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oai:dspace.mit.edu:1721.1/1432162022-06-16T03:07:04Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022

Fraenkel, Ernest Li, Jonathan Massachusetts Institute of Technology. Computational and Systems Biology Program 2022-06-15T13:04:11Z 2022-06-15T13:04:11Z 2022-02 2022-03-10T00:17:27.537Z https://hdl.handle.net/1721.1/143216 https://orcid.org/ 0000-0003-0782-2077 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. Ph.D. Massachusetts Institute of Technology In Copyright - Educational Use Permitted Copyright MIT http://rightsstatements.org/page/InC-EDU/1.0/ Systems Biology Approaches for Elucidating Early ALS Disease Processes Thesis application/pdf Doctoral Doctor of Philosophy Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="d7d11c91-7176-4717-99b5-4bed2b6fba99"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Title>Systems Biology Approaches for Elucidating Early ALS Disease Processes</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2022-02</PublicationDate> <Authors> <Author> <DisplayName>Li, Jonathan</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://rightsstatements.org/page/InC-EDU/1.0/</License> <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.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>