Characterization of neurophysiologic and neurocognitive biomarkers for use in genomic and clinical outcome studies of schizophrenia.

BackgroundEndophenotypes are quantitative, laboratory-based measures representing intermediate links in the pathways between genetic variation and the clinical expression of a disorder. Ideal endophenotypes exhibit deficits in patients, are stable over time and across shifts in psychopathology, and are suitable for repeat testing. Unfortunately, many leading candidate endophenotypes in schizophrenia have not been fully characterized simultaneously in large cohorts of patients and controls across these properties. The objectives of this study were to characterize the extent to which widely-used neurophysiological and neurocognitive endophenotypes are: 1) associated with schizophrenia, 2) stable over time, independent of state-related changes, and 3) free of potential practice/maturation or differential attrition effects in schizophrenia patients (SZ) and nonpsychiatric comparison subjects (NCS). Stability of clinical and functional measures was also assessed.MethodsParticipants (SZ n = 341; NCS n = 205) completed a battery of neurophysiological (MMN, P3a, P50 and N100 indices, PPI, startle habituation, antisaccade), neurocognitive (WRAT-3 Reading, LNS-forward, LNS-reorder, WCST-64, CVLT-II). In addition, patients were rated on clinical symptom severity as well as functional capacity and status measures (GAF, UPSA, SOF). 223 subjects (SZ n = 163; NCS n = 58) returned for retesting after 1 year.ResultsMost neurophysiological and neurocognitive measures exhibited medium-to-large deficits in schizophrenia, moderate-to-substantial stability across the retest interval, and were independent of fluctuations in clinical status. Clinical symptoms and functional measures also exhibited substantial stability. A Longitudinal Endophenotype Ranking System (LERS) was created to rank neurophysiological and neurocognitive biomarkers according to their effect sizes across endophenotype criteria.ConclusionsThe majority of neurophysiological and neurocognitive measures exhibited deficits in patients, stability over a 1-year interval and did not demonstrate practice or time effects supporting their use as endophenotypes in neural substrate and genomic studies. These measures hold promise for informing the "gene-to-phene gap" in schizophrenia research

Is There an Association between Advanced Paternal Age and Endophenotype Deficit Levels in Schizophrenia?

The children of older fathers have increased risks of developing schizophrenia spectrum disorders, and among those who develop these disorders, those with older fathers present with more severe clinical symptoms. However, the influence of advanced paternal age on other important domains related to schizophrenia, such as quantitative endophenotype deficit levels, remains unknown. This study investigated the associations between paternal age and level of endophenotypic impairment in a well-characterized family-based sample from the Consortium on the Genetics of Schizophrenia (COGS). All families included at least one affected subject and one unaffected sibling. Subjects met criteria for schizophrenia (probands; n = 293) or were unaffected first-degree siblings of those probands (n = 382). Paternal age at the time of subjects’ birth was documented. Subjects completed a comprehensive clinical assessment and a battery of tests that measured 16 endophenotypes. After controlling for covariates, potential paternal age–endophenotype associations were analyzed using one model that included probands alone and a second model that included both probands and unaffected siblings. Endophenotype deficits in the Identical Pairs version of the 4-digit Continuous Performance Test and in the Penn Computerized Neurocognitive Battery verbal memory test showed significant associations with paternal age. However, after correcting for multiple comparisons, no endophenotype was significantly associated with paternal age. These findings suggest that factors other than advanced paternal age at birth may account for endophenotypic deficit levels in schizophrenia

