NCT03790085

Identification of Multi-modal Bio-markers for Early Diagnosis and Treatment Prediction in Schizophrenia Individuals

• Status: Unknown
• Phase: EARLY_Phase 1
• Study type: Interventional
• Enrollment: 2,700 (estimated)
• Sponsor: Tianjin Medical University General Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 45 Years
• Healthy volunteers: Accepted

Summary

This study aims to screen and validate multi-scale bio-markers for early diagnosis and medication monitoring for early schizophrenia, including the genetic, neurobiochemistry, neuroimaging and eletrophysiological measures. Based on the validated bio-markers, the present study further tries to build several prediction models for early differential diagnosis of schizophrenia from healthy controls and other mental diseases (such as the major depression and anxiety disorders), biological sub-typing and diagnosis of the schizophrenia sub-types, and early prediction of the medication effects.

Detailed description

Schizophrenia is one of the most important diseases that threaten the health of Chinese people. In view of the current lack of objective biological markers in the diagnosis and treatment of schizophrenia, as well as the lack of effective early diagnosis methods and curative effect prediction methods, the investigators carried out joint research by integrating research teams from molecular genetics, neurobiochemistry, psychiatry, medical imaging, information science and other fields. The overall objective of the project is to establish a bio-marker system for individualized diagnosis and treatment of early schizophrenia. Specific research contents include: screening and verifying multidimensional objective biological markers such as genetics, neurobiochemistry, neuroimaging, electrophysiology, which is related to early diagnosis and efficacy prediction of schizophrenia through big data analysis of healthy controls and patients with first episode schizophrenia, depression and anxiety disorder. Pattern recognition method is used to build the individualized early diagnosis model, biological sub-type clustering model, biological sub-type individualized diagnosis model and early curative effect prediction model of schizophrenia. Based on the individualized diagnosis and treatment prediction model of schizophrenia, the individualized diagnosis and treatment toolkit was developed, and the individualized diagnosis and treatment prediction cloud platform was established to provide assist for clinicians.

Conditions

• Schizophrenia
• Major Depressive Disorder
• Anxiety Disorders

Interventions

Type	Name	Description
DRUG	Risperidone	Risperidone tablet
DRUG	Olanzapine	Olanzapine tablet
DRUG	Aripiprazole	Aripiprazole tablet

Timeline

• Start date: 2018-09-01
• Primary completion: 2020-06-30
• Completion: 2020-12-31
• First posted: 2018-12-31
• Last updated: 2018-12-31

Locations

1 site across 1 country: China