771
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The cross-sectional GRAS sample: A comprehensive phenotypical data collection of schizophrenic patients

      research-article
      1 , 1 , 1 , 1 , 1 , 30 , 1 , 1 , 1 , 1 , 1 , 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 30 , 26 , 30 , 31 , 27 , 30 , 31 , 25 , 30 , 31 , 28 , 30 , 31 , 29 , 30 , 31 , 1 , 30 , 31 ,
      BMC Psychiatry
      BioMed Central

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Schizophrenia is the collective term for an exclusively clinically diagnosed, heterogeneous group of mental disorders with still obscure biological roots. Based on the assumption that valuable information about relevant genetic and environmental disease mechanisms can be obtained by association studies on patient cohorts of ≥ 1000 patients, if performed on detailed clinical datasets and quantifiable biological readouts, we generated a new schizophrenia data base, the GRAS (Göttingen Research Association for Schizophrenia) data collection. GRAS is the necessary ground to study genetic causes of the schizophrenic phenotype in a 'phenotype-based genetic association study' (PGAS). This approach is different from and complementary to the genome-wide association studies (GWAS) on schizophrenia.

          Methods

          For this purpose, 1085 patients were recruited between 2005 and 2010 by an invariable team of traveling investigators in a cross-sectional field study that comprised 23 German psychiatric hospitals. Additionally, chart records and discharge letters of all patients were collected.

          Results

          The corresponding dataset extracted and presented in form of an overview here, comprises biographic information, disease history, medication including side effects, and results of comprehensive cross-sectional psychopathological, neuropsychological, and neurological examinations. With >3000 data points per schizophrenic subject, this data base of living patients, who are also accessible for follow-up studies, provides a wide-ranging and standardized phenotype characterization of as yet unprecedented detail.

          Conclusions

          The GRAS data base will serve as prerequisite for PGAS, a novel approach to better understanding 'the schizophrenias' through exploring the contribution of genetic variation to the schizophrenic phenotypes.

          Related collections

          Most cited references48

          • Record: found
          • Abstract: found
          • Article: not found

          The positive and negative syndrome scale (PANSS) for schizophrenia.

          The variable results of positive-negative research with schizophrenics underscore the importance of well-characterized, standardized measurement techniques. We report on the development and initial standardization of the Positive and Negative Syndrome Scale (PANSS) for typological and dimensional assessment. Based on two established psychiatric rating systems, the 30-item PANSS was conceived as an operationalized, drug-sensitive instrument that provides balanced representation of positive and negative symptoms and gauges their relationship to one another and to global psychopathology. It thus constitutes four scales measuring positive and negative syndromes, their differential, and general severity of illness. Study of 101 schizophrenics found the four scales to be normally distributed and supported their reliability and stability. Positive and negative scores were inversely correlated once their common association with general psychopathology was extracted, suggesting that they represent mutually exclusive constructs. Review of five studies involving the PANSS provided evidence of its criterion-related validity with antecedent, genealogical, and concurrent measures, its predictive validity, its drug sensitivity, and its utility for both typological and dimensional assessment.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Schizophrenia: a concise overview of incidence, prevalence, and mortality.

            Recent systematic reviews have encouraged the psychiatric research community to reevaluate the contours of schizophrenia epidemiology. This paper provides a concise overview of three related systematic reviews on the incidence, prevalence, and mortality associated with schizophrenia. The reviews shared key methodological features regarding search strategies, analysis of the distribution of the frequency estimates, and exploration of the influence of key variables (sex, migrant status, urbanicity, secular trend, economic status, and latitude). Contrary to previous interpretations, the incidence of schizophrenia shows prominent variation between sites. The median incidence of schizophrenia was 15.2/100,000 persons, and the central 80% of estimates varied over a fivefold range (7.7-43.0/100,000). The rate ratio for males:females was 1.4:1. Prevalence estimates also show prominent variation. The median lifetime morbid risk for schizophrenia was 7.2/1,000 persons. On the basis of the standardized mortality ratio, people with schizophrenia have a two- to threefold increased risk of dying (median standardized mortality ratio = 2.6 for all-cause mortality), and this differential gap in mortality has increased over recent decades. Compared with native-born individuals, migrants have an increased incidence and prevalence of schizophrenia. Exposures related to urbanicity, economic status, and latitude are also associated with various frequency measures. In conclusion, the epidemiology of schizophrenia is characterized by prominent variability and gradients that can help guide future research.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The MATRICS Consensus Cognitive Battery, part 2: co-norming and standardization.

