT11, FOS, and TGFB1, which are related to cell proliferation and differentiation. The most statistically significant CpG site was cg19830739 in gene EGF, and it was associated with lower methylation levels in women prenatally exposed to DES compared with those not exposed (P < 0.0001; false discovery rate<0.05). The association between prenatal DES exposure in utero and age acceleration was not statistically significant (P = 0.07 for meta-analyzed results). CONCLUSIONS: There are few opportunities to investigate the effects of prenatal DES exposure. These findings suggest that in utero DES exposure may be associated with differential blood DNA methylation levels, which could mediate the increased risk of several adverse health outcomes observed in exposed women. Our findings need further evaluation using larger data sets.

Intermediate and long-term exposure to air pollution and temperature and the extracellular microRNA profile of participants in the normative aging study (NAS).

BACKGROUND: The molecular effects of intermediate and long-term exposure to air pollution and temperature, such as those on extracellular microRNA (ex-miRNA) are not well understood but may have clinical consequences. OBJECTIVES: To assess the association between exposure to ambient air pollution and temperature and ex-miRNA profiles. METHODS: Our study population consisted of 734 participants in the Normative Aging Study (NAS) between 1999 and 2015. We used high-resolution models to estimate four-week, eight-week, twelve-week, six-month, and one-year moving averages of PM2.5, O3, NO2, and ambient temperature based on geo-coded residential addresses. The outcome of interest was the extracellular microRNA (ex-miRNA) profile of each participant over time. We used a longitudinal quantile regression approach to estimate the association between the exposures and each ex-miRNA. Results were corrected for multiple comparisons and ex-miRNAs that were still significantly associated with the exposures were further analyzed using KEGG pathway analysis and Ingenuity Pathway Analysis. RESULTS: We found 151 significant associations between levels of PM2.5, O3, NO2, and ambient temperature and 82 unique ex-miRNAs across multiple quantiles. Most of the significant results were associations with intermediate-term exposure to O3, long-term exposure to PM2.5, and both intermediate and long-term exposure to ambient temperature. The exposures were most often associated with the 75th and 90th percentile of the outcomes. Pathway analyses of significant ex-miRNAs revealed their involvement in biological pathways involving cell function and communication as well as clinical diseases such as cardiovascular disease, respiratory disease, and neurological disease. CONCLUSION: Our results show that intermediate and long-term exposure to all our exposures of interest were associated with changes in the ex-miRNA profile of study participants. Further studies on environmental risk factors and ex-miRNAs are warranted.

Epigenome-wide DNA methylation in leukocytes and toenail metals: The normative aging study.

BACKGROUND: Environmental metal exposures have been associated with multiple deleterious health endpoints. DNA methylation (DNAm) may provide insight into the mechanisms underlying these relationships. Toenail metals are non-invasive biomarkers, reflecting a medium-term time exposure window. OBJECTIVES: This study examined variation in leukocyte DNAm and toenail arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg) among elderly men in the Normative Aging Study, a longitudinal cohort. METHODS: We repeatedly collected samples of blood and toenail clippings. We measured DNAm in leukocytes with the Illumina HumanMethylation450 K BeadChip. We first performed median regression to evaluate the effects of each individual toenail metal on DNAm at three levels: individual cytosine-phosphate-guanine (CpG) sites, regions, and pathways. Then, we applied a Bayesian kernel machine regression (BKMR) to assess the joint and individual effects of metal mixtures on DNAm. Significant CpGs were identified using a multiple testing correction based on the independent degrees of freedom approach for correlated outcomes. The approach considers the effective degrees of freedom in the DNAm data using the principal components that explain >95% variation of the data. RESULTS: We included 564 subjects (754 visits) between 1999 and 2013. The numbers of significantly differentially methylated CpG sites, regions, and pathways varied by metals. For example, we found six significant pathways for As, three for Cd, and one for Mn. The As-associated pathways were associated with cancer (e.g., skin cancer) and cardiovascular disease, whereas the Cd-associated pathways were related to lung cancer. Metal mixtures were also associated with 47 significant CpG sites, as well as pathways, mainly related to cancer and cardiovascular disease. CONCLUSIONS: This study provides an approach to understanding the potential epigenetic mechanisms underlying observed relations between toenail metals and adverse health endpoints.

