This study was designed to explore the association between Graves disease (GD) and thyroid-stimulating hormone receptor (TSHR) and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) single nucleotide polymorphisms (SNPs). We studied a total of 1217 subjects from a Han population in northern Anhui province in China. Six SNPs within TSHR (rs179247, rs12101261, rs2284722, rs4903964, rs2300525, and rs17111394) and four SNPs within CTLA-4 (rs10197319, rs231726, rs231804, and rs1024161) were genotyped via a Taqman probe technique using a Fluidigm EP1 platform. The TSHR alleles rs179247-G, rs12101261-C, and rs4903964-G were negatively correlated with GD, whereas the rs2284722-A and rs17111394-C alleles were positively correlated with GD. Analyzing TSHR SNPs at rs179247, rs2284722, rs12101261, and rs4903964 yielded 8 different haplotypes. There were positive correlations between GD risk and the haplotypes AGTA and AATA (
GD is a common organ-specific autoimmune disease and the most common cause of thyrotoxicosis. At present, however, the molecular mechanisms underlying GD have not been elucidated. GD susceptibility stems from a confluence of genetic, environmental, and immunological factors [
TSHR is a primary candidate gene believed to be related to GD susceptibility. TSHR is a specific protein expressed in thyroid cells in the thyroid follicular membrane. TSH regulates both thyroid growth and functionality via TSHR signaling. A study by Zhan et al. [
TSHR is a member of the G-protein-coupled receptor superfamily encoded on chromosome 14. The protein is a single 764 amino acid peptide chain encoded for across 10 exons with a molecular weight of 84000 daltons. TSH binding to TSHR promotes G-protein signaling, leading to activation of the cAMP and/or phosphoinositide Ca2+ signal transduction pathways. There are many antithyroid autoantibodies present in the serum of patients with GD, including thyrotrophin receptor antibody (TRAb), thyroglobulin antibody (TGAb), and thyroid peroxidase antibody (TPOAb). TRAb is an antibody which is specific to TSHR, and it is believed to be the autoantibody most important for the development of hyperthyroidism. Most patients with GD exhibit TRAb autoantibodies in the peripheral blood. TRAb is an immunoglobulin (IgG) that, when present in the serum, competes with TSH to bind to TSHR, activating the receptor and inducing biological effects similar to those of TSH. Research has shown that a targeted immunotherapy strategy in mice aimed at disrupting antigen processing and presentation in HLA-DR3 transgenic mice blocks the immune response to TSHR, thus offering a potential avenue for GD treatment [
CTLA-4 is a member of the immunoglobulin gene superfamily and a negative regulator of T cell responses that is associated with immune tolerance. CTLA-4 is expressed on the surface of T cells mainly in the form of a dimer, and when it interacts with its cognate ligands, this induces inhibitory signals which terminate T cell activation and proliferation. Polymorphisms in CTLA-4 may alter its functionality such that the activation of T cells cannot be inhibited, resulting in a loss of immune tolerance and the occurrence of autoimmunity, making it vital that normal CTLA-4 activity be maintained. CTLA-4 is a major susceptibility gene associated with autoimmune thyroid disease (AITD). An association study aimed at identifying SNPs in the CTLA-4 gene present in GD patients and control subjects has confirmed that CTLA-4 is indeed a susceptibility gene for GD in the Chinese Han population [
A number of GD susceptibility genes have been identified to date including human leukocyte antigen (HLA) I and II, cluster of differentiation 40 (CD40), TSHR, protein tyrosine phosphatase nonreceptor 22 (PTPN22), interferon-inducible helicase domain 1 (IFIH1), CTLA-4, forkhead Box P3 (FoxP3), Ikaros family of zinc finger3 (IKZF3), FC-receptor-like 3 (FCRL3), and thyroglobulin (TG) [
We studied a total of 1217 subjects, divided into a case group and a control group. The control group was composed of 620 healthy subjects including 113 males and 507 females. The GD case group was composed of 597 individuals including 127 male patients and 470 female patients. All patients and control subjects were from a Chinese Han population from northern Anhui province and were unrelated to each other. Patients with other autoimmune diseases or a family history thereof were excluded.
Subjects were diagnosed with GD based upon clinical and laboratory examinations that confirmed hyperthyroidism, which was accompanied by symptoms of a high metabolism, diffuse goiter, thyroid ophthalmopathy, and pretibial myxedema, as well as high serum levels of free thyroxine (FT4) and free T3 (FT3), very low levels of circulating thyroid-stimulating hormone (TSH), and positive TRAb circulation. This study was approved by our local ethics committee.
