Remote assessment of the Penn computerised neurocognitive battery in individuals with 22q11.2 deletion syndrome.

BACKGROUND: Neurocognitive functioning is an integral phenotype of 22q11.2 deletion syndrome relating to severity of psychopathology and outcomes. A neurocognitive battery that could be administered remotely to assess multiple cognitive domains would be especially beneficial to research on rare genetic variants, where in-person assessment can be unavailable or burdensome. The current study compares in-person and remote assessments of the Penn computerised neurocognitive battery (CNB). METHODS: Participants (mean age = 17.82, SD = 6.94 years; 48% female) completed the CNB either in-person at a laboratory (n = 222) or remotely (n = 162). RESULTS: Results show that accuracy of CNB performance was equivalent across the two testing locations, while slight differences in speed were detected in 3 of the 11 tasks. CONCLUSIONS: These findings suggest that the CNB can be used in remote settings to assess multiple neurocognitive domains.

Heritable anisotropy associated with cognitive impairments among patients with schizophrenia and their non-psychotic relatives in multiplex families.

BACKGROUND: To test the functional implications of impaired white matter (WM) connectivity among patients with schizophrenia and their relatives, we examined the heritability of fractional anisotropy (FA) measured on diffusion tensor imaging data acquired in Pittsburgh and Philadelphia, and its association with cognitive performance in a unique sample of 175 multigenerational non-psychotic relatives of 23 multiplex schizophrenia families and 240 unrelated controls (total = 438). METHODS: We examined polygenic inheritance (h2r) of FA in 24 WM tracts bilaterally, and also pleiotropy to test whether heritability of FA in multiple WM tracts is secondary to genetic correlation among tracts using the Sequential Oligogenic Linkage Analysis Routines. Partial correlation tests examined the correlation of FA with performance on eight cognitive domains on the Penn Computerized Neurocognitive Battery, controlling for age, sex, site and mother's education, followed by multiple comparison corrections. RESULTS: Significant total additive genetic heritability of FA was observed in all three-categories of WM tracts (association, commissural and projection fibers), in total 33/48 tracts. There were significant genetic correlations in 40% of tracts. Diagnostic group main effects were observed only in tracts with significantly heritable FA. Correlation of FA with neurocognitive impairments was observed mainly in heritable tracts. CONCLUSIONS: Our data show significant heritability of all three-types of tracts among relatives of schizophrenia. Significant heritability of FA of multiple tracts was not entirely due to genetic correlations among the tracts. Diagnostic group main effect and correlation with neurocognitive performance were mainly restricted to tracts with heritable FA suggesting shared genetic effects on these traits.

Association among income loss, financial strain and depressive symptoms during COVID-19: evidence from two longitudinal studies.

BACKGROUND: The COVID-19 pandemic has major ramifications for global health and the economy, with growing concerns about economic recession and implications for mental health. Here we investigated the associations between COVID-19 pandemic-related income loss with financial strain and mental health trajectories over a 1-month course. METHODS: Two independent studies were conducted in the U.S and in Israel at the beginning of the outbreak (March-April 2020, T1; N = 4 171) and at a 1-month follow-up (T2; N = 1 559). Mixed-effects models were applied to assess associations among COVID-19-related income loss, financial strain, and pandemic-related worries about health, with anxiety and depression, controlling for multiple covariates including pre-COVID-19 income. FINDINGS: In both studies, income loss and financial strain were associated with greater depressive symptoms at T1, above and beyond T1 anxiety, worries about health, and pre-COVID-19 income. Worsening of income loss was associated with exacerbation of depression at T2 in both studies. Worsening of subjective financial strain was associated with exacerbation of depression at T2 in one study (US). INTERPRETATION: Income loss and financial strain were uniquely associated with depressive symptoms and the exacerbation of symptoms over time, above and beyond pandemic-related anxiety. Considering the painful dilemma of lockdown versus reopening, with the tradeoff between public health and economic wellbeing, our findings provide evidence that the economic impact of COVID-19 has negative implications for mental health. FUNDING: This study was supported by grants from the National Institute of Mental Health, the US-Israel Binational Science Foundation, Foundation Dora and Kirsh Foundation.

Intensity warping for multisite MRI harmonization.

