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

Early Phase 1UnknownNCT03790085

Tianjin Medical University General Hospital2,700 enrolled

Overview

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.

Study Type

INTERVENTIONAL

Allocation

NON_RANDOMIZED

Purpose

DIAGNOSTIC

Eligibility

Sex: ALLMin age: 18 YearsMax age: 45 YearsHealthy volunteers:

Medical Language ↔ Plain English

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

Outcomes

Primary Outcomes

Positive and Negative Syndrome Scale (PANSS)

It is a scale involved and standardized for assessing the severity of symptoms of different types of schizophrenia. Of the 30 items included in the PANSS, 7 constitute a Positive Scale, 7 a Negative Scale, and the remaining 16 a General Psychopathology Scale. Each of the 30 items is accompanied by a specific definition as well as detailed anchoring criteria for all seven rating points. The scores for these scales are arrived at by summation of ratings across component items. These seven points represent increasing levels of psychopathology, as follows: 1- absent, 2- minimal, 3-mild, 4-moderate, 5-moderate severe, 6-severe, 7-extreme. Therefore, the potential ranges are 7 to 49 for the Positive and Negative Scales, and 16 to 112 for the General Psychopathology Scale. A rating of 7 (extreme) refers to the most serious level of psychopathology in each item, so the higher the score is, the more serious the physical level is.

Time frame: 30-45 minutes

Clinical Global Impression(CGI)

the CGI is a 3-item observer-rated scale that measures illness severity (CGIS), global improvement or change (CGIC) and therapeutic response.The CGI is rated on a 7-point scale, with the severity of illness scale using a range of responses from 1 (normal) through to 7 (amongst the most severely ill patients).CGI-C scores range from 1 (very much improved) through to 7 (very much worse). Treatment response ratings should take account of both therapeutic efficacy and treatment-related adverse events and range from 0 (marked improvement and no side-effects) and 4 (unchanged or worse and side-effects outweigh the therapeutic effects). Each component of the CGI is rated separately; the instrument does not yield a global score.

Time frame: 10-15 minutes

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

Overview

Conditions

Interventions

Eligibility

Locations (1)

Outcomes

Primary Outcomes

Central Contacts