Symptom trajectories and psychosis onset in a clinical high-risk cohort: the relevance of subthreshold thought disorder

Emotional tone in clinical high risk for psychosis: novel insights from a natural language analysis approach

Background

Individuals at clinical high risk (CHR) for psychosis experience subtle emotional disturbances that are traditionally difficult to assess, but natural language processing (NLP) methods may provide novel insight into these symptoms. We predicted that CHR individuals would express more negative emotionality and less emotional language when compared to controls. We also examined associations with symptomatology.

Methods

Participants included 49 CHR individuals and 42 healthy controls who completed a semi-structured narrative interview. Interview transcripts were analyzed using Linguistic Inquiry and Word Count (LIWC) to assess the emotional tone of the language (tone -the ratio of negative to positive language) and count positive/negative words used. Participants also completed clinical symptom assessments to determine CHR status and characterize symptoms (i.e., positive and negative symptom domains).

Results

The CHR group had more negative emotional tone compared to healthy controls (t=2.676, p=.009), which related to more severe positive symptoms (r2=.323, p=.013). The percentages of positive and negative words did not differ between groups (p's>.05).

Conclusions

Language analyses provided accessible, ecologically valid insight into affective dysfunction and psychosis risk symptoms. Natural language processing analyses unmasked differences in language for CHR that captured language tendencies that were more nuanced than the words that are chosen.

Differences in the neural correlates of schizophrenia with positive and negative formal thought disorder in patients with schizophrenia in the ENIGMA dataset

Formal thought disorder (FTD) is a clinical key factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, the relationship between FTD symptom dimensions and patterns of regional brain volume loss in schizophrenia remains to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles by enrolling a large multi-site cohort acquired by the ENIGMA Schizophrenia Working Group (752 schizophrenia patients and 1256 controls), to unravel the neuroanatomy of FTD in schizophrenia and using virtual histology tools on implicated brain regions to investigate the cellular basis. Based on the findings of previous clinical and neuroimaging studies, we decided to separately explore positive, negative and total formal thought disorder. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but positive and negative FTD demonstrated a dissociation: negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD also showed associations with microglial cell types. These results provide an important step towards linking FTD to brain structural changes and their cellular underpinnings, providing an avenue for a better mechanistic understanding of this syndrome.

Network Meta-Analysis Indicates Superior Effects of Omega-3 Polyunsaturated Fatty Acids in Preventing the Transition to Psychosis in Individuals at Clinical High-Risk

BACKGROUND

The efficacy of pharmacological and nutritional interventions in individuals at clinical high risk for psychosis (CHR-P) remains elusive. This study aims to investigate the efficacy of pharmacological and nutritional interventions in CHR-P and whether these interventions can enhance the efficacy of psychological treatments.

METHODS

We systematically reviewed data from 5 databases until July 24, 2021: PubMed, Web of Science, EMBASE, China National Knowledge Infrastructure, and WanFang Data. The primary outcome was the transition to psychosis. Network meta-analyses were conducted at 3 time points (6, 12, and ≥24 months) considering both pharmacological/nutritional interventions alone and its combination with psychotherapy.

RESULTS

Out of 11 417 identified references, 21 studies were included, comprising 1983 participants. CHR-P participants receiving omega-3 polyunsaturated fatty acids treatment were associated with a lower probability of transition compared with placebo/control at 6 months (odds ratio [OR] = 0.07, 95% confidence interval [CI] = .01 to .054), 12 months (OR = 0.14, 95% CI = .03 to .66), and ≥24 months (OR = 0.16, 95% CI = .05 to .54). Moreover, risperidone plus psychotherapy was associated with a lower likelihood of transition at 6 months compared with placebo/control plus psychotherapy, but this result was not sustained over longer durations.

CONCLUSION

Omega-3 polyunsaturated fatty acids helped in preventing transitions to psychosis compared with controls.

PROSPERO REGISTRATION NUMBER

CRD42021256209.

20-Year trajectories of six psychopathological dimensions in patients with first-episode psychosis: Could they be predicted?

Patients with first-episode psychoses (FEP) exhibit heterogeneity in clinical manifestations and outcomes. This study investigated the long-term trajectories of six key psychopathological dimensions (reality-distortion, negative, disorganization, catatonia, mania and depression) in patients diagnosed with FEP. A total of 243 patients were followed up for 20 years and the trajectories of the dimensions were analysed using growth mixture modelling. These dimensions showed varied course patterns, ranging from two to five trajectories. Additionally, the study examined the predictive value of different factors in differentiating between the long-term trajectories. The exposome risk score showed that familial load, distal and intermediate risk factors, acute psychosocial stressors and acute onset were significant predictors for differentiating between long-term psychopathological trajectories. In contrast, polygenic risk score, duration of untreated psychosis and duration of untreated illness demonstrated little or no predictive value. The findings highlight the importance of conducting a multidimensional assessment not only at FEP but also during follow-up to customize the effectiveness of interventions. Furthermore, the results emphasize the relevance of assessing premorbid predictors from the onset of illness. This may enable the identification of FEP patients at high-risk of poor long-term outcomes who would benefit from targeted prevention programs on specific psychopathological dimensions.

Predicting new onset thought disorder in early adolescence with optimized deep learning implicates environmental-putamen interactions

Background

Thought disorder (TD) is a sensitive and specific marker of risk for schizophrenia onset. Specifying factors that predict TD onset in adolescence is important to early identification of youth at risk. However, there is a paucity of studies prospectively predicting TD onset in unstratified youth populations.

Study Design

We used deep learning optimized with artificial intelligence (AI) to analyze 5,777 multimodal features obtained at 9-10 years from youth and their parents in the ABCD study, including 5,014 neural metrics, to prospectively predict new onset TD cases at 11-12 years. The design was replicated for all prevailing TD cases at 11-12 years.

Study Results

Optimizing performance with AI, we were able to achieve 92% accuracy and F1 and 0.96 AUROC in prospectively predicting the onset of TD in early adolescence. Structural differences in the left putamen, sleep disturbances and the level of parental externalizing behaviors were specific predictors of new onset TD at 11-12 yrs, interacting with low youth prosociality, the total parental behavioral problems and parent-child conflict and whether the youth had already come to clinical attention. More important predictors showed greater inter-individual variability.

Conclusions

This study provides robust person-level, multivariable signatures of early adolescent TD which suggest that structural differences in the left putamen in late childhood are a candidate biomarker that interacts with psychosocial stressors to increase risk for TD onset. Our work also suggests that interventions to promote improved sleep and lessen parent-child psychosocial stressors are worthy of further exploration to modulate risk for TD onset.

Neural Correlates of Positive and Negative Formal Thought Disorder in Individuals with Schizophrenia: An ENIGMA Schizophrenia Working Group Study

Formal thought disorder (FTD) is a key clinical factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, relationship between FTD symptom dimensions and patterns of regional brain volume deficiencies in schizophrenia remain to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles based on a large multi-site cohort through the ENIGMA Schizophrenia Working Group (752 individuals with schizophrenia and 1256 controls), to unravel the neuroanatomy of positive, negative and total FTD in schizophrenia and their cellular bases. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks for positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD was also linked to microglial cell types. These findings relate different dimensions of FTD to distinct brain structural changes and their cellular underpinnings, improve our mechanistic understanding of these key psychotic symptoms.

