Individuals with a family history of bipolar disorder are at increased risk of developing affective psychopathology. Longitudinal imaging studies in young people with familial risk have been limited, and cortical developmental trajectories in the progression towards illness remain obscure.

To establish high-resolution longitudinal differences in cortical structure that are associated with risk of bipolar disorder.

Using structural magnetic resonance imaging data from 217 unrelated ‘Bipolar Kids and Sibs study’ participants (baseline n = 217, follow-up n = 152), we examined changes over a 2-year period in cortical area, thickness and volume, measured at each vertex across the cortical surface. Groups comprised 105 ‘high-risk’ participants with a first-degree relative with bipolar disorder (female n = 64; age in years: M (mean) = 20.9, s.d. = 5.5) and 112 controls with no familial psychiatric history (females n = 60; age in years: M = 22.4, s.d. = 3.7).

Accelerated thickness and volume reductions over time were observed in ‘high-risk’ individuals across multiple cortical regions, relative to controls, including right lateral orbitofrontal thickness (β = 0.033, P < 0.001) and inferior frontal volume (β = 0.021, P < 0.001). These differences were observed after controlling for age, sex, ancestry, current medication status, lifetime psychiatric diagnoses and measures of gross brain morphology.

Longitudinal group differences suggest the presence of thicker cortex in familial ‘high-risk’ individuals at earlier developmental stages, followed by accelerated thinning towards the typical age of bipolar disorder onset. Future examination of genetic and environmental components of familial risk and the mechanistic nature (pathological or protective) of cortical-trajectory differences over time may facilitate the identification of prodromal biomarkers and opportunities for early clinical intervention.

Recent stressful life events (SLE) are a risk factor for psychosis, but limited research has explored how SLEs affect individuals at clinical high risk (CHR) for psychosis. The current study investigated the longitudinal effects of SLEs on functioning and symptom severity in CHR individuals, where we hypothesized CHR would report more SLEs than healthy controls (HC), and SLEs would be associated with poorer outcomes.

The study used longitudinal data from the EU-GEI High Risk study. Data from 331 CHR participants were analyzed to examine the effects of SLEs on changes in functioning, positive and negative symptoms over a 2-year follow-up. We compared the prevalence of SLEs between CHR and HCs, and between CHR who did (CHR-T) and did not (CHR-NT) transition to psychosis.

CHR reported 1.44 more SLEs than HC (p < 0.001), but there was no difference in SLEs between CHR-T and CHR-NT at baseline. Recent SLEs were associated with poorer functioning and more severe positive and negative symptoms in CHR individuals (all p < 0.01) but did not reveal a significant interaction with time.

CHR individuals who had experienced recent SLEs exhibited poorer functioning and more severe symptoms. However, as the interaction between SLEs and time was not significant, this suggests SLEs did not contribute to a worsening of symptoms and functioning over the study period. SLEs could be a key risk factor to becoming CHR for psychosis, however further work is required to inform when early intervention strategies mitigating against the effects of stress are most effective.

Cognitive impairment constitutes a prevailing issue in the schizophrenia spectrum, severely impacting patients' functional outcomes. A global cognitive score, sensitive to the stages of the spectrum, would benefit the exploration of potential factors involved in the cognitive decline.

First, we performed principal component analysis on cognitive scores from 768 individuals across the schizophrenia spectrum, including first-degree relatives of patients, individuals at ultra-high risk, who had a first-episode psychosis, and chronic schizophrenia patients, alongside 124 healthy controls. The analysis provided 10 g-factors as global cognitive scores, validated through correlations with intelligence quotient and assessed for their sensitivity to the stages on the spectrum using analyses of variance. Second, using the g-factors, we explored potential mechanisms underlying cognitive impairment in the schizophrenia spectrum using correlations with sociodemographic, clinical, and developmental data, and linear regressions with genotypic data, pooled through meta-analyses.

The g-factors were highly correlated with intelligence quotient and with each other, confirming their validity. They presented significant differences between subgroups along the schizophrenia spectrum. They were positively correlated with educational attainment and the polygenic risk score (PRS) for cognitive performance, and negatively correlated with general psychopathology of schizophrenia, neurodevelopmental load, and the PRS for schizophrenia.

