Functional Network Composed of 1,219 Genes for Schizophrenia-a Literature Data Mining and Enrichment Analysis

Background:Over the past decade, numerous studies have focused on identifying genetic factors associated with schizophrenia (SCZ). Sample variations, such as size, population, race, disease status, and data processing methods resulted in selection differences. Nevertheless, no systemic study has been completed to summarize these reports and provide an objective full list of genes with a reported association to SCZ. Methods:We conducted a literature data mining (LDM) of over 13,515 articles covering publications from 1958 to Feb. 2016. These articles reported multiple types of marker-disease associations between 1,219 genes and SCZ. Then we conducted a gene set enrichment analysis (GSEA) and a sub-network enrichment analysis (SNEA) to study the functional profile and validate the pathogenic significance of these genes to SCZ. Finally, we presented additional results from the systemic review, including publication date, quality scores, and author affiliations. Results:All of these genes have been demonstrated to present multiple mutations associating with SCZ, some of which were supported by a large number of high quality articles. Enrichment analyses showed that many psychiatric and neuropathic pathways/groups related to SCZ have been significantly enriched by these genes and that they are functionally associated with each other. Conclusion:Our results indicate that these genes may operate as a functional biomarker network influencing the development of SCZ, and that LDM together with GSEA and SNEA could serve as an effective approach in finding these potential target genes