Latent class cluster analysis of symptom ratings identifies distinct subgroups within the clinical high risk for psychosis syndrome

Obsessive-compulsive symptoms in individuals at clinical high risk for psychosis: A 2-year longitudinal study

Aim - Recent findings suggest that OCS are prevalent in individuals with early psychosis. However, their clinical relevance still needs to be clarified. This research specifically explored OCS in subjects at Clinical High Risk for Psychosis (CHRP), with the aims of determining their baseline prevalence, examining their 2-year stability, and analyzing their association with sociodemographic data, clinical characteristics and outcomes. Methods - Clinical assessments at baseline and during the 2-year follow-up period included: the Comprehensive Assessment of At-Risk Mental states (CAARMS), the Positive And Negative Syndrome Scale (PANSS), and the Global Assessment of Functioning (GAF). OCS were identified using the CAARMS item 7.6 subscore. Results - Among 180 CHR-P participants, 66 (36.7 %) had OCS at baseline. CHR-P with OCS had higher PANSS scores and greater antidepressant prescription rates. OCS severity levels improved in the first year, but plateaued over two years, correlating with longitudinal changes in GAF and PANSS total scores. OCS improvement was specifically associated with antidepressant use and intensity of individual psychotherapy sessions. CHR-P subjects with OCS had higher service engagement rates. Conclusions - The presence of OCS could characterize a distinct CHR-P subtype with specific clinical and prognostic characteristics, requiring tailored diagnostic and therapeutic approaches. Recognizing the heterogeneity in CHR-P population is crucial for optimizing care.

Cognitive subtypes in youth at clinical high risk for psychosis

Introduction

Schizophrenia is a mental health condition that severely impacts well-being. Cognitive impairment is among its core features, often presenting well before the onset of overt psychosis, underscoring a critical need to study it in the psychosis proneness (clinical high risk; CHR) stage, to maximize the benefits of interventions and to improve clinical outcomes. However, given the heterogeneity of cognitive impairment in this population, a one-size-fits-all approach to therapeutic interventions would likely be insufficient. Thus, identifying cognitive subtypes in this population is crucial for tailored and successful therapeutic interventions. Here we identify, validate, and characterize cognitive subtypes in large CHR samples and delineate their baseline and longitudinal cognitive and functional trajectories.

Methods

Using machine learning, we performed cluster analysis on cognitive measures in a large sample of CHR youth (n = 764), and demographically comparable controls (HC; n = 280) from the North American Prodrome Longitudinal Study (NAPLS) 2, and independently validated our findings with an equally large sample (NAPLS 3; n = 628 CHR, 84 HC). By utilizing several statistical approaches, we compared the clusters on cognition and functioning at baseline, and over 24 months of followup. We further delineate the conversion status within those clusters.

Results

Two main cognitive clusters were identified, "impaired" and "intact" across all cognitive domains in CHR compared to HC. Baseline differences between the cognitively intact cluster and HC were found in the verbal abilities and attention and working memory domains. Longitudinally, those in the cognitively impaired cluster group demonstrated an overall floor effect and did not deteriorate further over time. However, a "catch up" trajectory was observed in the attention and working memory domain. This group had higher instances of conversion overall, with these converters having significantly more non-affective psychotic disorder diagnosis versus bipolar disorder, than those with intact cognition. In the cognitively intact group, we observed differences in trajectory based on conversion status, where those who start with intact cognition and later convert demonstrate a sharp decline in attention and functioning. Functioning was significantly better in the cognitively intact than in the impaired group at baseline. Most of the cognitive trajectories demonstrate a positive relationship with functional ones.

Conclusion

Our findings provide evidence for intact and impaired cognitive subtypes in youth at CHR, independent of conversion status. They further indicate that attention and working memory are important to distinguish between the CHR with intact cognition and controls. The cognitively intact CHR group becomes less attentive after conversion, while the cognitively impaired one demonstrates a catch up trajectory on both attention and working memory. Overall, early evaluation, covering several cognitive domains, is crucial for identifying trajectories of improvement and deterioration for the purpose of tailoring intervention for improving outcomes in individuals at CHR for psychosis.

