Interleukin-1β and Tumor Necrosis Factor-α Gene Polymorphisms in Systemic Sclerosis
Categoría del artículo: ORIGINAL ARTICLE
Publicado en línea: 06 mar 2025
Páginas: 59 - 68
DOI: https://doi.org/10.2478/bjmg-2024-0017
Palabras clave
© 2024 Hakami M.A et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Systemic sclerosis (SSc) is a generalized disorder of small arteries, microvessels, and connective tissue. It is a disease of unknown origin, with the highest incidence occurring between 45 to 55 years of age [1]; the frequency is three to eight times higher in females [2]. Several studies have demonstrated that the extent of skin involvement directly correlates with internal organ involvement and prognosis in SSc patients [3, 4]. Manifestations associated with SSc have been found to negatively impact the quality of life in affected individuals [5].
Long-term occupational exposure to environmental toxins is a common finding in SSc patients [6]. However, the effect of these environmental toxins on immune system of these genetically susceptible patients is unclear. Recent studies have raised the possibility that both genetic and environmental factors act synergistically at several stages of autoimmunity pathogenesis. These studies predict that individuals susceptible to spontaneous autoimmunity should be more susceptible following xenobiotic exposure by virtue of the presence of predisposing background genes [7]. Studies have shown that genetic predisposition plays an important role in susceptibility and the development of autoimmune diseases. This is likely due to functional polymorphisms within multiple genes, each of which, by modulating corresponding protein expression, influences disease susceptibility.
Cytokines may promote the deposition of collagen and fibrosis [8] and many studies have focused on the role of these mediators in SSc, enlisting alterations in their concentrations [9, 10] or in the balance between Th1 and Th2 cytokine levels [11]. Because cytokine production is regulated at the genetic level [12, 13], it has been hypothesized that single-nucleotide polymorphisms (SNPs) in or near cytokine genes may be relevant to the development of SSc.
Numerous studies examining patients with SSc from diverse ancestral backgrounds have identified SNPs in various cytokine genes. Among these, the
These and several other contradictions motivated us to investigate the commonly studied cytokine gene SNPs among our SSc patients, and compare our findings with those previously reported. In this study we evaluated the presence of 22 SNPs in 13 cytokine genes in SSc patients and attempted to associate the significant SNPs with SSc disease susceptibility in our population.
Patients clinically diagnosed with SSc, confirmed through established laboratory investigations and meeting the American College of Rheumatology (ACR) criteria [20], were consecutively enrolled at a tertiary care hospital in North India. The rarity of SSc, its genetic heterogeneity, and strict diagnostic criteria present significant challenges in participant recruitment for SNP studies. Additionally, specific disease subtypes, comorbidities, drug exclusions, geographic barriers, and ethical concerns further limit the eligible patient pool.
Our study involved 23 SSc patients and 80 age-matched healthy volunteers of Asian ethnicity. Patients and healthy volunteers were unrelated, and the latter had no clinical history of skin disease, minimizing potential con-founders and ensuring clear group distinction. Peripheral venous blood (2ml) was collected aseptically from each patient and healthy volunteers into EDTA vacutainer tubes and used for DNA extraction. The study was approved by the Institutional Ethical Committee-Human Research, and written informed consent was obtained from each patient and healthy volunteer before enrollment in the study.
Genomic DNA was extracted from blood samples of 23 SSc patients and 80 healthy controls for cytokine genotyping of 22 SNPs in 13 cytokine genes using PCR with sequence-specific primers. DNA extraction was performed using the HiPurA™ blood genomic DNA extraction kit (HiMedia Laboratories) as per the manufacturer’s protocol. Briefly, 200μl of blood was mixed with 20μl Proteinase K solution, vortexed, then treated with 20μl RNase A solution. After incubation, 200μl of lysis buffer (C1) was added, followed by a 10-minute incubation at 55°C. Ethanol (200μl) was added, and the lysate was transferred to a spin column for centrifugation. The column was washed with prewash and wash buffers, then eluted with 100μl elution buffer after a 5-minute incubation. DNA was stored at -20°C for PCR analysis.
