<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03790085</url>
  </required_header>
  <id_info>
    <org_study_id>2018YFC1314300</org_study_id>
    <nct_id>NCT03790085</nct_id>
  </id_info>
  <brief_title>Identification of Multi-modal Bio-markers for Early Diagnosis and Treatment Prediction in Schizophrenia Individuals</brief_title>
  <official_title>Identification of Multi-modal Bio-markers for Early Diagnosis and Treatment Prediction in Schizophrenia Individuals</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Tianjin Medical University General Hospital</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Shanghai Mental Health Center</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Nanjing Medical University</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Tianjin Anding Hospital</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Harbin First Specialist Hospital</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>First Affiliated Hospital of Chongqing Medical University</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Anhui Mental Health Center</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Wuhan Psychiatric Hospital</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Wenzhou Seventh People's Hospital</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>First Affiliated Hospital of Harbin Medical University</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Tianjin Medical University General Hospital</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      This study aims to screen and validate multi-scale bio-markers for early diagnosis and&#xD;
      medication monitoring for early schizophrenia, including the genetic, neurobiochemistry,&#xD;
      neuroimaging and eletrophysiological measures. Based on the validated bio-markers, the&#xD;
      present study further tries to build several prediction models for early differential&#xD;
      diagnosis of schizophrenia from healthy controls and other mental diseases (such as the major&#xD;
      depression and anxiety disorders), biological sub-typing and diagnosis of the schizophrenia&#xD;
      sub-types, and early prediction of the medication effects.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Schizophrenia is one of the most important diseases that threaten the health of Chinese&#xD;
      people. In view of the current lack of objective biological markers in the diagnosis and&#xD;
      treatment of schizophrenia, as well as the lack of effective early diagnosis methods and&#xD;
      curative effect prediction methods, the investigators carried out joint research by&#xD;
      integrating research teams from molecular genetics, neurobiochemistry, psychiatry, medical&#xD;
      imaging, information science and other fields. The overall objective of the project is to&#xD;
      establish a bio-marker system for individualized diagnosis and treatment of early&#xD;
      schizophrenia. Specific research contents include: screening and verifying multidimensional&#xD;
      objective biological markers such as genetics, neurobiochemistry, neuroimaging,&#xD;
      electrophysiology, which is related to early diagnosis and efficacy prediction of&#xD;
      schizophrenia through big data analysis of healthy controls and patients with first episode&#xD;
      schizophrenia, depression and anxiety disorder. Pattern recognition method is used to build&#xD;
      the individualized early diagnosis model, biological sub-type clustering model, biological&#xD;
      sub-type individualized diagnosis model and early curative effect prediction model of&#xD;
      schizophrenia. Based on the individualized diagnosis and treatment prediction model of&#xD;
      schizophrenia, the individualized diagnosis and treatment toolkit was developed, and the&#xD;
      individualized diagnosis and treatment prediction cloud platform was established to provide&#xD;
      assist for clinicians.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">September 1, 2018</start_date>
  <completion_date type="Anticipated">December 31, 2020</completion_date>
  <primary_completion_date type="Anticipated">June 30, 2020</primary_completion_date>
  <phase>Early Phase 1</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Non-Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <primary_purpose>Diagnostic</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Positive and Negative Syndrome Scale (PANSS)</measure>