Cognitive disturbances basic symptoms in help-seeking patients with borderline personality disorder: Characteristics and association with schizotypy

AIM

Although the presence of psychotic symptoms has been widely recognized in Borderline Personality Disorder (BPD), no study previously investigated cognitive Basic Symptoms (BS) and their clinical implications in patients with BPD.

METHODS

This cross-sectional study specifically examined the prevalence of COGDIS (cognitive disturbances) BS criteria in 93 help-seeking outpatients with BPD by using the Schizophrenia Proneness Instrument-Adult Version (SPI-A). We then explored associations of COGDIS with personality traits, functioning and core psychopathological features of BPD.

RESULTS

The prevalence rates of COGDIS criterion were 62.4%. BPD patients meeting COGDIS criteria reported higher levels of schizotypal personality traits, dissociative experiences and work/social functional impairment compared to individuals without COGDIS criteria. Furthermore, the number of cognitive BSs showed a positive correlation with severity levels of schizotypy.

CONCLUSIONS

Cognitive BS are common in BPD. Cognitive disturbances are associated with schizotypal personality traits and specific clinical features. The presence of cognitive BSs may identify a more severe subgroup of patients with BPD, potentially vulnerable to psychotic symptoms and reliably identifiable through assessment of schizotypal traits.

Anhedonia in adolescents at transdiagnostic familial risk for severe mental illness: Clustering by symptoms and mechanisms of association with behavior

BACKGROUND

Anhedonia is a transdiagnostic symptom of severe mental illness (SMI) and emerges during adolescence. Possible subphenotypes and neural mechanisms of anhedonia in adolescents at risk for SMI are understudied.

METHODS

Adolescents at familial risk for SMI (N = 81) completed anhedonia (e.g., consummatory, anticipatory, social), demographic, and clinical measures and one year prior, a subsample (N = 46) completed fMRI scanning during a monetary reward task. Profiles were identified using k-means clustering of anhedonia type and differences in demographics, suicidal ideation, impulsivity, and emotional processes were examined. Moderation analyses were conducted to investigate whether levels of brain activation of reward regions moderated the relationships between anhedonia type and behaviors.

RESULTS

Two-clusters emerged: a high anhedonia profile (high-anhedonia), characterized by high levels of all types of anhedonia, (N = 32) and a low anhedonia profile (low-anhedonia), characterized by low levels of anhedonia types (N = 49). Adolescents in the high-anhedonia profile reported more suicidal ideation and negative affect, and less positive affect and desire for emotional closeness than low-anhedonia profile. Furthermore, more suicidal ideation, less positive affect, and less desire for emotional closeness differentiated the familial high-risk, high-anhedonia profile adolescents from the familial high-risk, low-anhedonia profile adolescents. Across anhedonia profiles, moderation analyses revealed that adolescents with high dmPFC neural activation in response to reward had positive relationships between social, anticipatory, and consummatory anhedonia and suicidal ideation.

LIMITATIONS

Small subsample with fMRI data.

CONCLUSION

Profiles of anhedonia emerge transdiagnostically and vary on clinical features. Anhedonia severity and activation in frontostriatal reward areas have value for clinically important outcomes such as suicidal ideation.

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.

Identification of high-risk patterns of myopia in Chinese students based on four major behavioral risk factors: a latent class analysis

BACKGROUND

Myopia is prevalent in children and adolescents. Understanding the effect of multiple behaviors and their latent patterns on ocular biometric parameters may help clinicians and public health practitioners understand the behavioral risk pattern of myopia from a person-centered perspective. The purpose of this study was to identify the patterns of four major behavioral risk factors associated with myopia, including time spent outdoors, digital screen time, sleep duration, and performance of Chinese eye exercises. The study also examined the relationships between these behavioral patterns and myopia as well as ocular biometric parameters in a sample of Chinese college students.

METHODS

This study included 2014 students from the Dali University Students Eye Health Study. The average age of the subjects was 19.0 ± 0.9 years old, ranging from 15.7 to 25.1 years old. Each participant's refractive status was measured using an autorefractor without cycloplegia and ocular biometric parameters were measured using an IOL Master. Behavioral risk factors were collected using a pre-designed self-administered questionnaire. Latent class analysis (LCA) was performed to identify cluster patterns of various behaviors.

