Despite hundreds of structural MRI studies documenting smaller brain volumes on average in schizophrenia compared to controls, little attention has been paid to group differences in the variability of brain volumes. Examination of variability may help interpret mean group differences in brain volumes and aid in better understanding the heterogeneity of schizophrenia. Variability in 246 MRI studies was meta-analyzed for 13 structures that have shown medium to large mean effect sizes (Cohen's d≥0.4): intracranial volume, total brain volume, lateral ventricles, third ventricle, total gray matter, frontal gray matter, prefrontal gray matter, temporal gray matter, superior temporal gyrus gray matter, planum temporale, hippocampus, fusiform gyrus, insula; and a control structure, caudate nucleus. No significant differences in variability in cortical/subcortical volumes were detected in schizophrenia relative to controls. In contrast, increased variability was found in schizophrenia compared to controls for intracranial and especially lateral and third ventricle volumes. These findings highlight the need for more attention to ventricles and detailed analyses of brain volume distributions to better elucidate the pathophysiology of schizophrenia.

Objective Clinical anxiety is prevalent, highly comorbid with other conditions, and associated with significant medical morbidity, disability, and public health burden. Excessive attentional deployment towards threat is a transdiagnostic dimension of anxiety seen at both initial and sustained stages of threat processing. However, group-level observations of these phenomena mask considerable within-group heterogeneity that has been linked to treatment outcomes, suggesting that a transdiagnostic, individual differences approach may capture critical, clinically relevant information. Methods 70 clinically anxious individuals were randomized to receive 8 sessions of Attention Bias Modification (ABM; n=41 included in analysis), a computer-based mechanistic intervention that specifically targets initial stages of threat processing, or a sham control (n=21). Participants completed a mixed block/event-related fMRI task optimized to discriminate transient from sustained neural responses to threat. Results Larger transient responses across a wide range of cognitive-affective regions (e.g., ventrolateral prefrontal cortex, anterior cingulate cortex, amygdala) predicted better clinical outcomes following ABM, in both a priori anatomical regions and whole-brain analyses; sustained responses did not. A spatial pattern recognition algorithm using transient threat responses successfully discriminated the top quartile of ABM responders with 68% accuracy. Conclusions Neural alterations occurring on the relatively transient timescale that is specifically targeted by ABM predict favorable clinical outcomes. Results inform how to expand on the initial promise of neurocognitive treatments like ABM by fine-tuning their clinical indications (e.g., through personalized mechanistic intervention relevant across diagnoses) and by increasing the range of mechanisms that can be targeted (e.g., through synergistic treatment combinations and/or novel neurocognitive training protocols designed to tackle identified predictors of nonresponse).

Objective:The authors sought to compare GABA levels in treated and untreated patients with psychosis with levels in their unaffected siblings and healthy control subjects, and to assess the effects of antipsychotic medications on GABA levels.Method: GABA+ levels (i.e., including signal from unrelated proteins or macromolecules) referenced to creatine or water were studied with J-edited proton spectroscopy in the dorsal anterior cingulate cortex of 289 individuals: 184 healthy control subjects, 83 treated patients with psychosis, 25 untreated patients, 31 unaffected siblings, and 17 patients studied both while off all medications and while on a single antipsychotic.Results: GABA+ levels in the dorsal anterior cingulate did not differ between untreated patients and healthy controls. For treated patients, levels were modestly lower for GABA+/ creatine but did not differ for GABA+/water compared with healthy controls. For both GABA+ measures, unaffected siblings had significantly lower levels compared with controls. GABA+/creatine showed a modest degree of familiality (intraclass correlation=0.36). Antipsychotic dosage was negatively correlated with GABA+ levels, but the on-off medication studies indicated no difference in GABA+ levels on antipsychotics compared with off antipsychotics.Conclusions: GABA+/creatine in the dorsal anterior cingulate may constitute an intermediate phenotype with low effect size for psychosis, but GABA+/water measures do not fully support this conclusion. Low GABA+ levels in unaffected siblings could suggest a genetic association, but the failure to find consistent evidence of this phenotype in the patients themselves weakens genetic inference on risk for psychosis. Replication in independent samples of siblings is warranted to confirm the potential genetic risk association.

Autism Spectrum Disorder (ASD) and schizophrenia are neurodevelopmental disorders which show substantial cognitive heterogeneity in adulthood, yet it remains unclear whether cognitive profiles may overlap across these diagnoses. Thus, the aim of this review was to summarize comparisons between ASD and schizophrenia on nonsocial cognition in adulthood. To minimize between-study heterogeneity in a relatively small literature, subtest scaled scores from the Wechsler Adult Intelligence Scale were compared between ASD (N=190) and schizophrenia (N=260) in six studies comprising a total of 450 participants. Meta-analyses of 11 subtests indicated that participants with ASD demonstrated significantly better performance than schizophrenia for visuospatial perception and reasoning and problem solving (Hedge's g=0.636), as well as visual attention and organization (g=0.433-0.475). Participants with ASD also demonstrated better performance than those with schizophrenia for working memory (g=0.334) and language (g=0.275), and generally comparable performance on processing speed and verbal comprehension. These findings were largely stable across age, sex, intelligence quotient (IQ), intellectual disability, scale version, and age-and sex-matching. Overall, ASD and schizophrenia showed striking differences in visuospatial perception and reasoning and problem solving, small differences in working memory and language, and substantial overlap in processing speed and verbal comprehension. These cognitive profiles were generally stable from adolescence to middle adulthood. To our knowledge, this is the first review to summarize comparisons of nonsocial cognition in verbal adults with ASD or schizophrenia. These findings are consistent with and substantially extend prior metaanalyses of case-control studies for ASD and schizophrenia (8, 9), which also suggest that, in comparison to neurotypical controls, ASD demonstrates smaller cognitive impairments than schizophrenia across most cognitive domains, particularly working