In multisite neuroimaging studies there is often unwanted technical variation across scanners and sites. These "scanner effects" can hinder detection of biological features of interest, produce inconsistent results, and lead to spurious associations. We propose mica (multisite image harmonization by cumulative distribution function alignment), a tool to harmonize images taken on different scanners by identifying and removing within-subject scanner effects. Our goals in the present study were to (1) establish a method that removes scanner effects by leveraging multiple scans collected on the same subject, and, building on this, (2) develop a technique to quantify scanner effects in large multisite studies so these can be reduced as a preprocessing step. We illustrate scanner effects in a brain MRI study in which the same subject was measured twice on seven scanners, and assess our method's performance in a second study in which ten subjects were scanned on two machines. We found that unharmonized images were highly variable across site and scanner type, and our method effectively removed this variability by aligning intensity distributions. We further studied the ability to predict image harmonization results for a scan taken on an existing subject at a new site using cross-validation.

Genetics of schizophrenia in the South African Xhosa.

Africa, the ancestral home of all modern humans, is the most informative continent for understanding the human genome and its contribution to complex disease. To better understand the genetics of schizophrenia, we studied the illness in the Xhosa population of South Africa, recruiting 909 cases and 917 age-, gender-, and residence-matched controls. Individuals with schizophrenia were significantly more likely than controls to harbor private, severely damaging mutations in genes that are critical to synaptic function, including neural circuitry mediated by the neurotransmitters glutamine, γ-aminobutyric acid, and dopamine. Schizophrenia is genetically highly heterogeneous, involving severe ultrarare mutations in genes that are critical to synaptic plasticity. The depth of genetic variation in Africa revealed this relationship with a moderate sample size and informed our understanding of the genetics of schizophrenia worldwide.

Deviation from expected cognitive ability is a core cognitive feature of schizophrenia related to neurophysiologic, clinical and psychosocial functioning.

Cognitive functioning in schizophrenia is characterized by a generalized impairment in current cognitive ability based on traditional population-based norms. However, these norms assume a normal cognitive trajectory and do not directly account for illness-related declines from expected cognitive potential. Indeed, schizophrenia patients exhibit even greater deviation between their observed and expected cognitive functioning based on expanded norms that leverage premorbid variables resistant to illness-related features. The current study further quantified the extent to which illness-related features account for this deviation from expectation and assessed its relationship to neurophysiologic (mismatch negativity, P3a, theta oscillations), clinical, and psychosocial functioning in schizophrenia patients. Expected cognitive ability (PENN-CNB global cognition) in patients (n = 684) was calculated using healthy comparison subject (n = 660) weighted regression based on premorbid variables resistant to illness-related decline (demographics, single-word reading, parental education). The magnitude of any deviation between current (observed) and regression-predicted (expected) cognitive ability was calculated. Results indicated that 24% (n = 164) of the total patient population exhibited significant (≥-1.96 SD) deviation between observed and expected global cognitive ability. Interestingly, 20% of the total patient population (n = 136) had "normal" range cognitive performance when using traditional population-based norms, but also had significant deviation from expected cognitive ability. The magnitude of this deviation was associated with more severe neurophysiologic abnormalities, longer illness duration, higher levels of negative symptoms, and worse psychosocial functioning. Assessment of cognitive deviation is thus a complementary metric for characterizing the severity of illness-related cognitive declines in patients, while also reflecting the expression and severity of key endophenotypes of schizophrenia.

Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group.

The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.

Prefrontal cortical thinning links to negative symptoms in schizophrenia via the ENIGMA consortium.

BACKGROUND: Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity. METHODS: This study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores). RESULTS: Meta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (ß std = -0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged. CONCLUSIONS: Using an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.

Common and dissociable regional cerebral blood flow differences associate with dimensions of psychopathology across categorical diagnoses.

The high comorbidity among neuropsychiatric disorders suggests a possible common neurobiological phenotype. Resting-state regional cerebral blood flow (CBF) can be measured noninvasively with magnetic resonance imaging (MRI) and abnormalities in regional CBF are present in many neuropsychiatric disorders. Regional CBF may also provide a useful biological marker across different types of psychopathology. To investigate CBF changes common across psychiatric disorders, we capitalized upon a sample of 1042 youths (ages 11-23 years) who completed cross-sectional imaging as part of the Philadelphia Neurodevelopmental Cohort. CBF at rest was quantified on a voxelwise basis using arterial spin labeled perfusion MRI at 3T. A dimensional measure of psychopathology was constructed using a bifactor model of item-level data from a psychiatric screening interview, which delineated four factors (fear, anxious-misery, psychosis and behavioral symptoms) plus a general factor: overall psychopathology. Overall psychopathology was associated with elevated perfusion in several regions including the right dorsal anterior cingulate cortex (ACC) and left rostral ACC. Furthermore, several clusters were associated with specific dimensions of psychopathology. Psychosis symptoms were related to reduced perfusion in the left frontal operculum and insula, whereas fear symptoms were associated with less perfusion in the right occipital/fusiform gyrus and left subgenual ACC. Follow-up functional connectivity analyses using resting-state functional MRI collected in the same participants revealed that overall psychopathology was associated with decreased connectivity between the dorsal ACC and bilateral caudate. Together, the results of this study demonstrate common and dissociable CBF abnormalities across neuropsychiatric disorders in youth.

