2024
Evidence from comprehensive independent validation studies for smooth pursuit dysfunction as a sensorimotor biomarker for psychosis
Meyhoefer I, Sprenger A, Derad D, Grotegerd D, Leenings R, Leehr E, Breuer F, Surmann M, Rolfes K, Arolt V, Romer G, Lappe M, Rehder J, Koutsouleris N, Borgwardt S, Schultze-Lutter F, Meisenzahl E, Kircher T, Keedy S, Bishop J, Ivleva E, McDowell J, Reilly J, Hill S, Pearlson G, Tamminga C, Keshavan M, Gershon E, Clementz B, Sweeney J, Hahn T, Dannlowski U, Lencer R. Evidence from comprehensive independent validation studies for smooth pursuit dysfunction as a sensorimotor biomarker for psychosis. Scientific Reports 2024, 14: 13859. PMID: 38879556, PMCID: PMC11180169, DOI: 10.1038/s41598-024-64487-6.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultBiomarkersBipolar DisorderCase-Control StudiesFemaleHumansMaleMiddle AgedPsychotic DisordersPursuit, SmoothYoung AdultConceptsSmooth pursuit eye movementsPsychosis syndromePursuit eye movementsNon-psychotic bipolar disorderNon-psychotic affective disorderEye movementsSmooth pursuit dysfunctionMultivariate pattern analysisHealthy controlsPsychiatric sampleNeurobiological markersPsychosis probandsPsychotic syndromesAffective disordersPsychosis researchBipolar disorderPsychosis statusPsychosisSensorimotor functionSensorimotor measuresIndividual levelSensorimotor dysfunctionSensorimotorDisordersPattern analysis
2023
Double dissociation between P300 components and task switch error type in healthy but not psychosis participants
Huang L, Parker D, Ethridge L, Hamm J, Keedy S, Tamminga C, Pearlson G, Keshavan M, Hill S, Sweeney J, McDowell J, Clementz B. Double dissociation between P300 components and task switch error type in healthy but not psychosis participants. Schizophrenia Research 2023, 261: 161-169. PMID: 37776647, PMCID: PMC11015813, DOI: 10.1016/j.schres.2023.09.025.Peer-Reviewed Original ResearchMeSH KeywordsCognitionElectroencephalographyEvent-Related Potentials, P300Evoked PotentialsHumansPsychotic DisordersConceptsEvent-related potentialsDouble dissociationParietal P300Oddball taskCognitive functionPsychosis participantsInductive reasoningP300 event-related potentialFrontal P300 amplitudePossible neural correlatesMental flexibilityCognitive demandsMemory maintenanceNeural correlatesPerseverative errorsRegressive errorsBehavioral performanceOddball targetsP300 componentP300 amplitudeError typesSubjects' abilityNeural activityP300 reductionHealthy participantsClinical characterization and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT)-1
Clementz B, Chattopadhyay I, Trotti R, Parker D, Gershon E, Hill S, Ivleva E, Keedy S, Keshavan M, McDowell J, Pearlson G, Tamminga C, Gibbons R. Clinical characterization and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT)-1. Schizophrenia Research 2023, 260: 143-151. PMID: 37657281, PMCID: PMC10712427, DOI: 10.1016/j.schres.2023.08.006.Peer-Reviewed Original ResearchSupervised machine learning classification of psychosis biotypes based on brain structure: findings from the Bipolar-Schizophrenia network for intermediate phenotypes (B-SNIP)
Koen J, Lewis L, Rugg M, Clementz B, Keshavan M, Pearlson G, Sweeney J, Tamminga C, Ivleva E. Supervised machine learning classification of psychosis biotypes based on brain structure: findings from the Bipolar-Schizophrenia network for intermediate phenotypes (B-SNIP). Scientific Reports 2023, 13: 12980. PMID: 37563219, PMCID: PMC10415369, DOI: 10.1038/s41598-023-38101-0.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkersBipolar DisorderBrainHumansMagnetic Resonance ImagingPhenotypePsychotic DisordersSchizophreniaConceptsPsychosis biotypesPsychosis casesBrain-based biomarkersLogistic regression modelsT1-weighted imagesBipolar-Schizophrenia NetworkHealthy controlsDisease neurobiologyPsychotic disordersClinical diagnosisStructural MRIBrain structuresGrey matter density mapsDSM diagnosesEvidence of specificityAbove-chance classification accuracyPeripheral inflammatory subgroup differences in anterior Default Mode network and multiplex functional network topology are associated with cognition in psychosis
