Severity of thought disorder predicts psychosis in persons at clinical high-risk

Automated linguistic analysis in youth at clinical high risk for psychosis

Identifying individuals at clinical high risk for psychosis (CHRP) is crucial for preventing psychosis and improving the prognosis for schizophrenia. Individuals at CHR-P may exhibit mild forms of formal thought disorder (FTD), making it possible to identify them using natural language processing (NLP) methods. In this study, speech samples of 62 CHR-P individuals and 45 healthy controls (HCs) were elicited using Thematic Apperception Test images. The evaluation involved various NLP measures such as semantic similarity, generic, and part-of-speech (POS) features. The CHR-P group demonstrated higher sentence-level semantic similarity and reduced mean image-to-text similarity. Regarding generic analysis, they demonstrated reduced verbosity and produced shorter sentences with shorter words. The POS analysis revealed a decrease in the utilization of adverbs, conjunctions, and first-person singular pronouns, alongside an increase in the utilization of adjectives in the CHR-P group compared to HC. In addition, we developed a machine-learning model based on 30 NLP-derived features to distinguish between the CHR-P and HC groups. The model demonstrated an accuracy of 79.6 % and an AUC-ROC of 0.86. Overall, these findings suggest that automated language analysis of speech could provide valuable information for characterizing FTD during the clinical high-risk phase and has the potential to be applied objectively for early intervention for psychosis.

Development of the PSYCHS: Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS

AIM

To harmonize two ascertainment and severity rating instruments commonly used for the clinical high risk syndrome for psychosis (CHR-P): the Structured Interview for Psychosis-risk Syndromes (SIPS) and the Comprehensive Assessment of At-Risk Mental States (CAARMS).

METHODS

The initial workshop is described in the companion report from Addington et al. After the workshop, lead experts for each instrument continued harmonizing attenuated positive symptoms and criteria for psychosis and CHR-P through an intensive series of joint videoconferences.

RESULTS

Full harmonization was achieved for attenuated positive symptom ratings and psychosis criteria, and modest harmonization for CHR-P criteria. The semi-structured interview, named Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS (PSYCHS), generates CHR-P criteria and severity scores for both CAARMS and SIPS.

CONCLUSIONS

Using the PSYCHS for CHR-P ascertainment, conversion determination, and attenuated positive symptom severity rating will help in comparing findings across studies and in meta-analyses.

Heterogeneity of clinical symptomatology in pediatric patients at clinical high risk for psychosis

OBJECTIVE

Widespread use of diagnostic tools like the Structured Interview for Prodromal Symptoms (SIPS) has highlighted that youth at Clinical High Risk for Psychosis (CHR-P) present with heterogeneous symptomatology. This pilot study aims to highlight the range of clinical characteristics of CHR-P youth, investigate the role of the non-positive (negative, disorganization, and general) symptoms in risk assessment, and determine if specific profiles are associated with severe symptomatology.

METHODS

38 participants aged 7-18 were administered the SIPS and designated as CHR-P. Descriptive statistics and mean difference t-tests were used to describe the range in prevalence and severity of SIPS symptoms and to identify symptoms associated with greater overall symptomatology.

RESULTS

Participants who had a greater number of positive symptoms also had significantly more negative, disorganization, and general symptoms. A number of SIPS symptoms were associated with greater number of positive symptoms.

CONCLUSION

CHR-P youth represent a heterogeneous group, presenting with a wide range in clinical presentation as reflected in both the number of SIPS symptoms and their severity. Though the severity and duration of positive SIPS symptoms determines the CHR-P classification, high ratings on several of the other SIPS negative, disorganization, and general items may be useful indicators of elevated symptomatology.

Development of the PSYCHS: Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS

Aim

To harmonize two ascertainment and severity rating instruments commonly used for the clinical high risk syndrome for psychosis (CHR-P): the Structured Interview for Psychosis-risk Syndromes (SIPS) and the Comprehensive Assessment of At-Risk Mental States (CAARMS).

Methods

The initial workshop is described in the companion report from Addington et al. After the workshop, lead experts for each instrument continued harmonizing attenuated positive symptoms and criteria for psychosis and CHR-P through an intensive series of joint videoconferences.

Results

Full harmonization was achieved for attenuated positive symptom ratings and psychosis criteria, and partial harmonization for CHR-P criteria. The semi-structured interview, named P ositive SY mptoms and Diagnostic Criteria for the C AARMS H armonized with the S IPS (PSYCHS), generates CHR-P criteria and severity scores for both CAARMS and SIPS.

Conclusion

Using the PSYCHS for CHR-P ascertainment, conversion determination, and attenuated positive symptom severity rating will help in comparing findings across studies and in meta-analyses.

Predictive validity of psychosis risk models when applied to adolescent psychiatric patients

BACKGROUND

Several multivariate algorithms have been developed for predicting psychosis, as attempts to obtain better prognosis prediction than with current clinical high-risk (CHR) criteria. The models have typically been based on samples from specialized clinics. We evaluated the generalizability of 19 prediction models to clinical practice in an unselected adolescent psychiatric sample.

METHODS

In total, 153 adolescent psychiatric patients in the Helsinki Prodromal Study underwent an extensive baseline assessment including the SIPS interview and a neurocognitive battery, with 50 participants (33%) fulfilling CHR criteria. The adolescents were followed up for 7 years using comprehensive national registers. Assessed outcomes were (1) any psychotic disorder diagnosis (n = 18, 12%) and (2) first psychiatric hospitalization (n = 25, 16%) as an index of overall deterioration of functioning.

RESULTS

Most models improved the overall prediction accuracy over standard CHR criteria (area under the curve estimates ranging between 0.51 and 0.82), although the accuracy was worse than that in the samples used to develop the models, also when applied only to the CHR subsample. The best models for transition to psychosis included the severity of positive symptoms, especially delusions, and negative symptoms. Exploratory models revealed baseline negative symptoms, low functioning, delusions, and sleep problems in combination to be the best predictor of psychiatric hospitalization in the upcoming years.

CONCLUSIONS

Including the severity levels of both positive and negative symptomatology proved beneficial in predicting psychosis. Despite these advances, the applicability of extended psychosis-risk models to general psychiatric practice appears limited.

Thalamic dysconnectivity in the psychosis risk syndrome and early illness schizophrenia

BACKGROUND

Schizophrenia (SZ) is associated with thalamic dysconnectivity. Compared to healthy controls (HCs), individuals with SZ have hyperconnectivity with sensory regions, and hypoconnectivity with cerebellar, thalamic, and prefrontal regions. Despite replication of this pattern in chronically ill individuals, less is known about when these abnormalities emerge in the illness course and if they are present prior to illness onset.

METHODS

Resting-state functional magnetic resonance imaging data were collected from psychosis risk syndrome (PRS) youth (n = 45), early illness SZ (ESZ) (n = 74) patients, and HCs (n = 85). Age-adjusted functional connectivity, seeded from the thalamus, was compared among the groups.

RESULTS

Significant effects of group were observed in left and right middle temporal regions, left and right superior temporal regions, left cerebellum, and bilateral thalamus. Compared to HCs, ESZ demonstrated hyperconnectivity to all temporal lobe regions and reduced connectivity with cerebellar, anterior cingulate, and thalamic regions. Compared to HCs, PRS demonstrated hyperconnectivity with the left and right middle temporal regions, and hypoconnectivity with the cerebellar and other thalamic regions. Compared to PRS participants, ESZ participants were hyperconnected to temporal regions, but did not differ from PRS in hypoconnectivity with cerebellar and thalamic regions. Thalamic dysconnectivity was unrelated to positive symptom severity in ESZ or PRS groups.

CONCLUSIONS

PRS individuals demonstrated an intermediate level of thalamic dysconnectivity, whereas ESZ showed a pattern consistent with prior observations in chronic samples. These cross-sectional findings suggest that thalamic dysconnectivity may occur prior to illness onset and become more pronounced in early illness stages.

