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Article

Investigation of the Correlation between Graves’ Ophthalmopathy and CTLA4 Gene Polymorphism

1
Department of Laboratory Medicine, Chang Gung Memorial Hospital at Linkou, Taoyuan 33305, Taiwan
2
Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
3
Medical Biotechnology and Laboratory Science, Chang Gung University, Taoyuan 33302, Taiwan
4
Department of ophthalmology, Chang Gung Memorial Hospital at Linkou, Taoyuan 33305, Taiwan
5
Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
6
Department of Life Science, Fu Jen University, Taipei 24205, Taiwan
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
J. Clin. Med. 2019, 8(11), 1842; https://doi.org/10.3390/jcm8111842
Submission received: 9 October 2019 / Revised: 25 October 2019 / Accepted: 26 October 2019 / Published: 2 November 2019
(This article belongs to the Section Immunology)

Abstract

:
Graves’ disease (GD) is an autoimmune inflammatory disease, and Graves’ ophthalmopathy (GO) occurs in 25–50% of patients with GD. Several susceptible genes were identified to be associated with GO in some genetic analysis studies, including the immune regulatory gene CTLA4. We aimed to find out the correlation of CTLA4 gene polymorphism and GO. A total of 42 participants were enrolled in this study, consisting of 22 patients with GO and 20 healthy controls. Chi-square or Fisher’s exact test were used to appraise the association between Graves’ ophthalmopathy and CTLA4 single nucleotide polymorphisms (SNPs). All regions of CTLA4 including promoter, exon and 3’UTR were investigated. There was no nucleotide substitution in exon 2 and exon 3 of CTLA4 region, and the allele frequencies of CTLA4 polymorphisms had no significant difference between patients with GO and controls. However, the genotype frequency of “TT” genotype in rs733618 significantly differed between patients with GO and healthy controls (OR = 0.421, 95%CI: 0.290–0.611, p = 0.043), and the “CC” and “CT” genotype in rs16840252 were nearly significantly differed in genotype frequency (p = 0.052). Haplotype analysis showed that CTLA4 Crs733618Crs16840252 might increase the risk of GO (OR = 2.375, 95%CI: 1.636–3.448, p = 0.043). In conclusion, CTLA4 Crs733618Crs16840252 was found to be a potential marker for GO, and these haplotypes would be ethnicity-specific. Clinical application of CTLA4 Crs733618Crs16840252 in predicting GO in GD patients may be beneficial.

1. Introduction

Graves’ disease (GD) is an autoimmune inflammatory disease. The annual incidence of Graves’ disease is 20 to 50 cases per 100,000 persons [1]. Graves’ ophthalmopathy (GO) also called thyroid eye disease occurs in 25–50% of patients suffered from GD [2]. The reported prevalence rates of Graves’ ophthalmopathy among different ethnic populations are limited. An early study demonstrated 6.4 times higher risk of developing GO in Caucasians than that of Asians [3] but has been criticized for a small sample size. Recent studies reported similar prevalence rate in Malaysians (Malay, Chinese, and Indian) [4] and Indians [5] with GD as compared with Caucasian GD patients. The clinical presentation of GO includes eyelid retraction, restrictive extraocular myopathy, proptosis, glaucoma, exposure keratitis and compressive optic neuropathy [6]. Patients may experience frequent diplopia, dry eye, chemosis, eyelid swelling and even vision loss in severe cases [7]. Additionally, patients with Graves’ disease tend to have concomitant hyperthyroidism.
Genetic analysis has identified several susceptible genes, including genes encoding thyroglobulin, thyrotropin receptor, HLA-DRβ-Arg74, protein tyrosine phosphatase nonreceptor type 22 (PTPN22), cytotoxic T-lymphocyte–associated antigen 4 (CTLA4), CD25, and CD40 [8]. Recent studies have identified circulating autoantibodies which target the thyroid-stimulating hormone receptor and insulin-like growth factor-1 receptor on the orbital fibroblasts [9,10]. Further activation of inflammatory genes leads to overproduction of cytokines, chemoattractants, hyaluronan and glycosaminoglycan, which results in orbital inflammation in the early phase and tissue hypertrophy in the late phase [11]. The expression level of these gene associated with GD and inflammation would different according to their genotype, and further study on genetic polymorphism in these genes would predict prognosis or complications in GD patients.
Treatment of GO varies according to the disease severity [12]. Establishing a euthyroid state and quitting smoking are helpful [13]. Active inflammatory phase often requires corticosteroids or other immunosuppressants to reduce orbital congestion [14]. Early intervention and close monitoring may hamper the progression and the severity of the disease [15]. It would be beneficial to find biomarkers early predicting severe GO in GD patients. Herein, all regions of CTLA4 including promoter, exon and 3′UTR were investigated to find the correlation of CTLA4 gene polymorphism and GO.