Cytokine genotyping was carried out from genomic DNA by PCR with sequence-specific primers using commercially available Cytokine Genotyping Kit (Invitrogen Corporation, USA). Twenty two SNPs (
For 48 reactions/wells for each sample, 140μl of PCR buffer was mixed with 3.3μl of Taq DNA polymerase, 329μl of water and 50μl of 75-125ng/μl concentrated DNA template. The reaction mixture (10μl) was dispensed into each well and the following thermal cycler profile was used for amplification. Step 1 was denaturation for 2 minutes at 94°C; Step 2 comprised 10 cycles of 94°C for 15 seconds and 65°C for 60 seconds with no separate extension step; Step 3 (20 cycles) consisted of 94°C for 15 seconds, 61°C for 50 seconds, and 72°C for 30 seconds. The profile was set on hold at 4°C.
The PCR products were loaded onto a 2 percent agarose gel in a specific order for electrophoresis and run at 150 volts for 20-25 minutes for separating the DNA. After electrophoresis, the ethidium bromide stained gel was photographed and interpreted for specific amplification patterns using the worksheet provided with the kit. Presence of a control band in each lane was ascertained. Wells identifying the
Two-sided Fisher’s exact test was used to compare allele, genotype and haplotype frequencies between patients and controls. The threshold for significance was
A total of 23 patients with SSc (4 males, 19 females; mean age 35.5 years) and 80 healthy volunteers (32 males, 48 females; mean age 36 years) were analyzed for 22 SNPs in 13 cytokine genes using cytokine genotyping with sequence-specific primers. The duration of SSc disease ranged from 2 months to 14 years. Common presentations included Raynaud phenomenon, skin sclerosis, and pigmentation, along with finger contractures, digital ulcers, dyspnea, restricted mouth opening, joint issues, and dysphagia. The Rodnan skin score ranged from 9 to 51. The higher proportion of females in the SSc patient group (82.6%) compared to the control group (60%) reflects the well-established female predominance in systemic sclerosis (SSc), with the disease being more prevalent in women. The higher number of healthy volunteers was driven by the rarity of SSc, its strict diagnostic criteria, and the challenges in recruitment, while healthy volunteers are more readily available. This larger control group ensures a robust comparison, minimizes biases, and enhances the study’s ability to detect genetic associations, especially given SSc’s genetic heterogeneity and clinical variability. All SNPs, except the
Distribution of allelic or genotypic frequencies of
Single nucleotide polymorphisms showing allele and genotype frequencies in patients with systemic sclerosis and healthy controls.
Cytokine polymorphism | SSc (n=23) | HC (n=80) | |||
---|---|---|---|---|---|
IL1β -511 (rs16944) | Alleles | T | 33 (71.7) | 80 (50.0) | |
C | 13 (28.3) | 80 (50.0) | |||
Genotypes | TT | 14 (60.9) | 29 (36.3) | 0.054 | |
TC | 5 (21.7) | 22 (27.4) | 0.789 | ||
CC | 4 (17.4) | 29 (36.3) | 0.128 | ||
IL1β +3962 (rs1143634) | Alleles | C | 28 (60.9) | 129 (80.6) | |
T | 18 (39.1) | 31 (19.4) | |||
Genotypes | CC | 11 (47.8) | 56 (70.0) | 0.081 | |
CT | 6 (26.1) | 17 (21.2) | 0.585 | ||
