Influence of haplotypes, gene expression and soluble levels of L-selectin on the risk of acute coronary syndrome

Gene 625 (2017) 31–41

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Research paper

Influence of haplotypes, gene expression and soluble levels of L-selectin on the risk of acute coronary syndrome

MARK

Elena Sandoval-Pintoa,b, Jorge Ramón Padilla-Gutiérreza, Jorge Hernández-Belloa,c, Diana Emilia Martínez-Fernándeza,b, Emmanuel Valdés-Alvaradoa,b, José Francisco Muñoz-Vallea, H.E. Flores-Salinasd,e, Yeminia Vallea,⁎ a

Instituto de Investigación en Ciencias Biomédicas, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico Doctorado en Ciencias Biomédicas, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico c Doctorado en Genética Humana, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico d Especialidad en Cardiología IMSS, Centro Universitario de Ciencias de la Salud, Guadalajara, Jalisco, Mexico e Unidad Médica de Alta Especialidad, Centro Médico Nacional de Occidente, Departamento de Cardiología, Instituto Mexicano del Seguro Social, Mexico b

A R T I C L E I N F O

A B S T R A C T

Keywords: Adhesion molecules Genetic variants mRNA Myocardial infarction Soluble protein concentration Unstable angina

Background: L-selectin gene (SELL) is a candidate gene for the development of acute coronary syndrome (ACS) that contributes to endothelial dysfunction. The −642C > T (rs2205849) and 725C > T (rs2229569) polymorphisms have been associated with changes in gene expression, ligand affinity and increased risk of cardiovascular disease. The aim of this study was to investigate the association between the haplotypes constructed with the −642C > T and 725C > T polymorphisms of the SELL gene, the expression levels of its mRNA and the serum levels of soluble L-selectin with ACS. Methods: We recruited 615 individuals of Mexican origin matched by age, including 342 patients with ACS and 273 individuals without personal history of ischemic cardiopathy as control group (CG). Genotyping was performed by PCR-RFLP. The qPCR technique was used to analyze the expression of mRNA using TaqMan® UPL probes. The levels of soluble L-selectin were measured with ELISA. Results: The allele variants in both polymorphisms were over-represented in the CG compared to the ACS (OR range: 0.371–0.716, p < 0.006). The CT and TT haplotypes had a protective effect against the development of ACS (OR = 0.401, p < 0.0001; OR = 0.628, p < 0.0001, respectively). SELL expression was 3.076 times higher in the ACS group compared to CG (p < 0.001). The levels of soluble L-selectin were similar between ACS and CG. Conclusions: Both polymorphisms had no effect on mRNA expression and soluble protein levels. The polymorphisms −642C > T and 725C > T of the SELL gene are protective factors against the development of ACS. There is an increased gene expression of L-selectin in ACS compared to CG in the population of Western Mexico.

1. Introduction Acute coronary syndrome (ACS) is a term used to identify a group of clinical entities with the same pathophysiological mechanism: ischemia

or acute coronary insufficiency. This spectrum includes unstable angina (UA), acute myocardial infarction with and without ST elevation (STEMI and NSTEMI, respectively). Acute ischemia is in most cases caused by the rupture of an atherosclerotic plaque in a coronary artery,

Abbreviations: ACS, acute coronary syndrome; ACC, American College of Cardiology; ADAM17, a disintegrin and metalloproteinase 17; BMI, body mass index; bp, base pairs; cDNA, complementary deoxyribonucleic acid; CG, control group; CPK, creatine phosphokinase; Cq, quantification cycle; D´, normalized linkage disequilibrium; DM2, Type 2 diabetes mellitus; ELISA, enzyme-linked immunosorbent assay; gDNA, genomic deoxyribonucleic acid; HWE, Hardy-Weinberg equilibrium; ICAM-1, Intercellular Adhesion Molecule-1; IFN-γ, interferon gamma; IgA, immunoglobulin A; IL-1β, interleukin 1 beta; IL-6, interleukin 6; IQR, interquartile range; LD, linkage disequilibrium; MAP kinase, mitogen-activated protein kinase; mRNA, messenger RNA; NSTEMI, non ST segment elevation myocardial infarction; OR, odds ratio; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; qPCR, quantitative polymerase chain reaction; r, Spearman's correlation test; r2, squared correlation of allele frequencies; REU, relative expression units; SELL, selectin L gene; sL-selectin, soluble L-selectin; SNP, single nucleotide polymorphism; STEMI, ST segment elevation myocardial infarction; sVCAM, soluble vascular cell adhesion molecule 1; TNF-α, tumor necrosis factor alpha; UA, Unstable angina ⁎ Corresponding author at: Instituto de Investigación en Ciencias Biomédicas (IICB), Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico. E-mail address: [email protected] (Y. Valle). http://dx.doi.org/10.1016/j.gene.2017.05.005 Received 27 January 2017; Received in revised form 14 March 2017; Accepted 2 May 2017 Available online 03 May 2017 0378-1119/ © 2017 Elsevier B.V. All rights reserved.

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and signed a written informed consent. Ethical approval was given by Centro Universitario de Ciencias de la Salud, CUCS, U de G (CI/065/ 2014).

with rapid platelet accumulation and formation of an occlusive thrombus (Cannon et al., 2013; Leiva-Pons, 2009). The vulnerable atherosclerotic plaques that cause acute ischemic events have their own characteristics: a) An intense local inflammatory reaction; b) Rupture or erosion; c) Presence of intracoronary thrombus; d) Increased vasoreactivity (Domínguez Franco et al., 2006). The pathogenesis of atherosclerosis involves a significant inflammatory component, requiring the recruitment and adhesion of circulating inflammatory cells and their transendothelial migration (Libby, 2002; Ross, 1999). L-selectin is a cell adhesion molecule belonging to the selectin family. It is expressed by leukocytes, mainly neutrophils, and plays an important role in the initial phases of leukocyte adhesion to the endothelium (Berlin et al., 1995; Kadono et al., 2002). The increased soluble levels and/or mRNA expression of L-selectin has been associated with various diseases including unstable angina (Atalar et al., 2001; Blann et al., 1996; Siminiak et al., 1999) and coronary artery disease (Atalar et al., 2002; Signorelli et al., 2003). L-selectin is coded by the human SELL gene, located in 1q24-q25 (Iida and Nakamura, 2003). Variants in this gene can act as genetic risk factors for atherosclerosis-related diseases. A relation between several polymorphisms in the SELL gene and inflammatory diseases has been reported (Kamiuchi et al., 2002; Xia et al., 2007). The −642C > T polymorphism (rs2205849) in the promoter region has shown a consistent association with some autoimmune and viral diseases, but its involvement in cardiovascular diseases has not been explored. Luciferase assays have been used to determine that the T allele is associated with increased expression of SELL (Takei et al., 2006). The 725C > T polymorphism (rs2229569) involves a substitution of proline for serine at codon 213 in the short consensus repeat domain-1, and probably alters the interaction between the leukocyte and the endothelium (Derzbach et al., 2006). A previous study proved that C/C (Pro/ Pro) homozygous individuals had a higher risk of coronary heart disease in Asian population (Xia et al., 2007). In this study, we evaluate the association between the −642C > T and 725C > T polymorphisms in the SELL gene, their mRNA expression and their soluble protein levels in ACS.

2.3. Genetic analysis The genomic DNA (gDNA) was obtained from peripheral blood using a modified Miller's technique (Miller et al., 1988). The gDNA purity and concentration was measured with spectrophotometer at a wavelength of 260 nm (absorbance of nucleic acids) and 280 nm (absorbance of proteins). The polymorphisms were amplified by polymerase chain reactionrestriction fragment length polymorphism (PCR-RFLP) using the primers described previously for the 725C > G (Kamiuchi et al., 2002). Regarding the −642C > T polymorphism, the following sequence was used. Sense: 5′-AGGTACTTGTAGGCTCCC-3′ and anti-sense: 5′CTTCACCTCCGTCTTTCCTT-3′ (Kamiuchi et al., 2002). These polymorphisms were selected based on their functional effect (described in Introduction). PCR amplification was performed in a total volume of 20 μL containing 10 ng/μL of gDNA, 0.08 IU/μL of Taq polymerase (Invitrogen™, Carlsbad, CA, USA), 1X buffer, 0.6 pM of each primer, 1.5 mM of MgCl2 and 0.1 mM of dNTP. The thermal cycling conditions for the −642C > T polymorphism the following cycling conditions were used: initial denaturation for 5 min at 94 °C, followed by 30 cycles of 45 s at 94 °C, 45 s at 62 °C as annealing temperature and 45 s at 72 °C, before a final extension for 5 min at 72 °C. Regarding 725C > G were as follows: 3 min initial denaturation at 94 °C, 32 cycles of 94 °C for 30 s, 57 °C for 30s and 72 °C for 30s with a final extension for 60s at 72 °C. The PCR fragments of 132 bp for the −642C > T and 186 bp for the 725C > G polymorphisms were digested with 5 U of the PflMI (New England BioLabs®, Beverly, MA) and HphI (New England BioLabs®, Beverly, MA) enzymes, respectively. The final volume of the reaction was 15 μL and digested at 37 °C/1 h. The digestion pattern for the e642C allele showed two fragments of 103 and 29 bp and 132 bp for the T allele. The 725C allele was digested in two fragments of 141 and 45 bp and 186 bp for the G allele. The PCR products and the digested products were analyzed by polyacrylamide gel electrophoresis 6% (29:1, acrylamide:bis-acrylamide) and silver nitrate staining. As quality control, 25% of samples were randomly repeated.

