Identification of SNP barcode biomarkers for genes associated with facial emotion perception using particle swarm optimization algorithm.

Li-Yeh Chuang, Hsien-Yuan Lane, Yu-Da Lin, Ming-Teng Lin, Cheng-Hong Yang, Hsueh-Wei Chang

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Article in Annals of general psychiatry, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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6 authors.

Li-Yeh ChuangDepartment of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung 84001, Taiwan.

Hsien-Yuan LaneInstitute of Clinical Medical Science, China Medical University, Taichung 40402, Taiwan ; Department of Psychiatry, China Medical University Hospital, Taichung 40402, Taiwan.

Yu-Da LinDepartment of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 80778, Taiwan.

Ming-Teng LinDepartment of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung 84001, Taiwan ; Department of Psychiatry, Taipei Veterans General Hospital, Hsinchu Branch, Hsinchu 31064, Taiwan.

Cheng-Hong YangDepartment of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 80778, Taiwan.

Hsueh-Wei ChangCancer Center, Translational Research Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan ; Institute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung 80424, Taiwan ; Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.

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6 · The paper itself

Abstract

backgroundFacial emotion perception (FEP) can affect social function. We previously reported that parts of five tested single-nucleotide polymorphisms (SNPs) in the MET and AKT1 genes may individually affect FEP performance. However, the effects of SNP-SNP interactions on FEP performance remain unclear.

methodsThis study compared patients with high and low FEP performances (n = 89 and 93, respectively). A particle swarm optimization (PSO) algorithm was used to identify the best SNP barcodes (i.e., the SNP combinations and genotypes that revealed the largest differences between the high and low FEP groups).

resultsThe analyses of individual SNPs showed no significant differences between the high and low FEP groups. However, comparisons of multiple SNP-SNP interactions involving different combinations of two to five SNPs showed that the best PSO-generated SNP barcodes were significantly associated with high FEP score. The analyses of the joint effects of the best SNP barcodes for two to five interacting SNPs also showed that the best SNP barcodes had significantly higher odds ratios (2.119 to 3.138; P < 0.05) compared to other SNP barcodes. In conclusion, the proposed PSO algorithm effectively identifies the best SNP barcodes that have the strongest associations with FEP performance.

conclusionsThis study also proposes a computational methodology for analyzing complex SNP-SNP interactions in social cognition domains such as recognition of facial emotion.

Indexed as

AlgorithmFacial emotion perceptionParticle swarm optimizationSingle-nucleotide polymorphismSNP interaction

Identifiers

PMID24955105

DOI10.1186/1744-859X-13-15

PMCPMC4050220

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