    <time_frame>30-45 minutes</time_frame>
    <description>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.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Clinical Global Impression(CGI)</measure>
    <time_frame>10-15 minutes</time_frame>
    <description>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.</description>
  </primary_outcome>
  <number_of_arms>3</number_of_arms>
  <enrollment type="Anticipated">2700</enrollment>
  <condition>Schizophrenia</condition>
  <condition>Major Depressive Disorder</condition>
  <condition>Anxiety Disorders</condition>
  <arm_group>
    <arm_group_label>Risperidone</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>It can be used after schizophrenia is diagnosed. Risperidone affects prolactin and may affect menstruation in young women, so we will try not to use it in such patients. Patients were randomized to a single Risperidone control trial for 8 weeks to evaluate the clinical efficacy of the patients. Risperidone routine daily 2-6 mg, up to 8 mg, can be taken orally twice a day.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Olanzapine</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>It can be used after schizophrenia is diagnosed. Olanzapine is not generally used in patients with diabetes and hyperlipidemia. Patients were randomized to a single Olanzapine control trial for 8 weeks to evaluate the clinical efficacy of the patients. Olanzapine is available once or twice a day, starting at 5 mg daily and up to 20 mg daily.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Aripiprazole</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>It can be used after schizophrenia is diagnosed. Aripiprazole has no specific contraindications. Patients were randomized to a single Aripiprazole control trial for 8 weeks to evaluate the clinical efficacy of the patients. Aripiprazole is taken orally once a day, starting at 10 mg daily and up to 30 mg daily.</description>
  </arm_group>
  <intervention>
    <intervention_type>Drug</intervention_type>
    <intervention_name>Risperidone</intervention_name>
    <description>Risperidone tablet</description>
    <arm_group_label>Risperidone</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Drug</intervention_type>
    <intervention_name>Olanzapine</intervention_name>
    <description>Olanzapine tablet</description>
    <arm_group_label>Olanzapine</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Drug</intervention_type>
    <intervention_name>Aripiprazole</intervention_name>
    <description>Aripiprazole tablet</description>
    <arm_group_label>Aripiprazole</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria for patients:&#xD;
&#xD;
          -  According with American mental disorder diagnosis and Diagnostic criteria for&#xD;
             schizophrenia, major depressive disorder, and anxiety disorder in the statistical&#xD;
             manual DSM-IV&#xD;
&#xD;
          -  The time from the onset of symptoms for the first time to participate in study is less&#xD;
             than 12 months&#xD;
&#xD;
          -  No any anti-psychotic drugs or medication was taken more than 14 days&#xD;
&#xD;
          -  Han nationality&#xD;
&#xD;
          -  18 to 45 years old&#xD;
&#xD;
          -  Right-handed&#xD;
&#xD;
        Inclusion Criteria for healthy controls:&#xD;
&#xD;
          -  Han nationality&#xD;
&#xD;
          -  Right-handedness&#xD;
&#xD;
          -  Gender, age and education level are matched with patients&#xD;
&#xD;
          -  18 to 45 years old&#xD;
&#xD;
          -  Any mental disorder diagnosis in DSM-IV was excluded&#xD;
&#xD;
          -  There were no relatives with severe mental disorder in the two or three generations&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  The patient has other psychiatric disorder beside the illness&#xD;
&#xD;
          -  A history of psychoactive substance use, accompanied by severe physical disease&#xD;
&#xD;
          -  Have a history of epilepsy or coma&#xD;
&#xD;
          -  Women who are pregnant or breast-feeding&#xD;
&#xD;
