Journal of Immunology Research
Volume 2020 (2020), Article ID 8528976, 11 pages
https://doi.org/10.1155/2020/8528976

Research Article

Association of NCF2, NCF4, and CYBA Gene Polymorphisms with Rheumatoid Arthritis in a Chinese Population

Tian-Ping Zhang,¹ Rui Li,² Qian Huang,³ Han-Feng Pan,³ Dong-Qing Ye,³ and Xiao-Mei Li¹

¹The First Affiliated Hospital of University of Science and Technology of China, Hefei, 230001 Anhui, China
²Department of Nosocomial Infection Management, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
³School of Public Health, Anhui Medical University, Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032 Anhui, China

Correspondence should be addressed to Dong-Qing Ye; anhuiydq@126.com and Xiao-Mei Li; lixiaomei@ustc.edu.cn

Received 27 March 2020; Revised 7 October 2020; Accepted 14 October 2020; Published 21 October 2020

Academic Editor: Lihua Duan

Copyright © 2020 Tian-Ping Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Objective. Recent studies have focused on the special roles of NADPH-oxidase in multiple autoimmune diseases. Nevertheless, the association of genetic variation in NADPH-oxidase genes with rheumatoid arthritis (RA) was not extensively studied in a Chinese population. We performed this study to examine the association of NCF2, NCF4, and CYBA gene polymorphisms with RA susceptibility in a Chinese population. Methods. Six single nucleotide polymorphisms (SNPs) (NCF2 rs10911363, NCF4 rs1883112, rs4821544, rs729749, CYBA rs3794624, and rs4673) were genotyped in a cohort composed of 593 RA patients and 596 normal controls. Improved multiple ligase detection reaction (iMLDR) was used for genotyping. Results. We observed that NCF4 rs4821544 CT genotype and C allele frequencies in RA patients were significantly decreased when compared to controls (CT vs. TT: ; C vs. T: ), and rs4821544 polymorphism was significantly associated with an increased RA risk under the dominant model (TT vs. CT+CC: ). Our results also indicated that rs729749 CT genotype frequency was significantly lower in RA patients than that in controls (CT vs. CC: ). Moreover, the rs729749 CT genotype frequency was also significantly decreased in RA patients in males (CT vs. CC: ). No significant association between NCF2 and CYBA gene polymorphisms and RA susceptibility was observed. There were significant associations between rs4821544 TT genotype and T allele frequencies and anti-CCP in male RA patients. Conclusions. In summary, NCF4 rs4821544 and rs729749 polymorphisms might contribute to RA susceptibility, while NCF2 and CYBA gene polymorphisms were not associated with RA susceptibility.

1. Introduction

Rheumatoid arthritis (RA) is a systemic, chronic autoimmune disease affecting approximately 1-2% of the population worldwide [1]. The disease is characterized by immunologic inadequacy and chronic inflammation and predominantly causes deformity and destruction of the joints [2]. The pathogenesis of RA is not completely identified and generally considered to be related to the interaction between environmental factors and genetic predisposition [3]. Despite many efforts devoted to the studies of predominant genetic markers, only few genetic loci including human leukocyte antigen (HLA) locus and protein tyrosine phosphatase nonreceptor type 22 (PTPN22) have been identified to be associated with RA [4, 5]. Therefore, it is necessary to continue to analyze whether immune-modulating gene variations are associated with RA.

Recent studies indicated that elevated levels of reactive oxygen species (ROS) and reactive nitrogen species (RNS) were found in several autoimmune diseases such as RA and systemic lupus erythematosus (SLE) and involved in inflammatory processes [6, 7]. The production of ROS was a physiological defense against microbial infection, and ROS had an important antibacterial effect on a variety of pathogens. However, the aberrant generation of ROS in autoimmune inflammation could result in tissue damage [6]. Moreover, ROS also had important regulatory functions in the immune system [8]. The NADPH-oxidase (NOX) complex, which was critical for ROS generation, was composed of gp91phox, p22phox, IM7phox, p67phox, and p40phox encoded by CYBB, CYBA, NCFl, NCF2, and NCF4 genes, respectively [9, 10]. The ability to induce ROS extends to phagocytes and dendritic cells, also implying the key functions of the NOX complex in the immune system [11].

The hypothesis that genetically controlled reduced production of ROS caused by NOX gene variations could affect the risk of autoimmune diseases and ROS-regulated chronic autoimmune inflammatory diseases was supported by several studies [12, 13]. Olsson et al. suggested that NCF1-339 T allele frequency in SLE patients was increased in comparison to controls. In addition, the NCF1-339 T allele reduced extracellular ROS production in neutrophils and resulted in the elevated expression of type 1 interferon-regulated gene [12]. It was remarkable that there were several researches exploring the association between NOX gene polymorphisms and RA susceptibility [13, 14]. Zhao et al. demonstrated that the p.Arg90His variant in NCF1, which was observed to cause reduced ROS production, predisposed to RA in a Korean population [13].

Apart from NCF1, several single nucleotide polymorphisms (SNPs) in NCF2, NCF4, and CYBA genes were reported to be associated with autoimmune diseases [15–17]. The results by Olsson et al. indicated that the NCF4 rs729749 variant was involved in the development of RA in a Swedish cohort [16]. However, the association between NCF2, NCF4, and CYBA genetic variants and RA risk in a Chinese population had not been reported. To investigate whether NCF2, NCF4, and CYBA gene polymorphisms are associated with RA susceptibility, we performed this case-control study in a Chinese population.

2. Materials and Methods

2.1. Study Populations

In this study, a total of 593 RA patients including 101 males and 492 females were recruited from Anhui Provincial Laboratory of Inflammatory and Immune Diseases. All patients were diagnosed depending on the 1987 American College of Rheumatology revised criteria [18]. Then, a normal cohort of 97 males and 499 females, which had no history of inflammatory/autoimmune diseases and cancer, was enrolled from the same region. The average ages of RA patients and normal controls were years and years, respectively, and there was no significant difference in age distribution between RA patients and controls. The demographic and clinical data of RA patients were collected from the medical records and reviewed by a rheumatologist, and the clinical data mainly included anticyclic citrullinated peptide (anti-CCP) and rheumatoid factor (RF). All RA patients and normal controls were enrolled after their written informed consent had been obtained, and the study protocol was approved by the Medical Ethics Committee of Anhui Medical University.

