Schizophrenia genes discovery by mining the minimum spanning trees from multi-dimensional imaging genomic data integration

Su Ping Deng, Dongdong Lin, Vince Daniel Calhoun, Yu Ping Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Schizophrenia (SCZ) disease ranks among the top 10 causes of disability in developed countries worldwide. Its onset is the combination result of genetic, biological and environmental factors. It is increasingly important but difficult to determine which genes are potential biomarkers for SCZ, owing to the complex nature of the pathophysiology of this disease. In our study, we integrated genomic, epigenomic and neuroimaging data to identify genetic biomarkers for schizophrenia. Important cross-correlated features were selected using multiple sparse canonical correlation analysis (smCCA) among single nucleotide polymorphism (SNP), DNA methylation and functional magnetic resonance imaging (fMRI) data. The features were then used to construct two state (health and case) gene-gene interaction networks for SNP or DNA methylation data. A network-based framework was proposed by comparing two different minimum spanning trees (MSTs), which were extracted from two fused state gene networks, respectively. We selected top 20 genes with significant changes of network features for schizophrenia. These genes were finally validated by disease association enrichment analysis, Gene Ontology (GO) enrichment analysis, pathway enrichment analysis and related literature reports. We also demonstrated the effectiveness of our framework through the comparison with other network-based discovery methods. Therefore, our proposed network-based approach can effectively discover biomarkers and resulting genes, promising better diagnosis and treatment of schizophrenia disease.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1493-1500
Number of pages8
ISBN (Electronic)9781509016105
DOIs
Publication statusPublished - Jan 17 2017
Externally publishedYes
Event2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 - Shenzhen, China
Duration: Dec 15 2016Dec 18 2016

Other

Other2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
CountryChina
CityShenzhen
Period12/15/1612/18/16

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ASJC Scopus subject areas

  • Genetics
  • Medicine (miscellaneous)
  • Genetics(clinical)
  • Biochemistry, medical
  • Biochemistry
  • Molecular Medicine
  • Health Informatics

Cite this

Deng, S. P., Lin, D., Calhoun, V. D., & Wang, Y. P. (2017). Schizophrenia genes discovery by mining the minimum spanning trees from multi-dimensional imaging genomic data integration. In Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 (pp. 1493-1500). [7822743] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2016.7822743