Predicting schizophrenia by fusing networks from SNPs, DNA methylation and fMRI data

Su Ping Deng, Dongdong Lin, Vince D. Calhoun, Yu Ping Wang

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

Abstract

In order to comprehensively utilize complementary information from multiple types of data for better disease diagnosis, in this study, we applied a network fusion based approach to integrating three types of data including genetic, epigenetic and neuroimaging data from a study of schizophrenia patients (SCZ). A network is a map of interactions, which contributes to investigating the connectivity of components or links between sub-units. We exploited the potential of using networks as features for discriminating SCZ from healthy controls. We first constructed a single network from each type of data. Then we built four fused networks by the network fusion method: three fused networks for each combination of two types of data and one fused network for all three data types. Based on the local consistency of network, we can predict the group of the unlabeled SCZ subjects. The group prediction method was applied to test the power of network-based features and the performance was evaluated by a 10-fold cross validation. The results show that the prediction accuracy is the highest when applying our prediction method to the fused network derived from three data types among 7 tested networks. As a conclusion, integrative approaches that can comprehensively utilize multiple types of data are more useful for diagnosis and prediction.

Original languageEnglish (US)
Title of host publication2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1447-1450
Number of pages4
ISBN (Electronic)9781457702204
DOIs
StatePublished - Oct 13 2016
Externally publishedYes
Event38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States
Duration: Aug 16 2016Aug 20 2016

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2016-October
ISSN (Print)1557-170X

Other

Other38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
CountryUnited States
CityOrlando
Period8/16/168/20/16

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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