2024
Categorical and Dimensional Approaches for Psychiatric Classification and Treatment Targeting: Considerations from Psychosis Biotypes
Clementz B, Assaf M, Sweeney J, Gershon E, Keedy S, Hill S, Ivleva E, Tamminga C, McDowell J, Keshavan M, Gibbons R, Carpenter W, Pearlson G. Categorical and Dimensional Approaches for Psychiatric Classification and Treatment Targeting: Considerations from Psychosis Biotypes. Advances In Neurobiology 2024, 40: 685-723. PMID: 39562461, DOI: 10.1007/978-3-031-69491-2_23.Peer-Reviewed Original ResearchConceptsIdiopathic psychosisBiotype-1Response to clozapineBipolar-Schizophrenia NetworkContinuum of severityReduced physiological responseDSM diagnosesNeurobiological distinctionsCategorical diagnosisSchizophrenia NetworkDiagnostic boundariesSalient stimuliPsychosis diagnosisPsychosis casesPsychiatric classificationPsychosis dataPsychosisBiotype-2Identified biotypesNeural activityIntermediate phenotypesTreatment targetElectrophysiological biomarkersElectrophysiological measurementsMedical model
2021
Anterior-posterior axis of hippocampal subfields across psychoses: A B-SNIP study
del Re E, Zeng V, Alliey-Rodriguez N, Lizano P, Bolo N, Lutz O, Pearlson G, Sweeney J, Clementz B, Gershon E, Tamminga C, Keshavan M. Anterior-posterior axis of hippocampal subfields across psychoses: A B-SNIP study. Biomarkers In Neuropsychiatry 2021, 5: 100037. DOI: 10.1016/j.bionps.2021.100037.Peer-Reviewed Original ResearchVolumetric abnormalitiesPsychosis probandsBipolar type 1Granule cell layerT MRI scansB-SNIP studyB-SNIPDentate gyrusBipolar-Schizophrenia NetworkHealthy controlsClinical dataHippocampal subfieldsDSM categoriesMRI scansSchizoaffective disorderHippocampusType 1Schizophrenia NetworkAbnormalitiesUnaffected relativesAnterior-posterior axisSchizophreniaPsychosisProbandsConclusions Differences
2017
5.3 Endophenotypes Guide Psychosis Neurobiology Formulations
Tamminga C, Clementz B, Keshavan M, Gershon E, Pearlson G, Ivleva E. 5.3 Endophenotypes Guide Psychosis Neurobiology Formulations. Schizophrenia Bulletin 2017, 43: s7-s7. DOI: 10.1093/schbul/sbx021.019.Peer-Reviewed Original ResearchConventional diagnosisFunctional brain biomarkersBiomarker compositesGray matter changesPsychosis researchHealthy controlsAdditional biomarkersClear pathophysiologyBrain biomarkersMatter changesAxis IProband groupsBiotype 1Higher negative symptomsLifetime ratesPsychiatric conditionsNegative symptomsPsychosis groupPsychotic conditionsSchizophrenia NetworkDistinct molecular markersDiagnosisAdolescent cannabisBiomarkersEEG characteristics205. Machine Learning to Further Improve Classification of Psychotic Disorders Using Clinical and Biological Stratification: Updates From the Bipolar Schizophrenia Network for Intermediate Phenotypes (BSNIP)
Tandon N, Sudarshan M, Mothi S, Clementz B, Pearlson G, Sweeney J, Tamminga C, Keshavan M. 205. Machine Learning to Further Improve Classification of Psychotic Disorders Using Clinical and Biological Stratification: Updates From the Bipolar Schizophrenia Network for Intermediate Phenotypes (BSNIP). Schizophrenia Bulletin 2017, 43: s105-s105. PMCID: PMC5475741, DOI: 10.1093/schbul/sbx021.283.Peer-Reviewed Original ResearchSA64. Hallucination Severity Predicted by Auditory Cortex Resting State Connectivity in Bipolar and Schizophrenia Network on Intermediate Phenotypes Study
Okuneye V, Meda S, Keshavan M, Sweeney J, Tamminga C, Pearlson G, Gershon E, Keedy S. SA64. Hallucination Severity Predicted by Auditory Cortex Resting State Connectivity in Bipolar and Schizophrenia Network on Intermediate Phenotypes Study. Schizophrenia Bulletin 2017, 43: s136-s136. PMCID: PMC5475960, DOI: 10.1093/schbul/sbx023.063.Peer-Reviewed Original ResearchAuditory cortexHallucination severityState connectivityPsychosis patientsSignificant negative associationIntermediate Phenotypes (B-SNIP) studySchizophrenia NetworkResting-state connectivityAbnormal activation patternsBrodmann area 22Primary auditory cortexSecondary auditory cortexRight orbitofrontal cortexPrevious functional imaging studiesPhenotype studiesClinical rating scalesAuditory processing areasPossible common pathwayFunctional imaging studiesMiddle temporal cortexNegative associationPsychosis subjectsHealthy controlsHealthy subjectsConnectivity dysfunctionAPPLYING MULTIVARIATE TECHNIQUES, INCLUDING PARALLEL ICA TO COMMON COMPLEX PSYCHIATRIC ENDOPHENOTYPES
Pearlson G, Meda, Khadka S, Tamminga C, Keshavan M, Clementz B, Sweeney J, Gershon E, Raskin S, Fallahi C. APPLYING MULTIVARIATE TECHNIQUES, INCLUDING PARALLEL ICA TO COMMON COMPLEX PSYCHIATRIC ENDOPHENOTYPES. European Neuropsychopharmacology 2017, 27: s519. DOI: 10.1016/j.euroneuro.2016.09.636.Peer-Reviewed Original ResearchNeuron differentiationMultiple risk genesState functional MRIMolecular biological pathwaysComplex psychiatric diseasesSynaptic contactsBipolar-Schizophrenia NetworkEnrichment analysisUnivariate analysisMedical disordersIntermediate Phenotypes (B-SNIP) studyPsychiatric diseasesLarger sample sizeDisease riskEEG phenotypesFunctional MRISchizophrenia NetworkState EEG dataElectrophysiological phenotypeInterneuron development