Precision pharmacological reversal of strain-specific diet-induced metabolic syndrome in mice informed by epigenetic and transcriptional regulation.

Diet-related metabolic syndrome is the largest contributor to adverse health in the United States. However, the study of gene-environment interactions and their epigenomic and transcriptomic integration is complicated by the lack of environmental and genetic control in humans that is possible in mouse models. Here we exposed three mouse strains, C57BL/6J (BL6), A/J, and NOD/ShiLtJ (NOD), to a high-fat, high-carbohydrate diet, leading to varying degrees of metabolic syndrome. We then performed transcriptomic and genome-wide DNA methylation analyses for each strain and found overlapping but also highly divergent changes in gene expression and methylation upstream of the discordant metabolic phenotypes. Strain-specific pathway analysis of dietary effects revealed a dysregulation of cholesterol biosynthesis common to all three strains but distinct regulatory networks driving this dysregulation. This suggests a strategy for strain-specific targeted pharmacologic intervention of these upstream regulators informed by epigenetic and transcriptional regulation. As a pilot study, we administered the drug GW4064 to target one of these genotype-dependent networks, the farnesoid X receptor pathway, and found that GW4064 exerts strain-specific protection against dietary effects in BL6, as predicted by our transcriptomic analysis. Furthermore, GW4064 treatment induced inflammatory-related gene expression changes in NOD, indicating a strain-specific effect in its associated toxicities as well as its therapeutic efficacy. This pilot study demonstrates the potential efficacy of precision therapeutics for genotype-informed dietary metabolic intervention and a mouse platform for guiding this approach

A Dysregulated DNA Methylation Landscape Linked to Gene Expression in MLL-Rearranged AML

Translocations of the KMT2A (MLL) gene define a biologically distinct and clinically aggressive subtype of acute myeloid leukaemia (AML), marked by a characteristic gene expression profile and few cooperating mutations. Although dysregulation of the epigenetic landscape in this leukaemia is particularly interesting given the low mutation frequency, its comprehensive analysis using whole genome bisulphite sequencing (WGBS) has not been previously performed. Here we investigated epigenetic dysregulation in nine MLL-rearranged (MLL-r) AML samples by comparing them to six normal myeloid controls, using a computational method that encapsulates mean DNA methylation measurements along with analyses of methylation stochasticity. We discovered a dramatically altered epigenetic profile in MLL-r AML, associated with genome-wide hypomethylation and a markedly increased DNA methylation entropy reflecting an increasingly disordered epigenome. Methylation discordance mapped to key genes and regulatory elements that included bivalent promoters and active enhancers. Genes associated with significant changes in methylation stochasticity recapitulated known MLL-r AML expression signatures, suggesting a role for the altered epigenetic landscape in the transcriptional programme initiated by MLL translocations. Accordingly, we established statistically significant associations between discordances in methylation stochasticity and gene expression in MLL-r AML, thus providing a link between the altered epigenetic landscape and the phenotype

Precision pharmacological reversal of strain-specific diet-induced metabolic syndrome in mice informed by epigenetic and transcriptional regulation.

Diet-related metabolic syndrome is the largest contributor to adverse health in the United States. However, the study of gene-environment interactions and their epigenomic and transcriptomic integration is complicated by the lack of environmental and genetic control in humans that is possible in mouse models. Here we exposed three mouse strains, C57BL/6J (BL6), A/J, and NOD/ShiLtJ (NOD), to a high-fat, high-carbohydrate diet, leading to varying degrees of metabolic syndrome. We then performed transcriptomic and genome-wide DNA methylation analyses for each strain and found overlapping but also highly divergent changes in gene expression and methylation upstream of the discordant metabolic phenotypes. Strain-specific pathway analysis of dietary effects revealed a dysregulation of cholesterol biosynthesis common to all three strains but distinct regulatory networks driving this dysregulation. This suggests a strategy for strain-specific targeted pharmacologic intervention of these upstream regulators informed by epigenetic and transcriptional regulation. As a pilot study, we administered the drug GW4064 to target one of these genotype-dependent networks, the farnesoid X receptor pathway, and found that GW4064 exerts strain-specific protection against dietary effects in BL6, as predicted by our transcriptomic analysis. Furthermore, GW4064 treatment induced inflammatory-related gene expression changes in NOD, indicating a strain-specific effect in its associated toxicities as well as its therapeutic efficacy. This pilot study demonstrates the potential efficacy of precision therapeutics for genotype-informed dietary metabolic intervention and a mouse platform for guiding this approach

Paternal sperm DNA methylation associated with early signs of autism risk in an autism-enriched cohort.

Background: Epigenetic mechanisms such as altered DNA methylation have been suggested to play a role in autism, beginning with the classical association of Prader-Willi syndrome, an imprinting disorder, with autistic features. Objectives: Here we tested for the relationship of paternal sperm DNA methylation with autism risk in offspring, examining an enriched-risk cohort of fathers of autistic children. Methods: We examined genome-wide DNA methylation (DNAm) in paternal semen biosamples obtained from an autism spectrum disorder (ASD) enriched-risk pregnancy cohort, the Early Autism Risk Longitudinal Investigation (EARLI) cohort, to estimate associations between sperm DNAm and prospective ASD development, using a 12-month ASD symptoms assessment, the Autism Observation Scale for Infants (AOSI). We analysed methylation data from 44 sperm samples run on the CHARM 3.0 array, which contains over 4 million probes (over 7 million CpG sites), including 30 samples also run on the Illumina Infinium HumanMethylation450 (450K) BeadChip platform (∼485 000 CpG sites). We also examined associated regions in an independent sample of post-mortem human brain ASD and control samples for which Illumina 450K DNA methylation data were available. Results: Using region-based statistical approaches, we identified 193 differentially methylated regions (DMRs) in paternal sperm with a family-wise empirical P-value [family-wise error rate (FWER)] <0.05 associated with performance on the Autism Observational Scale for Infants (AOSI) at 12 months of age in offspring. The DMRs clustered near genes involved in developmental processes, including many genes in the SNORD family, within the Prader-Willi syndrome gene cluster. These results were consistent among the 75 probes on the Illumina 450K array that cover AOSI-associated DMRs from CHARM. Further, 18 of 75 (24%) 450K array probes showed consistent differences in the cerebellums of autistic individuals compared with controls. Conclusions: These data suggest that epigenetic differences in paternal sperm may contribute to autism risk in offspring, and provide evidence that directionally consistent, potentially related epigenetic mechanisms may be operating in the cerebellum of individuals with autism