Lizano P, Kiely C, Mijalkov M, Meda S, Keedy S, Hoang D, Zeng V, Lutz O, Pereira J, Ivleva E, Volpe G, Xu Y, Lee A, Rubin L, Hill S, Clementz B, Tamminga C, Pearlson G, Sweeney J, Gershon E, Keshavan M, Bishop J. Peripheral inflammatory subgroup differences in anterior Default Mode network and multiplex functional network topology are associated with cognition in psychosis. Brain Behavior And Immunity 2023, 114: 3-15. PMID: 37506949, PMCID: PMC10592140, DOI: 10.1016/j.bbi.2023.07.014.Peer-Reviewed Original ResearchMeSH KeywordsBrainBrain MappingCognitionDefault Mode NetworkHumansInflammationMagnetic Resonance ImagingPsychotic DisordersSchizophreniaConceptsResting-state networksHealthy controlsInter-network connectivityWorse verbal fluencyAnterior default mode networkC-reactive proteinResting-state functional networksDefault mode network connectivityRight frontoparietal networkMode network connectivityWorse cognitive performanceResting-state fMRIDefault mode networkFunctional network topologyInflammatory signatureSystemic inflammationInflammatory subgroupIL-6Neuroanatomical alterationsPsychosis probandsCo-activation patternsPsychosis spectrum disordersNetwork dysfunctionMultiple comparison correctionClinical implicationsEmotional scene processing in biotypes of psychosis
Trotti R, Parker D, Sabatinelli D, Keshavan M, Keedy S, Gershon E, Pearlson G, Hill S, Tamminga C, McDowell J, Clementz B. Emotional scene processing in biotypes of psychosis. Psychiatry Research 2023, 324: 115227. PMID: 37121219, PMCID: PMC10175237, DOI: 10.1016/j.psychres.2023.115227.Peer-Reviewed Original ResearchMeSH KeywordsBrainElectroencephalographyEmotionsEvoked PotentialsHumansPsychotic DisordersSchizophreniaConceptsSocial-emotional deficitsEmotional scenesSelf-reported emotional experienceEvent-related potential studyEmotional scene processingEmotional processing deficitsPsychosis groupPsychosis subgroupsSocio-occupational functioningEmotional processingProcessing deficitsScene processingEmotional experienceNeurophysiological correlatesNeural responsesPotential studiesScalp locationsPsychosis biotypesERPCurrent studyDeficitsFirst variateFuture translational researchPsychosisPsychosis casesCharacterization of childhood trauma, hippocampal mediation and Cannabis use in a large dataset of psychosis and non-psychosis individuals
Del Re E, Yassin W, Zeng V, Keedy S, Alliey-Rodriguez N, Ivleva E, Hill S, Rychagov N, McDowell J, Bishop J, Mesholam-Gately R, Merola G, Lizano P, Gershon E, Pearlson G, Sweeney J, Clementz B, Tamminga C, Keshavan M. Characterization of childhood trauma, hippocampal mediation and Cannabis use in a large dataset of psychosis and non-psychosis individuals. Schizophrenia Research 2023, 255: 102-109. PMID: 36989667, DOI: 10.1016/j.schres.2023.03.029.Peer-Reviewed Original ResearchMeSH KeywordsAdverse Childhood ExperiencesBipolar DisorderCannabisChildCross-Sectional StudiesHippocampusHumansPsychotic DisordersConceptsChildhood Trauma QuestionnaireChildhood traumaPsychosis onsetBipolar disorder type 1Rich brain regionsAbuse/dependenceHigh childhood traumaSevere childhood traumaPolygenic risk scoresRisk scoreClinical interviewersSchizoaffective disorderMulticenter sampleSurvival analysisCA exposureYounger ageBrain regionsType 1Psychosis riskLower ageCeiling effectsHippocampusTrauma QuestionnaireSZ-polygenic risk scoreGenetic riskPeripheral inflammation is associated with impairments of inhibitory behavioral control and visual sensorimotor function in psychotic disorders
Zhang L, Lizano P, Xu Y, Rubin L, Lee A, Lencer R, Reilly J, Keefe R, Keedy S, Pearlson G, Clementz B, Keshavan M, Gershon E, Tamminga C, Sweeney J, Hill S, Bishop J. Peripheral inflammation is associated with impairments of inhibitory behavioral control and visual sensorimotor function in psychotic disorders. Schizophrenia Research 2023, 255: 69-78. PMID: 36965362, PMCID: PMC10175233, DOI: 10.1016/j.schres.2023.03.030.Peer-Reviewed Original ResearchMeSH KeywordsBehavior ControlBipolar DisorderHumansInflammationNeuropsychological TestsPsychotic DisordersSchizophreniaConceptsCognitive domainsInhibitory controlGeneral cognitive abilitySpecific cognitive domainsInhibitory behavioral controlC-reactive proteinPsychotic disordersPsychosis spectrum disordersCognitive abilitiesPeripheral inflammationInflammation factorsSpectrum disorderSensorimotor functionSensorimotor tasksNeurobehavioral domainsGreater deficitsSubgroup of individualsBehavioral controlPsychosis subgroupsCognitive impairmentPreliminary evidenceHigher inflammation scoresNeurobehavioral batteryBrain anatomyBehavioral monitoringEvaluation of boundaries between mood and psychosis disorder using dynamic functional network connectivity (dFNC) via deep learning classification
