Background
Multiple sclerosis (MS) is a chronic inflammatory demyelinating disorder with axonal degeneration of the central nervous system. Although the etiology of MS is not well understood, the interplay of both genetic and environmental factors is the most likely hypothesis [
1‐
5]. With regard to the role of genetic factors, genome-wide association studies (GWAS) have confirmed more than 100 loci with genome-wide significance [
6‐
8]. According to the most recent GWAS, approximately 22% of signals overlapped at least one other autoimmune disease signal [
8], However, all loci except HLA showed modest odds-ratio (OR) in the range of 1.1-1.3 [
9]. In particular the association between MS and the
HLA-DRB1*15:01 haplotype has been shown to be strong.
A number or reports have suggested a possible role of oxidative stress and lipid peroxidation in the inflammatory processes and in the pathogenesis of MS [
10‐
40]. Reactive oxygen species (ROS) generated in excess primarily by macrophages and microglia, have been implicated as mediators of demyelination and axonal damage [
10]. The main results of studies on oxidative stress markers in the brain, spinal cord, and CSF, both in MS patients and in experimental autoimmune encephalomyelitis (EAE) are summarized in a table included as an Additional file
1: Table S1.
NAD(P)H dehydrogenase, quinone 1 (NQO1) is a phase II detoxification enzyme that catalyzes the one-electron reduction of endogenous and exogenous quinones, preventing their participation in redox cycling and subsequent generation of reactive oxygen species. This enzyme is encoded by the
NQO1 gene (chromosome 16q22.1, Gene Identity 1728) (link
http://www.ncbi.nlm.nih.gov/gene/1728). The enzymatic activity of NQO1 depends fundamentally on a single nucleotide polymorphism (SNP) at the NQO1 locus, rs1800566 (C609T), which produces a proline-to-serine substitution at amino acid 187 (P187S) (link
http://www.ncbi.nih.gov/pubmed/9000600). Individuals with rs1800566TT genotype completely lack NQO1 activity, whereas those with rs1800566C/T genotype present approximately threefold decreased enzyme activity [
41].
Although
NQO1 polymorphisms are not mentioned among the possible susceptibility genes in GWAS studies, the possible role of oxidative stress in the pathogenesis of MS makes it reasonable to analyse the possible relationship between
NQO1 gene polymorphisms and the risk of MS. Moreover, NQO1 has been found to be markedly up-regulated in active demyelinating MS lesions [
13,
14] Stavropoulou et al. [
42], in a case–control association study involving 231 MS patients and 380 controls, reported an association between the rs1800566CT and TT genotypes and the risk of developing MS, and a higher incidence of rs1800566CT genotype in patients with primary progressive MS. The aim of the present study was to replicate the findings by Stavropoulou et al. [
42] in the Spanish population.
Results
The frequencies of
NQO1 rs1800566 genotypes and allelic variants in patients diagnosed with MS did not differ from those of controls (Table
2). The genotype and allele frequencies in MS patients and healthy subjects were in Hardy-Weinberg’s equilibrium. Mean age at onset of MS did not differ significantly between patients carrying
NQO1 rs1800566 C/C (mean ± SD = 32.1 ± 10.2 years, reference), C/T (mean ± SD = 33.5 ± 11.6 years, p = 0.220) and T/T (mean ± SD = 32.4 ± 12.0 years, p = 0.270). Association between the rs1800566 variant and MS risk was not observed when analyzing gender separately (Table
2). The distribution of the
NQO1 rs1800566 genotype and allelic frequencies did not differ between each MS clinical evolutive type and controls (Table
3) or in the severity scores: Expanded Disability Status Score or EDSS (p = 0.508 and p = 0.370 for heterozygous and homozygous carriers of the minor allele, respectively, as compared with homozygous carriers of the major allele) or progression index (p = 0.872 and p = 0.673 for heterozygous and homozygous carriers of the minor allele, respectively, as compared with homozygous carriers of the major allele).
