Abstract
The study of clinical high risk (CHR) states for psychosis is at a crossroads. After decades of largely observational studies, the field is preparing to develop targeted interventions for prevention or amelioration of psychosis risk. This is timely given the large scale, international Accelerating Medicines Partnership® Program in Schizophrenia (AMP® SCZ) initiative that began in 2020 to identify biomarkers of psychosis risk that may serve as treatment targets in forthcoming clinical trials. This initiative reflects a recent view that while our knowledge of CHR states remains incomplete (Mittal and Addington, 2021), we cannot afford to wait longer to develop therapeutic interventions (McGorry et al., 2008; McGorry et al., 2021; Woods et al., 2021).
The Shanghai-at-Risk-for-Psychosis (SHARP) program has also emphasized observational studies of CHR for over the last decade (Zhang et al., 2018). Like AMP® SCZ, our focus in SHARP is to transition towards intervention. Based on our previous CHR and schizophrenia studies, we developed a mechanistic approach to identify and to manipulate neural networks involved in schizophrenia. This novel approach utilizes brain responses to targeted manipulations of specific neural networks as putative biomarkers that will provide foundations for intervention-based models. Specifically, we suggest that these targeted brain manipulations may reduce positive and negative symptoms in CHR. We suggest further that dynamic neural responses to such manipulations may reflect neuroplasticity, provide mechanistic understanding of psychosis risk, and predict the efficacy of future treatments for these core clinical problems. Below, we present a theoretical framework for the work that we propose. The model is complementary to AMP® SCZ and offers a way to identify and to modulate relevant neural pathways and networks. Our working model and its conceptual and empirical bases are described below.