From each individual, a 5 mL sample of peripheral blood was collected in an EDTA-treated tube and use for DNA extraction with a DNA purification kit (Fujifilm Company) based on the provided instructions. All DNA samples were genotyped using Illumina Human660-Quad BeadChips. Illumina BeadStudio 3.3 software was used for genotype clustering. All samples had a mean call rate of 99.8%. The genotypes of the TSHR and CTLA-4 gene SNPs were determined using a Taqman probe technique with a Fluidigm EP1 platform. Polymerase chain reaction (PCR) was employed to amplify each target gene sequence as previously described [
Quantitative data are given as
Clinical data is shown in Table
Clinical data.
Basic information | Case group ( |
Control group ( |
|||
---|---|---|---|---|---|
Sex | Male | 127 | 113 | 1.78 | 0.18 |
Female | 470 | 507 | |||
Age | 6.76 | <0.001 | |||
Diffuse goiter | 0 | 15 | — | — | — |
I | 186 | — | — | — | |
II | 386 | — | — | — | |
III | 10 | — | — | — | |
Exophthalmos | Yes | 252 | — | — | — |
No | 345 | — | — | — | |
TRAb | ≥1.5 U/L | 456 | — | — | — |
<1.5 U/L | 96 |
Genotype distribution of TSHR and CTLA-4 gene and Hardy-Weinberg equilibrium test.
SNPs | Case group ( |
Control group ( |
HWE ( | |||
---|---|---|---|---|---|---|
TSHR | 0.80 | |||||
A | 895 (74.96) | 782 (63.06) | 40.16 | <0.001 | ||
G | 299 (25.04) | 458 (36.94) | ||||
AA | 342 (57.29) | 248 (40.00) | 39.44 | <0.001 | ||
AG | 211 (35.34) | 286 (46.13) | ||||
GG | 44 (7.37) | 86 (13.87) | ||||
0.06 | ||||||
G | 833 (69.77) | 937 (75.56) | 10.31 | 0.001 | ||
A | 361 (30.23) | 303 (24.44) | ||||
GG | 291 (48.74) | 345 (55.65) | 12.97 | 0.002 | ||
AG | 251 (42.04) | 247 (39.84) | ||||
AA | 55 (9.22) | 28 (4.51) | ||||
0.56 | ||||||
T | 872 (73.03) | 756 (60.97) | 39.97 | <0.001 | ||
C | 322 (26.97) | 484 (39.03) | ||||
TT | 320 (53.60) | 234 (37.74) | 38.60 | <0.001 | ||
CT | 232 (38.86) | 288 (46.45) | ||||
CC | 45 (7.54) | 98 (15.81) | ||||
0.29 | ||||||
A | 824 (69.01) | 701 (56.53) | 40.49 | <0.001 | ||
G | 370 (30.99) | 539 (43.47) | ||||
AA | 279 (46.73) | 205 (33.06) | 41.47 | <0.001 | ||
AG | 266 (44.56) | 291 (46.94) | ||||
GG | 52 (8.71) | 124 (20.00) | ||||
rs2300525 (T>C) | 0.68 | |||||
T | 836 (70.02) | 909 (73.31) | 3.24 | 0.072 | ||
C | 358 (29.98) | 331 (26.69) | ||||
TT | 297 (49.75) | 335 (54.03) | 3.26 | 0.196 | ||
CT | 242 (40.54) | 239 (38.55) | ||||
CC | 58 (9.71) | 46 (7.42) | ||||
0.61 | ||||||
T | 913 (76.47) | 1001 (80.73) | 6.57 | 0.010 | ||
C | 281 (23.53) | 239 (19.27) | ||||
TT | 355 (59.46) | 406 (65.48) | 6.55 | 0.038 | ||
CT | 203 (34.00) | 189 (30.48) | ||||
CC | 39 (6.54) | 25 (4.04) | ||||
CTLA-4 | rs231804 (A>G) | 1.00 | ||||
A | 1031 (86.35) | 1036 (83.55) | 3.72 | 0.054 | ||
G | 163 (13.65) | 204 (16.45) | ||||
AA | 447 (74.87) | 432 (69.68) | 4.10 | 0.129 | ||
AG | 137 (22.95) | 172 (27.74) | ||||
