Hiske E. Becker

Baseline differences in clinical symptomatology between ultra high risk subjects with and without a transition to psychosis.

BACKGROUND The chance of transition to psychosis in patients at Ultra High Risk for developing psychosis (UHR) is 10-15%. The aim of present study was to investigate differences in baseline clinical symptomatology, general level of functioning (GAF-score) and genetic risk between UHR patients who did (UHR+T) or did not (UHR+NT) make a transition to psychosis. Sharpening UHR inclusion criteria may aid in improving prediction of transition to psychosis. METHOD The study sample was taken from 285 patients who were examined within the Dutch Prediction of Psychosis Study (DUPS) at the Academic Medical Center of the University of Amsterdam, the Netherlands. Out of 73 included UHR subjects, 18 made a transition to psychosis. Psychopathology was investigated with the Structured Interview for Prodromal Syndromes, Bonn Scale for the Assessment of Basic Symptoms and GAF-score. The follow-up period of the study was three years. RESULTS The UHR+T group showed more social anhedonia and withdrawal, more bizarre thinking and a lower GAF score at baseline than the UHR+NT group. CONCLUSIONS In agreement with the results of Cannon et al. [Cannon, T.D., Cadenhead, K., Cornblatt, B., Woods, S.W., Addington, J., Walker, E., Seidman, L.J., Perkins, D., Tsuang, M., McGlashan, T., Heinssen, R., 2008. Prediction of Psychosis in Youth at High Clinical Risk: A Multisite Longitudinal Study in North America. Arch. Gen. Psychiat. 65 (1) 28-37.], our study indicates that severity of specific symptoms at baseline is related to transition to psychosis in UHR subjects. These findings may contribute to a more accurate prediction of a first psychotic episode. Furthermore, symptoms that are increased at baseline in the UHR+T group could be a focus of cognitive behavioural therapy in the UHR period.

Disability in people clinically at high risk of psychosis

BACKGROUND Decline in social functioning occurs in individuals who later develop psychosis. AIMS To investigate whether baseline differences in disability are present in those who do and those who do not make a transition to psychosis in a group clinically at high risk and whether disability is a risk factor for transition. METHOD Prospective multicentre, naturalistic field study with an 18-month follow-up period on 245 help-seeking individuals clinically at high risk. Disability was assessed with the Disability Assessment Schedule of the World Health Organization (WHODAS-II). RESULTS At baseline, the transition group displayed significantly greater difficulties in making new friends (z = -3.40, P = 0.001), maintaining a friendship (z =-3.00, P = 0.003), dealing with people they do not know (z =-2.28, P = 0.023) and joining community activities (z =-2.0, P = 0.05) compared with the non-transition group. In Cox regression, difficulties in getting along with people significantly contributed to the prediction of transition to psychosis in our sample (β = 0.569, s.e. = 0.184, Wald = 9.548, P = 0.002, hazard ratio (HR) = 1.767, 95% CI 1.238-2.550). CONCLUSIONS Certain domains of social disability might contribute to the prediction of psychosis in a sample clinically at high risk.

White matter fibertracking in first-episode schizophrenia, schizoaffective patients and subjects at ultra-high risk of psychosis

There is increasing evidence of white matter pathology in schizophrenia. The aim of this study was to examine whether white matter abnormalities found with diffusion tensor imaging (DTI) in previous schizophrenia studies are present in the early phase of the illness. DTI was performed at 3 T on 10 male patients with a first (n = 8) or second (n = 2) psychotic episode of schizophrenia or schizoaffective disorder, 10 male patients at ultra-high risk of psychosis with (pre)psychotic symptoms and 10 healthy controls. Fibertracts found to be abnormal in other DTI studies (uncinate and arcuate fasciculus, anterior and dorsal cingulum, subdivisions of the corpus callosum) were calculated and visualized; tract-specific measurements (fractional anisotropy and trace) were performed. No differences were found between the healthy subjects and the 2 patient groups. These preliminary findings suggest that there is no white matter pathology of these association tracts detectable with DTI in the early stages of schizophrenic illness in males. Our findings are in contrast with DTI abnormalities found in some other first-episode studies. This discrepancy in findings may be related to differences in subject characteristics and DTI methodology. Possible effects of age, gender, level of education and illicit substance use on DTI findings in schizophrenia are discussed.

