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The development of biological markers of aging has primarily focused on adult samples. Epigenetic clocks are a promising tool for measuring biological age that show impressive accuracy across most tissues and age ranges. In adults, deviations from the DNA methylation (DNAm) age prediction are correlated with several age-related phenotypes, such as mortality and frailty. In children, however, fewer such associations have been made, possibly because DNAm changes are more dynamic in pediatric populations as compared to adults. To address this gap, we aimed to develop a highly accurate, noninvasive, biological measure of age specific to pediatric samples using buccal epithelial cell DNAm. We gathered 1,721 genome-wide DNAm profiles from 11 different cohorts of typically developing individuals aged 0 to 20 y old. Elastic net penalized regression was used to select 94 CpG sites from a training dataset (n = 1,032), with performance assessed in a separate test dataset (n = 689). DNAm at these 94 CpG sites was highly predictive of age in the test cohort (median absolute error = 0.35 y). The Pediatric-Buccal-Epigenetic (PedBE) clock was characterized in additional cohorts, showcasing the accuracy in longitudinal data, the performance in nonbuccal tissues and adult age ranges, and the association with obstetric outcomes. The PedBE tool for measuring biological age in children might help in understanding the environmental and contextual factors that shape the DNA methylome during child development, and how it, in turn, might relate to child health and disease.

Multiple myeloma is an incurable hematological malignancy that relies on drug combinations for first and secondary lines of treatment. The inclusion of proteasome inhibitors, such as bortezomib, into these combination regimens has improved median survival. Resistance to bortezomib, however, is a common occurrence that ultimately contributes to treatment failure, and there remains a need to identify improved drug combinations. We developed the quadratic phenotypic optimization platform (QPOP) to optimize treatment combinations selected from a candidate pool of 114 approved drugs. QPOP uses quadratic surfaces to model the biological effects of drug combinations to identify effective drug combinations without reference to molecular mechanisms or predetermined drug synergy data. Applying QPOP to bortezomib-resistant multiple myeloma cell lines determined the drug combinations that collectively optimized treatment efficacy. We found that these combinations acted by reversing the DNA methylation and tumor suppressor silencing that often occur after acquired bortezomib resistance in multiple myeloma. Successive application of QPOP on a xenograft mouse model further optimized the dosages of each drug within a given combination while minimizing overall toxicity in vivo, and application of QPOP to ex vivo multiple myeloma patient samples optimized drug combinations in patient-specific contexts.

Context: Antenatal hyperglycemia is associated with increased risk of future adverse health outcomes in both mother and child. Variations in offspring's epigenome can reflect the impact and response to in utero glycemic exposure, and may have different consequences for the child. Objective: We examined possible differences in associations of basal glucose status and glucose handling during pregnancy with both clinical covariates and offspring cord tissue DNA methylation. Research Design and Methods: This study included 830 mother-offspring dyads from the Growing Up in Singapore Towards Healthy Outcomes cohort. The fetal epigenome of umbilical cord tissue was profiled using Illumina HumanMethylation450 arrays. Associations of maternal mid-pregnancy fasting (fasting plasma glucose [FPG]) and 2-hour plasma glucose (2hPG) after a 75-g oral glucose challenge with both maternal clinical phenotypes and offspring epigenome at delivery were investigated separately. Results: Maternal age, prepregnancy body mass index, and blood pressure measures were associated with both FPG and 2hPG, whereas Chinese ethnicity (P = 1.9 × 10-4), maternal height (P = 1.1 × 10-4), pregnancy weight gain (P = 2.2 × 10-3), prepregnancy alcohol consumption (P = 4.6 × 10-4), and tobacco exposure (P = 1.9 × 10-3) showed significantly opposite associations between the 2 glucose measures. Most importantly, we observed a dichotomy in the effects of these glycemic indices on the offspring epigenome. Offspring born to mothers with elevated 2hPG showed global hypomethylation. CpGs most associated with the 2 measures also reflected differences in gene ontologies and had different associations with offspring birthweight. Conclusions: Our findings suggest that 2 traditionally used glycemic indices for diagnosing gestational diabetes may reflect distinctive pathophysiologies in pregnancy, and have differential impacts on the offspring's DNA methylome. [ABSTRACT FROM AUTHOR]

