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dc.contributor.advisorFraenkel, Ernest
dc.contributor.authorLi, Jonathan
dc.date.accessioned2022-06-15T13:04:11Z
dc.date.available2022-06-15T13:04:11Z
dc.date.issued2022-02
dc.date.submitted2022-03-10T00:17:27.537Z
dc.identifier.urihttps://hdl.handle.net/1721.1/143216
dc.description.abstractALS is a devastating neurodegenerative disorder with no known cure. In this thesis, I describe high-throughput omics characterization of patient-derived induced pluripotent stem cell (iPSC) models. I present analyses aimed at discovering disease pathways and genes associated with ALS using systems biology approaches. In patients with the C9orf72 mutation, I use a network-based algorithm to identify disrupted pathways enriched for extracellular matrix organization and protein transport. Integrating these findings with results from a C9orf72 Drosophila model, I found causal and compensatory pathways that may be active in C9-ALS. Next, I investigated the genetics of ALS using genomic, transcriptomic, and epigenomic data collected across 181 iPSC-derived motor neurons from ALS patients and controls. I performed quantitative trait loci (QTL) analyses and found transcriptional regulators and genes implicated in ALS pathology which were enriched for autophagy and DNA damage repair. Notably, we found missplicing of G2E3 and SCFD1 to be a consequence of the previously uncharacterized SCFD1 risk locus. In all, these findings further our understanding of ALS pathology and help prioritize potential targets for therapeutic intervention. The systems biology approaches outlined in this thesis can be useful for studying other disease contexts as well.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright MIT
dc.rights.urihttp://rightsstatements.org/page/InC-EDU/1.0/
dc.titleSystems Biology Approaches for Elucidating Early ALS Disease Processes
dc.typeThesis
dc.description.degreePh.D.
dc.contributor.departmentMassachusetts Institute of Technology. Computational and Systems Biology Program
dc.identifier.orcidhttps://orcid.org/ 0000-0003-0782-2077
mit.thesis.degreeDoctoral
thesis.degree.nameDoctor of Philosophy


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