RESULTS

The prevalence of myopia was 91.8% in this population. The 2-class model was selected for the LCA based on goodness-of-fit evaluation metrics. Among the overall study sample, 41.1% and 58.9% were assigned into the high-risk and low-risk class, respectively. The risk of myopia [odds ratio (OR) = 2.12, 95% confidence interval (CI) = 1.52-3.14], high myopia (OR = 1.43, 95% CI = 1.14-1.78) and axial length/corneal radius (AL/CR) ratio of more than 3.0 (OR = 1.82, 95% CI = 1.22-2.72) were significantly higher in the high-risk compared with low-risk class.

CONCLUSIONS

Chinese university students showed differential risks of myopia and could be subdivided into high- and low-risk clusters based on four behavioral variables.

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.

Screening high-risk population of persistent postpartum hypertension in women with preeclampsia using latent class cluster analysis

BACKGROUND

A significant proportion of women with preeclampsia (PE) exhibit persistent postpartum hypertension (PHTN) at 3 months postpartum associated with cardiovascular morbidity. This study aimed to screen patients with PE to identify the high-risk population with persistent PHTN.

METHODS

This retrospective cohort study enrolled 1,000 PE patients with complete parturient and postpartum blood pressure (BP) profiles at 3 months postpartum. The enrolled patients exhibited new-onset hypertension after 20 weeks of pregnancy, while those with PE superimposed upon chronic hypertension were excluded. Latent class cluster analysis (LCCA), a method of unsupervised learning in machine learning, was performed to ascertain maternal exposure clusters from eight variables and 35 subordinate risk factors. Logistic regression was applied to calculate odds ratios (OR) indicating the association between clusters and PHTN.

RESULTS

The 1,000 participants were classified into three exposure clusters (subpopulations with similar characteristics) according to persistent PHTN development: high-risk cluster (31.2%), medium-risk cluster (36.8%), and low-risk cluster (32.0%). Among the 1,000 PE patients, a total of 134 (13.4%) were diagnosed with persistent PHTN, while the percentages of persistent PHTN were24.68%, 10.05%, and 6.25% in the high-, medium-, and low-risk clusters, respectively. Persistent PHTN in the high-risk cluster was nearly five times higher (OR, 4.915; 95% confidence interval (CI), 2.92-8.27) and three times (OR, 2.931; 95% CI, 1.91-4.49) than in the low- and medium-risk clusters, respectively. Persistent PHTN did not differ between the medium- and low-risk clusters. Subjects in the high-risk cluster were older and showed higher BP, poorer prenatal organ function, more adverse pregnancy events, and greater medication requirement than the other two groups.

CONCLUSION

Patients with PE can be classified into high-, medium-, and low-risk clusters according to persistent PHTN severity; each cluster has cognizable clinical features. This study's findings stress the importance of controlling persistent PHTN to prevent future cardiovascular disease.

Developmental profiles of schizotypy in the general population: A record linkage study of Australian children aged 11-12 years

Objectives

The detection of young people at high risk for psychotic disorders has been somewhat narrowly focused on overt symptom‐based markers that reflect mild reality distortion (e.g., psychotic‐like experiences), or prodromal syndromes that are proximal to psychosis onset. The concept of schizotypy represents a broader framework for investigating risk for schizophrenia (and other disorders) in childhood, before the onset of prodromal or overt symptoms. We sought to detect profiles of risk for psychosis (schizotypy) in a general population sample of 22,137 Australian children aged 11–12 years, and to determine early life risk factors associated with these profiles from data available in linked records (registers).

Methods

Fifty‐nine self‐reported items were used as indicators of schizotypy across six broad domains; z‐scores for each domain were subjected to latent profile analyses (LPA). A series of multinomial logistic regressions was used to examine the association between resulting profile (class) membership and several childhood and parental risk factors, and the proportion of children with mental disorders among each schizotypy profile was examined.

Results

The LPA revealed three person‐centred profiles referred to as True Schizotypy (n = 1,323; 6.0%), Introverted Schizotypy (n = 4,473; 20.2%), and Affective Schizotypy (n = 4,261; 19.2%), as well as a group of children showing no risk (n = 12,080; 54.6%). Prior exposure to perinatal and familial adversities including childhood maltreatment, as well as poor early childhood development and academic functioning, was variously associated with all risk groups. There was a higher proportion of childhood mental disorder diagnoses among children in the True Schizotypy group, relative to other profiles.