2.2. SNP Selection

Several previous studies had shown that NCF2 gene polymorphisms (rs17849502, rs35937854, rs13306575, rs789181, and rs10911363) were significantly associated with the development of autoimmune diseases [16, 19, 20]. However, only the minor allele frequency (MAF) of rs10911363 was greater than 0.05 in the CHB population. Hence, rs10911363 in NCF2 was included for genotyping in the present study. Because of limited research on the NCF4 and CYBA genetic variants in RA, we utilized genotype data of the CHB from Ensembl genome browser 85 and CHBS_1000g and selected the tagSNPs capturing all the common SNPs located in the chromosome locus transcribed into NCF4 and CYBA and their flanking 2000 bp region by the Haploview 4.0 software (Cambridge, MA, USA). We finally selected rs1883112, rs4821544, and rs729749 in NCF4 and rs3794624 and rs4673 in CYBA for genotyping, and the NCF4 rs4821544, rs729749, CYBA rs3794624, and rs4673 had also been studied in the Swedish population [16]. Above SNPs accorded with in CHB and .

2.3. DNA Extraction and Genotyping

A total of 5 ml peripheral blood sample was collected from all study populations by tubes containing ethylenediaminetetraacetic acid (EDTA). Then, genomic DNA was prepared from the peripheral blood leukocytes according to the standard procedures with the FlexiGene DNA Kit (Qiagen, Valencia, CA).

The genotyping was conducted using improved multiple ligase detection reaction (iMLDR) genotyping assays, with the technical support of Genesky Biotechnologies Inc., Shanghai. Those subjects with 100% genotype success for all SNPs were involved in the final analysis.

2.4. Statistical Analysis

Statistical analysis was done in the SPSS 23.00 (SPSS Inc., IL, USA). The chi-square () test was used to analyze the association of the genotype and allele frequencies of above SNPs and RA patients. Odds ratios (OR) and 95% confidence interval (CI) were also evaluated using logistic regression analyses. Two genetic models including the dominant model and the recessive model were also analyzed. The Hardy-Weinberg equilibrium (HWE) test was conducted in the control group. Haplotype was assessed using the SHEsis software (http://analysis.bio-x.cn/myAnalysis.php) [21]. A two-sided was considered as statistically significant.

3. Results

3.1. Association of NCF2, NCF4, and CYBA Gene Polymorphisms with RA Susceptibility

In normal controls, the genotype frequencies of NCF2 rs10911363, NCF4 rs1883112, rs4821544, rs729749 and CYBA rs3794624, and rs4673 were all in compliance with the HWE (all ). The allele and genotype frequencies of these SNPs are shown in Table 1. There was no significant difference in the genotype frequencies of NCF2 rs10911363 between RA patients and controls. Similarly, the allele frequencies of rs10911363 in RA patients were comparable to controls. Then, we stratified all subjects by sex and analyzed the association between rs10911363 and RA susceptibility in males and females, respectively. No significant association was found.

Table 1: The association between NCF2, NCF4, and CYBA gene polymorphisms and RA susceptibility among different groups ( (%)).

SNP
Analyze model
RA patients
Controls
value
OR (95% CI)

All

rs10911363
GG
125 (21.08)
144 (24.16)
0.371
0.863 (0.625, 1.192)

GT
304 (51.26)
289 (48.49)
0.747
1.045 (0.798, 1.370)

TT
164 (27.66)
163 (27.35)
Reference

G
554 (46.71)
577 (48.41)
0.408
1.070 (0.911, 1.257)

T
632 (53.29)
615 (51.59)
Reference

TT
164 (27.66)
163 (27.35)
0.906
1.016 (0.787, 1.310)

GT+GG
429 (72.34)
433 (72.65)
Reference

GG
125 (21.08)
144 (24.16)
0.204
0.838 (0.639, 1.101)

GT+TT
468 (78.92)
452 (75.84)
Reference

rs3794624
AA
14 (2.36)
15 (2.52)
0.929
0.967 (0.461, 2.027)

GA
160 (26.98)
147 (24.66)
0.368
1.127 (0.868, 1.464)

GG
419 (70.66)
434 (72.82)
Reference

A
188 (15.85)
177 (14.85)
0.498
1.080 (0.864, 1.350)

G
998 (84.15)
1015 (85.15)
Reference

GG
419 (70.66)
434 (72.82)
0.408
0.899 (0.698, 1.157)

GA+AA
174 (29.34)
162 (27.18)
Reference

AA
14 (2.36)
15 (2.52)
0.862
0.937 (0.448, 1.958)

GA+GG
579 (97.64)
581 (97.48)
Reference

rs4673
AA
1 (0.17)
5 (0.84)
0.140
0.198 (0.023, 1.698)

GA
85 (14.33)
90 (15.10)
0.673
0.933 (0.677, 1.287)

GG
507 (85.50)
501 (84.06)
Reference

A
87 (7.34)
100 (8.39)
0.340
0.864 (0.641, 1.166)

G
1099 (92.66)
1092 (91.61)
Reference

GG
507 (85.50)
501 (84.06)
0.491
1.118 (0.814, 1.535)

GA+AA
86 (14.50)
95 (15.94)
Reference

AA
1 (0.17)
5 (0.84)
0.142
0.200 (0.023, 1.714)

GA+GG
592 (99.83)
591 (99.16)
Reference

rs1883112
GG
57 (9.61)
56 (9.39)
0.972
1.007 (0.673, 1.508)

GA
248 (41.82)
255 (42.79)
0.754
0.962 (0.757, 1.223)

AA
288 (48.57)
285 (47.82)
Reference

G
362 (30.52)
367 (30.79)
0.888
0.988 (0.830, 1.176)

A
824 (69.48)
825 (69.21)
Reference

AA
288 (48.57)
285 (47.82)
0.796
1.030 (0.821, 1.294)

GA+GG
305 (52.43)
311 (52.18)
Reference

GG
57 (9.61)
56 (9.40)
0.899
1.025 (0.696, 1.511)

GA+AA
536 (90.39)
540 (90.60)
Reference

rs4821544
CC
4 (0.67)
7 (1.17)
0.323
0.536 (0.156, 1.845)

CT
117 (19.73)
146 (24.50)
0.043
0.752 (0.571, 0.991)

TT
472 (79.60)
443 (74.33)
Reference

C
125 (10.54)
160 (13.42)
0.031
1.316 (1.026, 1.688)

T
1061 (89.46)
1032 (86.58)
Reference

TT
472 (79.60)
443 (74.33)
0.031
0.742 (0.566, 0.974)

CT+CC
121 (20.40)
153 (25.67)
Reference

CC
4 (0.67)
7 (1.17)
0.374
0.571 (0.166, 1.962)

CT+TT
589 (99.33)
589 (98.83)
Reference

rs729749
TT
104 (17.54)
102 (17.11)
0.445
0.878 (0.628, 1.226)

