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Negative symptoms occur frequently in individuals at clinical high risk (CHR) for psychosis and contribute to functional impairments. The aim of this study was to predict negative symptom severity in CHR after 9 months. Predictive models either included baseline negative symptoms measured with the Structured Interview for Psychosis-Risk Syndromes (SIPS-N), whole-brain gyrification, or both to forecast negative symptoms of at least moderate severity in 94 CHR. We also conducted sequential risk stratification to stratify CHR into different risk groups based on the SIPS-N and gyrification model. Additionally, we assessed the models' ability to predict functional outcomes in CHR and their transdiagnostic generalizability to predict negative symptoms in 96 patients with recent-onset psychosis (ROP) and 97 patients with recent-onset depression (ROD). Baseline SIPS-N and gyrification predicted moderate/severe negative symptoms with significant balanced accuracies of 68 and 62%, while the combined model achieved 73% accuracy. Sequential risk stratification stratified CHR into a high (83%), medium (40-64%), and low (19%) risk group regarding their risk of having moderate/severe negative symptoms at 9 months follow-up. The baseline SIPS-N model was also able to predict social (61%), but not role functioning (59%) at above-chance accuracies, whereas the gyrification model achieved significant accuracies in predicting both social (76%) and role (74%) functioning in CHR. Finally, only the baseline SIPS-N model showed transdiagnostic generalization to ROP (63%). This study delivers a multimodal prognostic model to identify those CHR with a clinically relevant negative symptom severity and functional impairments, potentially requiring further therapeutic consideration.

Aim: Gender differences in the current symptomatology of patients with psychotic disorders have previously been described in the literature. However, it has not yet been investigated whether gender differences exist in the very first self-perceived signs or symptoms of illness onset. The aim of this study was to investigate this aspect in at-risk mental state (ARMS) and first-episode psychosis (FEP) patients., Methods: ARMS and FEP were recruited via the early detection of psychosis (FePsy) clinic Basel, Switzerland. The Basel Interview for Psychosis (BIP) was used to retrospectively assess the first 3 self-perceived signs and symptoms at illness onset. Differences between gender and patient groups on single item and symptom cluster levels were analysed using logistic regression models., Results: One-hundred-thirty six ARMS (91 men, 45 women) and 89 FEP patients (63 men, 26 women) could be recruited for this study. On a single item level, women more frequently reported "unusual anxiety, fears" and men (at a trend level) "social withdrawal" as being among their 3 first self-perceived symptoms, independent of diagnostic group. On the symptom cluster level, women more frequently reported "increased worrying/anxiety" and (sub-threshold) "hallucinations", independent of diagnostic group. Problems with "thinking, concentration" were reported more frequently by men in the ARMS group only., Conclusion: Our results suggest that only few and relatively small gender differences exist in the first self-perceived signs and symptoms. While men initially mainly notice negative/cognitive symptoms, women first notice (sub-threshold) positive and affective symptoms., (© 2017 John Wiley & Sons Australia, Ltd.)

Aim: Research findings on the correlations between self-rating and observer-rating of schizophrenic psychopathology are inconsistent and have rarely considered first-episode psychosis (FEP) and at-risk mental state (ARMS) for psychosis patients. This study investigates these correlations in ARMS and FEP patients and how they are moderated by disease stage and gender., Methods: In the Basel Früherkennung von Psychosen (FePsy) study, positive and negative psychotic and affective symptoms were rated in 126 ARMS and 94 FEP patients using two observer- and three self-rating scales. The agreement between self-rating and observer-rating and the moderating influence of disease stage and gender was quantified using Pearson correlation and multiple regression models., Results: Correlations between self- and observer-rated subscales covering the same symptom dimension were low and mostly non-significant except for one correlation of positive and one of negative symptoms. There was no moderating influence of disease stage and gender on the correlations between self-rating and observer-rating except for one higher association in positive symptoms in FEP compared to ARMS and in women compared to men. However, these significant interaction effects did not withstand correction for multiple testing., Conclusions: This study suggests that the agreement between self-rating and observer-rating in FEP and ARMS patients is rather low, similar across symptom dimensions, and only partially dependent on disease stage and gender. However, low correlations between self-rating and observer-rating do not necessarily indicate that these patients have difficulties reporting their symptoms. They could also have occurred because the scales did not exactly cover the same symptom dimensions., (© 2015 Wiley Publishing Asia Pty Ltd.)

