Developmental trajectories of premorbid functioning predict cognitive remediation treatment response in first-episode schizophrenia.

BACKGROUND: Cognitive development after schizophrenia onset can be shaped by interventions such as cognitive remediation, yet no study to date has investigated whether patterns of early behavioral development may predict later cognitive changes following intervention. We therefore investigated the extent to which premorbid adjustment trajectories predict cognitive remediation gains in schizophrenia. METHODS: In a total sample of 215 participants (170 first-episode schizophrenia participants and 45 controls), we classified premorbid functioning trajectories from childhood through late adolescence using the Cannon-Spoor Premorbid Adjustment Scale. For the 62 schizophrenia participants who underwent 6 months of computer-assisted, bottom-up cognitive remediation interventions, we identified MATRICS Consensus Cognitive Battery scores for which participants demonstrated mean changes after intervention, then evaluated whether developmental trajectories predicted these changes. RESULTS: Growth mixture models supported three premorbid functioning trajectories: stable-good, deteriorating, and stable-poor adjustment. Schizophrenia participants demonstrated significant cognitive remediation gains in processing speed, verbal learning, and overall cognition. Notably, participants with stable-poor trajectories demonstrated significantly greater improvements in processing speed compared to participants with deteriorating trajectories. CONCLUSIONS: This is the first study to our knowledge to characterize the associations between premorbid functioning trajectories and cognitive remediation gains after schizophrenia onset, indicating that 6 months of bottom-up cognitive remediation appears to be sufficient to yield a full standard deviation gain in processing speed for individuals with early, enduring functioning difficulties. Our findings highlight the connection between trajectories of premorbid and postmorbid functioning in schizophrenia and emphasize the utility of considering the lifespan developmental course in personalizing therapeutic interventions.

Developmental Variability in Autism Across 17 000 Autistic Individuals and 4000 Siblings Without an Autism Diagnosis: Comparisons by Cohort, Intellectual Disability, Genetic Etiology, and Age at Diagnosis.

Importance: Presence of developmental delays in autism is well established, yet few studies have characterized variability in developmental milestone attainment in this population. Objective: To characterize variability in the age at which autistic individuals attain key developmental milestones based on co-occurring intellectual disability (ID), presence of a rare disruptive genetic variant associated with neurodevelopmental disorders (NDD), age at autism diagnosis, and research cohort membership. Design: The study team harmonized data from 4 cross-sectional autism cohorts: the Autism Genetics Research Exchange (n = 3284; 1997-2015), The Autism Simplex Collection (n = 694; 2008-2011), the Simons Simplex Collection (n = 2753; 2008-2011), and the Simons Foundation Powering Autism Research for Knowledge (n = 10 367; 2016-present). The last sample further included 4145 siblings without an autism diagnosis or ID. Participants: Convenience sample of 21 243 autistic individuals or their siblings without an autism diagnosis aged 4 to 17 years. Main Outcomes and Measures: Parents reported ages at which participants attained key milestones including smiling, sitting upright, crawling, walking, spoon-feeding self, speaking words, speaking phrases, and acquiring bladder and bowel control. A total of 5295 autistic individuals, and their biological parents, were genetically characterized to identify de novo variants in NDD-associated genes. The study team conducted time-to-event analyses to estimate and compare percentiles in time with milestone attainment across autistic individuals, subgroups of autistic individuals, and the sibling sample. Results: Seventeen thousand ninety-eight autistic individuals (mean age, 9.15 years; 80.8% male) compared with 4145 siblings without autism or ID (mean age, 10.2 years; 50.2% female) showed delays in milestone attainment, with median (IQR) delays ranging from 0.7 (0.3-1.6) to 19.7 (11.4-32.2) months. More severe and more variable delays in autism were associated with the presence of co-occurring ID, carrying an NDD-associated rare genetic variant, and being diagnosed with autism by age 5 years. More severe and more variable delays were also associated with membership in earlier study cohorts, consistent with autism's diagnostic and ascertainment expansion over the last 30 years. Conclusions and Relevance: As the largest summary to date of developmental milestone attainment in autism, to our knowledge, this study demonstrates substantial developmental variability across different conditions and provides important context for understanding the phenotypic and etiological heterogeneity of autism.

Age-dependent effects of schizophrenia genetic risk on cortical thickness and cortical surface area: Evaluating evidence for neurodevelopmental and neurodegenerative models of schizophrenia.