2. Experimental Section

2.1. Study Subjects

Twenty-two patients with GO (46.2 ± 16.5 years old, eight males and fourteen females) and 20 healthy controls (28.3 years old, 5 males and 15 females) were included in Linkou Chang Gung Memorial Hospital during the period from June 2017 to May 2019.

2.2. DNA Extraction

The blood samples were collected in EDTA-coated vacuum tubes. The genomic DNA was extracted using QIAamp® DNA Mini kit (Qiagen GmbH, Hilden, Germany) according to the manufacturer’s instructions. DNA concentration and purity were evaluated by measuring the optical density at 260 and 280 nm through UV spectrometer.

2.3. PCR Amplification

The PCR mixture contained 1 µL DNA, 10µL HotStarTaq DNA Polymerase (Qiagen GmbH, Hilden, Germany), 1 µL forward primer (10 µM), 1 µL reverse primer (10 µM) and 12 µL ddH2O. Table 1 displayed the primers used in the present study. The PCR program for promoter and exon 1 was 1 cycle 95 °C for 10 min, 35 cycles of 94 °C for 30 sec, 65.5 °C for 30 sec, and 72 °C for 1 min. The PCR program for exon 2, exon 3, exon 4, and 3′UTR was 1 cycle 95 °C for 10 min, 35 cycles of 94 °C for 30 s, 59 °C for 30 s, and 72 °C for 1 min. The final elongation step was 3 min at 72 °C and then soaking at 10 °C. For gel electrophoresis visualization, 5 μL of the PCR products was pipetted onto a 1.5% agarose gel and run at 100 V for 20 min. Correct PCR products were visualized under UV illumination.

2.4. Purifying and Sequencing

The PCR production was purified by mixture containing 2.5 µL shrimp alkaline phosphatase and 0.05 µL exonuclease I (New England Biolabs, UK), and the purified PCR products were sequenced using ABI PRISM 3730 DNA Analyzer (Applied Biosystems, Foster City, CA, USA). Single nucleotide polymorphisms (SNPs) analysis were performed on CTLA4 gene, and rs11571315, rs733618, rs4553808, rs11571316, rs62182595, rs16840252, rs5742909, rs231775, and rs3087243 were selected for genotyping.

2.5. Statistical Analysis

All statistical data analyses were performed by the SPSS 17.0. Genotype and allele frequencies of CTLA4 gene for patients with GO were compared to healthy controls. Chi-square or Fisher’s exact test were used to evaluate the association between GO and CTLA4 SNPs.

3. Results

Among 22 GO patients, there were 14 females and 8 males, and the average age of patients was 46 years old. Moreover, half of GO patients was moderate in severity categories [16], and the most common symptom of GO patients was proptosis. The characteristics of patients were shown in Table 2.
The severity of GO was classified via the criterion proposed by Werner [6]. Class 0 to class 2 were classified as “mild”, class 3 and class 4 were classified as “moderate”, class 5 and class 6 were classified as “severe”.
All SNPs were in accordance with the Hardy-Weinberg equilibrium in the control group (p > 0.05) (Table 3). There was no nucleotide substitution in exon 2 and exon 3 of CTLA4 region, and the allele frequencies of CTLA4 polymorphisms had no significant difference between patients with GO and controls. However, the genotype frequency (Table 4) of “TT” genotype in rs733618 significantly differed between patients with GO and healthy controls (OR = 0.421, 95%CI: 0.290–0.611, p = 0.043), and the “CC” and “CT” genotype in rs16840252 were nearly significantly differed in genotype frequency (p = 0.052). Haplotype analysis (Table 5) showed that CTLA4 Crs733618Crs16840252 might increase the risk of GO (OR = 2.375, 95%CI: 1.636-3.448, p = 0.043).
Our data suggested that the genotype of −1722 (rs733618) in the promoter region of CTLA4 was associated with GO, the p value of TT vs. (CT + CC) was 0.043. We further combined −1722 (rs733618) and −1147 (rs16840252) together to observe the correlation between GO and controls, because the genotype of −1147 was very close to the critical point, p = 0.052. As a result, the two-marker combination was found to be more significantly related to GO (p = 0.025).

