Haase, F.; Singh, R.; Gloss, B.; Tam, P.; Gold, W. Meta-Analysis Identifies BDNF and Novel Common Genes Differently Altered in Cross-Species Models of Rett Syndrome. Int. J. Mol. Sci.2022, 23, 11125.
Haase, F.; Singh, R.; Gloss, B.; Tam, P.; Gold, W. Meta-Analysis Identifies BDNF and Novel Common Genes Differently Altered in Cross-Species Models of Rett Syndrome. Int. J. Mol. Sci. 2022, 23, 11125.
Haase, F.; Singh, R.; Gloss, B.; Tam, P.; Gold, W. Meta-Analysis Identifies BDNF and Novel Common Genes Differently Altered in Cross-Species Models of Rett Syndrome. Int. J. Mol. Sci.2022, 23, 11125.
Haase, F.; Singh, R.; Gloss, B.; Tam, P.; Gold, W. Meta-Analysis Identifies BDNF and Novel Common Genes Differently Altered in Cross-Species Models of Rett Syndrome. Int. J. Mol. Sci. 2022, 23, 11125.
Abstract
Rett syndrome (RTT) is a rare disease and one of the most abundant causes for intellectual disa-bilities in females. Single mutations in the gene coding for methyl-CpG-binding protein 2 (MECP2), are responsible for the disease. MeCP2 regulates gene expression as a transcriptional regulator as well as through epigenetic imprinting and chromatin condensation. Consequently, numerous biological pathways on multiple levels are influenced however, the exact molecular pathways from genotype to phenotype are currently not fully elucidated. Treatment of RTT is purely symptomatic where no curative options for RTT have yet to reach the clinic. The paucity of this is mainly due to an incomplete understanding of the underlying pathophysiology of the dis-order with no clinically useful common disease drivers, biomarkers or therapeutic targets being identified. With the premise of identifying universal and robust disease drivers and therapeutic targets, here we interrogated a range of RTT transcriptomic studies spanning different species, models and MECP2 mutations. A meta-analysis using RNA sequencing data from brains of RTT mouse models human post-mortem brain tissue and patient-derived induced pluripotent stem cells (iPSC) neurons was performed using Weighted Gene Correlation Network Analysis (WGC-NA). This study identified a module of genes common to all datasets with the following ten hub genes driving the expression ATRX, ADCY7, ADCY9, SOD1, CACNA1A, PLCG1, CCT5, RPS9, BDNF and MECP2. Here we discuss the potential benefits of these genes as therapeutic targets.
Keywords
Rett syndrome; WGCNA; MECP2
Subject
Biology and Life Sciences, Biochemistry and Molecular Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