2. Material and methods 2.1. Study population We studied 615 unrelated subjects from Western of Mexico with a Mexican origin of at least three generations, including their own. Two groups were formed with the following characteristics: (1) Two hundred seventy-three individuals were assigned to the control group (CG, 137 men and 136 women). A survey of their medical history was carried out in all subjects. The inclusion criteria consisted of individuals with a similar age to ACS patients with no personal history of ischemic cardiomyopathy, without treatment and recruited in the same period. The number of controls was lesser than cases because the medical treatment consumption in CG. The laboratory parameters (cholesterol, glucose and triglycerides) of the CG were within the normal ranges (Biosystems Cod. 11506, Cod. 11538 and Cod. 11529). (2) The ACS group was formed by 342 patients (265 men, 77 women) from the "Hospital de Especialidades del Centro Médico Nacional de Occidente del Instituto Mexicano del Seguro Social (CMNO IMSS)" meeting the criteria of the American College of Cardiology (ACC) for ACS (Cannon et al., 2013). The recruitment was made within the second and third days after the acute coronary event. Individuals with other diseases such as infections, cancer and autoimmune diseases were not considered.

2.3.1. Sample size calculation The sample size was calculated in Open Epi info (http://www. openepi.com/Menu/OE_Menu.htm) with the following parameters, confidence interval (CI) = 95%, case:control proportion = 1:1, statistical power β = 0.80, minor allele frequency reported in CEU population MAF = 10.6% (http://www.ncbi.nlm.nih.gov/SNP/snp_ref.cgi? type=rs&rs=2229569), OR > 2, and expected proportion in cases = 19.17%, 2n = 271 alleles (at least 136 individuals). 2.4. Analysis of linkage disequilibrium (LD). Haplotypes were inferred by EM algorithm. The normalized LD (D´) and squared correlation of allele frequencies (r2) were estimated using the SHEsis program (http://analysis.bio-x.cn/myAnalysis.php). 2.5. Analysis of mRNA expression RNA was extracted from leukocytes from peripheral blood samples according to the Chomczynski and Sacchi method (Chomczynski and Sacchi, 1987). cDNA was synthesized from RNA using the oligo-dT and M-MLV reverse transcriptase (Promega, Madison, Wis, USA). The concentrations of RNA and cDNA were quantified with spectrophotometer at a ratio concentration between 1.8 and 2 (A260/280 nm). The relative levels of mRNA expression in the SELL gene were measured by

2.2. Ethical considerations The study was conducted in accordance with the Declaration of Helsinki. All patients with ACS and CG subjects agreed to participate 32

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qPCR with TaqMan probes (probe# 72 Roche, ref.: 04688953001), using GAPDH (Universal ProbeLibrary Human GAPDH Gene Assay REF: 05190541001) as reference gene in a LightCycler 96 (ROCHE). The primers amplified a fragment of 60 nucleotides which included exons 2 and 3 of the gene. The cDNA concentration was 250 ng/μL. The amplification by qPCR was performed in a total volume of 10 μL containing 10 ng/μL of cDNA, 1X of Master mix, 0.2 μM of probe and 0.4 μM of each primer. The thermocycling conditions were as follows: initial denaturation at 95 °C for 10 min, 40 cycles that included 15 s of warming and 1 min of alignment and extension at 60 °C. The assays were performed in triplicate. The coefficients of variation were within acceptable ranges (< 10%). No-template controls were included in each reaction. For the assessment of the expression levels, the individuals were matched by age (60 ± 15 years) and gender (CG: 12 women and 26 males; ACS: 11 women and 20 males). The qPCR conditions resulted in expected amplicon size and a single-band of amplification and further validated by melting curve analysis.

Table 1 Clinical and demographic data.

Age (mean ± SD) Female/Male FHC NSTEMI Reinfarction STEMI UA Risk factors Hypertension DM2 Smoking Dyslipidemia Overweight Obesity

CG n = 273 (%)

ACS n = 342 (%)

p

57 ± 8.4 136/137 – – – – –

63 ± 10.9 77/265 147 (43.0) 64 (18.7) 51 (14.9) 236 (69.0) 42 (12.3)

< 0.001* < 0.001* – – – – –

90 (33.0) 59 (21.6) 37 (13.6) 41(15.0) 36 (13.2) 28 (10.3)

226 (66.1) 176 (51.5) 171 (50.0) 143 (41.8) 139 (40.6) 92 (26.9)

< 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001

Para-clinical

Mean (CI 95%)

Mean (CI 95%)

p

Reference value

CPK (UI/mL)

–

< 0.001

24–195

Glucose (mg/dL)

118.9 (109.1–128.6) 173.2 (163.2–183.3) 119.7 (112.2–127.2) –

902 (742.2–1062) 142.7 (136.2–149.2) 120.8 (116.6–125.0) 97.9 (93.89–101.9) 6.617 (4.47–8.49)

< 0.001

75–105

< 0.001

150–199

< 0.001

< 250

–

0.1–0.4

0.1342 < 0.001

– –

2.6. Amplification efficiency Serial cDNA dilution curves were made to calculate the amplification efficiency for both genes. A graph of quantification cycle (Cq) versus log10 relative copy number of the sample from dilution series was produced. Efficiency values were < 2, indicating efficient amplification (Livak and Schmittgen, 2001; Wilkening and Bader, 2004).

Total Cholesterol (mg/dL) Triglycerides (mg/dL) Troponin I (ng/ dL) Cytokines IL-1β (pg/mL) TNF-α (pg/mL)

2.7. Analysis of soluble L-selectin, TNF-α and IL-1β levels The levels of soluble L-selectin (sL-selectin), TNF-α and IL-1β were measured in duplicate in serum samples from patients in the ACS and CG groups using the enzyme-linked immunosorbent assay (ELISA) according to the manufacturer's specifications (Abcam™). The detection range for sL-selectin and IL-1β was 1.7 to 1000 ng/mL and for TNF-α was from 1.7 to 1000 pg/mL. The assay sensitivity for sL-selectin, TNFα and IL-1β was 1.7, 8.0 and 6.5 ng/mL, respectively. The concentration was calculated using a four-parameter analysis with curve fitting. The coefficients of variation were within acceptable ranges (< 10%). The ELISA inclusion criteria were the age (57 ± 8 years), gender (CG: 49 women and 71 men; ACS: 45 women and 75 men) and clinical spectrum (38 UA, 39 NSTEMI and 43 STEMI).

1.0 (0.4–1.6) 23.7 (21.1–26.3)

0.7 (0.4–1.0) 36.6 (33.4–39.9)

ACS, acute coronary syndrome; CG, control group; CPK: creatine phosphokinase; DM2, diabetes mellitus type 2; FHC, family history of cardiovascular disease; NSTEMI, non-ST segment elevation myocardial infarction; p value for U-Mann–Whitney test or *Fisher exact test; SD, standard deviation; STEMI, ST segment elevation myocardial infarction; UA, unstable angina.

respectively. The male gender was 3.5 times more affected than female. STEMI was the most prevalent type of ACS (69%). A positive history of cardiovascular disease was reported in 43% of the patients. The main risk factor was hypertension in both groups. According to the para-clinical data, only glucose concentration was elevated in both groups (142.7 vs 118.9 mg/dL, ACS and CG respectively). The remainder parameters were within reference values, although more increased in the control group, probably due to therapeutic control in patients. As expected, cardiac markers were increased especially Creatine Phosphokinase (CPK: 902 IU/mL). In addition, we measured IL-1β and TNF-α cytokines in serum of both groups, only TNF-α levels were higher in ACS (36.6 vs 23.7 pg/mL, p < 0.0001).