          -  Accompanied by metal implants, claustrophobia and other contraindications of MRI scan&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>45 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Chunshui Yu, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Tianjin Medical University General Hospital</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Chunshui Yu, MD</last_name>
    <phone>862260363760</phone>
    <email>chunshuiyu@vip.163.com</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Wen Qin, MD</last_name>
    <phone>862260363760</phone>
    <email>qinwen@tmu.edu.cn</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Tianjin Medical University General Hospital</name>
      <address>
        <city>Tianjin</city>
        <zip>300052</zip>
        <country>China</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Chunshui Yu, MD</last_name>
      <phone>862260362260</phone>
      <email>chunshuiyu@vip.163.com</email>
    </contact>
    <contact_backup>
      <last_name>Wen Qin, MD</last_name>
      <phone>862260363760</phone>
      <email>qinwen@tmu.edu.cn</email>
    </contact_backup>
  </location>
  <location_countries>
    <country>China</country>
  </location_countries>
  <results_reference>
    <citation>Gusev A, Mancuso N, Won H, Kousi M, Finucane HK, Reshef Y, Song L, Safi A; Schizophrenia Working Group of the Psychiatric Genomics Consortium; McCarroll S, Neale BM, Ophoff RA, O'Donovan MC, Crawford GE, Geschwind DH, Katsanis N, Sullivan PF, Pasaniuc B, Price AL. Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights. Nat Genet. 2018 Apr;50(4):538-548. doi: 10.1038/s41588-018-0092-1. Epub 2018 Apr 9.</citation>
    <PMID>29632383</PMID>
  </results_reference>
  <results_reference>
    <citation>Zhu J, Zhuo C, Xu L, Liu F, Qin W, Yu C. Altered Coupling Between Resting-State Cerebral Blood Flow and Functional Connectivity in Schizophrenia. Schizophr Bull. 2017 Oct 21;43(6):1363-1374. doi: 10.1093/schbul/sbx051.</citation>
    <PMID>28521048</PMID>
  </results_reference>
  <results_reference>
    <citation>Drysdale AT, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, Fetcho RN, Zebley B, Oathes DJ, Etkin A, Schatzberg AF, Sudheimer K, Keller J, Mayberg HS, Gunning FM, Alexopoulos GS, Fox MD, Pascual-Leone A, Voss HU, Casey BJ, Dubin MJ, Liston C. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med. 2017 Jan;23(1):28-38. doi: 10.1038/nm.4246. Epub 2016 Dec 5. Erratum In: Nat Med. 2017 Feb 7;23 (2):264.</citation>
    <PMID>27918562</PMID>
  </results_reference>
  <results_reference>
    <citation>Jaffe AE, Gao Y, Deep-Soboslay A, Tao R, Hyde TM, Weinberger DR, Kleinman JE. Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex. Nat Neurosci. 2016 Jan;19(1):40-7. doi: 10.1038/nn.4181. Epub 2015 Nov 30.</citation>
    <PMID>26619358</PMID>
  </results_reference>
  <results_reference>
    <citation>Marshall CR, Howrigan DP, Merico D, Thiruvahindrapuram B, Wu W, Greer DS, Antaki D, Shetty A, Holmans PA, Pinto D, Gujral M, Brandler WM, Malhotra D, Wang Z, Fajarado KVF, Maile MS, Ripke S, Agartz I, Albus M, Alexander M, Amin F, Atkins J, Bacanu SA, Belliveau RA Jr, Bergen SE, Bertalan M, Bevilacqua E, Bigdeli TB, Black DW, Bruggeman R, Buccola NG, Buckner RL, Bulik-Sullivan B, Byerley W, Cahn W, Cai G, Cairns MJ, Campion D, Cantor RM, Carr VJ, Carrera N, Catts SV, Chambert KD, Cheng W, Cloninger CR, Cohen D, Cormican P, Craddock N, Crespo-Facorro B, Crowley JJ, Curtis D, Davidson M, Davis KL, Degenhardt F, Del Favero J, DeLisi LE, Dikeos D, Dinan T, Djurovic S, Donohoe G, Drapeau E, Duan J, Dudbridge F, Eichhammer P, Eriksson J, Escott-Price V, Essioux L, Fanous AH, Farh KH, Farrell MS, Frank J, Franke L, Freedman R, Freimer NB, Friedman JI, Forstner AJ, Fromer M, Genovese G, Georgieva L, Gershon ES, Giegling I, Giusti-Rodriguez P, Godard S, Goldstein JI, Gratten J, de Haan L, Hamshere ML, Hansen M, Hansen T, Haroutunian V, Hartmann AM, Henskens FA, Herms S, Hirschhorn JN, Hoffmann P, Hofman A, Huang H, Ikeda M, Joa I, Kahler AK, Kahn RS, Kalaydjieva L, Karjalainen J, Kavanagh D, Keller MC, Kelly BJ, Kennedy JL, Kim Y, Knowles JA, Konte B, Laurent C, Lee P, Lee SH, Legge SE, Lerer B, Levy DL, Liang KY, Lieberman J, Lonnqvist J, Loughland CM, Magnusson PKE, Maher BS, Maier W, Mallet J, Mattheisen M, Mattingsdal M, McCarley RW, McDonald C, McIntosh AM, Meier S, Meijer CJ, Melle I, Mesholam-Gately RI, Metspalu A, Michie PT, Milani L, Milanova V, Mokrab Y, Morris