Mismatch Negativity in Response to Auditory Deviance and Risk for Future Psychosis in Youth at Clinical High Risk for Psychosis

Importance

Although clinical criteria for identifying youth at risk for psychosis have been validated, they are not sufficiently accurate for predicting outcomes to inform major treatment decisions. The identification of biomarkers may improve outcome prediction among individuals at clinical high risk for psychosis (CHR-P).

Objective

To examine whether mismatch negativity (MMN) event-related potential amplitude, which is deficient in schizophrenia, is reduced in young people with the CHR-P syndrome and associated with outcomes, accounting for effects of antipsychotic medication use.

Design, Setting, and Participants

MMN data were collected as part of the multisite case-control North American Prodrome Longitudinal Study (NAPLS-2) from 8 university-based outpatient research programs. Baseline MMN data were collected from June 2009 through April 2013. Clinical outcomes were assessed throughout 24 months. Participants were individuals with the CHR-P syndrome and healthy controls with MMN data. Participants with the CHR-P syndrome who developed psychosis (ie, converters) were compared with those who did not develop psychosis (ie, nonconverters) who were followed up for 24 months. Analysis took place between December 2019 and December 2021.

Main Outcomes and Measures

Electroencephalography was recorded during a passive auditory oddball paradigm. MMN elicited by duration-, pitch-, and duration + pitch double-deviant tones was measured.

Results

The CHR-P group (n = 580; mean [SD] age, 19.24 [4.39] years) included 247 female individuals (42.6%) and the healthy control group (n = 241; mean age, 20.33 [4.74] years) included 114 female individuals (47.3%). In the CHR-P group, 450 (77.6%) were not taking antipsychotic medication at baseline. Baseline MMN amplitudes, irrespective of deviant type, were deficient in future CHR-P converters to psychosis (n = 77, unmedicated n = 54) compared with nonconverters (n = 238, unmedicated n = 190) in both the full sample (d = 0.27) and the unmedicated subsample (d = 0.33). In the full sample, baseline medication status interacted with group and deviant type indicating that double-deviant MMN, compared with single deviants, was reduced in unmedicated converters compared with nonconverters (d = 0.43). Further, within the unmedicated subsample, deficits in double-deviant MMN were most strongly associated with earlier conversion to psychosis (hazard ratio, 1.40 [95% CI, 1.03-1.90]; P = .03], which persisted over and above positive symptom severity.

Conclusions and Relevance

This study found that MMN amplitude deficits were sensitive to future psychosis conversion among individuals at risk of CHR-P, particularly those not taking antipsychotic medication at baseline, although associations were modest. While MMN shows limited promise as a biomarker of psychosis onset on its own, it may contribute novel risk information to multivariate prediction algorithms and serve as a translational neurophysiological target for novel treatment development in a subgroup of at-risk individuals.

Neural mechanisms of motor dysfunction in individuals at clinical high-risk for psychosis: Evidence for impairments in motor activation

Motor abnormalities are a core feature of psychotic disorders observed from the premorbid period through chronic illness, suggesting motor dysfunction may reflect the pathophysiology of psychosis. Electrophysiology research in schizophrenia suggests impaired motor activation and preparation may underlie these motor abnormalities. Despite behavioral studies suggesting similar motor dysfunction in those at clinical high-risk (CHR) for psychosis, there have been no studies examining neural mechanisms of motor dysfunction in the CHR period, where research can inform pathophysiological and risk models. The present study used the lateralized readiness potential (LRP), an event-related potential index of motor activation and preparation, to examine mechanisms of motor dysfunction in 42 CHR and 41 control participants (N = 83, 56% female). Response competition was manipulated to determine whether deficits are secondary to cognitive control impairments or reflect primary motor deficits. Behaviorally, CHR participants exhibited overall slower responses than controls. Further, relative to controls, CHR participants showed reduced activation of correct but not incorrect responses, reflected in blunted LRP amplitude under weak response competition and no difference in amplitude associated with the incorrect response under strong response competition. This pattern of results suggests individuals at CHR for psychosis exhibit primary motor deficits in activating and preparing behavioral responses and are contrary to a deficit in cognitive control. Further, blunted LRP amplitude was associated with worsening of negative symptoms at 12-month follow-up. Together, these findings are consistent with LRP studies in psychosis and implicate motor activation deficits as potential mechanisms of motor dysfunction in the high-risk period. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A greedy regression algorithm with coarse weights offers novel advantages

Regularized regression analysis is a mature analytic approach to identify weighted sums of variables predicting outcomes. We present a novel Coarse Approximation Linear Function (CALF) to frugally select important predictors and build simple but powerful predictive models. CALF is a linear regression strategy applied to normalized data that uses nonzero weights + 1 or - 1. Qualitative (linearly invariant) metrics to be optimized can be (for binary response) Welch (Student) t-test p-value or area under curve (AUC) of receiver operating characteristic, or (for real response) Pearson correlation. Predictor weighting is critically important when developing risk prediction models. While counterintuitive, it is a fact that qualitative metrics can favor CALF with ± 1 weights over algorithms producing real number weights. Moreover, while regression methods may be expected to change most or all weight values upon even small changes in input data (e.g., discarding a single subject of hundreds) CALF weights generally do not so change. Similarly, some regression methods applied to collinear or nearly collinear variables yield unpredictable magnitude or the direction (in p-space) of the weights as a vector. In contrast, with CALF if some predictors are linearly dependent or nearly so, CALF simply chooses at most one (the most informative, if any) and ignores the others, thus avoiding the inclusion of two or more collinear variables in the model.

Glutathione as a Molecular Marker of Functional Impairment in Patients with At-Risk Mental State: 7-Tesla 1H-MRS Study

A substantial number of individuals with clinical high-risk (CHR) mental state do not transition to psychosis. However, regardless of future diagnostic trajectories, many of these individuals develop poor social and occupational functional outcomes. The levels of glutathione, a crucial cortical antioxidant, may track variations in functional outcomes in early psychosis and prodromal states. Thirteen clinical high-risk and 30 healthy control volunteers were recruited for a 7-Tesla magnetic resonance spectroscopy scan with a voxel positioned within the dorsal anterior cingulate cortex (ACC). Clinical assessment scores were collected to determine if any association was observable with glutathione levels. The Bayesian Spearman's test revealed a positive association between the Social and Occupational Functioning Assessment Scale (SOFAS) and the glutathione concentration in the clinical high-risk group but not in the healthy control group. After accounting for variations in the SOFAS scores, the CHR group had higher GSH levels than the healthy subjects. This study is the first to use 7-Tesla magnetic resonance spectroscopy to test whether ACC glutathione levels relate to social and occupational functioning in a clinically high-risk group and offers preliminary support for glutathione levels as a clinically actionable marker of prognosis in emerging adults presenting with risk features for various severe mental illnesses.

Longitudinal outcome of attenuated positive symptoms, negative symptoms, functioning and remission in people at clinical high risk for psychosis: a meta-analysis

BACKGROUND

Little is known about clinical outcomes other than transition to psychosis in people at Clinical High-Risk for psychosis (CHR-P). Our aim was to comprehensively meta-analytically evaluate for the first time a wide range of clinical and functional outcomes beyond transition to psychosis in CHR-P individuals.

METHODS

PubMed and Web of Science were searched until November 2020 in this PRISMA compliant meta-analysis (PROSPERO:CRD42020206271). Individual longitudinal studies conducted in individuals at CHR-P providing data on at least one of our outcomes of interest were included. We carried out random-effects pairwise meta-analyses, meta-regressions, and assessed publication bias and study quality. Analyses were two-tailed with α=0.05.