CT
266 (44.86)
302 (50.67)
0.033
0.758 (0.588, 0.977)

CC
223 (37.61)
192 (32.21)
Reference

T
474 (39.97)
506 (42.45)
0.219
0.903 (0.767, 1.063)

C
712 (60.03)
686 (57.55)
Reference

CC
223 (37.61)
192 (32.21)
0.051
1.268 (0.999, 1.611)

CT+TT
370 (62.39)
404 (67.79)
Reference

TT
104 (17.54)
102 (17.11)
0.847
1.030 (0.763, 1.391)

CT+CC
489 (82.46)
494 (82.89)
Reference

Female

rs10911363
GG
104 (21.14)
117 (23.45)
0.548
0.896 (0.625, 1.283)

GT
259 (52.64)
252 (50.50)
0.818
1.036 (0.768, 1.397)

TT
129 (26.22)
130 (26.05)
Reference

G
467 (47.46)
486 (48.70)
0.581
1.051 (0.881, 1.253)

T
517 (52.54)
512 (51.30)
Reference

TT
129 (26.22)
130 (26.05)
0.952
0.991 (0.747, 1.316)

GT+GG
363 (73.78)
369 (73.95)
Reference

GG
104 (21.14)
117 (23.45)
0.383
1.143 (0.847, 1.542)

GT+TT
388 (78.86)
382 (76.55)
Reference

rs3794624
AA
12 (2.44)
12 (2.40)
0.876
1.067 (0.473, 2.407)

GA
137 (27.85)
121 (24.25)
0.194
1.208 (0.908, 1.607)

GG
343 (69.72)
366 (73.35)
Reference

A
161 (16.36)
145 (14.53)
0.259
0.869 (0.681, 1.109)

G
823 (83.64)
853 (85.47)
Reference

GG
343 (69.72)
366 (73.35)
0.205
1.195 (0.907, 1.576)

GA+AA
149 (30.28)
133 (26.65)
Reference

AA
12 (2.44)
12 (2.40)
0.972
0.986 (0.438, 2.216)

GA+GG
480 (97.56)
487 (97.60)
Reference

rs4673
AA
1 (0.20)
5 (1.00)
0.140
0.198 (0.023, 1.703)

GA
70 (14.23)
77 (15.43)
0.558
0.900 (0.634, 1.279)

GG
421 (85.57)
417 (83.57)
Reference

A
72 (7.32)
87 (8.72)
0.252
1.210 (0.874, 1.675)

G
912 (92.68)
911 (91.28)
Reference

GG
421 (85.57)
417 (83.57)
0.346
0.847 (0.600, 1.196)

GA+AA
71 (14.43)
83 (16.63)
Reference

AA
1 (0.20)
5 (1.00)
0.144
4.970 (0.579, 42.692)

GA+GG
491 (99.8)
494 (99.00)
Reference

rs1883112
GG
41 (8.33)
47 (9.42)
0.630
0.894 (0.567, 1.409)

GA
211 (42.89)
206 (41.28)
0.715
1.050 (0.808, 1.364)

AA
240 (48.78)
246 (49.30)
Reference

G
293 (29.78)
300 (30.06)
0.890
1.014 (0.836, 1.229)

A
691 (70.22)
698 (69.94)
Reference

AA
240 (48.78)
246 (49.30)
0.870
1.021 (0.796, 1.310)

GA+GG
252 (51.22)
253 (50.70)
Reference

GG
41 (8.33)
47 (9.42)
0.548
1.144 (0.738, 1.774)

GA+AA
451 (91.67)
452 (90.58)
Reference

rs4821544
CC
4 (0.81)
6 (1.20)
0.494
0.641 (0.180, 2.290)

CT
95 (19.31)
115 (23.05)
0.141
0.795 (0.585, 1.079)

TT
393 (79.88)
378 (75.75)
Reference

C
103 (10.47)
127 (12.73)
0.117
1.247 (0.946, 1.644)

T
881 (89.53)
871 (87.27)
Reference

TT
393 (79.88)
378 (75.75)
0.118
0.787 (0.583, 1.063)

CT+CC
99 (20.12)
121 (24.25)
Reference

CC
4 (0.81)
6 (1.20)
0.540
1.485 (0.416, 5.294)

CT+TT
488 (99.19)
493 (98.80)
Reference

rs729749
TT
84 (17.07)
87 (17.43)
0.469
0.873 (0.604, 1.261)

CT
231 (46.95)
252 (50.50)
0.186
0.829 (0.627, 1.095)

CC
177 (35.98)
160 (32.06)
Reference

T
399 (40.55)
426 (42.69)
0.335
1.092 (0.913, 1.306)

C
585 (59.45)
572 (57.31)
Reference

CC
177 (35.98)
160 (32.06)
0.194
0.840 (0.646, 1.093)

CT+TT
315 (64.02)
339 (67.94)
Reference

TT
84 (17.07)
87 (17.43)
0.880
1.026 (0.738, 1.426)

CT+CC
408 (82.93)
412 (82.57)
Reference

Male

rs10911363
GG
21 (20.79)
27 (27.84)
0.413
0.733 (0.349, 1.541)

GT
45 (44.55)
37 (38.14)
0.677
1.147 (0.602, 2.184)

TT
35 (34.65)
33 (34.02)
Reference

G
87 (43.07)
91 (46.91)
0.443
1.168 (0.786, 1.736)

T
115 (56.93)
103 (53.09)
Reference

TT
35 (34.65)
33 (34.02)
0.925
0.972 (0.541, 1.749)

GT+GG
66 (65.35)
64 (65.98)
Reference

GG
21 (20.79)
27 (27.84)
0.249
1.469 (0.764, 2.827)

GT+TT
80 (79.21)
70 (72.16)
Reference

rs3794624
AA
2 (1.98)
3 (3.09)
0.578
0.596 (0.097, 3.677)

GA
23 (22.77)
26 (26.8)
0.480
0.791 (0.413, 1.515)

GG
76 (75.25)
68 (70.1)
Reference

A
27 (13.37)
32 (16.49)
0.383
1.280 (0.735, 2.230)

G
175 (86.63)
162 (83.51)
Reference

GG
76 (75.25)
68 (70.1)
0.417
0.771 (0.412, 1.444)

GA+AA
25 (24.75)
29 (29.9)
Reference

AA
2 (1.98)
3 (3.09)
0.621
1.580 (0.258, 9.666)

GA+GG
99 (98.02)
94 (96.91)
Reference

rs4673
AA
0
0
—
—

GA
15 (14.85)
13 (13.40)
0.770
1.127 (0.506, 2.511)