Conclusion

Subtle differences in the pattern of exposures and antecedents among schizophrenia liability profiles in childhood may reflect distinct pathogenic pathways to psychotic or other mental illness.

Practitioner points

Children aged 11–12 years report characteristics of schizotypy which can be classified into three distinct profiles that may represent different pathological processes towards later mental ill‐health.

Early life exposure to perinatal and familial adversities including childhood maltreatment, early childhood developmental vulnerability, and poor academic functioning predict membership in all three childhood schizotypy profiles.

Latent liability for schizophrenia (and potentially other mental disorders) may be represented by different profiles of functioning observable in childhood.

Cerebello-limbic functional connectivity patterns in youth at clinical high risk for psychosis

Youth at clinical high risk (CHR) for psychosis can present not only with characteristic attenuated psychotic symptoms but also may have other comorbid conditions, including anxiety and depression. These undifferentiated mood symptoms can overlap with the clinical presentation of youth with Distress syndromes. Increased resting-state functional connectivity within cerebello-thalamo-cortical (CTC) pathways has been proposed as a trait-specific biomarker for CHR. However, it is unclear whether this functional neural signature remains specific when compared to a different risk group: youth with Distress syndromes. The purpose of the present work was to describe CTC alterations that distinguish between CHR and Distressed individuals. Using machine learning algorithms, we analyzed CTC connectivity features of CHR (n = 51), Distressed (n = 41), and healthy control (n = 36) participants. We found four cerebellar (lobes VII and left Crus II anterior/posterior) and two basal ganglia (right putamen and right thalamus) nodes containing a set of specific connectivity features that distinguished between CHR, Distressed and healthy control groups. Hyperconnectivity between medial lobule VIIb, somatomotor network and middle temporal gyrus was associated with CHR status and more severe symptoms. Detailed atlas parcellation suggested that CHR individuals may have dysfunction mainly within the associative (cognitive) pathways, particularly, between those brain areas responsible for the multi-sensory signal integration.

Alterations in Emotional Diversity Correspond With Increased Severity of Attenuated Positive and Negative Symptoms in the Clinical High-Risk Syndrome

Background: Alterations in emotional functioning are a key feature of psychosis and are present in individuals with a clinical high-risk (CHR) syndrome. However, little is known about alterations in emotional diversity (i.e., the variety and relative abundance of emotions that humans experience) and clinical correlates in this population. Methods: Individuals meeting criteria for a CHR syndrome (N = 47) and matched healthy controls (HC) (N = 58) completed the modified Differential Emotions Scale (used to derive scores of total, positive, and negative emotional diversity) and clinical interviews (i.e., Structured Interview for Psychosis-Risk Syndromes). Results: Findings showed that the CHR group experienced lower levels of positive emotional diversity compared to HCs. Among the CHR individuals, lower levels of positive and higher levels of negative emotional diversity were associated with more severe attenuated positive and negative symptoms. Analyses controlled for mean levels of emotion and current antipsychotic medication use. Discussion: Results demonstrate that altered emotional diversity (in particular lower levels of positive and higher levels of negative emotional diversity) is a clinically relevant marker in CHR individuals, above and beyond alterations in mean levels of emotional experiences. Future studies may probe sources, downstream consequences, and potential modifiability of decreased emotional diversity in individuals at CHR.

The COVID-19 Pandemic Introduces Diagnostic and Treatment Planning Complexity for Individuals at Clinical High Risk for Psychosis

COVID-19 has led to a great deal of general suffering and an increased prevalence of psychiatric illness worldwide. Within the area of psychosis-risk syndromes, a highly heterogeneous clinical population, the picture is quite nuanced as the social restrictions resulting from the pandemic have reduced stress for some and increased it for others. Further, a number of pandemic-related societal and cultural changes have obfuscated the diagnostic and treatment landscape in this area as well. In this opinion article, we describe several prototypical cases, representative of presentations seen in our clinical high-risk (CHR) research programs. The cases highlight considerable clinical variability and, in addition, speak to the current complexities faced by diagnosticians and treatment providers. In addition to discussing these issues, this piece introduces potential solutions highlighting the promise of incorporating data-driven strategies to identify more homogenous CHR subtypes and employ precision medicine.

