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

So far, only little more than one-third of individuals classified as being at-risk for psychosis have been shown to actually convert to frank psychosis during follow-up. There have therefore been enormous efforts to improve the accuracy of predicting this transition. We reviewed the most recent studies in the field with the aim to clarify whether accuracy of prediction has been improved by the different research endeavors and what could be done to further improve it, and/or what alternative goals research should pursue.; A total of 56 studies published between May 2015 and December 2016 were included, of which eight were meta-analyses. New meta-analytical evidence confirms that established instruments for checking clinical risk criteria have an excellent clinical utility in individuals referred to high-risk services. Within a such identified group of ultra-high-risk (UHR) individuals, especially Brief Limited Intermittent Psychotic Symptoms and Attenuated Psychotic Symptoms seem to predict transition. Further assessments should be performed within the UHR individuals, as risk of transition seems particularly high in those with an even higher severity of certain symptoms such as suspiciousness or anhedonia, in those with lower global or social functioning, poor neurocognitive performance or cannabis abuse. Also, electroencephalography, neuroimaging and blood biomarkers might contribute to improving individual prediction. The most promising approach certainly is a staged multidomain assessment. Risk calculators to integrate all data for an individualized prediction are being developed.; Prediction of psychosis is already possible with an excellent prognostic performance based on clinical assessments. Recent studies show that this accuracy can be further improved by using multidomain approaches and modern statistics for individualized prediction. The challenge now is the translation into the clinic with a broad clinical implementation

Cannabis und beginnende Psychose

Cannabis ist neben Nikotin und Alkohol eine der am häufigsten psychotropen Substanzen weltweit. Welche Auswirkungen hat regelmässiger Cannabis-Konsum auf die Wahrscheinlichkeit an einer Psychose zu erkranken? Wie wirkt er sich aus bei Personen mit einer Prädisposition oder bei bereits Erkrankten

EEG Microstate Differences in Medicated vs. Medication-Naïve First-Episode Psychosis Patients

There has been considerable interest in the role of synchronous brain activity abnormalities in the pathophysiology of psychotic disorders and their relevance for treatment; one index of such activity are EEG resting-state microstates. These reflect electric field configurations of the brain that persist over 60-120 ms time periods. A set of quasi-stable microstates classes A, B, C, and D have been repeatedly identified across healthy participants. Changes in microstate parameters coverage, duration and occurrence have been found in medication-naïve as well as medicated patients with psychotic disorders compared to healthy controls. However, to date, only two studies have directly compared antipsychotic medication effects on EEG microstates either pre- vs. post-treatment or between medicated and unmedicated chronic schizophrenia patients. The aim of this study was therefore to directly compare EEG resting-state microstates between medicated and medication-naïve (untreated) first-episode (FEP) psychosis patients (mFEP vs. uFEP). We used 19-channel clinical EEG recordings to compare temporal parameters of four prototypical microstate classes (A-D) within an overall sample of 47 patients (mFEP n = 17; uFEP n = 30). The results demonstrated significant decreases of microstate class A and significant increases of microstate class B in mFEP compared to uFEP. No significant differences between groups were found for microstate classes C and D. Further studies are needed to replicate these results in longitudinal designs that assess antipsychotic medication effects on neural networks at the onset of the disorder and over time during illness progression. As treatment response and compliance in FEP patients are relatively low, such studies could contribute to better understand treatment outcomes and ultimately improve treatment strategies

