Identification of psychopathological course types in schizophrenic psychoses

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Schizophrenia is a heterogeneous disorder. Modern diagnostic criteria for schizophrenia in ICD-10 and DSM-IV fail to identify homogeneous groups with respect to psychopathological course and neurobiological findings. A subdivision with respect to course and outcome, however, could improve the individual treatment of schizophrenia. Furthermore, the identification of psychopathological subtypes is important for neurobiological research, e.g. for genotype-phenotype correlations. As yet, several attempts have been made in order to establish a course typology of schizophrenic psychoses. These traditional course typologies, however, are based merely upon clinical judgment without a confirmation by systematic empirical research. Against this background, the project aims to identify and to characterize psychopathological phenotypes in the longitudinal course of schizophrenic disorders. Therefore, a cohort of 150 patients suffering from schizophrenic disorders with a longitudinal assessment over a period of 2 years will be established. The psychopathological characterization will be performed using standardized rating instruments (5 visits over a period of 2 years). In addition, we will create a narrative case report of each patient which should reflect the psychopathological course of the illness. Based upon this database we will perform statistical analyses like latent class growth analysis (LCGA) or factor-mixture analysis (FMA) on psychopathological rating scales in order to identify empirical phenotypes. While LCGA corresponds to qualitatively distinct subtypes, FMA allows performing categorical and dimensional data analyses in one statistical model in order to identify both subtypes and severity differences of psychopathological symptoms within subtypes. Psychopathological case reports can help to evaluate the clinical plausibility of the results of statistical analyses. Furthermore, traditional course typologies for schizophrenic disorders will be applied to the psychopathological case records. Moreover, we will try to operationalize traditional course typologies (e.g. those of Leonhard and Watt and coworkers) using suitable rating scales. Based on this database we will examine the reliability and the validity of these concepts. The results of the statistical analyses will be compared with traditional course typologies in order to examine accordance and differences. Lastly, in cooperation with Clinical Research Group 241 (Genotype-phenotype relationships and neurobiology of the longitudinal course of psychosis) we will try to correlate the identified psychopathological phenotypes with genotype data.