Marlon O. Pflueger

Efficacy of Using Cognitive Status in Predicting Psychosis: A 7-Year Follow-Up

BACKGROUND Despite extensive early detection research in schizophrenic psychoses, methods for identifying at-risk individuals and predicting their transition to psychosis are still unreliable. Moreover, there are sparse data on long-term prediction. We therefore investigated long-term psychosis transition in individuals with an At Risk Mental State (ARMS) and examined the relative efficacy of clinical and neuropsychological status in optimizing the prediction of transition. METHODS Sixty-four individuals with ARMS for psychosis were identified from all referrals to our early detection clinic between March 1, 2000 and February 29, 2004. Fifty-three (83%) were followed up for up to 7 (mean 5.4) years. RESULTS Twenty-one of the 53 staying in follow-up developed psychosis, corresponding to a transition rate of .34 (Kaplan-Meier estimates). Median time to transition was 10 months (range <1-55). Six of all transitions (29%) occurred only after 12 months from referral. Best transition predictors within this population were selected attenuated psychotic symptoms (suspiciousness), negative symptoms (anhedonia/asociality), and cognitive deficits (reduced speed of information processing). With these predictors in an integrated model for predicting transition to psychosis, the overall predictive accuracy was 80.9% with a sensitivity of 83.3% and a specificity of 79.3%. CONCLUSIONS Follow-up of ARMS subjects should exceed the usual 12 months. Prediction of transitions could be improved by a stronger weighting of certain early symptoms and by introducing neurocognitive tests into a stepwise risk assessment. Confirmatory research will hopefully further improve risk algorithm, including psychopathology and neuropsychological performance, for clinical application in early detection clinics.

Neuropsychological deficits in individuals with an at risk mental state for psychosis — Working memory as a potential trait marker

OBJECTIVE To investigate the neuropsychological profile of individuals with an at risk mental state for psychosis (ARMS, N=60) compared to healthy controls (HC, N=51) and to identify those cognitive domains which discriminate best between groups. METHOD Study subjects and controls were compared using a neuropsychological test battery covering the domains of intelligence (LPS3, MWT-A), executive functions (ToH, WCST, TAP - Go/NoGo), working memory (Tests for Attentional Performance (TAP) - Working Memory), and attention (CPT-OX). A multivariate analysis of variance (MANOVA) comparing ARMS subjects with HC was conducted. A stepwise logit regression procedure was performed in order to determine the subset of measures which best distinguish ARMS subjects from HC. RESULTS ARMS subjects revealed deficiencies in intelligence, executive functions, working memory and attention. Verbal intelligence, executive functions, and, in particular, working memory discriminated best between the groups. CONCLUSION Individuals with an at risk mental state for psychosis already show impairment of neuropsychological functions prior to the onset of the first psychotic episode and can best be distinguished from healthy controls on the basis of working memory.

Hippocampus abnormalities in at risk mental states for psychosis? A cross-sectional high resolution region of interest magnetic resonance imaging study

BACKGROUND Hippocampal volume (HV) reduction is well documented in schizophrenia. However, it is still unclear whether this change is a pre-existing vulnerability factor, a sign of disease progression, a consequence of environmental factors, such as drug use, antipsychotic medication, or malnutrition. The timing of HV changes is not well established, but a lack of macrostructural hippocampal brain abnormalities before disease onset would rather support a neuroprogressive illness model. AIM To investigate the timing of HV changes in emerging psychosis. METHODS A cross-sectional MRI study of manually traced HVs in 37 individuals with an At Risk Mental State (ARMS) for psychosis, 23 individuals with First-Episode Psychosis (FEP), and 22 Healthy Controls (HC) was performed. We compared left and right HVs corrected for whole brain volume across groups using analysis of covariance (ANCOVA) with gender as a covariate. Sixteen of 37 ARMS individuals developed a psychotic disorder during follow up (ARMS-T). The mean duration of follow up in ARMS was 25.1months. RESULTS The overall ANCOVA model comparing left HVs across FEP, ARMS and HC indicated a significant general group effect (p<.05) with largest volumes in ARMS and smallest in FEP. ARMS-T subjects had significantly larger left HVs compared to FE but no HV differences compared to HC (p<0.05). Over all groups, we found an asymmetry between the left and right mean HVs and a strong effect of sex. DISCUSSION The present study suggests that macrostructural hippocampal abnormalities probably occur in the context of the first psychotic breakdown.