DW, Muller-Myhsok B, Murphy KC, Murray RM, Myin-Germeys I, Nenadic I, Nertney DA, Nestadt G, Nicodemus KK, Nisenbaum L, Nordin A, O'Callaghan E, O'Dushlaine C, Oh SY, Olincy A, Olsen L, O'Neill FA, Van Os J, Pantelis C, Papadimitriou GN, Parkhomenko E, Pato MT, Paunio T; Psychosis Endophenotypes International Consortium; Perkins DO, Pers TH, Pietilainen O, Pimm J, Pocklington AJ, Powell J, Price A, Pulver AE, Purcell SM, Quested D, Rasmussen HB, Reichenberg A, Reimers MA, Richards AL, Roffman JL, Roussos P, Ruderfer DM, Salomaa V, Sanders AR, Savitz A, Schall U, Schulze TG, Schwab SG, Scolnick EM, Scott RJ, Seidman LJ, Shi J, Silverman JM, Smoller JW, Soderman E, Spencer CCA, Stahl EA, Strengman E, Strohmaier J, Stroup TS, Suvisaari J, Svrakic DM, Szatkiewicz JP, Thirumalai S, Tooney PA, Veijola J, Visscher PM, Waddington J, Walsh D, Webb BT, Weiser M, Wildenauer DB, Williams NM, Williams S, Witt SH, Wolen AR, Wormley BK, Wray NR, Wu JQ, Zai CC, Adolfsson R, Andreassen OA, Blackwood DHR, Bramon E, Buxbaum JD, Cichon S, Collier DA, Corvin A, Daly MJ, Darvasi A, Domenici E, Esko T, Gejman PV, Gill M, Gurling H, Hultman CM, Iwata N, Jablensky AV, Jonsson EG, Kendler KS, Kirov G, Knight J, Levinson DF, Li QS, McCarroll SA, McQuillin A, Moran JL, Mowry BJ, Nothen MM, Ophoff RA, Owen MJ, Palotie A, Pato CN, Petryshen TL, Posthuma D, Rietschel M, Riley BP, Rujescu D, Sklar P, St Clair D, Walters JTR, Werge T, Sullivan PF, O'Donovan MC, Scherer SW, Neale BM, Sebat J; CNV and Schizophrenia Working Groups of the Psychiatric Genomics Consortium. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nat Genet. 2017 Jan;49(1):27-35. doi: 10.1038/ng.3725. Epub 2016 Nov 21. Erratum In: Nat Genet. 2017 Mar 30;49(4):651. Nat Genet. 2017 Sep 27;49(10 ):1558.</citation>
    <PMID>27869829</PMID>
  </results_reference>
  <verification_date>December 2018</verification_date>
  <study_first_submitted>December 25, 2018</study_first_submitted>
  <study_first_submitted_qc>December 27, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">December 31, 2018</study_first_posted>
  <last_update_submitted>December 27, 2018</last_update_submitted>
  <last_update_submitted_qc>December 27, 2018</last_update_submitted_qc>
  <last_update_posted type="Actual">December 31, 2018</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Tianjin Medical University General Hospital</investigator_affiliation>
    <investigator_full_name>Chunshui Yu</investigator_full_name>
    <investigator_title>Vice president of Tianjin Medical University</investigator_title>
  </responsible_party>
  <keyword>Precision medicine</keyword>
  <keyword>Bio-marker</keyword>
  <keyword>Neuroimaging</keyword>
  <keyword>Molecular genetics</keyword>
  <keyword>Neurobiochemical</keyword>
  <keyword>Early diagnosis</keyword>
  <keyword>Early prediction</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Schizophrenia</mesh_term>
    <mesh_term>Depressive Disorder</mesh_term>
    <mesh_term>Depressive Disorder, Major</mesh_term>
    <mesh_term>Anxiety Disorders</mesh_term>
  </condition_browse>
  <intervention_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Olanzapine</mesh_term>
    <mesh_term>Risperidone</mesh_term>
    <mesh_term>Aripiprazole</mesh_term>
  </intervention_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03790085
org study id: 2018YFC1314300
nct id: NCT03790085
lead sponsor: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
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.
allocation: Non-Randomized
intervention model: Parallel Assignment
primary purpose: Diagnostic
masking: None (Open Label)
measure: Positive and Negative Syndrome Scale (PANSS)
time frame: 30-45 minutes
description: 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.
measure: Clinical Global Impression(CGI)
time frame: 10-15 minutes
description: 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.
arm group label: Risperidone
arm group type: Experimental
description: It can be used after schizophrenia is diagnosed. Risperidone affects prolactin and may affect menstruation in young women, so we will try not to use it in such patients. Patients were randomized to a single Risperidone control trial for 8 weeks to evaluate the clinical efficacy of the patients. Risperidone routine daily 2-6 mg, up to 8 mg, can be taken orally twice a day.