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 insight in individuals with an at-risk mental state for psychosis: A meta-analysis

AIM

To compare cognitive insight abilities measured with the Beck Cognitive Insight Scale (BCIS) between individuals with an at-risk mental state (ARMS) and healthy controls.

METHOD

Review and meta-analysis based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

RESULTS

A search for articles investigating cognitive insight in ARMS in the MEDLINE and ScienceDirect databases revealed five studies including 303 ARMS and 376 controls. Regarding BCIS subscales, ARMS individuals displayed significant higher scores for self-certainty than controls with a small-to-moderate effect size (ESg = 0.45 [0.23;0.67], P < .005), whereas no significant difference was observed for self-reflectiveness (ESg = -0.56 [-0.18;1.29], P = .14). No significant differences were observed between ARMS and controls for overall cognitive insight abilities as indexed by the BCIS composite score (ESg = -0.24 [-0.43;0.91], P = .45).

CONCLUSIONS

Self-certainty abnormalities seem to predate the expression of full-blown psychotic episode and to be higher in ARMS than in healthy controls. By contrast, ARMS did not display abnormal self-reflectiveness and overall cognitive insight abilities.

Deconstructing Negative Symptoms in Individuals at Clinical High-Risk for Psychosis: Evidence for Volitional and Diminished Emotionality Subgroups That Predict Clinical Presentation and Functional Outcome

Negative symptoms are characteristic of schizophrenia and closely linked to numerous outcomes. A body of work has sought to identify homogenous negative symptom subgroups-a strategy that can promote mechanistic understanding and precision medicine. However, our knowledge of negative symptom subgroups among individuals at clinical high-risk (CHR) for psychosis is limited. Here, we investigated distinct negative symptom profiles in a large CHR sample (N = 244) using a cluster analysis approach. Subgroups were compared on external validators that are (1) commonly observed in the schizophrenia literature and/or (2) may be particularly relevant for CHR individuals, informing early prevention and prediction. We observed 4 distinct negative symptom subgroups, including individuals with (1) lower symptom severity, (2) deficits in emotion, (3) impairments in volition, and (4) global elevations. Analyses of external validators suggested a pattern in which individuals with global impairments and volitional deficits exhibited more clinical pathology. Furthermore, the Volition group endorsed more disorganized, anxious, and depressive symptoms and impairments in functioning compared to the Emotion group. These data suggest there are unique negative symptom profiles in CHR individuals, converging with studies in schizophrenia indicating motivational deficits may be central to this symptom dimension. Furthermore, observed differences in CHR relevant external validators may help to inform early identification and treatment efforts.

Identifying extended psychosis phenotypes at school: Associations with socio-emotional adjustment, academic, and neurocognitive outcomes

The main goal of the present study was to explore the latent structure of extended psychosis phenotypes in a representative sample of adolescents. Moreover, associations with socio-emotional adjustment, academic achievement, and neurocognition performance across the latent profiles were compared. Participants were 1506 students, 667 males (44.3%), derived from random cluster sampling. Various tools were used to measure psychosis risk, subjective well-being, academic performance, and neurocognition. Based on three psychometric indicators of psychosis risk (schizotypal traits, psychotic-like experiences, and bipolar-like experiences), four latent classes were found: non-risk, low-risk, high reality distortion experiences, and high psychosis liability. The high-risk latent groups scored significantly higher on mental health difficulties, and negative affect, and lower on positive affect and well-being, compared to the two non-risk groups. Moreover, these high-risk groups had a significantly higher number of failed academic subjects compared to the non-risk groups. In addition, no statistically significant differences in efficiency performance were found in the neurocognitive domains across the four latent profiles. This study allows us to improve the early identification of adolescents at risk of serious mental disorder in school settings in order to prevent the incidence and burden associated with these kinds of mental health problems.

