Network-based investigation of genetic modules associated with functional brain networks in schizophrenia

Dongdong Lin, Hao He, Jingyao Li, Hong Wen Deng, Vince D. Calhoun, Yu Ping Wang

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

Abstract

We developed a new sparse multivariate regression method, collaborative sparse reduced rank regression(C-sRRR) for detecting genetic networks associated with brain functional networks in schizophrenia (SZ). Our study: 1) introduced both genetic and brain network structure to group single nucleotide polymorphism (SNP) and voxels simultaneously for utilizing the interacting effects implied in both features; 2) used collaborative sparse group lasso to perform genetic variants selection and nuclear norm penalty to address the interrelationship among voxels; 3) developed an efficient algorithm for solving the non-smooth optimization. In real data analysis, we constructed 8605 genetic sub-networks (modules) from 722177 SNPs with a median module size of 9. A functional brain network was extracted which also showed significant discriminative characteristics between SZ and healthy controls. A sub sampling strategy was applied to identify 57 highly ranked genes from 14 high-ranking modules. 14 of them are SZ susceptibility genes and 6 genes were consistent with the findings in previous study.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
Pages9-16
Number of pages8
DOIs
StatePublished - 2013
Event2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013 - Shanghai, China
Duration: Dec 18 2013Dec 21 2013

Publication series

NameProceedings - 2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013

Other

Other2013 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013
CountryChina
CityShanghai
Period12/18/1312/21/13

Keywords

  • Collaborative sparse group lasso
  • imaging genetics
  • network analysis
  • reduced-rank regression

ASJC Scopus subject areas

  • Biomedical Engineering

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