Perspective on clinical high-risk for psychosis in Africa

Clinical High Risk for Psychosis has evolved in recent years as a conceptual and clinical entity, representing a shift in focus from the syndromal psychosis state to a recognition of the pre-psychotic state as a period of potential preventive intervention. Much existing evidence has been generated from well-resourced countries, with a more limited body of literature available from Africa and other Majority World countries. Against a backdrop of prevailing systemic challenges, it is necessary to appraise the state of knowledge on Clinical High Risk for Psychosis in Africa. In this perspective article, we cover epidemiology, risk factors, predictors of psychosis conversion, as well as an overview of sociocultural factors, notably stigma, and the barriers to mental health services in African settings. We discuss existing and promising assessment approaches and reflect on preventive and early intervention strategies. We conclude with recommendations including the need for more clinical, longitudinal, and collaborative research anchored in an integrative transdisciplinary approach. We highlight the need for more culturally valid assessment tools and strategies to improve access to and utilization of services while also reducing stigma.

The SPEAK study rationale and design: A linguistic corpus-based approach to understanding thought disorder

AIM

Psychotic symptoms are typically measured using clinical ratings, but more objective and sensitive metrics are needed. Hence, we will assess thought disorder using the Research Domain Criteria (RDoC) heuristic for language production, and its recommended paradigm of "linguistic corpus-based analyses of language output". Positive thought disorder (e.g., tangentiality and derailment) can be assessed using word-embedding approaches that assess semantic coherence, whereas negative thought disorder (e.g., concreteness, poverty of speech) can be assessed using part-of-speech (POS) tagging to assess syntactic complexity. We aim to establish convergent validity of automated linguistic metrics with clinical ratings, assess normative demographic variance, determine cognitive and functional correlates, and replicate their predictive power for psychosis transition among at-risk youths.

METHODS

This study will assess language production in 450 English-speaking individuals in Australia and Canada, who have recent onset psychosis, are at clinical high risk (CHR) for psychosis, or who are healthy volunteers, all well-characterized for cognition, function and symptoms. Speech will be elicited using open-ended interviews. Audio files will be transcribed and preprocessed for automated natural language processing (NLP) analyses of coherence and complexity. Data analyses include canonical correlation, multivariate linear regression with regularization, and machine-learning classification of group status and psychosis outcome.

CONCLUSIONS

This prospective study aims to characterize language disturbance across stages of psychosis using computational approaches, including psychometric properties, normative variance and clinical correlates, important for biomarker development. SPEAK will create a large archive of language data available to other investigators, a rich resource for the field.

Do antidepressants prevent transition to psychosis in individuals at clinical high-risk (CHR-P)? Systematic review and meta-analysis

BACKGROUND

Emerging meta-analytical evidence indicates that baseline exposure to antipsychotics in individuals at clinical high-risk for psychosis (CHR-P) is associated with a higher risk of an imminent transition to psychosis. Despite their tolerability profile and potential beneficial effects, baseline exposure to antidepressants (AD) in CHR-P has surprisingly received far less attention as a potential risk modulator for transition to psychosis. The current systematic review and meta-analysis were performed to fix such a knowledge gap.

METHODS

Systematic scrutiny of Medline and Cochrane library, performed up to 1 August 2021, searching for English-language studies on CHR-P reporting numeric data about the sample, the transition outcome at a predefined follow-up time and raw data on AD baseline exposure in relation to such outcome.

RESULTS

Of 1942 identified records, 16 studies were included in the systematic review and meta-analysis. 26% of the participants were already exposed to AD at baseline; at the end of the follow-up 13.5% (95% CI 10.2-17.1%) of them (n = 448) transitioned to psychosis against 21.0% (18.9 to 23.3%) of non-AD exposed CHR-P (n = 1371). CHR-P participants who were already under AD treatment at baseline had a lower risk of transition than non-AD exposed CHR-P. The RR was 0.71 (95% CI 0.56-0.90) in the fixed-effects model (z = -2.79; p = 0.005), and 0.78 (0.58-1.05) in the random-effects model (z = -1.77; p = 0.096; tau-squared = 0.059). There was no relevant heterogeneity (Cochran's Q = 18.45; df = 15; p = 0.239; I2 = 18.7%).

CONCLUSIONS

Ongoing AD exposure at inception in CHR-P is associated to a reduced risk of transition to psychosis at follow up.

Neural Correlates of Positive and Negative Formal Thought Disorder in Individuals with Schizophrenia: An ENIGMA Schizophrenia Working Group Study

Formal thought disorder (FTD) is a key clinical factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, relationship between FTD symptom dimensions and patterns of regional brain volume deficiencies in schizophrenia remain to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles based on a large multi-site cohort through the ENIGMA Schizophrenia Working Group (752 individuals with schizophrenia and 1256 controls), to unravel the neuroanatomy of positive, negative and total FTD in schizophrenia and their cellular bases. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks for positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD was also linked to microglial cell types. These findings relate different dimensions of FTD to distinct brain structural changes and their cellular underpinnings, improve our mechanistic understanding of these key psychotic symptoms.

Linguistic markers of psychosis in Mandarin Chinese: Relations to theory of mind

Disorganized and impoverished language is a key feature of schizophrenia (Sz), but whether and which linguistic changes previously observed in Indo-European languages generalize to other languages remains unclear. Targeting Mandarin Chinese, we aimed to profile aspects of grammatical complexity that we hypothesized would be reduced in schizophrenia in a task of verbalizing social events. 51 individuals with Sz and 39 controls participated in the animated triangles task, a standardized measure of theory of mind (ToM), in which participants describe triangles moving in either a random or an 'intentional' condition. Results revealed that clauses embedded as arguments in other clauses were reduced in Sz, and that both groups produced such clauses and grammatical aspect more frequently in the intentional condition. ToM scores specifically correlated with production of embedded argument clauses. These results document grammatical impoverishment in Sz in Chinese across several structural domains, which in some of its specific aspects relate to mentalizing performance.

The temporal dynamics of transition to psychosis in individuals at clinical high-risk (CHR-P) shows negative prognostic effects of baseline antipsychotic exposure: a meta-analysis

Meta-analytic evidence indicates that baseline exposure to antipsychotics (AP) in individuals at clinical high-risk for psychosis (CHR-P) is associated with an even higher risk of transition to psychosis. However, the temporal dynamics of such prognostic effect have not been clarified yet. This study was therefore designed to address this knowledge gap. We performed a systematic review and meta-analysis of all longitudinal studies published up to 31 December 2021 on CHR-P individuals identified according to a validated diagnostic procedure and reporting numeric data of transition to psychosis according to baseline antipsychotic exposure. 28 studies covering a total of 2405 CHR-P were included. 554 (23.0%) were exposed to AP at baseline, whereas 1851 (77.0%) were not. At follow-up (12 to 72 months), 182 individuals among AP-exposed (32.9%; 95% CI: 29.4% to 37.8%) and 382 among AP-naive CHR-P (20.6%; 18.8% to 22.8%) developed psychosis. Transition rates increased over time, with the best-fit for an ascending curve peaking at 24 months and reaching then a plateau, with a further increase at 48 months. Baseline AP-exposed CHR-P had higher transition risk at 12 months and then again at 36 and 48 months, with an overall higher risk of transition (fixed-effect model: risk ratio = 1.56 [95% CI: 1.32-1.85]; z = 5.32; p < 0.0001; Random-effect model: risk ratio = 1.56 [95% CI: 1.07-2.26]; z = 2.54; p = 0.0196). In conclusion, the temporal dynamics of transition to psychosis differ in AP-exposed vs. AP-naive CHR-P. Baseline AP exposure in CHR-P is associated with a persistently higher risk of transition at follow up, supporting the rationale for more stringent clinical monitoring in AP-exposed CHR-P. The insufficiency of more granular information in available primary literature (e.g., temporal and quantitative details of AP exposure as well as psychopathological dimensions in CHR-P) did not allow the testing of causal hypotheses on this negative prognostic association.