Integrated network analysis of symptom clusters across disease conditions

Identifying the symptom clusters (two or more related symptoms) with shared underlying molecular mechanisms has been a vital analysis task to promote the symptom science and precision health. Related studies have applied the clustering algorithms (e.g. k-means, latent class model) to detect the symptom clusters mostly from various kinds of clinical data. In addition, they focused on identifying the symptom clusters (SCs) for a specific disease, which also mainly concerned with the clinical regularities for symptom management. Here, we utilized a network-based clustering algorithm (i.e., BigCLAM) to obtain 208 typical SCs across disease conditions on a large-scale symptom network derived from integrated high-quality disease-symptom associations. Furthermore, we evaluated the underlying shared molecular mechanisms for SCs, i.e., shared genes, protein-protein interaction (PPI) and gene functional annotations using integrated networks and similarity measures. We found that the symptoms in the same SCs tend to share a higher degree of genes, PPIs and have higher functional homogeneities. In addition, we found that most SCs have related symptoms with shared underlying molecular mechanisms (e.g. enriched pathways) across different disease conditions. Our work demonstrated that the integrated network analysis method could be used for identifying robust SCs and investigate the molecular mechanisms of these SCs, which would be valuable for symptom science and precision health.

Clinical subtypes that predict conversion to psychosis: A canonical correlation analysis study from the ShangHai At Risk for Psychosis program

OBJECTIVE

Since only 30% or fewer of individuals at clinical high risk convert to psychosis within 2 years, efforts are underway to refine risk identification strategies to increase their predictive power. The clinical high risk is a heterogeneous syndrome presenting with highly variable clinical symptoms and cognitive dysfunctions. This study investigated whether subtypes defined by baseline clinical and cognitive features improve the prediction of psychosis.

METHOD

Four hundred clinical high-risk subjects from the ongoing ShangHai At Risk for Psychosis program were enrolled in a prospective cohort study. Canonical correlation analysis was applied to 289 clinical high-risk subjects with completed Structured Interview for Prodromal Syndromes and cognitive battery tests at baseline, and at least 1-year follow-up. Canonical variates were generated by canonical correlation analysis and then used for hierarchical cluster analysis to produce subtypes. Kaplan-Meier survival curves were constructed from the three subtypes to test their utility further in predicting psychosis.

RESULTS

Canonical correlation analysis determined two linear combinations: (1) negative symptom and functional deterioration-related cognitive features, and (2) Positive symptoms and emotional disorganization-related cognitive features. Cluster analysis revealed three subtypes defined by distinct and relatively homogeneous patterns along two dimensions, comprising 14.2% (subtype 1, n = 41), 37.4% (subtype 2, n = 108) and 48.4% (subtype 3, n = 140) of the sample, and each with distinctive features of clinical and cognitive performance. Those with subtype 1, which is characterized by extensive negative symptoms and cognitive deficits, appear to have the highest risk for psychosis. The conversion risk for subtypes 1-3 are 39.0%, 11.1% and 18.6%, respectively.

CONCLUSION

Our results define important subtypes within clinical high-risk syndromes that highlight clinical symptoms and cognitive features that transcend current diagnostic boundaries. The three different subtypes reflect significant differences in clinical and cognitive characteristics as well as in the risk of conversion to psychosis.

Patterns of symptoms before a diagnosis of first episode psychosis: a latent class analysis of UK primary care electronic health records

BACKGROUND

The nature of symptoms in the prodromal period of first episode psychosis (FEP) remains unclear. The objective was to determine the patterns of symptoms recorded in primary care in the 5 years before FEP diagnosis.

METHODS

The study was set within 568 practices contributing to a UK primary care health record database (Clinical Practice Research Datalink). Patients aged 16-45 years with a first coded record of FEP, and no antipsychotic prescription more than 1 year prior to FEP diagnosis (n = 3045) was age, gender, and practice matched to controls without FEP (n = 12,180). Fifty-five symptoms recorded in primary care in the previous 5 years, categorised into 8 groups (mood-related, 'neurotic', behavioural change, volition change, cognitive change, perceptual problem, substance misuse, physical symptoms), were compared between cases and controls. Common patterns of symptoms prior to FEP diagnosis were identified using latent class analysis.

RESULTS

Median age at diagnosis was 30 years, 63% were male. Non-affective psychosis (67%) was the most common diagnosis. Mood-related, 'neurotic', and physical symptoms were frequently recorded (> 30% of patients) before diagnosis, and behavioural change, volition change, and substance misuse were also common (> 10%). Prevalence of all symptom groups was higher in FEP patients than in controls (adjusted odds ratios 1.33-112). Median time from the first recorded symptom to FEP diagnosis was 2-2.5 years except for perceptual problem (70 days). The optimal latent class model applied to FEP patients determined three distinct patient clusters: 'no or minimal symptom cluster' (49%) had no or few symptoms recorded; 'affective symptom cluster' (40%) mainly had mood-related and 'neurotic' symptoms; and 'multiple symptom cluster' (11%) consulted for three or more symptom groups before diagnosis. The multiple symptom cluster was more likely to have drug-induced psychosis, female, obese, and have a higher morbidity burden. Affective and multiple symptom clusters showed a good discriminative ability (C-statistic 0.766; sensitivity 51.2% and specificity 86.7%) for FEP, and many patients in these clusters had consulted for their symptoms several years before FEP diagnosis.

