The role of DNA methylation in the association between childhood adversity and cardiometabolic disease

Hao, Guang; Youssef, Nagy A.; Davis, Catherine L.; Su, Shaoyong

doi:10.1016/j.ijcard.2017.12.063

Cited by 29 publications

(19 citation statements)

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“…Linking DNA methylation patterns in blood cells to specific health risks or diseases is an area of active research. Recent studies describe blood cell epigenetic markers for: pediatric cardiac risk [ 41 ], immune stress associated with sclerosis [ 42 ], infant cerebral palsy markers in cord blood [ 38 ], regulatory T cell imprinting as a marker for therapeutic efficacy [ 43 ], and immuno-profiling for specific disease / stress states [ 44 ]. These types of studies demonstrate that information about past environmental exposures and health/disease status are present in blood cell methylation patterns and suggest that such alterations are present in the hematopoietic stem cell populations that give rise to circulating myeloid and lymphoid cells.…”

Section: Discussionmentioning

confidence: 99%

Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy

et al. 2018

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BackgroundSpastic cerebral palsy (CP) is a leading cause of physical disability. Most people with spastic CP are born with it, but early diagnosis is challenging, and no current biomarker platform readily identifies affected individuals. The aim of this study was to evaluate epigenetic profiles as biomarkers for spastic CP. A novel analysis pipeline was employed to assess DNA methylation patterns between peripheral blood cells of adolescent subjects (14.9 ± 0.3 years old) with spastic CP and controls at single CpG site resolution.ResultsSignificantly hypo- and hyper-methylated CpG sites associated with spastic CP were identified. Nonmetric multidimensional scaling fully discriminated the CP group from the controls. Machine learning based classification modeling indicated a high potential for a diagnostic model, and 252 sets of 40 or fewer CpG sites achieved near-perfect accuracy within our adolescent cohorts. A pilot test on significantly younger subjects (4.0 ± 1.5 years old) identified subjects with 73% accuracy.ConclusionsAdolescent patients with spastic CP can be distinguished from a non-CP cohort based on DNA methylation patterns in peripheral blood cells. A clinical diagnostic test utilizing a panel of CpG sites may be possible using a simulated classification model. A pilot validation test on patients that were more than 10 years younger than the main adolescent cohorts indicated that distinguishing methylation patterns are present earlier in life. This study is the first to report an epigenetic assay capable of distinguishing a CP cohort.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2224-0) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy

et al. 2018

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“…A gene ontology-based enrichment analysis of the genes annotated to these modules found strong enrichment for either immune-related or development-related processes. The finding of immune-related processes is intuitive given that DNA from blood measures primarily immune cells, while the development-related enrichment could possibly reflect influences during early life [28]. Notably, these two module "types" (immune and development) have been uncovered in a prior network-based DNA methylation analysis related to asthma [19], suggesting that similar module types are a potentially general feature of blood-based methylation patterns and that these patterns may not be fully cardiovascular-specific, reflecting instead a predisposition toward general inflammatory disease processes.…”

Section: Discussionmentioning

confidence: 99%

“…Broadly, the brown module is enriched for enhancers and other non-proximal regions near immune-related genes, while the blue module is enriched for CpG islands near the TSS of development-related genes. One could speculate that these modules also represent different mechanisms of cardiovascular risk: one related to inflammatory burden and the other to long-term effects of early-life exposures, both of which are well-established as contributing to cardiovascular risk [28,37]. Analyses based on cross-tissue epigenome annotations added an additional dimension to these insights by suggesting differential importance of blood cell sub-types for these modules.…”

Section: Discussionmentioning

confidence: 99%

DNA methylation modules associate with incident cardiovascular disease and cumulative risk factor exposure

Westerman

Sebastiani

Jacques

et al. 2018

Preprint

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Background Epigenome-wide association studies using DNA methylation have the potential to uncover novel biomarkers and mechanisms of cardiovascular disease (CVD) risk. However, the direction of causation for these associations is not always clear, and investigations to-date have generally failed to replicate at the level of individual loci. Here, we undertook module-and region-based DNA methylation analyses of incident CVD in the Women's Health Initiative (WHI) and Framingham Heart Study Offspring Cohort (FHS) in order to find more robust epigenetic biomarkers for cardiovascular risk. Methods and FindingsWe applied weighted gene correlation network analysis (WGCNA) and the Comb-p algorithm to find methylation modules and regions associated with incident CVD in the WHI dataset. We discovered two modules whose activation correlated with CVD risk and replicated across cohorts. One of these modules was enriched for development-related processes and overlaps strongly with epigenetic aging sites. For the other, we showed preliminary evidence for monocyte-specific effects and statistical links to cumulative exposure to traditional cardiovascular risk factors. Additionally, we found three regions (associated with the genes SLC9A1, SLC1A5, and TNRC6C) whose methylation associates with CVD risk. ConclusionsIn sum, we present several epigenetic associations with incident CVD that reveal potential monocyte biology-related mechanisms for CVD risk as well as a novel link between DNA methylation and cumulative cardiovascular risk factor exposure.

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“…Although the main focus of the review is on the psychological and psychiatric effect of trauma transgenerationally via methylation changes, another area that could be impacted by trauma and stress (and supported by emerging and preliminary evidence) is that the transgenerational effects may not only affect psychological health but also physical health [ 18 ]. These physical effects are briefly demonstrated in the following studies.…”

Section: Transgenerational Effects Of Trauma and Stress And Physicmentioning

confidence: 99%

The Effects of Trauma, with or without PTSD, on the Transgenerational DNA Methylation Alterations in Human Offsprings

Youssef

Lockwood

et al. 2018

Brain Sciences

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Exposure to psychological trauma is a strong risk factor for several debilitating disorders including post-traumatic stress disorder (PTSD) and depression. Besides the impact on mental well-being and behavior in the exposed individuals, it has been suggested that psychological trauma can affect the biology of the individuals, and even have biological and behavioral consequences on the offspring of exposed individuals. While knowledge of possible epigenetic underpinnings of the association between exposure to trauma and risk of PTSD has been discussed in several reviews, it remains to be established whether trauma-induced epigenetic modifications can be passed from traumatized individuals to subsequent generations of offspring. The aim of this paper is to review the emerging literature on evidence of transgenerational inheritance due to trauma exposure on the epigenetic mechanism of DNA methylation in humans. Our review found an accumulating amount of evidence of an enduring effect of trauma exposure to be passed to offspring transgenerationally via the epigenetic inheritance mechanism of DNA methylation alterations and has the capacity to change the expression of genes and the metabolome. This manuscript summarizes and critically reviews the relevant original human studies in this area. Thus, it provides an overview of where we stand, and a clearer vision of where we should go in terms of future research directions.

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The role of DNA methylation in the association between childhood adversity and cardiometabolic disease

Cited by 29 publications

References 99 publications

Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy

Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy

DNA methylation modules associate with incident cardiovascular disease and cumulative risk factor exposure

The Effects of Trauma, with or without PTSD, on the Transgenerational DNA Methylation Alterations in Human Offsprings

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