Hyperprolactinemia in antipsychotic-naive patients with first-episode psychosis

BACKGROUND Hyperprolactinemia is frequent in patients with schizophrenic psychoses. It is usually regarded as an adverse effect of antipsychotics but has recently also been shown in patients without antipsychotic medication. Our objective was to test whether hyperprolactinemia occurs in antipsychotic-naive first-episode patients (FEPs). METHOD In the framework of the European First Episode Schizophrenia Trial (EUFEST), 249 out of 498 FEPs were eligible for this study, of whom 74 were antipsychotic naive. All patients were investigated regarding their serum prolactin levels with immunoassays standardized against the 3rd International Reference Standard 84/500. RESULTS Twenty-nine (39%) of the 74 antipsychotic-naive patients showed hyperprolactinemia not explained by any other reason, 11 (50%) of 22 women and 18 (35%) of 52 men. CONCLUSIONS Hyperprolactinemia may be present in patients with schizophrenic psychoses independent of antipsychotic medication. It might be stress induced. As enhanced prolactin can increase dopamine release through a feedback mechanism, this could contribute to explaining how stress can trigger the outbreak of psychosis.

Pituitary volume increase during emerging psychosis

BACKGROUND Morphologic abnormalities of the pituitary gland volume (PV) have been reported in schizophrenia, but at what point in time they occur remains unclear. This study determines PV across different stages of emerging psychotic disorders compared to healthy controls. METHODS We compared PV of 36 individuals with an at-risk mental state (ARMS) for psychosis, 23 patients with a first episode psychosis (FEP) and 20 healthy controls (HC). Transition to psychosis was monitored using the BPRS transition criteria according to Yung et al. (Yung, A.R. et al., 1998. Prediction of psychosis. A step towards indicated prevention of schizophrenia. Br. J. Psychiatry Suppl. 172 (33), 14-20). Applying these transition criteria, 16 of the 36 ARMS individuals made the transition to psychosis (ARMS-T) and 20 did not (ARMS-NT). We traced PV manually on 1mm slices of magnetic resonance images in three dimensions (coronal, sagittal and axial) blind to group status. We used univariate analysis of covariance (ANCOVA) with PV as dependent variable, group and sex as between-subject factors and whole brain volume as covariate. RESULTS PV increased from HC to ARMS-NT to ARMS-T/FEP. ANCOVA revealed a significant effect of group (F(3,78)=3.0; p=.036) and a sex × group interaction (F(3,78)=6.5; p=.001). Over all groups, women had considerably larger PV than men (F(1,78)=9.8; p=.003). CONCLUSIONS Our findings provide further evidence that PV is increased in emerging psychotic disorders, and suggest that this is due to a stress-associated activation of the pituitary gland.

Duration of untreated psychosis and cognitive functioning.

BACKGROUND Studies examining the influence of duration of untreated psychosis (DUP) or duration of untreated illness (DUI) on cognition vary with regard to results and methods. This study is the first in this field to include an at risk mental state with later transition to psychosis (ARMS-T) sample and to analyse how the DUI relates to their cognitive functioning. Because methodological operationalization of cognitive functioning in previous studies is highly heterogeneous, we aimed to compare different approaches. METHOD 60 first episode psychosis (FEP) patients and 24 ARMS-T patients were examined. Associations between DUP, DUI and neurocognitive performance were tested by three different operationalizations of cognition: as the raw outcome measure of different neuropsychological tests, as outcome scores which were normed on a sample of 75 healthy participants, and as the deterioration index (DI). RESULTS There were no significant correlations between DUP or DUI and outcome of neuropsychological tests in both normed and raw scores. When adjusted for covariates, DUP and DUI also did not significantly predict any cognitive performance. There was no significant relationship between DUP or DUI and the DI index. However, longer DUP and DUI were significantly associated with stronger negative symptoms. CONCLUSIONS This study could not confirm an association between duration of untreated psychosis or duration of untreated illness and neurocognitive performance in the ARMS-T and FEP samples. This could be because schizophrenic psychoses are neurodevelopmental disorders in which most cognitive deficits exist long before the onset of psychiatric symptoms.

Negative symptoms in neuroleptic-naïve patients with first-episode psychosis correlate with QEEG parameters

