Dataset Information

Hippocampal DNA Methylation in a Mouse Model of Fetal Alcohol Spectrum Disorder That Includes Maternal Separation Stress Only Partially Explains Changes in Gene Expression.

ABSTRACT: Fetal alcohol spectrum disorder (FASD) is characterized by developmental and behavioral deficits caused by maternal drinking during pregnancy. Children born with FASD often face additional stresses, including maternal separation, that add yet additional deficits. The mechanism associated with this interaction is not known. We have used a mouse model for prenatal ethanol exposure and maternal separation to demonstrate that the combination of the two treatments results in more than additive deficits. Furthermore, the behavioral deficits are associated with changes in hippocampal gene expression that persist into adulthood. What initiates and maintains these changes remains to be established and forms the focus of this report. Specifically, MeDIP-Seq was used to assess if changes in promoter DNA methylation are affected by exposure to prenatal ethanol and maternal separation including its relationship to gene expression. The novel results show that different sets of genes implicated by promoter DNA methylation are affected by both treatments independently, and a relatively unique set of genes are affected by the combination of the two treatments. Prenatal ethanol exposure leads to altered promoter DNA methylation at genes important for transcriptional regulation. Maternal separation leads to changes at genes important for histone methylation and immune response, and the combination of two treatments results in DNA methylation changes at genes important for neuronal migration and immune response. Our dual results from the same hippocampal samples suggest there is minimal complementarity between changes in promoter DNA methylation and gene expression, although genes involved tend to be critical for brain development and function. While remaining to be validated, such results argue that mechanisms beyond promoter DNA methylation must be involved in lasting gene expression alterations leading to behavioral deficits implicated in FASD. They may facilitate early and reliable diagnosis, as well as novel strategies for the amelioration of FASD-related deficits.

SUBMITTER: Alberry BLJ

PROVIDER: S-EPMC7056727 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Hippocampal DNA Methylation in a Mouse Model of Fetal Alcohol Spectrum Disorder That Includes Maternal Separation Stress Only Partially Explains Changes in Gene Expression.

Alberry Bonnie L J BLJ Singh Shiva M SM

Frontiers in genetics 20200227

Fetal alcohol spectrum disorder (FASD) is characterized by developmental and behavioral deficits caused by maternal drinking during pregnancy. Children born with FASD often face additional stresses, including maternal separation, that add yet additional deficits. The mechanism associated with this interaction is not known. We have used a mouse model for prenatal ethanol exposure and maternal separation to demonstrate that the combination of the two treatments results in more than additive defici ...[more]

PMID: 32174962

Similar Datasets

Project description:Background:Fetal alcohol spectrum disorder (FASD) is a developmental disorder that manifests through a range of cognitive, adaptive, physiological, and neurobiological deficits resulting from prenatal alcohol exposure. Although the North American prevalence is currently estimated at 2-5%, FASD has proven difficult to identify in the absence of the overt physical features characteristic of fetal alcohol syndrome. As interventions may have the greatest impact at an early age, accurate biomarkers are needed to identify children at risk for FASD. Building on our previous work identifying distinct DNA methylation patterns in children and adolescents with FASD, we have attempted to validate these associations in a different clinical cohort and to use our DNA methylation signature to develop a possible epigenetic predictor of FASD. Methods:Genome-wide DNA methylation patterns were analyzed using the Illumina HumanMethylation450 array in the buccal epithelial cells of a cohort of 48 individuals aged 3.5-18 (24 FASD cases, 24 controls). The DNA methylation predictor of FASD was built using a stochastic gradient boosting model on our previously published dataset FASD cases and controls (GSE80261). The predictor was tested on the current dataset and an independent dataset of 48 autism spectrum disorder cases and 48 controls (GSE50759). Results:We validated findings from our previous study that identified a DNA methylation signature of FASD, replicating the altered DNA methylation levels of 161/648 CpGs in this independent cohort, which may represent a robust signature of FASD in the epigenome. We also generated a predictive model of FASD using machine learning in a subset of our previously published cohort of 179 samples (83 FASD cases, 96 controls), which was tested in this novel cohort of 48 samples and resulted in a moderately accurate predictor of FASD status. Upon testing the algorithm in an independent cohort of individuals with autism spectrum disorder, we did not detect any bias towards autism, sex, age, or ethnicity. Conclusion:These findings further support the association of FASD with distinct DNA methylation patterns, while providing a possible entry point towards the development of epigenetic biomarkers of FASD.