Schizophrenia has substantial variation in symptom severity, course of illness, and overall functioning. Earlier age of onset (AOO) is consistently associated with negative outcomes and yet the causes of this association are still unknown. We used a multiplex, extended pedigree design (total N = 771; 636 relatives from 43 multigenerational families with at least 2 relatives diagnosed with schizophrenia and 135 matched controls) to examine among the schizophrenia relatives (N = 103) the relationship between AOO and negative and positive symptom severity, cognition, and community functioning. Most importantly, we assessed whether there are shared genetic effects between AOO and negative symptoms, positive symptoms, cognition, and community functioning. As expected, earlier AOO was significantly correlated with increased severity of negative and positive symptoms and poorer cognition and community functioning among schizophrenia patients. Notably, the genetic correlation between AOO of schizophrenia and negative symptoms was significant (Rg = −1.00, p = .007). Although the genetic correlations between AOO and positive symptoms, cognition, and community functioning were estimated at maximum and in the predicted direction, they were not statistically significant. AOO of schizophrenia itself was modestly heritable, although not significant and negative symptoms, positive symptoms, and cognition were all strongly and significantly heritable. In sum, we replicated prior findings indicating that earlier AOO is associated with increased symptom severity and extended the literature by detecting shared genetic effects between AOO and negative symptoms, suggestive of pleiotropy.

Although cognition is one of the most important predictors of community functioning in schizophrenia, little is known about the causes of this correlation. To our knowledge, this study is the first to examine the extent to which this correlation is genetically mediated and whether the genetic correlation is specific to schizophrenia. Six hundred thirty-six participants from 43 multigenerational families with at least two relatives with schizophrenia and 135 unrelated controls underwent diagnostic interview and cognition and functioning assessment. Quantitative genetic analyses were conducted using maximum-likelihood variance decomposition methods implemented in SOLAR (Almasy & Blangero, 1998). Among patients with schizophrenia, cognition and community functioning were positively correlated and genetic effects shared between them were significant contributors to this relationship whereas environmental effects shared between them were not. In contrast, genetic effects were not shared significantly between cognition in depressed or nondiagnosed relatives and community functioning in schizophrenia. In all analyses, the contributions of social cognition to community functioning were accounted for by general cognition. These findings support heritable factors that contribute to the correlation between cognition and community functioning that are relatively specific to schizophrenia and are not significantly shared with depression or a lack of psychopathology. This suggests the possibility of identifying specific genetic variants that contribute to this correlation and to these important individual differences among schizophrenia patients. (PsycINFO Database Record

This study characterizes variability in the age at which autistic individuals attain key developmental milestones compared with siblings who do not have an autism diagnosis.

BackgroundAutism Spectrum Disorder (ASD) and schizophrenia are neurodevelopmental disorders which share substantial overlap in cognitive deficits during adulthood. However, treatment evaluation in ASD and treatment comparisons across ASD and schizophrenia are limited by a dearth of empirical work establishing the validity of a standard cognitive battery across ASD and schizophrenia. Promisingly, the MATRICS Consensus Cognitive Battery (MCCB) has been validated in schizophrenia and encompasses cognitive domains that are impacted in ASD. Thus, this study aimed to establish MCCB's generalizability from schizophrenia to ASD.MethodsCommunity-residing adults with schizophrenia (N = 100) and ASD (N = 113) underwent MCCB assessment. Using multigroup confirmatory factor analysis, MCCB's transdiagnostic validity was evaluated by examining whether schizophrenia and ASD demonstrate the same configuration, magnitude, and directionality of relationships within and among measures and their underlying cognitive domains.ResultsAcross schizophrenia and ASD, the same subsets of MCCB measures inform three cognitive domains: processing speed, attention/working memory, and learning. Except for group means in category fluency, continuous performance, and spatial span, both groups show vastly comparable factor structures and characteristics.ConclusionsTo our knowledge, this study is the first to establish the validity of a standard cognitive battery in adults with ASD and furthermore the first to establish a cognitive battery's comparability across ASD and schizophrenia. Cognitive domain scores can be compared across new samples using weighted sums of MCCB scores resulting from this study. These findings highlight MCCB's applicability to ASD and support its utility for standardizing treatment evaluation of cognitive outcomes across the autism-schizophrenia spectrum.