A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles
Sey NYA, Hu B, Mah W, Fauni H, McAfee JC, Rajarajan P, Brennand KJ, Akbarian S, Won H. A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles. Nature Neuroscience 2020, 23: 583-593. PMID: 32152537, PMCID: PMC7131892, DOI: 10.1038/s41593-020-0603-0.Peer-Reviewed Original ResearchConceptsChromatin interaction profilesH-MAGMARisk genesMost risk variantsGenome-wide association studiesCell typesGene regulatory relationshipsRelevant target genesCell-type specificitySingle nucleotide polymorphism associationsBrain cell typesDisease-relevant tissuesInteraction profilesGenomic annotationsNearest geneTarget genesRegulatory relationshipsAssociation studiesBiological pathwaysGenesRisk variantsDevelopmental windowBiological mechanismsNeurodegenerative disordersHuman brain tissueIntegrating CRISPR Engineering and hiPSC-Derived 2D Disease Modeling Systems
Rehbach K, Fernando MB, Brennand KJ. Integrating CRISPR Engineering and hiPSC-Derived 2D Disease Modeling Systems. Journal Of Neuroscience 2020, 40: 1176-1185. PMID: 32024766, PMCID: PMC7002154, DOI: 10.1523/jneurosci.0518-19.2019.Peer-Reviewed Original ResearchConceptsHuman induced pluripotent stem cellsMajor brain cell typesDual Perspectives CompanionBrain cell typesNeuronal maturityPsychiatric disordersHuman neuronsDisease riskStudy designBrain organoidsIntradonor variabilityDisease modelsHuman neurodevelopmentInduced pluripotent stem cellsNeural differentiationDiseaseStem cellsCell typesPluripotent stem cellsHuman diseasesEfficient neural differentiationInduction strategyPatient-specific cellsDisease modelingCells