TT | 6 (26.1) | 7 (8.8) | 0.068 | ||
IL4Rα +1902 (rs1801275) | Alleles | G | 9 (19.6) | 23 (14.4) | 0.488 |
A | 37 (80.4) | 137 (85.6) | 0.488 | ||
Genotypes | GG | 2 (8.7) | 0 (0.0) | ||
GA | 5 (21.7) | 23 (28.8) | 0.602 | ||
AA | 16 (69.6) | 57 (71.2) | 1.000 | ||
IL12 -1188 (rs3212227) [deviation from HWE, therefore excluded] | Alleles | C | 16 (34.8) | 94 (58.8) | |
A | 30 (65.2) | 66 (41.2) | |||
Genotypes | CC | 0 (0.0) | 35 (43.8) | ||
CA | 16 (69.6) | 24 (30.0) | |||
AA | 7 (30.4) | 21 (26.2) | 0.791 | ||
TGFβ1 codon10 (rs1982073) | Alleles | C | 23 (50.0) | 81 (50.6) | 1.000 |
T | 23 (50.0) | 79 (49.4) | 1.000 | ||
Genotypes | CC | 0 (0.0) | 1 (1.2) | 1.000 | |
CT | 23 (100.0) | 79 (98.8) | 1.000 | ||
TT | 0 (0.0) | 0 (0.0) | - | ||
TGFβ1 codon25 (rs1800471) | Alleles | G | 35 (76.1) | 96 (60.0) | 0.056 |
C | 11 (23.9) | 64 (40.0) | 0.056 | ||
Genotypes | GG | 12 (52.2) | 16 (20.0) | ||
GC | 11 (47.8) | 64 (80.0) | |||
CC | 0 (0.0) | 0 (0.0) | - | ||
TGFβ1 codon10, codon25 | Haplotypes | CG | 12 (26.1) | 17 (10.6) | |
TG | 23 (50.0) | 79 (49.4) | 1.000 | ||
CC | 11 (23.9) | 64 (40.0) | 0.056 | ||
TNFα -308 (rs1800629) | Alleles | G | 42 (91.3) | 103 (64.4) | |
A | 4 (8.7) | 57 (35.6) | |||
Genotypes | GG | 19 (82.6) | 23 (28.8) | ||
GA | 4 (17.4) | 57 (71.2) | |||
AA | 0 (0.0) | 0 (0.0) | - | ||
TNFα -238 (rs361525) | Alleles | G | 27 (58.7) | 137 (85.6) | |
A | 19 (41.3) | 23 (14.4) | |||
Genotypes | GG | 4 (17.4) | 57 (71.2) | ||
GA | 19 (82.6) | 23 (28.8) | |||
AA | 0 (0.0) | 0 (0.0) | - | ||
TNFα -308, -238 | Haplotypes | GG | 23 (50.0) | 80 (50.0) | 1.000 |
AG | 4 (8.7) | 57 (35.6) | |||
GA | 19 (41.3) | 23 (14.4) | |||
IL4 -1098 (rs 2243248) | Alleles | T | 35 (76.1) | 138 (86.2) | 0.112 |
G | 11 (23.9) | 22 (13.8) | 0.112 | ||
Genotypes | TT | 14 (60.9) | 58 (72.5) | 0.309 | |
TG | 7 (30.4) | 22 (27.5) | 0.796 | ||
GG | 2 (8.7) | 0 (0.0) | |||
IL4 -590 (rs2243250) | Alleles | C | 38 (82.6) | 109 (68.1) | 0.065 |
T | 8 (17.4) | 51 (31.9) | 0.065 | ||
Genotypes | CC | 15 (65.2) | 43 (53.7) | 0.353 | |
CT | 8 (34.8) | 23 (28.8) | 0.611 | ||
TT | 0 (0.0) | 14 (17.5) | |||
IL4 -33 (rs2070874) | Alleles | T | 9 (19.6) | 52 (32.5) | 0.102 |
C | 37 (80.4) | 108 (67.5) | 0.102 | ||
Genotypes | TT | 3 (13.05) | 15 (18.8) | 0.757 | |
TC | 3 (13.05) | 22 (27.4) | 0.180 | ||
CC | 17 (73.9) | 43 (53.8) | 0.098 | ||
IL6 -174 (rs1800795) | Alleles | G | 38 (82.6) | 144 (90.0) | 0.193 |
C | 8 (17.4) | 16 (10.0) | 0.193 | ||
Genotypes | GG | 18 (78.3) | 64 (80.0) | 1.000 | |
GC | 2 (8.7) | 16 (20.0) | 0.350 | ||
CC | 3 (13.0) | 0 (0.0) | |||
IL6 nt565 (rs1800797) | Alleles | G | 40 (87.0) | 145 (90.6) | 0.580 |
A | 6 (13.0) | 15 (9.4) | 0.580 | ||
Genotypes | GG | 20 (87.0) | 65 (81.2) | 0.757 | |
GA | 0 (0.0) | 15 (18.8) | |||
AA | 3 (13.0) | 0 (0.0) | |||
IL10 -1082 (rs1800896) | Alleles | A | 32 (69.6) | 88 (55.0) | 0.091 |
G | 14 (30.4) | 72 (45.0) | 0.091 | ||
Genotypes | AA | 9 (39.1) | 8 (10.0) | ||
AG | 14 (60.9) | 72 (90.0) | |||
GG | 0 (0.0) | 0 (0.0) | - | ||
IL10 -819 (rs1800871) | Alleles | C | 23 (50.0) | 103 (64.4) | 0.088 |
T | 23 (50.0) | 57 (35.6) | 0.088 | ||
Genotypes | CC | 6 (26.1) | 23 (28.8) | 1.000 | |
