Regional differences in mitochondrial DNA methylation in human post-mortem brain tissue

Background: DNA methylation is an important epigenetic mechanism involved in gene regulation, with alterations in DNA methylation in the nuclear genome being linked to numerous complex diseases. Mitochondrial DNA methylation is a phenomenon that is receiving ever-increasing interest, particularly in diseases characterized by mitochondrial dysfunction; however, most studies have been limited to the investigation of specific target regions. Analyses spanning the entire mitochondrial genome have been limited, potentially due to the amount of input DNA required. Further, mitochondrial genetic studies have been previously confounded by nuclear-mitochondrial pseudogenes. Methylated DNA Immunoprecipitation Sequencing is a technique widely used to profile DNA methylation across the nuclear genome; however, reads mapped to mitochondrial DNA are often discarded. Here, we have developed an approach to control for nuclear-mitochondrial pseudogenes within Methylated DNA Immunoprecipitation Sequencing data. We highlight the utility of this approach in identifying differences in mitochondrial DNA methylation across regions of the human brain and pre-mortem blood. Results: We were able to correlate mitochondrial DNA methylation patterns between the cortex, cerebellum and blood. We identified 74 nominally significant differentially methylated regions (p < 0.05) in the mitochondrial genome, between anatomically separate cortical regions and the cerebellum in matched samples (N = 3 matched donors). Further analysis identified eight significant differentially methylated regions between the total cortex and cerebellum after correcting for multiple testing. Using unsupervised hierarchical clustering analysis of the mitochondrial DNA methylome, we were able to identify tissue-specific patterns of mitochondrial DNA methylation between blood, cerebellum and cortex. Conclusions: Our study represents a comprehensive analysis of the mitochondrial methylome using pre-existing Methylated DNA Immunoprecipitation Sequencing data to identify brain region-specific patterns of mitochondrial DNA methylation

Methylation Markers of Early-Stage Non-Small Cell Lung Cancer

Despite of intense research in early cancer detection, there is a lack of biomarkers for the reliable detection of malignant tumors, including non-small cell lung cancer (NSCLC). DNA methylation changes are common and relatively stable in various types of cancers, and may be used as diagnostic or prognostic biomarkers.We performed DNA methylation profiling of samples from 48 patients with stage I NSCLC and 18 matching cancer-free lung samples using microarrays that cover the promoter regions of more than 14,500 genes. We correlated DNA methylation changes with gene expression levels and performed survival analysis.We observed hypermethylation of 496 CpGs in 379 genes and hypomethylation of 373 CpGs in 335 genes in NSCLC. Compared to adenocarcinoma samples, squamous cell carcinoma samples had 263 CpGs in 223 hypermethylated genes and 513 CpGs in 436 hypomethylated genes. 378 of 869 (43.5%) CpG sites discriminating the NSCLC and control samples showed an inverse correlation between CpG site methylation and gene expression levels. As a result of a survival analysis, we found 10 CpGs in 10 genes, in which the methylation level differs in different survival groups.We have identified a set of genes with altered methylation in NSCLC and found that a minority of them showed an inverse correlation with gene expression levels. We also found a set of genes that associated with the survival of the patients. These newly-identified marker candidates for the molecular screening of NSCLC will need further analysis in order to determine their clinical utility

Identification of rare de novo epigenetic variations in congenital disorders

Certain human traits such as neurodevelopmental disorders (NDs) and congenital anomalies (CAs) are believed to be primarily genetic in origin. However, even after whole-genome sequencing (WGS), a substantial fraction of such disorders remain unexplained. We hypothesize that some cases of ND-CA are caused by aberrant DNA methylation leading to dysregulated genome function. Comparing DNA methylation profiles from 489 individuals with ND-CAs against 1534 controls, we identify epivariations as a frequent occurrence in the human genome. De novo epivariations are significantly enriched in cases, while RNAseq analysis shows that epivariations often have an impact on gene expression comparable to loss-of-function mutations. Additionally, we detect and replicate an enrichment of rare sequence mutations overlapping CTCF binding sites close to epivariations, providing a rationale for interpreting non-coding variation. We propose that epivariations contribute to the pathogenesis of some patients with unexplained ND-CAs, and as such likely have diagnostic relevance.The authors are grateful to the patients and families who participated in this study and to the collaborators who supported patient recruitment. This work was supported by NIH grant HG006696 and research grant 6-FY13-92 from the March of Dimes to A.J.S., grant HL098123 to B.D.G. and A.J.S., Gulbenkian Programme for Advanced Medical Education and the Portuguese Foundation for Science and Technology (SFRH/BDINT/51549/ 2011, PIC/IC/83026/2007, PIC/IC/83013/2007, SFRH/BD/90167/2012, Portugal) to P.M., F.L., and M.B., by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER) (NORTE-01-0145-FEDER-000013) to P.M., a Beatriu de Pinos Postdoctoral Fellowship to R.S.J. (2011BP-A00515), and a Seaver Foundation fellowship to S.D.R. The views expressed are those of the authors and do not necessarily reflect those of the National Heart, Lung, and Blood Institute or the National Institutes of Health. Research reported in this paper was supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD018522. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai.The authors are grateful to the patients and families who participated in this study and to the collaborators who supported patient recruitment. This work was supported by NIH grant HG006696 and research grant 6-FY13-92 from the March of Dimes to A.J.S., grant HL098123 to B.D.G. and A.J.S., Gulbenkian Programme for Advanced Medical Education and the Portuguese Foundation for Science and Technology (SFRH/BDINT/51549/ 2011, PIC/IC/83026/2007, PIC/IC/83013/2007, SFRH/BD/90167/2012, Portugal) to P.M., F.L., and M.B., by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER) (NORTE-01-0145-FEDER-000013) to P.M., a Beatriu de Pinos Postdoctoral Fellowship to R.S.J. (2011BP-A00515), and a Seaver Foundation fellowship to S.D.R. The views expressed are those of the authors and do not necessarily reflect those of the National Heart, Lung, and Blood Institute or the National Institutes of Health. Research reported in this paper was supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD018522. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai

Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements

Background: Recent assays for individual-specific genome-wide DNA methylation profiles have enabled epigenome-wide association studies to identify specific CpG sites associated with a phenotype. Computational prediction of CpG site-specific methylation levels is important, but current approaches tackle average methylation within a genomic locus and are often limited to specific genomic regions. Results: We characterize genome-wide DNA methylation patterns, and show that correlation among CpG sites decays rapidly, making predictions solely based on neighboring sites challenging. We built a random forest classifier to predict CpG site methylation levels using as features neighboring CpG site methylation levels and genomic distance, and co-localization with coding regions, CGIs, and regulatory elements from the ENCODE project, among others. Our approach achieves 91% -- 94% prediction accuracy of genome-wide methylation levels at single CpG site precision. The accuracy increases to 98% when restricted to CpG sites within CGIs. Our classifier outperforms state-of-the-art methylation classifiers and identifies features that contribute to prediction accuracy: neighboring CpG site methylation status, CpG island status, co-localized DNase I hypersensitive sites, and specific transcription factor binding sites were found to be most predictive of methylation levels. Conclusions: Our observations of DNA methylation patterns led us to develop a classifier to predict site-specific methylation levels that achieves the best DNA methylation predictive accuracy to date. Furthermore, our method identified genomic features that interact with DNA methylation, elucidating mechanisms involved in DNA methylation modification and regulation, and linking different epigenetic processes

Interventions targeting social isolation in older people: a systematic review

This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.BACKGROUND: Targeting social isolation in older people is a growing public health concern. The proportion of older people in society has increased in recent decades, and it is estimated that approximately 25% of the population will be aged 60 or above within the next 20 to 40 years. Social isolation is prevalent amongst older people and evidence indicates the detrimental effect that it can have on health and wellbeing. The aim of this review was to assess the effectiveness of interventions designed to alleviate social isolation and loneliness in older people. METHODS: Relevant electronic databases (MEDLINE, EMBASE, ASSIA, IBSS, PsycINFO, PubMed, DARE, Social Care Online, the Cochrane Library and CINAHL) were systematically searched using an extensive search strategy, for randomised controlled trials and quasi-experimental studies published in English before May 2009. Additional articles were identified through citation tracking. Studies were included if they related to older people, if the intervention aimed to alleviate social isolation and loneliness, if intervention participants were compared against inactive controls and, if treatment effects were reported. Two independent reviewers extracted data using a standardised form. Narrative synthesis and vote-counting methods were used to summarise and interpret study data. RESULTS: Thirty two studies were included in the review. There was evidence of substantial heterogeneity in the interventions delivered and the overall quality of included studies indicated a medium to high risk of bias. Across the three domains of social, mental and physical health, 79% of group-based interventions and 55% of one-to-one interventions reported at least one improved participant outcome. Over 80% of participatory interventions produced beneficial effects across the same domains, compared with 44% of those categorised as non-participatory. Of interventions categorised as having a theoretical basis, 87% reported beneficial effects across the three domains compared with 59% of interventions with no evident theoretical foundation. Regarding intervention type, 86% of those providing activities and 80% of those providing support resulted in improved participant outcomes, compared with 60% of home visiting and 25% of internet training interventions. Fifty eight percent of interventions that explicitly targeted socially isolated or lonely older people reported positive outcomes, compared with 80% of studies with no explicit targeting. CONCLUSIONS: More, well-conducted studies of the effectiveness of social interventions for alleviating social isolation are needed to improve the evidence base. However, it appeared that common characteristics of effective interventions were those developed within the context of a theoretical basis, and those offering social activity and/or support within a group format. Interventions in which older people are active participants also appeared more likely to be effective. Future interventions incorporating all of these characteristics may therefore be more successful in targeting social isolation in older people.National Institute for Health Researc

DNA methylation patterns of behavior-related gene promoter regions dissect the gray wolf from domestic dog breeds

A growing body of evidence highlights the relationship between epigenetics, especially DNA methylation, and population divergence as well as speciation. However, little is known about how general the phenomenon of epigenetics-wise separation of different populations is, or whether population assignment is, possible based on solely epigenetic marks. In the present study, we compared DNA methylation profiles between four different canine populations: three domestic dog breeds and their ancestor the gray wolf. Altogether, 79 CpG sites constituting the 65 so-called CpG units located in the promoter regions of genes affecting behavioral and temperamental traits (COMT, HTR1A, MAOA, OXTR, SLC6A4, TPH1, WFS1)-regions putatively targeted during domestication and breed selection. Methylation status of buccal cells was assessed using EpiTYPER technology. Significant inter-population methylation differences were found in 52.3% of all CpG units investigated. DNA methylation profile-based hierarchical cluster analysis indicated an unambiguous segregation of wolf from domestic dog. In addition, one of the three dog breeds (Golden Retriever) investigated also formed a separate, autonomous group. The findings support that population segregation is interrelated with shifts in DNA methylation patterns, at least in putative selection target regions, and also imply that epigenetic profiles could provide a sufficient basis for population assignment of individuals