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

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• 作者：Shyh-Jong Wu (1)
  Li-Yeh Chuang (2)
  Yu-Da Lin (3)
  Wen-Hsien Ho (4)
  Fu-Tien Chiang (5)
  Cheng-Hong Yang (3)
  Hsueh-Wei Chang (6) (7)
  
• 关键词：Hypertension ; Single nucleotide polymorphism ; SNP interactions ; Particle swarm optimization ; Renin ; angiotensin system
• 刊名：Molecular Biology Reports
• 出版年：2013
• 出版时间：July 2013
• 年：2013
• 卷：40
• 期：7
• 页码：4227-4233
• 全文大小：229KB
• 参考文献：1. Mehri S, Mahjoub S, Hammami S et al (2012) Renin-angiotensin system polymorphisms in relation to hypertension status and obesity in a Tunisian population. Mol Biol Rep 39:4059-065 CrossRef
  2. Turgut S, Akin F, Akcilar R et al (2011) Angiotensin converting enzyme I/D, angiotensinogen M235T and AT1-R A/C1166 gene polymorphisms in patients with acromegaly. Mol Biol Rep 38:569-76 CrossRef
  3. Wu SJ, Chiang FT, Jiang JR et al (2003) The G-217A variant of the angiotensinogen gene affects basal transcription and is associated with hypertension in a Taiwanese population. J Hypertens 21:2061-067 CrossRef
  4. Wu SJ, Chiang FT, Chen WJ et al (2004) Three single-nucleotide polymorphisms of the angiotensinogen gene and susceptibility to hypertension: single locus genotype vs. haplotype analysis. Physiol Genomics 17:79-6 CrossRef
  5. Tsai CT, Hwang JJ, Lai LP et al (2009) Interaction of gender, hypertension, and the angiotensinogen gene haplotypes on the risk of coronary artery disease in a large angiographic cohort. Atherosclerosis 203:249-56 CrossRef
  6. Tsai CT, Fallin D, Chiang FT et al (2003) Angiotensinogen gene haplotype and hypertension: interaction with ACE gene I allele. Hypertension 41:9-5 CrossRef
  7. Jiang Z, Zhao W, Yu F et al (2001) Association of angiotensin II type 1 receptor gene polymorphism with essential hypertension. Chin Med J (Engl) 114:1249-251
  8. Srivastava K, Sundriyal R, Meena PC et al (2012) Association of angiotensin converting enzyme (insertion/deletion) gene polymorphism with essential hypertension in northern Indian subjects. Genet Test Mol Biomarkers 16:174-77 CrossRef
  9. Niu W, Qi Y (2010) Association of the angiotensin II type I receptor gene +1166 A>C polymorphism with hypertension risk: evidence from a meta-analysis of 16,474 subjects. Hypertens Res 33:1137-143 CrossRef
  10. Manolio TA, Collins FS, Cox NJ et al (2009) Finding the missing heritability of complex diseases. Nature 461:747-53 CrossRef
  11. Stringer S, Wray NR, Kahn RS et al (2011) Underestimated effect sizes in GWAS: fundamental limitations of single SNP analysis for dichotomous phenotypes. PLoS ONE 6:e27964 CrossRef
  12. Yen CY, Liu SY, Chen CH et al (2008) Combinational polymorphisms of four DNA repair genes XRCC1, XRCC2, XRCC3, and XRCC4 and their association with oral cancer in Taiwan. J Oral Pathol Med 37:271-77 CrossRef
  13. Lin GT, Tseng HF, Chang CK et al (2008) SNP combinations in chromosome-wide genes are associated with bone mineral density in Taiwanese women. Chin J Physiol 51:32-1
  14. Lavender NA, Rogers EN, Yeyeodu S et al (2012) Interaction among apoptosis-associated sequence variants and joint effects on aggressive prostate cancer. BMC Med Genomics 5:11 CrossRef
  15. Yang CW, Li CI, Liu CS et al (2013) The joint effect of cigarette smoking and polymorphisms on LRP5, LEPR, near MC4R and SH2B1 genes on metabolic syndrome susceptibility in Taiwan. Mol Biol Rep 40:525-33 CrossRef
  16. Tsai CT, Hwang JJ, Ritchie MD et al (2007) Renin-angiotensin system gene polymorphisms and coronary artery disease in a large angiographic cohort: detection of high order gene–gene interaction. Atherosclerosis 195:172-80 CrossRef
  17. Heslop CL, Tebbutt SJ, Podder M et al (2012) Combined polymorphisms in oxidative stress genes predict coronary artery disease and oxidative stress in coronary angiography patients. Ann Hum Genet 76:435-47 CrossRef
  18. Montasser ME, Gu D, Chen J et al (2011) Interactions of genetic variants with physical activity are associated with blood pressure in Chinese: the GenSalt study. Am J Hypertens 24:1035-040 CrossRef
  19. Meyers KJ, Chu J, Mosley TH et al (2010) SNP–SNP interactions dominate the genetic architecture of candidate genes associated with left ventricular mass in African–Americans of the GENOA study. BMC Med Genet 11:160 CrossRef
  20. Kaur R, Das R, Ahluwalia J et al (2012) Synergistic effect of angiotensin II type-1 receptor 1166A/C with angiotensin-converting enzyme polymorphism on risk of acute myocardial infarction in north Indians. J Renin Angiotensin Aldosterone Syst 13:440-45 CrossRef
  21. Chang HW, Chuang LY, Ho CH et al (2008) Odds ratio-based genetic algorithms for generating SNP barcodes of genotypes to predict disease susceptibility. OMICS 12:71-1 CrossRef
