Schizophrenia is a complex mental disorder that is commonly characterized as deterioration of intellectual process and emotional responses and affects 1% of any given population. SNPs are single nucleotide changes that take place in DNA sequences and establish the major percentage of genomic variations. In this study, our goal was to identify SNPs as genomic markers that are related with schizophrenia and investigate the genes and pathways that are identified through the analysis of SNPs. Genome wide association studies (GWAS) analyse the whole genome of case and control groups to identify genetic variations and search for related markers, like SNPs. GWASs are the most common method to investigate genetic causes of a complex disease such as
v
schizophrenia because regular linkage studies are not sufficient. Out of 909,622 SNPs analysis of the dbGAP Schizophrenia genotyping data identified 25,555 SNPs with a p-value 5x10-5. Next, combined p-value approach to identify associated genes and pathways and AHP based prioritization to select biologically relevant SNPs with high statistical association are used through METU-SNP software. 6,000 SNPs had an AHP score above 0.4, which mapped to 2,500 genes suggested to be associated with schizophrenia and related conditions. In addition to previously described neurological pathways, pathway and network analysis showed enrichment of two pathways.
Melanogenesis and vascular smooth muscle contraction pathways were found to be highly associated with schizophrenia. We have also shown that these pathways can be organized in one biological network, which might have a role in the molecular etiology of schizophrenia. Overall analysis results revealed two novel candidate genes SOS1 and GUCY1B3 that have a possible relation with schizophrenia.
Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12615642/index.pdf |
Date | 01 January 2013 |
Creators | Dom, Huseyin Alper |
Contributors | Aydin Son, Yesim |
Publisher | METU |
Source Sets | Middle East Technical Univ. |
Language | English |
Detected Language | English |
Type | M.S. Thesis |
Format | text/pdf |
Rights | To liberate the content for public access |
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