Deglycation activity of the Escherichia coli glycolytic enzyme phosphoglucose isomerase.

Glycation is a spontaneous chemical reaction, which affects the structure and function of proteins under normal physiological conditions. Therefore, organisms have evolved diverse mechanisms to combat glycation. In this study, we show that the Escherichia coli glycolytic enzyme phosphoglucose isomerase (Pgi) exhibits deglycation activity. We found that E. coli Pgi catalyzes the breakdown of glucose 6-phosphate (G6P)-derived Amadori products (APs) in chicken lysozyme. The affinity of Pgi to the glycated lysozyme (Km, 1.1 mM) was ten times lower than the affinity to its native substrate, fructose 6-phosphate (Km, 0.1 mM). However, the high kinetic constants of the enzyme with the glycated lysozyme (kcat, 396 s-1 and kcat/Km, 3.6 × 105 M-1 s-1) indicated that the Pgi amadoriase activity may have physiological implications. Indeed, when using total E. coli protein (20 mg/mL) as a substrate in the deglycation reaction, we observed a release of G6P from the bacterial protein at a Pgi specific activity of 33 µmol/min/mg. Further, we detected 11.4 % lower APs concentration in protein extracts from Pgi-proficient vs. deficient cells (p = 0.0006) under conditions where the G6P concentration in Pgi-proficient cells was four times higher than in Pgi-deficient cells (p = 0.0001). Altogether, these data point to physiological relevance of the Pgi deglycation activity.

Pruning and thresholding approach for methylation risk scores in multi-ancestry populations.

Recent efforts have focused on developing methylation risk scores (MRS), a weighted sum of the individual's DNA methylation (DNAm) values of pre-selected CpG sites. Most of the current MRS approaches that utilize Epigenome-wide association studies (EWAS) summary statistics only include genome-wide significant CpG sites and do not consider co-methylation. New methods that relax the p-value threshold to include more CpG sites and account for the inter-correlation of DNAm might improve the predictive performance of MRS. We paired informed co-methylation pruning with P-value thresholding to generate pruning and thresholding (P+T) MRS and evaluated its performance among multi-ancestry populations. Through simulation studies and real data analyses, we demonstrated that pruning provides an improvement over simple thresholding methods for prediction of phenotypes. We demonstrated that European-derived summary statistics can be used to develop P+T MRS among other populations such as African populations. However, the prediction accuracy of P+T MRS may differ across multi-ancestry population due to environmental/cultural/social differences.

Autosomal sex-associated co-methylated regions predict biological sex from DNA methylation.

Sex is a modulator of health that has been historically overlooked in biomedical research. Recognizing this knowledge gap, funding agencies now mandate the inclusion of sex as a biological variable with the goal of stimulating efforts to illuminate the molecular underpinnings of sex biases in health and disease. DNA methylation (DNAm) is a strong molecular candidate for mediating such sex biases; however, a robust and well characterized annotation of sex differences in DNAm is yet to emerge. Beginning with a large (n = 3795) dataset of DNAm profiles from normative adult whole blood samples, we identified, validated and characterized autosomal sex-associated co-methylated genomic regions (sCMRs). Strikingly, sCMRs showed consistent sex differences in DNAm over the life course and a subset were also consistent across cell, tissue and cancer types. sCMRs included sites with known sex differences in DNAm and links to health conditions with sex biased effects. The robustness of sCMRs enabled the generation of an autosomal DNAm-based predictor of sex with 96% accuracy. Testing this tool on blood DNAm profiles from individuals with sex chromosome aneuploidies (Klinefelter [47,XXY], Turner [45,X] and 47,XXX syndrome) revealed an intimate relationship between sex chromosomes and sex-biased autosomal DNAm.

CoMeBack: DNA methylation array data analysis for co-methylated regions.

MOTIVATION: High-dimensional DNA methylation (DNAm) array coverage, while sparse in the context of the entire DNA methylome, still constitutes a very large number of CpG probes. The ensuing multiple-test corrections affect the statistical power to detect associations, likely contributing to prevalent limited reproducibility. Array probes measuring proximal CpG sites often have correlated levels of DNAm that may not only be biologically meaningful but also imply statistical dependence and redundancy. New methods that account for such correlations between adjacent probes may enable improved specificity, discovery and interpretation of statistical associations in DNAm array data. RESULTS: We developed a method named Co-Methylation with genomic CpG Background (CoMeBack) that estimates DNA co-methylation, defined as proximal CpG probes with correlated DNAm across individuals. CoMeBack outputs co-methylated regions (CMRs), spanning sets of array probes constructed based on all genomic CpG sites, including those not measured on the array, and without any phenotypic variable inputs. This approach can reduce the multiple-test correction burden, while enhancing the discovery and specificity of statistical associations. We constructed and validated CMRs in whole blood, using publicly available Illumina Infinium 450 K array data from over 5000 individuals. These CMRs were enriched for enhancer chromatin states, and binding site motifs for several transcription factors involved in blood physiology. We illustrated how CMR-based epigenome-wide association studies can improve discovery and reduce false positives for associations with chronological age. AVAILABILITY AND IMPLEMENTATION: https://bitbucket.org/flopflip/comeback. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Exposure to childhood abuse is associated with human sperm DNA methylation.