Emergent, remitted and persistent psychosis-spectrum symptoms in 22q11.2 deletion syndrome.

Individuals with 22q11.2 deletion syndrome (22q11DS) are at markedly elevated risk for schizophrenia-related disorders. Stability, emergence, remission and persistence of psychosis-spectrum symptoms were investigated longitudinally. Demographic, clinical and cognitive predictors of psychosis were assessed. Prospective follow-up over 2.8 years was undertaken in 75 individuals with 22q11DS aged 8-35 years. Mood, anxiety, attention-deficit hyperactivity disorders and psychosis-spectrum symptoms were assessed with the Kiddie-Schedule for Affective Disorders and Schizophrenia and Scale of Prodromal Symptoms (SOPS). Four domains of cognition were evaluated with the Penn Computerized Neurocognitive Battery (executive functioning, memory, complex cognition and social cognition). Psychotic disorder or clinically significant SOPS-positive ratings were consistently absent in 35%, emergent in 13%, remitted in 22% and persistent in 31% of participants. Negative symptoms and functional impairment were found to be predictive of the emergence of positive psychosis-spectrum symptoms and to reflect ongoing deficits after remission of positive symptoms. Dysphoric mood and anxiety were predictive of emergent and persistent-positive psychosis-spectrum symptoms. Lower baseline global cognition and greater global cognitive decline were predictive of psychosis-spectrum outcomes but no particular cognitive domain stood out as being significantly more discriminating than others. Our findings suggest that negative symptoms, functioning and dysphoric mood are important predictors of psychosis risk in this population.

Positive symptoms associate with cortical thinning in the superior temporal gyrus via the ENIGMA Schizophrenia consortium.

OBJECTIVE: Based on the role of the superior temporal gyrus (STG) in auditory processing, language comprehension and self-monitoring, this study aimed to investigate the relationship between STG cortical thickness and positive symptom severity in schizophrenia. METHOD: This prospective meta-analysis includes data from 1987 individuals with schizophrenia collected at seventeen centres around the world that contribute to the ENIGMA Schizophrenia Working Group. STG thickness measures were extracted from T1-weighted brain scans using FreeSurfer. The study performed a meta-analysis of effect sizes across sites generated by a model predicting left or right STG thickness with a positive symptom severity score (harmonized SAPS or PANSS-positive scores), while controlling for age, sex and site. Secondary models investigated relationships between antipsychotic medication, duration of illness, overall illness severity, handedness and STG thickness. RESULTS: Positive symptom severity was negatively related to STG thickness in both hemispheres (left: ßstd = -0.052; P = 0.021; right: ßstd = -0.073; P = 0.001) when statistically controlling for age, sex and site. This effect remained stable in models including duration of illness, antipsychotic medication or handedness. CONCLUSION: Our findings further underline the important role of the STG in hallmark symptoms in schizophrenia. These findings can assist in advancing insight into symptom-relevant pathophysiological mechanisms in schizophrenia.

Glutamate imaging (GluCEST) reveals lower brain GluCEST contrast in patients on the psychosis spectrum.