CT | 11 (47.8) | 57 (71.2) | |||
TT | 6 (26.1) | 0 (0.0) | |||
IL10 -592 (rs1800872) | Alleles | A | 19 (41.3) | 57 (35.6) | 0.493 |
C | 27 (58.7) | 103 (64.4) | 0.493 | ||
Genotypes | AA | 2 (8.7) | 0 (0.0) | ||
AC | 15 (65.2) | 57 (71.2) | 0.611 | ||
CC | 6 (26.1) | 23 (28.8) | 1.000 | ||
IL10 -1082, -819, -592 | Haplotypes | ATA | 17 (37.0) | 50 (31.2) | 0.479 |
ACC | 15 (32.6) | 38 (23.8) | 0.252 | ||
GCC | 14 (30.4) | 72 (45.0) | 0.091 |
Allele, genotype and haplotype frequencies are presented as absolute numbers with percentage in parentheses; rs - refSNP cluster ID number;
*Mean difference is significant at the indicated
As polymorphism in
Significant differences in allele distributions were found between the patients with SSc and controls for
IL-1β Cytokine Gene Polymorphism association with systemic sclerosis.
Cytokine polymorphism | SSc (n=23) | HC (n=80) | Odds Ratio | 95% CI | |||
---|---|---|---|---|---|---|---|
IL-1β -511 (rs16944) | Alleles | T | 33 (71.7) | 80 (50.0) | 2.538 | 1.245 - 5.177 | |
C | 13 (28.3) | 80 (50.0) | 0.394 | 0.193 - 0.803 | |||
Genotypes | TT | 14 (60.9) | 29 (36.3) | 0.054 | 2.736 | 1.054 - 7.098 | |
TC | 5 (21.7) | 22 (27.4) | 0.789 | 0.732 | 0.242 - 2.213 | ||
CC | 4 (17.4) | 29 (36.3) | 0.128 | 0.370 | 0.115 - 1.194 | ||
IL-1β +3962 (rs1143634) | Alleles | C | 28 (60.9) | 129 (80.6) | 0.374 | 0.184 - 0.760 | |
T | 18 (39.1) | 31 (19.4) | 2.675 | 1.315 - 5.442 | |||
Genotypes | CC | 11 (47.8) | 56 (70.0) | 0.081 | 0.393 | 0.152 - 1.013 | |
CT | 6 (26.1) | 17 (21.2) | 0.585 | 1.308 | 0.447 - 3.828 | ||
TT | 6 (26.1) | 7 (8.8) | 0.068 | 3.681 | 1.096 - 12.36 |
Allele and genotype frequencies are presented as absolute numbers with percentage in parentheses;
rs - refSNP cluster ID number; 95% CI - 95% confidence interval;
*Mean difference is significant at the indicated
The
TNF-α Cytokine Gene Polymorphism association with systemic sclerosis.
Cytokine polymorphism | SSc (n=23) | HC (n=80) | Odds Ratio | 95% CI | |||
---|---|---|---|---|---|---|---|
TNF-α -308 (rs1800629) | Alleles | G | 42 (91.3) | 103 (64.4) | 5.811 | 1.982 - 17.032 | |
A | 4 (8.7) | 57 (35.6) | 0.172 | 0.059 - 0.504 | |||
Genotypes | GG | 19 (82.6) | 23 (28.8) | 11.772 | 3.61 - 38.384 | ||
GA | 4 (17.4) | 57 (71.2) | 0.085 | 0.026 - 0.277 | |||
AA | 0 (0.0) | 0 (0.0) | - | - | - | ||
TNF-α -238 (rs361525) | Alleles | G | 27 (58.7) | 137 (85.6) | 0.239 | 0.114 - 0.497 | |
A | 19 (41.3) | 23 (14.4) | 4.192 | 2.011 - 8.737 | |||
Genotypes | GG | 4 (17.4) | 57 (71.2) | 0.085 | 0.026 - 0.277 | ||
GA | 19 (82.6) | 23 (28.8) | 11.772 | 3.61 - 38.384 | |||
AA | 0 (0.0) | 0 (0.0) | - | - | - | ||
TNF-α -308, -238 | Haplotypes | GG | 23 (50.0) | 80 (50.0) | 1.000 | 1.000 | 0.519 - 1.927 |
AG | 4 (8.7) | 57 (35.6) | 0.172 | 0.059 - 0.504 | |||
GA | 19 (41.3) | 23 (14.4) | 4.192 | 2.011 - 8.737 |
Allele, genotype and haplotype frequencies are presented as absolute numbers with percentage in parentheses;
rs - refSNP cluster ID number; 95% CI - 95% confidence interval;
*Mean difference is significant at the indicated
There were significant differences in the genotype frequencies of the
IL-10 Cytokine Gene Polymorphism association with systemic sclerosis.
