Clinical high-risk criteria of psychosis in 8-17-year-old community subjects and inpatients not suspected of developing psychosis.

Background: In children and adolescents compared to adults, clinical high-risk of psychosis (CHR) criteria and symptoms are more prevalent but less psychosis-predictive and less clinically relevant. Based on high rates of non-converters to psychosis, especially in children and adolescents, it was suggested that CHR criteria were: (1) Pluripotential; (2) A transdiagnostic risk factor; and (3) Simply a severity marker of mental disorders rather than specifically psychosis-predictive. If any of these three alternative explanatory models were true, their prevalence should differ between persons with and without mental disorders, and their severity should be associated with functional impairment as a measure of severity.

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.

Importance: Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to young patients with depressive syndromes remains unclear.

Objectives: To evaluate whether psychosis transition can be predicted in patients with CHR or recent-onset depression (ROD) using multimodal machine learning that optimally integrates clinical and neurocognitive data, structural magnetic resonance imaging (sMRI), and polygenic risk scores (PRS) for schizophrenia; to assess models' geographic generalizability; to test and integrate clinicians' predictions; and to maximize clinical utility by building a sequential prognostic system.

Rare copy number variants in individuals at clinical high risk for psychosis: Enrichment of synaptic/brain-related functional pathways.

Schizophrenia is a complex and chronic neuropsychiatric disorder, with a heritability of around 60-80%. Large (>100 kb) rare (<1%) copy number variants (CNVs) occur more frequently in schizophrenia patients compared to controls. Currently, there are no studies reporting genome-wide CNVs in clinical high risk for psychosis (CHR-P) individuals.

Adolescents and adults at clinical high-risk for psychosis: age-related differences in attenuated positive symptoms syndrome prevalence and entanglement with basic symptoms.

Background: The attenuated positive symptoms syndrome (APSS) is considered an at-risk indicator for psychosis. However, the characteristics and developmental aspects of the combined or enriched risk criteria of APSS and basic symptom (BS) criteria, including self-experienced cognitive disturbances (COGDIS) remain under-researched.

Method: Based on the Structured Interview of Prodromal Syndromes (SIPS), the prevalence of APSS in 13- to 35-year-old individuals seeking help in an early recognition program for schizophrenia and bipolar-spectrum disorders was examined.

Changes in neurocognitive functioning during transition to manifest disease: comparison of individuals at risk for schizophrenic and bipolar affective psychoses.

Background: Neurocognitive deficits are important aspects of schizophrenic disorder because they have a strong impact on social and vocational outcomes. Previously it was assumed that cognitive abilities progressively deteriorate with illness onset. However, recent research results have contradicted this with observations of continuous or even improved performance in individuals at risk for psychosis or manifest schizophrenia.

Neurocognitive profiles in help-seeking individuals: comparison of risk for psychosis and bipolar disorder criteria.

Background: Neurocognitive deficits are important aspects of the schizophrenic disorders because they have a strong impact on social and vocational outcomes. We expanded on previous research by focusing on the neurocognitive profiles of persons at high risk (HR) or ultra-high risk (UHR) for schizophrenic and affective psychoses. Our main aim was to determine whether neurocognitive measures are sufficiently sensitive to predict a group affiliation based on deficits in functional domains.