Language Network Dysfunction and Formal Thought Disorder in Schizophrenia

BACKGROUND

Pathophysiological inquiries into schizophrenia require a consideration of one of its most defining features: disorganization and impoverishment in verbal behavior. This feature, often captured using the term Formal Thought Disorder (FTD), still remains to be one of the most poorly understood and understudied dimensions of schizophrenia. In particular, the large-scale network level dysfunction that contributes to FTD remains obscure to date.

STUDY DESIGN

In this narrative review, we consider the various challenges that need to be addressed for us to move towards mapping FTD (construct) to a brain network level account (circuit).

STUDY RESULTS

The construct-to-circuit mapping goal is now becoming more plausible than it ever was, given the parallel advent of brain stimulation and the tools providing objective readouts of human speech. Notwithstanding this, several challenges remain to be overcome before we can decisively map the neural basis of FTD. We highlight the need for phenotype refinement, robust experimental designs, informed analytical choices, and present plausible targets in and beyond the Language Network for brain stimulation studies in FTD.

CONCLUSIONS

Developing a therapeutically beneficial pathophysiological model of FTD is a challenging endeavor, but holds the promise of improving interpersonal communication and reducing social disability in schizophrenia. Addressing the issues raised in this review will be a decisive step in this direction.

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.

Negative Symptom Trajectories in Individuals at Clinical High Risk for Psychosis: Differences Based on Deficit Syndrome, Persistence, and Transition Status

Background and Hypothesis

Negative symptom trajectory in clinical high risk (CHR) for psychosis is ill defined. This study aimed to better characterize longitudinal patterns of change in negative symptoms, moderators of change, and differences in trajectories according to clinical subgroups. We hypothesized that negative symptom course will be nonlinear in CHR. Clinical subgroups known to be more severe variants of psychotic illness-deficit syndrome (DS), persistent negative syndrome (PNS), and acute psychosis onset-were expected to show more severe baseline symptoms, slower rates of change, and less stable rates of symptom resolution.

Study Design

Linear, curvilinear, and stepwise growth curve models, with and without moderators, were fitted to negative symptom ratings from the NAPLS-3 CHR dataset (N = 699) and within clinical subgroups.

Study Results

Negative symptoms followed a downward curvilinear trend, with marked improvement 0-6 months that subsequently stabilized (6-24 months), particularly among those with lower IQ and functioning. Clinical subgroups had higher baseline ratings, but distinct symptom courses; DS vs non-DS: more rapid initial improvement, similar stability of improvements; PNS vs non-PNS: similar rates of initial improvement and stability; transition vs no transition: slower rate of initial improvement, with greater stability of this rate.

Conclusions

Continuous, frequent monitoring of negative symptoms in CHR is justified by 2 important study implications: (1) The initial 6 months of CHR program enrollment may be a key window for improving negative symptoms as less improvement is likely afterwards, (2) Early identification of clinical subgroups may inform distinct negative symptom trajectories and treatment needs.

Language abnormalities in schizophrenia: binding core symptoms through contemporary empirical evidence

Both the ability to speak and to infer complex linguistic messages from sounds have been claimed as uniquely human phenomena. In schizophrenia, formal thought disorder (FTD) and auditory verbal hallucinations (AVHs) are manifestations respectively relating to concrete disruptions of those abilities. From an evolutionary perspective, Crow (1997) proposed that "schizophrenia is the price that Homo sapiens pays for the faculty of language". Epidemiological and experimental evidence points to an overlap between FTD and AVHs, yet a thorough investigation examining their shared neural mechanism in schizophrenia is lacking. In this review, we synthesize observations from three key domains. First, neuroanatomical evidence indicates substantial shared abnormalities in language-processing regions between FTD and AVHs, even in the early phases of schizophrenia. Second, neurochemical studies point to a glutamate-related dysfunction in these language-processing brain regions, contributing to verbal production deficits. Third, genetic findings further show how genes that overlap between schizophrenia and language disorders influence neurodevelopment and neurotransmission. We argue that these observations converge into the possibility that a glutamatergic dysfunction in language-processing brain regions might be a shared neural basis of both FTD and AVHs. Investigations of language pathology in schizophrenia could facilitate the development of diagnostic tools and treatments, so we call for multilevel confirmatory analyses focused on modulations of the language network as a therapeutic goal in schizophrenia.

Cognitive Patterns and Conversion in a Representative Sample of Individuals at Risk for Psychosis

ABSTRACT

Clinical high-risk (CHR) individuals belong to a heterogeneous group, of which only a few will cross the threshold for a clinical diagnosis. Cognitive disturbances are present in CHR subjects and may be indicative of transition. Our study aims to identify such deficits in a representative CHR for psychosis sample. Our sample comprised 92 CHR individuals and 54 controls from a representative cohort of the general population. They were followed up for a mean of 2.5 years, with 15 individuals converting to schizophrenia or other Diagnostic and Statistical Manual of Mental Disorders, 5th Edition diagnoses. Neurocognitive assessment was performed with the University of Pennsylvania Computerized Neuropsychological Testing, and CHR status was assessed with the Structured Interview for Prodromal Syndromes (SIPS). Baseline scores were entered in a latent profile analysis model. Our study brought forward a four-class model on cognitive performance. One class displayed better performance, whereas the other three performed worse, all compared with controls. The class with lower executive function also had the highest score on disorganized communication (SIPS P5 = 1.36, p < 0.05), although unrelated to conversion. Among the low performers, the class significantly related to conversion (p = 0.023) had the highest score in decreased expression of emotion (SIPS N3 = 0.85, p < 0.05). Our study brings new and relevant data on non-help-seeking CHR individuals and the relationship between cognitive patterns and conversion. We have highlighted a specific cognitive signature, associated with negative symptoms, which represents a stable trait with presumed lower conversion to a psychiatric illness.

Abnormal oligodendrocyte function in schizophrenia explains the long latent interval in some patients

A puzzling feature of schizophrenia, is the long latency between the beginning of neuropathological changes and the clinical presentation that may be two decades later. Abnormalities in oligodendrocyte function may explain this latency, because mature oligodendrocytes produce myelination, and if myelination were abnormal from the outset, it would cause the synaptic dysfunction and abnormal neural tracts that are underpinning features of schizophrenia. The hypothesis is that latency is caused by events that occur in some patients as early as in-utero or infancy, because clones of abnormal, myelinating oligodendrocytes may arise at that time; their number doubles every ~2 years, so their geometric increase between birth and age twenty, when clinical presentation occurs, is about 1000-fold plus the effect of compounding. For those patients in particular, the long latency is because of a small but ongoing increase in volume of the resulting, abnormally myelinated neural tracts until, after a long latent interval, a critical mass is reached that allows the full clinical features of schizophrenia. During latency, there may be behavioral aberrancies because of abnormally myelinated neural tracts but they are insufficiently numerous for the clinical syndrome. The occurrence of behavioral symptoms during the long latent period, substantiates the hypothesis that abnormal oligodendrocytes explain the latency in some patients. Treatment with fingolimod or siponimod benefits both oligodendrocytes and neural tracts. Clinical trial would validate their potential benefit in appropriate patients with schizophrenia and, concurrently, would validate the hypothesis.

