Interaction between SELP genetic polymorphisms with inflammatory cytokine interleukin-6 (IL-6) gene variants on cardiovascular disease in Chinese Han population

Abstract

The aim of the study is to investigate the impact of SELP and IL-6 genetic single-nucleotide polymorphisms (SNPs) and its gene-gene interaction on cardiovascular disease (CVD) risk based on Chinese population. A total of 1082 subjects (519 males, 563 females), with a mean age of 53.9 ± 13.1 years, were selected, including 540 CVD patients and 542 normal control participants. Logistic regression model was used to examine the association between six SNPs and CVD risk. Odds ratio (OR) and 95% confident interval (95% CI) were calculated. Generalized multifactor dimensionality reduction (GMDR) was employed to analyze the gene-gene interaction. CVD risk was significantly higher in carriers with rs1800805-A allele than those with GG genotype (GA + AA vs. GG), adjusted OR (95% CI) = 1.69 (1.31-2.16), and CVD risk was also higher in carriers with rs6136-AC or CC genotype than those with AA genotype (AC + CC vs. AA), adjusted OR (95% CI) = 1.78 (1.28-2.26), and higher in carriers with rs1800796-GC or CC genotype than those with GG genotype (CC + GC vs. GG), adjusted OR (95% CI) = 1.67 (1.25-2.14). GMDR analysis suggested a significant two-locus model (p = 0.0010) involving rs1800805 and rs1800796. Overall, the cross-validation consistency of this model was 10/10, and the testing accuracy was 62.17%, and participants with rs1800805-GA or AA and rs1800796-GC or CC genotype have the highest CVD risk, compared to participants with rs1800805-GG and rs1800796-GG genotypes, and OR (95% CI) was 2.52 (1.81-2.66). Our results support an important association of rs1800805, rs6136 minor allele of SELP gene, rs1800796 within IL-6 gene, and additional interaction between rs1800805 and rs1800796 with increased risk of CVD.

Interleukin 6 (rs1800795) gene polymorphism is associated with cardiovascular diseases: a meta-analysis of 74 studies with 86,229 subjects

“…After excluding the overlapping articles of the literature search and applying the selection criteria mentioned previously, 74 research articles (Coker et al, 2011[ 14 ]; Banerjee et al, 2008[ 3 ], 2009[ 4 ]; Balding et al, 2004[ 2 ]; Bennet et al, 2003[ 7 ]; Akinyemi et al, 2017[ 1 ]; Humphries et al, 2001[ 31 ], 2007[ 30 ]; Jabir et al, 2017[ 33 ]; Jenny et al, 2002[ 34 ]; Elsaid et al, 2014[ 17 ]; Chiappelli et al, 2005[ 13 ]; Flex et al, 2004[ 20 ]; Karahan et al, 2005[ 37 ]; Li et al, 2015[ 41 ]; Liaquat et al, 2014[ 42 ]; Kelberman et al, 2004[ 38 ]; Kou et al, 2017[ 39 ]; Lalouschek et al, 2006[ 40 ]; Satti et al, 2013[ 63 ]; Sekuri et al 2007[ 64 ]; Sie et al, 2006[ 65 ]; Wang et al, 2015;[ 81 ] Weger et al, 2005[ 82 ]; Yang et al, 2015[ 83 ]; Basso et al, 2002[ 5 ]; Bennermo et al, 2011[ 6 ]; Berg et al, 2009[ 8 ]; Bhanushali et al, 2013[ 9 ]; Buraczynska et al, 2016[ 10 ]; Chakraborty et al, 2013[ 11 ]; Chamorro et al, 2005[ 12 ]; Danielsson et al, 2005[ 15 ]; Densem et al, 2005[ 16 ]; Fan et al, 2011[ 18 ]; Flex et al, 2002[ 21 ]; Galimudi et al, 2014[ 22 ]; George et al, 2004[ 23 ]; Georges et al, 2001[ 24 ]; Ghazouani et al, 2010[ 26 ], 2011[ 25 ]; Greisenegger et al, 2003[ 27 ]; Hongmei et al, 2016[ 28 ]; Jun et al, 2017[ 36 ]; Licastro et al, 2004[ 43 ]; Lieb et al, 2004[ 44 ]; Maitra et al, 2008[ 48 ]; Mao et al, 2016[ 49 ]; Mastana et al, 2017[ 50 ]; Mishra et al, 2013[ 51 ]; Mitrokhin et al, 2017[ 52 ]; Myśliwska et al, 2006[…”