arm group label: Olanzapine
arm group type: Experimental
description: It can be used after schizophrenia is diagnosed. Olanzapine is not generally used in patients with diabetes and hyperlipidemia. Patients were randomized to a single Olanzapine control trial for 8 weeks to evaluate the clinical efficacy of the patients. Olanzapine is available once or twice a day, starting at 5 mg daily and up to 20 mg daily.
arm group label: Aripiprazole
arm group type: Experimental
description: It can be used after schizophrenia is diagnosed. Aripiprazole has no specific contraindications. Patients were randomized to a single Aripiprazole control trial for 8 weeks to evaluate the clinical efficacy of the patients. Aripiprazole is taken orally once a day, starting at 10 mg daily and up to 30 mg daily.
intervention type: Drug
intervention name: Risperidone
description: Risperidone tablet
arm group label: Risperidone
intervention type: Drug
intervention name: Olanzapine
description: Olanzapine tablet
arm group label: Olanzapine
intervention type: Drug
intervention name: Aripiprazole
description: Aripiprazole tablet
arm group label: Aripiprazole
criteria: 
gender: All
minimum age: 18 Years
maximum age: 45 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Chunshui Yu, MD
role: Principal Investigator
affiliation: Tianjin Medical University General Hospital
last name: Chunshui Yu, MD
phone: 862260363760
email: chunshuiyu@vip.163.com
last name: Wen Qin, MD
phone: 862260363760
email: qinwen@tmu.edu.cn
facility: 
status: Recruiting
contact: 
contact backup: 
country: China
citation: Gusev A, Mancuso N, Won H, Kousi M, Finucane HK, Reshef Y, Song L, Safi A; Schizophrenia Working Group of the Psychiatric Genomics Consortium; McCarroll S, Neale BM, Ophoff RA, O'Donovan MC, Crawford GE, Geschwind DH, Katsanis N, Sullivan PF, Pasaniuc B, Price AL. Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights. Nat Genet. 2018 Apr;50(4):538-548. doi: 10.1038/s41588-018-0092-1. Epub 2018 Apr 9.
PMID: 29632383
citation: Zhu J, Zhuo C, Xu L, Liu F, Qin W, Yu C. Altered Coupling Between Resting-State Cerebral Blood Flow and Functional Connectivity in Schizophrenia. Schizophr Bull. 2017 Oct 21;43(6):1363-1374. doi: 10.1093/schbul/sbx051.
PMID: 28521048
citation: Drysdale AT, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, Fetcho RN, Zebley B, Oathes DJ, Etkin A, Schatzberg AF, Sudheimer K, Keller J, Mayberg HS, Gunning FM, Alexopoulos GS, Fox MD, Pascual-Leone A, Voss HU, Casey BJ, Dubin MJ, Liston C. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med. 2017 Jan;23(1):28-38. doi: 10.1038/nm.4246. Epub 2016 Dec 5. Erratum In: Nat Med. 2017 Feb 7;23 (2):264.
PMID: 27918562
citation: Jaffe AE, Gao Y, Deep-Soboslay A, Tao R, Hyde TM, Weinberger DR, Kleinman JE. Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex. Nat Neurosci. 2016 Jan;19(1):40-7. doi: 10.1038/nn.4181. Epub 2015 Nov 30.