Association between formal thought disorders, neurocognition and functioning in the early stages of psychosis: a systematic review of the last half-century studies

Recent review articles provided an extensive collection of studies covering many aspects of format thought disorders (FTD) among their epidemiology and phenomenology, their neurobiological underpinnings, genetics as well as their transdiagnostic prevalence. However, less attention has been paid to the association of FTD with neurocognitive and functioning deficits in the early stages of evolving psychosis. Therefore, this systematic review aims to investigate the state of the art regarding the association between FTD, neurocognition and functioning in the early stages of evolving psychotic disorders in adolescents and young adults, by following the PRISMA flowchart. A total of 106 studies were screened. We included 8 studies due to their reports of associations between FTD measures and functioning outcomes measured with different scales and 7 studies due to their reports of associations between FTD measures and neurocognition. In summary, the main findings of the included studies for functioning outcomes showed that FTD severity predicted poor social functioning, unemployment, relapses, re-hospitalisations, whereas the main findings of the included studies for neurocognition showed correlations between attentional deficits, executive functions and FTD, and highlighted the predictive potential of executive dysfunctions for sustained FTD. Further studies in upcoming years taking advantage of the acceleration in computational psychiatry would allow researchers to re-investigate the clinical importance of FTD and their role in the transition from at-risk to full-blown psychosis conditions. Employing automated computer-assisted diagnostic tools in the early stages of psychosis might open new avenues to develop targeted neuropsychotherapeutics specific to FTD.

The role of white matter abnormality in the left anterior corona radiata: In relation to formal thought disorder in patients with schizophrenia

White matter abnormality has been widely reported in patients with schizophrenia (Sz). However, few studies have focused on the relationship between the white matter deficit and formal thought disorder (FTD). Moreover, the role of genetic high risk in FTD-related white matter deficit remains unclear. The present study recruited 46 Sz patients, 18 unaffected first-degree relatives of Sz patients, and 29 healthy controls. There was a widespread fractional anisotropy (FA) reduction in Sz. In addition, reduced FA in the left anterior corona radiata was related to more severe FTD symptoms in Sz. However, the genetic high-risk group only showed lower mean FA in the left anterior limb of the internal capsule than healthy controls. Our findings suggest that abnormality in the left anterior corona radiata may only occur in Sz but not in the genetic high-risk group. Such an abnormality might be associated with the severity of FTD symptoms. Meanwhile, genetic vulnerability may contribute to the abnormality in the left anterior limb of the internal capsule. Better analytical methods are needed to validate our results.

Dissecting the neurobiology of linguistic disorganisation and impoverishment in schizophrenia

Schizophrenia provides a quintessential disease model of how disturbances in the molecular mechanisms of neurodevelopment lead to disruptions in the emergence of cognition. The central and often persistent feature of this illness is the disorganisation and impoverishment of language and related expressive behaviours. Though clinically more prominent, the periodic perceptual distortions characterised as psychosis are non-specific and often episodic. While several insights into psychosis have been gained based on study of the dopaminergic system, the mechanistic basis of linguistic disorganisation and impoverishment is still elusive. Key findings from cellular to systems-level studies highlight the role of ubiquitous, inhibitory processes in language production. Dysregulation of these processes at critical time periods, in key brain areas, provides a surprisingly parsimonious account of linguistic disorganisation and impoverishment in schizophrenia. This review links the notion of excitatory/inhibitory (E/I) imbalance at cortical microcircuits to the expression of language behaviour characteristic of schizophrenia, through the building blocks of neurochemistry, neurophysiology, and neurocognition.

Cognitive correlates of 'Formal Thought Disorder' in a non-clinical sample with elevated schizotypal traits

Different dimensions of formal thought disorder (FTD) are distinguished by different patterns of cognitive dysfunction in patients with schizophrenia; however, inconsistent findings may relate to patient-related confounds. To avoid these confounds, we examined relationships between FTD dimensions and cognitive domains in a non-clinical sample with attenuated schizophrenia-like traits, or schizotypal traits, on the Schizotypal Personality Questionnaire (N = 91). To our knowledge, no study has done this. FTD dimension scores were derived following principal component analysis of the Scale for the Assessment of Thought, Language and Communication (TLC dimensions: Disorganisation, Verbosity, Emptiness) and the Thought and Language Index (TLI dimensions: Negative, Idiosyncratic). The sample completed a comprehensive neuropsychological battery. Findings indicate that higher-order reasoning, executive function (set shift and generative ability) and language/semantic functioning are the primary drivers of FTD in our non-clinical sample with elevated schizotypal traits, in line with schizophrenia research. FTD may have shared aetiology along the schizophrenia spectrum.

Prediction of clinical outcomes beyond psychosis in the ultra-high risk for psychosis population

AIM

Several prediction models have been introduced to identify young people at greatest risk of transitioning to psychosis. To date, none has examined the possibility of developing a clinical prediction model of outcomes other than transition. The aims of this study were to examine the association between baseline clinical predictors and outcomes including, but not limited to, transition to psychosis in young people at risk for psychosis, and to develop a prediction model for these outcomes.

METHODS

Several evidence-based variables previously associated with transition to psychosis and some important clinical comorbidities experienced by ultra-high risk (UHR) individuals were identified in 202 UHR individuals. Secondary analysis of the Neurapro clinical trial were conducted to investigate the associations between these variables and favourable (remission and recovery) or unfavourable (transition to psychosis, no remission, any recurrence and relapse) clinical outcomes. Logistic regression, best subset selection, Akaike Information Criterion and receiver operating characteristic curves were used to seek the best prediction model for clinical outcomes from all combinations of possible predictors.

RESULTS

When considered individually, only higher general psychopathology levels (P = .023) was associated with the unfavourable outcomes. Prediction models suggest that general psychopathology and functioning are predictive of unfavourable outcomes.

CONCLUSION

The predictive performance of the resulting models was modest and further research is needed. Nonetheless, when designing early intervention centres aiming to support individuals in the early phases of a mental disorder, the proper assessment of general psychopathology and functioning should be considered in order to inform interventions and length of care provided.

Negative Prognostic Effect of Baseline Antipsychotic Exposure in Clinical High Risk for Psychosis (CHR-P): Is Pre-Test Risk Enrichment the Hidden Culprit?

INTRODUCTION

Sample enrichment is a key factor in contemporary early-detection strategies aimed at the identification of help-seekers at increased risk of imminent transition to psychosis. We undertook a meta-analytic investigation to ascertain the role of sample enrichment in the recently highlighted negative prognostic effect of baseline antipsychotic (AP) exposure in clinical high-risk (CHR-P) of psychosis individuals.

METHODS

Systematic review and meta-analysis of all published studies on CHR-P were identified according to a validated diagnostic procedure. The outcome was the proportion of transition to psychosis, which was calculated according to the Freeman-Tukey double arcsine transformation.

RESULTS

Thirty-three eligible studies were identified, including 16 samples with details on AP exposure at baseline and 17 samples with baseline AP exposure as exclusion criterion for enrollment. Those with baseline exposure to AP (n = 395) had higher transition rates (29.9%; 95% CI: 25.1%-34.8%) than those without baseline exposure to AP in the same study (n = 1289; 17.2%; 15.1%-19.4%) and those coming from samples that did not include people who were exposed to AP at baseline (n = 2073; 16.2%; 14.6%-17.8%; P < .05 in both the fixed-effects and the random-effects models). Heterogeneity within studies was substantial, with values above 75% in all comparisons.