Assisted reproductive technologies (ART) are increasingly used, however little is known about the long-term health of ART-conceived offspring. Weak selection of comparison groups and poorly characterized mechanisms impede current understanding. In a prospective cohort (Growing Up in Singapore Towards healthy Outcomes; GUSTO; Clinical Trials ID: NCT01174875) including 83 ART-conceived and 1095 spontaneously-conceived singletons, we estimate effects of ART on anthropometry, blood pressure, serum metabolic biomarkers, and cord tissue DNA methylation by emulating a pragmatic trial supported by machine learning-based estimators. We find ART-conceived children to be shorter (−0.5 SD [95% CI: −0.7, −0.2]), lighter (−0.6 SD [−0.9, −0.3]) and have lower skinfold thicknesses (e.g. −14% [−24%, −3%] suprailiac), and blood pressure (−3 mmHg [−6, −0.5] systolic) at 6-6.5 years, with no strong differences in metabolic biomarkers. Differences are not explained by parental anthropometry or comorbidities, polygenic risk score, breastfeeding, or illnesses. Our simulations demonstrate ART is strongly associated with lower NECAB3 DNA methylation, with negative control analyses suggesting these estimates are unbiased. However, methylation changes do not appear to mediate observed differences in child phenotype. Huang and colleagues used machine-learning estimators to analyse a broad range of parameters in a prospective cohort consisting ART and spontaneously conceived children. Small differences in stature and growth could not be explained by parental or perinatal environment factors, nor differences in fetal DNA methylation. No strong differences in metabolic parameters were seen. [ABSTRACT FROM AUTHOR]

Objectives: To assess whether epigenetic mechanisms affecting gene expression may be involved in the pathogenesis of early-onset myopia, we performed genome-wide DNA methylation analyses of umbilical cord tissues, and assessed any associations between CpG site-specific methylation and the development of the disorder when the children were 3 years old. Methods: Genome-wide DNA methylation profiling of umbilical cord samples from 519 Singaporean infants involved in a prospective birth cohort ‘Growing Up in Singapore Towards healthy Outcomes’ (GUSTO) was performed using the Illumina Infinium HumanMethylation450K chip microarray. Multivariable logistic regression models were used to assess any associations between site-specific CpG methylation of umbilical cord tissue at birth and myopia risk in 3 year old children, adjusting for potential confounders. Gene expression of genes located near CpG sites that demonstrated statistically significant associations were measured in relevant ocular tissues using human and mouse fetal and adult eye samples. Results: We identified statistically significant associations between DNA methylation levels at five CpG sites and early-onset myopia risk after correcting for multiple comparisons using a false discovery rate of 5%. Two statistically significant CpG sites were identified in intergenic regions: 8p23(p = 1.70×10−7) and 12q23.2(p = 2.53×10−7). The remaining 3 statistically significant CpG sites were identified within the following genes: FGB (4q28, p = 3.60×10−7), PQLC1 (18q23, p = 8.9×10−7) and KRT12 (17q21.2, p = 1.2×10−6). Both PQLC1 and KRT12 were found to be significantly expressed in fetal and adult cornea and sclera tissues in both human and mouse. Conclusions: We identified five CpG methylation sites that demonstrate a statistically significant association with increased risk of developing early-onset myopia. These findings suggest that variability in the neonatal cord epigenome may influence early-onset myopia risk in children. Further studies of the epigenetic influences on myopia risk in larger study populations, and the associations with adulthood myopia risk are warranted. [ABSTRACT FROM AUTHOR]

