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Background Cognitive deficits are core symptoms of psychotic disorders like schizophrenia, responsible for more functional impairment and disability than classical symptoms like auditory or visual hallucinations. Yet quickly quantifying cognition remains a challenge, and even brief assessments often requires at least 30 minutes. Because of the inability to easily assess cognition - cognitive side effects of medications are rarely tracked, referrals for cognitive remediation therapy are rarely made, and accommodations for patients' specific cognitive deficits are rarely considered. Methods We define micro-cognitive measures (MCM) to be a multimodal stream of data that is variably composed of 1) smartphone metadata 2) smartphone digital phenotyping data, and 3) smartphone cognitive assessments. By smartphone metadata we refer to the ability to now automatically collect phone behaviors that are related to cognitive domains such as attention associated with phone checking behaviors, memory associated with recalling passwords, and specific patterns of speech associated with language. In this observational 3-month study with 30 participants with a confirmed diagnosis of schizophrenia, the Brief Assessment of Cognition (BACS) was administered before and after 90 days of capturing micro-cognitive measures via a smartphone app. Participants downloaded the app onto their personal smartphone and were promoted to take assessments of memory and attention 5 days per week for all weeks of the study. There was no compensation for app use. Results While our study is currently collecting ongoing data, results will be finalized by early 2019. To date participants in the study are completing ~60% of prompted assessments with the rate of engagement declining over the 90-day study duration. There have been no adverse reported events. Qualitative feedback from participants about the app has been positive. Conclusions It is feasible to collect micro-cognitive measures via smartphones in patients with schizophrenia. Understanding both the validity and reliability of these new measures will require continued careful research. [ABSTRACT FROM AUTHOR]

Background Evidence for age related brain white matter (WM) abnormalities in schizophrenia (SZ) has been observed using MRI, and interpreted by various studies as reflecting either developmental, maturational and/or degenerative pathology. Such conflicting findings, mostly due to lack of longitudinal data and statistical power, have hindered consensus on patterns and trajectories of brain dysfunction in SZ. 'Big Data' provides a new and powerful means to identify subtle abnormalities across the course of SZ. We have accumulated and processed, what we believe the biggest, to-date, sample of thoughtfully harmonized diffusion MRI (dMRI) cross sectional data, and performed the study aimed at comprehensively characterizing age-related WM changes (trajectories) through the course of SZ. Methods Our dMRI data comprises a total of 1092 participants, aged between 14 and 65. This includes 600 individuals with SZ at different illness stages (383 males, 217 females, age: 31.3+/- 12) and 492 healthy controls-HC (275 males, 217 females, age: 29.8+/-13), from 13 different sites. Preprocessing and dMRI data harmonization based on the rotation invariant spherical harmonics were used to remove the nonlinear scanner and sequence differences across sites. All harmonized data was registered to a common template. Fractional Anisotropy (FA) for Whole Brain (WB) and 14 individual WM regions of interest (ROIs) were computed using a probabilistic tractography atlas. We modeled FA changes over age by quadratic curves (the best fitted model: highest adjusted r^2) and fitted separately to SZ and HC. Peak age and upper and lower bounds of the model were estimated after 5000 bootstraps. FA% differences were modeled at each age between SZ and HC for WB and each ROI, while sex was treated as a confound. The effect sizes (Cohen's d) between SZ and HC were also computed at each age. Finally, WM pathologies (i.e. based on between-group differences) were clustered into three groups according to d occurring along trajectory using kmeans. Results In WB, FA was lower in SZ comparing to HC at each age, but the percentage differences as well as d varied significantly by age (range of %FA change = [1.5 7], d = [.5 1.8]). Also, WB peaks of FA differed between groups, observed at the age of 33 in HC, shifted to the age of 27 in SZ. Three groups emerged from examining the degree of WM pathology across the age trajectories in ROIs, characterized by: 1).3