GG
86 (85.15)
84 (86.60)
Reference

A
15 (7.43)
13 (6.70)
0.779
0.895 (0.414, 1.934)

G
187 (92.57)
181 (93.30)
Reference

rs1883112
GG
16 (15.84)
9 (9.28)
0.433
1.444 (0.576, 3.623)

GA
37 (36.63)
49 (50.52)
0.111
0.614 (0.336, 1.119)

AA
48 (47.52)
39 (40.21)
Reference

G
69 (34.16)
67 (34.54)
0.937
1.017 (0.672, 1.540)

A
133 (65.84)
127 (65.46)
Reference

AA
48 (47.52)
39 (40.21)
0.300
0.742 (0.423, 1.304)

GA+GG
53 (52.48)
58 (59.79)
Reference

GG
16 (15.84)
9 (9.28)
0.169
0.543 (0.228, 1.296)

GA+AA
85 (84.16)
88 (90.72)
Reference

rs4821544
CC
0
1 (1.03)
1.000
—

CT
22 (21.78)
31 (31.96)
0.098
0.584 (0.309, 1.104)

TT
79 (78.22)
65 (67.01)
Reference

C
22 (10.89)
33 (17.01)
0.081
1.677 (0.939, 2.995)

T
180 (89.11)
161 (82.99)
Reference

TT
79 (78.22)
65 (67.01)
0.078
0.566 (0.300, 1.067)

CT+CC
22 (21.78)
32 (32.99)
Reference

CC
0
1 (1.03)
1.000
—

CT+TT
101 (100.00)
96 (98.97)
Reference

rs729749
TT
20 (19.8)
15 (15.46)
0.855
0.928 (0.414, 2.079)

CT
35 (34.65)
50 (51.55)
0.024
0.487 (0.261, 0.909)

CC
46 (45.54)
32 (32.99)
Reference

T
75 (37.13)
80 (41.24)
0.403
1.188 (0.793, 1.780)

C
127 (62.87)
114 (58.76)
Reference

CC
46 (45.54)
32 (32.99)
0.072
0.589 (0.331, 1.041)

CT+TT
55 (54.46)
65 (67.01)
Reference

TT
20 (19.80)
15 (15.46)
0.425
0.741 (0.355, 1.547)

CT+CC
81 (80.20)
82 (84.54)
Reference

Regarding the genotype and allele frequencies of NCF4 rs1883112, rs4821544, and rs729749, we noted that the CT genotype and C allele frequencies of rs4821544 in RA patients were significantly decreased when compared to controls (CT vs. TT: , 95% CI: 0.571-0.991, ; C vs. T: , 95% CI: 1.026-1.688, ). Moreover, the rs4821544 polymorphism was significantly associated with an increased RA risk under the dominant model (TT vs. CT+CC: , 95% CI: 0.566-0.974, ). However, the rs4821544 polymorphism was not correlated with RA susceptibility in male and female subjects, respectively. The results also indicated that rs729749 CT genotype frequency in RA patients was significantly lower than that in controls (CT vs. CC: , 95% CI: 0.588-0.977, ). Moreover, the rs729749 CT genotype frequency was significantly decreased in RA patients in males (CT vs. CC: , 95% CI: 0.261-0.909, ) and was not associated with RA susceptibility in females. No significant association between rs1883112 polymorphism and RA susceptibility was observed.

The genotype and allele frequencies of rs3794624 in CYBA were not significantly different among RA patients and controls (all ), and no significant differences have existed in genotype and allele frequencies of CYBA rs4673 polymorphism (all ). Similarly, CYBA rs3794624 and rs4673 polymorphisms were also not related to RA susceptibility in males and females, respectively.

3.2. Association of NCF2, NCF4, and CYBA Gene Polymorphisms with Clinical Features in RA Patients

Considering that RA was a heterogeneous disease, and different RF, anti-CCP antibody status might reflect disparate mechanisms of RA patients. We determined to evaluate whether NCF2, NCF4, and CYBA gene polymorphisms were associated with different serotypes of RA in a case-only study (Table 2). No significant differences have existed in NCF2, NCF4, and CYBA gene polymorphisms between RF-positive RA patients and RF-negative RA patients, as well as anti-CCP-positive RA patients and anti-CCP-negative RA patients, among the entire study population (all ). Nonetheless, we found that the TT genotype and T allele frequencies of rs4821544 were significantly associated with anti-CCP in male RA patients (, ).

Table 2: Association of clinical characteristics with genotype and allele frequencies in NCF2, NCF4, and CYBA genes among different groups ( (%)).

SNP
Allele
Clinical features
Group
Genotypes (%)
value
Alleles (%)
value

(M/m)
MM
Mm
mm
M
m

All

rs10911363
T/G
Anti-CCP
Positive
128 (26.28)
255 (52.36)
104 (21.35)
0.110
511 (52.46)
463 (47.54)
0.206

Negative
28 (37.33)
31 (41.33)
16 (21.33)

87 (58.00)
63 (42.00)

RF
Positive
126 (26.30)
256 (53.44)
97 (20.25)
0.122
508 (53.03)
450 (46.97)
0.806

Negative
30 (30.93)
41 (42.27)
26 (26.80)

101 (52.06)
93 (47.94)

rs3794624
G/A
Anti-CCP
Positive
346 (71.05)
132 (27.10)
9 (1.85)
0.172
824 (84.60)
150 (13.40)
0.416

Negative
52 (69.33)
19 (25.33)
4 (5.33)

123 (82.00)
27 (18.00)

RF
Positive
340 (70.98)
128 (26.72)
11 (2.30)
0.682
808 (84.34)
150 (15.66)
0.946

Negative
68 (70.10)
28 (28.87)
1 (1.03)

164 (84.54)
30 (15.46)

rs4673
G/A
Anti-CCP
Positive
421 (86.45)
66 (13.55)
0
0.238
908 (93.22)
66 (6.78)
0.257

Negative
61 (81.33)
14 (28.67)
0

136 (90.67)
14 (9.33)

RF
Positive
409 (85.39)
69 (14.41)
1 (0.21)
0.904
887 (92.59)
71 (7.41)
0.925

Negative
83 (85.57)
14 (14.43)
0

180 (92.78)
14 (7.22)

rs1883112
A/G
Anti-CCP
Positive
241 (49.49)
201 (41.27)
45 (9.24)
0.880
683 (70.12)
291 (29.88)
0.976

Negative
36 (48.00)
33 (44.00)
6 (8.00)

105 (70.00)
45 (30.00)

RF
Positive
238 (49.69)
192 (40.08)
49 (10.23)
0.076
668 (69.73)
290 (30.27)
0.697

