The "at risk mental state" for psychosis approach has been a catalytic, highly productive research paradigm over the last 25 years. In this paper we review that paradigm and summarize its key lessons, which include the valence of this phenotype for future psychosis outcomes, but also for comorbid, persistent or incident non-psychotic disorders; and the evidence that onset of psychotic disorder can at least be delayed in ultra high risk (UHR) patients, and that some full-threshold psychotic disorder may emerge from risk states not captured by UHR criteria. The paradigm has also illuminated risk factors and mechanisms involved in psychosis onset. However, findings from this and related paradigms indicate the need to develop new identification and diagnostic strategies. These findings include the high prevalence and impact of mental disorders in young people, the limitations of current diagnostic systems and risk identification approaches, the diffuse and unstable symptom patterns in early stages, and their pluripotent, transdiagnostic trajectories. The approach we have recently adopted has been guided by the clinical staging model and adapts the original "at risk mental state" approach to encompass a broader range of inputs and output target syndromes. This approach is supported by a number of novel modelling and prediction strategies that acknowledge and reflect the dynamic nature of psychopathology, such as dynamical systems theory, network theory, and joint modelling. Importantly, a broader transdiagnostic approach and enhancing specific prediction (profiling or increasing precision) can be achieved concurrently. A holistic strategy can be developed that applies these new prediction approaches, as well as machine learning and iterative probabilistic multimodal models, to a blend of subjective psychological data, physical disturbances (e.g., EEG measures) and biomarkers (e.g., neuroinflammation, neural network abnormalities) acquired through fine-grained sequential or longitudinal assessments. This strategy could ultimately enhance our understanding and ability to predict the onset, early course and evolution of mental ill health, further opening pathways for preventive interventions.
This study will be the first to introduce and validate clinical criteria to identify a broader at-risk patient population, which may facilitate young people's access to clinical services and early treatment by reducing the reliance on "caseness" defined according to current diagnostic categories being required for service entry. These criteria may introduce a new, trans-diagnostic approach for understanding risk factors and pathogenic mechanisms that drive the onset of severe mental illness and the next generation of preventive intervention trials.
The developmental trajectory of language lateralisation over the preschool years is unclear. We explored the relationship between lateralisation of cerebral blood flow velocity response to object naming and cognitive performance in children aged 1-5 years. Functional transcranial Doppler ultrasound was used to record blood flow velocity bilaterally from middle cerebral arteries during a naming task in 58 children (59% male). At group level, the Lateralisation Index (LI) revealed a greater relative increase in cerebral blood flow velocity within the left as compared to right middle cerebral artery. After controlling for maternal IQ, left-lateralised children displayed lower expressive language scores compared to right- and bi-lateralised children, and reduced variability in LI. Supporting this, greater variability in lateralised response, rather than mean response, was indicative of greater expressive language ability. Findings suggest that a delayed establishment of language specialisation is associated with better language ability in the preschool years.
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