CONCLUSIONS

Sample enrichment is not a plausible explanation for the higher risk of transition to psychosis of CHR-P individuals who were already exposed to AP at the enrollment in specialized early-detection programs. Baseline exposure to AP at CHR-P assessment is a major index of enhanced, imminent risk of psychosis.

Neurobiological substrates of the positive formal thought disorder in schizophrenia revealed by seed connectome-based predictive modeling

•

Formal thought disorder (FTD) is a core symptom of schizophrenia, but its neurobiological substrates remain elusive.

•

Resting-state functional connectivity (rsFC) of three meta-analytically defined seeds were correlated to positive and negative symptom dimensions of FTD.

•

RsFC patterns allowed individual prediction of positive FTD symptom severity.

•

These findings generalized to an independent data set.

•

Our study has identified robust neurobiological correlates of positive FTD in schizophrenia.

Formal thought disorder (FTD) is a core symptom cluster of schizophrenia, but its neurobiological substrates remain poorly understood. Here we collected resting-state fMRI data from 276 subjects at seven sites and employed machine-learning to investigate the neurobiological correlates of FTD along positive and negative symptom dimensions in schizophrenia. Three a priori, meta-analytically defined FTD-related brain regions were used as seeds to generate whole-brain resting-state functional connectivity (rsFC) maps, which were then compared between schizophrenia patients and controls. A repeated cross-validation procedure was realized within the patient group to identify clusters whose rsFC patterns to the seeds were repeatedly observed as significantly associated with specific FTD dimensions. These repeatedly identified clusters (i.e., robust clusters) were functionally characterized and the rsFC patterns were used for predictive modeling to investigate predictive capacities for individual FTD dimensional-scores. Compared with controls, differential rsFC was found in patients in fronto-temporo-thalamic regions. Our cross-validation procedure revealed significant clusters only when assessing the seed-to-whole-brain rsFC patterns associated with positive-FTD. RsFC patterns of three fronto-temporal clusters, associated with higher-order cognitive processes (e.g., executive functions), specifically predicted individual positive-FTD scores (p = 0.005), but not other positive symptoms, and the PANSS general psychopathology subscale (p > 0.05). The prediction of positive-FTD was moreover generalized to an independent dataset (p = 0.013). Our study has identified neurobiological correlates of positive FTD in schizophrenia in a network associated with higher-order cognitive functions, suggesting a dysexecutive contribution to FTD in schizophrenia. We regard our findings as robust, as they allow a prediction of individual-level symptom severity.

Forecasting Remission From the Psychosis Risk Syndrome With Mismatch Negativity and P300: Potentials and Pitfalls

Clinical outcomes vary for individuals at clinical high risk (CHR) for psychosis, ranging from conversion to a psychotic disorder to full remission from the risk syndrome. Given that most CHR individuals do not convert to psychosis, recent research efforts have turned toward identifying specific predictors of CHR remission, a task that is conceptually and empirically dissociable from the identification of predictors of conversion to psychosis, and one that may reveal specific biological characteristics that confer resilience to psychosis and provide further insights into the mechanisms associated with the pathogenesis of schizophrenia and those underlying a transient CHR syndrome. Such biomarkers may ultimately facilitate the development of novel early interventions and support the optimization of individualized care. In this review, we focus on two event-related brain potential measures, mismatch negativity and P300, that have attracted interest as predictors of future psychosis among CHR individuals. We describe several recent studies examining whether mismatch negativity and P300 predict subsequent CHR remission and suggest that intact mismatch negativity and P300 may reflect the integrity of specific neurocognitive processes that confer resilience against the persistence of the CHR syndrome and its associated risk for future transition to psychosis. We also highlight several major methodological concerns associated with these studies that apply to the broader literature examining predictors of CHR remission. Among them is the concern that studies that predict dichotomous remission versus nonremission and/or dichotomous conversion versus nonconversion outcomes potentially confound remission and conversion effects, a phenomenon we demonstrate with a data simulation.

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.

Meta-analyzing the prevalence and prognostic effect of antipsychotic exposure in clinical high-risk (CHR): when things are not what they seem

BACKGROUND

The clinical high-risk (CHR) for psychosis paradigm is changing psychiatric practice. However, a widespread confounder, i.e. baseline exposure to antipsychotics (AP) in CHR samples, is systematically overlooked. Such exposure might mitigate the initial clinical presentation, increase the heterogeneity within CHR populations, and confound the evaluation of transition to psychosis at follow-up. This is the first meta-analysis examining the prevalence and the prognostic impact on transition to psychosis of ongoing AP treatment at baseline in CHR cohorts.

METHODS

Major databases were searched for articles published until 20 April 2020. The variance-stabilizing Freeman-Tukey double arcsine transformation was used to estimate prevalence. The binary outcome of transition to psychosis by group was estimated with risk ratio (RR) and the inverse variance method was used for pooling.

RESULTS

Fourteen studies were eligible for qualitative synthesis, including 1588 CHR individuals. Out of the pooled CHR sample, 370 individuals (i.e. 23.3%) were already exposed to AP at the time of CHR status ascription. Transition toward full-blown psychosis at follow-up intervened in 112 (29%; 95% CI 24-34%) of the AP-exposed CHR as compared to 235 (16%; 14-19%) of the AP-naïve CHR participants. AP-exposed CHR had higher RR of transition to psychosis (RR = 1.47; 95% CI 1.18-1.83; z = 3.48; p = 0.0005), without influence by age, gender ratio, overall sample size, duration of the follow-up, or quality of the studies.

CONCLUSIONS

Baseline AP exposure in CHR samples is substantial and is associated with a higher imminent risk of transition to psychosis. Therefore, such exposure should be regarded as a non-negligible red flag for clinical risk management.

Language as a biomarker for psychosis: A natural language processing approach

Human ratings of conceptual disorganization, poverty of content, referential cohesion and illogical thinking have been shown to predict psychosis onset in prospective clinical high risk (CHR) cohort studies. The potential value of linguistic biomarkers has been significantly magnified, however, by recent advances in natural language processing (NLP) and machine learning (ML). Such methodologies allow for the rapid and objective measurement of language features, many of which are not easily recognized by human raters. Here we review the key findings on language production disturbance in psychosis. We also describe recent advances in the computational methods used to analyze language data, including methods for the automatic measurement of discourse coherence, syntactic complexity, poverty of content, referential coherence, and metaphorical language. Linguistic biomarkers of psychosis risk are now undergoing cross-validation, with attention to harmonization of methods. Future directions in extended CHR networks include studies of sources of variance, and combination with other promising biomarkers of psychosis risk, such as cognitive and sensory processing impairments likely to be related to language. Implications for the broader study of social communication, including reciprocal prosody, face expression and gesture, are discussed.

