Lauren E Ethridge1, Jordan P Hamm2, Godfrey D Pearlson3, Carol A Tamminga1, John A Sweeney1, Matcheri S Keshavan4, Brett A Clementz5. 1. Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas Texas. 2. Departments of Psychology, BioImaging Research Center, University of Georgia, Athens, Georgi; Neuroscience, BioImaging Research Center, University of Georgia, Athens, Georgia. 3. Olin Neuropsychiatry Research Center, Institute of Living, Hartford; Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Connecticut. 4. Department of Psychiatry, Beth Israel Deaconness Medical Center, Harvard University, Boston, Massachusetts. 5. Departments of Psychology, BioImaging Research Center, University of Georgia, Athens, Georgi; Neuroscience, BioImaging Research Center, University of Georgia, Athens, Georgia. Electronic address: clementz@uga.edu.
Abstract
BACKGROUND: The investigators compared event-related potential (ERP) amplitudes and event-related oscillations across a broad frequency range during an auditory oddball task using a comprehensive analysis approach to describe shared and unique neural auditory processing characteristics among healthy subjects (HP), schizophrenia probands (SZ) and their first-degree relatives, and bipolar disorder I with psychosis probands (BDP) and their first-degree relatives. METHODS: This Bipolar-Schizophrenia Network on Intermediate Phenotypes sample consisted of clinically stable SZ (n = 229) and BDP (n = 188), HP (n = 284), first-degree relatives of schizophrenia probands (n = 264), and first-degree relatives of bipolar disorder I with psychosis probands (n = 239). They were administered an auditory oddball task in the electroencephalography environment. Principal components analysis derived data-driven frequency bands evoked power. Spatial principal components analysis reduced ERP and frequency data to component waveforms for each subject. Clusters of time bins with significant group differences on response magnitude were assessed for proband/relative differences from HP and familiality. RESULTS: Nine variables survived a linear discriminant analysis between HP, SZ, and BDP. Of those, two showed evidence (deficit in relatives and familiality) as genetic risk markers more specific to SZ (N1, P3b), one was specific to BDP (P2) and one for psychosis in general (N2). CONCLUSIONS: This study supports for both shared and unique deficits in early sensory and late cognitive processing across psychotic diagnostic groups. Additional ERP and time-frequency component alterations (frontal N2/P2, late high, early, mid, and low frequency) may provide insight into deficits in underlying neural architecture and potential protective/compensatory mechanisms in unaffected relatives.
BACKGROUND: The investigators compared event-related potential (ERP) amplitudes and event-related oscillations across a broad frequency range during an auditory oddball task using a comprehensive analysis approach to describe shared and unique neural auditory processing characteristics among healthy subjects (HP), schizophrenia probands (SZ) and their first-degree relatives, and bipolar disorder I with psychosis probands (BDP) and their first-degree relatives. METHODS: This Bipolar-Schizophrenia Network on Intermediate Phenotypes sample consisted of clinically stable SZ (n = 229) and BDP (n = 188), HP (n = 284), first-degree relatives of schizophrenia probands (n = 264), and first-degree relatives of bipolar disorder I with psychosis probands (n = 239). They were administered an auditory oddball task in the electroencephalography environment. Principal components analysis derived data-driven frequency bands evoked power. Spatial principal components analysis reduced ERP and frequency data to component waveforms for each subject. Clusters of time bins with significant group differences on response magnitude were assessed for proband/relative differences from HP and familiality. RESULTS: Nine variables survived a linear discriminant analysis between HP, SZ, and BDP. Of those, two showed evidence (deficit in relatives and familiality) as genetic risk markers more specific to SZ (N1, P3b), one was specific to BDP (P2) and one for psychosis in general (N2). CONCLUSIONS: This study supports for both shared and unique deficits in early sensory and late cognitive processing across psychotic diagnostic groups. Additional ERP and time-frequency component alterations (frontal N2/P2, late high, early, mid, and low frequency) may provide insight into deficits in underlying neural architecture and potential protective/compensatory mechanisms in unaffected relatives.
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