2.8. Statistical analysis Statistical analysis was performed using SPSS v21.0, Excel 2010 and GraphPad Prism 6.04 (GraphPad Software, CA, USA). The X2 test or Fisher's exact test were used to compare discrete variables and to estimate the Hardy-Weinberg equilibrium. The measure of association was the odds ratio (OR). The analysis of quantitative variables was performed using Mann-Whitney U test and Spearman's correlation test (r). The relative expression was determined by the 2− ΔΔCq and 2− Δcq (Schmittgen and Livak, 2008). In the gene expression and soluble data, outlier identification was performed by non-parametric test evaluated in the CG (Hoaglin and Iglewicz, 1987). In order to analyze LD in multiple tests, the significance value was adjusted using the Bonferroni correction. Bi- and multivariate logistic regression analyses were performed to assess the significance of the relationship between the variables involved (Nick and Campbell, 2007). The significance level was p < 0.05.

3.2. Genetic contribution The −642C > T and 725C > G polymorphisms were in HardyWeinberg equilibrium (HWE) in the CG (p > 0.05). In the ACS group, the genotype frequencies deviate from HWE (p ≤ 0.0006) due it is a selected population; nonetheless this attribute evaluated in cases could be a measure of disease association (Namipashaki et al., 2015). The genetic distribution of the −642C > T polymorphism showed a significant difference between groups (Table 2), in which a protective contribution was attributed to the T allele (OR = 0.716, p = 0.0057), C/T genotype (OR = 0.506, p = 0.0002) and dominant model (OR = 0.546, p < 0.0001). The analysis of the 725C > T polymorphism showed also a protective contribution for the T allele (OR = 0.570, p < 0.0001), C/T (OR = 0.371, p < 0.0001) and T/T (OR = 0.412,

3. Results 3.1. Clinical and demographic characteristics Table 1 shows the clinical and demographic data of both groups. The mean age of ACS and CG was 63 ± 10.9 and 57 ± 8.4 years, 33

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3.3. Gene expression

Table 2 Genotype, allele and haplotype distribution of the −642C > T and 725C > T polymorphisms in the SELL gene by group. SNP

CG n (%)

-642C > T (rs2205849) Genotype C/C 96 (35.16) C/T 135 (49.45) T/T Allele C T p of HWE Dominant model C/C C/T + T/T Recessive model C/C + C/T T/T

OR CI (95%)

P

163 (49.85) 116 (35.47)

− 0.506 (0.355–0.721) 0.673 (0.414–1.093)

− 0.0002

− 0.716 (0.565–0.908)

− 0.0057

42 (15.39)

48 (14.68)

327 (59.89) 219 (40.11)

442 (67.58) 212 (32.42)

0.6285

0.0006

96 (35.16) 177 (64.84)

163 (49.8) 164 (50.2)

− 0.546 (0.392–0.759)

− < 0.0001

279 (85.3) 48 (14.7)

− 0.946 (0.604–1.483)

− 0.8095

146 (45.20) 105 (32.51)

− 0.371 (0.251–0.547) 0.412 (0.268–0.635)

− < 0.0001

The relative expression of the SELL gene was 3.076 times higher in patients with ACS compared to individuals in the CG (Fig. 2a). When comparing the medians with the 2− ΔCq method, we observed a statistically significant difference between ACS and CG (225.5 vs 55.36 relative expression units, REU, p = 0.0009) (Fig. 2b). The assessment of relative mRNA expression of the SELL gene with respect to age, gender, clinical spectrum of ACS, genotypes, genetic models and haplotype did not indicate significant differences (p > 0.05, data not shown).

0.1085

3.4. Soluble levels There were similar sL-selectin levels in ACS and CG (p = 0.2433) (Fig. 3a). There was no association with soluble protein levels according to genotype, genetic models or haplotypes (p ≥ 0.05, data not shown). With respect to the diagnosis of ACS, we observed a trend of increased levels of sL-Selectin in patients with UA compared with NSTEMI or STEMI, however the data did not reach statistical significance (Fig. 3b). Regarding gender, there was a statistically significant difference in the levels of sL-selectin in the CG; the levels were higher in women (3878 vs 3010 ng/mL, p = 0.0001) (Fig. 3c); this finding was not replicated in the ACS group (Fig. 3d). A stratification by myocardial infarction risk age indicated higher levels in individuals under 55 years (CG: 3653 vs. 3158 ng/mL, p = 0.0260; ACS: 3803 vs. 3122 ng/mL, p = 0.0078) (Fig. 3e and f, respectively). With respect to comorbidities, the concentration of sL-selectin was higher in individuals with normal body mass index, BMI (3611 ng/ml) compared with overweight (2607 ng/mL, p = 0.0064) or obese (2723 ng/mL, p = 0.0047) individuals in the CG (Fig. 3g). In the ACS group, in contrast, obese individuals had higher levels of the protein compared with individuals with normal BMI (3498 vs. 2814 ng/mL, p = 0.0190, Fig. 3h). No correlation was found between the relative expression and the levels of sL-selectin (r = 0.2395, p > 0.05, data not shown). Finally, in consideration of the role of TNF-α and IL-1β in the regulation of L-selectin, we conducted a correlation analysis in both study groups. However, these cytokines showed no correlation with sLselectin levels (Fig. 4).

Recessive 231 (84.6) 42 (15.4)

725C > T (rs2229569) Genotype C/C 66 (24.18) C/T 128 (46.89) T/T

ACS n (%)

79 (28.94)

72 (22.29)

< 0.0001

p of HWE Allele C T

0.3204

1.6980 × 10− 8

260 (47.62) 286 (52.38)

397 (61.46) 249 (38.54)

− 0.570 (0.453–0.718)

− < 0.0001

Dominant model C/C C/T + T/T

66 (24.18) 207 (75.82)

146 (45.2) 177 (54.8)

− 0.387 (0.272–0.550)

− < 0.0001

Recessive model C/C + C/T T/T

194 (71.0) 79 (29.0)

251 (77.7) 72 (22.3)

− 0.704 (0.486–1.020)

− 0.0631

Haplotypes CC CT

258 (47.25) 68 (12.45)

388 (60.63) 41 (6.41)

− < 0.0001

TC

2 (0.37)

5 (0.78)

TT

218 (39.93)

206 (32.19)

− 0.401 (0.264–0.609) 1.662 (0.320–8.633) 0.628 (0.491–0.805)

4. Discussion In the last ten years, ACS has been the cause of > 29% of deaths in industrialized countries, making it a leading cause of mortality. The pathogenesis of ACS includes oxidative, inflammatory and thrombotic processes. Adhesion molecules have an important participation in the plaque disruption (Vargas-Alarcón et al., 2011). In the search for predictive factors that can help prevent the development of diseases such as ACS, the identification of genetic variants has gained importance in recent decades. Genome wide studies have identified association of several genes and its variants with common diseases such as myocardial infarction (Dorn and Cresci, 2009; Erdmann et al., 2009; McCarthy et al., 2008). The reported heritability of ACS is higher when both parents are affected, which suggests that genetic research could have implications for clinical practice, from the timely identification of individuals with potential risks to important pharmacogenomic developments (Banerjee et al., 2011).

0.4233* < 0.0001

Abbreviations: ACS, acute coronary syndrome; CG, control group; CI, confidence interval; HWE: Hardy-Weinberg Equilibrium; OR, odds ratio; p value for χ2 or *Fisher's test.

p < 0.0001) genotypes and in the dominant model (OR = 0.387, p < 0.0001) (Table 2). The main risk factors and demographic characteristics of the ACS group were stratified according to the genotypes; no significant differences were found (data not shown). The linkage disequilibrium analysis showed that the alleles of both polymorphisms do not segregate independently (D´ = 0.97, r2 = 0.58 in controls and D´ = 0.95 and r2 = 0.72 in cases, Fig. 1). Subsequently, we compared the haplotype distribution between groups and found a protective effect for CT (OR = 0.4009, p < 0.0001) and TT (OR = 0.6283, p < 0.0001) haplotypes (Table 2).

