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Journal Article

Citation

Zhou Y, Xiong L, Chen J, Wang Q. Int. J. Neuropsychopharmacol. 2023; ePub(ePub): ePub.

Copyright

(Copyright © 2023, Cambridge University Press)

DOI

10.1093/ijnp/pyad057

PMID

37774423

Abstract

BACKGROUND: Suicidal behaviors have become a serious public health concern globally due to the economic and human cost of suicidal behavior to individuals, families, communities, and society. However, the underlying etiology and biological mechanism of suicidal behavior remains poorly understood.

METHODS: We collected different single omic data, including scRNA-seq, bulk mRNA-seq, DNA methylation microarrays from the cortex of MDD with suicide subjects' studies, as well as fluoxetine-treated rats brains. We matched subject IDs that overlapped between the transcriptome dataset and the methylation dataset. The differential expression genes (DEGs) and differentially methylated regions (DMRs) were calculated with a two-group comparision analysis. Cross-omics analysis was performed to calculate the correlation between the methylated and transcript levels of differentially methylated CpG sites and mapped transcripts. Additionally, we performed a deconvolution analysis for bulk mRNA-seq and DNA methylation profiling with scRNA-seq as the reference profiles.

RESULTS: The results demonstrated that 17 key genes were finally found to share changes in the different omics and tissues and oligodendrocyte precursor cells (OPCs) have a significant difference in cell type proportions among 7 cell types. Meanwhile, our analysis of single-cell sequence from the antidepressant-treated rats found that drug-specific differential expression genes were enriched into biological pathways, including ion channels and glutamatergic receptors.

CONCLUSIONS: This study identified some important dysregulated genes influenced by DNA methylation in two brain regions of depression and suicide patients. Interestingly, we found that OPCs have the most contributors for cell-type proportions related into differential expression genes and methylated sites in suicidal behavior.


Language: en

Keywords

Suicide; Depression; Deconvolution analysis; Multi-omics analysis; Postmortem brain tissues

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