GG | 13 (2.18) | 16 (2.58) | ||||
rs1024161 (A>G) | 0.44 | |||||
A | 876 (73.37) | 868 (70.00) | 3.40 | 0.065 | ||
G | 318 (26.63) | 372 (30.00) | ||||
AA | 326 (54.61) | 308 (49.68) | 3.30 | 0.192 | ||
AG | 224 (37.52) | 252 (40.65) | ||||
GG | 47 (7.87) | 60 (9.67) | ||||
0.79 | ||||||
A | 813 (68.09) | 794 (64.03) | 4.47 | 0.035 | ||
G | 381 (31.91) | 446 (35.97) | ||||
AA | 283 (47.40) | 256 (41.29) | 4.75 | 0.093 | ||
AG | 247 (41.37) | 282 (45.48) | ||||
GG | 67 (11.23) | 82 (13.23) | ||||
rs10197319 (C>T) | 0.45 | |||||
C | 937 (78.48) | 938 (75.65) | 2.76 | 0.097 | ||
T | 257 (21.52) | 302 (24.35) | ||||
CC | 367 (61.48) | 351 (56.61) | 3.00 | 0.223 | ||
CT | 203 (34.00) | 236 (38.07) | ||||
TT | 27 (4.52) | 33 (5.32) |
HWE: Hardy-Weinberg equilibrium;
In the TSHR gene, there was no difference in the distribution of alleles or genotypes at rs2300525 between the case group and the control group (
In the CTLA-4 gene, there was no difference in the distribution of alleles or genotypes at sites rs231804, rs1024161, or rs10197319 between the case group and the control group (
After adjusting for age, a correlation analysis of the association between these ten SNPs and GD revealed that rs179247-G, rs12101261-C, and rs4903964-G were negatively correlated with the incidence of GD in both the male and female populations. In addition, rs2284722-A and rs17111394-C were positively correlated with the incidence of GD in the overall and female populations, while rs2300525-C was positively correlated with the incidence of GD only in the female population. CTLA-4 rs231726-G was negatively correlated with the risk of GD in the overall population. In the dominant model of rs10197319, TT+CT carriers had a higher risk of GD in the overall and male populations than those with the homozygous CC genotype (Table
Multifactor logistic regression analyzes the correlation of TSHR and CTLA-4 SNPs with GD.
SNPs | Alleles | Dominant model | Recessive model | Homozygous model | Heterozygous model | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | ||||||||
TSHR | G/A | GG+AG/AA | GG/AG+AA | GG/AA | AG/AA | |||||||
TP | 0.57 (0.48, 0.68) | <0.001 |
0.50 (0.40, 0.63) | <0.001 |
0.50 (0.34, 0.73) | <0.001 |
0.37 (0.25, 0.55) | <0.001 |
0.54 (0.42, 0.68) | <0.001 | ||
Sex | M | 0.56 (0.38, 0.84) | 0.005 |
0.57 (0.34, 0.95) | 0.030 |
0.30 (0.11, 0.80) | 0.016 |
0.25 (0.09, 0.69) | 0.007 |
0.67 (0.39, 1.15) | 0.148 | |
F | 0.57 (0.47, 0.70) | <0.001 |
0.48 (0.37, 0.62) | <0.001 |
0.55 (0.36, 0.83) | 0.005 |
0.40 (0.26, 0.62) | <0.001 |
0.51 (0.39, 0.66) | <0.001 | ||
A/G | AA+AG/GG | AA/AG+GG | AA/GG | AG/GG | ||||||||
TP | 1.34 (1.12, 1.60) | 0.001 |
1.33 (1.06, 1.67) | 0.013 |
2.14 (1.34, 3.42) | 0.002 |
2.33 (1.44, 3.78) | 0.001 |
1.22 (0.96, 1.55) | 0.097 | ||
