Huntington's disease (HD) is a rare neurodegenerative disorder caused by an expansion of the CAG trinucleotide repeat in exon 1 of the HTT gene. Early and accurate detection of this genetic mutation is vital for effective symptom management and enhancing the quality of life, especially in pediatric cases. This thesis addresses the pressing need for advanced tools to elucidate the complexities of HD pathogenesis, including somatic mosaicism and variability in repeat expansions. To this end, this thesis work implemented a novel computational tool, SearcHD, designed to facilitate precise and efficient genotyping of the HTT gene from Next Generation Sequencing (NGS) data in HD patients. SearcHD enhances somatic allele-calling accuracy and introduces innovative features such as somatic mosaicism index calculations and the detection of Loss of Interruption (LOI) events within the CAG repeat tract. This tool was applied to analyze NGS short-read data from a local cohort of HD patients, generating comprehensive genotypic profiles. Additionally, we performed mitochondrial genome sequencing on a subset of these patients, using a custom bioinformatics pipeline to identify pathogenic variants and to assess the burden of heteroplasmic variants, exploring their correlation with HD pathogenesis, and observing significant shifts in heteroplasmy levels over time, suggesting impaired mitochondrial turnover, especially in patients with early-onset HD. Furthermore, we analyzed brain expression data from two public datasets to evaluate transcriptional changes associated with adult- and juvenile-onset HD. We employed differential expression analysis and weighted gene co-expression network analysis (WGCNA) and we identified co-expressed gene clusters that may characterize HD phenotypes. Overall, this thesis presents a multi-layered exploration of HD, providing a bioinformatics framework that enhances the speed, precision, and accuracy of patient genotyping. In doing so, it aims to shed light on the intricacies of the molecular mechanisms underlying HD pathogenesis.

A multi-omics perspective on Huntington’s Disease

LIORNI, NICCOLO'
2025

Abstract

Huntington's disease (HD) is a rare neurodegenerative disorder caused by an expansion of the CAG trinucleotide repeat in exon 1 of the HTT gene. Early and accurate detection of this genetic mutation is vital for effective symptom management and enhancing the quality of life, especially in pediatric cases. This thesis addresses the pressing need for advanced tools to elucidate the complexities of HD pathogenesis, including somatic mosaicism and variability in repeat expansions. To this end, this thesis work implemented a novel computational tool, SearcHD, designed to facilitate precise and efficient genotyping of the HTT gene from Next Generation Sequencing (NGS) data in HD patients. SearcHD enhances somatic allele-calling accuracy and introduces innovative features such as somatic mosaicism index calculations and the detection of Loss of Interruption (LOI) events within the CAG repeat tract. This tool was applied to analyze NGS short-read data from a local cohort of HD patients, generating comprehensive genotypic profiles. Additionally, we performed mitochondrial genome sequencing on a subset of these patients, using a custom bioinformatics pipeline to identify pathogenic variants and to assess the burden of heteroplasmic variants, exploring their correlation with HD pathogenesis, and observing significant shifts in heteroplasmy levels over time, suggesting impaired mitochondrial turnover, especially in patients with early-onset HD. Furthermore, we analyzed brain expression data from two public datasets to evaluate transcriptional changes associated with adult- and juvenile-onset HD. We employed differential expression analysis and weighted gene co-expression network analysis (WGCNA) and we identified co-expressed gene clusters that may characterize HD phenotypes. Overall, this thesis presents a multi-layered exploration of HD, providing a bioinformatics framework that enhances the speed, precision, and accuracy of patient genotyping. In doing so, it aims to shed light on the intricacies of the molecular mechanisms underlying HD pathogenesis.
17-gen-2025
Inglese
CAPUTO, VIVIANA
Mazza, Tommaso
STRONATI, LAURA
Università degli Studi di Roma "La Sapienza"
83
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/193909
Il codice NBN di questa tesi è URN:NBN:IT:UNIROMA1-193909