The g-factors appeared as valid estimators of global cognition, enabling discerning cognitive states within the schizophrenia spectrum. Educational attainment and genetics related to cognitive performance may have a positive influence on cognitive functioning, while general psychopathology of schizophrenia, neurodevelopmental load, and genetic liability to schizophrenia may have an adverse impact.

In our previous study, we have developed the Child Psychosis-risk Screening System (CPSS), which incorporates psychological and behavioral characteristics of childhood into an algorithm, based on a retrospective survey.

In this study, we actually tried to evaluate the risk of psychosis in pediatric and psychiatric outpatients using the CPSS.

We conducted an epidemiological study of 323 outpatients aged 6-18 years visiting pediatric and psychiatric departments using CBCL and clinical data (sex, age, winter birth, chief complaint, diagnosis, abuse, bullying, hikikomori). ROC analysis was used to assess the accuracy of CPSS predictions. Cross-sectional logistic regression analysis was performed on the clinical data to identify factors associated with risk groups exceeding the cutoff value.

The results of the ROC analysis showed that the AUC (Area under the ROC Curve) was 80.3%, indicating that the CPSS has Moderate accuracy. The cutoff value was 98.11% (sensitivity: 0.857, specificity: 0.835), and 18% of the subjects were identified as risk groups above this value. Cross-sectional logistic regression analysis showed that schizophrenia diagnosis, no abuse, winter birth, and hikikomori were associated with the risk group, with respective odds ratios of 22.88, 10.76, 1.91, and 1.37.

The results of this study suggest that the CPSS can be applied to pediatric practice for early detection of risk for psychosis. The risk group is also present among pediatric patients with physical chief complaints. The factors suggested to be associated with risk groups may reflect the factors acting on the critical period of psychosis onset and the dynamic state.

No significant relationships.

Uncontrolled epilepsy creates a constant source of worry for patients and puts them at a high risk of injury. Identifying recurrent “premonitory” symptoms of seizures and using them to recalibrate seizure prediction algorithms may improve prediction performances. This study aimed to investigate patients’ ability to predict oncoming seizures based on preictal symptoms.

Through an online survey, demographics and clinical characteristics (e.g., seizure frequency, epilepsy duration, and postictal symptom duration) were collected from people with epilepsy and caregivers across Canada. Respondents were asked to answer questions regarding their ability to predict seizures through warning symptoms. A total of 196 patients and 150 caregivers were included and were separated into three groups: those who reported warning symptoms within the 5 minutes preceding a seizure, prodromes (symptoms earlier than 5 minutes before seizure), and no warning symptoms.

Overall, 12.2% of patients and 12.0% of caregivers reported predictive prodromes ranging from 5 minutes to more than 24 hours before the seizures (median of 2 hours). The most common were dizziness/vertigo (28%), mood changes (26%), and cognitive changes (21%). Statistical testing showed that respondents who reported prodromes also reported significantly longer postictal recovery periods compared to those who did not report predictive prodromes (P < 0.05).

Findings suggest that patients who present predictive seizure prodromes may be characterized by longer patient-reported postictal recovery periods. Studying the correlation between seizure severity and predictability and investigating the electrical activity underlying prodromes may improve our understanding of preictal mechanisms and ability to predict seizures.

Rapid progression from the first identifiable symptom to the onset of first-episode psychosis (FEP) allows less time for early intervention. The aim of this study was to examine the association between the first identifiable symptom and the subsequent speed of illness progression.

Data were available for 390 patients attending a catchment-based early intervention service for FEP. Exposure to non-psychotic and subthreshold psychotic symptoms was retrospectively recorded using semi-structured interviews. Outcomes following the onset of the first identifiable symptom were (1) time to onset of FEP and (2) symptom incidence rate (i.e. number of symptoms emerging per person-year until FEP onset). These outcomes were respectively analyzed with Cox proportional hazards and negative binomial regressions.