Deficient prepulse inhibition in schizophrenia detected by the multi-site COGS

BACKGROUND: Startle inhibition by weak prepulses (PPI) is studied to understand the biology of information processing in schizophrenia patients and healthy comparison subjects (HCS). The Consortium on the Genetics of Schizophrenia (COGS) identified associations between PPI and single nucleotide polymorphisms in schizophrenia probands and unaffected relatives, and linkage analyses extended evidence for the genetics of PPI deficits in schizophrenia in the COGS-1 family study. These findings are being extended in a 5-site “COGS-2” study of 1800 patients and 1200 unrelated HCS to facilitate genetic analyses. We describe a planned interim analysis of COGS-2 PPI data. METHODS: Eyeblink startle was measured in carefully screened HCS and schizophrenia patients (n=1402). Planned analyses of PPI (60 ms intervals) assessed effects of diagnosis, sex and test site, PPI-modifying effects of medications and smoking, and relationships between PPI and neurocognitive measures. RESULTS: 884 subjects met strict inclusion criteria. ANOVA of PPI revealed significant effects of diagnosis (p=0.0005) and sex (p<0.002), and a significant diagnosis × test site interaction. HCS > schizophrenia PPI differences were greatest among patients not taking 2(nd) generation antipsychotics, and were independent of smoking status. Modest but significant relationships were detected between PPI and performance in specific neurocognitive measures. DISCUSSION: The COGS-2 multi-site study detects schizophrenia-related PPI deficits reported in single-site studies, including patterns related to diagnosis, prepulse interval, sex, medication and other neurocognitive measures. Site differences were detected and explored. The target COGS-2 schizophrenia “endophenotype” of reduced PPI should prove valuable for identifying and confirming schizophrenia risk genes in future analyses

Abnormal phase discontinuity of alpha- and theta-frequency oscillations in schizophrenia.

BACKGROUND: Schizophrenia patients have abnormal electroencephalographic (EEG) power over multiple frequency bands, even at rest, though the primary neural generators and spatiotemporal dynamics of these abnormalities are largely unknown. Disturbances in the precise synchronization of oscillations within and across cortical sources may underlie abnormal resting-state EEG activity in schizophrenia patients. METHODS: A novel assessment method was applied to identify the independent contributing sources of resting-state EEG and assess the phase discontinuity in schizophrenia patients (N = 148) and healthy subjects (N = 143). RESULTS: A network of 11 primary contributing sources of scalp EEG was identified in both groups. Schizophrenia patients showed abnormal elevations of EEG power in the temporal region in the theta, beta, and gamma-bands, as well as the posterior cingulate gyrus in the delta, theta, alpha, and beta-bands. The higher theta-band power in the middle temporal gyrus was significantly correlated with verbal memory impairment in patients. The peak frequency of alpha was lower in patients in the cingulate and temporal regions. Furthermore, patients showed a higher rate of alpha phase discontinuity in the temporal region as well as a lower rate of theta phase discontinuity in the temporal and posterior cingulate regions. CONCLUSIONS: Abnormal rates of phase discontinuity of alpha- and theta-band, abnormal elevations of EEG power in multiple bands, and a lower peak frequency of alpha were identified in schizophrenia patients at rest. Clarification of the mechanistic substrates of abnormal phase discontinuity may clarify core pathophysiologic abnormalities of schizophrenia and contribute to the development of novel biomarkers for therapeutic interventions

Sources of the frontocentral mismatch negativity and P3a responses in schizophrenia patients and healthy comparison subjects

BackgroundMismatch negativity (MMN) and P3a are event-related potential measures of early auditory information processing that are increasingly used as translational biomarkers in the development of treatments for neuropsychiatric disorders. These responses are reduced in schizophrenia patients over the frontocentral scalp electrodes and are associated with important domains of cognitive and psychosocial functioning. While MMN and P3a responses are generated by a dynamic network of cortical sources distributed across the temporal and frontal brain regions, it is not clear how these sources independently contribute to MMN and P3a at the primary frontocentral scalp electrode or to abnormalities observed in schizophrenia. This study aimed to determine the independent source contributions and characterize the magnitude of impairment in source-level MMN and P3a responses in schizophrenia patients.MethodsA novel method was applied to back-project the contributions of 11 independent cortical source components to Fz, the primary scalp sensor that is used in clinical studies, in n&nbsp;=&nbsp;589 schizophrenia patients and n&nbsp;=&nbsp;449 healthy comparison subjects.ResultsThe groups showed comparable individual source contributions underlying both MMN and P3a responses at Fz. Source-level responses revealed an increasing magnitude of impairment in schizophrenia patients from the temporal to more frontal sources.ConclusionsSchizophrenia patients have a normal architecture of source contributions that are accompanied by widespread abnormalities in source resolved mismatch and P3a responses, with more prominent deficits detected from the frontal sources. Quantification of source contributions and source-level responses accelerates clarification of the neural networks underlying MMN reduction at Fz in schizophrenia patients

Evidence of systematic attenuation in the measurement of cognitive deficits in schizophrenia.