4.1. Demographic and clinical characteristics The risk factors associated with ACS were overrepresented in our patients compared with the CG, probably due to the inclusion criteria of the latter. Hypertension, DM2 and smoking still remain the main risk factors related with ACS similar to recent reports (Duc Cong and Dung, 34

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a)

2

D´

b)

r

2

D´

r

Fig. 1. Linkage disequilibrium plot of −642C > T (rs2205849) and 725C > T (rs2229569) polymorphisms. Within the squares the D' and r2 percentages are presented in controls (a) and patients (b). The two SNPs were in strong Linkage Disequilibrium in both groups.

with respect to the latter. (Alkhateeb et al., 2013; Thyagarajan et al., 2013). To the best of our knowledge, there are no studies of association of the −642C > T polymorphism in subjects with ACS or any other cardiovascular disease, limiting the possibility of contrast our results. The 725C > T polymorphism also showed a protective effect, since carriers of at least one copy of the T allele (C/C vs T/C + T/T) were 2.58 times less susceptible to ACS. So far there are no reports of the association of this polymorphism with ACS. Wei et al., studied ischemic stroke and reported the following frequencies of the genotypes C/C, C/ T and T/T of this polymorphism: 42.9%, 47.5% and 9.6% in the control group, and 56.2%, 38.5% and 5.3% in cases of ischemic stroke, respectively. They found that carriers of the C allele had a significantly increased risk of ischemic stroke compared to T allele carriers (Wei et al., 2011). In this regard, it is clear that this polymorphic variant has shown a protective effect against the pathologies studied in previous works and this study, but with a different etiological basis. This work showed strong linkage disequilibrium between both

2014). Regarding para-clinical characteristics, the control group has higher levels of lipids than ACS, aspect related with the lowering lipid therapy consumption in the former. Notwithstanding ACS continues leading the list of the first causes of mortality worldwide not surprising since some other factors are related in its genesis. Our results denote that normalization of serum lipids does not allow controlling the disease evolution. 4.2. Genetic contribution In this work, the − 642T was identified as protective against ACS. We found the dominant model to be significant, meaning that only one copy of the T allele is necessary to produce a change in the susceptibility, in other words C/T and T/T carriers have 1.8 times less risk to develop the disease compared with C/C carriers in this population. This polymorphism has been studied in recurrent aphthous stomatitis and IgA-related nephropathy; an association of susceptibility was found 35

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Fig. 2. Relative mRNA expression of the SELL gene in CG and ACS.a) Comparison between the relative expression of the SELL gene of each study group. (2− ΔΔCq method).b) Comparison between the relative expression of the SELL gene of each study group: CG (IQR25–75: 22.54–132.5); ACS (IQR25–75: 67.53–439.7). (2− ΔCq method).Abbreviations: ACS, acute coronary syndrome; CG, control group; IQR, interquartile range; REU, relative expression units. *Calibrating group. The values in parenthesis above the bars represent the minimum and maximum.

expression could be attributed to other neighboring polymorphisms strengthening the gene multi-locus analysis; in this context further studies are needed. In literature, there are no reports that include this analysis in ACS. There is only one work related in IgA nephropathy previously discussed (Takei et al., 2006).

studied loci. This had already been described by a previous report in an Asian population that analyzed three loci including the 1402C > T of E-selectin, −642C > T and 725C > T of SELL polymorphisms. Their results showed a strong association of the haplotype formed by the variants of these polymorphisms and IgA-related nephropathy. In addition, the functional effect of this haplotype was associated with a lower adhesion of Human umbilical vein endothelial cells compared to the wild haplotype; concluding that the presence of the T allele of SNP 725C > T was responsible for this association (Takei et al., 2006). Moreover, we observed two protective haplotypes, indicating that individuals carrying CT and TT haplotypes have 2.5 and 1.6 times lesser risk of developing ACS compared with CC haplotype carriers, respectively. The presence of the T allele in both haplotypes suggests 725C > T might produce the effect; however, we cannot rule out that other nearby polymorphisms could mask the association.

4.4. Soluble levels sL-selectin is produced by the shedding of L-selectin from the membrane by effect of disintegrin and metalloproteinases. There have been many studies on the participation of sL-selectin in cardiovascular diseases, but the results have been highly inconsistent (Berardi et al., 2015). The function of sL-selectin is antagonist to the membrane-bound form, as this form binds to the ligands present on endothelial cells, preventing the binding of leukocytes to those cells (Schleiffenbaum et al., 1992). However, in some studies sL-selectin is considered a protective factor (Albertini et al., 1999; Haught et al., 1996; Patiar et al., 2002) and in others a risk factor (Atalar et al., 2001; Signorelli et al., 2003; Siminiak et al., 1998, 1999; Wei et al., 2011). In the present study, the concentration of sL-selectin was lower in the ACS group compared with CG, but the difference was not statistically significant (3245 vs. 3473 ng/mL). Berardi et al., showed that there is no association between the plasma levels of L-selectin and the incidence of cardiovascular disease, but they found a difference of plasma levels among ethnicity when compared non-Hispanic American whites, Chinese American, African American and Hispanic Americans (Berardi et al., 2014). Our Mexican population has an admixture of Caucasian, Amerindian and to a lesser extent an African component (Rubi-Castellanos et al., 2009), in this sense the genetic heterogeneity could influence the production of the soluble protein rather than pathological status. Our results are consistent with these previous findings, since patients and controls had no significant differences in sL-selectin levels however ethnicity could be important. In this respect, it would be interesting to analyze soluble L-selectin concentration in mestizo and ethnic subgroups all over Mexico country in future studies. The comparison of sL-selectin levels according to the clinical spectrum showed no significant differences; however, the levels of sLselectin decreased with the degree of severity of the disease (UA: 3501; NSTEMI 3402; STEMI: 2828 ng/mL). Similarly, other authors have found that patients with UA showed higher sL-selectin levels compared with the control group and with stable angina (Atalar et al., 2002). Fassbender et al., evaluated the association between various adhesion molecules and acute ischemic stroke, finding that the levels of sLselectin decreased in patients with infarction compared to the control group; they also noted that the concentrations of sL-selectin were significantly lower 72 h after infarction compared with those obtained

4.3. mRNA expression In this study, we found that the relative expression of the SELL gene is three times higher in ACS compared to CG. This is expected, since ACS patients undergo an acute inflammatory process (Mulvihill and Foley, 2002), which could have a significant effect on the expression of the SELL gene due to the participation of pro-inflammatory cytokines such as TNF-α, which regulates the expression of the SELL gene in monocytes and neutrophils (Izycka et al., 2005). The deregulation of the SELL gene expression has been associated with metastasis (Qian et al., 2001), ischemia (Zoldhelyi et al., 2000), autoimmunity and other diseases (Chen et al., 2007; Kretowski and Kinalska, 2000; Ley, 2003; Steeber et al., 1998). Moreover, an increased mRNA expression of the SELL gene has been found in atherosclerosis (Berardi et al., 2015) this is important due this is one of the main triggers of an ACS. No significant differences were found (p > 0.05) when the relative expression of the SELL gene were compared with ACS spectrum. There are no studies evaluating the relative expression of the SELL gene in ACS or in any of the clinical entities that comprise (UA, NSTEMI, and STEMI). As there were no differences between these entities, we hypothesize that the increase in the relative expression of the SELL gene in the ACS group is produced by common factors that triggers the three clinical entities, including cytokines such as TNF-α, IL-6, IL-1β, INF-γ or transcription factors (Akira, 1997; Bouwmeester et al., 2004; Dong et al., 2002; Liacini et al., 2003; Weinreich et al., 2009). Regarding haplotypes, we found no association with the expression of SELL. Due to the biological implications of polymorphisms, we expected a lower expression in TT haplotype carriers; however, no significant difference was found. This can denote that the previously described functional effect of both polymorphisms on L-selectin gene 36

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p=0.2433

6000

p=0.1218

5000

3473

sL-selectin (ng/mL)

3245

4000

2000

3402

4000

2828

3000 2000 1000

0

I ST EM

M I

A U

N

A

C

C S

G

0

ST E

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3501

b)

Study group

p=0.0001

3384

3878

3000 2000

3000 2000 1000

0

0

C S A

C

C

G

G

M

F

1000

c)

M

3010

3146

4000

sL-selectin (ng/mL)

4000

F

sL-selectin (ng/mL)

p=0.1039

5000

C S

5000

Diagnosis

A

a)

d)

Gender by group

Gender by group p=0.0078

p=0.0260

5000 3803

sL-selectin (ng/mL)

3653

sL-selectin (ng/mL)

5000 3158

4000 3000 2000

3122

4000 3000 2000 1000

1000

C S A

A

C

f)

Age

55

<5 5

G

C S

>5 5

<5 5 G C

Age p= 0.0188

p=0.0047 p=0.0064

p=0.2263

5000

5000

3498

2607

sL-selectin (ng/mL)

2723

3000 2000 1000

3195

3000 2000 1000

O

C S

C S

A

A

C

V

N

G

O

C S

B

V G

O

N G C

C

h)

BMI

B

0

0

g)

2814

4000

A

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3611 4000

O

e)

>

0 0

BMI (caption on next page)