After Bonferroni correction, having a subthreshold psychotic (v. non-psychotic) symptom as the first symptom was not associated with time to FEP onset [hazard ratio (HR) = 1.39; 95% CI 0.94–2.04] but was associated with higher symptom incidence [incidence rate ratio (IRR) = 1.92; 95% CI 1.10–3.48]. A first symptom of suspiciousness was associated with shorter time to FEP onset (HR = 2.37; 95% CI 1.38–4.08) and higher symptom incidence rate (IRR = 3.20; 95% CI 1.55–7.28) compared to other first symptoms. In contrast, a first symptom of self-harm was associated with lower symptom incidence rate (IRR = 0.06; 95% CI 0.01–0.73) compared to other first symptoms. Several associations between symptoms and illness progression were moderated by the age at symptom onset.

Appreciating the content and timing of early symptoms can identify windows and treatment targets for early interventions in psychosis.

Schizophrenia (SZ) is typically preceded by a prodromal (i.e. pre-illness) period characterized by attenuated positive symptoms and declining functional outcome. Negative symptoms are prominent among individuals at clinical high-risk (CHR) for psychosis (i.e. those with prodromal syndromes) and predictive of conversion to illness. Mechanisms underlying negative symptoms are unclear in the CHR population.

The current study evaluated whether CHR participants demonstrated deficits in the willingness to expend effort for rewards and whether these impairments are associated with negative symptoms and greater risk for conversion. Participants included 44 CHR participants and 32 healthy controls (CN) who completed the Effort Expenditure for Reward Task (EEfRT).

Compared to CN, CHR participants displayed reduced likelihood of exerting high effort for high probability and magnitude rewards. Among CHR participants, reduced effort expenditure was associated with greater negative symptom severity and greater probability of conversion to a psychotic disorder on a cross-sectional risk calculator.

Findings suggest that effort-cost computation is a marker of illness liability and a transphasic mechanism underlying negative symptoms in the SZ spectrum.

Assessment of risks of illnesses has been an important part of medicine for decades. We now have hundreds of ‘risk calculators’ for illnesses, including brain disorders, and these calculators are continually improving as more diverse measures are collected on larger samples.

We first replicated an existing psychosis risk calculator and then used our own sample to develop a similar calculator for use in recruiting ‘psychosis risk’ enriched community samples. We assessed 632 participants age 8–21 (52% female; 48% Black) from a community sample with longitudinal data on neurocognitive, clinical, medical, and environmental variables. We used this information to predict psychosis spectrum (PS) status in the future. We selected variables based on lasso, random forest, and statistical inference relief; and predicted future PS using ridge regression, random forest, and support vector machines.

Cross-validated prediction diagnostics were obtained by building and testing models in randomly selected sub-samples of the data, resulting in a distribution of the diagnostics; we report the mean. The strongest predictors of later PS status were the Children's Global Assessment Scale; delusions of predicting the future or having one's thoughts/actions controlled; and the percent married in one's neighborhood. Random forest followed by ridge regression was most accurate, with a cross-validated area under the curve (AUC) of 0.67. Adjustment of the model including only six variables reached an AUC of 0.70.

Results support the potential application of risk calculators for screening and identification of at-risk community youth in prospective investigations of developmental trajectories of the PS.

The establishment phase of an early detection centre for prodromal psychosis is introduced and characterised, along with its detaining and promoting factors within a universal multi-payer health care system.

Across the first six years (1998–2003), users' characteristics are compared between different diagnostic groups and to the local population statistics; and, for an exemplary 12-months period (3-1-2002 to 2-28-2003), the characteristics of telephone contacts with the service are studied.

Rising steadily in number across the first three years, 872 persons, predominately of German citizenship and higher education, consulted the service until 2003, 326 with first-episode psychosis and 144 not fulfilling criteria for a current or beginning psychosis. Of the 402 putatively prodromal patients, 94% reported predictive basic symptoms, 68.9% attenuated and 20.6% transient psychotic symptoms. Most contacts by persons meeting any prodromal criterion were initiated by mental health professionals (psychiatrists or psychologists) and counselling services.

Supported by public awareness campaigns, an early detection service is well received by its users and private practitioners as reflected by the large proportion of referrals from the latter. However, persons of non-German background as well as of lower education were underrepresented indicating that these sub-groups should be approached by tailored programmes.

Schizophrenia (SZ) is typically preceded by a prodromal (i.e. pre-illness) period characterized by attenuated positive symptoms and declining functional outcome. Negative symptoms are prominent among individuals at clinical high-risk (CHR) for psychosis (i.e. those with prodromal syndromes) and highly predictive of conversion to illness. Mechanisms underlying negative symptoms in the CHR population are unclear. Two studies were conducted to evaluate whether abnormalities in a reward processing mechanism thought to be core to negative symptoms in SZ, value representation, also exist in CHR individuals and whether they are associated with negative symptoms transphasically.