Background While it is clear that social determinants of health impact those with schizophrenia and often may impair access to treatment or support - to date accurate reporting of how patients interact with their environments has been challenging. Utilizing digital phenotyping via smartphone apps, it is now possible to study the correlations between patients; real time location and symptoms as well as quantity the environments patients interact with on a minute by minute time scale. Methods Utilizing the open source Beiwe smartphone platform developed by Dr. Onnela at the Harvard School of Public Health and the open source LAMP smartphone platform developed by our group - we have to date captured smartphone data on location (GPS), sociability (anonymized call/text logs), physical activity (accelerometer), symptoms (phone surveys), and cognition (phone games) from 25 patents. Patients are asked to install these apps and then use them for 90 days. Using the ESRI ArcGIS 10.3 geospatial analysis platform, we are able to compare the locations of patients against a variety of U.S. census collected information including spaces that are considered 'environmental justice areas' where the government has raised concern about lack of access to public services, support, green spaces, and other factors. Results The amount of GPS data varies greatly by patient with a mean of 408,291 but standard deviation of 301,680. For results to date, the total time that patients with schizophrenia spent in environmental justice areas compared to non-environment justice area was 60% with a standard deviation with a standard deviation of 42.3%. With ongoing data collection, we expect the standard deviations will reduce. In examining psychotics symptoms that patients self-report to the smartphone apps, preliminary analysis suggests there is an association between environmental justice areas and more severe self-reported symptoms. Discussion Our results suggest that it is feasible to collect environmental and symptom data via smartphones in patients with schizophrenia. Our preliminary results that patients spend more time in environmental justice areas suggests that those with schizophrenia may have less access to spaces conducive to recovery. Further data collection and analysis from this work may offer quantification of the potential impact of the environment and produce the necessary data to lobby for specific change and improved services for those with schizophrenia. [ABSTRACT FROM AUTHOR]

Background Evidence shows that cognitive remediation therapy helps improve cognition in people with schizophrenia. Previous studies have demonstrated mild to moderate positive effects of cognitive remediation therapy, but often with a high attrition rate. Furthermore, the impact of cognitive remediation therapy on patients' lives following treatment completion remains unclear. Systematic exploration of patients' perspectives on cognitive remediation therapy will allow for better understanding of its impact and the factors influencing adherence to treatment. Methods This quantitative and qualitative descriptive study aimed to identify factors that influence patients' experiences going through a comprehensive cognitive remediation treatment called Cognitive Enhancement Therapy (CET). CET is designed to provide enriched cognitive experiences by combining individual therapy with neurocognitive training and skills group therapy. We recruited 9 patients who have completed CET (mean age: 26.8, 8 men) and we performed two semi-structured focus groups, as well as one individual interview. We assessed three inductive themes when analyzing responses: 1) Motivational factors, 2) Experiences with the CET program, and 3) Impacts of the treatment. All participants also answered questionnaires on their current life satisfaction and subjective impression on CET. Results Patients reported that family support and subjective feeling of improvement during CET were two motivational factors in choosing to attend and complete the treatment. The size and lighting of the room where treatment took place were also reported to influence motivation. When asked about their experiences with the CET program, participants mentioned that they liked learning and being challenged. Participants specifically raised the importance of learning strategies during the computerized exercises portion of the treatment, as well as the importance of receiving feedback overall. Every participant mentioned that carrying the CET educational binder reduced motivation and that it could be improved in the future. When asked about long-term impacts of the treatment, patients reported that CET improved focus and confidence, and helped facilitate successful peer interactions. Patients also mentioned that CET made them more confident to go back to school or apply for a job. All participants reported that CET helped them (a lot: 55.6%, a good amount: 44.4%), and the majority reported enjoying their participation in CET (a good amount: 55.6%, a lot: 33.3%). Most