Understanding Language Abnormalities and Associated Clinical Markers in Psychosis: The Promise of Computational Methods

The language and speech of individuals with psychosis reflect their impairments in cognition and motor processes. These language disturbances can be used to identify individuals with and at high risk for psychosis, as well as help track and predict symptom progression, allowing for early intervention and improved outcomes. However, current methods of language assessment-manual annotations and/or clinical rating scales-are time intensive, expensive, subject to bias, and difficult to administer on a wide scale, limiting this area from reaching its full potential. Computational methods that can automatically perform linguistic analysis have started to be applied to this problem and could drastically improve our ability to use linguistic information clinically. In this article, we first review how these automated, computational methods work and how they have been applied to the field of psychosis. We show that across domains, these methods have captured differences between individuals with psychosis and healthy controls and can classify individuals with high accuracies, demonstrating the promise of these methods. We then consider the obstacles that need to be overcome before these methods can play a significant role in the clinical process and provide suggestions for how the field should address them. In particular, while much of the work thus far has focused on demonstrating the successes of these methods, we argue that a better understanding of when and why these models fail will be crucial toward ensuring these methods reach their potential in the field of psychosis.

[Linguistic markers in improving the predictive model of the transition to schizophrenia]

Over the past twenty years, research in psychiatry has focused primarily on the early detection of schizophrenia. The objective has been to engage the patient with prodromal symptoms in a trajectory of care. It has also been a question of being able to offer treatment as soon as the patient "at risk" of schizophrenia triggered a possible first psychotic episode. Standardized clinical tools were developed and now allow identification of subjects at risk of developing psychotic disorders. However, the reliability of predictions of the psychotic transition, which is between 15 and 25%, remains insufficient. In order to improve care, it is now necessary to highlight markers to refine the prediction of the risk of developing schizophrenia. Some teams are trying to identify linguistic anomalies in UHR subjects (disorganized speech, illogical thoughts, poor speech, altered semantic verbal fluencies…). Some of these abnormalities could be specific to the transition to psychosis. The severity of these markers could be proportional to the progressive stage of the disorder, consistent with the hypothesis of a continuum from normal to pathological in schizophrenia. In addition, automated speech analysis techniques in UHR subjects allow identification of subtle semantic and syntactic anomalies (a decrease in semantic coherence, but also the use of possessive pronouns and a poverty of speech) predictive in 79% of cases of psychotic transition. Some authors demonstrate the value of using linguistic markers and automated speech analysis methods to improve the predictive model of the transition to schizophrenia. However, from reification of language to desubjectification of the individual, this transformation in clinical practice raises ethical and epistemological challenges.

Cortical Complexity in People at Ultra-High-Risk for Psychosis Moderated by Childhood Trauma

Subjects with ultra-high risk (UHR) states for psychosis show brain structural volume changes similar to first-episode psychosis and also elevated incidence of environmental risk factors like childhood trauma. It is unclear, however, whether early neurodevelopmental trajectories are altered in UHR. We screened a total of 12,779 first-year Chinese students to enroll 36 UHR subjects (based on clinical interviews) and 59 non-UHR healthy controls for a case-control study of markers of early neurodevelopment. Subjects underwent 3T MRI scanning and clinical characterization, including the childhood trauma questionnaire (CTQ). We then used the CAT12 toolbox to analyse structural brain scans for cortical surface complexity, a spherical harmonics-based marker of early neurodevelopmental changes. While we did not find statistically significant differences between the groups, a trend level finding for reduced cortical complexity (CC) in UHR vs. non-UHR subjects emerged in the left superior temporal cortex (and adjacent insular and transverse temporal cortices), and this trend level association was significantly moderated by childhood trauma (CTQ score). Our findings indicate that UHR subjects tend to show abnormal cortical surface morphometry, in line with recent research; more importantly, however, this association seems to be considerably modulated by early environmental impacts. Hence, our results provide an indication of environmental or gene × environment interactions on early neurodevelopment leading up to elevated psychosis risk.

Early language measures associated with later psychosis features in 22q11.2 deletion syndrome

The 22q11.2 deletion syndrome (22q11DS) is associated with impaired cognitive functions and increased risk for schizophrenia spectrum disorders. Speech and language deficits are prominent, with evidence of decline anteceding emergence of psychosis. There is paucity of data examining language function in children with 22q11DS with follow-up assessment of psychosis spectrum (PS) symptoms. We examined the association between early language measures, obtained clinically, and PS status, obtained on average 10.1 years later, in 166 youths with 22q11DS, with repeated language testing in 48. Participants were administered the Preschool Language Scale (receptive/expressive), and/or, for school aged children, the Clinical Evaluation of Language Fundamentals (receptive/expressive), and age appropriate IQ tests. The structured interview for prodromal syndromes (SIPS) assessed PS symptoms. We found that performance on all preschool measures showed age associated decline, and males performed more poorly on core composite (receptive/expressive) and receptive language measures. For language assessment later in childhood, poorer performance was consistently associated with subsequent PS status. Furthermore, steeper age-related decline was seen in the PS group across language measures and marginally for full-scale IQ. These findings suggest that while preschool language testing is useful in characterizing performance decline in individuals with 22q11DS, it does not robustly differentiate those with subsequent PS from those without. However, language testing in the school age population can help identify individuals with 22q11DS who are at risk for psychosis. Such data are needed for elucidating a lifespan trajectory for affected individuals and may help understand pathways to psychosis applicable to the general population.

Individualized Diagnostic and Prognostic Models for Patients With Psychosis Risk Syndromes: A Meta-analytic View on the State of the Art

BACKGROUND

The clinical high risk (CHR) paradigm has facilitated research into the underpinnings of help-seeking individuals at risk for developing psychosis, aiming at predicting and possibly preventing transition to the overt disorder. Statistical methods such as machine learning and Cox regression have provided the methodological basis for this research by enabling the construction of diagnostic models (i.e., distinguishing CHR individuals from healthy individuals) and prognostic models (i.e., predicting a future outcome) based on different data modalities, including clinical, neurocognitive, and neurobiological data. However, their translation to clinical practice is still hindered by the high heterogeneity of both CHR populations and methodologies applied.

METHODS

We systematically reviewed the literature on diagnostic and prognostic models built on Cox regression and machine learning. Furthermore, we conducted a meta-analysis on prediction performances investigating heterogeneity of methodological approaches and data modality.

RESULTS

A total of 44 articles were included, covering 3707 individuals for prognostic studies and 1052 individuals for diagnostic studies (572 CHR patients and 480 healthy control subjects). CHR patients could be classified against healthy control subjects with 78% sensitivity and 77% specificity. Across prognostic models, sensitivity reached 67% and specificity reached 78%. Machine learning models outperformed those applying Cox regression by 10% sensitivity. There was a publication bias for prognostic studies yet no other moderator effects.

CONCLUSIONS

Our results may be driven by substantial clinical and methodological heterogeneity currently affecting several aspects of the CHR field and limiting the clinical implementability of the proposed models. We discuss conceptual and methodological harmonization strategies to facilitate more reliable and generalizable models for future clinical practice.

Cortical thickness and formal thought disorder in schizophrenia: An ultra high-field network-based morphometry study

BACKGROUND

Persistent formal thought disorder (FTD) is a core feature of schizophrenia. Recent cognitive and neuroimaging studies indicate a distinct mechanistic pathway underlying the persistent positive FTD (pFTD or disorganized thinking), though its structural determinants are still elusive. Using network-based cortical thickness estimates from ultra-high field 7-Tesla Magnetic Resonance Imaging (7T MRI), we investigated the structural correlates of pFTD.

METHODS

We obtained speech samples and 7T MRI anatomical scans from medicated clinically stable patients with schizophrenia (n = 19) and healthy controls (n = 20). Network-based morphometry was used to estimate the mean cortical thickness of 17 functional networks covering the entire cortical surface from each subject. We also quantified the vertexwise variability of thickness within each network to quantify the spatial coherence of the 17 networks, estimated patients vs. controls differences, and related the thickness of the affected networks to the severity of pFTD.