Rokham H, Falakshahi H, Fu Z, Pearlson G, Calhoun V. Evaluation of boundaries between mood and psychosis disorder using dynamic functional network connectivity (dFNC) via deep learning classification. Human Brain Mapping 2023, 44: 3180-3195. PMID: 36919656, PMCID: PMC10171526, DOI: 10.1002/hbm.26273.Peer-Reviewed Original ResearchMeSH KeywordsArtificial IntelligenceBrainDeep LearningHumansMagnetic Resonance ImagingPsychotic DisordersReproducibility of ResultsConceptsDynamic functional network connectivityFunctional network connectivityDSM-IVFMRI-based measuresResting-state fMRI dataBiomarker-based approachPsychosis disordersClinical courseBipolar-Schizophrenia NetworkClinical evaluationSymptomatic measuresHealthy controlsPsychotic illnessHealthy individualsNeurological observationsMental disordersReliability of diagnosisStatistical group differencesMental healthNeuroimaging techniquesStatistical ManualDiagnostic problemsGroup differencesIntermediate phenotypesDisorders
2022
Multimodal data fusion of cortical-subcortical morphology and functional network connectivity in psychotic spectrum disorder
DeRamus T, Wu L, Qi S, Iraji A, Silva R, Du Y, Pearlson G, Mayer A, Bustillo J, Stromberg S, Calhoun V. Multimodal data fusion of cortical-subcortical morphology and functional network connectivity in psychotic spectrum disorder. NeuroImage Clinical 2022, 35: 103056. PMID: 35709557, PMCID: PMC9207350, DOI: 10.1016/j.nicl.2022.103056.Peer-Reviewed Original ResearchConceptsResting-state functional network connectivityFunctional network connectivityGray matterFractional anisotropyMultimodal canonical correlation analysisSchizoaffective disorderBipolar disorderJoint independent component analysisDiagnostic categoriesFunctional brain featuresWhite matter fractional anisotropyBrain featuresPsychotic spectrum disordersClinical indicatorsMultiple diagnostic categoriesFunctional alterationsSubcortical structuresDisorders
2021
An opportunity for primary prevention research in psychotic disorders
Gershon ES, Lee SH, Zhou X, Sweeney JA, Tamminga C, Pearlson GA, Clementz BA, Keshavan MS, Alliey-Rodriguez N, Hudgens-Haney M, Keedy SK, Glahn DC, Asif H, Lencer R, Hill SK. An opportunity for primary prevention research in psychotic disorders. Schizophrenia Research 2021, 243: 433-439. PMID: 34315649, PMCID: PMC8784565, DOI: 10.1016/j.schres.2021.07.001.Peer-Reviewed Original Research
1995
In Vivo D2 Dopamine Receptor Density in Psychotic and Nonpsychotic Patients With Bipolar Disorder
Pearlson G, Wong D, Tune L, Ross C, Chase G, Links J, Dannals R, Wilson A, Ravert H, Wagner H, DePaulo J. In Vivo D2 Dopamine Receptor Density in Psychotic and Nonpsychotic Patients With Bipolar Disorder. JAMA Psychiatry 1995, 52: 471-477. PMID: 7771917, DOI: 10.1001/archpsyc.1995.03950180057008.Peer-Reviewed Original ResearchConceptsSchizophrenic patientsBipolar disorderBmax valuesNonpsychotic patientsNormal controlsPsychotic symptomsPsychotic patientsAffective disordersPositron emission tomographic scansD2 dopamine receptor densityNeuroleptic-naive schizophrenic patientsPositron emission tomographic studiesDopamine receptor densityReceptor density valuesDSM-III criteriaPresent State ExaminationPresence of psychosisEmission tomographic studiesHigher Bmax valuesPsychotic bipolar disorderNeuroleptic medicationReceptor BmaxMood abnormalitiesReceptor valuesTomographic scan
1988
The Late-Onset Psychoses Possible Risk Factors
Pearlson G, Rabins P. The Late-Onset Psychoses Possible Risk Factors. Psychiatric Clinics Of North America 1988, 11: 15-32. PMID: 3288978, DOI: 10.1016/s0193-953x(18)30514-8.Peer-Reviewed Original Research