participants who completed CET reported high satisfaction with their current work/school situation (55.6%) but reported less satisfaction with their social life (66.7%). Discussion Patients' perspectives on CET can guide future cognitive remediation trials. Simple aspects such as the treatment setting or the quality of the educational materials can make a difference in patients' motivation and satisfaction. Our results highlight the importance of providing learning strategies and constant feedback to the patients during the course of the treatment. CET seems to improve patients' self-reported focus and helps them to achieve their professional and academic goals. Our findings also suggest that promoting family support could increase motivation to pursue and complete CET. Further work is needed to help improve patients' social lives after treatment. [ABSTRACT FROM AUTHOR]

Background Clinical high risk (CHR) for psychosis is a heterogeneous syndrome presenting with highly variable clinical symptoms and cognitive dysfunctions. This study investigated whether subtypes defined by clinical and cognitive features in the initial presentation in CHR might improve the prediction of psychosis. Methods From the ongoing ShangHai at Risk for Psychosis (SHARP) program, a total of 400 CHR subjects were enrolled in a prospective cohort study. Canonical correlation analysis (CCA) was applied to 289 CHR subjects with completed structured interviews for prodromal symptoms and MATRICS consensus cognitive battery tests at baseline, and at least 1-year follow-up. Canonical variates were generated by CCA and then used for hierarchical cluster analysis to produce subtypes. To test further the utility of 3 subtypes in predicting psychosis, Kaplan-Meyer survival curves were constructed from the 3 subtypes. Results CCA determined two linear combinations: 1) Negative symptom and functional deterioration-related cognitive features; and 2) Positive symptoms and emotional disorganization-related cognitive features. Cluster analysis revealed 3 subtypes defined by distinct and relatively homogeneous patterns along two dimensions, and comprising 14.2% (subtype-1, n=41), 37.4% (subtype-2, n=108), and 48.4% (subtype-3, n=140) of the sample, each with distinctive features of clinical and cognitive performance. Those with subtype-1, which is characterized by extensive negative symptoms and cognitive deficits, appear to have the highest risk for psychosis. The conversion risk for subtypes 1–3 are 39.0%, 11.1% and 18.6%, respectively. Discussion Our results define important subtypes within CHR syndromes that highlight clinical symptoms and cognitive features that transcend current diagnostic boundaries. The three different subtypes were associated with significant differences in their clinical and cognitive characteristics as well as in their risk of conversion to psychosis. [ABSTRACT FROM AUTHOR]

Background Electroconvulsive therapy (ECT) is a promising treatment option in Clozapine refractory schizophrenia patients. ECT is known to improve functional connectivity in default mode network (DMN) in depression. We studied the effect of ECT on resting state functional magnetic resonance imaging (rsfMRI) of patients with clozapine refractory/intolerant schizophrenia. Methods 50 patients [mean age 30.24 ± 10.14 yr, 21 (42%) females] with 48% clozapine refractory schizophrenia rest clozapine intolerant schizophrenia, posted for modified ECT were recruited. We performed clinical symptoms ratings (SAPS, SANS, CGI_SCH) and image acquisition (rsfMRI ~10-minute with eyes open, T1 MPRAGE) prior to and after 8th ECT. 27 healthy controls [mean age = 30.74 ± 7.93, 11 (42%) females] age, sex and years of education matched for cases, underwent imaging (rsfMRI, T1 MPRAGE) once. Results With 3-point improvement on CGI SCH severity scale defined as response, 64% responded, and with 50% improvement in SAPS scale defined as response, 76% responded over the course of ECT (average no of ECTs = 7.5 ± 1.2). The rsfMRI of 40 patients who co-operated for pre- and post-ECT MRI-scans were preprocessed using FSL v.5.0.10. We discarded 13 patients scans which had >=5mm movement. We extracted 25 group independent components out of 27 patients' scans using FSL MELODIC after correcting for motion and other physiological noise with FSL FIX. Dual regression analysis showed significant (TFCE corrected p<0.001) increase in connectivity between angular gyrus and ipsilateral dorsolateral prefrontal cortex (DLPFC) bilaterally following ECT none of which correlated with clinical scores. We found that DMN remains hypo connected in refractory schizophrenia, which was unaltered by ECT in comparison to healthy controls. Discussion Following ECT, we observed a strong increase in functional connectivity between angular gyrus and the ipsilateral DLPFC on both sides indicating improved connectivity in DMN and fronto-parietal network, however DMN remains hypo connected in comparison to healthy controls. [ABSTRACT FROM AUTHOR]