Neurocognitive functioning before and after the first psychotic episode: does psychosis result in cognitive deterioration?

BACKGROUND Cognitive impairment is considered to be a core characteristic of schizophrenia. The relationship between psychosis and cognitive deterioration, however, remains unclear. This longitudinal study investigated the neuropsychological functioning of patients before and after their first psychotic episode. Cognitive functioning of participants who later developed a psychosis was compared to that of people at ultra-high risk (UHR) for psychosis who did not develop psychosis at follow-up and healthy controls.MethodParticipants were 41 persons at UHR for psychosis (the UHR group), of whom 17 developed psychosis between the first and second assessment. Seventeen healthy controls were included in the study. Cognitive performance was assessed at intake (T0) and again after 18 months (T1). The areas of cognitive functioning assessed include verbal memory and learning, visuospatial working memory, executive function, sustained attention and motor speed. RESULTS The transition group did not perform significantly worse at the second assessment than at the first on any of the outcome measures. The UHR group performed better on a verbal learning and memory test at T1 compared to T0. At T0, the control group scored significantly better than the UHR group and the transition group on the verbal learning and memory test and the verbal fluency test. CONCLUSIONS The results indicate that no cognitive deterioration occurs during the first psychotic episode. Problems in verbal memory may be present before the first episode of psychosis.

Cannabis use and age at onset of symptoms in subjects at clinical high risk for psychosis

Dragt S, Nieman DH, Schultze‐Lutter F, van der Meer F, Becker H, de Haan L, Dingemans PM, Birchwood M, Patterson P, Salokangas RKR, Heinimaa M, Heinz A, Juckel G, Graf von Reventlow H, French P, Stevens H, Ruhrmann S, Klosterkötter J, Linszen DH, on behalf of the EPOS group. Cannabis use and age at onset of symptoms in subjects at clinical high risk for psychosis.

Environmental factors and social adjustment as predictors of a first psychosis in subjects at ultra high risk

BACKGROUND The onset of schizophrenia is associated with genetic, symptomatic, social and environmental risk factors. The aim of the present study was to determine which environmental factors may contribute to a prediction of a first psychotic episode in subjects at Ultra High Risk (UHR) for developing psychosis. METHOD We included 72 UHR subjects and followed them over a period of 36 months, of whom nineteen (26.4%) made a transition to psychosis. We applied survival analyses to determine associations between a transition to psychosis and environmental factors and social adjustment. To determine which items are the best predictors of transition to a first psychotic episode, Cox Regression analyses were applied. RESULTS Urbanicity, receiving state benefits and poor premorbid adjustment (PMA) significantly influenced the transition to psychosis. Urbanicity (Wald=10.096, p=.001, HR=30.97), social-sexual aspects (Wald=8.795, p=.003, HR=1.91) and social-personal adjustment (Wald=10.794, p=.001, HR=4.26) appeared to be predictors for developing psychosis in our UHR group. CONCLUSIONS Environmental characteristics and social adjustment are predictive of transition to a psychosis in subjects at UHR. These characteristics should be implemented in a model for prediction of psychosis. Such a model would be more specific than current models and may lead to patient-specific preventive interventions.

Early intervention in patients at ultra high risk of psychosis: benefits and risks

Objective:  Prediction of transition to psychosis in the prodromal phase of schizophrenia has raised interest in intervention prior to the onset of frank psychosis. The aim of this review was to examine whether interventions in the prodromal phase have a favourable benefit/risk ratio.

Pathways to psychosis: a comparison of the pervasive developmental disorder subtype Multiple Complex Developmental Disorder and the "At Risk Mental State".

