Gene expression profiles complement the analysis of genomic modifiers of the clinical onset of Huntington disease. (18th August 2020)

• Record Type: Journal Article
• Authors: Wright, Galen E B; Caron, Nicholas S; Ng, Bernard; Casal, Lorenzo; Casazza, William; Xu, Xiaohong; Ooi, Jolene; Pouladi, Mahmoud A; Mostafavi, Sara; Ross, Colin J D; Hayden, Michael R
• Is Part Of: Human molecular genetics. Volume 29:Number 16(2020)
• Page Start: 2788
• Page End: 2802
• Publication Date: 2020-08-18
• Subjects: Human molecular genetics -- Periodicals; Human chromosome abnormalities -- Periodicals; 572.8
• DOI: 10.1093/hmg/ddaa184
• Languages: English
• ISSNs: 0964-6906

Abstract

Abstract: Huntington disease (HD) is a neurodegenerative disorder that is caused by a CAG repeat expansion in HTT . The length of this repeat, however, only explains a proportion of the variability in age of onset in patients. Genome-wide association studies have identified modifiers that contribute toward a proportion of the observed variance. By incorporating tissue-specific transcriptomic information with these results, additional modifiers can be identified. We performed a transcriptome-wide association study assessing heritable differences in genetically determined expression in diverse tissues, with genome-wide data from over 4000 patients. Functional validation of prioritized genes was undertaken in isogenic HD stem cells and patient brains. Enrichment analyses were performed with biologically relevant gene sets to identify the core pathways. HD-associated gene coexpression modules were assessed for associations with neurological phenotypes in an independent cohort and to guide drug repurposing analyses. Transcriptomic analyses identified genes that were associated with age of HD onset and displayed colocalization with gene expression signals in brain tissue ( FAN1, GPR161, PMS2, SUMF2 ), with supporting evidence from functional experiments. This included genes involved in DNA repair, as well as novel-candidate modifier genes that have been associated with other neurological conditions. Further, cortical coexpression modules were also associated with cognitive decline and HD-related traits in a longitudinal cohort. In summary, the combination of population-scale gene expression information with HD patient genomic data identified novel modifier genes for the disorder. Further, these analyses expanded the pathways potentially involved in modifying HD onset and prioritized candidate therapeutics for future study. Graphical Abstract: Schematic representation of methodology employed to identify transcriptomic modifiers of Huntington disease (HD). Transcriptome-wide association analyses facilitated (A ) the identification of top transcriptomic HD onset modifier genes, (B ) relevant biologically diverse gene sets that are enriched for this trait and (C ) human cortical coexpression modules that are relevant for HD onset and related phenotypes in an aging cohort, along with signature matching of HD signals for drug repurposing.