Risk for schizophrenia peaks during early adulthood, a critical period for brain development. Although several influential theoretical models have been proposed for the developmental relationship between brain pathology and clinical onset, to our knowledge, no study has directly evaluated the predictions of these models for schizophrenia developmental genetic effects on brain structure. To address this question, we introduce a framework to estimate the effects of schizophrenia genetic variation on brain structure phenotypes across the life span. Five-hundred and six participants, including 30 schizophrenia probands, 200 of their relatives (aged 12-85 years) from 32 families with at least two first-degree schizophrenia relatives, and 276 unrelated controls, underwent MRI to assess regional cortical thickness (CT) and cortical surface area (CSA). Genetic variance decomposition analyses were conducted to distinguish among schizophrenia neurogenetic effects that are most salient before schizophrenia peak age-of-risk (i.e., early neurodevelopmental effects), after peak age-of-risk (late neurodevelopmental effects), and during the later plateau of age-of-risk (neurodegenerative effects). Genetic correlations between schizophrenia and cortical traits suggested early neurodevelopmental effects for frontal and insula CSA, late neurodevelopmental effects for overall CSA and frontal, parietal, and occipital CSA, and possible neurodegenerative effects for temporal CT and parietal CSA. Importantly, these developmental neurogenetic effects were specific to schizophrenia and not found with nonpsychotic depression. Our findings highlight the potentially dynamic nature of schizophrenia genetic effects across the lifespan and emphasize the utility of integrating neuroimaging methods with developmental behavior genetic approaches to elucidate the nature and timing of risk-conferring processes in psychopathology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Age-dependent patterns of schizophrenia genetic risk affect cognition.

Cognition shares substantial genetic overlap with schizophrenia, yet it remains unclear whether such genetic effects become significant during developmental periods of elevated risk for schizophrenia, such as the peak age of onset. We introduce an investigative framework integrating epidemiological, developmental, and genetic approaches to determine whether genetic effects shared between schizophrenia and cognition are significant across periods of differing risk for schizophrenia onset, and whether these effects are shared with depression. 771 European-American participants, including 636 (ages 15-84 years) from families with at least two first-degree relatives with schizophrenia and 135 unrelated controls, were divided into three age-risk groups based on ages relative to epidemiological age of onset patterns for schizophrenia: Pre-Peak (before peak age-of-onset: 15 to 22 years), Post-Peak (after peak age-of-onset: 23-42 years), and Plateau (during plateau of age-of-onset: over 42 years). For general cognition and 11 specific cognitive traits, we estimated genetic correlations with schizophrenia and with depression within each age-risk group. Genetic effects shared between deficits in general cognition and schizophrenia were nonsignificant before peak age of onset, yet were high and significant after peak age of onset and during the plateau of onset. These age-dependent genetic effects were largely consistent across specific cognitive traits and not transdiagnostically shared with depression. Schizophrenia genetic effects appear to influence cognitive traits in an age-dependent manner, supporting late developmental and perhaps neurodegenerative models that hypothesize increased expression of schizophrenia risk genes during and after the peak age of risk. Our findings underscore the utility of cognitive traits for tracking schizophrenia genetic effects across the lifespan.

Why does age of onset predict clinical severity in schizophrenia? A multiplex extended pedigree study.

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.

Meta-Analysis of Cognitive Performance in Neurodevelopmental Disorders during Adulthood: Comparisons between Autism Spectrum Disorder and Schizophrenia on the Wechsler Adult Intelligence Scales.

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 meta-analyses 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 memory, visuospatial learning/memory, and language. Our findings therefore highlight the importance of comparing cognition transdiagnostically to inform the etiologies of these neurodevelopmental disorders and to refine shared and unique targets for remediating cognition.

Transdiagnostic validity of the MATRICS Consensus Cognitive Battery across the autism-schizophrenia spectrum.

BACKGROUND: Autism 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. METHODS: Community-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. RESULTS: Across 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. CONCLUSIONS: To 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.

Establishing a standard emotion processing battery for treatment evaluation in adults with autism spectrum disorder: Evidence supporting the Mayer-Salovey-Caruso Emotion Intelligence Test (MSCEIT).

