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A Novel Schizophrenia Diagnostic Model Based on Statistically Significant Changes in Gene Methylation in Specific Brain Regions.

ABSTRACT: Objective:The present study identified methylation patterns of schizophrenia- (SCZ-) related genes in different brain regions and used them to construct a novel DNA methylation-based SCZ diagnostic model. Methods:Four DNA methylation datasets representing different brain regions were downloaded from the Gene Expression Omnibus. The common differentially methylated genes (CDMGs) in all datasets were identified to perform functional enrichment analysis. The differential methylation sites of 10 CDMGs involved in the largest numbers of neurological or psychiatric-related biological processes were used to construct a DNA methylation-based diagnostic model for SCZ in the respective datasets. Results:A total of 849 CDMGs were identified in the four datasets, but the methylation sites as well as degree of methylation differed across the brain regions. Functional enrichment analysis showed CDMGs were significantly involved in biological processes associated with neuronal axon development, intercellular adhesion, and cell morphology changes and, specifically, in PI3K-Akt, AMPK, and MAPK signaling pathways. Four DNA methylation-based classifiers for diagnosing SCZ were constructed in the four datasets, respectively. The sample recognition efficiency of the classifiers showed an area under the receiver operating characteristic curve of 1.00 in three datasets and >0.9 in one dataset. Conclusion:DNA methylation patterns in SCZ vary across different brain regions, which may be a useful epigenetic characteristic for diagnosing SCZ. Our novel model based on SCZ-gene methylation shows promising diagnostic power.

SUBMITTER: Zou D

PROVIDER: S-EPMC7037884 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A Novel Schizophrenia Diagnostic Model Based on Statistically Significant Changes in Gene Methylation in Specific Brain Regions.

Zou Donghua D Qiu Yufen Y Li Rongjie R Meng Youshi Y Wu Yuan Y

BioMed research international 20200212

<h4>Objective</h4>The present study identified methylation patterns of schizophrenia- (SCZ-) related genes in different brain regions and used them to construct a novel DNA methylation-based SCZ diagnostic model.<h4>Methods</h4>Four DNA methylation datasets representing different brain regions were downloaded from the Gene Expression Omnibus. The common differentially methylated genes (CDMGs) in all datasets were identified to perform functional enrichment analysis. The differential methylation ...[more]

PMID: 32104705

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Project description:Schizophrenia (SCZ) is a psychiatric disorder that can include symptoms of disorganized speech and thoughts with uncertain underlying mechanisms possibly linked to over-activated microglia. In this study, we used brain samples from sixteen donors with SCZ and thirteen control donors to assess the differential activation of microglia by quantifying density and 3D reconstruction of microglia stained with ionized calcium-binding adaptor molecule-1 (Iba1). Our samples consisted of sections from the frontal, temporal, and cingulate cortical gray matter, subcortical white matter regions (SCWM), and included the anterior corpus callosum. In the first series of studies, we performed a density analysis followed by a spatial analysis to ascertain the microglial density, distribution, and soma size in SCZ brains. Second, we performed a series of morphological quantification techniques to investigate the arborization patterns of the microglia in SCZ. The results demonstrated an increase in microglia density in the cortical gray matter regions in SCZ cases, while in the SCWM, there was a significant increase in microglia density in the frontal and temporal, but not in the other brain regions of interest (ROIs). Spatial analysis using the "nearest neighbor" demonstrated that there was no effect in "clustering", but there were shorter distances between microglia seen in the SCZ cases. The morphological measures showed that there was a region-dependent increase in the microglia soma size in the SCZ cases while the Sholl analysis revealed a significant decrease in the microglia arborization in the SCZ cases across all the ROI's studied. An in-depth 3D reconstruction of microglia in Brodmann area 9 cortical region found that there was a significant association between age and reduced microglial arborization in the SCZ cases. This region-dependent age association can help determine whether longitudinal changes in microglial activation across age are brain region-dependent, which may point to potential therapeutic targets.

Dataset Information

A Novel Schizophrenia Diagnostic Model Based on Statistically Significant Changes in Gene Methylation in Specific Brain Regions.

Publications

A Novel Schizophrenia Diagnostic Model Based on Statistically Significant Changes in Gene Methylation in Specific Brain Regions.

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