“…In Table 1 (Tab. 1) (References in Table 1: Akinyemi, 2017[ 1 ]; Balding, 2004[ 2 ]; Banerjee, 2008[ 3 ]; Basso, 2002[ 5 ]; Bennermo, 2011[ 6 ]; Bennet, 2003[ 7 ]; Berg, 2009[ 8 ]; Bhanushali, 2013[ 9 ]; Buraczynska, 2016[ 10 ]; Chakraborty, 2013[ 11 ]; Chamorro, 2005[ 12 ]; Chiapelli, 2005[ 13 ]; Coker, 2011[ 14 ]; Danielsson, 2005[ 15 ]; Densem, 2005[ 16 ]; Elsaid, 2014[ 17 ]; Fan, 2011[ 18 ]; Flex, 2002[ 21 ]; Flex, 2004[ 20 ]; Flex, 2007[ 19 ]; Galimudi, 2014[ 22 ]; George, 2004[ 23 ]; Georges, 2001[ 24 ]; Ghazouani, 2010[ 26 ]; Ghazouani, 2011[ 25 ]; Greisenegger, 2003[ 27 ]; Hongmei, 2016[ 28 ]; Humphries, 2001[ 31 ]; Humphries, 2007[ 30 ]; Jabir, 2017[ 33 ]; Jenny, 2002[ 34 ]; Jun, 2017[ 36 ]; Karahan, 2005[ 37 ]; Kelberman, 2004[ 38 ]; Kou, 2017[ 39 ]; Lalouschek, 2006[ 40 ]; Li, 2015[ 41 ]; Liaquat, 2014[ 42 ]; Licastro, 2004[ 43 ]; Lieb, 2004[ 44 ]; Maitra, 2008[ 48 ]; Mao, 2016[ 49 ]; Mastana, 2017[ 50 ]; Mishra[ 51 ], 2013; Mitrokhin, 2017[ 52 ]; Mysliwska, 2006[ 53 ]; Nauck, 2002[ 54 ]; Panoulas, 2009[ 55 ]; Phulukdaree, 2013[ 56 ]; Potacsek, 2007[ 57 ]; Revilla, 2002[ 58 ]; Rios, 2010[ 59 ]; Rosner, 2005[ 60 ]; Salama, 2015[ 61 ]; Sarecka, 2008[ 62 ]; Satti, 2013[ 63 …”

“…Firstly, in the Chinese population, there was no evidence of heterogeneity in the genetic models and rs1800795 was a risk factor due to its association with CVD ( allelic OR=1.36, CI 95%=1.26-1.48, Z p value= <0.0001 (Figure 2 (Fig. 2) ; References in Figure 2: Fan, 2011[ 18 ]; Hongmei, 2016[ 28 ]; Jun, 2017[ 36 ]; Kou, 2017[ 39 ]; Li, 2015[ 41 ]; Mao, 2016[ 49 ]; Sun, 2014[ 72 ]; Tong, 2010[ 75 ]; Tong, 2013[ 76 ]; Wang, 2015[ 81 ]; Yang, 2015[ 83 ]); homozygous OR = 1.91, CI 95%=1.61-2.27, Z p value= <0.0001; heterozygous OR=1.21, CI 95%=1.09-1.34, Z p value= <0.0001; dominant OR= 1.16, CI 95%=1.05-1.27, Z p value= 0.002; recessive OR= 1.78, CI 95%= 1.51-2.10, Z p value <0.0001).…”

“…The results of this analysis revealed a role of -174 G>C polymorphism as a risk factor for CVD under the allelic (OR= 1.12, CI 95%= 1.07-1.18, Z p value <0.0001; Figure 7 (Fig. 7) ; References in Figure 7: Akinyemi, 2017[ 1 ]; Balding, 2004[ 2 ]; Banerjee, 2009[ 4 ]; Chakraborty, 2013[ 11 ]; Chiapelli, 2005[ 13 ]; Danielsson, 2005[ 15 ]; Fan, 2011[ 18 ]; George, 2004[ 23 ]; Georges, 2001[ 24 ]; Ghazouani, 2010[ 26 ]; Ghazouani, 2011[ 25 ]; Greisenegger, 2003[ 27 ]; Hongmei, 2016[ 28 ]; Humphries, 2001[ 31 ]; Humphries, 2007[ 30 ]; Jabir, 2017[ 33 ]; Jenny, 2002[ 34 ]; Jun, 2017[ 36 ]; Karahan, 2005[ 37 ]; Kou, 2017[ 39 ]; Lalouschek, 2006[ 40 ]; Maitra, 2008[ 48 ]; Mastana, 2017[ 50 ]; Mishra, 2013[ 51 ]; Mysliwska, 2006[ 53 ]; Potacsek, 2007[ 57 ]; Salama, 2015[ 61 ]; Sarecka, 2008[ 62 ]; Sekuri, 2007[ 64 ]; Smith, 2008[ 68 ]; Tong, 2010[ 75 ]; Tretjakovs, 2007[ 77 ]; Wang, 2015[ 81 ]), homozygous (OR= 1.23, CI 95%= 1.11 1.37, Z p value <0.0001), heterozygous (OR= 1.17, CI 95%= 1.10-1.24, Z p value <0.0001), and dominant models (OR= 1.24, CI 95%= 1.16-1.31, Z p value <0.0001). Nonetheless, in the presence of heterogeneity, an association was found under the recessive model (OR= 1.31, CI 95%= 1.11-1.54, Z p value <0.0001; I 2 =76.56), but not when the articles favoring heterogeneity were excluded.…”

“…The expression of IL-6 is regulated mainly at the transcriptional level (Li et al, 2015[ 41 ]; Liaquat et al, 2014[ 42 ]). The promoter of the human IL-6 gene contains several polymorphisms; one commonly studied variant is the single G>C base exchange polymorphism in the promoter region of IL-6 gene, 174 base pairs (bp) upstream from the start site of transcription (-174 G>C , rs1800795) (Karahan et al, 2005[ 37 ]; Li et al, 2015[ 41 ]; Kelberman et al, 2004[ 38 ]; Kou et al, 2017[ 39 ]; Lalouschek et al, 2006[ 40 ]). The -174 G>C promoter polymorphism has been shown to be functionally important because it influences the transcription rate of the gene and the plasma concentrations of IL-6 (Satti et al, 2013[ 63 ]; Sekuri et al 2007[ 64 ]; Sie et al, 2006[ 65 ]).…”