Background Deviation in level of intrinsic activity (IA; what some call "background brain state" or "resting state"), quantified from ongoing EEG/MEG, has been observed in psychosis. Neurophysiological models of psychosis have leaned on this physiological indicator as a possible core deviation. Translational models of IA deviations hold promise for identifying multiple distinct physiological mechanisms for psychosis manifestation. IA deviations may cause diminished signal-to-noise ratios, and contribute to, or at least set the stage for, psychosis-related problems like identifying stimulus salience. B-SNIP published a means for categorizing psychosis cases by neurobiological homology through use of multiple biomarkers (psychosis Biotypes) rather than by surface level clinical features. B-SNIP demonstrated the superiority of Biotypes versus DSM diagnoses for capturing neurobiological similarity through comparisons on multiple external validating measures (social functioning, measures of brain volume from structural magnetic resonance images, clinical diagnoses of the first-degree relatives, and biomarker features among clinically healthy first-degree relatives). Independent analyses since the initial publication have provided additional support for the usefulness of psychosis Biotypes, and the psychosis Biotypes have been replicated in an independent sample (B-SNIP2). In this presentation we interrogated B-SNIP1 data for whether there is evidence of differential IA patterns as a function of treatment with Clozapine (should be higher) versus Depakote (should be lower). Because Biotype-1 cases are defined by low intrinsic activity, Clozapine should bring them closer to healthy values and Depakote should take them farther from healthy values. Alternatively, because Biotype-2 cases are defined by high intrinsic activity, Clozapine should take them farther from healthy values and Depakote should take them closer to healthy values. Methods For this project, we analyzed ongoing neural activity from 64 EEG sensors during 150 intervals of 10 sec duration from over 1450 B-SNIP subjects. These data were from the inter-trial interval (ITI) of an auditory paired-stimuli task used in Biotypes construction (although the ITI data themselves were not used). Although the subjects were engaged in a task (the counting of the number of presented stimulus pairs), the data used here were not part of the task itself. Data were evaluated for single trial power (an estimate of strength of neural response on individual trials) as a function of frequency of neural oscillations (from 2–50 Hz) over the whole head. Data were then averaged over single trials to yield an estimate of the overall strength of nonspecific (unrelated to sensory processing) neural activity. Probands were also grouped by whether they were treated with either Clozapine or Depakote (but not both). Results When evaluated as a function of DSM psychosis diagnoses (schizophrenia, schizoaffective disorder, bipolar disorder), the 95% confidence intervals for all groups overlapped the healthy group means across all frequencies. When considered by psychosis Biotypes, however, differences were both obvious and statistically significant. In comparison to healthy persons, Biotype-2 probands (the most neurophysiologically activated subgroup based on previous analyses) were notably high on intrinsic neural activity, and Biotype-1 probands (the most cognitively and neurophysiologically compromised subgroup based on previous analysis) were notably low on intrinsic neural activity. Group separations on this metric were better than those obtained with the original intrinsic EEG measure used to construct psychosis Biotypes. Furthermore, Clozapine treatment was associated with higher intrinsic activity, which normalized Biotype-1 but worsened Biotype-2. Depakote treatment was associated with lower intrinsic activity, which normalized Biotype-2 but worsened Biotype-1. When these same biomarker outcomes were considered by DSM diagnoses, the results were less convincing. Conclusions Intrinsic neural activity, quantifiable in numerous ways is an effective metric for capturing a meaningful component of Biotype neurophysiology. This was true across a range of oscillatory frequencies for the probands. Biotypes subgrouping may provide a means for meaningful and clinically useful neuroscience-based predictions of treatment response in psychosis. [ABSTRACT FROM AUTHOR]