FINDINGS

75 prospective studies were included (n=5,288, age=20.0 years, females=44.5%). Attenuated positive symptoms improved at 12 (Hedges' g=0.753, 95%CI=0.495-1.012) and 24 (Hedges' g=0.836, 95%CI=0.463-1.209), but not ≥36 months (Hedges' g=0.315. 95%CI=-0.176-0.806). Negative symptoms improved at 12 (Hedges' g=0.496, 95%CI=0.315-0.678), but not 24 (Hedges' g=0.499, 95%CI=-0.137-1.134) or ≥36 months (Hedges' g=0.033, 95%CI=-0.439-0.505). Depressive symptoms improved at 12 (Hedges' g=0.611, 95%CI=0.441-0.782) and 24 (Hedges' g=0.583, 95%CI=0.364-0.803), but not ≥36 months (Hedges' g=0.512 95%CI=-0.337-1.361). Functioning improved at 12 (Hedges' g=0.711, 95%CI=0.488-0.934), 24 (Hedges' g=0.930, 95%CI=0.553-1.306) and ≥36 months (Hedges' g=0.392, 95%CI=0.117-0.667). Remission from CHR-P status occurred in 33.4% (95%CI=22.6-44.1%) at 12 months, 41.4% (95%CI=32.3-50.5%) at 24 months and 42.4% (95%CI=23.4-61.3%) at ≥36 months. Heterogeneity across the included studies was significant and ranged from I2=53.6% to I2=96.9%. The quality of the included studies (mean±SD) was 4.6±1.1 (range=2-8).

INTERPRETATION

CHR-P individuals improve on symptomatic and functional outcomes over time, but these improvements are not maintained in the longer term, and less than half fully remit. Prolonged duration of care may be needed for this patient population to optimize outcomes.

FUNDING

None.

Lower speech connectedness linked to incidence of psychosis in people at clinical high risk

BACKGROUND

Formal thought disorder is a cardinal feature of psychotic disorders, and is also evident in subtle forms before psychosis onset in individuals at clinical high-risk for psychosis (CHR-P). Assessing speech output or assessing expressive language with speech as the medium at this stage may be particularly useful in predicting later transition to psychosis.

METHOD

Speech samples were acquired through administration of the Thought and Language Index (TLI) in 24 CHR-P participants, 16 people with first-episode psychosis (FEP) and 13 healthy controls. The CHR-P individuals were then followed clinically for a mean of 7 years (s.d. = 1.5) to determine if they transitioned to psychosis. Non-semantic speech graph analysis was used to assess the connectedness of transcribed speech in all groups.

RESULTS

Speech was significantly more disconnected in the FEP group than in both healthy controls (p < .01) and the CHR-P group (p < .05). Results remained significant when IQ was included as a covariate. Significant correlations were found between speech connectedness measures and scores on the TLI, a manual assessment of formal thought disorder. In the CHR-P group, lower scores on two measures of speech connectedness were associated with subsequent transition to psychosis (8 transitions, 16 non-transitions; p < .05).

CONCLUSION

These findings support the utility and validity of speech graph analysis methods in characterizing speech connectedness in the early phases of psychosis. This approach has the potential to be developed into an automated, objective and time-efficient way of stratifying individuals at CHR-P according to level of psychosis risk.

Deficits in auditory predictive coding in individuals with the psychosis risk syndrome: Prediction of conversion to psychosis

The mismatch negativity (MMN) event-related potential (ERP) component is increasingly viewed as a prediction error signal elicited when a deviant sound violates the prediction that a frequent "standard" sound will repeat. Support for this predictive coding framework emerged with the identification of the repetition positivity (RP), a standard stimulus ERP component that increases with standard repetition and is thought to reflect strengthening of the standard's memory trace and associated predictive code. Using electroencephalographic recordings, we examined the RP elicited by repeating standard tones presented during a traditional "constant standard" MMN paradigm in individuals with the psychosis risk syndrome (PRS; n = 579) and healthy controls (HC; n = 241). Clinical follow-up assessments identified PRS participants who converted to a psychotic disorder (n = 77) and PRS nonconverters who were followed for the entire 24-month clinical follow-up period and either remained symptomatic (n = 144) or remitted from the PRS (n = 94). In HC, RP linearly increased from early- to late-appearing standards within local trains of repeating standards (p < .0001), consistent with auditory predictive code/memory trace strengthening. Relative to HC, PRS participants showed a reduced RP across standards (p = .0056). PRS converters showed a relatively small RP deficit for early appearing standards relative to HC (p = .0.0107) and a more prominent deficit for late-appearing standards (p = .0006) relative to both HC and PRS-remitted groups. Moreover, greater RP deficits predicted shorter time to conversion in a subsample of unmedicated PRS individuals (p = .02). Thus, auditory predictive coding/memory trace deficits precede psychosis onset and predict future psychosis risk in PRS individuals. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Recency and intensification of positive symptoms enhance prediction of conversion to syndromal psychosis in clinical high-risk patients

BACKGROUND

Early detection and intervention strategies in patients at clinical high-risk (CHR) for syndromal psychosis have the potential to contain the morbidity of schizophrenia and similar conditions. However, research criteria that have relied on severity and number of positive symptoms are limited in their specificity and risk high false-positive rates. Our objective was to examine the degree to which measures of recency of onset or intensification of positive symptoms [a.k.a., new or worsening (NOW) symptoms] contribute to predictive capacity.

METHODS

We recruited 109 help-seeking individuals whose symptoms met criteria for the Progression Subtype of the Attenuated Positive Symptom Psychosis-Risk Syndrome defined by the Structured Interview for Psychosis-Risk Syndromes and followed every three months for two years or onset of syndromal psychosis.

RESULTS

Forty-one (40.6%) of 101 participants meeting CHR criteria developed a syndromal psychotic disorder [mostly (80.5%) schizophrenia] with half converting within 142 days (interquartile range: 69-410 days). Patients with more NOW symptoms were more likely to convert (converters: 3.63 ± 0.89; non-converters: 2.90 ± 1.27; p = 0.001). Patients with stable attenuated positive symptoms were less likely to convert than those with NOW symptoms. New, but not worsening, symptoms, in isolation, also predicted conversion.

CONCLUSIONS

Results suggest that the severity and number of attenuated positive symptoms are less predictive of conversion to syndromal psychosis than the timing of their emergence and intensification. These findings also suggest that the earliest phase of psychotic illness involves a rapid, dynamic process, beginning before the syndromal first episode, with potentially substantial implications for CHR research and understanding the neurobiology of psychosis.

Clinical, cognitive and neuroanatomical associations of serum NMDAR autoantibodies in people at clinical high risk for psychosis

Serum neuronal autoantibodies, such as those to the NMDA receptor (NMDAR), are detectable in a subgroup of patients with psychotic disorders. It is not known if they are present before the onset of psychosis or whether they are associated with particular clinical features or outcomes. In a case-control study, sera from 254 subjects at clinical high risk (CHR) for psychosis and 116 healthy volunteers were tested for antibodies against multiple neuronal antigens implicated in CNS autoimmune disorders, using fixed and live cell-based assays (CBAs). Within the CHR group, the relationship between NMDAR antibodies and symptoms, cognitive function and clinical outcomes over 24 month follow-up was examined. CHR subjects were not more frequently seropositive for neuronal autoantibodies than controls (8.3% vs. 5.2%; OR = 1.50; 95% CI: 0.58-3.90). The NMDAR was the most common target antigen and NMDAR IgGs were more sensitively detected with live versus fixed CBAs (p < 0.001). Preliminary phenotypic analyses revealed that within the CHR sample, the NMDAR antibody seropositive subjects had higher levels of current depression, performed worse on the Rey Auditory Verbal Learning Task (p < 0.05), and had a markedly lower IQ (p < 0.01). NMDAR IgGs were not more frequent in subjects who later became psychotic than those who did not. NMDAR antibody serostatus and titre was associated with poorer levels of functioning at follow-up (p < 0.05) and the presence of a neuronal autoantibody was associated with larger amygdala volumes (p < 0.05). Altogether, these findings demonstrate that NMDAR autoantibodies are detectable in a subgroup of CHR subjects at equal rates to controls. In the CHR group, they are associated with affective psychopathology, impairments in verbal memory, and overall cognitive function: these findings are qualitatively and individually similar to core features of autoimmune encephalitis and/or animal models of NMDAR antibody-mediated CNS disease. Overall the current work supports further evaluation of NMDAR autoantibodies as a possible prognostic biomarker and aetiological factor in a subset of people already meeting CHR criteria.