Negative
45 (46.39)
48 (49.48)
4 (4.12)

138 (71.13)
56 (28.87)

rs4821544
T/C
Anti-CCP
Positive
384 (78.85)
99 (20.33)
4 (0.82)
0.598
867 (89.01)
107 (10.99)
0.392

Negative
62 (82.67)
13 (17.33)
0

137 (91.33)
13 (8.67)

RF
Positive
378 (78.91)
97 (20.25)
4 (0.84)
0.609
853 (89.04)
105 (10.96)
0.489

Negative
79 (81.44)
18 (18.56)
0

176 (90.72)
18 (9.28)

rs729749
C/T
Anti-CCP
Positive
188 (38.60)
215 (44.15)
84 (17.25)
0.820
591 (60.68)
383 (39.32)
0.754

Negative
29 (38.67)
31 (41.33)
15 (20.00)

89 (59.33)
61 (40.67)

RF
Positive
183 (38.20)
215 (44.89)
81 (16.91)
0.676
581 (60.65)
377 (39.35)
0.533

Negative
36 (37.11)
41 (42.27)
20 (20.62)

113 (58.25)
81 (41.75)

Female

rs10911363
T/G
Anti-CCP
Positive
86 (21.18)
218 (53.69)
102 (25.12)
0.162
390 (48.03)
422 (51.97)
0.265

Negative
13 (21.31)
26 (42.62)
22 (36.07)

52 (42.62)
70 (57.38)

RF
Positive
98 (24.69)
220 (55.42)
79 (19.9)
0.074
416 (52.39)
378 (47.61)
0.680

Negative
24 (29.63)
34 (41.98)
23 (28.40)

82 (50.62)
80 (49.38)

rs3794624
G/A
Anti-CCP
Positive
283 (69.70)
115 (28.33)
8 (1.97)
0.360
681 (83.87)
131 (16.13)
0.597

Negative
42 (68.85)
16 (26.23)
3 (4.92)

100 (81.97)
22 (18.03)

RF
Positive
277 (69.77)
110 (27.71)
10 (2.52)
0.750
664 (83.63)
130 (16.37)
0.919

Negative
56 (69.14)
24 (29.63)
1 (1.23)

136 (83.95)
26 (16.05)

rs4673
G/A
Anti-CCP
Positive
352 (86.70)
54 (13.30)
0
0.096
109 (89.34)
13 (10.66)
0.110

Negative
48 (78.69)
13 (21.31)
0

758 (93.35)
54 (6.65)

RF
Positive
341 (85.89)
55 (13.85)
1 (0.25)
0.660
737 (92.82)
57 (7.18)
0.517

Negative
67 (82.72)
14 (17.28)
0

148 (91.36)
14 (8.64)

rs1883112
A/G
Anti-CCP
Positive
202 (49.75)
171 (42.12)
33 (8.13)
0.844
575 (70.81)
237 (29.19)
0.658

Negative
28 (45.90)
28 (45.90)
5 (8.20)

84 (68.85)
38 (31.15)

RF
Positive
201 (50.63)
162 (40.81)
34 (8.56)
0.151
564 (71.03)
230 (28.97)
0.629

Negative
35 (43.21)
42 (51.85)
4 (4.94)

112 (69.14)
50 (30.86)

rs4821544
T/C
Anti-CCP
Positive
324 (79.80)
78 (19.21)
4 (0.99)
0.694
726 (89.41)
86 (10.59)
0.983

Negative
48 (78.69)
13 (21.31)
0

109 (89.34)
13 (10.66)

RF
Positive
317 (79.85)
76 (19.14)
4 (1.01)
0.625
710 (89.42)
84 (10.58)
0.974

Negative
64 (79.01)
17 (20.99)
0

145 (89.51)
17 (10.49)

rs729749
C/T
Anti-CCP
Positive
150 (36.95)
187 (46.06)
69 (17.00)
0.978
487 (59.98)
325 (40.02)
0.840

Negative
22 (36.07)
28 (45.90)
11 (18.03)

72 (59.02)
50 (40.98)

RF
Positive
148 (37.28)
184 (46.35)
65 (16.37)
0.513
480 (60.45)
314 (39.55)
0.247

Negative
26 (32.10)
38 (46.91)
17 (20.99)

90 (55.56)
72 (44.44)

Male

rs10911363
T/G
Anti-CCP
Positive
26 (32.10)
37 (45.68)
18 (22.22)
0.711
89 (54.94)
73 (45.06)
0.570

Negative
6 (42.86)
5 (35.71)
3 (21.43)

17 (60.71)
11 (39.29)

RF
Positive
28 (34.15)
36 (43.90)
18 (21.95)
0.948
92 (56.10)
72 (43.90)
0.732

Negative
6 (37.50)
7 (43.75)
3 (18.75)

19 (59.38)
13 (40.63)

rs3794624
G/A
Anti-CCP
Positive
63 (77.78)
17 (20.99)
1 (1.23)
0.360
143 (88.27)
19 (11.73)
0.367

Negative
10 (71.43)
3 (21.43)
1 (7.14)

23 (82.14)
5 (17.86)

RF
Positive
63 (76.83)
18 (21.95)
1 (1.22)
0.880
144 (87.80)
20 (12.20)
0.962

Negative
12 (75.00)
4 (25.00)
0

28 (87.50)
4 (12.50)

rs4673
G/A
Anti-CCP
Positive
69 (85.19)
12 (14.81)
0
0.441
150 (92.59)
12 (7.41)
0.458

Negative
13 (92.86)
1 (7.14)
0

27 (96.43)
1 (3.57)

RF
Positive
68 (82.93)
14 (17.07)
0
0.074
150 (91.46)
14 (8.54)
0.086

Negative
16 (100.00)
0
0

32 (100.00)
0

rs1883112
A/G
Anti-CCP
Positive
39 (48.15)
30 (37.04)
12 (14.81)
0.700
108 (66.67)
54 (33.33)
0.383

Negative
8 (57.14)
5 (35.71)
1 (7.14)

21 (75.00)
7 (25.00)

RF
Positive
37 (45.12)
30 (36.59)
15 (18.29)
0.152
104 (63.41)
60 (36.59)
0.051

Negative
10 (62.50)
6 (37.50)
0

26 (81.25)
6 (18.75)

rs4821544
T/C
Anti-CCP
Positive
60 (74.07)
21 (25.93)
0
0.031
141 (87.04)
21 (12.96)
0.043

Negative
14 (100.00)
0
0

28 (100.00)
0

RF
Positive
61 (74.39)
21 (25.61)
0
0.090
143 (87.20)
21 (12.80)
0.113

Negative
15 (93.75)
1 (6.25)
0

31 (96.88)
1 (3.13)

rs729749
C/T
Anti-CCP
Positive
38 (46.91)
28 (34.57)
15 (18.52)
0.533
104 (64.20)
58 (35.80)
0.723

Negative
7 (50.00)
3 (21.43)
4 (28.57)

17 (60.71)
11 (39.29)

RF
Positive
35 (42.68)
31 (37.80)
16 (19.51)
0.279
101 (61.59)
63 (38.41)
0.269

Negative
10 (62.50)
3 (18.75)
3 (18.75)

23 (71.88)
9 (28.13)

M: major alleles; m: minor alleles.