Sex | M | 0.91 (0.61, 1.38) | 0.669 | 0.90 (0.54, 1.51) | 0.694 | 0.88 (0.34, 2.30) | 0.797 | 0.85 (0.32, 2.28) | 0.748 | 0.91 (0.53, 1.57) | 0.744 | |
F | 1.47 (1.21, 1.80) | <0.001 |
1.46 (1.14, 1.88) | 0.003 |
2.79 (1.61, 4.83) | <0.001 |
3.15 (1.79, 5.53) | <0.001 |
1.31 (1.01, 1.70) | 0.046 | ||
C/T | CC+CT/TT | CC/CT+TT | CC/TT | CT/TT | ||||||||
TP | 0.58 (0.49, 0.69) | <0.001 |
0.53 (0.42, 0.66) | <0.001 |
0.44 (0.30, 0.63) | <0.001 |
0.34 (0.23, 0.50) | <0.001 |
0.59 (0.46, 0.75) | <0.001 | ||
Sex | M | 0.58 (0.40, 0.86) | 0.006 |
0.54 (0.32, 0.90) | 0.018 |
0.43 (0.18, 1.01) | 0.053 | 0.34 (0.14, 0.82) | 0.017 |
0.60 (0.35, 1.04) | 0.066 | |
F | 0.58 (0.48, 0.70) | <0.001 |
0.52 (0.41, 0.68) | <0.001 |
0.44 (0.29, 0.66) | <0.001 |
0.34 (0.22, 0.52) | <0.001 |
0.59 (0.45, 0.77) | <0.001 | ||
G/A | GG+AG/AA | GG/AG+AA | GG/AA | AG/AA | ||||||||
TP | 0.58 (0.50, 0.69) | <0.001 |
0.57 (0.45, 0.71) | <0.001 |
0.38 (0.27, 0.54) | <0.001 |
0.31 (0.21, 0.45) | <0.001 |
0.67 (0.53, 0.86) | 0.020 | ||
Sex | M | 0.60 (0.41, 0.87) | 0.008 |
0.56 (0.33, 0.94) | 0.027 |
0.46 (0.21, 0.98) | 0.044 |
0.36 (0.16, 0.82) | 0.014 |
0.64 (0.37, 1.10) | 0.107 | |
F | 0.58 (0.48, 0.70) | <0.001 |
0.57 (0.44, 0.74) | <0.001 |
0.37 (0.25, 0.54) | <0.001 |
0.30 (0.20, 0.45) | <0.001 |
0.68 (0.52, 0.90) | 0.007 | ||
rs2300525 | C/T | CC+CT/TT | CC/CT+TT | CC/TT | CT/TT | |||||||
TP | 1.18 (0.99, 1.40) | 0.072 | 1.18 (0.95, 1.48) | 0.143 | 1.34 (0.90, 2.01) | 0.154 | 1.42 (0.93, 2.15) | 0.101 | 1.14 (0.90, 1.44) | 0.288 | ||
Sex | M | 0.92 (0.62, 1.36) | 0.668 | 0.87 (0.53, 1.45) | 0.600 | 0.98 (0.40, 2.39) | 0.959 | 0.91 (0.36, 2.32) | 0.849 | 0.87 (0.51, 1.47) | 0.593 | |
F | 1.25 (1.03, 1.52) | 0.028 |
1.28 (0.99, 1.64) | 0.058 | 1.45 (0.92, 2.29) | 0.106 | 1.58 (0.99, 2.52) | 0.055 | 1.22 (0.93, 1.59) | 0.146 | ||
C/T | CC+CT/TT | CC/CT+TT | CC/TT | CT/TT | ||||||||
TP | 1.29 (1.06, 1.57) | 0.010 |
1.29 (1.02, 1.63) | 0.031 |
1.66 (0.99, 2.78) | 0.055 | 1.78 (1.05, 3.00) | 0.031 |
1.22 (0.96, 1.56) | 0.111 | ||
Sex | M | 1.02 (0.66, 1.57) | 0.934 | 1.06 (0.63, 1.78) | 0.834 | 0.88 (0.30, 2.60) | 0.822 | 0.91 (0.30, 2.72) | 0.865 | 1.06 (0.61, 1.82) | 0.844 | |
F | 1.37 (1.10, 1.70) | 0.005 |
1.36 (1.05, 1.76) | 0.021 |
1.99 (1.10, 3.59) | 0.023 |
2.15 (1.18, 3.91) | 0.012 |
1.26 (0.96, 1.66) | 0.092 | ||
CTLA-4 | rs231804 | G/A | GG+AG/AA | GG/AG+AA | GG/AA | AG/AA | ||||||
TP | 0.80 (0.64, 1.00) | 0.054 | 0.77 (0.60, 1.00) | 0.045 | 0.86 (0.41, 1.80) | 0.680 | 0.80 (0.38, 1.86) | 0.556 | 0.77 (0.59, 1.00) | 0.050 | ||
Sex | M | 0.66 (0.39, 1.11) | 0.116 | 0.69 (0.39, 1.23) | 0.203 | — | — | — | — | 0.75 (0.42, 1.36) | 0.346 | |
F | 0.84 (0.66, 1.08) | 0.176 | 0.80 (0.60, 1.05) | 0.108 | 1.08 (0.50, 2.36) | 0.845 | 1.01 (0.46, 2.21) | 0.977 | 0.78 (0.58, 1.04) | 0.086 | ||
rs1024161 | G/A | GG+AG/AA | GG/AG+AA | GG/AA | AG/AA | |||||||