Cytokine polymorphism | SSc (n=23) | HC (n=80) | p-value | Odds Ratio | 95% CI | ||
---|---|---|---|---|---|---|---|
IL-10 -1082 (rs1800896) | Alleles | A | 32 (69.6) | 88 (55.0) | 0.091 | 1.870 | 0.928 - 3.77 |
G | 14 (30.4) | 72 (45.0) | 0.091 | 0.535 | 0.265 - 1.078 | ||
Genotypes | AA | 9 (39.1) | 8 (10.0) | 5.786 | 1.904 17.577 | ||
AG | 14 (60.9) | 72 (90.0) | 0.173 | 0.057 - 0.525 | |||
GG | 0 (0.0) | 0 (0.0) | - | - | - | ||
IL-10 -819 (rs1800871) | Alleles | C | 23 (50.0) | 103 (64.4) | 0.088 | 0.553 | 0.285 - 1.073 |
T | 23 (50.0) | 57 (35.6) | 0.088 | 1.807 | 0.932 - 3.504 | ||
Genotypes | CC | 6 (26.1) | 23 (28.8) | 1.000 | 0.875 | 0.306 - 2.497 | |
CT | 11 (47.8) | 57 (71.2) | 0.370 | 0.143 - 0.957 | |||
TT | 6 (26.1) | 0 (0.0) | 0.739 | 0.580 - 0.942 | |||
IL-10 -592 (rs1800872) | Alleles | A | 19 (41.3) | 57 (35.6) | 0.493 | 1.272 | 0.651 - 2.485 |
C | 27 (58.7) | 103 (64.4) | 0.493 | 0.786 | 0.402 - 1.537 | ||
Genotypes | AA | 2 (8.7) | 0 (0.0) | 0.913 | 0.805 - 1.036 | ||
AC | 15 (65.2) | 57 (71.2) | 0.611 | 0.757 | 0.282 - 2.026 | ||
CC | 6 (26.1) | 23 (28.8) | 1.000 | 0.875 | 0.306 - 2.497 | ||
IL-10 -1082, -819, -592 | Haplotypes | ATA | 17 (37.0) | 50 (31.2) | 0.479 | 1.290 | 0.650 - 2.560 |
ACC | 15 (32.6) | 38 (23.8) | 0.252 | 1.553 | 0.759 - 3.179 | ||
GCC | 14 (30.4) | 72 (45.0) | 0.091 | 0.535 | 0.265 - 1.078 |
Allele, genotype and haplotype frequencies are presented as absolute numbers with percentage in parentheses;
rs - refSNP cluster ID number; 95% CI - 95% confidence interval;
*Mean difference is significant at the indicated
In addition to these results, significantly higher frequencies of genotypes were also observed in SSc patients as compared to controls in
Cytokine production and release are key events in SSc pathogenesis as they are involved in T and B cell activation leading to inflammation, auto-antibodies production, microvascular damage and fibrosis [21]. The Th1/Th2/Th17/Treg balance is one of the hallmarks of SSc pathogenesis, as the Th2 and Th17 cytokines response leads to tissue fibrosis, whereas Th1 and Th17 cytokines promote inflammation in SSc patients.
Changes in
A significant association of
In our study, despite the patients and controls being of the same ethnic origin and from the same geographic region, we identified a strong association between the
The
The importance of
The significant association between
Our study is limited by a small sample size and a restricted number of SNPs, as genetic susceptibility to SSc likely involves a broader combination of genes, along with environmental and epigenetic factors. Additionally, we did not adjust
Future research should explore the functional roles of these SNPs through
Our study found a significant association between