Skip navigation
  • Home
  • Browse
    • Communities
      & Collections
    • Browse Items by:
    • Publication Date
    • Author
    • Title
    • Subject
    • Department
  • Sign on to:
    • My MacSphere
    • Receive email
      updates
    • Edit Profile


McMaster University Home Page
  1. MacSphere
  2. Open Access Dissertations and Theses Community
  3. Open Access Dissertations and Theses
Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/27968
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorSingh, Karun-
dc.contributor.authorMurtaza, Nadeem-
dc.date.accessioned2022-10-11T15:22:14Z-
dc.date.available2022-10-11T15:22:14Z-
dc.date.issued2022-11-
dc.identifier.urihttp://hdl.handle.net/11375/27968-
dc.description.abstractAutism spectrum disorder (ASD) encompasses a broad range of neurodevelopmental disorders, with two core symptoms: deficits in social communication, and restrictive interests and repetitive behaviors. Genetics is thought to play a large role in ASD and currently there are hundreds of associated genes. We first studied the thousand and one amino acid kinase gene (TAOK2), which plays an important role in neurodevelopment. We found that loss of TAOK2 causes deficits in neuron development and activity, leading to morphological changes in various mouse brain regions and ASD-related behaviors. We studied the impact of de novo mutations identified in TAOK2, which caused aberrant neuron dendritic arborization and formation of synapses. To elucidate how TAOK2 regulates neuron development we used a proximity-labeling proteomics technique (BioID) to identify its protein-protein interaction (PPI) network. We applied this same methodology to a total of 41 ASD-risk genes and observed multiple convergent biological processes, including the less-studied mitochondrial and metabolic pathways. ASD-risk genes, including TAOK2, associated with mitochondrial proteins were found to have altered cellular respiration. The shared ASD-risk gene PPI network enriched for other ASD-risk genes and was used to group genes based on their shared PPI networks. These gene groups showed correlation between the clinical behavior scores of individuals that had mutations within the distinct gene groups. Lastly, we identified changes in the PPI networks of multiple ASD-risk genes through BioID, which we validated with various functional assays. In summary, we developed a proximity-labeling proteomics method that identified multiple convergent biological pathways associated with ASD. Studying the function of TAOK2 revealed multiple disease-relevant pathologies associated with the disorder, however proximity labeling has the potential to categorize multiple ASD-risk genes and elucidate their shared signaling pathways, which together, can advance the development of robust treatments for ASD.en_US
dc.language.isoenen_US
dc.subjectNeurodevelopmental Disorderen_US
dc.subjectBioIDen_US
dc.subjectAutism spectrum disorderen_US
dc.titleThe shared signaling pathways of autism-risk genes and their disruption by genetic variantsen_US
dc.title.alternativeINVESTIGATING THE CONVERGENT DISEASE-RELEVANT MECHANISMS IN AUTISM SPECTRUM DISORDERen_US
dc.typeThesisen_US
dc.contributor.departmentBiochemistry and Biomedical Sciencesen_US
dc.description.degreetypeThesisen_US
dc.description.degreeDoctor of Philosophy (PhD)en_US
dc.description.layabstractAutism spectrum disorder (ASD) is a group of brain disorders that affect more than 1% of children. Genetic variants are thought to cause ASD pathology, however there are currently hundreds of genes that have not been studied. We studied how disruption of one of those genes, TAOK2, alters brain development in mice and identified TAOK2 variants in multiple children with ASD. We then used BioID to find the shared disease-related mechanisms between multiple ASD-risk genes, and found that mitochondrial function and activity were connected to many of these genes. We showed that BioID can be used to study the effect of mutations in multiple ASD-risk genes simultaneously. Last, we could group children with ASD with similar behavior test scores based on the shared mechanisms of ASD-risk genes. Together our findings could be used to advance the development of robust treatments or new diagnostic tools for ASD.en_US
Appears in Collections:Open Access Dissertations and Theses

Files in This Item:
File Description SizeFormat 
Murtaza_Nadeem_2022Sept_PhD.pdf
Open Access
27.95 MBAdobe PDFView/Open
Show simple item record Statistics


Items in MacSphere are protected by copyright, with all rights reserved, unless otherwise indicated.

Sherman Centre for Digital Scholarship     McMaster University Libraries
©2022 McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4L8 | 905-525-9140 | Contact Us | Terms of Use & Privacy Policy | Feedback

Report Accessibility Issue