TP | 0.85 (0.71, 1.01) | 0.065 | 0.82 (0.66, 1.03) | 0.085 | 0.81 (0.54, 1.20) | 0.293 | 0.75 (0.49, 1.13) | 0.162 | 0.84 (0.66, 1.06) | 0.145 | ||
Sex | M | 0.93 (0.62, 1.39) | 0.712 | 0.94 (0.57, 1.57) | 0.825 | 0.77 (0.27, 2.18) | 0.617 | 0.76 (0.26, 2.22) | 0.612 | 0.98 (0.58, 1.65) | 0.929 | |
F | 0.83 (0.68, 1.01) | 0.065 | 0.79 (0.62, 1.02) | 0.070 | 0.81 (0.53, 1.26) | 0.351 | 0.74 (0.48, 1.16) | 0.192 | 0.81 (0.62, 1.05) | 0.112 | ||
rs231726 | G/A | GG+AG/AA | GG/AG+AA | GG/AA | AG/AA | |||||||
TP | 0.83 (0.59, 1.18) | 0.300 | 0.74 (0.52, 1.07) | 0.108 | 0.79 (0.62, 1.01) | 0.055 | ||||||
Sex | M | 0.76 (0.52, 1.12) | 0.163 | 0.74 (0.44, 1.23) | 0.248 | 0.62 (0.27, 1.41) | 0.254 | 0.55 (0.23, 1.31) | 0.177 | 0.79 (0.46, 1.36) | 0.398 | |
F | 0.85 (0.71, 1.03) | 0.097 | 0.79 (0.61, 1.02) | 0.067 | 0.89 (0.61, 1.30) | 0.541 | 0.79 (0.53, 1.18) | 0.252 | 0.79 (0.60, 1.03) | 0.084 | ||
rs10197319 | T/C | TT+CT/CC | TT/CT+CC | TT/CC | CT/CC | |||||||
TP | 0.85 (0.70, 1.03) | 0.097 | 0.85 (0.51, 1.43) | 0.543 | 0.75 (0.44, 1.28) | 0.291 | ||||||
Sex | M | 0.94 (0.62, 1.45) | 0.793 | 1.12 (0.29, 4.27) | 0.872 | 0.78 (0.20, 3.03) | 0.725 | |||||
F | 0.83 (0.67, 1.03) | 0.085 | 0.80 (0.62, 1.03) | 0.080 | 0.81 (0.46, 1.43) | 0.466 | 0.75 (0.42, 1.33) | 0.319 | 0.80 (0.62, 1.05) | 0.107 |
TP: total population; M: male; F: female;
The linkage disequilibrium analysis of the tested polymorphisms in TSHR and CTLA-4 revealed that four TSHR SNPs rs179247, rs2284722, rs12101261, and rs4903964, two SNPs (rs2300525 and rs17111394), and three SNPs in CTLA-4 (rs231804, rs1024161, and rs231726), respectively, formed three haplotype regions, each with a linkage disequilibrium coefficient
TSHR and CTLA-4 linkage disequilibrium analysis diagram (
TSHR and CTLA-4 linkage disequilibrium analysis diagram (
Linkage disequilibrium analysis of 4 loci and 2 loci of the TSHR gene and 3 loci of the CTLA-4 gene.
rs179247 | rs2284722 | rs12101261 | rs4903964 | ||
---|---|---|---|---|---|
rs179247 | — | ||||
rs2284722 | 0.121 | — | |||
rs12101261 | 0.832 | 0.134 | — | ||
rs4903964 | 0.562 | 0.141 | 0.645 | — | |
rs2300525 | rs17111394 | ||||
rs2300525 | — | ||||
rs17111394 | 0.657 | — | |||
rs231804 | rs1024161 | rs231726 | |||
rs231804 | — | ||||
rs1024161 | 0.437 | — | |||
rs231726 | 0.338 | 0.758 | — |
The italic part represents
Eight different haplotypes were identified based on the rs179247, rs2284722, rs12101261, and rs4903964 sites in the TSHR gene. The TSHR sites rs2300525 and rs17111394 composed three different haplotypes, while four different haplotypes were identified based on the rs231804, rs1024161, and rs231726 alleles of CTLA-4. The relationship between these haplotypes and GD revealed that haplotypes AGTA, GGCG, and AATA, haplotype CC, and haplotype AAA, respectively, were associated with the risk of GD (Table
The relationship between haplotypes and GD.