Psychosis commonly develops in adolescence or early adulthood. Youths at clinical high risk (CHR) for psychosis exhibit similar, subtle symptoms to those with schizophrenia (SZ). Malfunctioning neurotransmitter systems, such as glutamate, are implicated in the disease progression of psychosis. Yet, in vivo imaging techniques for measuring glutamate across the cortex are limited. Here, we use a novel 7 Tesla MRI glutamate imaging technique (GluCEST) to estimate changes in glutamate levels across cortical and subcortical regions in young healthy individuals and ones on the psychosis spectrum. Individuals on the psychosis spectrum (PS; n=19) and healthy young individuals (HC; n=17) underwent MRI imaging at 3 and 7 T. At 7 T, a single slice GluCEST technique was used to estimate in vivo glutamate. GluCEST contrast was compared within and across the subcortex, frontal, parietal and occipital lobes. Subcortical (χ2 (1)=4.65, P=0.031) and lobular (χ2 (1)=5.17, P=0.023) GluCEST contrast levels were lower in PS compared with HC. Abnormal GluCEST contrast levels were evident in both CHR (n=14) and SZ (n=5) subjects, and correlated differentially, across regions, with clinical symptoms. Our findings describe a pattern of abnormal brain neurochemistry early in the course of psychosis. Specifically, CHR and young SZ exhibit diffuse abnormalities in GluCEST contrast attributable to a major contribution from glutamate. We suggest that neurochemical profiles of GluCEST contrast across cortex and subcortex may be considered markers of early psychosis. GluCEST methodology thus shows promise to further elucidate the progression of the psychosis disease state.

sGraSP: A graph-based method for the derivation of subject-specific functional parcellations of the brain.

BACKGROUND: Resting-state fMRI (rs-fMRI) has emerged as a prominent tool for the study of functional connectivity. The identification of the regions associated with the different brain functions has received significant interest. However, most of the studies conducted so far have focused on the definition of a common set of regions, valid for an entire population. The variation of the functional regions within a population has rarely been accounted for. NEW METHOD: In this paper, we propose sGraSP, a graph-based approach for the derivation of subject-specific functional parcellations. Our method generates first a common parcellation for an entire population, which is then adapted to each subject individually. RESULTS: Several cortical parcellations were generated for 859 children being part of the Philadelphia Neurodevelopmental Cohort. The stability of the parcellations generated by sGraSP was tested by mixing population and subject rs-fMRI signals, to generate subject-specific parcels increasingly closer to the population parcellation. We also checked if the parcels generated by our method were better capturing a development trend underlying our data than the original parcels, defined for the entire population. COMPARISON WITH EXISTING METHODS: We compared sGraSP with a simpler and faster approach based on a Voronoi tessellation, by measuring their ability to produce functionally coherent parcels adapted to the subject data. CONCLUSIONS: Our parcellations outperformed the Voronoi tessellations. The parcels generated by sGraSP vary consistently with respect to signal mixing, the results are highly reproducible and the neurodevelopmental trend is better captured with the subject-specific parcellation, under all the signal mixing conditions.

Association between polygenic risk for schizophrenia, neurocognition and social cognition across development.

Breakthroughs in genomics have begun to unravel the genetic architecture of schizophrenia risk, providing methods for quantifying schizophrenia polygenic risk based on common genetic variants. Our objective in the current study was to understand the relationship between schizophrenia genetic risk variants and neurocognitive development in healthy individuals. We first used combined genomic and neurocognitive data from the Philadelphia Neurodevelopmental Cohort (4303 participants ages 8-21 years) to screen 26 neurocognitive phenotypes for their association with schizophrenia polygenic risk. Schizophrenia polygenic risk was estimated for each participant based on summary statistics from the most recent schizophrenia genome-wide association analysis (Psychiatric Genomics Consortium 2014). After correction for multiple comparisons, greater schizophrenia polygenic risk was significantly associated with reduced speed of emotion identification and verbal reasoning. These associations were significant by age 9 years and there was no evidence of interaction between schizophrenia polygenic risk and age on neurocognitive performance. We then looked at the association between schizophrenia polygenic risk and emotion identification speed in the Harvard/MGH Brain Genomics Superstruct Project sample (695 participants ages 18-35 years), where we replicated the association between schizophrenia polygenic risk and emotion identification speed. These analyses provide evidence for a replicable association between polygenic risk for schizophrenia and a specific aspect of social cognition. Our findings indicate that individual differences in genetic risk for schizophrenia are linked with the development of aspects of social cognition and potentially verbal reasoning, and that these associations emerge relatively early in development.

Characterizing social environment's association with neurocognition using census and crime data linked to the Philadelphia Neurodevelopmental Cohort.