Help-seeking and pathways to care in the early stages of psychosis

Purpose: Delay in the treatment of a first psychotic episode can have a negative influence on the future course of the disease. In this context, it is important to examine pathways to care to understand factors contributing to delay in access to adequate care. Methods: Using the Basel Interview for Psychosis, we examined the help-seeking behaviour of 61 individuals with an at-risk mental state for psychosis and 37 patients with a first episode of psychosis in a low threshold health care system as part of the Basel early detection of psychosis study. Results: The median duration of untreated illness was 3.4years, of untreated psychosis 12months. Eighty-six percent of all individuals sought help of some kind before reaching our specialised early detection outpatient clinic, with a mean number of help-seeking contacts of 1.5 prior to referral. The most frequent first help-seeking contacts were family members or relatives n=24 (26.7%), close friends n=17 (17.9%), psychiatrists in private practice n=13 (14.4%) or general practitioners n=11 (12.2%). Most patients consulted other health professionals in the early course of the illness before reaching our specialised service; help-seeking with non-medical institutions was rare. Women had more help-seeking contacts than men before contact with our early detection clinic. Conclusions: Family, close friends and medical professionals play an important role in help-seeking leading to specialised psychiatric care. Men seek help less often; specific strategies for encouraging young, at-risk men to seek help should be develope

Individualized prediction of psychosis in subjects with an at-risk mental state

Early intervention strategies in psychosis would significantly benefit from the identification of reliable prognostic biomarkers. Pattern classification methods have shown the feasibility of an early diagnosis of psychosis onset both in clinical and familial high-risk populations. Here we were interested in replicating our previous classification findings using an independent cohort at clinical high risk for psychosis, drawn from the prospective FePsy (Fruherkennung von Psychosen) study. The same neuroanatomical-based pattern classification pipeline, consisting of a linear Support Vector Machine (SVM) and a Recursive Feature Selection (RFE) achieved 74% accuracy in predicting later onset of psychosis. The discriminative neuroanatomical pattern underlying this finding consisted of many brain areas across all four lobes and the cerebellum. These results provide proof-of-concept that the early diagnosis of psychosis is feasible using neuroanatomical-based pattern recognition

Aberrant Current Source-Density and Lagged Phase Synchronization of Neural Oscillations as Markers for Emerging Psychosis

Background: Converging evidence indicates that neural oscillations coordinate activity across brain areas, a process which is seemingly perturbed in schizophrenia. In particular, beta (13-30 Hz) and gamma (30-50 Hz) oscillations were repeatedly found to be disturbed in schizophrenia and linked to clinical symptoms. However, it remains unknown whether abnormalities in current source density (CSD) and lagged phase synchronization of oscillations across distributed regions of the brain already occur in patients with an at-risk mental state (ARMS) for psychosis. Methods: To further elucidate this issue, we assessed resting-state EEG data of 63 ARMS patients and 29 healthy controls (HC). Twenty-three ARMS patients later made a transition to psychosis (ARMS-T) and 40 did not (ARMS-NT). CSD and lagged phase synchronization of neural oscillations across brain areas were assessed using eLORETA and their relationships to neurocognitive deficits and clinical symptoms were analyzed using linear mixed-effects models. Results: ARMS-T patients showed higher gamma activity in the medial prefrontal cortex compared to HC, which was associated with abstract reasoning abilities in ARMS-T. Furthermore, in ARMS-T patients lagged phase synchronization of beta oscillations decreased more over Euclidian distance compared to ARMS-NT and HC. Finally, this steep spatial decrease of phase synchronicity was most pronounced in ARMS-T patients with high positive and negative symptoms scores. Conclusions: These results indicate that patients who will later make the transition to psychosis are characterized by impairments in localized and synchronized neural oscillations providing new insights into the pathophysiological mechanisms of schizophrenic psychoses and may be used to improve the prediction of psychosi

Are neurological soft signs pre-existing markers in individuals with an at-risk mental state for psychosis?

Neurological soft signs (NSS) are more common in schizophrenic psychoses and in genetically high-risk individuals than in healthy controls. But nothing is known so far regarding individuals with a clinical at-risk mental state (ARMS). The goals of our study therefore were (a) to compare the NSS frequency in ARMS individuals to that of first-episode psychosis (FEP) patients and (b) to test whether NSS could predict the transition to psychosis. Neurological soft signs were assessed using a shortened version of the Neurological Evaluation Scale (NES). Fifty-three ARMS individuals (16 with later transition to psychosis=ARMS-T, and 37 without transition=ARMS-NT) and 27 FEP patients were recruited through the Basel Early Detection Clinic FePsy. Of the FEP patients 37% showed NSS. We found no significant differences between FEP and ARMS-T patients or between ARMS-NT and ARMS-T. Our findings of NSS being present already before transition to psychosis to the same extent as after transition provide further support to the neurodevelopmental hypothesis of schizophrenic psychoses. Furthermore, our findings might indicate that ARMS-NT individuals also suffer from some sort of neurodevelopmental abnormalities