SNP | Haplotype | Case group | Control group | OR (95% CI) | |||
---|---|---|---|---|---|---|---|
% | % | ||||||
rs179247 | 224 | 37.6 | 200 | 32.2 | 1.27 (1.07, 1.50) | 0.005 | |
rs2284722 | 127 | 21.3 | 203 | 32.7 | 0.56 (0.46, 0.67) | <0.001 | |
rs12101261 | 168 | 28.2 | 132 | 21.3 | 1.45 (1.21, 1.75) | <0.001 | |
rs4903964 | AGTG | 32 | 5.3 | 33 | 5.3 | 1.00 (0.70, 1.43) | 0.997 |
AGCG | 14 | 2.4 | 16 | 2.6 | 0.94 (0.57, 1.57) | 0.820 | |
GGCA | 11 | 1.9 | 10 | 1.6 | 1.20 (0.66, 2.20) | 0.548 | |
AATG | 6 | 1.0 | 8 | 1.3 | 0.76 (0.36, 1.64) | 0.488 | |
GACG | 4 | 0.6 | 9 | 1.5 | 0.40 (0.18, 0.92) | 0.031 | |
rs2300525 | TT | 417 | 69.8 | 451 | 72.8 | 0.86 (0.73, 1.03) | 0.105 |
rs17111394 | 139 | 23.3 | 117 | 18.8 | 1.32 (1.08, 1.60) | 0.006 | |
CT | 39 | 6.6 | 49 | 7.9 | 0.83 (0.61, 1.12) | 0.223 | |
rs231804 | 405 | 67.9 | 395 | 63.7 | 1.21 (1.02, 1.43) | 0.029 | |
rs1024161 | GGG | 81 | 13.5 | 102 | 16.4 | 0.80 (0.64, 1.00) | 0.046 |
rs231726 | AGG | 79 | 13.2 | 83 | 13.4 | 0.98 (0.78, 1.24) | 0.863 |
AAG | 32 | 5.3 | 38 | 6.2 | 0.84 (0.60, 1.19) | 0.323 |
Four of the eight haplotypes (composed of rs179247, rs2284722, rs12101261, and rs4903964) had frequencies greater than 0.03. There are four haplotypes (composed of rs231804, rs1024161, and rs231726) that had frequencies greater than 0.03.
Correlation between TSHR and CTLA-4 SNPs and clinical phenotypes.
Goiter | Exophthalmos | TRAb (U/L) | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
SNP | Genotype | 0 | I | II | III | Yes | No | ≥1.5 | <1.5 | |||||||
TSHR | rs179247 | AA | 7 | 99 | 232 | 4 | 3.67 | 0.30 | 150 | 192 | 1.11 | 0.57 | 274 | 47 | 4.23 | 0.12 |
AG | 7 | 71 | 127 | 6 | 83 | 128 | 153 | 40 | ||||||||
GG | 1 | 16 | 27 | 0 | 19 | 25 | 29 | 9 | ||||||||
rs2284722 | GG | 9 | 81 | 197 | 4 | 1.10 | 0.78 | 119 | 172 | 0.41 | 0.82 | 215 | 53 | 2.72 | 0.26 | |
AG | 6 | 87 | 153 | 5 | 109 | 142 | 194 | 37 | ||||||||
AA | 0 | 18 | 36 | 55 | 24 | 31 | 47 | 6 | ||||||||
rs12101261 | TT | 7 | 103 | 204 | 6 | 3.14 | 0.37 | 136 | 184 | 0.17 | 0.92 | 260 | 43 | 4.84 | 0.09 | |
CT | 6 | 68 | 154 | 4 | 96 | 136 | 164 | 45 | ||||||||
CC | 2 | 15 | 28 | 0 | 20 | 25 | 32 | 8 | ||||||||
rs4903964 | AA | 7 | 86 | 179 | 7 | 2.61 | 0.46 | 121 | 158 | 0.32 | 0.85 | 226 | 36 | 5.60 | 0.06 | |
AG | 5 | 83 | 175 | 3 | 109 | 157 | 192 | 53 | ||||||||
GG | 3 | 17 | 32 | 0 | 22 | 30 | 38 | 7 | ||||||||
rs2300525 | TT | 8 | 90 | 195 | 4 | 3.48 | 0.32 | 129 | 168 | 1.62 | 0.45 | 227 | 49 | 0.11 | 0.95 | |
CT | 5 | 76 | 155 | 6 | 103 | 139 | 184 | 37 | ||||||||
CC | 2 | 20 | 36 | 0 | 20 | 38 | 45 | 10 | ||||||||
rs17111394 | TT | 10 | 111 | 230 | 4 | 2.87 | 0.41 | 153 | 202 | 2.24 | 0.33 | 267 | 63 | 4.42 | 0.11 | |
CT | 4 | 58 | 135 | 6 | 87 | 116 | 161 | 24 | ||||||||
CC | 1 | 17 | 21 | 0 | 12 | 27 | 28 | 9 | ||||||||
