Description of transcriptomic alterations in Huntington’s disease is essential for the identification of targets for biomedical studies and drug development. A recent article presented a meta-analysis of publicly available transcriptomic data from Huntington’s disease patients to identify genes altered in several pre-published studies, which could be promising targets for drug development.
The Huntingtin (HTT) gene functions in diverse cellular processes including autophagy, endocytosis, vesicle transport and transcriptional regulation. A triple repeat expansion in exon 1 of the HTT gene causes expansion of an N-terminal polyglutamine tract, which results in development of Huntington’s disease. This condition is characterised by progressive loss of motor functions, cognitive impairment and psychiatric symptoms such as depression and anxiety. Expansion of the N-terminal polyQ tract impairs the multi-faceted function of the HTT gene and its interaction with other proteins. Transcriptomic studies of Huntington’s disease patients, cell lines and mouse models expressing mutant HTT observed transcriptional dysregulation of a number of genes, such as differences in the regulation of genes involved in neuronal differentiation and mRNA processing.
Meta-analysis of transcriptomic data from Huntington’s disease patients
Previously published analyses of transcriptomic profiles from Huntington’s disease patients have yielded varying results. A thorough understanding of the pathological mechanisms behind Huntington’s disease is essential for the design of further biomedical studies and the development of therapeutics. Therefore, the researchers performed a meta-analysis of publicly available transcriptomic data from Huntington’s disease patients to identify genes that were found to be altered in several previously published studies. The researchers included three published transcriptomic studies using post-mortem brain tissue from the prefrontal cortex and the caudate nucleus of prodromal HD patients.
To identify genes with significantly altered mRNA levels in the three studies, the researchers determined differentially expressed genes for each. The team then ranked the differentially expressed genes according to their absolute Z-ratio. Following that, the researchers performed a robust rank aggregation analysis. A Z-ratio is a statistical measurement of a score’s relationship to the mean group, so in this case it was used to rank genes found in the three studies based on how different the Huntington’s disease genes are from the normal gene expression levels. In addition to that, a rank aggregation analysis detects genes that are ranked consistently better than expected under a null hypothesis of uncorrelated inputs, and assigns a significance score for each gene.
Dysregulated genes found in the transcriptomic data from Huntington’s disease patients
The researcher’s meta-analysis identified 661 genes with a robustly altered mRNA expression level in the blood of Huntington’s disease patients. Moreover, they also identified 737 differentially expressed genes that were among the most altered genes in the brains of Huntington’s disease patients. The researchers carried our weighted gene co-expression network analysis, which enabled them to identify a subnetwork of 320 genes, enriched in genes functioning in protein transport that strongly correlated with Huntington’s disease in the brain. This finding strongly suggests that dysfunction in protein transport and metabolism are central in Huntington’s disease. Additionally, the researchers identified the cell division cycle 43 (CDC42), p21 (CDC42 / RAC1) Activated Kinase 1 (PAK1), 14-3-3 protein eta (YWHAH), and protein phosphatase-2 catalytic subunit α (PP2CA) as hub genes of this 320 gene subnetwork.
This study’s meta-analysis also identified that a subnetwork of 118 genes, including genes coding for constituents of the Arp2-Arp3 complex, were significantly altered in the blood of Huntington’s disease patients. Strikingly, the researchers found that 78% of the genes in this blood subgroup were direct or indirect targets of the transcription regulator CREB1.
This study carried out a meta-analysis on transcriptomic data from Huntington’s disease patients, which enabled the researchers to identify subnetworks of genes with robustly altered mRNA levels in the brains and blood of Huntington’s disease patients. The researchers were able to identify that CDC42 and YWHAH were dysregulated in the samples from Huntington’s disease patients, indicating that those genes and their upstream regulators, such as CREB1, could be interesting therapeutic targets for the treatment of Huntington’s disease.
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