PMID: 26619358
citation: Marshall CR, Howrigan DP, Merico D, Thiruvahindrapuram B, Wu W, Greer DS, Antaki D, Shetty A, Holmans PA, Pinto D, Gujral M, Brandler WM, Malhotra D, Wang Z, Fajarado KVF, Maile MS, Ripke S, Agartz I, Albus M, Alexander M, Amin F, Atkins J, Bacanu SA, Belliveau RA Jr, Bergen SE, Bertalan M, Bevilacqua E, Bigdeli TB, Black DW, Bruggeman R, Buccola NG, Buckner RL, Bulik-Sullivan B, Byerley W, Cahn W, Cai G, Cairns MJ, Campion D, Cantor RM, Carr VJ, Carrera N, Catts SV, Chambert KD, Cheng W, Cloninger CR, Cohen D, Cormican P, Craddock N, Crespo-Facorro B, Crowley JJ, Curtis D, Davidson M, Davis KL, Degenhardt F, Del Favero J, DeLisi LE, Dikeos D, Dinan T, Djurovic S, Donohoe G, Drapeau E, Duan J, Dudbridge F, Eichhammer P, Eriksson J, Escott-Price V, Essioux L, Fanous AH, Farh KH, Farrell MS, Frank J, Franke L, Freedman R, Freimer NB, Friedman JI, Forstner AJ, Fromer M, Genovese G, Georgieva L, Gershon ES, Giegling I, Giusti-Rodriguez P, Godard S, Goldstein JI, Gratten J, de Haan L, Hamshere ML, Hansen M, Hansen T, Haroutunian V, Hartmann AM, Henskens FA, Herms S, Hirschhorn JN, Hoffmann P, Hofman A, Huang H, Ikeda M, Joa I, Kahler AK, Kahn RS, Kalaydjieva L, Karjalainen J, Kavanagh D, Keller MC, Kelly BJ, Kennedy JL, Kim Y, Knowles JA, Konte B, Laurent C, Lee P, Lee SH, Legge SE, Lerer B, Levy DL, Liang KY, Lieberman J, Lonnqvist J, Loughland CM, Magnusson PKE, Maher BS, Maier W, Mallet J, Mattheisen M, Mattingsdal M, McCarley RW, McDonald C, McIntosh AM, Meier S, Meijer CJ, Melle I, Mesholam-Gately RI, Metspalu A, Michie PT, Milani L, Milanova V, Mokrab Y, Morris DW, Muller-Myhsok B, Murphy KC, Murray RM, Myin-Germeys I, Nenadic I, Nertney DA, Nestadt G, Nicodemus KK, Nisenbaum L, Nordin A, O'Callaghan E, O'Dushlaine C, Oh SY, Olincy A, Olsen L, O'Neill FA, Van Os J, Pantelis C, Papadimitriou GN, Parkhomenko E, Pato MT, Paunio T; Psychosis Endophenotypes International Consortium; Perkins DO, Pers TH, Pietilainen O, Pimm J, Pocklington AJ, Powell J, Price A, Pulver AE, Purcell SM, Quested D, Rasmussen HB, Reichenberg A, Reimers MA, Richards AL, Roffman JL, Roussos P, Ruderfer DM, Salomaa V, Sanders AR, Savitz A, Schall U, Schulze TG, Schwab SG, Scolnick EM, Scott RJ, Seidman LJ, Shi J, Silverman JM, Smoller JW, Soderman E, Spencer CCA, Stahl EA, Strengman E, Strohmaier J, Stroup TS, Suvisaari J, Svrakic DM, Szatkiewicz JP, Thirumalai S, Tooney PA, Veijola J, Visscher PM, Waddington J, Walsh D, Webb BT, Weiser M, Wildenauer DB, Williams NM, Williams S, Witt SH, Wolen AR, Wormley BK, Wray NR, Wu JQ, Zai CC, Adolfsson R, Andreassen OA, Blackwood DHR, Bramon E, Buxbaum JD, Cichon S, Collier DA, Corvin A, Daly MJ, Darvasi A, Domenici E, Esko T, Gejman PV, Gill M, Gurling H, Hultman CM, Iwata N, Jablensky AV, Jonsson EG, Kendler KS, Kirov G, Knight J, Levinson DF, Li QS, McCarroll SA, McQuillin A, Moran JL, Mowry BJ, Nothen MM, Ophoff RA, Owen MJ, Palotie A, Pato CN, Petryshen TL, Posthuma D, Rietschel M, Riley BP, Rujescu D, Sklar P, St Clair D, Walters JTR, Werge T, Sullivan PF, O'Donovan MC, Scherer SW, Neale BM, Sebat J; CNV and Schizophrenia Working Groups of the Psychiatric Genomics Consortium. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nat Genet. 2017 Jan;49(1):27-35. doi: 10.1038/ng.3725. Epub 2016 Nov 21. Erratum In: Nat Genet. 2017 Mar 30;49(4):651. Nat Genet. 2017 Sep 27;49(10 ):1558.
PMID: 27869829
responsible party type: Principal Investigator
investigator affiliation: Tianjin Medical University General Hospital
investigator full name: Chunshui Yu
investigator title: Vice president of Tianjin Medical University
mesh term: Schizophrenia
mesh term: Depressive Disorder
mesh term: Depressive Disorder, Major
mesh term: Anxiety Disorders
mesh term: Olanzapine
mesh term: Risperidone
mesh term: Aripiprazole
sharing ipd: No