4. Discussion

Previous research had found that rs733618 [17], rs231775 [17], rs3087243 [18,19] and a two-marker combination containing rs733618 and rs16840252 [17] were related to GD. Our results showed that rs733618 was specifically related to GO. Comparing family-based research [17] to our results, only rs733618 in promoter was related to GO but not rs231775 in exon 1, and it indicated that major transcription level of CTLA4 was affected by SNPs in promoter region. Moreover, SNPs in exon 1 did not lead to significant reduced protein expression [20]. Therefore, rs733618 were associated with GD and GO, and “TT” genotype of rs733618 which was found to increasing the risk of GO in our study may affect major transcription level of CTLA4.
W. Tang et al., used expectation-maximization (EM) algorithm to create several feasible haplotypes, and haplotype compounded of Grs733618Crs16840252Ars231775Grs3087243 was associated with gastric cardia adenocarcinoma (p = 0.012) [21]. Our results indicated that Crs733618Crs16840252 was related to GO. Therefore, these two SNPs might be involved in both cancer and autoimmune disease. The immune dysfunction would be affected by CTLA4 genetic variation, and the risk of cancer and the development of autoimmune disease would be increased [22]. The rs16840252 mutation would increase the risk of cancer as well [23]. The most central function of CTLA4 is negative regulation of T cell activation, and it is expressed on the surface of activated T cells and competes to B7 with CD28 [24,25]. On the contrary, autoimmune disease would develop by reducing CTLA4 transcription level because of the immune responses are overreacting [26]. Investigation of rs733618 and rs16840252 in T cell activation would uncover the underlying mechanism in development of GO. In Table 6, disease association of rs733618 [23,27,28,29,30,31,32,33,34] and rs16840252 [35,36] were summarized.
Several studies in GD-related CTLA4 SNPs were summarized in Table 7. We found that those GD-related SNPs were located at different positions in the CTLA4 region within different populations. The majority of patients with GD from different ethnicities were associated with rs231775 and/or rs3087243 (Polish [37,38], Chinese [39,40,41,42,43,44], Saudi Arabian [45,46], Iranian [47,48], Italian [49], Japanese [50], and Taiwanese [17,18,19]). However, rs733618 and its relationship with GO have been found merely in Taiwan population. Thus, the correlation between GO and SNPs would diversely result from racial specificity, severity of GO and various inclusion criteria. Further investigation on racial specific GD-related SNPs associated with GO would be indicated.
Herein, Crs733618Crs16840252 of the CTLA4 promoter was shown to be associated with increasing risk of GO. Promoter polymorphism can influence gene transcription, as well as the disease severity [53]. The signal peptide is encoded by exon 1, and mutations in this exon suppress CTLA-4 protein expression [54]. Regulation of mRNA-based processes, such as mRNA localization, mRNA stability, translation, as well as regulation of protein features not encoded in the amino acid sequence are most commonly regulated by 3′UTR [55]. Consequently, there would be other significant SNPs located including but not limited to promoter region associated with GO. Further clinical application for prediction of GO in GD patients needs a feasibility study, and investigation of the mechanism of CTLA4 SNPs and haplotype of GO should be performed.

5. Conclusions

In conclusion, CTLA4 Crs733618Crs16840252 was found to be a potential marker for GO, and these haplotypes would be ethnicity-specific. Clinical application of CTLA4 Crs733618Crs16840252 in predicting GO in GD patients may be beneficial.

Author Contributions

D.-P.C. conceived and designed the experiments, and wrote draft of the manuscript. Y.-C.C. analyzed the data, contributed reagents/materials/analysis tools. Y.-H.W. reviewed literature. W.-T.L. performed the experiments. A.-L.H. analyzed all data. W.-T.W. reviewed and approved the final draft. All authors read and approved the final manuscript.

Funding

This work was supported by the Chang Gung Memorial Hospital grants BMRPA81 to D.P. Chen.

Conflicts of Interest

The authors declare that they have no competing interests.

