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Particle swarm optimization algorithm for analyzing SNP–SNP interaction of renin-angiotensin system genes against hypertension

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Abstract

Most non-significant individual single nucleotide polymorphisms (SNPs) were undiscovered in hypertension association studies. Their possible SNP–SNP interactions were usually ignored and leaded to missing heritability. In present study, we proposed a particle swarm optimization (PSO) algorithm to analyze the SNP–SNP interaction associated with hypertension. Genotype dataset of eight SNPs of renin-angiotensin system genes for 130 non-hypertension and 313 hypertension subjects were included. Without SNP–SNP interaction, most individual SNPs were non-significant difference between the hypertension and non-hypertension groups. For SNP–SNP interaction, PSO can select the SNP combinations involving different SNP numbers, namely the best SNP barcodes, to show the maximum frequency difference between non-hypertension and hypertension groups. After computation, the best PSO-generated SNP barcodes were dominant in non-hypertension in terms of the occurrences of frequency differences between non-hypertension and hypertension groups. The OR values of the best SNP barcodes involving 2–8 SNPs were 0.705–0.334, suggesting that these SNP barcodes were protective against hypertension. In conclusion, this study demonstrated that non-significant SNPs may generate the joint effect in association study. Our proposed PSO algorithm is effective to identify the best protective SNP barcodes against hypertension.

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Acknowledgments

This work was supported by the National Science Council of Taiwan NSC 94-2320-B-037-014 to Shyh-Jong Wu, NSC101-2221-E-214-075 to Li-Yeh Chuang, NSC101-2622-E-151-027-CC3 to Cheng-Hong Yang, and NSC101-2320-B-037-049 to Hsueh-Wei Chang, the Department of Health, Executive Yuan, Republic of China (DOH102-TD-C-111-002), the Kaohsiung Medical University Research Foundation (KMUER001), and the National Sun Yat-Sen University-KMU Joint Research Project (#NSYSUKMU 102-034).

Conflict of interest

The authors declared no conflicts of interest.

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Authors and Affiliations

  1. Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung, Taiwan

    Shyh-Jong Wu

  2. Department of Chemical Engineering and Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan

    Li-Yeh Chuang

  3. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan

    Yu-Da Lin & Cheng-Hong Yang

  4. Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan

    Wen-Hsien Ho

  5. Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan

    Fu-Tien Chiang

  6. Cancer Center, Kaohsiung Medical University, Kaohsiung, Taiwan

    Hsueh-Wei Chang

  7. Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan

    Hsueh-Wei Chang

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  1. Shyh-Jong Wu
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  2. Li-Yeh Chuang
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  3. Yu-Da Lin
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  4. Wen-Hsien Ho
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  5. Fu-Tien Chiang
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  6. Cheng-Hong Yang
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  7. Hsueh-Wei Chang
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Correspondence to Cheng-Hong Yang or Hsueh-Wei Chang.

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Wu, SJ., Chuang, LY., Lin, YD. et al. Particle swarm optimization algorithm for analyzing SNP–SNP interaction of renin-angiotensin system genes against hypertension. Mol Biol Rep 40, 4227–4233 (2013). https://doi.org/10.1007/s11033-013-2504-8

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  • DOI: https://doi.org/10.1007/s11033-013-2504-8

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