The Frankfurt Complaint Questionnaire for self-assessment of basic symptoms in the early detection of psychosis-Factor structure, reliability, and predictive validity

OBJECTIVES: Patients with schizophrenia often experience subtle disturbances in several domains of information processing-so-called basic symptoms (BS). BS are already present before onset of frank psychosis and can be assessed by interviews but also by the self-administered Frankfurt Complaint Questionnaire (FCQ). We investigated the factor structure, reliability, and predictive validity for transition to psychosis of the FCQ, comparing previously proposed factor solutions containing 1, 2, 4, and 10 factors. METHODS: Confirmatory factor analysis was used in a sample of 117 at-risk mental state and 92 first-episode psychosis participants of the Basel FePsy (early detection of psychosis) study. RESULTS: Although all factor models fitted to the data, the 2- or 4-factor solutions performed best among the models that used at least half of the FCQ items, suggesting the covariance between FCQ items is best explained by 2 to 4 underlying factors. No FCQ-scale predicted transition to psychosis. CONCLUSION: We could confirm a 2- to 4-factor structure of the FCQ in a sample of at-risk mental state and first-episode psychosis patients using confirmatory factor analysis. Contrary to interview-assessed cognitive-perceptive BS, self-assessed BS do not seem to improve prediction of psychosis. This result reinforces reports of poor correspondence between interview- and questionnaire-assessed BS

Latent state-trait structure of BPRS subscales in clinical high-risk state and first episode psychosis.

To investigate the longitudinal latent state-trait structure of the different dimensions of psychosis symptoms in clinical high-risk state (CHRS) and first episode psychosis (FEP) individuals over a one year time-span. This paper examines if the symptom clusters Positive Symptoms, Negative Symptoms, Affectivity, Resistance, Activation, and Excitement according to the Brief Psychiatric Rating Scale (BPRS) differ in their trait and state characters in 196 CHRS and 131 FEP individuals. Statistical analysis was performed using latent state-trait analysis. On average, trait differences accounted for 72.2% of Positive Symptoms, 81.1% of Negative Symptoms, 57.0% of Affectivity, and 69.2% of Activation, whereas 15.0% of the variance of Resistance and 13.2% of the variance of Excitement were explained by trait differences. Explorative analyses showed a trait components' increase of 0.408 in Positive Symptoms from baseline up to the 9th month and an increase of 0.521 in Affectivity from baseline up to the 6th month. Negative Symptoms had the highest trait component levels of all subscales between baseline and 6 months. The finding that an increasing proportion of psychosis symptoms is persisting over time underlines the importance of early intervention programs in individuals with psychotic disorders

Alpha oscillations underlie working memory abnormalities in the psychosis high-risk state

Working memory (WM) functioning, known to be modulated by neural oscillations, is impaired in schizophrenic psychoses. It remains unclear whether in the psychosis high-risk state, WM encoding is altered or whether patients are impaired at shielding their WM against distractors. We employed single-trial analyses of neurophysiological and behavioral data recorded during a WM paradigm, designed to include predictable distractors, on 18 patients with an at-risk mental state for psychosis (ARMS, 26.1±5.45 years) and 21 healthy controls (HCs, 25.5±3.95 years). Strong distractors were associated with reduced WM accuracy (p=0.036), but only ARMS patients required more processing time for strong distractors (p=0.002). Increased parieto-occipital alpha amplitude preceding distractor presentations was associated with enhanced accuracy only in HCs (p=0.009). During encoding, increased intertrial alpha phase locking values were associated with increased performance. Reduced shielding mechanisms against distractors in ARMS patients could lead to defective WM maintenance, which may result in significant confusion that may contribute to the formation of psychotic symptoms