Background Evidence suggests that clinical phenomenology incompletely captures biologically meaningful differentiations in psychosis. The Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP) consortium has employed cognitive and neurophysiological measures to identify three biologically distinct Biotypes, agnostic to clinical features. Biotype 1, 2, and 3, have distinctive neurobiological characteristics: Biotype 1 cases have significant neurocognitive impairment, high numbers of clinically affected relatives, and poor psychosocial functioning. Biotype 2 cases have high neural reactivity and more modest but significant cognitive impairment. Biotype 3 cases have nearly normal cognition and neural reactivity and better psychosocial functioning. As brain white matter is altered in psychosis, we aimed to externally validate the Biotype model using free-water imaging - an advanced diffusion imaging technique to compare differences across Biotypes, as well as across clinical categorization. Methods Diffusion tensor imaging (DTI) data from 69 individuals with schizophrenia, 49 with schizoaffective disorder (SAD), 42 with psychotic bipolar disorder, and 51 healthy controls (HC) from the Baltimore and Hartford sites in the B-SNIP consortium were included. Diffusion within each voxel was modeled using two compartments: isotropic free-water compartment, and a tissue compartment. Measures obtained from this model are the free-water compartment fraction (FW), and the tissue-FA fraction (FAt). Using Tract-based spatial statistics, the ENIGMA-DTI protocols were run on FAt and FW maps. The average FAt and FW within 25 bilateral white matter regions of interest was extracted. A MANCOVA model was used to test for differences in FAt and FW between diagnostic groups and Biotype groups, with age and sex as covariates. Results A significant group effect for diagnosis was observed in the corpus callosum (CC) (p<0.05, partial eta squared=0.1), whereby those diagnosed with SAD showed lower FAt in CC compared to HC. Using Biotype classification, a significant group effect was also observed for the CC, whereby Biotype 1 showed lower FAt than HC and Biotype 3 (p<0.01, partial eta squared=.13). For FW, no significant group differences were observed for diagnosis. However, group differences for Biotype were observed in the CC, whereby Biotypes 1 and 2 showed elevated FW compared to Biotype 3 and HC (p<0.01, partial eta squared = 0.1). Discussion While significant diagnosis comparisons were observed between schizoaffective disorder and HC, larger effects were observed when using Biotype classification. Patients in Biotype 1 group not only showed significant FAt reductions in the CC compared to HC, but also compared to Biotype 3. This is expected as Biotype 1 individuals were shown to be most impaired with regards to the biomarker dimensions of cognitive control and sensorimotor reactivity, whereas Biotype 3 were more comparable to healthy controls. Finally, no differences were observed for FW when grouping by diagnosis, however, when grouping by Biotype, significant elevations were observed for Biotypes 1 and 2. Aligned with our previous studies, FW appears to be a marker of acute response to psychosis, where elevations in FW are observed in individuals who were actively psychotic during scanning. Since neuroinflammation is expected to alter the extracellular FW fraction, it's possible that neuroinflammatory processes are apparent in these Biotype groups. However, further validation is required. In conclusion, grouping psychosis patients by Biotype may be a more biologically parsimonious approach for parsing heterogeneity of the disorder. [ABSTRACT FROM AUTHOR]

Background Flat and inappropriate affect and emotional labiality are features of psychosis syndromes and could involve impairments in neural processing of emotional stimuli. Studies have reported abnormal electrophysiological (EEG) responses to emotional stimuli in schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar I disorder with psychosis (BDP). The Bipolar-Schizophrenia Network on Intermediate Phenotypes (BSNIP) has identified three psychosis Biotypes (abbreviated B1, B2 & B3) which display differing patterns of neural activity, but emotional processing has not been assessed in these groups. Methods 814 participants (HC = 197, SZ = 230, SAD = 212, BDP = 175; B1 = 198, B2 = 176, B3 = 243) from the 5-site BSNIP consortium viewed pleasant, neutral, and unpleasant scenes from the IAPS while EEG was recorded from 64 sensors. Using a spatial PCA, two components reduced EEG data to one waveform per component. Spatial components were weighted in the occipital and centroparietal scalp regions and accounted for 56% and 42% of the variance, respectively. Early, mid-latency, and late time bins of interest (80–140 ms, 200–400 ms, & 400–1000 ms) were identified by visual inspection. Data were averaged across bins for each spatial component, yielding 6 spatiotemporal measures. Mixed-design ANOVAs were calculated using DSM and Biotype as between-subjects variables