Objective
Schizophrenia (SZ) is a complex and disabling disorder that continues to exact a heavy toll not only upon those afflicted but also on relatives and on our health and welfare systems. Family history significantly increases the risk of developing the disease and evidence from epidemiological and twin studies continues to support the notion that the genetic risk is the most substantial contributor to its aetiology. The SGENE project aims to identify genetic variants associating with SZ, study their impact on phenotype and their interactions with environmental factors contributing to the pathogenesis of the disease. The availability of ultra-high throughput genotyping platforms at manageable cost now allows for a direct genome-wide search for susceptibility variants. We propose a two-stage design for cost efficiency where we will in Phase I genotype 1600 SZ patients and 1600 controls using TagSNP CHIPs with 317,000 markers and search genome-wide for association to SZ. In this phase we will aim to identify a large number of markers with relative risk greater than 1.3 that have frequencies ranging from 10-50%. The most significant markers from Phase I will be carried over to Phase II and typed on a larger, independent sample. We expect most associations in Phase I and Phase II to be detected indirectly, by linkage disequilibrium (LD), rather than directly as causal variants.
Therefore, in Phase III we will search for causal variants in LD with the markers reaching genome-wide significance after Phase I and II. The isolation of SZ susceptibility variants allows the study of their contribution to other psychiatric disorders or risk of certain endophenotypes. Gene-environment interaction is at the heart of pathogenesis of SZ, and this calls for the inclusion of environmental factors into the study. Genes identified in this project may uncover dysfunction of biochemical pathways in SZ and provide new targets for the development of novel therapies.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- humanitieshistory and archaeologyhistory
- medical and health sciencesclinical medicinepsychiatryschizophrenia
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Topic(s)
Call for proposal
FP6-2005-LIFESCIHEALTH-6
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Funding Scheme
STREP - Specific Targeted Research ProjectCoordinator
REYKJAVIK
Iceland