RESULTS

Patients had reduced thickness of the frontoparietal and default mode networks, and reduced spatial coherence affecting the salience and the frontoparietal control network. A higher burden of positive FTD related to reduced frontoparietal thickness and reduced spatial coherence of the salience network. The presence of positive FTD, but not its severity, related to the reduced thickness of the language network comprising of the superior temporal cortex.

CONCLUSIONS

These results suggest that cortical thickness of both cognitive control and language networks underlie the positive FTD in schizophrenia. The structural integrity of cognitive control networks is a critical determinant of the expressed severity of persistent FTD in schizophrenia.

Using Language Processing and Speech Analysis for the Identification of Psychosis and Other Disorders

Increasingly, data-driven methods have been implemented to understand psychopathology. Language is the main source of information in psychiatry and represents "big data" at the level of the individual. Language and behavior are amenable to computational natural language processing (NLP) analytics, which may help operationalize the mental status examination. In this review, we highlight the application of NLP to schizophrenia and its risk states as an exemplar of its use, operationalizing tangential and concrete speech as reductions in semantic coherence and syntactic complexity, respectively. Other clinical applications are reviewed, including forecasting suicide risk and detecting intoxication. Challenges and future directions are discussed, including biomarker development, harmonization, and application of NLP more broadly to behavior, including intonation/prosody, facial expression and gesture, and the integration of these in dyads and during discourse. Similar NLP analytics can also be applied beyond humans to behavioral motifs across species, important for modeling psychopathology in animal models. Finally, clinical neuroscience can inform the development of artificial intelligence.

Models Predicting Psychosis in Patients With High Clinical Risk: A Systematic Review

OBJECTIVE

The present study reviews predictive models used to improve prediction of psychosis onset in individuals at clinical high risk for psychosis (CHR), using clinical, biological, neurocognitive, environmental, and combinations of predictors.

METHODS

A systematic literature search on PubMed was carried out (from 1998 through 2019) to find all studies that developed or validated a model predicting the transition to psychosis in CHR subjects.

RESULTS

We found 1,406 records. Thirty-eight of them met the inclusion criteria; 11 studies using clinical predictive models, seven studies using biological models, five studies using neurocognitive models, five studies using environmental models, and 18 studies using combinations of predictive models across different domains. While the highest positive predictive value (PPV) in clinical, biological, neurocognitive, and combined predictive models were relatively high (all above 83), the highest PPV across environmental predictive models was modest (63%). Moreover, none of the combined models showed a superiority when compared with more parsimonious models (using only neurocognitive, clinical, biological, or environmental factors).

CONCLUSIONS

The use of predictive models may allow high prognostic accuracy for psychosis prediction in CHR individuals. However, only ten studies had performed an internal validation of their models. Among the models with the highest PPVs, only the biological and neurocognitive but not the combined models underwent validation. Further validation of predicted models is needed to ensure external validity.

Clinical Validity of DSM-5 Attenuated Psychosis Syndrome: Advances in Diagnosis, Prognosis, and Treatment

IMPORTANCE

Since the release of the DSM-5 diagnosis of attenuated psychosis syndrome (DSM-5-APS) in 2013, several research studies have investigated its clinical validity. Although critical and narrative reviews have reviewed these progresses, no systematic review has comprehensively summarized the available evidence regarding the clinical validity of DSM-5-APS.

OBJECTIVE

To provide current evidence on the clinical validity of DSM-5-APS, focusing on recent advances in diagnosis, prognosis, and treatment.

EVIDENCE REVIEW

A multistep literature search using the Web of Science database, Cochrane Central Register of Reviews, Ovid/PsychINFO, conference proceedings, and trial registries from database inception to June 16, 2019, was conducted following PRISMA and MOOSE guidelines and PROSPERO protocol. Studies with original data investigating individuals diagnosed using DSM-5-APS or meeting comparable criteria were included. The results of the systematic review were summarized in tables and narratively synthesized against established evidence-based antecedent, concurrent, and prognostic validators. A quantitative meta-analysis was conducted to explore the cumulative risk of psychosis onset at 6, 12, 24, and 36 months in individuals diagnosed using DSM-5-APS criteria.

FINDINGS

The systematic review included 56 articles, which reported on 124 validators, including 15 antecedent, 55 concurrent, and 54 prognostic validators. The epidemiological prevalence of the general non-help-seeking young population meeting DSM-5-APS criteria was 0.3%; the prevalence of individuals meeting DSM-5-APS criteria was variable in clinical samples. The interrater reliability for DSM-5-APS criteria was comparable with that of other DSM-5 mental disorders and can be optimized by the use of specific psychometric instruments. DSM-5-APS criteria were associated with frequent depressive comorbid disorders, distress, suicidality, and functional impairment. The meta-analysis included 23 prospective cohort studies, including 2376 individuals. The meta-analytical risk of psychosis onset was 11% at 6 months, 15% at 12 months, 20% at 24 months, and 23% at 36 months. Research into predisposing and precipitating epidemiological factors, neurobiological correlates, and effective treatments for DSM-5-APS criteria has been limited.

CONCLUSIONS AND RELEVANCE

Over recent years, DSM-5-APS criteria have received substantial concurrent and prognostic validation, mostly driven by research into the clinical high-risk state for psychosis. Precipitating and predisposing factors, neurobiological correlates, and effective treatments are undetermined to date.

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.

Gray matter abnormalities in language processing areas and their associations with verbal ability and positive symptoms in first-episode patients with schizophrenia spectrum psychosis

BACKGROUND

Impaired verbal communication is a prominent feature in patients with schizophrenia. Verbal communication difficulties adversely affect psychosocial outcomes and worsen schizophrenia's clinical manifestation. In the present study, we aimed to investigate associations among gray matter (GM) volumes in language processing areas (LPAs), verbal ability, and positive symptoms in first-episode patients (FEPs) with schizophrenia spectrum psychosis.

METHODS

We enrolled 94 FEPs and 52 healthy controls (HCs) and subjected them to structural magnetic resonance imaging. The GM volumes of the bilateral pars opercularis (POp), pars triangularis (PTr), planum temporale (PT), Heschl's gyrus (HG), insula, and fusiform gyrus (FG), were estimated and compared between the FEPs and HCs. Verbal intelligence levels and positive symptom severity were examined for correlations with the left LPA volumes.

RESULTS

The GM volumes of the left POp, HG, and FG were significantly smaller in the FEPs than in the HCs, while the right regions showed no significant between-group difference. A multiple linear regression model revealed that larger left PT volume was associated with better verbal intelligence in FEPs. In exploratory correlation analysis, several LPAs showed significant correlations with the severity of positive symptoms in FEPs. The left FG volume had a strong inverse correlation with the severity of auditory verbal hallucinations, while the left PT volume was inversely associated with the severity of positive formal thought disorder and delusions. Moreover, the volume of the left insula was positively associated with the severity of bizarre behavior.

CONCLUSIONS

The present study suggests that GM abnormalities in the LPAs, which can be detected during the early stage of illness, may underlie impaired verbal communication and positive symptoms in patients with schizophrenia spectrum psychosis.

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.

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.