Long-term exposure to ambient fine particulate components and leukocyte epigenome-wide DNA Methylation in older men: the Normative Aging Study.

BACKGROUND: Epigenome-wide association studies of ambient fine particulate matter (PM2.5) have been reported. However, few have examined PM2.5 components (PMCs) and sources or included repeated measures. The lack of high-resolution exposure measurements is the key limitation. We hypothesized that significant changes in DNA methylation might vary by PMCs and the sources. METHODS: We predicted the annual average of 14 PMCs using novel high-resolution exposure models across the contiguous U.S., between 2000-2018. The resolution was 50 m × 50 m in the Greater Boston Area. We also identified PM2.5 sources using positive matrix factorization. We repeatedly collected blood samples and measured leukocyte DNAm with the Illumina HumanMethylation450K BeadChip in the Normative Aging Study. We then used median regression with subject-specific intercepts to estimate the associations between long-term (one-year) exposure to PMCs / PM2.5 sources and DNA methylation at individual cytosine-phosphate-guanine CpG sites. Significant probes were identified by the number of independent degrees of freedom approach, using the number of principal components explaining > 95% of the variation of the DNA methylation data. We also performed regional and pathway analyses to identify significant regions and pathways. RESULTS: We included 669 men with 1,178 visits between 2000-2013. The subjects had a mean age of 75 years. The identified probes, regions, and pathways varied by PMCs and their sources. For example, iron was associated with 6 probes and 6 regions, whereas nitrate was associated with 15 probes and 3 regions. The identified pathways from biomass burning, coal burning, and heavy fuel oil combustion sources were associated with cancer, inflammation, and cardiovascular diseases, whereas there were no pathways associated with all traffic. CONCLUSIONS: Our findings showed that the effects of PM2.5 on DNAm varied by its PMCs and sources.

ipDMR: identification of differentially methylated regions with interval P-values.

SUMMARY: ipDMR is an R software tool for identification of differentially methylated regions (DMRs) using auto-correlated P-values for individual CpGs from epigenome-wide association analysis using array or bisulfite sequencing data. It summarizes P-values for adjacent CpGs, identifies association peaks and then extends peaks to find boundaries of DMRs. ipDMR uses BED format files as input and is easy to use. Simulations guided by real data found that ipDMR outperformed current available methods and provided slightly higher true positive rates and much lower false discovery rates. AVAILABILITY AND IMPLEMENTATION: ipDMR is available at https://bioconductor.org/packages/release/bioc/html/ENmix.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Associations of Body Composition and Physical Activity Level With Multiple Measures of Epigenetic Age Acceleration.

Epigenetic clocks use DNA methylation to estimate biological age. Whether body composition and physical activity are associated with these clocks is not well understood. Using blood samples collected at enrollment (2003-2009) from 2,758 women in the US nationwide Sister Study, we calculated 6 epigenetic age acceleration metrics using 4 epigenetic clocks (Hannum, Horvath, PhenoAge, GrimAge). Recreational physical activity was self-reported, and adiposity measures were assessed by trained medical examiners (body mass index (BMI), waist-to-hip ratio (WtH), waist circumference). In cross-sectional analyses, all adiposity measures were associated with epigenetic age acceleration. The strongest association was for BMI and PhenoAge, a measure of biological age that correlates with chronic disease (BMI of ≥35.0 vs. 18.5-24.9, ß = 3.15 years, 95% confidence interval (CI): 2.41, 3.90; P for trend < 0.001). In a mutual-adjustment model, both were associated with PhenoAge age acceleration (BMI of ≥35.0 vs. 18.5-24.9, ß = 2.69 years, 95% CI: 1.90, 3.48; P for trend < 0.001; quartile 4 vs.1 WtH, ß = 1.00 years, 95% CI: 0.34, 1.65; P for trend < 0.008). After adjustment, physical activity was associated only with GrimAge (quartile 4 vs. 1, ß = -0.42 years, 95% CI: -0.70, -0.14; P for trend = 0.001). Physical activity attenuated the waist circumference associations with PhenoAge and GrimAge. Excess adiposity was associated with epigenetic age acceleration; physical activity might attenuate associations with waist circumference.