Predicting the individual risk of psychosis conversion in at-risk mental state (ARMS): a multivariate model reveals the influence of nonpsychotic prodromal symptoms

To improve the prediction of the individual risk of conversion to psychosis in UHR subjects, by considering all CAARMS' symptoms at first presentation and using a multivariate machine learning method known as logistic regression with Elastic-net shrinkage. 46 young individuals who sought help from the specialized outpatient unit at Sainte-Anne hospital and who met CAARMS criteria for UHR were assessed, among whom 27 were reassessed at follow-up (22.4 ± 6.54 months) and included in the analysis. Elastic net logistic regression was trained, using CAARMS items at baseline to predict individual evolution between converters (UHR-P) and non-converters (UHR-NP). Elastic-net was used to select the few CAARMS items that best predict the clinical evolution. All validations and significances of predictive models were computed with non-parametric re-sampling strategies that provide robust estimators even when the distributional assumption cannot be guaranteed. Among the 25 CAARMS items, the Elastic net selected 'obsessive-compulsive symptoms' and 'aggression/dangerous behavior' as risk factors for conversion while 'anhedonia' and 'mood swings/lability' were associated with non-conversion at follow-up. In the ten-fold stratified cross-validation, the classification achieved 81.8% of sensitivity (P = 0.035) and 93.7% of specificity (P = 0.0016). Non-psychotic prodromal symptoms bring valuable information to improve the prediction of conversion to psychosis. Elastic net logistic regression applied to clinical data is a promising way to switch from group prediction to an individualized prediction.

Linking psychophysiological adaptation, emotion regulation, and subjective stress to the occurrence of paranoia in daily life

As stress is relevant to the formation of paranoia, maladaptive behavioral and physiological stress regulation is discussed as a crucial indicator of vulnerability. This is supported by research linking psychosis to the tendency to make less use of functional and more use of dysfunctional emotion regulation strategies (ER) and with a lower vagally-mediated heart rate variability (HRV). However, it remains unclear whether ER serves as a mediator between resting-state HRV on the one hand and subjective stress levels and paranoia on the other and whether this is specific to paranoia as compared to depression. We used an experience sampling method during seven days to repeatedly assess the experience of stress, usage of ER strategies, paranoia und depression (9/day) in a sample with subclinical positive symptoms (N = 32). Resting-state HRV was measured during a 5min interval in the laboratory. Data was analyzed by multi-level models. Higher resting-state HRV was predictive of lower stress-levels and of using more functional ER strategies (reappraisal, acceptance) in daily life, but did not predict the use of dysfunctional strategies (rumination, suppression) or paranoia. The association between resting-state HRV and stress was mediated by the usage of functional ER. Less functional and more dysfunctional ER were linked to higher levels of stress, paranoia and depression. Our study highlights that deficits in ER represent a link between psychophysiological and phenomenological aspects of paranoia but also of depression. This encourages to further investigate transdiagnostic prevention and therapy programs aiming to improve ER and to increase HRV.

Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice

BACKGROUND

The impact of precision psychiatry for clinical practice has not been systematically appraised. This study aims to provide a comprehensive review of validated prediction models to estimate the individual risk of being affected with a condition (diagnostic), developing outcomes (prognostic), or responding to treatments (predictive) in mental disorders.

METHODS

PRISMA/RIGHT/CHARMS-compliant systematic review of the Web of Science, Cochrane Central Register of Reviews, and Ovid/PsycINFO databases from inception until July 21, 2019 (PROSPERO CRD42019155713) to identify diagnostic/prognostic/predictive prediction studies that reported individualized estimates in psychiatry and that were internally or externally validated or implemented. Random effect meta-regression analyses addressed the impact of several factors on the accuracy of prediction models.

FINDINGS

Literature search identified 584 prediction modeling studies, of which 89 were included. 10.4% of the total studies included prediction models internally validated (n = 61), 4.6% models externally validated (n = 27), and 0.2% (n = 1) models considered for implementation. Across validated prediction modeling studies (n = 88), 18.2% were diagnostic, 68.2% prognostic, and 13.6% predictive. The most frequently investigated condition was psychosis (36.4%), and the most frequently employed predictors clinical (69.5%). Unimodal compared to multimodal models (β = .29, P = .03) and diagnostic compared to prognostic (β = .84, p < .0001) and predictive (β = .87, P = .002) models were associated with increased accuracy.

INTERPRETATION

To date, several validated prediction models are available to support the diagnosis and prognosis of psychiatric conditions, in particular, psychosis, or to predict treatment response. Advancements of knowledge are limited by the lack of implementation research in real-world clinical practice. A new generation of implementation research is required to address this translational gap.

Potential Roles of Redox Dysregulation in the Development of Schizophrenia

Converging evidence implicates redox dysregulation as a pathological mechanism driving the emergence of psychosis. Increased oxidative damage and decreased capacity of intracellular redox modulatory systems are consistent findings in persons with schizophrenia as well as in persons at clinical high risk who subsequently developed frank psychosis. Levels of glutathione, a key regulator of cellular redox status, are reduced in the medial prefrontal cortex, striatum, and thalamus in schizophrenia. In humans with schizophrenia and in rodent models recapitulating various features of schizophrenia, redox dysregulation is linked to reductions of parvalbumin containing gamma-aminobutyric acid (GABA) interneurons and volumes of their perineuronal nets, white matter abnormalities, and microglia activation. Importantly, the activity of transcription factors, kinases, and phosphatases regulating diverse aspects of neurodevelopment and synaptic plasticity varies according to cellular redox state. Molecules regulating interneuron function under redox control include NMDA receptor subunits GluN1 and GluN2A as well as KEAP1 (regulator of transcription factor NRF2). In a rodent schizophrenia model characterized by impaired glutathione synthesis, the Gclm knockout mouse, oxidative stress activated MMP9 (matrix metalloprotease 9) via its redox-responsive regulatory sites, causing a cascade of molecular events leading to microglia activation, perineural net degradation, and impaired NMDA receptor function. Molecular pathways under redox control are implicated in the etiopathology of schizophrenia and are attractive drug targets for individualized drug therapy trials in the contexts of prevention and treatment of psychosis.

Polygenic Risk Score Contribution to Psychosis Prediction in a Target Population of Persons at Clinical High Risk

OBJECTIVE

The 2-year risk of psychosis in persons who meet research criteria for a high-risk syndrome is about 15%-25%; improvements in risk prediction accuracy would benefit the development and implementation of preventive interventions. The authors sought to assess polygenic risk score (PRS) prediction of subsequent psychosis in persons at high risk and to determine the impact of adding the PRS to a previously validated psychosis risk calculator.

METHODS

Persons meeting research criteria for psychosis high risk (N=764) and unaffected individuals (N=279) were followed for up to 2 years. The PRS was based on the latest schizophrenia and bipolar genome-wide association studies. Variables in the psychosis risk calculator included stressful life events, trauma, disordered thought content, verbal learning, information processing speed, and family history of psychosis.