Emerging Temporal Lobe Dysfunction in People at Clinical High Risk for Psychosis

Clinical high-risk (CHR) individuals have been increasingly utilized to investigate the prodromal phases of psychosis and progression to illness. Research has identified medial and lateral temporal lobe abnormalities in CHR individuals. Dysfunction in the medial temporal lobe, particularly the hippocampus, is linked to dysregulation of glutamate and dopamine via a hippocampal-striatal-midbrain network that may lead to aberrant signaling of salience underpinning the formation of delusions. Similarly, lateral temporal dysfunction may be linked to the disorganized speech and language impairments observed in the CHR stage. Here, we summarize the significance of these neurobiological findings in terms of emergent psychotic symptoms and conversion to psychosis in CHR populations. We propose key questions for future work with the aim to identify the neural mechanisms that underlie the development of psychosis.

Clinical psychopathology in youth at familial high risk for psychosis

AIM

While the course of psychopathology has been explored from an index mental health diagnosis onwards, there are few detailed, prospective studies of the occurrence of clinical psychopathology in youth with familial risk for severe mental illnesses such as psychosis. We sought to describe the appearance of Axis I psychopathology in a unique sample of adolescents with a family history of schizophrenia (FHR).

METHODS

One hundred and sixty two first- and second-degree relatives (mean age 15.7 ± 3.6; range 8-25) of probands with schizophrenia or schizoaffective disorder were assessed at baseline and annual intervals for up to 3 years, focusing on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) Axis I psychopathology.

RESULTS

Fourteen individuals (8.6%) developed a psychotic disorder. One hundred and five subjects (65%) met criteria for an Axis I disorder over the course of the study, the most common of which was a depressive episode (40 subjects; 25%). Of the 148 individuals who did not develop psychosis, 91 (61%) had one or more Axis I disorders compared with 10/14 converters who had a comorbid Axis I disorder (71%). Ordered by increasing age of onset, diagnoses included cognitive and externalizing disorders, anxiety disorders, affective disorders, substance use disorders and psychotic disorders.

CONCLUSIONS

In addition to an elevated risk of psychosis, young FHR relatives manifest a broad range of non-psychotic Axis I psychopathology in childhood and adolescence. This breadth of diagnoses has implications for the structure and function of mental health services for young people.

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.

At-risk studies and clinical antecedents of psychosis, bipolar disorder and depression: a scoping review in the context of clinical staging

Identifying young people at risk of developing serious mental illness and identifying predictors of onset of illness has been a focus of psychiatric prediction research, particularly in the field of psychosis. Work in this area has facilitated the adoption of the clinical staging model of early clinical phenotypes, ranging from at-risk mental states to chronic and severe mental illness. It has been a topic of debate if these staging models should be conceptualised as disorder-specific or transdiagnostic. In order to inform this debate and facilitate cross-diagnostic discourse, the present scoping review provides a broad overview of the body of literature of (a) longitudinal at-risk approaches and (b) identified antecedents of (homotypic) illness progression across three major mental disorders [psychosis, bipolar disorder (BD) and depression], and places these in the context of clinical staging. Stage 0 at-risk conceptualisations (i.e. familial high-risk approaches) were identified in all three disorders. However, formalised stage 1b conceptualisations (i.e. ultra-high-risk approaches) were only present in psychosis and marginally in BD. The presence of non-specific and overlapping antecedents in the three disorders may support a general staging model, at least in the early stages of severe psychotic or mood disorders.

The role of social isolation and social cognition in thought disorder

A better understanding of how social factors relate to the psychological processes in thought disorder (TD) is necessary for the development of effective psychological interventions. Sixty-eight participants diagnosed with psychosis (18-65; 47.1% female) were recruited and evaluated on social cognition (Hinting Task, HT; and reading the mind in the eyes test, RMET), social isolation (size of social network, frequency and quality of contact), psychotic symptoms (Positive and Negative Syndrome Scale, PANSS) and TD (Thought, Language and Communication Disorders Scale, TLC). A mediation model was tested with isolation as the predictor, TD as the outcome, and performance on HT and RMET as the mediators. The final model, with adjustment for comorbid symptoms (i.e. delusions, suspiciousness, hallucinations, and negative symptoms), supported full mediation and explained a significant amount of the observed variance (60%). Performance on the HT was a significant mediator of the relationship between social isolation and TD. From the covariates, delusions contributed independently and significantly to TD. The implications of the findings for psychological practice, and TD-specific interventions, are discussed as well as the limitations of the study. Further avenues for symptom-specific research are discussed, in particular with reference to more complex psychosocial models.

Formal thought disorders: from phenomenology to neurobiology

Formal thought disorder (FTD) is present in most psychiatric disorders and in some healthy individuals. In this Review, we present a comprehensive, integrative, and multilevel account of what is known about FTD, covering genetic, cellular, and neurotransmitter effects, environmental influences, experimental psychology and neuropsychology, brain imaging, phenomenology, linguistics, and treatment. FTD is a dimensional, phenomenologically defined construct, which can be clinically subdivided into positive versus negative and objective versus subjective symptom clusters. Because FTDs have been traditionally linked to schizophrenia, studies in other diagnoses are scarce. Aetiologically, FTD is the only symptom under genetic influence in schizophrenia as shown in linkage studies, but familial communication patterns (allusive thinking) have also been associated with the condition. Positive FTDs are related to synaptic rarefication in the glutamate system of the superior and middle lateral temporal cortices. Cortical volume of the left superior temporal gyrus is decreased in patients with schizophrenia who have positive FTD in structural MRI studies and shows reversed hemispheric (right more than left) activation in functional MRI experiments during speech production. Semantic network dysfunction in positive FTD has been demonstrated in experiments of indirect semantic hyperpriming (reaction time). In acute positive FTD, antipsychotics are effective, but a subgroup of patients have treatment-resistant, chronic, positive or negative FTD. Specific psychotherapy as treatment for FTD has not yet been developed. With this solid data on the pathogenesis of FTD, we can now implement clinical studies to treat this condition.

Prediction of psychosis across protocols and risk cohorts using automated language analysis

Language and speech are the primary source of data for psychiatrists to diagnose and treat mental disorders. In psychosis, the very structure of language can be disturbed, including semantic coherence (e.g., derailment and tangentiality) and syntactic complexity (e.g., concreteness). Subtle disturbances in language are evident in schizophrenia even prior to first psychosis onset, during prodromal stages. Using computer-based natural language processing analyses, we previously showed that, among English-speaking clinical (e.g., ultra) high-risk youths, baseline reduction in semantic coherence (the flow of meaning in speech) and in syntactic complexity could predict subsequent psychosis onset with high accuracy. Herein, we aimed to cross-validate these automated linguistic analytic methods in a second larger risk cohort, also English-speaking, and to discriminate speech in psychosis from normal speech. We identified an automated machine-learning speech classifier - comprising decreased semantic coherence, greater variance in that coherence, and reduced usage of possessive pronouns - that had an 83% accuracy in predicting psychosis onset (intra-protocol), a cross-validated accuracy of 79% of psychosis onset prediction in the original risk cohort (cross-protocol), and a 72% accuracy in discriminating the speech of recent-onset psychosis patients from that of healthy individuals. The classifier was highly correlated with previously identified manual linguistic predictors. Our findings support the utility and validity of automated natural language processing methods to characterize disturbances in semantics and syntax across stages of psychotic disorder. The next steps will be to apply these methods in larger risk cohorts to further test reproducibility, also in languages other than English, and identify sources of variability. This technology has the potential to improve prediction of psychosis outcome among at-risk youths and identify linguistic targets for remediation and preventive intervention. More broadly, automated linguistic analysis can be a powerful tool for diagnosis and treatment across neuropsychiatry.