Accounting for cellular heterogeneity is essential in neonatal epigenome-wide association studies (EWAS) performed on heterogeneous tissues, such as umbilical cord tissue (CT) or cord blood (CB). Using a reference-panel-based statistical approach, the cell type composition of heterogeneous tissues can be estimated by comparison of whole tissue DNA methylation profiles with cell type-specific DNA methylation signatures. Currently, there is no adequate DNA methylation reference panel for CT, and existing CB panels have been generated on lower coverage Infinium HumanMethylation450 arrays. In this study, we generate a reference panel for CT and improve available CB panels by using the higher coverage Infinium MethylationEPIC arrays. We performed DNA methylation profiling of 9 cell types isolated from CT and CB samples from 14 neonates. In addition to these cell types, we profiled DNA methylation of unfractionated CT and CB. Cell type composition of these unfractionated tissue samples, as estimated by our reference panels, was in agreement with that obtained by flow cytometry. Expectedly, DNA methylation profiles from CT and CB were distinct, reflecting their mesenchymal and hematopoietic stem cell origins. Variable CpGs from both unfractionated CT and its isolated cell types were more likely to be located in open seas and intronic regions than those in CB. Cell type specific CpGs in CT were enriched in intercellular matrix pathways, while those from CB were enriched in immune-related pathways. This study provides an open source reference panel for estimation and adjustment of cellular heterogeneity in CT and CB, and broadens the scope of tissue utilization assessed in future neonatal EWAS studies. [ABSTRACT FROM AUTHOR]

Background: Epigenomes are tissue specific and thus the choice of surrogate tissue can play a critical role in interpreting neonatal epigenome-wide association studies (EWAS) and in their extrapolation to target tissue. To develop a better understanding of the link between tissue specificity and neonatal EWAS, and the contributions of genotype and prenatal factors, we compared genome-wide DNA methylation of cord tissue and cord blood, two of the most accessible surrogate tissues at birth.Methods: In 295 neonates, DNA methylation was profiled using Infinium HumanMethylation450 beadchip arrays. Sites of inter-individual variability in DNA methylation were mapped and compared across the two surrogate tissues at birth, i.e., cord tissue and cord blood. To ascertain the similarity to target tissues, DNA methylation profiles of surrogate tissues were compared to 25 primary tissues/cell types mapped under the Epigenome Roadmap project. Tissue-specific influences of genotype on the variable CpGs were also analyzed. Finally, to interrogate the impact of the in utero environment, EWAS on 45 prenatal factors were performed and compared across the surrogate tissues.Results: Neonatal EWAS results were tissue specific. In comparison to cord blood, cord tissue showed higher inter-individual variability in the epigenome, with a lower proportion of CpGs influenced by genotype. Both neonatal tissues were good surrogates for target tissues of mesodermal origin. They also showed distinct phenotypic associations, with effect sizes of the overlapping CpGs being in the same order of magnitude.Conclusions: The inter-relationship between genetics, prenatal factors and epigenetics is tissue specific, and requires careful consideration in designing and interpreting future neonatal EWAS.Trial Registration: This birth cohort is a prospective observational study, designed to study the developmental origins of health and disease, and was retrospectively registered on 1 July 2010 under the identifier NCT01174875 . [ABSTRACT FROM AUTHOR]

HIV-Tat-interacting protein of 60 kDa (TIP60) is a lysine acetyltransferase and known to be downregulated in multiple cancers. Among various signalling pathways, TIP60 is implicated in regulating epithelial-mesenchymal transition (EMT). Here, we show that TIP60 expression abrogates cell migration and metastatic potential of breast cancer cells using in vitro and in vivo models. Mechanistically, we show that this is through its ability to destabilize DNMT1 and inhibit SNAIL2 function (SNAIL2-mediated EMT/cell migration). Depletion of TIP60 stabilizes DNMT1 and increases SNAIL2 levels, resulting in EMT. Recruitment of DNMT1 to the SNAIL2 targets in the absence of TIP60 increases DNA methylation on their promoter region and further represses the expression of epithelial markers. In pathophysiological scenario, we find TIP60 to be significantly downregulated in breast cancer patients with poor overall survival and disease-free survival prognoses. These data suggest that levels of TIP60 can be a prognostic marker of breast cancer progression and stabilization of TIP60 could be a promising strategy to treat cancers. [ABSTRACT FROM AUTHOR]