Clinical value of contrast-enhanced computed tomography (CECT) combined with contrast-enhanced ultrasound (CEUS) for characterization and diagnosis of small nodular lesions in liver.

OBJECTIVES: To explore the clinical value of contrast-enhanced computed tomography (CECT) combined with contrast-enhanced ultrasound (CEUS) for characterization and diagnosis of small nodular lesions in the liver and investigate the association between such small nodular lesions and the degree of tumor differentiation. METHODS: Combined imaging modalities were performed on 120 patients who were admitted by Linyi Maternal and Child Health hospital from December 2018 to December 2020 and diagnosed with hepatic nodular lesions. The CT scans were interpreted by two senior imageologists while the ultrasound scans were analyzed by two senior sonographers. A comparative analysis was carried out on different scan modes and the postoperative or post-puncture pathological results using the t-test, the χ2 test, and the Pearson's correlation analysis. RESULTS: Compared to the pathological results, definite diagnoses of 55 malignant cases were made using CECT alone, with the coincidence rate of 78.6%; CECT combined with CEUS formed correct diagnoses in 64 cases, and the coincidence rate was up to 91.4%. The difference between the two scan modes was statistically significant (p= 0.03). Based on pathological diagnosis, seventy out of the 120 cases of small nodular lesions were identified as malignant, while the other 50 cases were benign. The single imaging modality diagnosed 63 malignant and 57 benign nodules, whereas the combined modalities identified 68 malignancies and 52 benign conditions. Compared to CECT as a single imaging modality, the combined modalities showed a higher degree of sensitivity and accuracy, and the difference was statistically significant (sensitivity: p= 0.03; accuracy: p= 0.02); in the malignant cases, the magnitudes of contrast enhancement of CT and ultrasound imaging decreased with an increase in the degree of differentiation, indicating a negative correlation between these factors. CONCLUSIONS: CECT combined with CEUS has a higher coincidence rate, greater sensitivity, and better diagnostic accuracy when being used for characterization and diagnosis of small nodular lesions in the liver. A higher degree of tumor differentiation means a decreased magnitude of contrast enhancement and a blurrier boundary, which indicates that CECT and CEUS are complementary to each other in classifying malignant liver nodules. The use of the combined imaging modalities shows clinical value for characterizing small liver nodules and predicting the degree of malignancy.

Epigenome-wide analysis uncovers a blood-based DNA methylation biomarker of lifetime cannabis use.

Cannabis use is highly prevalent and is associated with adverse and beneficial effects. To better understand the full spectrum of health consequences, biomarkers that accurately classify cannabis use are needed. DNA methylation (DNAm) is an excellent candidate, yet no blood-based epigenome-wide association studies (EWAS) in humans exist. We conducted an EWAS of lifetime cannabis use (ever vs. never) using blood-based DNAm data from a case-cohort study within Sister Study, a prospective cohort of women at risk of developing breast cancer (Discovery N = 1,730 [855 ever users]; Replication N = 853 [392 ever users]). We identified and replicated an association with lifetime cannabis use at cg15973234 (CEMIP): combined p = 3.3 × 10-8 . We found no overlap between published blood-based cis-meQTLs of cg15973234 and reported lifetime cannabis use-associated single nucleotide polymorphism (SNPs; p < .05), suggesting that the observed DNAm difference was driven by cannabis exposure. We also developed a multi-CpG classifier of lifetime cannabis use using penalized regression of top EWAS CpGs. The resulting 50-CpG classifier produced an area under the curve (AUC) = 0.74 (95% CI [0.72, 0.76], p = 2.00 × 10-5 ) in the discovery sample and AUC = 0.54 ([0.51, 0.57], p = 2.87 × 10-2 ) in the replication sample. Our EWAS findings provide evidence that blood-based DNAm is associated with lifetime cannabis use.