Table 2
NQO1 rs1800566
genotype and allelic variants of patients with multiple sclerosis (MS) and healthy volunteers
rs1800566 GENOTYPE C/C | 178 (61.4, 55.8-67.0) | 195 (62.9, 57.5-68.3) | Reference | 120 (60.0, 53.2-66.8) | 134 (62.9, 56.4-69.4) | Reference | 58 (64.4, 54.6-74.3) | 61 (62.9, 53.3-72.5) | Reference |
C/T | 99 (34.1, 28.7-39.6) | 104 (33.5, 28.3-38.8) | 1.43 (0.74-1.47), 0.810 | 72 (36.0, 29.3-42.7) | 72 (33.8, 27.5-40.2) | 1.12 (0.74-1.68), 0.597 | 27 (30.0, 20.5-39.5) | 32 (33.0, 23.6-42.3) | 0.88 (0.48-1.66), 0.708 |
T/T | 13 (4.5, 2.1-6.9) | 11 (3.5, 1.5-5.6) | 1.30 (0.57-2.96), 0.540 | 8 (4.0, 1.3-6.7) | 7 (3.3, 0.9-5.7) | 1.28 (0.45-3.63), 0.646 | 5 (5.6, 0.8-10.3) | 4 (4.1, 0.2-8.1) | 1.32 (0.34-5.14), 0.693 |
Total | 290 | 310 | | 200 | 213 | | 90 | 97 | |
Allele C | 455 (78.4, 75.1-81.8) | 494 (79.7, 76.5-82.8) | Reference | 312 (78.0, 73.9-82.1) | 340 (79.8, 76.0-83.6) | Reference | 143 (79.4, 73.5-85.3) | 154 (79.4, 73.7-85.1) | Reference |
Allele T | 125 (21.6, 18.2-24.9) | 126 (20.3, 17.2-23.5) | 1.08 (0.82-1.42), 0.601 | 88 (22.0, 17.9-26.1) | 86 (20.2, 16.4-24.0) | 1.12 (0.80-1.56), 0.523 | 37 (20.6, 14.7-26.5) | 40 (20.6, 14.9-26.3) | 1.00 (0.60-1.65), 0.988 |
Total alleles | 580 | 620 | | 400 | 426 | | 180 | 194 | |
Table 3
NQO1 rs1800566
genotype and allelic variants in patients with multiple sclerosis (MS), and relation with the clinical evolutive type of MS
rs1800566 GENOTYPE C/C | 153 (61.9; 55.9-68.0) | Reference | 25 (58.1, 43.4-72.9) | Reference | 195 (62.9, 57.5-68.3) |
C/T | 85 (34.4; 28.5-40.3) | 1.04 (0.72-1.51); 0.822 | 14 (32.6, 18.6-46.6) | 1.05 (0.52-2.11), 0.891 | 104 (33.5, 28.3-38.8) |
T/T | 9 (3.6; 1.3-6.0) | 1.04 (0.39-2.79); 0.928 | 4 (9.3, 0.6-18.0) | 2.84 (0.84-9.59), 0.081 | 11 (3.5, 1.5-5.6) |
Total | 247 | | 43 | | 310 |
Allele C | 391 (79.1; 75.6-82.7) | Reference | 64 (74.4, 65.2-83.6) | Reference | 494 (79.7, 76.5-82.8) |
Allele T | 103 (20.9; 17.3-24.4) | 1.03 (0.76-1.40); 0.829 | 22 (25.6, 16.4-34.8) | 1.35 (0.80-2.27), 0.262 | 126 (20.3, 17.2-23.5) |
Total alleles | 494 | | 86 | | 620 |
Discussion
In contrast with the findings in the study by Stavropoulou et al. [
42], we did not find significant differences either in the frequencies of rs1800566 genotypes, or in the frequencies of the allelic variants of this polymorphism in patients with MS when compared with healthy controls. In addition, rs1800566 polymorphism was neither associated with age at onset of MS, nor with clinical type of MS. Patient sample size and statistical power are higher in our study than in the study by Stavropoulou et al. [
42].
A possible reason for the discrepancies between the study by Stavropoulou et al. [
42] and the present one is the fact that the genotype distribution in the control group of the Stavropoulou et al. [
42] study was in Hardy-Weinberg’s disequilibrium (Pearson’s p = 0.0086). The Hardy-Weinberg’s disequilibrium was attributable to the female control group of the study by Stavropoulou et al. [
42]. Another putative difference is that in the study by Stavropoulou et al. [
42] the genotyping analysis was carried out by using qPCR melting curves, whereas in our study TaqMan genotyping was used.
The present study has some limitations. First, the size of the analyzed cohorts may not be sufficient for strict conclusions about the role of NQO1in MS (though adequate to detect an OR as small as 1.5, a more modest association would not be detected). Secondly, because the cohort study included MS patients with different degrees of severity, it is not adequate for the investigation of the influence of NQO1 genotypes on disability or severity of MS. The ideal study for this purpose should be prospective, including the genotyping of patients with a recent diagnosis of MS and a re-examination of the same patient cohort after similar long-term follow-up periods to establish evolutive type).
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Competing interest
The authors declare that they have no competing interests.
Authors’ contributions
JAGA participated in the conception and design of the study, acquisition of data, analysis and interpretation of data, drafting of the manuscript, critical revision of the manuscript, administrative, technical, and material support, supervision, and obtaining funding. EGM participated in the conception and design of the study, acquisition of data, analysis and interpretation of data, drafting of the manuscript, critical revision of the manuscript, administrative, technical, and material support, supervision, and obtaining funding. CM participated in acquisition of data, analysis and interpretation of data, critical revision of the manuscript, administrative, technical, and material support. JBL participated in acquisition of data, and critical revision of the manuscript. JMP participated in acquisition of data, and critical revision of the manuscript. PC participated in acquisition of data, and critical revision of the manuscript. MDS participated in acquisition of data, and critical revision of the manuscript. DP participated in acquisition of data, and critical revision of the manuscript. LTF participated in acquisition of data, and critical revision of the manuscript. HAN participated in acquisition of data, analysis and interpretation of data, critical revision of the manuscript, administrative, technical, and material support. LAP participated in acquisition of data, and critical revision of the manuscript. DT participated in acquisition of data, and critical revision of the manuscript. JFPN participated in acquisition of data, and critical revision of the manuscript. FJJJ participated in the conception and design of the study, acquisition of data, analysis and interpretation of data, drafting of the manuscript, critical revision of the manuscript, administrative, technical, and material support, and supervision. All authors read and approved the final manuscript