Offspring of persons exposed to childhood abuse are at higher risk of neurodevelopmental and physical health disparities across the life course. Animal experiments have indicated that paternal environmental stressors can affect sperm DNA methylation and gene expression in an offspring. Childhood abuse has been associated with epigenetic marks in human blood, saliva, and brain tissue, with statistically significant methylation differences ranging widely. However, no studies have examined the association of childhood abuse with DNA methylation in gametes. We examined the association of childhood abuse with DNA methylation in human sperm. Combined physical, emotional, and sexual abuse in childhood was characterized as none, medium, or high. DNA methylation was assayed in 46 sperm samples from 34 men in a longitudinal non-clinical cohort using HumanMethylation450 BeadChips. We performed principal component analysis and examined the correlation of principal components with abuse exposure. Childhood abuse was associated with a component that captured 6.2% of total variance in DNA methylation (p < 0.05). Next, we investigated the regions differentially methylated by abuse exposure. We identified 12 DNA regions differentially methylated by childhood abuse, containing 64 probes and including sites on genes associated with neuronal function (MAPT, CLU), fat cell regulation (PRDM16), and immune function (SDK1). We examined adulthood health behaviors, mental health, and trauma exposure as potential mediators of an association between abuse and DNAm, and found that mental health and trauma exposure partly mediated the association. Finally, we constructed a parsimonious epigenetic marker for childhood abuse using a machine learning approach, which identified three probes that predicted high vs. no childhood abuse in 71% of participants. Our results suggested that childhood abuse is associated with sperm DNA methylation, which may have implications for offspring development. Larger samples are needed to identify with greater confidence specific genomic regions differentially methylated by childhood abuse.

DNA methylation signatures in peripheral blood mononuclear cells from a lifestyle intervention for women at midlife: a pilot randomized controlled trial.

Physical activity confers many health benefits, but the underlying mechanisms require further exploration. In this pilot randomized controlled trial we tested the association between longitudinal measures of DNA methylation and changes in objective measures, including physical activity, weight loss, and C-reactive protein levels in community-dwelling women aged 55 to 70 years. We assessed DNA methylation from 20 healthy postmenopausal women, who did not have a mobility disability and allocated them to a group-based intervention, Everyday Activity Supports You, or a control group (monthly group-based health-related education sessions). The original randomized controlled trial was 6 months in duration and consisted of nine 2-h sessions that focused on reducing sedentary behaviour for the intervention group, or six 1-h sessions that focused on other topics for the control group. We collected peripheral blood mononuclear cells, both at baseline and 6 months later. Samples were processed using the Illumina 450k Methylation array to quantify DNA methylation at >485 000 CpG sites in the genome. There were no significant associations between DNA methylation and physical activity, but we did observe alterations at epigenetic modifications that correlated with change in percent body weight over a 6-month period at 12 genomic loci, 2 of which were located near the previously reported weight-associated genes RUNX3 and NAMPT. We also generated a potential epigenetic predictor of weight loss using baseline DNA methylation at 5 CpG sites. These exploratory findings suggest a potential biological link between body weight changes and epigenetic processes.

Maternal blood contamination of collected cord blood can be identified using DNA methylation at three CpGs.

BACKGROUND: Cord blood is a commonly used tissue in environmental, genetic, and epigenetic population studies due to its ready availability and potential to inform on a sensitive period of human development. However, the introduction of maternal blood during labor or cross-contamination during sample collection may complicate downstream analyses. After discovering maternal contamination of cord blood in a cohort study of 150 neonates using Illumina 450K DNA methylation (DNAm) data, we used a combination of linear regression and random forest machine learning to create a DNAm-based screening method. We identified a panel of DNAm sites that could discriminate between contaminated and non-contaminated samples, then designed pyrosequencing assays to pre-screen DNA prior to being assayed on an array. RESULTS: Maternal contamination of cord blood was initially identified by unusual X chromosome DNA methylation patterns in 17 males. We utilized our DNAm panel to detect contaminated male samples and a proportional amount of female samples in the same cohort. We validated our DNAm screening method on an additional 189 sample cohort using both pyrosequencing and DNAm arrays, as well as 9 publically available cord blood 450K data sets. The rate of contamination varied from 0 to 10% within these studies, likely related to collection specific methods. CONCLUSIONS: Maternal blood can contaminate cord blood during sample collection at appreciable levels across multiple studies. We have identified a panel of markers that can be used to identify this contamination, either post hoc after DNAm arrays have been completed, or in advance using a targeted technique like pyrosequencing.