Alcohol and DNA Methylation: An Epigenome-Wide Association Study in Blood and Normal Breast Tissue.

The biological mechanisms driving associations between alcohol consumption and chronic diseases might include epigenetic modification of DNA methylation. We explored the hypothesis that alcohol consumption is associated with methylation in an epigenome-wide association study of blood and normal breast tissue DNA. Infinium HumanMethylation450 BeadChip (Illumina Inc., San Diego, California) array data on blood DNA methylation was examined in a discovery set of 2,878 non-Hispanic white women from the Sister Study (United States, 2004-2015) who provided detailed questionnaire information on lifetime alcohol use. Robust linear regression modeling was used to identify significant associations (false discovery rate of Q < 0.05) between the number of alcoholic drinks per week and DNA methylation at 5,458 cytosine-phosphate-guanine (CpG) sites. Associations were replicated (P < 0.05) for 677 CpGs in an independent set of 187 blood DNA samples from the Sister Study and for 628 CpGs in an independent set of 171 normal breast DNA samples; 1,207 CpGs were replicated in either blood or normal breast, with 98 CpGs replicated in both tissues. Individual gene effects were notable for phosphoglycerate dehydrogenase (PGHDH), peptidyl-prolyl cis-trans isomerase (PPIF), solute carrier 15 (SLC15), solute carrier family 43 member 1 (SLC43A1), and solute carrier family 7 member 11 (SLC7A11). We also found that high alcohol consumption was associated with significantly lower global methylation as measured by the average of CpGs on the entire array.

Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium.

Pre-pregnancy maternal obesity is associated with adverse offspring outcomes at birth and later in life. Individual studies have shown that epigenetic modifications such as DNA methylation could contribute. Within the Pregnancy and Childhood Epigenetics (PACE) Consortium, we meta-analysed the association between pre-pregnancy maternal BMI and methylation at over 450,000 sites in newborn blood DNA, across 19 cohorts (9,340 mother-newborn pairs). We attempted to infer causality by comparing the effects of maternal versus paternal BMI and incorporating genetic variation. In four additional cohorts (1,817 mother-child pairs), we meta-analysed the association between maternal BMI at the start of pregnancy and blood methylation in adolescents. In newborns, maternal BMI was associated with small (<0.2% per BMI unit (1 kg/m2), P < 1.06 × 10-7) methylation variation at 9,044 sites throughout the genome. Adjustment for estimated cell proportions greatly attenuated the number of significant CpGs to 104, including 86 sites common to the unadjusted model. At 72/86 sites, the direction of the association was the same in newborns and adolescents, suggesting persistence of signals. However, we found evidence for acausal intrauterine effect of maternal BMI on newborn methylation at just 8/86 sites. In conclusion, this well-powered analysis identified robust associations between maternal adiposity and variations in newborn blood DNA methylation, but these small effects may be better explained by genetic or lifestyle factors than a causal intrauterine mechanism. This highlights the need for large-scale collaborative approaches and the application of causal inference techniques in epigenetic epidemiology.

DNA Methylation in Newborns and Maternal Smoking in Pregnancy: Genome-wide Consortium Meta-analysis.