Autism spectrum disorder (ASD) and schizophrenia are neurodevelopmental disorders which show markedly similar deficits in emotion processing, yet treatment evaluation in ASD and treatment comparisons across ASD and schizophrenia are constrained by a lack of empirical work validating a standard emotion processing battery across ASD and schizophrenia. Encouragingly, the Mayer-Salovey-Caruso Emotion Intelligence Test, version 2.0 (MSCEIT (Mayer et al., 2003) spans the range of emotion processing deficits in schizophrenia and ASD. This study therefore aimed to establish MSCEIT's factorial, measurement, and structural invariance in community-residing adults with schizophrenia (N = 103) and ASD (N = 113) using multigroup confirmatory factor analysis. Consistent with prior studies in normative populations, a two-factor structure comprised of emotional experiencing and emotional reasoning was supported in ASD and schizophrenia. Both groups operationalize MSCEIT measures similarly, with all measures except for Facilitation and Management showing comparability across groups. To our knowledge, this study is not only the first to establish the measurement and structural invariance of a standard emotion perception battery in adults with ASD, it is also the first to establish its comparability across ASD and schizophrenia. Ultimately, these findings underscore MSCEIT's utility for standardizing treatment evaluation of social cognitive outcomes across the autism-schizophrenia spectrum.

Variation in fourteen brain structure volumes in schizophrenia: A comprehensive meta-analysis of 246 studies.

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.

Effects of peer social interaction on performance during computerized cognitive remediation therapy in patients with early course schizophrenia: A pilot study.

BACKGROUND: Recent studies show that computer-based training enhances cognition in schizophrenia; furthermore, socialization has also been found to improve cognitive functions. It is generally believed that non-social cognitive remediation using computer exercises would be a pre-requisite for therapeutic benefits from social cognitive training. However, it is also possible that social interaction by itself enhances non-social cognitive functions; this possibility has scarcely been explored in schizophrenia patients. This pilot study examined the effects of computer-based neurocognitive training, along with social interaction either with a peer (PSI) or without one (N-PSI). We hypothesized that PSI will enhance cognitive performance during computerized exercises in schizophrenia, as compared with N-PSI. METHODS: Sixteen adult participants diagnosed with schizophrenia or schizoaffective disorder participating in an ongoing trial of Cognitive Enhancement Therapy completed several computerized neurocognitive remediation training sessions (the Orientation Remedial Module©, or ORM), either with a peer or without a peer. RESULTS: We observed a significant interaction between the effect of PSI and performance on the different cognitive exercises (p<0.05). More precisely, when patients performed the session with PSI, they demonstrated better cognitive performances than with N-PSI in the ORM exercise that provides training in processing speed, alertness, and reaction time (the standard Attention Reaction Conditioner, or ARC) (p<0.01, corrected). PSI did not significantly affect other cognitive domains such as target detection and spatial attention. CONCLUSION: Our findings suggest that PSI could improve cognitive performance, such as processing speed, during computerized cognitive training in schizophrenia. Additional studies investigating the effect of PSI during cognitive remediation are needed to further evaluate this hypothesis.

Towards personalized, brain-based behavioral intervention for transdiagnostic anxiety: Transient neural responses to negative images predict outcomes following a targeted computer-based intervention.

OBJECTIVE: Clinical anxiety is prevalent, highly comorbid with other conditions, and associated with significant medical morbidity, disability, and public health burden. Excessive attentional deployment toward 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. METHOD: Seventy 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 functional MRI 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). (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Cognition and community functioning in schizophrenia: The nature of the relationship.

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

Bias in favour of self-selected hypotheses is associated with delusion severity in schizophrenia.

INTRODUCTION: Delusions are typically characterised by idiosyncratic, self-generated explanations used to interpret events, as opposed to the culturally normative interpretations. Thus, a bias in favour of one's own hypotheses may be a fundamental aspect of delusions. METHODS: We tested this possibility in the current study by comparing judgements of self-selected hypotheses to judgements of externally selected ones in a probabilistic reasoning task. This allowed us to equate self- and externally selected hypotheses in terms of objectively quantifiable supporting evidence. It is normal to be biased in favour of self-selected hypotheses, but we expected this bias to be exacerbated in schizophrenia patients relative to healthy and psychiatric controls, and to be correlated with the severity of delusions in the schizophrenia sample. RESULTS: As expected, all groups showed the self-selection bias. Although this bias was not increased in schizophrenia patients relative to the control groups, it was significantly correlated with the severity of delusions in the schizophrenia sample. CONCLUSIONS: These results fit with an account holding that the hypersalience of an individual's own interpretations of events, relative to culturally normative interpretations, may manifest in a self-selection bias, contributing to the delusional state in schizophrenia.