BACKGROUND: The contribution of 'environment' has been investigated across diverse and multiple domains related to health. However, in the context of large-scale genomic studies the focus has been on obtaining individual-level endophenotypes with environment left for future decomposition. Geo-social research has indicated that environment-level variables can be reduced, and these composites can then be used with other variables as intuitive, precise representations of environment in research. METHOD: Using a large community sample (N = 9498) from the Philadelphia area, participant addresses were linked to 2010 census and crime data. These were then factor analyzed (exploratory factor analysis; EFA) to arrive at social and criminal dimensions of participants' environments. These were used to calculate environment-level scores, which were merged with individual-level variables. We estimated an exploratory multilevel structural equation model (MSEM) exploring associations among environment- and individual-level variables in diverse communities. RESULTS: The EFAs revealed that census data was best represented by two factors, one socioeconomic status and one household/language. Crime data was best represented by a single crime factor. The MSEM variables had good fit (e.g. comparative fit index = 0.98), and revealed that environment had the largest association with neurocognitive performance (ß = 0.41, p < 0.0005), followed by parent education (ß = 0.23, p < 0.0005). CONCLUSIONS: Environment-level variables can be combined to create factor scores or composites for use in larger statistical models. Our results are consistent with literature indicating that individual-level socio-demographic characteristics (e.g. race and gender) and aspects of familial social capital (e.g. parental education) have statistical relationships with neurocognitive performance.

Heritability and familiality of neurological soft signs: evidence from healthy twins, patients with schizophrenia and non-psychotic first-degree relatives.

BACKGROUND: Neurological soft signs (NSS) have long been considered potential endophenotypes for schizophrenia. However, few studies have investigated the heritability and familiality of NSS. The present study examined the heritability and familiality of NSS in healthy twins and patient-relative pairs. METHOD: The abridged version of the Cambridge Neurological Inventory was administered to 267 pairs of monozygotic twins, 124 pairs of dizygotic twins, and 75 pairs of patients with schizophrenia and their non-psychotic first-degree relatives. RESULTS: NSS were found to have moderate but significant heritability in the healthy twin sample. Moreover, patients with schizophrenia correlated closely with their first-degree relatives on NSS. CONCLUSIONS: Taken together, the findings provide evidence on the heritability and familiality of NSS in the Han Chinese population.

Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium.

The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.

Connectome-wide network analysis of youth with Psychosis-Spectrum symptoms.

Adults with psychotic disorders have dysconnectivity in critical brain networks, including the default mode (DM) and the cingulo-opercular (CO) networks. However, it is unknown whether such deficits are present in youth with less severe symptoms. We conducted a multivariate connectome-wide association study examining dysconnectivity with resting state functional magnetic resonance imaging in a population-based cohort of 188 youths aged 8-22 years with psychosis-spectrum (PS) symptoms and 204 typically developing (TD) comparators. We found evidence for multi-focal dysconnectivity in PS youths, implicating the bilateral anterior cingulate, frontal pole, medial temporal lobe, opercular cortex and right orbitofrontal cortex. Follow-up seed-based and network-level analyses demonstrated that these results were driven by hyper-connectivity among DM regions and diminished connectivity among CO regions, as well as diminished coupling between frontal and DM regions. Collectively, these results provide novel evidence for functional dysconnectivity in PS youths, which show marked correspondence to abnormalities reported in adults with established psychotic disorders.

Emotion recognition deficits as predictors of transition in individuals at clinical high risk for schizophrenia: a neurodevelopmental perspective.

BACKGROUND: Schizophrenia is characterized by profound and disabling deficits in the ability to recognize emotion in facial expression and tone of voice. Although these deficits are well documented in established schizophrenia using recently validated tasks, their predictive utility in at-risk populations has not been formally evaluated. METHOD: The Penn Emotion Recognition and Discrimination tasks, and recently developed measures of auditory emotion recognition, were administered to 49 clinical high-risk subjects prospectively followed for 2 years for schizophrenia outcome, and 31 healthy controls, and a developmental cohort of 43 individuals aged 7-26 years. Deficit in emotion recognition in at-risk subjects was compared with deficit in established schizophrenia, and with normal neurocognitive growth curves from childhood to early adulthood. RESULTS: Deficits in emotion recognition significantly distinguished at-risk patients who transitioned to schizophrenia. By contrast, more general neurocognitive measures, such as attention vigilance or processing speed, were non-predictive. The best classification model for schizophrenia onset included both face emotion processing and negative symptoms, with accuracy of 96%, and area under the receiver-operating characteristic curve of 0.99. In a parallel developmental study, emotion recognition abilities were found to reach maturity prior to traditional age of risk for schizophrenia, suggesting they may serve as objective markers of early developmental insult. CONCLUSIONS: Profound deficits in emotion recognition exist in at-risk patients prior to schizophrenia onset. They may serve as an index of early developmental insult, and represent an effective target for early identification and remediation. Future studies investigating emotion recognition deficits at both mechanistic and predictive levels are strongly encouraged.