Background: The interplay among genetic, environment and epigenetic variation is not fully understood. Advances in high-throughput genotyping methods, high-density DNA methylation detection and well-characterized sample collections, enable epigenetic association studies at the genomic and population levels (EWAS). The field has extended to interrogate the interaction of environmental and genetic (GxE) influences on epigenetic variation. Also, the detection of methylation quantitative trait loci (methQTLs) and their association with health status has enhanced our knowledge of epigenetic mechanisms in disease trajectory. However analysis of this type of data brings computational challenges and there are few practical solutions to enable large scale studies in standard computational environments. Results: GEM is a highly efficient R tool suite for performing epigenome wide association studies (EWAS). GEM provides three major functions named GEM_Emodel, GEM_Gmodel and GEM_GxEmodel to study the interplay of Gene, Environment and Methylation (GEM). Within GEM, the pre-existing "Matrix eQTL" package is utilized and extended to study methylation quantitative trait loci (methQTL) and the interaction of genotype and environment (GxE) to determine DNA methylation variation, using matrix based iterative correlation and memory-efficient data analysis. Benchmarking presented here on a publicly available dataset, demonstrated that GEM can facilitate reliable genome-wide methQTL and GxE analysis on a standard laptop computer within minutes. Conclusions: The GEM package facilitates efficient EWAS study in large cohorts. It is written in R code and can be freely downloaded from Bioconductor at https://www.bioconductor.org/packages/GEM/. [ABSTRACT FROM AUTHOR]

The fetal origins of mental health is a well-established framework that currently lacks a robust index of the biological embedding of prenatal adversity. The Pediatric-Buccal-Epigenetic (PedBE) clock is a novel epigenetic tool that associates with aspects of the prenatal environment, but additional validation in longitudinal datasets is required. Likewise, the relationship between prenatal maternal mental health and the PedBE clock has not been described. Longitudinal cohorts from the Netherlands (Basal Influences on Baby Development [BIBO] n = 165) and Singapore (Growing Up in Singapore Towards Healthy Outcomes [GUSTO] n = 340) provided data on prenatal maternal anxiety and longitudinal assessments of buccal cell–derived genome-wide DNA methylation assessed at 6 and 10 years of age in BIBO, and at 3, 9, and 48 months of age in GUSTO. Measures of epigenetic age acceleration were calculated using the PedBE clock and benchmarked against an established multi-tissue epigenetic predictor. Prenatal maternal anxiety predicted child PedBE epigenetic age acceleration in both cohorts, with effects largely restricted to males and not females. These results were independent of obstetric, socioeconomic, and genetic risk factors, with a larger effect size for prenatal anxiety than depression. PedBE age acceleration predicted increased externalizing symptoms in males from mid- to late childhood in the BIBO cohort only. These findings point to the fetal origins of epigenetic age acceleration and reveal an increased sensitivity in males. Convergent evidence underscores the societal importance of providing timely and effective mental health support to pregnant individuals, which may have lasting consequences for both mother and child. [ABSTRACT FROM AUTHOR]

Statistical inference on neuroimaging data is often conducted using a mass-univariate model, equivalent to fitting a linear model at every voxel with a known set of covariates. Due to the large number of linear models, it is challenging to check if the selection of covariates is appropriate and to modify this selection adequately. The use of standard diagnostics, such as residual plotting, is clearly not practical for neuroimaging data. However, the selection of covariates is crucial for linear regression to ensure valid statistical inference. In particular, the mean model of regression needs to be reasonably well specified. Unfortunately, this issue is often overlooked in the field of neuroimaging. This study aims to adopt the existing Confounder Adjusted Testing and Estimation (CATE) approach and to extend it for use with neuroimaging data. We propose a modification of CATE that can yield valid statistical inferences using Principal Component Analysis (PCA) estimators instead of Maximum Likelihood (ML) estimators. We then propose a non-parametric hypothesis testing procedure that can improve upon parametric testing. Monte Carlo simulations show that the modification of CATE allows for more accurate modelling of neuroimaging data and can in turn yield a better control of False Positive Rate (FPR) and Family-Wise Error Rate (FWER). We demonstrate its application to an Epigenome-Wide Association Study (EWAS) on neonatal brain imaging and umbilical cord DNA methylation data obtained as part of a longitudinal cohort study. Software for this CATE study is freely available at http://www.bioeng.nus.edu.sg/cfa/Imaging_Genetics2.html . [ABSTRACT FROM AUTHOR]