  22. Emily M, Mailund T, Hein J et al (2009) Using biological networks to search for interacting loci in genome-wide association studies. Eur J Hum Genet 17:1231-240 CrossRef
  23. Yang CH, Chuang LY, Cheng YH et al (2012) Single nucleotide polymorphism barcoding to evaluate oral cancer risk using odds ratio-based genetic algorithms. Kaohsiung J Med Sci 28:362-68 CrossRef
  24. Guy RT, Santago P, Langefeld CD (2012) Bootstrap aggregating of alternating decision trees to detect sets of SNPs that associate with disease. Genet Epidemiol 36:99-06 CrossRef
  25. Lin GT, Tseng HF, Yang CH et al (2009) Combinational polymorphisms of seven CXCL12-related genes are protective against breast cancer in Taiwan. OMICS 13:165-72 CrossRef
  26. Mitra AK, Singh SV, Garg VK et al (2011) Protective association exhibited by the single nucleotide polymorphism (SNP) rs1052133 in the gene human 8-oxoguanine DNA glycosylase (hOGG1) with the risk of squamous cell carcinomas of the head and neck (SCCHN) among north Indians. Indian J Med Res 133:605-12
  27. Yang CH, Chuang LY, Chen YJ et al (2011) Computational analysis of simulated SNP interactions between 26 growth factor-related genes in a breast cancer association study. OMICS 15:399-07 CrossRef
  28. Rodrigues P, Furriol J, Tormo E et al (2012) The single-nucleotide polymorphisms +936 C/T VEGF and ?10 C/T VEGFR1 are associated with breast cancer protection in a Spanish population. Breast Cancer Res Treat 133:769-78 CrossRef
  29. Chuang LY, Lin YD, Chang HW et al (2012) An improved PSO algorithm for generating protective SNP barcodes in breast cancer. PLoS ONE 7:e37018 CrossRef
  30. Kennedy J, Eberhart RC (1995) Particle swarm optimization. Proceedings IEEE international conference on neural networks, Perth, Australia, pp 1942-948
  31. Niknam T, Amiri B (2010) An efficient hybrid approach based on PSO, ACO and k-means for cluster analysis. Appl Soft Comput 10:183-97 CrossRef
  32. Chen LF, Su CT, Chen KH (2012) An improved particle swarm optimization for feature selection. Intell Data Anal 16:167-82
  33. Bratton D, Kennedy J (2007) Defining a standard for particle swarm. Swarm Intelligence Symposium, 2007. SIS 2007. IEEE, pp 120-27
  34. Chiang FT, Hsu KL, Chen WM et al (1998) Determination of angiotensin-converting enzyme gene polymorphisms: stepdown PCR increases detection of heterozygotes. Clin Chem 44:1353-356
  35. Hilgers KF, Langenfeld MR, Schlaich M et al (1999) 1166 A/C polymorphism of the angiotensin II type 1 receptor gene and the response to short-term infusion of angiotensin II. Circulation 100:1394-399 CrossRef
  36. Zhang F, Yang Y, Hu D et al (2012) Lack of an association between TSC gene Arg904Gln polymorphisms and essential hypertension risk based on a meta-analysis. Genet Mol Res 11:3511-517 CrossRef
  37. Polimanti R, Piacentini S, Lazzarin N et al (2012) Lack of association between essential hypertension and GSTO1 uncommon genetic variants in Italian patients. Genet Test Mol Biomarkers 16:615-20 CrossRef
  38. Li YY (2012) Lack of association of A-6G polymorphism of AGT gene with essential hypertension in the Chinese population. J Cardiovasc Med (Hagerstown) 13:505-10 CrossRef
  39. Ayadi Kabadou I, Soualmiaa H, Jemaa R et al (2012) Lack of association between C3123A polymorphism of the angiotensin II type 2 receptor gene and hypertension in Tunisian population. Tunis Med 90:619-24
  40. Chang HW, Yang CH, Ho CH et al (2009) Generating SNP barcode to evaluate SNP–SNP interaction of disease by particle swarm optimization. Comput Biol Chem 33:114-19 CrossRef
  41. Chuang LY, Chang HW, Lin MC et al (2012) Chaotic particle swarm optimization for detecting SNP–SNP interactions for CXCL12-related genes in breast cancer prevention. Eur J Cancer Prev 21:336-42 CrossRef
  42. Su G, Christensen OF, Ostersen T et al (2012) Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers. PLoS ONE 7:e45293 CrossRef
  43. Sober S, Org E, Kepp K et al (2009) Targeting 160 candidate genes for blood pressure regulation with a genome-wide genotyping array. PLoS ONE 4:e6034 CrossRef
  
• 作者单位：Shyh-Jong Wu (1)
  Li-Yeh Chuang (2)
  Yu-Da Lin (3)
  Wen-Hsien Ho (4)
  Fu-Tien Chiang (5)
  Cheng-Hong Yang (3)
  Hsueh-Wei Chang (6) (7)
  
  1. Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung, Taiwan
  2. Department of Chemical Engineering and Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan
  3. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan
  4. Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan
  5. Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
  6. Cancer Center, Kaohsiung Medical University, Kaohsiung, Taiwan
  7. Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
  
• ISSN：1573-4978

文摘

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- SNPs were 0.705-.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.