3.3. Haplotype Analyses

In the present study, six main haplotypes (ATC, ATT, GCC, GCT, GTC, and GTT) for NCF4 and three main haplotypes (AG, GA, and GG) for CYBA were detected by the SHEsis software. There was no significant difference regarding these haplotype frequencies between RA patients and normal controls (Tables 3 and 4).

Table 3: Haplotype analysis of three SNPs in the NCF4 gene in RA patients and controls ( (%)).

Haplotype
RA patients
Controls
value
OR (95% CI)

rs1883112-rs4821544-rs729749

ATC
525.82 (44.3)
502.44 (42.2)
0.282
1.093 (0.929, 1.286)

ATT
298.18 (25.1)
322.56 (27.1)
0.286
0.905 (0.754, 1.087)

GCC
97.99 (8.3)
118.49 (9.9)
0.155
0.816 (0.616, 1.080)

GCT
27.01 (2.3)
41.51 (3.5)
0.079
0.646 (0.395, 1.056)

GTC
88.19 (7.4)
65.06 (5.5)
0.050
1.391 (0.999, 1.937)

GTT
148.81 (12.5)
141.94 (11.9)
0.634
1.061 (0.830, 1.357)

in both controls and RA patients has been dropped.

Table 4: Haplotype analysis of two SNPs in the CYBA gene in RA patients and controls ( (%)).

Haplotype
RA patients
Controls
value
OR (95% CI)

rs3794624-rs4673

AG
179.43 (15.1)
173.64 (14.6)
0.667
1.051 (0.838, 1.318)

GA
78.43 (6.6)
96.64 (8.1)
0.172
0.806 (0.592, 1.099)

GG
919.57 (77.5)
918.36 (77.0)
0.625
1.049 (0.865, 1.274)

in both controls and RA patients has been dropped.

4. Discussion

ROS was initially thought to be primarily involved in the chronic inflammation of autoimmune diseases such as SLE and RA. Then, the important regulatory functions of ROS were also observed in the immune system [8]. Additionally, some studies had attempted to explore whether NOX gene polymorphisms were related to multiple autoimmune diseases and suggested that NOX gene polymorphisms were associated with autoimmune diseases risk, as well as several specific clinical features [16, 22]. However, such studies were limited, especially in the Chinese population. To our knowledge, the present study was the first to analyze the relationship between polymorphisms of rs10911363 in NCF2; rs1883112, rs4821544, and rs729749 in NCF4; and rs3794624 and rs4673 in CYBA and RA susceptibility in a Chinese population. Since RA was more frequent in females than males, the disease mechanisms might be sex-dependent; hence, we stratified all subjects by sex and analyzed the association between all SNPs and RA susceptibility in males and females, respectively.

As a key component of the multiprotein NOX system, NCF2 was also called p67phox and encoded by the NCF2 gene. The function of NCF2 was considered to regulate the transfer of electrons from NADPH to flavin, and phagocyte ROS production [23]. NCF2 was recruited to the cell membrane for combination with other components to form the active NOX system through microbial stimuli [24]. Moreover, mutations in the NCF2 gene had been reported to affect the risk of a variety of diseases in previous studies [25]. Gateva et al. suggested that NCF2 rs10911363 polymorphism was associated with SLE risk in the US and Sweden populations [26]. In another study, the NCF2 rs789181 variant had been found to have a mild association with RA risk in men [16]. Here, we analyzed the possible relationship between rs10911363 polymorphism and RA susceptibility. However, the present result implied that rs10911363 might not be a contributing factor specific to RA susceptibility. Similarly, NCF2 rs10911363 polymorphism exhibited no significant association with SLE risk in a Chinese population [20]. These interesting observations implied that NCF2 gene rs10911363 polymorphism might not be involved in the pathogenesis of autoimmune diseases such as RA and SLE in a Chinese population. On the other hand, Yu et al. found that the rs10911363 G allele was positively correlated with several clinical characteristics and laboratory parameters in SLE patients and might influence the severity of this disease [20]. Therefore, the potential role of rs10911363 in RA development should be explored in future studies.

NCF4, known as a component of the NOX complex, could induce the NOX complex to phagosomal membranes through binding to phosphatidylinositol 3-phosphate (PtdIns3P) and had been proven to regulate the production of intracellular ROS [27, 28]. A recent animal experiment had explored the critical role of the NCF4-regulated intracellular ROS level in regulating chronic inflammation and autoimmunity, and the results found a mutation in the PtdIns3P-binding site of the regulatory NOX subunit NCF4/p40phox that could enhance autoimmune responses [29]. In another context, several genetic variants in the NCF4 gene had been associated with autoimmune diseases including RA and Crohn’s disease [16, 30, 31]. Roberts et al. revealed that NCF4 rs4821544 polymorphism was significantly related to ileal Crohn’s disease [30]. Similarly, our results demonstrated that rs4821544 CT genotype and C allele frequencies were significantly decreased in RA patients than controls. Olsson et al. found that rs729749 variant in NCF4 was significantly associated with RA risk in men and observed a meaningful association for rs729749 in auto-antibody-negative disease, especially RF negative [16]. Consistent with this result, we found a significant association between rs729749 variation and RA risk in males, while our study also suggested that rs729749 polymorphism was significantly associated with RA susceptibility among the entire study population. The results from our study strengthened the hypothesis that the disease pathway affected by the rs729749 variation was specific to men. Moreover, our results also suggested a significant finding that the role of rs729749 variation in the pathogenesis of RA was closely related to race. In another study, the author found rs1883112 GG genotype frequency associated with a higher risk of diffuse large B-cell lymphoma [32]. However, there was no statistical association between rs1883112 variant and RA susceptibility in our study.