INTRODUCTION While several studies have shown an association of QEEG band power with negative symptoms in patients with schizophrenia, this has not yet been investigated in a sample with neuroleptic-naïve first-episode patients (NNFE) up to now. From literature we hypothesized delta (0.5-4Hz) and theta (4-8Hz) power to be augmented and alpha (8-12Hz) power to be decreased with increased negative symptoms in NNFE. MATERIALS AND METHODS The sample consisted of 27 NNFE. Psychopathology was rated with the Scale for the Assessment of Negative Symptoms (SANS). EEG was recorded from 21 electrodes according to the 10/20 system. Spectral analysis was performed on mean power of 8 electrodes in seven frequency bands after artefact removal. Linear regressions were calculated with log transformed power as dependent and psychopathology as independent variable. We controlled for medication, drugs, age, sex, education and day time of EEG recording. RESULTS A positive correlation of SANS global score with power in delta and theta frequency bands could be confirmed in NNFE. In the alpha1 (8-10Hz) band we found no significant correlation with negative symptoms and in the alpha2 (10-12Hz) band there was a positive correlation with SANS (p=0.069). Beta1 (12-15Hz) power also correlated positively with SANS. DISCUSSION The present results confirm the correlation of negative symptoms with power of slow frequency bands. In addition to previous studies in chronic schizophrenia patients, the effect was shown in NNFE, which is compatible with augmented slow wave power being a marker for negative symptoms in psychosis.

Sleep Disruption and Daytime Sleepiness Correlating with Disease Severity and Insulin Resistance in Non-Alcoholic Fatty Liver Disease: A Comparison with Healthy Controls

Background & Aims Sleep disturbance is associated with the development of obesity, diabetes and hepatic steatosis in murine models. Hepatic triglyceride accumulation oscillates in a circadian rhythm regulated by clock genes, light-dark cycle and feeding time in mice. The role of the sleep-wake cycle in the pathogenesis of human non-alcoholic fatty liver disease (NAFLD) is indeterminate. We sought to detail sleep characteristics, daytime sleepiness and meal times in relation to disease severity in patients with NAFLD. Methods Basic Sleep duration and latency, daytime sleepiness (Epworth sleepiness scale), Pittsburgh sleep quality index, positive and negative affect scale, Munich Chronotype Questionnaire and an eating habit questionnaire were assessed in 46 patients with biopsy-proven NAFLD and 22 healthy controls, and correlated with biochemical and histological parameters. Results In NAFLD compared to healthy controls, time to fall asleep was vastly prolonged (26.9 vs. 9.8 min., p = 0.0176) and sleep duration was shortened (6.3 vs. 7.2 hours, p = 0.0149). Sleep quality was poor (Pittsburgh sleep quality index 8.2 vs. 4.7, p = 0.0074) and correlated with changes in affect. Meal frequency was shifted towards night-times (p = 0.001). In NAFLD but not controls, daytime sleepiness significantly correlated with liver enzymes (ALAT [r = 0.44, p = 0.0029], ASAT [r = 0.46, p = 0.0017]) and insulin resistance (HOMA-IR [r = 0.5, p = 0.0009]) independent of cirrhosis. In patients with fibrosis, daytime sleepiness correlated with the degree of fibrosis (r = 0.364, p = 0.019). Conclusions In NAFLD sleep duration was shortened, sleep onset was delayed and sleep quality poor. Food-intake was shifted towards the night. Daytime sleepiness was positively linked to biochemical and histologic surrogates of disease severity. The data may indicate a role for sleep-wake cycle regulation and timing of food-intake in the pathogenesis of human NAFLD as suggested from murine models.

Vorhersage von Psychosen durch stufenweise Mehrebenenabklärung - Das Basler FePsy(Früherkennung von Psychosen)-Projekt

BACKGROUND We have conducted various studies in Basel with the aim of improving the methods for the early detection of psychosis (Früherkennung von Psychosen, FePsy). METHODS From 1.3.2000 to 29.2.2004 234 individuals were screened using the Basel Screening Instrument for Psychosis (BSIP). 106 patients were identified as at risk for psychosis; out of these 53 remained in follow-up for up to 7 years (mean 5.4 years). The assessments were done with a specifically developed instrument for history taking, various scales for the psychopathology, assessments of neuropsychology and fine motor functioning, clinical and quantitative EEG, MRI of the brain, laboratory etc. RESULTS Based on the BSIP alone, a relatively reliable prediction was possible: 21 (39.6%) of the individuals identified as at risk developed psychosis within the follow-up time. Post-hoc prediction could be improved to 81% by weighting psychopathology and including neuropsychology. Including the other domains obviously allows further improvements of prediction. CONCLUSIONS The risk for psychosis should be assessed in a stepwise procedure. In a first step, a clinically oriented screening should be conducted. If an at-risk status is found, further assessments in various domains should be done in a specialised centre.

Can cognitive deficits facilitate differential diagnosis between at-risk mental state for psychosis and depressive disorders?

Many studies have provided evidence of cognitive deficits in individuals in an ‘At Risk Mental State’ (ARMS) for psychosis, which makes neuropsychology potentially useful in the early detection of psychosis. As depression is an important differential diagnosis in prodromal states of psychosis, the specificity of neurocognitive deficits in ARMS individuals as compared with non‐psychotic depressive disorders is investigated.