Genomics of Schizophrenia

Coordinator:		Prof. Dr. med. Dan Rujescu
Institution:		Klinik und Poliklinik für Psychiatrie und Psychotherapie, Ludwig-Maximilians-Universität München
Homepage:		psywifo.klinikum.uni-muenchen.de

The aim of subproject 3 is to identify susceptibility genes for schizophrenia. Approximately 800.000 people in Germany suffer from schizophrenia. Schizophrenia affects behaviour and experience and may be accompanied by delusions, hallucinations, disorganized thinking, communication deficits and social withdrawal. Despite the high number of affected patients and even though schizophrenia, similar to cancer or diabetes, seems to be caused mainly by biological and especially genetic factors, not much attention was paid to the disease over a long period of time.

There is overwhelming evidence for a substantial genetic component in schizophrenia. The risk of life time morbidity of 1% in the general population is increased to 3-5% in 2nd degree relatives or half siblings and up to 9-12% in siblings and dizygotic twins. Monozygotic twins share a relative risk of about 50%. The same applies to children of parents where each parent is affected. The overall heritability is estimated to be approximately  80%. Also epigenetic factors play a role, because concordance between monozygotic twins is not 100%. Schizophrenia is assumed to be a multifactorial disease where several genes with small to medium effects are involved. This, in combination with environmental factors leads to the manifestation of the disease.  
The aim of this subproject is to identify susceptibility genes for schizophrenia. First, a genome-wide association (GWA) study will be performed. In parallel such a GWA study will be conducted in bipolar (SP1) and unipolar depressive patients (SP2). The analysis of the genomic data of 1500 patients per disease and 2400 controls will be in close cooperation with SP7 and SP8. Furthermore a combined analysis of all 3 samples will be performed to identify genes associated across the diagnostic boundaries and the analysis of associations with clinical subtypes and intermediate phenotypes will be undertaken. In the third step the best SNPs will be selected using different validation steps and will be replicated in independent samples. The most promising loci will be resequenced to identify functionally relevant variants. The functional characterisation will be in close collaboration with SP6, 9, 11-13.
Development of specific and targeted treatment is dependent on an expanded knowledge of the genetic and pathophysiological causes of schizophrenia. This subproject will contribute to this aim.