Cognitive tasks that are too hard or too easy produce imprecise measurements of ability, which, in turn, attenuates group differences and can lead to inaccurate conclusions in clinical research. We aimed to illustrate this problem using a popular experimental measure of working memory-the N-back task-and to suggest corrective strategies for measuring working memory and other cognitive deficits in schizophrenia. Samples of undergraduates (n = 42), community controls (n = 25), outpatients with schizophrenia (n = 33), and inpatients with schizophrenia (n = 17) completed the N-back. Predictors of task difficulty-including load, number of word syllables, and presentation time-were experimentally manipulated. Using a methodology that combined techniques from signal detection theory and item response theory, we examined predictors of difficulty and precision on the N-back task. Load and item type were the 2 strongest predictors of difficulty. Measurement precision was associated with ability, and ability varied by group; as a result, patients were measured more precisely than controls. Although difficulty was well matched to the ability levels of impaired examinees, most task conditions were too easy for nonimpaired participants. In a simulation study, N-back tasks primarily consisting of 1- and 2-back load conditions were unreliable, and attenuated effect size (Cohen's d) by as much as 50%. The results suggest that N-back tasks, as commonly designed, may underestimate patients' cognitive deficits as a result of nonoptimized measurement properties. Overall, this cautionary study provides a template for identifying and correcting measurement problems in clinical studies of abnormal cognition. (PsycINFO Database Recor

Evidence of systematic attenuation in the measurement of cognitive deficits in schizophrenia.

Cognitive tasks that are too hard or too easy produce imprecise measurements of ability, which, in turn, attenuates group differences and can lead to inaccurate conclusions in clinical research. We aimed to illustrate this problem using a popular experimental measure of working memory-the N-back task-and to suggest corrective strategies for measuring working memory and other cognitive deficits in schizophrenia. Samples of undergraduates (n = 42), community controls (n = 25), outpatients with schizophrenia (n = 33), and inpatients with schizophrenia (n = 17) completed the N-back. Predictors of task difficulty-including load, number of word syllables, and presentation time-were experimentally manipulated. Using a methodology that combined techniques from signal detection theory and item response theory, we examined predictors of difficulty and precision on the N-back task. Load and item type were the 2 strongest predictors of difficulty. Measurement precision was associated with ability, and ability varied by group; as a result, patients were measured more precisely than controls. Although difficulty was well matched to the ability levels of impaired examinees, most task conditions were too easy for nonimpaired participants. In a simulation study, N-back tasks primarily consisting of 1- and 2-back load conditions were unreliable, and attenuated effect size (Cohen's d) by as much as 50%. The results suggest that N-back tasks, as commonly designed, may underestimate patients' cognitive deficits as a result of nonoptimized measurement properties. Overall, this cautionary study provides a template for identifying and correcting measurement problems in clinical studies of abnormal cognition. (PsycINFO Database Recor

Neurophysiologic Characterization of Resting State Connectivity Abnormalities in Schizophrenia Patients.