CTLA-4 | rs231804 | AA | 12 | 138 | 288 | 9 | 1.54 | 0.67 | 187 | 260 | 1.03 | 0.60 | 345 | 72 | 0.50 | 0.78 |
AG | 3 | 45 | 88 | 1 | 61 | 76 | 102 | 21 | ||||||||
GG | 0 | 3 | 10 | 0 | 4 | 9 | 9 | 3 | ||||||||
rs1024161 | AA | 11 | 101 | 207 | 7 | 2.56 | 0.46 | 140 | 186 | 0.78 | 0.68 | 250 | 53 | 1.51 | 0.47 | |
AG | 2 | 69 | 150 | 3 | 95 | 129 | 174 | 33 | ||||||||
GG | 2 | 16 | 29 | 0 | 17 | 30 | 32 | 10 | ||||||||
rs231726 | AA | 9 | 86 | 184 | 4 | 0.70 | 0.87 | 123 | 160 | 0.84 | 0.66 | 218 | 46 | 0.84 | 0.66 | |
AG | 4 | 81 | 157 | 5 | 104 | 143 | 190 | 37 | ||||||||
GG | 2 | 19 | 45 | 1 | 25 | 42 | 48 | 13 | ||||||||
rs10197319 | CC | 12 | 108 | 239 | 8 | 4.78 | 0.19 | 157 | 210 | 0.71 | 0.70 | 282 | 58 | 0.14 | 0.93 | |
CT | 3 | 69 | 129 | 2 | 82 | 121 | 153 | 34 | ||||||||
TT | 0 | 9 | 18 | 0 | 13 | 14 | 21 | 4 |
Using MDR analysis of TSHR and CTLA-4 multiple site interaction yielded a significance of
MDR analysis of TSHR and CTLA-4 multiple site interaction model.
Model | Training set balance precision | Test set balance precision | Cross-validation consistency | OR (95% CI) | |
---|---|---|---|---|---|
rs179247 | 0.5864 | 0.5864 | 10/10 | 0.0565 | 2.01 (0.98, 4.14) |
rs179247, rs4903964 | 0.5919 | 0.5734 | 6/10 | 0.1053 | 1.81 (0.88, 3.71) |
rs179247, rs4903964, rs10197319 | 0.6074 | 0.5706 | 5/10 | 0.1193 | 1.77 (0.86, 3.62) |
False-positive report probability.
SNP | OR (95% CI) | Prior probability | |||
---|---|---|---|---|---|
0.25 | 0.1 | 0.01 | 0.001 | ||
rs179247 | 0.57 (0.48, 0.68) | <0.001 | <0.001 | <0.001 | <0.001 |
rs2284722 | 1.34 (1.12, 1.60) | 0.004 | 0.012 | 0.119 | 0.576 |
rs12101261 | 0.58 (0.49, 0.69) | <0.001 | <0.001 | <0.001 | <0.001 |
rs4903964 | 0.58 (0.50, 0.69) | <0.001 | <0.001 | <0.001 | <0.001 |
rs17111394 | 1.29 (1.06, 1.57) | 0.034 | 0.096 | 0.540 | 0.922 |
rs231726 | 0.83 (0.71, 0.99) | 0.104 | 0.258 | 0.792 | 0.975 |
Preset the critical
GD is a common autoimmune thyroid disease. The prevalence of clinical hyperthyroidism in China is about 0.8%, and 80% of these cases are the result of GD. GD develops as a consequence of complex interactions between genetic, environmental, and immunological factors. TRAb is the most frequently encountered autoantibodies in those with GD (present in >90% of patients), and it can compete with TSH for TSHR binding. TSAb is a pathogenic antibody associated with GD, and recent work has shown that TSAb is linked with oxidative stress present in those with GD [
We confirmed that all 6 TSHR SNPS and all 4 CTLA-4 SNPs conformed to the Hardy-Weinberg equilibrium, indicating that our research subjects were a good representative population (
We next analyzed the correlation of the six studied TSHR SNPs with GD, and through different analysis models, we identified the risk alleles and genotypes for GD associated with these sites.