RESULTS

For Europeans, the PRS varied significantly by group and was higher in the psychosis converter group compared with both the nonconverter and unaffected groups, but was similar for the nonconverter group compared with the unaffected group. For non-Europeans, the PRS varied significantly by group; the difference between the converters and nonconverters was not significant, but the PRS was significantly higher in converters than in unaffected individuals, and it did not differ between nonconverters and unaffected individuals. The R2liability (R2 adjusted for the rate of disease risk in the population being studied, here assuming a 2-year psychosis risk between 10% and 30%) for Europeans varied between 9.2% and 12.3% and for non-Europeans between 3.5% and 4.8%. The amount of risk prediction information contributed by the addition of the PRS to the risk calculator was less than severity of disordered thoughts and similar to or greater than for other variables. For Europeans, the PRS was correlated with risk calculator variables of information processing speed and verbal memory.

CONCLUSIONS

The PRS discriminates psychosis converters from nonconverters and modestly improves individualized psychosis risk prediction when added to a psychosis risk calculator. The schizophrenia PRS shows promise in enhancing risk prediction in persons at high risk for psychosis, although its potential utility is limited by poor performance in persons of non-European ancestry.

DSM-5 Attenuated Psychosis Syndrome in Adolescents Hospitalized With Non-psychotic Psychiatric Disorders

Introduction: Although attenuated psychotic symptoms often occur for the first time during adolescence, studies focusing on adolescents are scarce. Attenuated psychotic symptoms form the criteria to identify individuals at increased clinical risk of developing psychosis. The study of individuals with these symptoms has led to the release of the DSM-5 diagnosis of Attenuated Psychosis Syndrome (APS) as a condition for further research. We aimed to characterize and compare hospitalized adolescents with DSM-5-APS diagnosis vs. hospitalized adolescents without a DSM-5-APS diagnosis. Methods: Interviewing help-seeking, hospitalized adolescents (aged 12-18 years) and their caregivers independently with established research instruments, we (1) evaluated the presence of APS among non-psychotic adolescents, (2) characterized and compared APS and non-APS individuals regarding sociodemographic, illness and intervention characteristics, (3) correlated psychopathology with levels of functioning and severity of illness and (4) investigated the influence of individual clinical, functional and comorbidity variables on the likelihood of participants to be diagnosed with APS. Results: Among 248 consecutively recruited adolescents (age=15.4 ± 1.5 years, females = 69.6%) with non-psychotic psychiatric disorders, 65 (26.2%) fulfilled APS criteria and 183 (73.8%) did not fulfill them. Adolescents with APS had higher number of psychiatric disorders than non-APS adolescents (3.5 vs. 2.4, p < 0.001; Cohen's d = 0.77), particularly, disruptive behavior disorders (Cramer's V = 0.16), personality disorder traits (Cramer's V = 0.26), anxiety disorders (Cramer's V = 0.15), and eating disorders (Cramer's V = 0.16). Adolescents with APS scored higher on positive (Cohen's d = 1.5), negative (Cohen's d = 0.55), disorganized (Cohen's d = 0.51), and general symptoms (Cohen's d = 0.84), and were more severely ill (Cohen's d = 1.0) and functionally impaired (Cohen's d = 0.31). Negative symptoms were associated with lower functional levels (Pearson ρ = -0.17 to -0.20; p = 0.014 to 0.031). Global illness severity was associated with higher positive, negative, and general symptoms (Pearson ρ = 0.22 to 0.46; p = 0.04 to p < 0.001). APS status was independently associated with perceptual abnormalities (OR = 2.0; 95% CI = 1.6-2.5, p < 0.001), number of psychiatric diagnoses (OR = 1.5; 95% CI = 1.2-2.0, p = 0.002), and impaired stress tolerance (OR = 1.4; 95% CI = 1.1-1.7, p = 0.002) (r ² = 0.315, p < 0.001). Conclusions: A considerable number of adolescents hospitalized with non-psychotic psychiatric disorders meet DSM-5-APS criteria. These help-seeking adolescents have more comorbid disorders and more severe symptoms, functional impairment, and severity of illness than non-APS adolescents. Thus, they warrant high intensity clinical care.

Association Between P300 Responses to Auditory Oddball Stimuli and Clinical Outcomes in the Psychosis Risk Syndrome

IMPORTANCE

In most patients, a prodromal period precedes the onset of schizophrenia. Although clinical criteria for identifying the psychosis risk syndrome (PRS) show promising predictive validity, assessment of neurophysiologic abnormalities in at-risk individuals may improve clinical prediction and clarify the pathogenesis of schizophrenia.

OBJECTIVE

To determine whether P300 event-related potential amplitude, which is deficient in schizophrenia, is reduced in the PRS and associated with clinical outcomes.

DESIGN, SETTING, AND PARTICIPANTS

Auditory P300 data were collected as part of the multisite, case-control North American Prodrome Longitudinal Study (NAPLS-2) at 8 university-based outpatient programs. Participants included 552 individuals meeting PRS criteria and 236 healthy controls with P300 data. Auditory P300 data of participants at risk who converted to psychosis (n = 73) were compared with those of nonconverters who were followed up for 24 months and continued to be symptomatic (n = 135) or remitted from the PRS (n = 90). Data were collected from May 27, 2009, to September 17, 2014, and were analyzed from December 3, 2015, to May 1, 2019.

MAIN OUTCOMES AND MEASURES

Baseline electroencephalography was recorded during an auditory oddball task. Two P300 subcomponents were measured: P3b, elicited by infrequent target stimuli, and P3a, elicited by infrequent nontarget novel stimuli.

RESULTS

This study included 788 participants. The PRS group (n = 552) included 236 females (42.8%) (mean [SD] age, 19.21 [4.38] years), and the healthy control group (n = 236) included 111 females (47.0%) (mean [SD] age, 20.44 [4.73] years). Target P3b and novelty P3a amplitudes were reduced in at-risk individuals vs healthy controls (d = 0.37). Target P3b, but not novelty P3a, was significantly reduced in psychosis converters vs nonconverters (d = 0.26), and smaller target P3b amplitude was associated with a shorter time to psychosis onset in at-risk individuals (hazard ratio, 1.45; 95% CI, 1.04-2.00; P = .03). Participants with the PRS who remitted had baseline target P3b amplitudes that were similar to those of healthy controls and greater than those of converters (d = 0.51) and at-risk individuals who remained symptomatic (d = 0.41).

CONCLUSIONS AND RELEVANCE

In this study, deficits in P300 amplitude appeared to precede psychosis onset. Target P3b amplitudes, in particular, may be sensitive to clinical outcomes in the PRS, including both conversion to psychosis and clinical remission. Auditory target P3b amplitude shows promise as a putative prognostic biomarker of clinical outcome in the PRS.

Does hallucination perceptual modality impact psychosis risk?

OBJECTIVE

Subthreshold perceptual abnormalities are commonly used to identify individuals at clinical high risk (CHR) for developing a psychotic disorder. Predictive validity for modality-specific perceptual abnormality severity on psychosis risk is unknown.

METHODS

We examined prospectively collected data from 164 individuals age 12-35 meeting criteria for CHR followed for 6-24 months or until conversion to psychosis. Using intake interview notes, baseline perceptual abnormality scores were split into auditory, visual, somatic/tactile, and olfactory/gustatory components, and auditory scores were further split into those for verbal vs non-verbal content. Relationships between perceptual abnormality characteristics and conversion were assessed with Cox proportional hazards regression and logistic regression.

RESULTS

Unusual thought content and paranoia were predictive of conversion, but no modality-specific perceptual abnormality score predicted conversion status or days to conversion. However, when auditory perceptual abnormalities were further categorized as verbal vs non-verbal, the severity of verbal experiences was predictive of conversion to psychosis (P = 0.007).