Project description:OBJECTIVES:Fetal alcohol spectrum disorders (FASD) is a worldwide problem. Maternal alcohol consumption is an important risk factor for FASD. It remains unknown which alcohol consumption patterns most strongly predict FASD. The objective of this study was to identify these. DESIGN:Systematic literature review. METHODS:We searched in PubMed, PsychINFO, PsycARTICLES, ERIC, CINAHL, Embase and MEDLINE up to August 2018. The query consisted of keywords and their synonyms related to FASD, pregnancy and behaviour. Studies were excluded when not published in English, were reviews or involved non-human subjects. Substantial heterogeneity precluded aggregation or meta-analysis of the data. Instead, data were qualitatively inspected. RESULTS:In total, 21 studies were eligible for further data analysis. All studies that measured both maternal alcohol drinking behaviours and FASD reported retrospective data on maternal drinking patterns, employing both continuous and categorical measures and exhibiting substantial heterogeneity in measures of alcohol consumption (eg, timing of exposure, quantification of alcohol measure and definition of a standard drink). Study quality improved over time and appeared higher for studies based on active case ascertainment, especially when conducted in schools and when behaviour was assessed through interviews. CONCLUSIONS:We aimed to identify specific maternal drinking behaviour(s) related to FASD. The state of the literature precludes such conclusions. Evidence-based preventive measures necessitate identifying which prenatal alcohol drinking behaviour(s) are most in need of intervention. Therefore, we formulate three recommendations for future research. First, future studies can optimise the value of the collected dataset through specifying measurements and reporting of maternal drinking behaviours and avoiding categorised measures (nominal or ordinal) whenever possible. Second, samples should not be selected based on FASD status, but instead, FASD status as well as maternal alcohol consumption should both be measured in a general population sample. Finally, we provide 10 reporting guidelines for FASD research.

Project description:Background: Fetal alcohol spectrum disorder (FASD) is a developmental disorder that manifests through a range of cognitive, adaptive, physiological, and neurobiological deficits resulting from prenatal alcohol exposure. Although the North American prevalence is currently estimated at 2-5%, FASD has proven difficult to identify in the absence of the overt physical features characteristic of fetal alcohol syndrome. As interventions may have the greatest impact at an early age, accurate biomarkers are needed to identify children at risk for FASD. Building on our previous work identifying distinct DNA methylation patterns in children and adolescents with FASD, we have attempted to validate these associations in a different clinical cohort and to use our DNA methylation signature to develop a possible epigenetic predictor of FASD. Methods: Genome-wide DNA methylation patterns were analyzed using the Illumina HumanMethylation450 array in the buccal epithelial cells of a cohort of 48 individuals aged 3.5-18 (24 FASD cases, 24 controls). The DNA methylation predictor of FASD was built using a stochastic gradient boosting model on our previously published dataset FASD cases and controls (GSE80261). The predictor was tested on the current dataset and an independent dataset of 48 autism spectrum disorder cases and 48 controls (GSE50759). Results: We validated findings from our previous study that identified a DNA methylation signature of FASD, replicating the altered DNA methylation levels of 161/648 CpGs in this independent cohort, which may represent a robust signature of FASD in the epigenome. We also generated a predictive model of FASD using machine learning in a subset of our previously published cohort of 179 samples (83 FASD cases, 96 controls), which was tested in this novel cohort of 48 samples and resulted in a moderately accurate predictor of FASD status. Upon testing the algorithm in an independent cohort of individuals with autism spectrum disorder, we did not detect any bias towards autism, sex, age, or ethnicity. Conclusion: These findings further support the association of FASD with distinct DNA methylation patterns, while providing a possible entry point towards the development of epigenetic biomarkers of FASD.

Project description:BACKGROUND:Fetal alcohol spectrum disorder (FASD) is the leading nongenetic cause of mental retardation. There are no treatments for FASD to date. Preclinical in vivo and in vitro studies could help in identifying novel drug targets as for other diseases. Here, we describe an ex vivo model that combines the physiological advantages of prenatal ethanol (EtOH) exposure in vivo with the uniformity of primary fetal hippocampal culture to characterize the effects of prenatal EtOH. The insulin signaling pathways are known to be involved in hippocampal functions. Therefore, we compared the expression of insulin signaling pathway genes between fetal hippocampi (in vivo) and primary hippocampal culture (ex vivo). The similarity of prenatal EtOH effects in these 2 paradigms would deem the ex vivo culture acceptable to screen possible treatments for FASD. METHODS:Pregnant Sprague-Dawley rats received 1 of 3 diets: ad libitum standard laboratory chow (control-C), isocaloric pair-fed (nutritional control), and EtOH containing liquid diets from gestational day (GD) 8. Fetal male and female hippocampi were collected either on GD21 (in vivo) or on GD18 for primary culture (ex vivo). Transcript levels of Igf2, Igf2r, Insr, Grb10, Rasgrf1, and Zac1 were measured by reverse transcription quantitative polymerase chain reaction. RESULTS:Hippocampal transcript levels differed by prenatal treatment in both males and females with sex differences observed in the expression of Igf2 and Insr. The effect of prenatal EtOH on the hippocampal expression of the insulin pathway genes was parallel in the in vivo and the ex vivo conditions. CONCLUSIONS:The similarity of gene expression changes in response to prenatal EtOH between the in vivo and the ex vivo conditions ascertains that these effects are already set in the fetal hippocampus at GD18. This strengthens the feasibility of the ex vivo primary hippocampal culture as a tool to test and screen candidate drug targets for FASD.

Dataset Information

Hippocampal DNA Methylation in a Mouse Model of Fetal Alcohol Spectrum Disorder That Includes Maternal Separation Stress Only Partially Explains Changes in Gene Expression.

Publications

Hippocampal DNA Methylation in a Mouse Model of Fetal Alcohol Spectrum Disorder That Includes Maternal Separation Stress Only Partially Explains Changes in Gene Expression.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets