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dc.contributor.authorCristino, Alexandre
dc.contributor.authorTyebally, Mubarika
dc.contributor.authorSabdia, Muhammed
dc.contributor.authorThillaiyampalam, Gayathri
dc.contributor.authorMackay-Sim, Alan
dc.description.abstractBackground: Genome-wide association studies have identified over 100 loci in which common genetic variants are associated with schizophrenia in the population. Other rare genetic risk variants have also been identified. The challenge to the field is to understand the functional consequences of these genetic variants and the frequency and combinations of common and rare variants in individuals are unknown. How do we move to a functional genomics understanding of schizophrenia? This must come from the biology of individual patient-derived cells where genotype relates directly to cell phenotype and where specific genetic variants are examined in context of the individual’s full array of genetic risks. Methods: We have developed a novel systems-based approach using multi-omics data and cellular function assays using schizophrenia patient-derived olfactory neural stem cells as the model system. We are identifying genetic variants that influence schizophrenia-associated cell functions in individual patient cells. This integrative and deep analysis of molecular networks, signaling pathways and cell functions in the same individual patient and control stem cells is unique in the fields of schizophrenia, cell biology, and systems biology. Results: Whole-exome sequencing data from this cohort of patient-derived stem cells confirm that the patient cells have higher polygenic risk scores when compared to healthy controls. We filtered schizophrenia-relevant, rare and common variants, present in individual patients, by their participation in the schizophrenia protein-protein interaction network that we previously built using genes located in schizophrenia-associated loci. We found that these selected variants were significantly enriched in schizophrenia-associated gene networks, pathways and functions that we have previously identified in these patient-derived cells: i.e. in multiple regulatory layers including DNA methylation, transcriptome and proteome; and in multiple assays of cell functions including cell proliferation, cell cycle, cell adhesion, cell motility, and protein synthesis. Discussion: This systems-level view draws attention away from single candidate genes and single cell functions, identifying failure of regulation of networks and pathways as central to schizophrenia stem cell biology, leading to modulation of multiple cell functions. Such failures of regulation could change subtly the behaviour of cells and the assembly of the brain during development as well as cell functions in the mature brain. Our long-term goal is to use un-biased systems-level cellular and molecular data from patient-derived stem cells to build a roadmap for discovery of new therapeutic strategies tailored to individual’s molecular and cellular signatures.
dc.publisherOxford University Press
dc.relation.ispartofconferencenameCongress of the Schizophrenia-International-Research-Society (SRIS)
dc.relation.ispartofconferencetitleSCHIZOPHRENIA BULLETIN
dc.relation.ispartoflocationOrlando, FL
dc.relation.ispartofpagefrom1 pages
dc.relation.ispartofpageto1 pages
dc.subject.fieldofresearchMedical and Health Sciences
dc.subject.fieldofresearchPsychology and Cognitive Sciences
dc.subject.keywordsScience & Technology
dc.subject.keywordsLife Sciences & Biomedicine
dc.titleSchizophrenia Patient-derived stem cells for systems genomics: Genetic variants, molecular pathways and cell functions altered in individual patients
dc.typeConference output
dc.type.descriptionE3 - Conferences (Extract Paper)
dcterms.bibliographicCitationCristino, A; Tyebally, M; Sabdia, M; Thillaiyampalam, G; Mackay-Sim, A, Schizophrenia Patient-derived stem cells for systems genomics: Genetic variants, molecular pathways and cell functions altered in individual patients, Schizophrenia Bulletin, 2019, 45 (Supplement_2), pp. S160-S160
gro.hasfulltextNo Full Text
gro.griffith.authorCristino, Alex
gro.griffith.authorThillaiyampalam, Gayathri
gro.griffith.authorMackay-Sim, Alan

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