CONCLUSIONS

Perceptual abnormality scores failed to meaningfully predict conversion to psychosis in either direction in this CHR sample. However, verbal auditory experiences may identify a group of CHR individuals at elevated risk of conversion. Further exploration of the relationship between phenomenological aspects of perceptual abnormalities and conversion risk is warranted.

Tobacco use and psychosis risk in persons at clinical high risk

AIM

To evaluate the role of tobacco use in the development of psychosis in individuals at clinical high risk.

METHOD

The North American Prodrome Longitudinal Study is a 2-year multi-site prospective case control study of persons at clinical high risk that aims to better understand predictors and mechanisms for the development of psychosis. The cohort consisted of 764 clinical high risk and 279 healthy comparison subjects. Clinical assessments included tobacco and substance use and several risk factors associated with smoking in general population studies.

RESULTS

Clinical high risk subjects were more likely to smoke cigarettes than unaffected subjects (light smoking odds ratio [OR] = 3.0, 95% confidence interval [CI] = 1.9-5; heavy smoking OR = 4.8, 95% CI = 1.7-13.7). In both groups, smoking was associated with mood, substance use, stress and perceived discrimination and in clinical high risk subjects with childhood emotional neglect and adaption to school. Clinical high risk subjects reported higher rates of several factors previously associated with smoking, including substance use, anxiety, trauma and perceived discrimination. After controlling for these potential factors, the relationship between clinical high risk state and smoking was no longer significant (light smoking OR = 0.9, 95% CI = 0.4-2.2; heavy smoking OR = 0.3, 95% CI = 0.05-2.3). Moreover, baseline smoking status (hazard ratio [HR] = 1.16, 95% CI = 0.82-1.65) and categorization as ever smoked (HR = 1.3, 95% CI = 0.8-2.1) did not predict time to conversion.

CONCLUSION

Persons at high risk for psychosis are more likely to smoke and have more factors associated with smoking than controls. Smoking status in clinical high risk subjects does not predict conversion. These findings do not support a causal relationship between smoking and psychosis.

Auditory and Visual Oddball Stimulus Processing Deficits in Schizophrenia and the Psychosis Risk Syndrome: Forecasting Psychosis Risk With P300

Identification of neurophysiological abnormalities associated with schizophrenia that predate and predict psychosis onset may improve clinical prediction in the psychosis risk syndrome (PRS) and help elucidate the pathogenesis of schizophrenia. Amplitude reduction of the P300 event-related potential component reflects attention-mediated processing deficits and is among the most replicated biological findings in schizophrenia, making it a candidate biomarker of psychosis risk. The relative extent to which deficits in P300 amplitudes elicited by auditory and visual oddball stimuli precede psychosis onset during the PRS and predict transition to psychosis, however, remains unclear. Forty-three individuals meeting PRS criteria, 19 schizophrenia patients, and 43 healthy control (HC) participants completed baseline electroencephalography recording during separate auditory and visual oddball tasks. Two subcomponents of P300 were measured: P3b, elicited by infrequent target stimuli, and P3a, elicited by infrequent nontarget novel stimuli. Auditory and visual target P3b and novel P3a amplitudes were reduced in PRS and schizophrenia participants relative to HC participants. In addition, baseline auditory and visual target P3b, but not novel P3a, amplitudes were reduced in 15 PRS participants who later converted to psychosis, relative to 18 PRS non-converters who were followed for at least 22 months. Furthermore, target P3b amplitudes predicted time to psychosis onset among PRS participants. These results suggest that P300 amplitude deficits across auditory and visual modalities emerge early in the schizophrenia illness course and precede onset of full psychosis. Moreover, target P3b may represent an important neurophysiological vulnerability marker of the imminence of risk for psychosis.

The psychosis risk timeline: can we improve our preventive strategies? Part 2: adolescence and adulthood

Current understanding of psychosis development is relevant to patients' clinical outcomes in mental health services as a whole, given that psychotic symptoms can be a feature of many different diagnoses at different stages of life. Understanding the risk factors helps clinicians to contemplate primary, secondary and tertiary preventive strategies that it may be possible to implement. In this second article of a three-part series, the psychosis risk timeline is again considered, here focusing on risk factors more likely to be encountered during later childhood, adolescence and adulthood. These include environmental factors, substance misuse, and social and psychopathological aspects.

LEARNING OBJECTIVES:

After reading this article you will be able to: •

DECLARATION OF INTEREST:

None.

Prediction of psychosis in prodrome: development and validation of a simple, personalized risk calculator

BACKGROUND

This study aim to derive and validate a simple and well-performing risk calculator (RC) for predicting psychosis in individual patients at clinical high risk (CHR).

METHODS

From the ongoing ShangHai-At-Risk-for-Psychosis (SHARP) program, 417 CHR cases were identified based on the Structured Interview for Prodromal Symptoms (SIPS), of whom 349 had at least 1-year follow-up assessment. Of these 349 cases, 83 converted to psychosis. Logistic regression was used to build a multivariate model to predict conversion. The area under the receiver operating characteristic (ROC) curve (AUC) was used to test the effectiveness of the SIPS-RC. Second, an independent sample of 100 CHR subjects was recruited based on an identical baseline and follow-up procedures to validate the performance of the SIPS-RC.

RESULTS

Four predictors (each based on a subset of SIPS-based items) were used to construct the SIPS-RC: (1) functional decline; (2) positive symptoms (unusual thoughts, suspiciousness); (3) negative symptoms (social anhedonia, expression of emotion, ideational richness); and (4) general symptoms (dysphoric mood). The SIPS-RC showed moderate discrimination of subsequent transition to psychosis with an AUC of 0.744 (p < 0.001). A risk estimate of 25% or higher had around 75% accuracy for predicting psychosis. The personalized risk generated by the SIPS-RC provided a solid estimate of conversion outcomes in the independent validation sample, with an AUC of 0.804 [95% confidence interval (CI) 0.662-0.951].

CONCLUSION

The SIPS-RC, which is simple and easy to use, can perform in the same manner as the NAPLS-2 RC in the Chinese clinical population. Such a tool may be used by clinicians to counsel appropriately their patients about clinical monitor v. potential treatment options.

External validation and extension of the NAPLS-2 and SIPS-RC personalized risk calculators in an independent clinical high-risk sample

Early identification of individuals likely to develop psychosis is a priority for the field, resulting in the development of risk calculators that provide personalized estimates that an individual at clinical high-risk (CHR) will develop psychosis. The North American Prodrome Longitudinal Study (NAPLS) consortium and Shanghai At-Risk for Psychosis program have recently developed such calculators (NAPLS-2/SIPS-RC, respectively), but their discrimination performance has never been examined within the same sample. Moreover, validation studies of NAPLS-2 are limited in number and the SIPS-RC has not been cross-validated in a North American sample. The present research (N = 68) used the area under the receiver operating characteristic curve (AUC) to examine the accuracy of the NAPLS-2 and SIPS-RC calculators for discriminating CHR converters and non-converters, as well as extend their use by examining their ability to predict illness progression over a two-year period. For conversion, the NAPLS-2 and SIPS-RC risk calculators demonstrated moderate (AUC = 0.71) and fair (AUC = 0.65) discrimination performance, respectively. Both calculators provided moderate accuracy for discriminating illness progression over two-years (NAPLS-2 AUC = 0.71/ SIPS-RC AUC = 0.76). We discuss implications for researchers and practitioners interested in using the NAPLS-2 and/or SIPS-RC and identify important steps for future research.

Comparison of the neurocognitive profiles of individuals with elevated psychotic or depressive symptoms

AIM

Neurocognitive deficits are pervasive and enduring features of severe mental illness that appear before the onset of clinical symptoms and contribute to functional disability. However, it remains unclear how individuals who display warning signs for psychotic or mood disorders compare on their neurocognitive profiles since previous studies have separately examined neurocognition in both groups. Therefore, the purpose of this study was to directly compare performance on a range of neurocognitive tasks in individuals with emerging psychotic or mood symptoms.