The present results suggested that TT genotype and T allele frequencies of rs4821544 were significantly lower in RA patients with anti-CCP-positive when compared to RA patients with anti-CCP-negative in male. This might help to develop a more appropriate therapeutic schedule for RA patients of different genders. However, it was worth noting that the sample of male RA patients with anti-CCP-negative in this study was small, and this result needed further verification. Our results found no association between rs729749 variants between RF and anti-CCP in RA patients. This was inconsistent with the results by Olsson et al. [16], possibly due to the different sample sizes and sources.

As a necessary subunit of NOX, p22phox was encoded by the CYBA gene and had an important role in regulating NOX activity. The other NOX subunits were expressed in thyroid and colon cells and paired with p22phox; therefore, p22phox was considered as an essential component in maintaining the function of NOX [33, 34]. A functional SNP (rs4673) had aroused great interest of many researchers, because it resulted in Tyr instead of His at residue 72 of p22phox, which has been suggested to significantly reduce basal and NAD(P)H-stimulated superoxide production [35]. Therefore, many studies had focused on the special role of CYBA gene variation in the development of multiple diseases. Lan et al. revealed that rs4673 polymorphism might lead to a high susceptibility of non-Hodgkin lymphoma [36]. Seibold et al. found some evidence for the association of CYBA rs3794624 polymorphism with postmenopausal breast cancer susceptibility [37]. Another meta-analysis showed a significant correlation between the rs4673 variant and T2DM susceptibility [38]. However, our data provide the first evidence that CYBA rs3794624 and rs4673 polymorphisms might not contribute to RA susceptibility in a Chinese population. Although rs3794624 and rs4673 polymorphisms showed no apparent link to RA risk, the accuracy of our results might be influenced by different genotyping, ethnicity, and environmental factors.

In conclusion, the present study demonstrated that NCF4 rs4821544 and rs729749 polymorphisms were associated with RA susceptibility, and rs4821544 polymorphism was also related to anti-CCP in male RA patients. Furthermore, our findings strongly supported the viewpoint that the NOX system played an important role in the pathogenesis of RA. What is worth mentioning is that several limitations existed in the present study. Firstly, our study subjects might be insufficient, which resulted in the low power of this study. Secondly, this study did not detect the protein expression levels of these genes, and we were unable to further analyze the association between gene polymorphism and protein expression levels. Thirdly, special functional verification of relevant SNPs was missing; thus, the mechanism behind the results of genetic association was still unclear. The functional, replication studies with larger sample size, disparate races, and gene-environmental and gene-gene interaction are required.

Data Availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request.

Ethical Approval

This study was approved by the Ethical Committee of Anhui Medical University.

Consent

All the study subjects provided informed consent to participate in this study.

Conflicts of Interest

The authors confirm that there are no conflicts of interest.

Authors’ Contributions

Tian-Ping Zhang and Rui Li contributed equally to this work and should be considered co-first authors.

Acknowledgments

This work was supported by grants from the National Natural Science Foundation of China (81871271) and the Anhui Key Research and Development Program (1804b06020354).

References

M. Rossini, E. Rossi, D. Bernardi et al., “Prevalence and incidence of rheumatoid arthritis in Italy,” Rheumatology International, vol. 34, no. 5, pp. 659–664, 2014.

I. B. McInnes and G. Schett, “The pathogenesis of rheumatoid arthritis,” The New England Journal of Medicine, vol. 365, no. 23, pp. 2205–2219, 2011.

H. F. Pan, R. X. Leng, G. C. Wu, and D. Q. Ye, “Advance in epidemiologic studies on major autoimmune diseases,” Chinese Journal of Disease Control and Prevention, vol. 22, pp. 1093–1095, 2018.

C. M. Weyand and J. J. Goronzy, “Association of MHC and rheumatoid arthritis: HLA polymorphisms in phenotypic variants of rheumatoid arthritis,” Arthritis Research, vol. 2, no. 3, pp. 212–216, 2000.

A. B. Begovich, V. E. H. Carlton, L. A. Honigberg et al., “A missense single-nucleotide polymorphism in a gene encoding a protein tyrosine phosphatase (PTPN22) is associated with rheumatoid arthritis,” American Journal of Human Genetics, vol. 75, no. 2, pp. 330–337, 2004.

M. J. Smallwood, A. Nissim, A. R. Knight, M. Whiteman, R. Haigh, and P. G. Winyard, “Oxidative stress in autoimmune rheumatic diseases,” Free Radical Biology & Medicine, vol. 125, pp. 3–14, 2018.

S. G. Sukkar and E. Rossi, “Oxidative stress and nutritional prevention in autoimmune rheumatic diseases,” Autoimmunity Reviews, vol. 3, no. 3, pp. 199–206, 2004.

R. Holmdahl, O. Sareila, L. M. Olsson, L. Bäckdahl, and K. Wing, “Ncf1 polymorphism reveals oxidative regulation of autoimmune chronic inflammation,” Immunological Reviews, vol. 269, no. 1, pp. 228–247, 2016.

W. M. Nauseef, “Assembly of the phagocyte NADPH oxidase,” Histochemistry and Cell Biology, vol. 122, no. 4, pp. 277–291, 2004.

Y. Groemping and K. Rittinger, “Activation and assembly of the NADPH oxidase: a structural perspective,” The Biochemical Journal, vol. 386, no. 3, pp. 401–416, 2005.

H. Matsue, D. Edelbaum, D. Shalhevet et al., “Generation and function of reactive oxygen species in dendritic cells during antigen presentation,” Journal of Immunology, vol. 171, no. 6, pp. 3010–3018, 2003.

L. M. Olsson, Å. C. Johansson, B. Gullstrand, A. Jönsen, S. Saevarsdottir, and L. Rönnblom, “A single nucleotide polymorphism in theNCF1gene leading to reduced oxidative burst is associated with systemic lupus erythematosus,” Annals of the Rheumatic Diseases, vol. 76, no. 9, pp. 1607–1613, 2017.

J. Zhao, J. Ma, Y. Deng et al., “A missense variant in NCF1 is associated with susceptibility to multiple autoimmune diseases,” Nature Genetics, vol. 49, no. 3, pp. 433–437, 2017.

L. M. Olsson, A. Nerstedt, A. K. Lindqvist et al., “Copy number variation of the gene NCF1 is associated with rheumatoid arthritis,” Antioxidants & Redox Signaling, vol. 16, no. 1, pp. 71–78, 2012.

C. O. Jacob, M. Eisenstein, M. C. Dinauer et al., “Lupus-associated causal mutation in neutrophil cytosolic factor 2 (NCF2) brings unique insights to the structure and function of NADPH oxidase,” Proceedings of the National Academy of Sciences, vol. 109, pp. E59–E67, 2012.

