Building a Prediction Model for Bipolar Disorder in High-Risk Youth Using Multimodal Data A Multicenter, Large Sample, Prospective Cohort Study

What this Trial Is About

Bipolar disorder BD is a serious mental illness that tends to run in families and affects behavior, thinking, emotions, social interactions, and work. It has characteristics like high prevalence, frequent recurrence, and early onset. Early recognition and diagnosis are challenging but important for better outcomes. This research aims to create a large, high-quality group of BD high-risk individuals by enrolling 400 participants over four years and following them intensively for ten years using an electronic mental health platform. The study will collect various types of data including clinical, genetic, cognitive, neuroimaging, sleep, EEG, eye movement, speech, facial expression, and movement to understand how biological, clinical, and environmental factors interact in BD onset. The study is observational and includes three groups children aged 6 to 18 who have at least one parent with BD, children with atypical depression diagnosed by DSM-5 criteria, and healthy children matched by age and gender without psychiatric family history. Participants will be assessed yearly for four years, including brain scans and multiple follow-ups to track the development of mental illnesses, brain structure and function, cognitive function, sleep quality, quality of life, and genetic features. Participants will be involved in annual evaluations for four years, including clinical assessments and brain imaging. Researchers will monitor the differences in development among the three groups over time. The main outcomes focus on the prevalence of mental illness, brain development, and multi-modal feature changes. Secondary outcomes include cognitive function, sleep quality, quality of life, and genetic differences. This long-term follow-up aims to develop predictive models for BD onset and guide early, personalized interventions for those at high risk.

A Cohort Study of Disease Prediction Model for High-risk Population With Bipolar Disorder