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Massachusetts Institute of Technology

Systems Biology Approaches for Elucidating Early ALS Disease Processes

Abstract

dc:description.abstract

ALS 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.

Degree

thesis:*
Name thesis:degree_name
Doctoral
Department dc:contributor.department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Li, Jonathan
Advisor dc:contributor.advisor
  • Fraenkel, Ernest

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright MIT

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/143216
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/143216

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Li, Jonathan. Systems Biology Approaches for Elucidating Early ALS Disease Processes. Massachusetts Institute of Technology, 2022. https://hdl.handle.net/1721.1/143216