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Fig. 3. Comparison of the serum levels of sL-selectina) Comparison of the serum levels of sL-selectin by group: CG (IQR25–75: 2593–4006) and ACS (IQR25–75: 2729–4141).b) Comparison of the serum levels of sL-selectin by type of diagnosis in ACS: UA (IQR25–75: 2707–4265); NSTEMI (IQR25–75: 2814–3961); STEMI (IQR25–75: 2245–3696).c) Comparison of the serum levels of sL-selectin according to gender in the CG: F (IQR25–75: 3233–4261); M (IQR25–75: 2497–3748).d) Comparison of the serum levels of sL-selectin according to gender in the ACS group: F (IQR25–75: 2801–4234); M (IQR25–75: 2429–3826).e) Comparison of the levels of sL-selectin according to age in the CG: < 55 (IQR25–75: 2988–4222); 55 > (IQR25–75: 2560–4090).f) Comparison of the levels of sL-selectin according to age in the ACS group: < 55 (IQR25–75: 3203–4431); 55 > (IQR25–75: 2453–3826).g) Comparison of the levels of sL-selectin according to body mass index in the CG: Normal (IQR25–75: 2987–4224); Overweight (IQR25–75: 2264–3850); Obese (IQR25–75: 2252–3462).h) Comparison of the levels of sL-selectin according to body mass index in the ACS group: Normal (IQR25–75: 2302–3932); Overweight (IQR25–75: 2451–3934); Obese (IQR25–75: 3146–4235).Abbreviations: ACS, acute coronary syndrome; CG, control group; IQR, interquartile range; N, normal weight; NSTEMI, non ST segment elevation myocardial infarction; STEMI, ST segment elevation myocardial infarction; OB, obese; OV, overweight; UA, unstable angina.

production could be similarly influenced. Unfortunately we did not register the menopause age; however the vast majority of women (96 and 93% CG and ACS, respectively) were older than 47 years, the average age of menopause in Mexico (Garrido-Latorre et al., 1996). A better designed study including enough pre and post-menopausal women as well the measurement of L-selectin ligands and the L-selectin sheddase ADAM-17 (a disintegrin and metalloproteinase 17) considering the hormone replacement therapy consumption could answer this hypothesis. Population studies have already noted the relation of age with the concentration of adhesion molecules (Andrýs et al., 2000; Nash et al., 1996; Sack et al., 1998). Age is an important risk factor to ACS (LomaOsorio et al., 2002) thus, we stratified the individuals in both groups as younger or older than 55 years. When comparing the levels of sLselectin in both groups, we observed that individuals older than 55 years had a lower concentration of sL-selectin in both the CG and ACS (p = 0.026). This is similar to that reported by Berardi et al., who found an inverse relationship between sL-selectin levels and age (Berardi et al., 2014). The study by Ponthieux et al., also showed that the sL-selectin levels decrease with age (Ponthieux et al., 2004). The effect of age on soluble L-selectin levels have not yet been elucidated, however it could be explained by immunosenescence where all functions, including lymphoid lineage, are declining (Aw et al., 2007).

at 4, 8, 10 and 24 h (Fassbender et al., 1995). Furthermore, Haught et al., found no significant differences between controls and patients with stable angina, UA and acute myocardial infarction; however, the average concentrations of sL-selectin were lower in patients with stable angina, UA or myocardial infarction compared to the control group (Haught et al., 1996). Thus we can see that the results on this subject, including ours, are quite heterogeneous and that standardized sampling times are needed to make correct interpretations. In our case, sampling was performed between the first and third day after the event; it would be interesting to have a single sampling time in subsequent studies. Some researchers have suggested that sL-selectin levels vary by gender (Ponthieux et al., 2004). In this study, CG women had higher concentrations of sL-selectin than men; however, the differences were not significant in the ACS group, although the levels tended to be higher in women. Similarly, Berardi et al., found increased levels of sL-selectin in women compared to men (Berardi et al., 2014), while Ponthieux et al., reported that there was no variation in the levels of sL-selectin according to gender in adults (Ponthieux et al., 2004). A low grade inflammation could be suggested for our findings. Previous reports indicate an increase in expression or production of adhesion molecules in females at late menopause, such as Intercellular Adhesion Molecule-1 (ICAM-1) and soluble vascular cell adhesion molecule 1 (sVCAM) (Figueroa-Vega et al., 2015). In this context, L-selectin or their ligands

r= 0.105 p= 0.79

r= 0.066 p= 0.65

a

b r= 0.151 p= 0.61

r= 0.003 p= 0.28

d

c

Fig. 4. Correlation between the levels of sTNF-α, sIL-1β and sL-selectina) Correlation between the levels of sTNF-α and the levels of sL-selectin in the CGb) Correlation between the levels of IL-1β and the levels of sL-selectin in the CGc) Correlation of the levels of sTNF-α and the levels of sL-selectin in the ACS groupd) Correlation of the levels of IL-1β and the levels of sLselectin in the ACS groupAbbreviations: ACS, acute coronary syndrome; CG, control group; sIL-1β, interleukin-1 beta; sL-selectin, soluble L-selectin; sTNF-α, soluble tumor necrosis factoralpha.

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expression of L-selectin in ACS compared to CG in a population of Western Mexico.

Together this data confirms that levels of sL-selectin depend on gender and age, but our study showed no evidence of an association between this adhesion molecule and ACS; hence all these factors, including ethnicity, must be taken into account in further analysis regarding this molecule. Regarding the association between sL-selectin levels and comorbidities, individuals with normal BMI showed higher concentrations of the soluble form of the protein compared to overweight and obese individuals in the CG. In the ACS group, obese individuals showed higher levels of the protein compared to individuals with normal BMI. There are few studies that associate sL-selectin levels with obesity; however, similar to the results of the present study, Cottam et al., demonstrated that chronic inflammation in obesity leads to decreased levels of sL-selectin, affecting the activation and migration of neutrophils, depressing the immune response and increasing the propensity to suffer multiple infections (Cottam et al., 2002a, 2002b). Several studies have evaluated the epidemiological data that associate obesity with multiple diseases (Fasol et al., 1992; Lew and Garfinkel, 1979; Miller, 1990; Norris et al., 1990); however, the results on the effects of obesity on the immune response have been contradictory (Nieman et al., 1999; Palmblad et al., 1977, 1979, 1980; Tedder et al., 1995). In this respect, the findings of this study in obese patients with ACS are difficult to interpret due to the presence of two chronic diseases that involve an exacerbated inflammatory response, and also due to the fact that there are several molecules that could alter the endothelial response (Berardi et al., 2014; Głowińska et al., 2004). In addition, the correlation analysis of the relative expression levels of the SELL gene and the soluble protein levels found no correlation (p > 0.05). This result can be explained by considering that only the soluble form of the protein was quantified. There is no knowledge about the levels of membrane form of sL-selectin in patients with ACS, even though it plays an important role in the development of atherosclerosis and could be involved in intracellular signaling (Juliano, 2002). Waddell et al., showed that L-selectin, despite having a small intracellular domain, has the capacity to transmit intracellular signals such as an increase in phosphorylation and the activation of MAP kinases in neutrophils. This can contribute to the activation and adhesion of neutrophils during an inflammatory process (Waddell et al., 1994). This allows us to infer that membrane-bound form has greater significance as a risk factor for the development of ACS; this might explain the lack of correlation between the relative expression levels and the soluble levels, indeed this issue is one of our study group perspectives. Otherwise, it has been established that the maximum correlation between mRNA and its protein is 0.40; it is thus necessary to consider other important aspects in the flow of genetic information, such as posttranscriptional modifications, the average life span of an mRNA, posttranslational and epigenetic modifications (Vogel and Marcotte, 2012). Two of the main cytokines that regulate SELL expression are TNF-α and IL-1β (Sugama et al., 1992). An increase in the circulating levels of these cytokines has been associated with the development of cardiovascular diseases and high mortality (Ferrari, 1999; Harris et al., 1999). For this reason, we analyzed the correlation of the levels of these cytokines with sL-selectin, but the results were not as expected. To date, there are no studies that evaluate the correlation of these proteins in ACS or any other pathology; in this regard, it would be important to study other molecules and ligands involved in the endothelial function. Limitations: one of the main limitations of our study is the sample size in some stratification analysis. In this regard, larger samples sizes are required in order to confirm our findings. In addition, sL-selectin levels could be biased by other factors not considered in this study such as menopause age.