Study 1 included 33 individuals in the chronic phase of illness who have been diagnosed with schizophrenia or schizoaffective disorder (SZ) and 40 healthy controls (CN). Study 2 included 37 CHR participants and 45 CN. In both studies, participants completed the delay discounting (DD) task as a measure of value representation and the Brief Negative Symptom Scale was rated to measure negative symptoms.

Results indicated that patients with SZ had steeper discounting rates than CN, indicating impairments in value representation. However, CHR participants were unimpaired on the DD task. In both studies, steeper discounting was associated with greater severity of negative symptoms.

These findings suggest that deficits in value representation are associated with negative symptoms transphasically.

Identifying factors predictive of long-term morbidity should improve clinical planning limiting disability and mortality associated with bipolar disorder (BD).

We analyzed factors associated with total, depressive and mania-related long-term morbidity and their ratio D/M, as %-time ill between a first-lifetime major affective episode and last follow-up of 207 BD subjects. Bivariate comparisons were followed by multivariable linear regression modeling.

Total % of months ill during follow-up was greater in 96 BD-II (40.2%) than 111 BD-I subjects (28.4%; P = 0.001). Time in depression averaged 26.1% in BD-II and 14.3% in BD-I, whereas mania-related morbidity was similar in both, averaging 13.9%. Their ratio D/M was 3.7-fold greater in BD-II than BD-I (5.74 vs. 1.96; P < 0.0001). Predictive factors independently associated with total %-time ill were: [a] BD-II diagnosis, [b] longer prodrome from antecedents to first affective episode, and [c] any psychiatric comorbidity. Associated with %-time depressed were: [a] BD-II diagnosis, [b] any antecedent psychiatric syndrome, [c] psychiatric comorbidity, and [d] agitated/psychotic depressive first affective episode. Associated with %-time in mania-like illness were: [a] fewer years ill and [b] (hypo)manic first affective episode. The long-term D/M morbidity ratio was associated with: [a] anxious temperament, [b] depressive first episode, and [c] BD-II diagnosis.

Long-term depressive greatly exceeded mania-like morbidity in BD patients. BD-II subjects spent 42% more time ill overall, with a 3.7-times greater D/M morbidity ratio, than BD-I. More time depressed was predicted by agitated/psychotic initial depressive episodes, psychiatric comorbidity, and BD-II diagnosis. Longer prodrome and any antecedent psychiatric syndrome were respectively associated with total and depressive morbidity.

Distinguishing prodromes of bipolar disorder (BD) specific to children/adolescents, adults, and elderly patients is essential. The primary objective of this systematic review was to determine initial and relapse prodromes identifying adult patients with BD.

PubMed, PsycINFO, and Web of Science databases were searched using a predetermined strategy. A controlled process of study selection and data extraction was performed.

The 22 articles selected included 1,809 adult patients with BD. Initial prodromes cited most frequently in these studies showed low specificity. Among relapse prodromes cited most frequently, more talkative than usual, increased energy/more goal-directed behavior, thoughts start to race, increased self-esteem, strong interest in sex, increase in activity, and spending too much were identified exclusively before a manic/hypomanic episode, while loss of interest and hypersomnia were detected only before a depressive episode. Initial prodromal phases lasted longer than prodromal relapse phases. In the selected studies, the most used prodrome identification procedure was the clinical interview.

For adult patients with BD, initial and relapse prodromes of manic, hypomanic, and depressive episodes were identified. It is proposed that the most frequent prodromes found in this review be incorporated into a smartphone app that monitors the functioning of people at risk of BD and patients who have already been diagnosed. Data from this app would constitute a relevant source of big data.

Consistent with pathophysiological models of psychosis, temporal disturbances in schizophrenia spectrum populations may reflect abnormal cortical (e.g. prefrontal cortex) and subcortical (e.g. striatum) cerebellar connectivity. However, few studies have examined associations between cerebellar connectivity and timing dysfunction in psychosis populations, and none have been conducted in youth at clinical high-risk (CHR) for psychosis. Thus, it is currently unknown if impairments in temporal processes are present in CHR youth or how they may be associated with cerebellar connectivity and worsening of symptoms.

