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

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

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.

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.

Inclusion Criteria for patients:

• According with American mental disorder diagnosis and Diagnostic criteria for schizophrenia, major depressive disorder, and anxiety disorder in the statistical manual DSM-IV
• The time from the onset of symptoms for the first time to participate in study is less than 12 months
• No any anti-psychotic drugs or medication was taken more than 14 days
• Han nationality
• 18 to 45 years old
• Right-handed

Inclusion Criteria for healthy controls:

• Han nationality
• Right-handedness
• Gender, age and education level are matched with patients
• 18 to 45 years old
• Any mental disorder diagnosis in DSM-IV was excluded
• There were no relatives with severe mental disorder in the two or three generations

Exclusion Criteria:

• The patient has other psychiatric disorder beside the illness
• A history of psychoactive substance use, accompanied by severe physical disease
• Have a history of epilepsy or coma
• Women who are pregnant or breast-feeding
• Accompanied by metal implants, claustrophobia and other contraindications of MRI scan