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 psychosis., (© The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

To date, the MRI-based individualized prediction of psychosis has only been demonstrated in single-site studies. It remains unclear if MRI biomarkers generalize across different centers and MR scanners and represent accurate surrogates of the risk for developing this devastating illness. Therefore, we assessed whether a MRI-based prediction system identified patients with a later disease transition among 73 clinically defined high-risk persons recruited at two different early recognition centers. Prognostic performance was measured using cross-validation, independent test validation, and Kaplan-Meier survival analysis. Transition outcomes were correctly predicted in 80% of test cases (sensitivity: 76%, specificity: 85%, positive likelihood ratio: 5.1). Thus, given a 54-month transition risk of 45% across both centers, MRI-based predictors provided a 36%-increase of prognostic certainty. After stratifying individuals into low-, intermediate-, and high-risk groups using the predictor's decision score, the high- vs low-risk groups had median psychosis-free survival times of 5 vs 51 months and transition rates of 88% vs 8%. The predictor's decision function involved gray matter volume alterations in prefrontal, perisylvian, and subcortical structures. Our results support the existence of a cross-center neuroanatomical signature of emerging psychosis enabling individualized risk staging across different high-risk populations. Supplementary results revealed that (1) potentially confounding between-site differences were effectively mitigated using statistical correction methods, and (2) the detection of the prodromal signature considerably depended on the available sample sizes. These observations pave the way for future multicenter studies, which may ultimately facilitate the neurobiological refinement of risk criteria and personalized preventive therapies based on individualized risk profiling tools., (© The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Aim: 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., Methods: Neurocognitive performance of four groups was analysed: 22 ARMS individuals with later transition to psychosis (ARMS-T), 25 ARMS individuals without later transition to psychosis (ARMS-NT), 34 controls with depressive disorders and 76 healthy controls. The subjects were assessed with a neurocognitive test battery covering the domains' intelligence, executive function and attention/ working memory. MANOVAs, ANOVAs and Tukey's tests were applied after adjustment for confounding factors., Results: ARMS-T showed significant cognitive deficits in working memory and in certain executive function tasks compared with healthy controls as well as with controls with depression. Controls with depression were only impaired in time per move in the tower of Hanoi test when compared with healthy controls., Conclusions: The psychosis prodrome seems to be associated with cognitive deficits in the domains of working memory and executive function. In contrast, depressive patients showed no cognitive deficits, but slowing in one executive function task. Neurocognitive testing might therefore contribute to the differential diagnosis between prodromal psychosis and depressive disorders., (© 2012 Wiley Publishing Asia Pty Ltd.)

Background: The at-risk mental state for psychosis (ARMS) and the first episode of psychosis have been associated with structural brain abnormalities that could aid in the individualized early recognition of psychosis. However, it is unknown whether the development of these brain alterations predates the clinical deterioration of at-risk individuals, or alternatively, whether it parallels the transition to psychosis at the single-subject level., Methods: We evaluated the performance of an magnetic resonance imaging (MRI)-based classification system in classifying disease stages from at-risk individuals with subsequent transition to psychosis (ARMS-T) and patients with first-episode psychosis (FE). Pairwise and multigroup biomarkers were constructed using the structural MRI data of 22 healthy controls (HC), 16 ARMS-T and 23 FE subjects. The performance of these biomarkers was measured in unseen test cases using repeated nested cross-validation., Results: The classification accuracies in the HC vs FE, HC vs ARMS-T, and ARMS-T vs FE analyses were 86.7%, 80.7%, and 80.0%, respectively. The neuroanatomical decision functions underlying these discriminative results particularly involved the frontotemporal, cingulate, cerebellar, and subcortical brain structures., Conclusions: Our findings suggest that structural brain alterations accumulate at the onset of psychosis and occur even before transition to psychosis allowing for the single-subject differentiation of the prodromal and first-episode stages of the disease. Pattern regression techniques facilitate an accurate prediction of these structural brain dynamics at the early stage of psychosis, potentially allowing for the early recognition of individuals at risk of developing psychosis.