A total of 108 (56 CHR/52 controls) youth were administered an auditory temporal bisection task along with a resting state imaging scan to examine cerebellar resting state connectivity. Positive and negative symptoms at baseline and 12 months later were also quantified.

Controlling for alcohol and cannabis use, CHR youth exhibited poorer temporal accuracy compared to controls, and temporal accuracy deficits were associated with abnormal connectivity between the bilateral anterior cerebellum and a right caudate/nucleus accumbens striatal cluster. Poor temporal accuracy accounted for 11% of the variance in worsening of negative symptoms over 12 months.

Behavioral findings suggest CHR youth perceive durations of auditory tones as shortened compared to objective time, which may indicate a slower internal clock. Poorer temporal accuracy in CHR youth was associated with abnormalities in brain regions involved in an important cerebellar network implicated in prominent pathophysiological models of psychosis. Lastly, temporal accuracy was associated with worsening of negative symptoms across 12 months, suggesting temporal dysfunction may be sensitive to illness progression.

Disturbances in trait emotions are a predominant feature in schizophrenia. However, less is known about (a) differences in trait emotion across phases of the illness such as the clinical high-risk (CHR) phase and (b) whether abnormalities in trait emotion that are associated with negative symptoms are driven by primary (i.e. idiopathic) or secondary (e.g. depression, anxiety) factors.

To examine profiles of trait affective disturbance and their clinical correlates in individuals with schizophrenia and individuals at CHR for psychosis.

In two studies (sample 1: 56 out-patients diagnosed with schizophrenia and 34 demographically matched individuals without schizophrenia (controls); sample 2: 50 individuals at CHR and 56 individuals not at CHR (controls)), participants completed self-report trait positive affect and negative affect questionnaires, clinical symptom interviews (positive, negative, disorganised, depression, anxiety) and community-based functional outcome measures.

Both clinical groups reported lower levels of positive affect (specific to joy among individuals with schizophrenia) and higher levels of negative affect compared with controls. For individuals with schizophrenia, links were found between positive affect and negative symptoms (which remained after controlling for secondary factors) and between negative affect and positive symptoms. For individuals at CHR, links were found between both affect dimensions and both types of symptom (which were largely accounted for by secondary factors).

Both clinical groups showed some evidence of reduced trait positive affect and elevated trait negative affect, suggesting that increasing trait positive affect and reducing trait negative affect is an important treatment goal across both populations. Clinical correlates of these emotional abnormalities were more integrally linked to clinical symptoms in individuals with schizophrenia and more closely linked to secondary influences such as depression and anxiety in individuals at CHR.

None.

Attenuated positive symptom syndrome (APSS), characterized by ‘putatively prodromal’ attenuated psychotic-like pathology, indicates increased risk for psychosis. Poor premorbid social adjustment predicts severity of APSS symptoms and predicts subsequent psychosis in APSS-diagnosed individuals, suggesting application for improving detection of ‘true’ prodromal youth who will transition to psychosis. However, these predictive associations have not been tested in controls and therefore may be independent of the APSS diagnosis, negating utility for improving prediction in APSS-diagnosed individuals.

Association between premorbid social maladjustment and severity of positive, negative, disorganized, and general APSS symptoms was tested in 156 individuals diagnosed with APSS and 76 help-seeking (non-APSS) controls enrolled in the Enhancing the Prospective Prediction of Psychosis (PREDICT) study using prediction analysis.

Premorbid social maladjustment was associated with social anhedonia, reduced expression of emotion, restricted ideational richness, and deficits in occupational functioning, independent of the APSS diagnosis. Associations between social maladjustment and suspiciousness, unusual thought content, avolition, dysphoric mood, and impaired tolerance to normal stress were uniquely present in participants meeting APSS criteria. Social maladjustment was associated with odd behavior/appearance and diminished experience of emotions and self only in participants who did not meet APSS criteria.

Predictive associations between poor premorbid social adjustment and attenuated psychotic-like pathology were identified, a subset of which were indicative of high risk for psychosis. This study offers a method for improving risk identification while ruling out low-risk individuals.