BACKGROUND The comparison of high-risk populations with different developmental pathways to psychosis may lend more insight into the heterogeneity of the manifestation of the psychotic syndrome, and possible differing etiological pathways. AIM To compare high-risk traits and symptoms in two populations at risk for psychosis, i.e. (1) help-seeking adolescents presenting with prodromal symptoms meeting the criteria for At Risk Mental State (ARMS), and (2) adolescents with Multiple Complex Developmental Disorder (MCDD), a PDD-NOS subtype characterized by severe, early childhood-onset deficits in affect regulation, anxieties, disturbed social relationships, and thought disorder. METHOD 80 ARMS- and 32 MCDD-adolescents (12-18 years) were compared on prodromal symptoms (Structured Interview of Prodromal Symptoms, and Bonn Scale for the Assessment of Basic Symptoms-Prediction list), and autism traits (Social Communication Questionnaire). In addition, both high-risk groups were compared with 82 healthy controls on schizotypal traits (Schizotypal Personality Questionnaire-Revised). RESULTS Although the high-risk groups clearly differed in early developmental and treatment histories as well as autism traits, they did not differ with regard to schizotypal traits and basic symptoms, as well as disorganized and general prodromal symptoms. There were, however, group differences in positive and negative prodromal symptoms. Interestingly, 78% of the adolescents with MCDD met criteria for ARMS. CONCLUSION These findings suggest that children diagnosed with MCDD are at high risk for developing psychosis later in life, and support the notion that there are different developmental pathways to psychosis. Follow-up research is needed to compare the rates of transition to psychosis in both high-risk groups.

Age of onset of cannabis use is associated with age of onset of high-risk symptoms for psychosis.

Objective: Increasing interest in the prodromal stage of schizophrenia over the past decade led us to perform our study to monitor people at high risk for developing a psychosis. We hypothesized that cannabis use or a cannabis use disorder at a younger age relates to high-risk symptoms at a younger age. Method: People referred to the Academic Medical Centre in Amsterdam, the Netherlands, with an ultra-high risk (UHR) for psychosis were interviewed with the Composite International Diagnostic Interview to assess their cannabis consumption. The Interview for the Retrospective Assessment of the Onset of Schizophrenia was used to collect data about age of onset of high-risk or prodromal symptoms. Nine high-risk symptoms were selected and clustered because of their known relation with cannabis use. Results: Among the 68 included participants, 35 had used cannabis (51.5%), of whom 15 had used recently. Twenty-two participants had been cannabis abusers or cannabis-dependent (32.4%) in the past. Younger age at onset of cannabis use was related to younger age of onset of the cluster of symptoms (rho = 0.48, P = 0.003) and also to 6 symptoms individually (rho = 0.47 to 0.90, P < 0.001 to 0.04). Younger age at onset of a cannabis use disorder was related to younger age of onset of the cluster of symptoms (rho = 0.67, P = 0.001) and also to 6 symptoms individually (rho = 0.50 to 0.93, P = 0.007 to 0.03). Conclusion: Cannabis use or a cannabis use disorder at a younger age in a group with an UHR for transition to psychosis is related to onset of high-risk symptoms for psychosis at a younger age.

Psychosis Prediction: Stratification of Risk Estimation With Information-Processing and Premorbid Functioning Variables

BACKGROUND The period preceding the first psychotic episode is regarded as a promising period for intervention. We aimed to develop an optimized prediction model of a first psychosis, considering different sources of information. The outcome of this model may be used for individualized risk estimation. METHODS Sixty-one subjects clinically at high risk (CHR), participating in the Dutch Prediction of Psychosis Study, were assessed at baseline with instruments yielding data on neuropsychology, symptomatology, environmental factors, premorbid adjustment, and neurophysiology. The follow-up period was 36 months. RESULTS At 36 months, 18 participants (29.5%) had made a transition to psychosis. Premorbid adjustment (P = .001, hazard ratio [HR] = 2.13, 95% CI = 1.39/3.28) and parietal P300 amplitude (P = .004, HR = 1.27, 95% CI = 1.08/1.45) remained as predictors in the Cox proportional hazard model. The resulting prognostic score (PS) showed a sensitivity of 88.9% and a specificity of 82.5%. The area under the curve of the PS was 0.91 (95% CI = 0.83-0.98, cross-validation: 0.86), indicating an outstanding ability of the model to discriminate between transition and nontransition. The PS was further stratified into 3 risk classes establishing a prognostic index. In the class with the worst social-personal adjustment and lowest P300 amplitudes, 74% of the subjects made a transition to psychosis. Furthermore, transition emerged on average more than 17 months earlier than in the lowest risk class. CONCLUSIONS Our results suggest that predicting a first psychotic episode in CHR subjects could be improved with a model including premorbid adjustment and information-processing variables in a multistep algorithm combining risk detection and stratification.