Conflict of interest Authors declare that there is no conflict of interest. Acknowledgements This work was supported by Grant from Fondo Sectorial SSA/IMSS/ ISSSTE-CONACYT-2014-c01-233713 to Valle Y. References Akira, S., 1997. IL-6-regulated transcription factors. Int. J. Biochem. Cell Biol. 29, 1401–1418. Albertini, J.P., Valensi, P., Lormeau, B., Vaysse, J., Attali, J.R., Gattegno, L., 1999. Soluble L-selectin level is a marker for coronary artery disease in type 2 diabetic patients. Diabetes Care 22, 2044–2048. Alkhateeb, A., Karasneh, J., Abbadi, H., Hassan, A., Thornhill, M., 2013. Association of cell adhesion molecule gene polymorphisms with recurrent aphthous stomatitis. J. Oral Pathol. Med. Off. Publ. Int. Assoc. Oral Pathol. Am. Acad. Oral Pathol. 42, 741–746. http://dx.doi.org/10.1111/jop.12100. Andrýs, C., Pozler, O., Krejsek, J., Derner, V., Drahosová, M., Kopecký, O., 2000. Serum soluble adhesion molecules (sICAM-1, sVCAM-1 and sE-selectin) in healthy school aged children and adults. Acta Medica Hradec Král. Univ. Carol. Fac. Medica Hradec Král. 43, 103–106. Atalar, E., Aytemir, K., Haznedaroğlu, I., Ozer, N., Ovünç, K., Aksöyek, S., Kes, S., Kirazli, S., Ozmen, F., 2001. Increased plasma levels of soluble selectins in patients with unstable angina. Int. J. Cardiol. 78, 69–73. Atalar, E., Ozmen, F., Haznedaroglu, I., Açil, T., Ozer, N., Ovünç, K., Aksöyek, S., Kes, S., 2002. Effects of short-term atorvastatin treatment on global fibrinolytic capacity, and sL-selectin and sFas levels in hyperlipidemic patients with coronary artery disease. Int. J. Cardiol. 84, 227–231. Aw, D., Silva, A.B., Palmer, D.B., 2007. Immunosenescence: emerging challenges for an ageing population. Immunology 120, 435–446. http://dx.doi.org/10.1111/j.13652567.2007.02555.x. Banerjee, A., Silver, L.E., Heneghan, C., Welch, S.J.V., Mehta, Z., Banning, A.P., Rothwell, P.M., 2011. Relative familial clustering of cerebral versus coronary ischemic events. Circ. Cardiovasc. Genet. 4, 390–396. http://dx.doi.org/10.1161/CIRCGENETICS. 110.959114. Berardi, C., Decker, P.A., Kirsch, P.S., de Andrade, M., Tsai, M.Y., Pankow, J.S., Sale, M.M., Sicotte, H., Tang, W., Hanson, N., Polak, J.F., Bielinski, S.J., 2014. Plasma and serum L-selectin and clinical and subclinical cardiovascular disease: the multi-ethnic study of atherosclerosis (MESA). Transl. Res. J. Lab. Clin. Med. 163, 585–592. http:// dx.doi.org/10.1016/j.trsl.2014.02.001. Berardi, C., Larson, N.B., Decker, P.A., Wassel, C.L., Kirsch, P.S., Pankow, J.S., Sale, M.M., Andrade, M. de, Sicotte, H., Tang, W., Hanson, N.Q., Tsai, M.Y., Chen, Y.-D.I., Bielinski, S.J., 2015. Multi-ethnic analysis reveals soluble l-selectin may be posttranscriptionally regulated by 3′UTR polymorphism: the multi-ethnic study of atherosclerosis (MESA). Hum. Genet. 134, 393–403. http://dx.doi.org/10.1007/ s00439-014-1527-0. Berlin, C., Bargatze, R.F., Campbell, J.J., von Andrian, U.H., Szabo, M.C., Hasslen, S.R., Nelson, R.D., Berg, E.L., Erlandsen, S.L., Butcher, E.C., 1995. Alpha 4 integrins mediate lymphocyte attachment and rolling under physiologic flow. Cell 80, 413–422. Blann, A.D., Amiral, J., Mccollum, C.N., 1996. Circulating endothelial cell/leucocyte adhesion molecules in ischaemic heart disease. Br. J. Haematol. 95, 263–265. http:// dx.doi.org/10.1046/j.1365-2141.1996.d01-1921.x. Bouwmeester, T., Bauch, A., Ruffner, H., Angrand, P.-O., Bergamini, G., Croughton, K., Cruciat, C., Eberhard, D., Gagneur, J., Ghidelli, S., Hopf, C., Huhse, B., Mangano, R., Michon, A.-M., Schirle, M., Schlegl, J., Schwab, M., Stein, M.A., Bauer, A., Casari, G., Drewes, G., Gavin, A.-C., Jackson, D.B., Joberty, G., Neubauer, G., Rick, J., Kuster, B., Superti-Furga, G., 2004. A physical and functional map of the human TNF-alpha/NFkappa B signal transduction pathway. Nat. Cell Biol. 6, 97–105. http://dx.doi.org/10. 1038/ncb1086. Cannon, C.P., Brindis, R.G., Chaitman, B.R., Cohen, D.J., Cross, J.T., Drozda, J.P., Fesmire, F.M., Fintel, D.J., Fonarow, G.C., Fox, K.A., Gray, D.T., Harrington, R.A., Hicks, K.A., Hollander, J.E., Krumholz, H., Labarthe, D.R., Long, J.B., Mascette, A.M., Meyer, C., Peterson, E.D., Radford, M.J., Roe, M.T., Richmann, J.B., Selker, H.P., Shahian, D.M., Shaw, R.E., Sprenger, S., Swor, R., Underberg, J.A., Van de Werf, F., Weiner, B.H., Weintraub, W.S., 2013. 2013 ACCF/AHA key data elements and definitions for measuring the clinical management and outcomes of patients with acute coronary syndromes and coronary artery disease: a report of the American College of Cardiology Foundation/American Heart Association task force on clinical data standards (writing committee to develop acute coronary syndromes and coronary artery disease clinical data standards). J. Am. Coll. Cardiol. 61, 992–1025. http://dx.doi.org/10.1016/j.jacc.2012.10.005. Chen, H.-Y., Cui, B., Wang, S., Zhao, Z.-F., Sun, H., Zhao, Y.-J., Li, X.-Y., Ning, G., 2007. Lselectin gene polymorphisms in Graves' disease. Clin. Endocrinol. 67, 145–151. http://dx.doi.org/10.1111/j.1365-2265.2007.02852.x.

5. Conclusion The polymorphisms −642C > T and 725C > T of the SELL gene are protective factors for the development of ACS. There is an increased 39

