2022
The three-dimensional landscape of cortical chromatin accessibility in Alzheimer’s disease
Bendl J, Hauberg M, Girdhar K, Im E, Vicari J, Rahman S, Fernando M, Townsley K, Dong P, Misir R, Kleopoulos S, Reach S, Apontes P, Zeng B, Zhang W, Voloudakis G, Brennand K, Nixon R, Haroutunian V, Hoffman G, Fullard J, Roussos P. The three-dimensional landscape of cortical chromatin accessibility in Alzheimer’s disease. Nature Neuroscience 2022, 25: 1366-1378. PMID: 36171428, PMCID: PMC9581463, DOI: 10.1038/s41593-022-01166-7.Peer-Reviewed Original ResearchConceptsOpen chromatin regionsCis-regulatory domainsChromatin accessibilitySpecific enhancer-promoter interactionsTranscription factor regulatory networksEnhancer-promoter interactionsATAC-seq librariesChromatin regionsLysosomal genesNonneuronal nucleiRegulatory networksThree-dimensional structureGenomeThree-dimensional landscapeRegulatory effectsAlzheimer's diseaseCommunity-based analysisUSF2GenesDysregulationRepertoireTFAD casesLandscapeDomain
2021
Molecular subtyping of Alzheimer’s disease using RNA sequencing data reveals novel mechanisms and targets
Neff R, Wang M, Vatansever S, Guo L, Ming C, Wang Q, Wang E, Horgusluoglu-Moloch E, Song W, Li A, Castranio E, Julia T, Ho L, Goate A, Fossati V, Noggle S, Gandy S, Ehrlich M, Katsel P, Schadt E, Cai D, Brennand K, Haroutunian V, Zhang B. Molecular subtyping of Alzheimer’s disease using RNA sequencing data reveals novel mechanisms and targets. Science Advances 2021, 7: eabb5398. PMID: 33523961, PMCID: PMC7787497, DOI: 10.1126/sciadv.abb5398.Peer-Reviewed Original ResearchMeSH KeywordsAlzheimer DiseaseAmyloid beta-PeptidesAnimalsBrainHumansMiceRNASequence Analysis, RNATau ProteinsConceptsAlzheimer's diseaseMouse modelAD mouse modelDiverse pathophysiologic mechanismsTau-mediated neurodegenerationMajor molecular subtypesSpecific mouse modelsPathophysiologic mechanismsHuman trialsMolecular subtypesImmune activityHeterogeneous diseaseAD cohortAD subtypesBrain regionsSynaptic signalingMolecular subtypingSubtype heterogeneityDiseaseCommon formPrecision medicineMultiscale network analysisDevastating diseaseMolecular heterogeneitySubtypes
2020
Transformative Network Modeling of Multi-omics Data Reveals Detailed Circuits, Key Regulators, and Potential Therapeutics for Alzheimer’s Disease
Wang M, Li A, Sekiya M, Beckmann ND, Quan X, Schrode N, Fernando MB, Yu A, Zhu L, Cao J, Lyu L, Horgusluoglu E, Wang Q, Guo L, Wang YS, Neff R, Song WM, Wang E, Shen Q, Zhou X, Ming C, Ho SM, Vatansever S, Kaniskan HÜ, Jin J, Zhou MM, Ando K, Ho L, Slesinger PA, Yue Z, Zhu J, Katsel P, Gandy S, Ehrlich ME, Fossati V, Noggle S, Cai D, Haroutunian V, Iijima KM, Schadt E, Brennand KJ, Zhang B. Transformative Network Modeling of Multi-omics Data Reveals Detailed Circuits, Key Regulators, and Potential Therapeutics for Alzheimer’s Disease. Neuron 2020, 109: 257-272.e14. PMID: 33238137, PMCID: PMC7855384, DOI: 10.1016/j.neuron.2020.11.002.Peer-Reviewed Original ResearchConceptsLate-onset Alzheimer's diseaseAlzheimer's diseaseKey regulatorPluripotent stem cell-derived neuronsRNAi-based knockdownStem cell-derived neuronsNovel therapeutic targetNext-generation therapeutic agentsCell-derived neuronsKey brain regionsIntegrative network analysisMulti-omics dataComplex molecular interactionsMulti-omics profilingNCH-51Neuronal impairmentGene subnetworksDisease-related processesCortical areasTherapeutic targetDrosophila modelNeuropathological phenotypeBrain regionsTherapeutic agentsMolecular mechanisms
2018
GJA1 (connexin43) is a key regulator of Alzheimer’s disease pathogenesis
Kajiwara Y, Wang E, Wang M, Sin WC, Brennand KJ, Schadt E, Naus CC, Buxbaum J, Zhang B. GJA1 (connexin43) is a key regulator of Alzheimer’s disease pathogenesis. Acta Neuropathologica Communications 2018, 6: 144. PMID: 30577786, PMCID: PMC6303945, DOI: 10.1186/s40478-018-0642-x.Peer-Reviewed Original ResearchConceptsPost-mortem Alzheimer's diseaseAlzheimer's diseaseTop key driverRNA sequencing analysisDisease pathogenesisProteomic datasetsKey regulatorNormal control brainsGJA1 expressionAlzheimer's disease (AD) pathogenesisApoE protein levelsPromising pharmacological targetSequencing analysisGJA1Wildtype astrocytesWildtype neuronsAβ metabolismAβ phagocytosisProtein levelsControl brainsAD pathogenesisAD amyloidPharmacological targetsAstrocytesCognitive function
2016
Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease
Wang M, Roussos P, McKenzie A, Zhou X, Kajiwara Y, Brennand K, De Luca G, Crary J, Casaccia P, Buxbaum J, Ehrlich M, Gandy S, Goate A, Katsel P, Schadt E, Haroutunian V, Zhang B. Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease. Genome Medicine 2016, 8: 104. PMID: 27799057, PMCID: PMC5088659, DOI: 10.1186/s13073-016-0355-3.Peer-Reviewed Original ResearchConceptsGene expression changesCell type-specific marker genesExpression changesSingle-cell RNA-sequencing dataCo-expressed gene modulesLarge-scale gene expressionTranscriptomic network analysisCo-expression networkRNA-sequencing dataIntegrative network analysisNervous system developmentSelective regional vulnerabilityCritical molecular pathwaysActin cytoskeletonGenomic studiesGene modulesGenomic analysisGene expression abnormalitiesMarker genesMolecular basisGene expressionNetwork analysisMolecular mechanismsAxon guidanceMolecular pathways