CONCLUSIONS

Distinctive patterns of prodromal symptoms may help alert general practitioners to those developing psychosis, facilitating earlier identification and referral to specialist care, thereby avoiding potentially detrimental treatment delay.

Latent profile analysis of psychosis liability in a community-derived sample of adolescents: Links with mental health difficulties, suicidal ideation, bipolar-like experiences and psychotic-like experiences

AIM

The main goal of the present study was to explore the latent structure of schizotypy as an indicator of psychosis liability, in a community-derived sample of adolescents. Links to mental health difficulties, prosocial behaviour, suicidal ideation, bipolar-like experiences and psychotic-like experiences (PLEs) (severity and distress) were compared across schizotypy latent profiles.

METHOD

The present research included 1588 adolescents selected by a stratified random cluster sampling. The Oviedo Schizotypy Assessment Questionnaire (ESQUIZO-Q), The Paykel Suicide Scale (PSS), The Strengths and Difficulties Questionnaire (SDQ), The Prodromal Questionnaire-Brief (PQ-B), The Mood Disorder Questionnaire (MDQ), The Penn Matrix Reasoning Test (PMRT), The Family Affluence Scale-II (FAS-II), and The Oviedo Infrequency Scale (INF-OV) were used.

RESULTS

Using latent profile analysis four latent classes (LC) were identified: "Positive schizotypy" (14.1%, n = 224), "Low schizotypy" (51.9%, n = 825), "Social Disorganization schizotypy" (27.2%, n = 432), and "High schizotypy" (6.7%, n = 107). The "High schizotypy" class scored higher on several psychometric indicators of psychopathology (ie, mental health difficulties, suicide ideation, bipolar-like experiences and PLEs) relative to the other three LC.

CONCLUSION

Four groups of adolescents with different patterns of schizotypal traits and different clinical-pathological meaning were found. Deficits found across schizotypy latent profiles, resembling those found in patients with psychosis and ultra-high risk samples. The identification of homogeneous subgroups of adolescents potentially at risk for psychosis may help us in the prevention of psychotic-spectrum disorders and mental health problems.

Latent Psychotic Symptom Profiles Amongst People Who Use Methamphetamine: What Do They Tell Us About Existing Diagnostic Categories?

The inability to distinguish clearly between methamphetamine-related psychosis and schizophrenia has led to the suggestion that "methamphetamine psychosis" does not represent a distinct diagnostic entity but rather that the drug has triggered a vulnerability to schizophrenia. We tested this possibility by exploring the latent class structure of psychotic symptoms amongst people who use the drug and examining how these latent symptom profiles correspond to a diagnosis of schizophrenia. Latent class analysis was carried out on the lifetime psychotic symptoms of 554 current methamphetamine users, of whom 40 met the DSM-IV criteria for schizophrenia. Lifetime diagnoses of schizophrenia and individual psychotic symptoms were assessed using the Composite International Diagnostic Interview. The chosen model found 22% of participants had a high propensity to experience a wide range of psychotic symptoms (schizophrenia-like), whereas the majority (56%) more specifically experienced persecutory delusions and hallucinations (paranoid psychosis) and had a lower probability of these symptoms than the schizophrenia-like class. A third class (22%) had a low probability of all symptoms, with the exception of 34% reporting persecutory delusions. Participants in the schizophrenia-like class were more likely to meet diagnostic criteria for schizophrenia (26 vs. 3 and 1% for each of the other classes, p < 0.001) but the diagnosis failed to encompass 74% of this group. These results are consistent with there being a distinction between schizophrenia and methamphetamine-related psychotic symptoms, both in terms of the propensity to experience psychotic symptoms, as well as the symptom profile; however, this distinction may not be captured well by existing diagnostic classifications.