METHODS

Participants were drawn from a database of individuals who completed a comprehensive assessment at a university-based assessment centre. We examined 3 groups: individuals who endorsed elevated psychotic symptoms (EPS; n = 64), individuals who endorsed elevated depressive symptoms (EDS; n = 58), or non-clinical comparisons (NCC; n = 57) without any elevated psychiatric symptoms or diagnoses.

RESULTS

EPS participants performed worse than NCC and EDS groups on verbal comprehension, working memory and cognitive flexibility, and worse than NCC, but not EDS, on perceptual reasoning. There were no significant differences between groups on processing speed, verbal fluency and set-shifting. EDS performed worse than both EPS and NCC groups on psychomotor speed. Dimensionally, poorer cognitive functioning was more strongly related to EPS than depressive symptoms.

CONCLUSIONS

These findings highlight the distinct yet overlapping neurocognitive profiles of both groups with emerging psychiatric symptoms, and suggest that, despite having no formal diagnosis, individuals with EPS exhibit observable cognitive impairment and may still benefit from interventions within academic and workplace contexts.

A predictive model for conversion to psychosis in clinical high-risk patients

BACKGROUND

The authors developed a practical and clinically useful model to predict the risk of psychosis that utilizes clinical characteristics empirically demonstrated to be strong predictors of conversion to psychosis in clinical high-risk (CHR) individuals. The model is based upon the Structured Interview for Psychosis Risk Syndromes (SIPS) and accompanying clinical interview, and yields scores indicating one's risk of conversion.

METHODS

Baseline data, including demographic and clinical characteristics measured by the SIPS, were obtained on 199 CHR individuals seeking evaluation in the early detection and intervention for mental disorders program at the New York State Psychiatric Institute at Columbia University Medical Center. Each patient was followed for up to 2 years or until they developed a syndromal DSM-4 disorder. A LASSO logistic fitting procedure was used to construct a model for conversion specifically to a psychotic disorder.

RESULTS

At 2 years, 64 patients (32.2%) converted to a psychotic disorder. The top five variables with relatively large standardized effect sizes included SIPS subscales of visual perceptual abnormalities, dysphoric mood, unusual thought content, disorganized communication, and violent ideation. The concordance index (c-index) was 0.73, indicating a moderately strong ability to discriminate between converters and non-converters.

CONCLUSIONS

The prediction model performed well in classifying converters and non-converters and revealed SIPS measures that are relatively strong predictors of conversion, comparable with the risk calculator published by NAPLS (c-index = 0.71), but requiring only a structured clinical interview. Future work will seek to externally validate the model and enhance its performance with the incorporation of relevant biomarkers.

Short clinically-based prediction model to forecast transition to psychosis in individuals at clinical high risk state

Objective:

The predictive accuracy of the Clinical High Risk criteria for Psychosis (CHR-P) regarding the future development of the disorder remains suboptimal. It is therefore necessary to incorporate refined risk estimation tools which can be applied at the individual subject level. The aim of the study was to develop an easy-to use, short refined risk estimation tool to predict the development of psychosis in a new CHR-P cohort recruited in European country with less established early detection services.

Methods:

A cohort of 105 CHR-P individuals was assessed with the Comprehensive Assessment of At Risk Mental States12/2006, and then followed for a median period of 36 months (25th-75th percentile:10–59 months) for transition to psychosis. A multivariate Cox regression model predicting transition was generated with preselected clinical predictors and was internally validated with 1000 bootstrap resamples.

Results:

Speech disorganization and unusual thought content were selected as potential predictors of conversion on the basis of published literature. The prediction model was significant (p < 0.0001) and confirmed that both speech disorganization (HR = 1.69; 95%CI: 1.39–2.05) and unusual thought content (HR = 1.51; 95%CI: 1.27–1.80) were significantly associated with transition. The prognostic accuracy of the model was adequate (Harrell’s c- index = 0.79), even after optimism correction through internal validation procedures (Harrell’s c-index = 0.78).

Conclusions:

The clinical prediction model developed, and internally validated, herein to predict transition from a CHR-P to psychosis may be a promising tool for use in clinical settings. It has been incorporated into an online tool available at:https://link.konsta.com.pl/psychosis. Future external replication studies are needed.

Evidence of disturbances of deep levels of semantic cohesion within personal narratives in schizophrenia

Since initial conceptualizations, schizophrenia has been thought to involve core disturbances in the ability to form complex, integrated ideas. Although this has been studied in terms of formal thought disorder, the level of involvement of altered latent semantic structure is less clear. To explore this question, we compared the personal narratives of adults with schizophrenia (n=200) to those produced by an HIV+ sample (n=55) using selected indices from Coh-Metrix. Coh-Metrix is a software system designed to compute various language usage statistics from transcribed written and spoken language documents. It differs from many other frequency-based systems in that Coh-Metrix measures a wide range of language processes, ranging from basic descriptors (e.g., total words) to indices assessing more sophisticated processes within sentences, between sentences, and across paragraphs (e.g., deep cohesion). Consistent with predictions, the narratives in schizophrenia exhibited less cohesion even after controlling for age and education. Specifically, the schizophrenia group spoke fewer words, demonstrated less connection between ideas and clauses, provided fewer causal/intentional markers, and displayed lower levels of deep cohesion. A classification model using only Coh-Metrix indices found language markers correctly classified participants in nearly three-fourths of cases. These findings suggest a particular pattern of difficulties cohesively connecting thoughts about oneself and the world results in a perceived lack of coherence in schizophrenia. These results are consistent with Bleuler's model of schizophrenia and offer a novel way to understand and measure alterations in thought and speech over time.

Intrinsic Connectivity Network-Based Classification and Detection of Psychotic Symptoms in Youth With 22q11.2 Deletions

22q11.2 Deletion syndrome (22q11DS) is a genetic disorder associated with numerous phenotypic consequences and is one of the greatest known risk factors for psychosis. We investigated intrinsic-connectivity-networks (ICNs) as potential biomarkers for patient and psychosis-risk status in 2 independent cohorts, UCLA (33 22q11DS-participants, 33 demographically matched controls), and Syracuse (28 22q11DS, 28 controls). After assessing group connectivity differences, ICNs from the UCLA cohort were used to train classifiers to distinguish cases from controls, and to predict psychosis risk status within 22q11DS; classifiers were subsequently tested on the Syracuse cohort. In both cohorts we observed significant hypoconnectivity in 22q11DS relative to controls within anterior cingulate (ACC)/precuneus, executive, default mode (DMN), posterior DMN, and salience networks. Of 12 ICN-derived classifiers tested in the Syracuse replication-cohort, the ACC/precuneus, DMN, and posterior DMN classifiers accurately distinguished between 22q11DS and controls. Within 22q11DS subjects, connectivity alterations within 4 networks predicted psychosis risk status for a given individual in both cohorts: the ACC/precuneus, DMN, left executive, and salience networks. Widespread within-network-hypoconnectivity in large-scale networks implicated in higher-order cognition may be a defining characteristic of 22q11DS during adolescence and early adulthood; furthermore, loss of coherence within these networks may be a valuable biomarker for individual prediction of psychosis-risk in 22q11DS.