DNA methylation shows genome-wide association of NFIX, RAPGEF2 and MSRB3 with gestational age at birth

Background Gestational age at birth strongly predicts neonatal, adolescent and adult morbidity and mortality through mostly unknown mechanisms. Identification of specific genes that are undergoing regulatory change prior to birth, such as through changes in DNA methylation, would increase our understanding of developmental changes occurring during the third trimester and consequences of pre-term birth (PTB). Methods We performed a genome-wide analysis of DNA methylation (using microarrays, specifically CHARM 2.0) in 141 newborns collected in Baltimore, MD, using novel statistical methodology to identify genomic regions associated with gestational age at birth. Bisulphite pyrosequencing was used to validate significant differentially methylated regions (DMRs), and real-time PCR was performed to assess functional significance of differential methylation in a subset of newborns. Results We identified three DMRs at genome-wide significance levels adjacent to the NFIX, RAPGEF2 and MSRB3 genes. All three regions were validated by pyrosequencing, and RAGPEF2 also showed an inverse correlation between DNA methylation levels and gene expression levels. Although the three DMRs appear very dynamic with gestational age in our newborn sample, adult DNA methylation levels at these regions are stable and of equal or greater magnitude than the oldest neonate, directionally consistent with the gestational age results. Conclusions We have identified three differentially methylated regions associated with gestational age at birth. All three nearby genes play important roles in the development of several organs, including skeletal muscle, brain and haematopoietic system. Therefore, they may provide initial insight into the basis of PTB's negative health outcomes. The genome-wide custom DNA methylation array technology and novel statistical methods employed in this study could constitute a model for epidemiologic studies of epigenetic variation

High-specificity bioinformatics framework for epigenomic profiling of discordant twins reveals specific and shared markers for ACPA and ACPA-positive rheumatoid arthritis

Background: Twin studies are powerful models to elucidate epigenetic modifications resulting from gene–environment interactions. Yet, commonly a limited number of clinical twin samples are available, leading to an underpowered situation afflicted with false positives and hampered by low sensitivity. We investigated genome-wide DNA methylation data from two small sets of monozygotic twins representing different phases during the progression of rheumatoid arthritis (RA) to find novel genes for further research.Methods: We implemented a robust statistical methodology aimed at investigating a small number of samples to identify differential methylation utilizing the comprehensive CHARM platform with whole blood cell DNA from two sets of twin pairs discordant either for ACPA (antibodies to citrullinated protein antigens)-positive RA versus ACPA-negative healthy or for ACPA-positive healthy (a pre-RA stage) versus ACPA-negative healthy. To deconvolute cell type-dependent differential methylation, we assayed the methylation patterns of sorted cells and used computational algorithms to resolve the relative contributions of different cell types and used them as covariates.Results: To identify methylation biomarkers, five healthy twin pairs discordant for ACPAs were profiled, revealing a single differentially methylated region (DMR). Seven twin pairs discordant for ACPA-positive RA revealed six significant DMRs. After deconvolution of cell type proportions, profiling of the healthy ACPA discordant twin-set revealed 17 genome-wide significant DMRs. When methylation profiles of ACPA-positive RA twin pairs were adjusted for cell type, the analysis disclosed one significant DMR, associated with the EXOSC1 gene. Additionally, the results from our methodology suggest a temporal connection of the protocadherine beta-14 gene to ACPA-positivity with clinical RA.Conclusions: Our biostatistical methodology, optimized for a low-sample twin design, revealed non-genetically linked genes associated with two distinct phases of RA. Functional evidence is still lacking but the results reinforce further study of epigenetic modifications influencing the progression of RA. Our study design and methodology may prove generally useful in twin studies

Epigenomic reprogramming during pancreatic cancer progression links anabolic glucose metabolism to distant metastasis

During the progression of pancreatic ductal adenocarcinoma (PDAC), heterogeneous subclonal populations emerge that drive primary tumor growth, regional spread, distant metastasis, and patient death. However, the genetics of metastases largely reflects that of the primary tumor in untreated patients, and PDAC driver mutations are shared by all subclones. This raises the possibility that an epigenetic process might operate during metastasis. Here we report large-scale reprogramming of chromatin modifications during the natural evolution of distant metastasis. Changes were targeted to thousands of large chromatin domains across the genome that collectively specified malignant traits, including euchromatin and large organized chromatin histone H3 lysine 9 (H3K9)-modified (LOCK) heterochromatin. Remarkably, distant metastases co-evolved a dependence on the oxidative branch of the pentose phosphate pathway (oxPPP), and oxPPP inhibition selectively reversed reprogrammed chromatin, malignant gene expression programs, and tumorigenesis. These findings suggest a model whereby linked metabolic epigenetic programs are selected for enhanced tumorigenic fitness during the evolution of distant metastasis