Genomic Characterization of Schizophrenia Candidate Gene Regions. A.Q. Nato, X. Kong, F. Chen, C. He, C. Chiu, L.M. Brzustowicz, T.C. Matise Department of Genetics, Rutgers University, Piscataway, NJ 08854.
Schizophrenia (SZ) affects 1% of the worldwide population and is considered the most devastating mental disorder. Family, twin and adoption studies have revealed that SZ has a complex genetic aetiology. At present, a handful of genetic factors are strongly implicated in SZ but it is likely that many more remain to be identified. In this study we analyzed data from 43 genome-wide scans and 2 meta-analyses for linkage to SZ and partitioned the genome into eleven genomic regions (designated as SCRs) that show either significant evidence of linkage in 1 or more scans or suggestive evidence in at least 4 scans where the peak lod scores lie within 25 cM of each other. Detailed descriptive web-pages for each of the SCRs are provided on our website. We characterize each SCR by identifying the known and predicted genes within these regions and categorize them based on whether they are linked to phenotypes, GO terms, diseases, or pathways, and on whether they are linked or associated with SZ in published linkage scans, meta-analyses, microarray studies, and association studies. Additionally, within each SCR, we identify copy-number variants, segmental duplications, defined regulatory regions, putative miRNA binding sites, rearrangement hotspots, and evolutionarily conserved sequence motifs that are candidate regulatory elements. We provide object-specific web links to existing large databases, thereby facilitating access to relevant subsets of data. We also compare the sequences of our SCRs with each other to identify homologous stretches of DNA that may include important regulatory elements. The total SCR coverage is 236 cM with SCR sizes ranging from 15.88 cM to 29.81 cM. As new genome scans are published, our SCRs are re-evaluated and refined. Our approach provides a novel method to identify and prioritize SZ susceptibility regions and genomic elements that could be applied to other complex diseases.