Epigenetic modifications, including DNA methylation, represent a potential mechanism for environmental impacts on human disease. Maternal smoking in pregnancy remains an important public health problem that impacts child health in a myriad of ways and has potential lifelong consequences. The mechanisms are largely unknown, but epigenetics most likely plays a role. We formed the Pregnancy And Childhood Epigenetics (PACE) consortium and meta-analyzed, across 13 cohorts (n = 6,685), the association between maternal smoking in pregnancy and newborn blood DNA methylation at over 450,000 CpG sites (CpGs) by using the Illumina 450K BeadChip. Over 6,000 CpGs were differentially methylated in relation to maternal smoking at genome-wide statistical significance (false discovery rate, 5%), including 2,965 CpGs corresponding to 2,017 genes not previously related to smoking and methylation in either newborns or adults. Several genes are relevant to diseases that can be caused by maternal smoking (e.g., orofacial clefts and asthma) or adult smoking (e.g., certain cancers). A number of differentially methylated CpGs were associated with gene expression. We observed enrichment in pathways and processes critical to development. In older children (5 cohorts, n = 3,187), 100% of CpGs gave at least nominal levels of significance, far more than expected by chance (p value < 2.2 × 10(-16)). Results were robust to different normalization methods used across studies and cell type adjustment. In this large scale meta-analysis of methylation data, we identified numerous loci involved in response to maternal smoking in pregnancy with persistence into later childhood and provide insights into mechanisms underlying effects of this important exposure.

Reproduction, DNA methylation and biological age.

STUDY QUESTION: Are reproductive characteristics associated with genome-wide DNA methylation and epigenetic age? SUMMARY ANSWER: Our data suggest that increasing parity is associated with differences in blood DNA methylation and small increases in epigenetic age. WHAT IS KNOWN ALREADY: A study of 397 young Filipino women (ages 20-22) observed increasing epigenetic age with an increasing number of pregnancies. STUDY DESIGN, SIZE, DURATION: We used data from 2356 non-Hispanic white women (ages 35-74) enrolled in the Sister Study cohort. PARTICIPANTS/MATERIALS, SETTING, METHODS: Data on reproductive history were ascertained via questionnaire. Of the 2356 women, 1897 (81%) reported at least one live birth. Among parous women, 487 (26%) women reported ever experiencing a pregnancy complication. Three epigenetic clocks (i.e. Hannum, Horvath and Levine) and genome-wide methylation were measured in DNA from whole blood using Illumina's HumanMethylation450 BeadChip. We estimated association ß-values and 95% CIs using linear regression. MAIN RESULTS AND THE ROLE OF CHANCE: All three epigenetic clocks showed weak associations between number of births and epigenetic age (per live birth; Hannum: ß = 0.16, 95% CI = 0.02, 0.29, P = 0.03; Horvath: ß = 0.12, 95% CI = -0.04, 0.27, P = 0.14; Levine: ß = 0.27, 95% CI = 0.08, 0.45, P = 0.01); however, additional adjustment for current BMI attenuated the associations. Among parous women, a history of abnormal glucose tolerance during pregnancy was associated with increased epigenetic age by the Hannum clock (ß = 0.96; 95% CI = 0.10, 1.81; P = 0.03) and Levine clocks (ß = 1.69; 95% CI = 0.54, 2.84; P < 0.01). In epigenome-wide analysis, increasing parity was associated with methylation differences at 17 CpG sites (Bonferroni corrected P≤ 1.0 × 10-7). LIMITATIONS, REASONS FOR CAUTION: We relied on retrospective recall to ascertain reproductive history and pregnancy complications. WIDER IMPLICATIONS OF THE FINDINGS: Our findings suggest that parity is associated with small increases in epigenetic age and with DNA methylation at multiple sites in the genome. STUDY FUNDING/COMPETING INTEREST(S): This research was supported by the Intramural Research program of the NIH, National Institute of Environmental Health Sciences (Z01-ES049033, Z01-ES049032 and Z01-ES044055). None of the authors have a conflict of interest. TRIAL REGISTRATION NUMBER: Not applicable.

Vitamin D, DNA methylation, and breast cancer.