              The consensus cognitive battery developed by the National Institute of Mental Health's (NIMH's) Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative includes 10 independently developed tests that are recommended as the standard battery for clinical trials of cognition-enhancing interventions for schizophrenia. To facilitate interpretation of results from the MATRICS Consensus Cognitive Battery using a common scaling across tests, normative data were obtained from a single representative U.S. community sample with the battery administered as a unit. The MATRICS Consensus Cognitive Battery was administered to 300 individuals from the general community at five sites in differing geographic regions. For each site, recruitment was stratified by age, gender, and education. A scientific survey sampling method was used to help avoid sampling bias. The battery was administered in a standard order to each participant in a single session lasting approximately 60 minutes. Descriptive data were generated, and age, gender, and education effects on performance were examined. Prominent age and education effects were observed across tests. The results for gender differed by measure, suggesting the need for age and gender corrections in clinical trials. The MATRICS Consensus Cognitive Battery components were co-normed, with allowance for demographic corrections. Co-norming a battery such as the MATRICS Consensus Cognitive Battery, comprising tests from independent test developers each with their own set of norms, facilitates valid interpretation of test scores and communication of findings across studies. These normative data will aid in estimating the magnitude of change during clinical trials of cognition-enhancing agents and make it possible to derive more directly interpretable composite scores.
                Bookmark

                Author and article information

                Journal
                BMC Psychiatry
                BMC Psychiatry
                BioMed Central
                1471-244X
                2010
                10 November 2010
                : 10
                : 91
                Affiliations
                [1 ]Division of Clinical Neuroscience, Max Planck Institute of Experimental Medicine, Göttingen, Germany
                [2 ]Department of Psychiatry and Psychotherapy, Ecumenical Hospital Hainich, Germany
                [3 ]Hospital of Psychiatry and Psychotherapy, Center for Integrative Psychiatry, Kiel, Germany
                [4 ]Karl-Jaspers-Hospital, Psychiatric Federation Oldenburger Land, Bad Zwischenahn, Germany
                [5 ]Department of Psychiatry II, Ulm University, District Hospital Günzburg, Germany
                [6 ]Department of Psychiatry and Psychotherapy, Hospital Fulda, Germany
                [7 ]Department of Psychiatry and Psychotherapy, Isar-Amper-Hospital, Taufkirchen (Vils), Germany
                [8 ]Department of Psychiatry and Psychotherapy, Reinhard-Nieter Hospital, Wilhelmshaven, Germany
                [9 ]Vitos Hospital of Forensic Psychiatry Eltville, Eltville, Germany
                [10 ]Vitos Hospital of Psychiatry and Psychotherapy Merxhausen, Kassel, Germany
                [11 ]Department of Psychiatry and Psychotherapy, University of Rostock, Germany
                [12 ]Hospital of Forensic Psychiatry, Moringen, Germany
                [13 ]Hospital of Psychiatry and Psychotherapy Langenhagen, Regional Hospitals Hannover, Germany
                [14 ]Vitos Hospital of Psychiatry and Psychotherapy, Bad Emstal-Merxhausen, Germany
                [15 ]Addiction Hospital "Am Waldsee", Rieden, Germany
                [16 ]Department of Psychiatry and Psychotherapy, University Medical Center of Bonn, Germany
                [17 ]Vitos Hospital of Psychiatry and Psychotherapy Merxhausen, Hofgeismar, Germany
                [18 ]Vitos Haina Forensic Psychiatric Hospital, Haina, Germany
                [19 ]Department of Psychiatry and Psychotherapy, Regional Hospitals Hannover, Wunstorf, Germany
                [20 ]Dr. K. Fontheim's Hospital for Mental Health, Liebenburg, Germany
                [21 ]Department of Psychiatry and Psychotherapy, Hospital Ingolstadt, Germany
                [22 ]Department of Psychiatry and Psychotherapy, Hospital Lübbecke, Germany
                [23 ]Hospital of Psychiatry and Psychotherapy, Rickling, Germany
                [24 ]Georg-Elias-Müller-Institute for Psychology, University of Göttingen, Germany
                [25 ]Department of Psychiatry and Psychotherapy, University Medical Center of Göttingen, Germany
                [26 ]Biomedical NMR Research GmbH, Max Planck Institute of Biophysical Chemistry, Göttingen, Germany
                [27 ]Department of Molecular Biology of Neuronal Signals, Max Planck Institute of Experimental Medicine, Göttingen, Germany
                [28 ]Department of Molecular Neurobiology, Max Planck Institute of Experimental Medicine, Göttingen, Germany
                [29 ]Department of Neurogenetics, Max Planck Institute of Experimental Medicine, Göttingen, Germany
                [30 ]DFG Research Center for Molecular Physiology of the Brain (CMPB), Germany
                [31 ]Founders of the GRAS Initiative
                Article
                1471-244X-10-91
                10.1186/1471-244X-10-91
                3002316
                21067598
                7e898097-e454-42e2-8c12-e96ccaaa5b4e
                Copyright ©2010 Ribbe et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<url>http://creativecommons.org/licenses/by/2.0</url>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 24 August 2010
                : 10 November 2010
                Categories
                Research Article

                Clinical Psychology & Psychiatry
                Clinical Psychology & Psychiatry

                Comments

                Comment on this article