2020
Transcriptomic organization of the human brain in post-traumatic stress disorder
Girgenti MJ, Wang J, Ji D, Cruz DA, Stein M, Gelernter J, Young K, Huber B, Williamson D, Friedman M, Krystal J, Zhao H, Duman R. Transcriptomic organization of the human brain in post-traumatic stress disorder. Nature Neuroscience 2020, 24: 24-33. PMID: 33349712, DOI: 10.1038/s41593-020-00748-7.Peer-Reviewed Original ResearchMeSH KeywordsAdultAutopsyBrain ChemistryCohort StudiesDepressive Disorder, MajorFemaleGene Expression RegulationGene Regulatory NetworksGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansInterneuronsMaleMiddle AgedNerve Tissue ProteinsSex CharacteristicsStress Disorders, Post-TraumaticTranscriptomeYoung AdultConceptsGenome-wide association studiesSignificant gene networksDifferential gene expressionSystems-level evidenceSignificant genetic liabilityMajor depressive disorder cohortGene networksTranscriptomic organizationTranscriptomic landscapeDownregulated setsGenomic networksGene expressionAssociation studiesMolecular determinantsExtensive remodelingGenotype dataSexual dimorphismSignificant divergenceMolecular profileNetwork analysisELFN1TranscriptsDimorphismPostmortem tissueDivergenceLeveraging functional annotation to identify genes associated with complex diseases
Liu W, Li M, Zhang W, Zhou G, Wu X, Wang J, Lu Q, Zhao H. Leveraging functional annotation to identify genes associated with complex diseases. PLOS Computational Biology 2020, 16: e1008315. PMID: 33137096, PMCID: PMC7660930, DOI: 10.1371/journal.pcbi.1008315.Peer-Reviewed Original ResearchMeSH KeywordsEpigenesis, GeneticGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMolecular Sequence AnnotationPolymorphism, Single NucleotideQuantitative Trait LociConceptsExpression quantitative trait lociComplex traitsNovel lociIdentification of eQTLGene expressionTranscriptome-wide association study methodLinkage disequilibriumQuantitative trait lociAssociation study methodsCombined Annotation Dependent Depletion (CADD) scoresAnnotation-dependent depletion scoreExpression levelsDisease-associated genesEpigenetic annotationsEpigenetic informationFunctional annotationTrait lociGenetic variationGenesPrevious GWASLociGenetic effectsTraitsComplex diseasesGWAS
2019
A statistical framework for cross-tissue transcriptome-wide association analysis
Hu Y, Li M, Lu Q, Weng H, Wang J, Zekavat SM, Yu Z, Li B, Gu J, Muchnik S, Shi Y, Kunkle BW, Mukherjee S, Natarajan P, Naj A, Kuzma A, Zhao Y, Crane PK, Lu H, Zhao H. A statistical framework for cross-tissue transcriptome-wide association analysis. Nature Genetics 2019, 51: 568-576. PMID: 30804563, PMCID: PMC6788740, DOI: 10.1038/s41588-019-0345-7.Peer-Reviewed Original ResearchMeSH KeywordsGene ExpressionGene Expression ProfilingGenome-Wide Association StudyGenotypeHumansModels, GeneticPolymorphism, Single NucleotideTranscriptomeConceptsTranscriptome-wide association analysisAssociation analysisGene-trait associationsGene expression dataGene expression levelsGenetic architectureComplex traitsMore genesGene expressionSingle tissueExpression dataAssociation resultsExpression levelsPowerful approachImputation modelHuman tissuesImputation accuracyGenotypesStatistical frameworkTissueGenesKey componentTraitsPowerful metricExpression