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Leiva-Pons, J.L., 2009. Management of acute coronary syndromes in Mexico: gaps and opportunities to improve outcomes. Am. J. Cardiovasc. Drugs Drugs Devices Interv. 9, 143–148. Lew, E.A., Garfinkel, L., 1979. Variations in mortality by weight among 750,000 men and women. J. Chronic Dis. 32, 563–576. Ley, K., 2003. The role of selectins in inflammation and disease. Trends Mol. Med. 9, 263–268. Liacini, A., Sylvester, J., Li, W.Q., Huang, W., Dehnade, F., Ahmad, M., Zafarullah, M., 2003. Induction of matrix metalloproteinase-13 gene expression by TNF-alpha is mediated by MAP kinases, AP-1, and NF-kappaB transcription factors in articular chondrocytes. Exp. Cell Res. 288, 208–217. Libby, P., 2002. Inflammation in atherosclerosis. Nature 420, 868–874. http://dx.doi. org/10.1038/nature01323. Livak, K.J., Schmittgen, T.D., 2001. Analysis of relative gene expression data using realtime quantitative PCR and the 2(− Delta Delta C(T)) method. Methods San Diego Calif. 25, 402–408. http://dx.doi.org/10.1006/meth.2001.1262. Loma-Osorio, A., García-Castrillo, L., Arós, F., Lopetegui, P., Recuerda, E., Epelde, F., Investigadores del estudio EVICURE, 2002. Role of emergency departments in acute myocardial infarction care. EVICURE study. Rev. Esp. Cardiol. 55, 1098–1100. McCarthy, M.I., Abecasis, G.R., Cardon, L.R., Goldstein, D.B., Little, J., Ioannidis, J.P.A., Hirschhorn, J.N., 2008. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat. Rev. Genet. 9, 356–369. http://dx.doi. org/10.1038/nrg2344. Miller, A.B., 1990. Diet and cancer. A review. Acta Oncol. Stockh. Swed. 29, 87–95. Miller, S.A., Dykes, D.D., Polesky, H.F., 1988. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res. 16, 1215. Mulvihill, N.T., Foley, J.B., 2002. Inflammation in acute coronary syndromes. Heart 87, 201–204. http://dx.doi.org/10.1136/heart.87.3.201. Namipashaki, A., Razaghi-Moghadam, Z., Ansari-Pour, N., 2015. The essentiality of reporting Hardy-Weinberg equilibrium calculations in population-based genetic association studies. Cell J. 17, 187–192. Nash, M.C., Wade, A.M., Shah, V., Dillon, M.J., 1996. Normal levels of soluble E-selectin, soluble intercellular adhesion molecule-1 (sICAM-1), and soluble vascular cell adhesion molecule-1 (sVCAM-1) decrease with age. Clin. Exp. Immunol. 103, 167–170. Nick, T.G., Campbell, K.M., 2007. Logistic regression. Methods Mol. Biol. Clifton NJ 404, 273–301. http://dx.doi.org/10.1007/978-1-59745-530-5_14. Nieman, D.C., Henson, D.A., Nehlsen-Cannarella, S.L., Ekkens, M., Utter, A.C., Butterworth, D.E., Fagoaga, O.R., 1999. Influence of obesity on immune function. J. Am. Diet. Assoc. 99, 294–299. http://dx.doi.org/10.1016/S0002-8223(99)00077-2. Norris, S.O., Provo, B., Stotts, N.A., 1990. Physiology of wound healing and risk factors that impede the healing process. AACN Clin. Issues Crit. Care Nurs. 1, 545–552. Palmblad, J., Hallberg, D., Engstedt, L., 1980. Polymorphonuclear (PMN) function after small intestinal shunt operation for morbid obesity. Br. J. Haematol. 44, 101–108. Palmblad, J., Hallberg, D., Rössner, S., 1977. Obesity, plasma lipids and polymorphonuclear (PMN) granulocyte functions. Scand. J. Haematol. 19, 293–303. Palmblad, J., Rössner, S., Uden, A.M., 1979. Granulocyte functions during treatment of obesity. Int. J. Obes. 3, 119–122. Patiar, S., Slade, D., Kirkpatrick, U., McCollum, C.N., 2002. Smoking causes a dosedependent increase in granulocyte-bound L-selectin. Thromb. Res. 106, 1–6. Ponthieux, A., Herbeth, B., Droesch, S., Haddy, N., Lambert, D., Visvikis, S., 2004. Biological determinants of serum ICAM-1, E-selectin, P-selectin and L-selectin levels in healthy subjects: the Stanislas study. Atherosclerosis 172, 299–308. http://dx.doi. org/10.1016/j.atherosclerosis.2003.11.003. Qian, F., Hanahan, D., Weissman, I.L., 2001. L-selectin can facilitate metastasis to lymph nodes in a transgenic mouse model of carcinogenesis. Proc. Natl. Acad. Sci. U. S. A. 98, 3976–3981. http://dx.doi.org/10.1073/pnas.061633698. Ross, R., 1999. Atherosclerosis–an inflammatory disease. N. Engl. J. Med. 340, 115–126. http://dx.doi.org/10.1056/NEJM199901143400207. Rubi-Castellanos, R., Martínez-Cortés, G., Muñoz-Valle, J.F., González-Martín, A., CerdaFlores, R.M., Anaya-Palafox, M., Rangel-Villalobos, H., 2009. Pre-Hispanic Mesoamerican demography approximates the present-day ancestry of mestizos throughout the territory of Mexico. Am. J. Phys. Anthropol. 139, 284–294. http://dx. doi.org/10.1002/ajpa.20980. Sack, U., Burkhardt, U., Borte, M., Schädlich, H., Berg, K., Emmrich, F., 1998. Agedependent levels of select immunological mediators in sera of healthy children. Clin. Diagn. Lab. Immunol. 5, 28–32. Schleiffenbaum, B., Spertini, O., Tedder, T.F., 1992. Soluble L-selectin is present in human plasma at high levels and retains functional activity. J. Cell Biol. 119, 229–238. Schmittgen, T.D., Livak, K.J., 2008. Analyzing real-time PCR data by the comparative C(T) method. Nat. Protoc. 3, 1101–1108. Signorelli, S.S., Mazzarino, M.C., Di Pino, L., Malaponte, G., Porto, C., Pennisi, G., Marchese, G., Costa, M.P., Digrandi, D., Celotta, G., Virgilio, V., 2003. High circulating levels of cytokines (IL-6 and TNFalpha), adhesion molecules (VCAM-1 and ICAM-1) and selectins in patients with peripheral arterial disease at rest and after a treadmill test. Vasc. Med. Lond. Engl. 8, 15–19. Siminiak, T., Smielecki, J., Dye, J.F., Baliñski, M., El-Gendi, H., Wysocki, H., Sheridan, D.J., 1998. Increased release of the soluble form of the adhesion molecules L-selectin and ICAM-1 but not E-selectin during attacks of angina pectoris. Heart Vessel. 13, 189–194. Siminiak, T., Smielecki, J., Rzeźniczak, J., Kaźmierczak, M., Kalawski, R., Wysocki, H., 1999. The effects of dipyridamole stress test on plasma levels of soluble adhesion molecules intracellular adhesion molecule-1, vascular cell adhesion molecule-1, Eselectin and L-selectin in patients with ischemic heart disease and patients with syndrome X. Coron. Artery Dis. 10, 235–240. Steeber, D.A., Campbell, M.A., Basit, A., Ley, K., Tedder, T.F., 1998. Optimal selectin-