L. M. Olsson, A. K. Lindqvist, H. Källberg et al., “A case-control study of rheumatoid arthritis identifies an associated single nucleotide polymorphism in the NCF4 gene, supporting a role for the NADPH-oxidase complex in autoimmunity,” Arthritis Research & Therapy, vol. 9, no. 5, p. R98, 2007.

E. N. Borisov, T. N. Krasnova, L. M. Samohodskaia, L. V. Ivanitskiĭ, N. V. Nikiforova, and N. A. Mukhin, “Prognostic value of allelic variants affecting the hemostatic system in the development of antiphospholipid syndrome and kidney lesion in patients with systemic lupus erythematosus,” Terapevticheskiĭ Arkhiv, vol. 86, no. 6, pp. 57–62, 2014.

F. C. Arnett, S. M. Edworthy, D. A. Bloch et al., “The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis,” Arthritis and Rheumatism, vol. 31, no. 3, pp. 315–324, 1988.

X. Kim-Howard, C. Sun, J. E. Molineros et al., “Allelic heterogeneity in NCF2 associated with systemic lupus erythematosus (SLE) susceptibility across four ethnic populations,” Human Molecular Genetics, vol. 23, no. 6, pp. 1656–1668, 2014.

B. Yu, Y. Chen, Q. Wu et al., “The association between single-nucleotide polymorphisms of NCF2 and systemic lupus erythematosus in Chinese mainland population,” Clinical Rheumatology, vol. 30, no. 4, pp. 521–527, 2011.

Z. Li, Z. Zhang, Z. He et al., “A partition-ligation-combination-subdivision EM algorithm for haplotype inference with multiallelic markers: update of the SHEsis,” Cell Research, vol. 19, no. 4, pp. 519–523, 2009, http://analysis.bio-x.cn.

S. M. Vieira, M. B. Monteiro, T. Marques et al., “Association of genetic variants in the promoter region of genes encoding p22phox (CYBA) and glutamate cysteine ligase catalytic subunit (GCLC) and renal disease in patients with type 1 diabetes mellitus,” BMC Medical Genetics, vol. 12, no. 1, p. 129, 2011.

Y. Nisimoto, S. Motalebi, C. H. Han, and J. D. Lambeth, “The p67(phox) activation domain regulates electron flow from NADPH to flavin in flavocytochrome b(558),” The Journal of Biological Chemistry, vol. 274, no. 33, pp. 22999–23005, 1999.

J. El-Benna, P. M. Dang, M. A. Gougerot-Pocidalo, and C. Elbim, “Phagocyte NADPH oxidase: a multicomponent enzyme essential for host defenses,” Archivum Immunologiae et Therapiae Experimentalis (Warsz), vol. 53, pp. 199–206, 2005.

L. Jiao, J. Song, L. Ding et al., “A novel genetic variation inNCF2, the core component of NADPH oxidase, contributes to the susceptibility of tuberculosis in western Chinese Han population,” DNA and Cell Biology, vol. 39, no. 1, pp. 57–62, 2020.

V. Gateva, J. K. Sandling, G. Hom et al., “A large-scale replication study identifies TNIP1, PRDM1, JAZF1, UHRF1BP1 and IL10 as risk loci for systemic lupus erythematosus,” Nature Genetics, vol. 41, no. 11, pp. 1228–1233, 2009.

K. E. Anderson, T. A. M. Chessa, K. Davidson et al., “PtdIns3P and Rac direct the assembly of the NADPH oxidase on a novel, pre-phagosomal compartment during FcR-mediated phagocytosis in primary mouse neutrophils,” Blood, vol. 116, no. 23, pp. 4978–4989, 2010.

C. Ellson, K. Davidson, K. Anderson, L. R. Stephens, and P. T. Hawkins, “PtdIns3P binding to the PX domain of p40phox is a physiological signal in NADPH oxidase activation,” The EMBO Journal, vol. 25, no. 19, pp. 4468–4478, 2006.

S. Winter, M. Hultqvist Hopkins, F. Laulund, and R. Holmdahl, “A reduction in intracellular reactive oxygen species due to a mutation in NCF4 promotes autoimmune arthritis in mice,” Antioxidants & Redox Signaling, vol. 25, no. 18, pp. 983–996, 2016.

R. L. Roberts, J. E. Hollis-Moffatt, R. B. Gearry, M. A. Kennedy, M. L. Barclay, and T. R. Merriman, “Confirmation of association of IRGM and NCF4 with ileal Crohn's disease in a population-based cohort,” Genes and Immunity, vol. 9, no. 6, pp. 561–565, 2008.

Y. Mazor, I. Maza, E. Kaufman et al., “Prediction of disease complication occurrence in Crohn's disease using phenotype and genotype parameters at diagnosis,” Journal of Crohn's & Colitis, vol. 5, no. 6, pp. 592–597, 2011.

D. Liu, N. Wu, H. Sun et al., “ABCG2andNCF4polymorphisms are associated with clinical outcomes in diffuse large B-cell lymphoma patients treated with R-CHOP,” Oncotarget, vol. 8, no. 35, pp. 58292–58303, 2017.

H. Kikuchi, M. Hikage, H. Miyashita, and M. Fukumoto, “NADPH oxidase subunit, gp91(phox) homologue, preferentially expressed in human colon epithelial cells,” Gene, vol. 254, no. 1-2, pp. 237–243, 2000.

H. Sumimoto, “Structure, regulation and evolution of Nox—family NADPH oxidases that produce reactive oxygen species,” The FEBS Journal, vol. 275, no. 13, pp. 3249–3277, 2008.

T. J. Guzik, N. E. West, E. Black et al., “Functional effect of the C242T polymorphism in the NAD(P)H oxidase p22phox gene on vascular superoxide production in atherosclerosis,” Circulation, vol. 102, no. 15, pp. 1744–1747, 2000.

Q. Lan, T. Zheng, M. Shen et al., “Genetic polymorphisms in the oxidative stress pathway and susceptibility to non-Hodgkin lymphoma,” Human Genetics, vol. 121, no. 2, pp. 161–168, 2007.

P. Seibold, P. Hall, N. Schoof et al., “Polymorphisms in oxidative stress-related genes and mortality in breast cancer patients – Potential differential effects by radiotherapy?” International Journal of Cancer, vol. 22, no. 5, pp. 817–823, 2013.

Q. Sun, Y. Yin, Z. Zhu, and Z. Yan, “Association of the C242T polymorphism in the NAD(P)H oxidase P22 phox gene with type 2 diabetes mellitus risk: a meta-analysis,” Meta Gene, vol. 30, no. 3, pp. 415–422, 2014.