2024
Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data
Dai R, Chu T, Zhang M, Wang X, Jourdon A, Wu F, Mariani J, Vaccarino F, Lee D, Fullard J, Hoffman G, Roussos P, Wang Y, Wang X, Pinto D, Wang S, Zhang C, consortium P, Chen C, Liu C. Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data. Science Advances 2024, 10: eadh2588. PMID: 38781336, PMCID: PMC11114236, DOI: 10.1126/sciadv.adh2588.Peer-Reviewed Original ResearchConceptsHuman brain transcriptome dataBrain transcriptomic dataRNA-seqTranscriptome dataCell-type gene expressionGene expressionCell-type proportionsSingle-cell dataMultiple brain disordersBrain cell typesCell deconvolution methodsPostmortem brainsRNA sequencingBrain disordersBrain developmentSchizophreniaEQTLAlzheimer's diseaseCell typesOrganoid samplesBrainBiological applications
2021
Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia
Zhu X, Zhou B, Pattni R, Gleason K, Tan C, Kalinowski A, Sloan S, Fiston-Lavier AS, Mariani J, Petrov D, Barres BA, Duncan L, Abyzov A, Vogel H, Moran J, Vaccarino F, Tamminga C, Levinson D, Urban A. Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia. Nature Neuroscience 2021, 24: 186-196. PMID: 33432196, PMCID: PMC8806165, DOI: 10.1038/s41593-020-00767-4.Peer-Reviewed Original ResearchMeSH KeywordsAdaptor Proteins, Signal TransducingAdultCation Transport ProteinsEmbryonic DevelopmentFemaleGenomeHeLa CellsHigh-Throughput Nucleotide SequencingHumansLong Interspersed Nucleotide ElementsMachine LearningMental DisordersMutagenesis, InsertionalNeurogliaNeuronsPregnancyRetroelementsSchizophreniaConceptsBrain developmentPossible pathological effectsAnatomical distributionBilateral distributionHuman neuronsNervous systemHuman nervous systemNeuropsychiatric diseasesNeuropsychiatric disordersGliaPathological effectsNeuronsSomatic L1 insertionsWhole-genome sequencingHuman brainSomatic retrotransposition
2016
Altering the course of schizophrenia: progress and perspectives
Millan MJ, Andrieux A, Bartzokis G, Cadenhead K, Dazzan P, Fusar-Poli P, Gallinat J, Giedd J, Grayson DR, Heinrichs M, Kahn R, Krebs MO, Leboyer M, Lewis D, Marin O, Marin P, Meyer-Lindenberg A, McGorry P, McGuire P, Owen MJ, Patterson P, Sawa A, Spedding M, Uhlhaas P, Vaccarino F, Wahlestedt C, Weinberger D. Altering the course of schizophrenia: progress and perspectives. Nature Reviews Drug Discovery 2016, 15: 485-515. PMID: 26939910, DOI: 10.1038/nrd.2016.28.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsCourse of schizophreniaCognitive-behavioral interventionsSocial deficitsSchizophrenia-like phenotypeCognitive deficitsCausal pathophysiologyYoung adulthoodYoung adultsPrediction of transitionBrain imagingKey PointsSchizophreniaLevel of individualsHigh-risk individualsSchizophreniaVulnerable young adultsDeficitsPsychosisIndividualsAdult rodentsRisk individualsPharmacological treatmentDisordersAdolescenceUse of biomarkersDistress