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1.
Brain Behav ; 8(6): e00989, 2018 06.
Article in English | MEDLINE | ID: mdl-30106247

ABSTRACT

INTRODUCTION: Studying innate sensitivity to ethanol can be an important first step toward understanding alcohol use disorders. In brain, we investigated transcripts, with evidence of miRNA modulation related to a predisposition to the hypnotic effect of ethanol, as measured by loss of righting reflex (LORR). METHODS: Expression of miRNAs (12 samples) and expression of mRNAs (353 samples) in brain were independently analyzed for an association with LORR in mice from the LXS recombinant inbred panel gathered across several small studies. These results were then integrated via a meta-analysis of miRNA-mRNA target pairs identified in miRNA-target interaction databases. RESULTS: We found 112 significant miRNA-mRNA pairs where a large majority of miRNAs and mRNAs were highly interconnected. Most pairs indicated a pattern of increased levels of miRNAs and reduced levels of mRNAs being associated with more alcohol-sensitive strains. For example, CaMKIIn1 was targeted by multiple miRNAs associated with LORR. CAMK2N1 is an inhibitor of CAMK2, which among other functions, phosphorylates, or binds to GABAA and NMDA receptors. CONCLUSIONS: Our results suggest a novel role of miRNA-mediated regulation of an inhibitor of CAMK2 and its downstream targets including the GABAA and NMDA receptors, which have been previously implicated to have a role in ethanol-induced sedation and sensitivity.


Subject(s)
Alcoholism/genetics , Ethanol/pharmacology , Hypnotics and Sedatives/pharmacology , MicroRNAs/physiology , Transcription, Genetic/genetics , Animals , Calcium-Calmodulin-Dependent Protein Kinase Type 2/antagonists & inhibitors , Female , GABA-A Receptor Antagonists/pharmacology , Gene Expression Regulation , Genetic Predisposition to Disease/genetics , Mice , Mice, Inbred Strains , MicroRNAs/genetics , MicroRNAs/metabolism , RNA, Messenger/metabolism , Receptors, GABA-A/drug effects , Receptors, GABA-A/genetics , Receptors, N-Methyl-D-Aspartate/antagonists & inhibitors , Receptors, N-Methyl-D-Aspartate/drug effects , Receptors, N-Methyl-D-Aspartate/genetics , Reflex, Righting/drug effects , Reflex, Righting/genetics
2.
Diabet Med ; 35(5): 612-620, 2018 05.
Article in English | MEDLINE | ID: mdl-29461653

ABSTRACT

AIMS: To identify gestational diabetes mellitus exposure-associated DNA methylation changes and assess whether such changes are also associated with adiposity-related outcomes. METHODS: We performed an epigenome-wide association analysis, using Illumina 450k methylation arrays, on whole blood collected, on average, at 10.5 years of age from 81 gestational diabetes-exposed and 81 unexposed offspring enrolled in the EPOCH (Exploring Perinatal Outcomes in Children) study, and on the cord blood of 31 gestational diabetes-exposed and 64 unexposed offspring enrolled in the Colorado Healthy Start cohort. Validation was performed by pyrosequencing. RESULTS: We identified 98 differentially methylated positions associated with gestational diabetes exposure at a false discovery rate of <10% in peripheral blood, with 51 loci remaining significant (plus additional 40 loci) after adjustment for cell proportions. We also identified 2195 differentially methylation regions at a false discovery rate of <5% after adjustment for cell proportions. We prioritized loci for pyrosequencing validation and association analysis with adiposity-related outcomes based on strengths of association and effect size, network and pathway analysis, analysis of cord blood, and previous publications. Methylation in six out of nine (67%) gestational diabetes-associated genes was validated and we also showed that methylation of SH3PXD2A was significantly (P<0.05) associated with multiple adiposity-related outcomes. CONCLUSIONS: Our findings suggest that epigenetic marks may provide an important link between in utero exposure to gestational diabetes and obesity in childhood, and add to the growing body of evidence that DNA methylation is affected by gestational diabetes exposure.


Subject(s)
DNA Methylation/genetics , Diabetes, Gestational/genetics , Epigenesis, Genetic , Pediatric Obesity/genetics , Prenatal Exposure Delayed Effects/genetics , Adaptor Proteins, Vesicular Transport/genetics , Adiposity/genetics , Case-Control Studies , Child , Cohort Studies , Epigenomics , Female , Fetal Blood , Humans , Male , Pregnancy
3.
Genes Brain Behav ; 13(8): 743-57, 2014 Nov.
Article in English | MEDLINE | ID: mdl-25160899

ABSTRACT

Numerous selective breeding experiments have been performed with rodents, in an attempt to understand the genetic basis for innate differences in preference for alcohol consumption. Quantitative trait locus (QTL) analysis has been used to determine regions of the genome that are associated with the behavioral difference in alcohol preference/consumption. Recent work suggests that differences in gene expression represent a major genetic basis for complex traits. Therefore, the QTLs are likely to harbor regulatory regions (eQTLs) for the differentially expressed genes that are associated with the trait. In this study, we examined brain gene expression differences over generations of selection of the third replicate lines of high and low alcohol-preferring (HAP3 and LAP3) mice, and determined regions of the genome that control the expression of these differentially expressed genes (de eQTLs). We also determined eQTL regions (rv eQTLs) for genes that showed a decrease in variance of expression levels over the course of selection. We postulated that de eQTLs that overlap with rv eQTLs, and also with phenotypic QTLs, represent genomic regions that are affected by the process of selection. These overlapping regions controlled the expression of candidate genes (that displayed differential expression and reduced variance of expression) for the predisposition to differences in alcohol consumption by the HAP3/LAP3 mice.


Subject(s)
Alcohol Drinking/genetics , Choice Behavior/physiology , Gene Expression , Quantitative Trait Loci , Animals , Breeding , Gene Expression Profiling , Genotype , Mice , Phenotype
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