BACKGROUND: Vitamin D has anticarcinogenic and immune-related properties and may protect against some diseases, including breast cancer. Vitamin D affects gene transcription and may influence DNA methylation. METHODS: We studied the relationships between serum vitamin D, DNA methylation, and breast cancer using a case-cohort sample (1070 cases, 1277 in subcohort) of non-Hispanic white women. For our primary analysis, we used robust linear regression to examine the association between serum 25-hydroxyvitamin D (25(OH)D) and methylation within a random sample of the cohort ("subcohort"). We focused on 198 CpGs in or near seven vitamin D-related genes. For these 198 candidate CpG loci, we also examined how multiplicative interactions between methylation and 25(OH)D were associated with breast cancer risk. This was done using Cox proportional hazards models and the full case-cohort sample. We additionally conducted an exploratory epigenome-wide association study (EWAS) of the association between 25(OH)D and DNA methylation in the subcohort. RESULTS: Of the CpGs in vitamin D-related genes, cg21201924 (RXRA) had the lowest p value for association with 25(OH)D (p = 0.0004). Twenty-two other candidate CpGs were associated with 25(OH)D (p < 0.05; RXRA, NADSYN1/DHCR7, GC, or CYP27B1). We observed an interaction between 25(OH)D and methylation at cg21201924 in relation to breast cancer risk (ratio of hazard ratios = 1.22, 95% confidence interval 1.10-1.34; p = 7 × 10-5), indicating a larger methylation-breast cancer hazard ratio in those with high serum 25(OH)D concentrations. We also observed statistically significant (p < 0.05) interactions for six other RXRA CpGs and CpGs in CYP24A1, CYP27B1, NADSYN1/DHCR7, and VDR. In the EWAS of the subcohort, 25(OH)D was associated (q < 0.05) with methylation at cg24350360 (EPHX1; p = 3.4 × 10-8), cg06177555 (SPN; p = 9.8 × 10-8), and cg13243168 (SMARCD2; p = 2.9 × 10-7). CONCLUSIONS: 25(OH)D concentrations were associated with DNA methylation of CpGs in several vitamin D-related genes, with potential links to immune function-related genes. Methylation of CpGs in vitamin D-related genes may interact with 25(OH)D to affect the risk of breast cancer.

ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip.

The Illumina HumanMethylation450 BeadChip is increasingly utilized in epigenome-wide association studies, however, this array-based measurement of DNA methylation is subject to measurement variation. Appropriate data preprocessing to remove background noise is important for detecting the small changes that may be associated with disease. We developed a novel background correction method, ENmix, that uses a mixture of exponential and truncated normal distributions to flexibly model signal intensity and uses a truncated normal distribution to model background noise. Depending on data availability, we employ three approaches to estimate background normal distribution parameters using (i) internal chip negative controls, (ii) out-of-band Infinium I probe intensities or (iii) combined methylated and unmethylated intensities. We evaluate ENmix against other available methods for both reproducibility among duplicate samples and accuracy of methylation measurement among laboratory control samples. ENmix out-performed other background correction methods for both these measures and substantially reduced the probe-design type bias between Infinium I and II probes. In reanalysis of existing EWAS data we show that ENmix can identify additional CpGs, and results in smaller P-value estimates for previously-validated CpGs. We incorporated the method into R package ENmix, which is freely available from Bioconductor website.

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

BACKGROUND: The Illumina Infinium HumanMethylation450 BeadChip and its successor, Infinium MethylationEPIC BeadChip, have been extensively utilized in epigenome-wide association studies. Both arrays use two fluorescent dyes (Cy3-green/Cy5-red) to measure methylation level at CpG sites. However, performance difference between dyes can result in biased estimates of methylation levels. RESULTS: Here we describe a novel method, called REgression on Logarithm of Internal Control probes (RELIC) to correct for dye bias on whole array by utilizing the intensity values of paired internal control probes that monitor the two color channels. We evaluate the method in several datasets against other widely used dye-bias correction methods. Results on data quality improvement showed that RELIC correction statistically significantly outperforms alternative dye-bias correction methods. We incorporated the method into the R package ENmix, which is freely available from the Bioconductor website ( https://www.bioconductor.org/packages/release/bioc/html/ENmix.html ). CONCLUSIONS: RELIC is an efficient and robust method to correct for dye-bias in Illumina Methylation BeadChip data. It outperforms other alternative methods and conveniently implemented in R package ENmix to facilitate DNA methylation studies.

RCP: a novel probe design bias correction method for Illumina Methylation BeadChip.

MOTIVATION: The Illumina HumanMethylation450 BeadChip has been extensively utilized in epigenome-wide association studies. This array and its successor, the MethylationEPIC array, use two types of probes-Infinium I (type I) and Infinium II (type II)-in order to increase genome coverage but differences in probe chemistries result in different type I and II distributions of methylation values. Ignoring the difference in distributions between the two probe types may bias downstream analysis. RESULTS: Here, we developed a novel method, called Regression on Correlated Probes (RCP), which uses the existing correlation between pairs of nearby type I and II probes to adjust the beta values of all type II probes. We evaluate the effect of this adjustment on reducing probe design type bias, reducing technical variation in duplicate samples, improving accuracy of measurements against known standards, and retention of biological signal. We find that RCP is statistically significantly better than unadjusted data or adjustment with alternative methods including SWAN and BMIQ. AVAILABILITY: We incorporated the method into the R package ENmix, which is freely available from the Bioconductor website (https://www.bioconductor.org/packages/release/bioc/html/ENmix.html). CONTACT: niulg@ucmail.uc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

oxBS-MLE: an efficient method to estimate 5-methylcytosine and 5-hydroxymethylcytosine in paired bisulfite and oxidative bisulfite treated DNA.

MOTIVATION: 5-Methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) are important epigenetic regulators of gene expression. 5mC and 5hmC levels can be computationally inferred at single base resolution using sequencing or array data from paired DNA samples that have undergone bisulfite and oxidative bisulfite conversion. Current estimation methods have been shown to produce irregular estimates of 5hmC level or are extremely computation intensive. RESULTS: We developed an efficient method oxBS-MLE based on binomial modeling of paired bisulfite and oxidative bisulfite data from sequencing or array analysis. Evaluation in several datasets showed that it outperformed alternative methods in estimate accuracy and computation speed. AVAILABILITY AND IMPLEMENTATION: oxBS-MLE is implemented in Bioconductor package ENmix. CONTACT: niulg@ucmail.uc.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Body mass index associated with genome-wide methylation in breast tissue.

Gene expression studies indicate that body mass index (BMI) is associated with molecular pathways involved in inflammation, insulin-like growth factor activation, and other carcinogenic processes in breast tissue. The goal of this study was to determine whether BMI is associated with gene methylation in breast tissue and to identify pathways that are commonly methylated in association with high BMI. Epigenome-wide methylation profiles were determined using the Illumina HumanMethylation450 BeadChip array in the non-diseased breast tissue of 81 women undergoing breast surgery between 2009 and 2013 at the University of North Carolina Hospitals. Multivariable, robust linear regression was performed to identify methylation sites associated with BMI at a false discovery rate q value <0.05. Gene expression microarray data was used to identify which of the BMI-associated methylation sites also showed correlation with gene expression. Gene set enrichment analysis was conducted to assess which pathways were enriched among the BMI-associated methylation sites. Of the 431,568 methylation sites analyzed, 2573 were associated with BMI (q value <0.05), 57 % of which showed an inverse correlation with BMI. Pathways enriched among the 2573 probe sites included those involved in inflammation, insulin receptor signaling, and leptin signaling. We were able to map 1251 of the BMI-associated methylation sites to gene expression data, and, of these, 226 (18 %) showed substantial correlations with gene expression. Our results suggest that BMI is associated with genome-wide methylation in non-diseased breast tissue and may influence epigenetic pathways involved in inflammatory and other carcinogenic processes.