and task as the within-subjects variable. Follow up Tukey tests were conducted as appropriate. Results There were no significant DSM by Biotype interactions for any component/time combination (F = 1.39, 1.40,.92, 1.27, 1.34, 1.08, all p >.05). There was a main effect of DSM for the centroparietal component during the early time bin (F = 5.82, p <.01), with significant differences from HC and BDP to SZ and SAD (all p <.05). There was also a significant DSM by task interaction at the late time bin of the centroparietal component (F = 2.60, p =.04), where response to emotional images distinguished HC from SZ (p =.02,.03). There were main effects of Biotype for the early time bin at both components (F = 6.33, 11.77, both p <.001), with significant differences from HC and B3 to B1 and B2 (all p <.01). The mid-latency time bin displayed main effects of Biotype and Biotype by task interactions for both components (main effects: F = 7.74, 5.66, interactions: F = 2.65, 5.50, all p <.05). For all stimulus types, B1 significantly differed from all other groups at the occipital component and from HC and B3 at the centroparietal component (all p <.05). There was also a Biotype by task interaction at the late time bin of the centroparietal component, with reactivity to neutral images differing between B1 and B3 (p =.04) and reactivity to emotional images differing between B2 and HC (p =.04,.03). Discussion Distinguishing patients by Biotype yielded new information regarding emotional scene perception in psychosis. Only one neural measure distinguished between DSM-defined groups and did not interact with emotional scene content. However, these same measures and other components of the neural emotional response presented a complex pattern of differences within psychosis Biotypes. Results indicate the most profound disruptions in scene processing are found in B1. B1 is also associated with reductions in amygdala volume, which could result in abnormal aversive and appetitive reactions captured by these scalp measures of the emotional response. This external measure of neural function provides novel evidence that psychosis Biotypes identified by the BSNIP consortium provide better separation between psychosis subtypes than current DSM categories. Future research will examine habituation to scenes, medication effects, subjective reports of emotional experience, and clinical and phenotypic correlates. [ABSTRACT FROM AUTHOR]

Background Schizophrenia is a chronic and disabling mental health condition. The early application of cognitive remediation interventions has provided some of the greatest hope of reducing long-term disability in the condition. Cognitive Enhancement Therapy (CET) is a particularly promising approach to cognitive remediation that integrates both computer-based neurocognitive training and structured social-cognitive groups. In 2009, Eack and colleagues demonstrated evidence that CET significantly improved cognitive and functional outcomes among individuals in the early course of schizophrenia (N = 58). The current study seeks to confirm these effects in the early course of the condition in a larger multi-site clinical trial. Methods A total of 106 (Pittsburgh: n = 54; Boston: n = 52) early course schizophrenia outpatients were randomized to either 18 months of CET (n = 61) or an Enriched Supportive Therapy (EST; n = 45) comparison treatment. Patients completed a comprehensive battery of cognitive, functional, and clinical assessments at baseline, 9 (mid-treatment), and 18 months (end of treatment). Composite indexes were calculated for neurocognition, social cognition, functional outcome, and symptomatology. Intent-to-treat linear mixed-effects models, adjusted for potential demographic and antipsychotic dose confounding effects, were used to investigate differential change trajectories in outcomes between CET and EST. The group (CET vs. EST) x time (baseline, 9, and 18 months) interaction was the effect of interest. Results No significant group x time interactions were observed for either neurocognition (F2,88 =.30, p =.742) or clinical symptoms (F2,88 =.13, p =.874). CET demonstrated particularly favorable effects on social cognition and functional outcomes. Over the 18 months of treatment, relative to the patients in the EST treatment group, those in CET had significantly greater linear gains in social-cognitive abilities (F2,88 = 3.62, p =.031, d =.64) and functional outcome (F2,88 = 4.18, p =.019, d =.37). Discussion These results support CET as an effective treatment for improving social cognitive and functional outcomes in the early course of schizophrenia, largely confirming the findings from the initial trial (Eack et al. 2009). Such evidence underscores the impact of CET on reducing disability when applied as an early course intervention. [ABSTRACT FROM AUTHOR]