Background: Patients with schizophrenia show abnormal spontaneous oscillatory activity in scalp-level electroencephalographic (EEG) responses across multiple frequency bands. While oscillations play an essential role in the transmission of information across neural networks, few studies have assessed the frequency-specific dynamics across cortical source networks at rest. Identification of the neural sources and their dynamic interactions may improve our understanding of core pathophysiologic abnormalities associated with the neuropsychiatric disorders. Methods: A novel multivector autoregressive modeling approach for assessing effective connectivity among cortical sources was developed and applied to resting-state EEG recordings obtained from n = 139 schizophrenia patients and n = 126 healthy comparison subjects. Results: Two primary abnormalities in resting-state networks were detected in schizophrenia patients. The first network involved the middle frontal and fusiform gyri and a region near the calcarine sulcus. The second network involved the cingulate gyrus and the Rolandic operculum (a region that includes the auditory cortex). Conclusions: Schizophrenia patients show widespread patterns of hyper-connectivity across a distributed network of the frontal, temporal, and occipital brain regions. Results highlight a novel approach for characterizing alterations in connectivity in the neuropsychiatric patient populations. Further mechanistic characterization of network functioning is needed to clarify the pathophysiology of neuropsychiatric and neurological diseases

Abnormal Spontaneous Gamma Power Is Associated With Verbal Learning and Memory Dysfunction in Schizophrenia.

BackgroundSchizophrenia patients exhibit cognitive deficits across multiple domains, including verbal memory, working memory, and executive function, which substantially contribute to psychosocial disability. Gamma oscillations are associated with a wide range of cognitive operations, and are important for cortico-cortical transmission and the integration of information across neural networks. While previous reports have shown that schizophrenia patients have selective impairments in the ability to support gamma oscillations in response to 40-Hz auditory stimulation, it is unclear if patients show abnormalities in gamma power at rest, or whether resting-state activity in other frequency bands is associated with cognitive functioning in schizophrenia patients.MethodsResting-state electroencephalogram (EEG) was assessed over 3 min in 145 healthy comparison subjects and 157 schizophrenia patients. Single-word reading ability was measured via the reading subtest of the Wide Range Achievement Test-3 (WRAT). Auditory attention and working memory were evaluated using Letter-Number Span and Letter-Number Sequencing. Executive function was assessed via perseverative responses on the Wisconsin Card Sorting Test (WCST). Verbal learning performance was measured using the California Verbal Learning Test second edition (CVLT-II).ResultsSchizophrenia patients showed normal levels of delta-band power but abnormally elevated EEG power in theta, alpha, beta, and gamma bands. An exploratory correlation analysis showed a significant negative correlation of gamma-band power and verbal learning performance in schizophrenia patients.ConclusionsPatients with schizophrenia have abnormal resting-state EEG power across multiple frequency bands; gamma-band abnormalities were selectively and negatively associated with impairments in verbal learning. Resting-state gamma-band EEG power may be useful for understanding the pathophysiology of cognitive dysfunction and developing novel therapeutics in schizophrenia patients

Neurophysiologic Characterization of Resting State Connectivity Abnormalities in Schizophrenia Patients.

Background: Patients with schizophrenia show abnormal spontaneous oscillatory activity in scalp-level electroencephalographic (EEG) responses across multiple frequency bands. While oscillations play an essential role in the transmission of information across neural networks, few studies have assessed the frequency-specific dynamics across cortical source networks at rest. Identification of the neural sources and their dynamic interactions may improve our understanding of core pathophysiologic abnormalities associated with the neuropsychiatric disorders. Methods: A novel multivector autoregressive modeling approach for assessing effective connectivity among cortical sources was developed and applied to resting-state EEG recordings obtained from n = 139 schizophrenia patients and n = 126 healthy comparison subjects. Results: Two primary abnormalities in resting-state networks were detected in schizophrenia patients. The first network involved the middle frontal and fusiform gyri and a region near the calcarine sulcus. The second network involved the cingulate gyrus and the Rolandic operculum (a region that includes the auditory cortex). Conclusions: Schizophrenia patients show widespread patterns of hyper-connectivity across a distributed network of the frontal, temporal, and occipital brain regions. Results highlight a novel approach for characterizing alterations in connectivity in the neuropsychiatric patient populations. Further mechanistic characterization of network functioning is needed to clarify the pathophysiology of neuropsychiatric and neurological diseases