Chomczynski, P., Sacchi, N., 1987. Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction. Anal. Biochem. 162, 156–159. http://dx.doi.org/10.1006/abio.1987.9999. Cottam, D.R., Schaefer, P.A., Fahmy, D., Shaftan, G.W., Angus, L.D.G., 2002a. The effect of obesity on neutrophil fc receptors and adhesion molecules (CD16, CD11b, CD62L). Obes. Surg. 12, 230–235. http://dx.doi.org/10.1381/096089202762552674. Cottam, D.R., Schaefer, P.A., Shaftan, G.W., Velcu, L., Angus, L.D.G., 2002b. Effect of surgically-induced weight loss on leukocyte indicators of chronic inflammation in morbid obesity. Obes. Surg. 12, 335–342. Derzbach, L., Bokodi, G., Treszl, A., Vásárhelyi, B., Nobilis, A., Rigó, J., 2006. Selectin polymorphisms and perinatal morbidity in low-birthweight infants. Acta Paediatr. Oslo Nor. 1992 (95), 1213–1217. http://dx.doi.org/10.1080/08035250600575404. Domínguez Franco, A.J., Pérez Caravante, M., Jiménez Navarro, M.F., de Teresa Galván, E., 2006. Prevención y tratamiento del síndrome coronario agudo. Rev. Esp. Cardiol. Supl. 6, 36G–45G. http://dx.doi.org/10.1016/S1131-3587(06)75327-4. Dong, C., Davis, R.J., Flavell, R.A., 2002. MAP kinases in the immune response. Annu. Rev. Immunol. 20, 55–72. http://dx.doi.org/10.1146/annurev.immunol.20.091301. 131133. Dorn, G.W., Cresci, S., 2009. Genome-wide association studies of coronary artery disease and heart failure: where are we going? Pharmacogenomics 10, 213–223. http://dx. doi.org/10.2217/14622416.10.2.213. Duc Cong, N., Dung, H.T., 2014. The risk factors of acute coronary syndrome in patients over 65 years old at thong Nhat Hospital of Ho Chi Minh City, Vietnam. J. Atheroscler. Thromb. 21 (Suppl. 1), S36–S41. Erdmann, J., Grosshennig, A., Braund, P.S., König, I.R., Hengstenberg, C., Hall, A.S., Linsel-Nitschke, P., Kathiresan, S., Wright, B., Trégouët, D.-A., Cambien, F., Bruse, P., Aherrahrou, Z., Wagner, A.K., Stark, K., Schwartz, S.M., Salomaa, V., Elosua, R., Melander, O., Voight, B.F., O'Donnell, C.J., Peltonen, L., Siscovick, D.S., Altshuler, D., Merlini, P.A., Peyvandi, F., Bernardinelli, L., Ardissino, D., Schillert, A., Blankenberg, S., Zeller, T., Wild, P., Schwarz, D.F., Tiret, L., Perret, C., Schreiber, S., El Mokhtari, N.E., Schäfer, A., März, W., Renner, W., Bugert, P., Klüter, H., Schrezenmeir, J., Rubin, D., Ball, S.G., Balmforth, A.J., Wichmann, H.-E., Meitinger, T., Fischer, M., Meisinger, C., Baumert, J., Peters, A., Ouwehand, W.H., Italian Atherosclerosis, Thrombosis, and Vascular Biology Working Group, Myocardial Infarction Genetics Consortium, Wellcome Trust Case Control Consortium, Cardiogenics Consortium, Deloukas, P., Thompson, J.R., Ziegler, A., Samani, N.J., Schunkert, H., 2009. New susceptibility locus for coronary artery disease on chromosome 3q22.3. Nat. Genet. 41, 280–282. http://dx.doi.org/10.1038/ng.307. Fasol, R., Schindler, M., Schumacher, B., Schlaudraff, K., Hannes, W., Seitelberger, R., Schlosser, V., 1992. The influence of obesity on perioperative morbidity: retrospective study of 502 aortocoronary bypass operations. Thorac. Cardiovasc. Surg. 40, 126–129. http://dx.doi.org/10.1055/s-2007-1020129. Fassbender, K., Mössner, R., Motsch, L., Kischka, U., Grau, A., Hennerici, M., 1995. Circulating selectin- and immunoglobulin-type adhesion molecules in acute ischemic stroke. Stroke J. Cereb. Circ. 26, 1361–1364. Ferrari, R., 1999. The role of TNF in cardiovascular disease. Pharmacol. Res. Off. J. Ital. Pharmacol. Soc. 40, 97–105. http://dx.doi.org/10.1006/phrs.1998.0463. Figueroa-Vega, N., Moreno-Frías, C., Malacara, J.M., 2015. Alterations in adhesion molecules, pro-inflammatory cytokines and cell-derived microparticles contribute to intima-media thickness and symptoms in postmenopausal women. PLoS One 10, e0120990. http://dx.doi.org/10.1371/journal.pone.0120990. Garrido-Latorre, F., Lazcano-Ponce, E.C., López-Carrillo, L., Hernández-Avila, M., 1996. Age of natural menopause among women in Mexico City. Int. J. Gynaecol. Obstet. Off. Organ Int. Fed. Gynaecol. Obstet. 53, 159–166. Głowińska, B., Urban, M., Peczyńska, J., Florys, B., 2004. Selectins in the pathogenesis and diagnosis of early atherosclerotic changes in children and adolescents with risk factors (obesity, hypertension and diabetes). Przegl. Lek. 61, 935–939. Harris, T.B., Ferrucci, L., Tracy, R.P., Corti, M.C., Wacholder, S., Ettinger, W.H., Heimovitz, H., Cohen, H.J., Wallace, R., 1999. Associations of elevated interleukin-6 and C-reactive protein levels with mortality in the elderly. Am. J. Med. 106, 506–512. Haught, W.H., Mansour, M., Rothlein, R., Kishimoto, T.K., Mainolfi, E.A., Hendricks, J.B., Hendricks, C., Mehta, J.L., 1996. Alterations in circulating intercellular adhesion molecule-1 and L-selectin: further evidence for chronic inflammation in ischemic heart disease. Am. Heart J. 132, 1–8. Hoaglin, D.C., Iglewicz, B., 1987. Fine-Tuning Some Resistant Rules for Outlier Labeling. J. Am. Stat. Assoc. 82, 1147–1149. http://dx.doi.org/10.1080/01621459.1987. 10478551. Iida, A., Nakamura, Y., 2003. High-resolution SNP map in the 55-kb region containing the selectin gene family on chromosome 1q24-q25. J. Hum. Genet. 48, 150–154. http:// dx.doi.org/10.1007/s100380300023. Izycka, A., Jabłońska, E., Izycki, T., Chyczewska, E., 2005. Expression of L-selectin on the surface of neutrophils stimulated by TNF-alpha and level of sL-selectin in serum of patients with lung cancer. Pol. Merkur. Lek. Organ Pol. Tow. Lek. 18, 62–65. Juliano, R.L., 2002. Signal transduction by cell adhesion receptors and the cytoskeleton: functions of integrins, cadherins, selectins, and immunoglobulin-superfamily members. Annu. Rev. Pharmacol. Toxicol. 42, 283–323. http://dx.doi.org/10.1146/ annurev.pharmtox.42.090401.151133. Kadono, T., Venturi, G.M., Steeber, D.A., Tedder, T.F., 2002. Leukocyte rolling velocities and migration are optimized by cooperative L-selectin and intercellular adhesion molecule-1 functions. J. Immunol. Baltim. Md 1950 (169), 4542–4550. Kamiuchi, K., Hasegawa, G., Obayashi, H., Kitamura, A., Ishii, M., Yano, M., Kanatsuna, T., Yoshikawa, T., Nakamura, N., 2002. Leukocyte-endothelial cell adhesion molecule 1 (LECAM-1) polymorphism is associated with diabetic nephropathy in type 2 diabetes mellitus. J. Diabetes Complicat. 16, 333–337. Kretowski, A., Kinalska, I., 2000. L-selectin gene T668C mutation in type 1 diabetes patients and their first degree relatives. Immunol. Lett. 74, 225–228.

40

Gene 625 (2017) 31–41

E. Sandoval-Pinto et al.

org/10.1038/nrg3185. Waddell, T.K., Fialkow, L., Chan, C.K., Kishimoto, T.K., Downey, G.P., 1994. Potentiation of the oxidative burst of human neutrophils. A signaling role for L-selectin. J. Biol. Chem. 269, 18485–18491. Weinreich, M.A., Takada, K., Skon, C., Reiner, S.L., Jameson, S.C., Hogquist, K.A., 2009. KLF2 transcription-factor deficiency in T cells results in unrestrained cytokine production and upregulation of bystander chemokine receptors. Immunity 31, 122–130. http://dx.doi.org/10.1016/j.immuni.2009.05.011. Wei, Y.-S., Lan, Y., Meng, L.-Q., Nong, L.-G., 2011. The association of L-selectin polymorphisms with L-selectin serum levels and risk of ischemic stroke. J. Thromb. Thrombolysis 32, 110–115. http://dx.doi.org/10.1007/s11239-011-0587-4. Wilkening, S., Bader, A., 2004. Quantitative real-time polymerase chain reaction: methodical analysis and mathematical model. J. Biomol. Tech. JBT 15, 107–111. Xia, Z., Li, Y., Ming, K., Xiong, X., 2007. Association of L-selectin gene polymorphism with susceptibility to coronary heart disease. Zhonghua Yi Xue Yi Chuan Xue Za Zhi Zhonghua Yixue Yichuanxue Zazhi Chin. J. Med. Genet. 24, 173–176. Zoldhelyi, P., Beck, P.J., Bjercke, R.J., Ober, J.C., Hu, X., McNatt, J.M., Akhtar, S., Ahmed, M., Clubb, F.J., Chen, Z.Q., Dixon, R.A., Yeh, E.T., Willerson, J.T., 2000. Inhibition of coronary thrombosis and local inflammation by a noncarbohydrate selectin inhibitor. Am. J. Physiol. Heart Circ. Physiol. 279, H3065–H3075.

mediated rolling of leukocytes during inflammation in vivo requires intercellular adhesion molecule-1 expression. Proc. Natl. Acad. Sci. 95, 7562–7567. Sugama, Y., Tiruppathi, C., Offakidevi, K., Andersen, T.T., Fenton, J.W., Malik, A.B., 1992. Thrombin-induced expression of endothelial P-selectin and intercellular adhesion molecule-1: a mechanism for stabilizing neutrophil adhesion. J. Cell Biol. 119, 935–944. Takei, T., Hiraoka, M., Nitta, K., Uchida, K., Deushi, M., Yu, T., Nitta, N., Tsuchiya, K., Yumura, W., Nihei, H., Nakamura, Y., Yoshida, M., 2006. Functional impact of IgA nephropathy-associated selectin gene haplotype on leukocyte-endothelial interaction. Immunogenetics 58, 355–361. http://dx.doi.org/10.1007/s00251-006-0120-7. Tedder, T.F., Steeber, D.A., Pizcueta, P., 1995. L-selectin-deficient mice have impaired leukocyte recruitment into inflammatory sites. J. Exp. Med. 181, 2259–2264. Thyagarajan, B., Jackson, S., Basu, S., Jacobson, P., Gross, M.D., Weisdorf, D.J., Arora, M., 2013. Association between genetic variants in adhesion molecules and outcomes after hematopoietic cell transplants. Int. J. Immunogenet. 40, 108–115. http://dx.doi.org/ 10.1111/j.1744-313X.2012.01131.x. Vargas-Alarcón, G., Fragoso, J.M., Delgadillo, H., 2011. Acute coronary syndrome. Physiopathology and genetics. Rev. Investig. Clínica Organo Hosp. Enfermedades Nutr. 63, 64–74. Vogel, C., Marcotte, E.M., 2012. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat. Rev. Genet. 13, 227–232. http://dx.doi.

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