Thought Disorder in Schizophrenia and Bipolar Disorder Probands, Their Relatives, and Nonpsychiatric Controls

Thought disorder (TD) has long been associated with schizophrenia (SZ) and is now widely recognized as a symptom of mania and other psychotic disorders as well. Previous studies have suggested that the TD found in the clinically unaffected relatives of SZ, schizoaffective and bipolar probands is qualitatively similar to that found in the probands themselves. Here, we examine which quantitative measures of TD optimize the distinction between patients with diagnoses of SZ and bipolar disorder with psychotic features (BP) from nonpsychiatric controls (NC) and from each other. In addition, we investigate whether these same TD measures also distinguish their respective clinically unaffected relatives (RelSZ, RelBP) from controls as well as from each other. We find that deviant verbalizations are significantly associated with SZ and are co-familial in clinically unaffected RelSZ, but are dissociated from, and are not co-familial for, BP disorder. In contrast, combinatory thinking was nonspecifically associated with psychosis, but did not aggregate in either group of relatives. These results provide further support for the usefulness of TD for identifying potential non-penetrant carriers of SZ-risk genes, in turn enhancing the power of genetic analyses. These findings also suggest that further refinement of the TD phenotype may be needed in order to be suitable for use in genetic studies of bipolar disorder.

Prediction of transition to psychosis in patients with a clinical high risk for psychosis: a systematic review of methodology and reporting

BACKGROUND

To enhance indicated prevention in patients with a clinical high risk (CHR) for psychosis, recent research efforts have been increasingly directed towards estimating the risk of developing psychosis on an individual level using multivariable clinical prediction models. The aim of this study was to systematically review the methodological quality and reporting of studies developing or validating such models.

METHOD

A systematic literature search was carried out (up to 14 March 2016) to find all studies that developed or validated a clinical prediction model predicting the transition to psychosis in CHR patients. Data were extracted using a comprehensive item list which was based on current methodological recommendations.

RESULTS

A total of 91 studies met the inclusion criteria. None of the retrieved studies performed a true external validation of an existing model. Only three studies (3.5%) had an event per variable ratio of at least 10, which is the recommended minimum to avoid overfitting. Internal validation was performed in only 14 studies (15%) and seven of these used biased internal validation strategies. Other frequently observed modeling approaches not recommended by methodologists included univariable screening of candidate predictors, stepwise variable selection, categorization of continuous variables, and poor handling and reporting of missing data.

CONCLUSIONS

Our systematic review revealed that poor methods and reporting are widespread in prediction of psychosis research. Since most studies relied on small sample sizes, did not perform internal or external cross-validation, and used poor model development strategies, most published models are probably overfitted and their reported predictive accuracy is likely to be overoptimistic.

Prediction of conversion to psychosis in individuals with an at-risk mental state: a brief update on recent developments

PURPOSE OF REVIEW

So far, only little more than one-third of individuals classified as being at-risk for psychosis have been shown to actually convert to frank psychosis during follow-up. There have therefore been enormous efforts to improve the accuracy of predicting this transition. We reviewed the most recent studies in the field with the aim to clarify whether accuracy of prediction has been improved by the different research endeavors and what could be done to further improve it, and/or what alternative goals research should pursue.

RECENT FINDINGS

A total of 56 studies published between May 2015 and December 2016 were included, of which eight were meta-analyses. New meta-analytical evidence confirms that established instruments for checking clinical risk criteria have an excellent clinical utility in individuals referred to high-risk services. Within a such identified group of ultra-high-risk (UHR) individuals, especially Brief Limited Intermittent Psychotic Symptoms and Attenuated Psychotic Symptoms seem to predict transition. Further assessments should be performed within the UHR individuals, as risk of transition seems particularly high in those with an even higher severity of certain symptoms such as suspiciousness or anhedonia, in those with lower global or social functioning, poor neurocognitive performance or cannabis abuse. Also, electroencephalography, neuroimaging and blood biomarkers might contribute to improving individual prediction. The most promising approach certainly is a staged multidomain assessment. Risk calculators to integrate all data for an individualized prediction are being developed.

SUMMARY

Prediction of psychosis is already possible with an excellent prognostic performance based on clinical assessments. Recent studies show that this accuracy can be further improved by using multidomain approaches and modern statistics for individualized prediction. The challenge now is the translation into the clinic with a broad clinical implementation.

The Role of Cognition and Social Functioning as Predictors in the Transition to Psychosis for Youth With Attenuated Psychotic Symptoms

In the literature, there have been several attempts to develop prediction models for youth who are at clinical high risk (CHR) of developing psychosis. Although there are no specific clinical or demographic variables that seem to consistently predict the later transition to psychosis in those CHR youth, in addition to attenuated psychotic symptoms, the most commonly occuring predictors tend to be poor social functioning and certain cognitive tasks. Unfortunately, there has been little attempt to replicate alogorithms. A recently published article by Cornblatt et al suggested that, for individuals with attentuated psychotic symptoms (APS), disorganized communication, suspiciousness, verbal memory, and a decline in social functioning were the best predictors of later transition to psychosis (the RAP model). The purpose of this article was to first test the prediction model of Cornblatt et al with a new sample of individuals with APS from the PREDICT study. The RAP model was not the best fit for the PREDICT data. However, using other variables from PREDICT, it was demonstrated that unusual thought content, disorganized communication, baseline social functioning, verbal fluency, and memory, processing speed and age were predictors of later transition to psychosis in the PREDICT sample. Although the predictors were different in these 2 models, both supported that disorganized communication, poor social functioning, and verbal memory, were good candidates as predictors for later conversion to psychosis.

Personalized Prediction of Psychosis: External Validation of the NAPLS-2 Psychosis Risk Calculator With the EDIPPP Project

OBJECTIVE

As part of the second phase of the North American Prodrome Longitudinal Study (NAPLS-2), Cannon and colleagues report, concurrently with the present article, on a risk calculator for the individualized prediction of a psychotic disorder in a 2-year period. The present study represents an external validation of the NAPLS-2 psychosis risk calculator using an independent sample of patients at clinical high risk for psychosis collected as part of the Early Detection, Intervention, and Prevention of Psychosis Program (EDIPPP).

METHOD

Of the total EDIPPP sample of 210 subjects rated as being at clinical high risk based on the Structured Interview for Prodromal Syndromes, 176 had at least one follow-up assessment and were included in the construction of a new prediction model with six predictor variables in the NAPLS-2 psychosis risk calculator (unusual thoughts and suspiciousness, symbol coding test performance, verbal learning test performance, decline in social functioning, baseline age, and family history). Discrimination performance was assessed with the area under the receiver operating characteristic curve (AUC). The NAPLS-2 risk calculator was then used to generate a psychosis risk estimate for each case in the external validation sample.

RESULTS

The external validation model showed good discrimination, with an AUC of 0.790 (95% CI=0.644-0.937). In addition, the personalized risk generated by the risk calculator provided a solid estimation of the actual conversion outcome in the validation sample.

CONCLUSIONS

Two independent samples of clinical high-risk patients converge to validate the NAPLS-2 psychosis risk calculator. This prediction calculator represents a meaningful step toward early intervention and the personalized treatment of psychotic disorders.

Idea density in the life-stories of people with schizophrenia: Associations with narrative qualities and psychiatric symptoms

Disordered speech and language deficits are well-documented in schizophrenia-spectrum disorders. Researchers often assess speech samples using manualized rating systems, though recently computerized language assessment methods have been used more frequently in the study of speech from people with schizophrenia. Most typically, these computerized assessments measure aspects of expressivity (i.e., pause durations, prosody) or use word-count technology; less attention has focused on similar methods that can capture more sophisticated aspects of linguistic complexity (e.g., idea density). The primary objective of the present study was to assess idea density - via a computerized measure - in the life-story narratives of people with schizophrenia (n=32) compared to a group of community control participants (n=15). In the schizophrenia group, we also examined associations between idea density, narrative qualities rated via a manualized measure, and psychiatric symptoms. Our findings indicate that idea density is diminished in individuals with schizophrenia compared to controls. Further, our results suggest that though people with schizophrenia with richer idea density tended to have more developed insight into illness, they also had higher levels of depression, anxiety, and avolition. Implications of these results and suggestions for future research are discussed.