For TSHR site rs179247, GD patients had a higher frequency of the A allele than healthy controls, and this allele was found to be the primary risk factor. In contrast, the G allele was negatively correlated with GD in the total population and in the individual male and female populations. Bufalo et al. demonstrated that TSHR intronic polymorphisms are associated with GD and Graves’ ophthalmopathy susceptibility in a Brazilian population, with the AA genotype for rs179247 increasing GD risk [
Several meta-analyses of this site have reported that it is associated with GD [
In our study, the main GD risk factor at site rs2284722 was the A allele; A alleles were positively correlated with GD incidence in both the total population and the female population, and the AA genotype was associated with a higher risk for GD, especially in females.
For TSHR site rs12101261, the C alleles were negatively correlated with the incidence of GD in the total population, the male population, and the female population. The GD main risk factor for rs12101261 was the T alleles. There have been reports identifying this site as a possible causal SNP for GD susceptibility in the TSHR gene, potentially serving as a genetic marker to predict the outcome of persistent TSHR autoantibody positivity in GD patients [
The main GD risk factors for rs4903964 were the A alleles; the G alleles were negatively correlated with the incidence of GD in the total population, the male population, and the female population.
There were no difference in the distribution of alleles or genotypes at rs2300525 between the case group and the control group (
For TSHR site rs17111394, the C alleles were positively correlated with the incidence of GD in the total population and the female population. The risk of GD in mutant homozygous carriers was 1.78x and 2.15x, respectively, relative to homozygous TT carriers.
Linkage disequilibrium is a measure of the correlation between alleles at different loci. The linkage disequilibrium analysis of the four TSHR SNP sites rs179247, rs2284722, rs12101261, and rs4903964 and the linkage disequilibrium coefficient
The TSHR SNPs rs179247, rs2284722, rs12101261, and rs4903964 together formed 8 distinct haplotypes. We analyzed the relationship between these haplotypes and GD. Haplotypes AGTA, GGCG, and AATA were the most frequent of all haplotypes, accounting for more than 80 percent of the entire population. There was a positive correlation between GD risk and haplotypes AGTA and AATA. The risk was negatively correlated with the haplotypes GGCG and GACG; however, the GACG haplotype was a very small percentage of the study population. No association with GD was found for the other haplotypes (
As for CTLA-4, there was no difference in the distribution of genotypes at four sites on the CTLA-4 gene between the case group and the control group (
We further analyzed the relationship between GD and the haplotypes formed by CTLA-4 SNP sites rs231804, rs1024161, and rs231726. A positive correlation was identified between haplotype AAA and GD risk (
We analyzed comparisons between TSHR and CTLA-4 genotypes and clinical GD characteristics such as diffuse goiter, exophthalmos, and different levels of TRAb, but we did not identify any correlations between these variables (
GD is a complex disease triggered by multiple genes and other factors. The information provided by a single SNP site is thus very limited in the study of such complex diseases. The variation and the interaction between multiple SNP sites are what ultimately lead to the development of such complex diseases. The pathogenesis of GD is related to the interaction between genes and the environment [
We calculated the FPRP for the TSHR and CTLA-4 SNPS significantly associated with GD, yielding
In conclusion, genetic factors play an important role in the development of GD. The five studied SNPs in TSHR intron 1 and the linkage disequilibrium haplotype composed of those related loci were all associated with GD. Only one linkage disequilibrium haplotype (AAA, composed of CTLA-4 sites rs231804, rs1024161, and rs231726) was found to be related to GD.
Previously, functional SNPs associated with diseases have been found to be more concentrated in the regulatory or coding regions of the genome. In contrast, most SNPs in the noncoding regions of the genome have been ignored by researchers. Most detected SNPs are normal variants and do not have biological functions. In spite of the fact that these SNPs function weakly or are even nonfunctional, their combinations often show a good correlation with disease or related phenotypes. To detect different specific SNP combinations associated with disease groups and to analyze the combination of these SNPs, it is possible to determine the indicators of disease sensitivity and predict therapeutic efficacy with the goal of improving early treatment and prevention. There have been many reports regarding the relationship between TSHR and CTLA-4 and GD in different populations [
The genotype data used to support the findings of this study are restricted by the Medical Ethics Committee of The First Affiliated Hospital of Bengbu Medical College in order to protect patient privacy. Data are available from the author
No competing interests exist.
Weihua Sun and Xiaomei Zhang contributed equally to this work.
We are grateful to our patients and healthy volunteers for donating blood for our study as well as for their agreement for using their data for this study. This work was supported by the Anhui Provincial Department of Education Key Projects (KJ2013A187).