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Table 1. Primers used for CTLA4 in this study.
Table 1. Primers used for CTLA4 in this study.
PrimerGC ContentTm (°C)Base Pair
promotor and exon1
F: 5′ GGC AAC AGA GAC CCC ACC GTT 3′
R: 5′ GAG GAC CTT CCT TAA ATC TGG AGA G 3′
21/13 (62%)
25/12 (48%)
65.3
65.8
1234
F: 5′ CTC TCC AGA TTT AAG GAA GGT CCT C 3′
R: 5′ GGA ATA CAG AGC CAG CCA AGC C 3′
25/12 (48%)65.81170
22/13 (59%)65.8
Exon2 and exon3
F: 5′ CAT GAG TTC ACT GAG TTC CC 3′
R: 5′ TAC CAC TGT CCT TCC TCT TC 3′
20/10 (50%)58.4 °C1034
20/10 (50%)58.4 °C
Exon4
F: 5′ CTA GGG ACC CAA TAT GTG TTG 3′
R: 5′ AGA AAC ATC CCA GCT CTG TC 3
21/10 (48%)59.5360
20/10 (50%)58.4
3′UTR
F1: 5′ CAG CTA GGG ACC CAA TAT GTG TTG AG 3′
R1: 5′ GTC AAG TCA ACT CAG ATA CCA CCA GC 3′
F2: 5′ GCT TGG AAA CTG GAT GAG GTC ATA GC 3′
R2: 5′ AGA GGA AGA GAC ACA GAC AGA GTT GC 3′
26/13 (50%)59.51088
26/13 (50%)59.5
26/13 (50%)59.51255
26/13 (50%)59.5
F: forward primer; R: reverse primer.
Table 2. Characteristics of patients (n = 22).
Table 2. Characteristics of patients (n = 22).
Total, No. (%)
Median age of the patients46.2 ± 16.5
Sex of the patients
Male8 (36.4)
Female14 (63.6)
Graves’ ophthalmopathy
Mild7 (31.8)
Moderate14 (63.6)
Severe1 (4.6)
Table 3. Allele frequencies in patients and controls and odds ratio of developing Graves’ ophthalmopathy.
Table 3. Allele frequencies in patients and controls and odds ratio of developing Graves’ ophthalmopathy.
SNPPositionAlleleMinor Allele FrequencyHWE p ValueOdds Ratioχ2 p Value
PatientControl(95% CI)
rs11571315203866178C/T0.1810.2750.2371.707 (0.607–4.799)0.308
rs733618203866221T/C0.4090.5000.6701.444 (0.609–3.425)0.403
rs4553808203866282A/G0.0680.1750.6382.899 (0.695–12.091)0.182
rs11571316203866366A/G0.1140.1000.8841.154 (0.287–4.635)1
rs62182595203866465A/G0.0680.1750.6382.899 (0.695–12.091)0.182
rs16840252203866796C/T0.0680.2000.5353.417 (0.838–13.927)0.074
rs5742909203867624C/T0.0680.1750.6382.899 (0.695–12.091)0.182
rs231775203867991A/G0.1820.2750.2371.707 (0.607–4.799)0.308
rs3087243203874196A/G0.1140.1000.8841.154 (0.287–4.635)1
HWE: Hardy-Weinberg equilibrium; 95%CI: 95% confidence interval.
Table 4. Statistical analysis of CTLA4 (SNPs).
Table 4. Statistical analysis of CTLA4 (SNPs).
SNPGenotypeGenotype FrequencyOdds Ratio (95 % CI)p Value
Patient (n)Control (n)
rs11571315CC00NANA
CT8110.468 (0.136–1.611)p = 0.226
TT1492.139 (0.621–7.370)p = 0.226
rs733618CC440.889 (0.190–4.150)p = 1
CT18123.000 (0.736–12.227)p = 0.118
TT040.421 (0.290–0.611)p = 0.043 **
rs4553808AA19133.410 (0.742–15.677)p = 0.152
AG370.293 (0.064–1.348)p = 0.152
GG00NANA
rs11571316AA00NANA
AG541.176 (0.267–5.176)p = 1
GG17160.850 (0.193–3.739)p =1
rs62182595AA00NANA
AG370.293 (0.064–1.348)p = 0.152
GG19133.410 (0.742–15.677)p = 0.152
rs16840252CC19121.22 (0.932–19.131)p = 0.052 *
CT380.237 (0.052–1.073)p = 0.052 *
TT00NANA
rs5742909CC19133.410 (0.742–15.677)p = 0.152
CT370.293 (0.064–1.348)p = 0.152
TT00NANA
rs231775AA00NANA
AG8110.468 (0.136–1.611)p = 0.226
GG1492.139 (0.621–7.370)p = 0.226
rs3087243AA00NANA
AG541.250 (0.283–5.525)p = 1
GG17160.800 (0.181–3.536)p = 1
95%CI: 95% confidence interval; NA: Not applicable. * indicates p < 0.1, ** indicates p < 0.05.
Table 5. CTLA4 haplotypes and odds ratio of developing Graves’ ophthalmopathy.
Table 5. CTLA4 haplotypes and odds ratio of developing Graves’ ophthalmopathy.
CTLA4 HaplotypesPatient(n) Control (n)OR (95%CI)p Value
Crs733618Crs1684025222162.375 (1.636–3.448) 0.043 **
Crs733618Trs16840252350.474 (0.097–2.307) 0.445
Trs733618Crs1684025218161.125 (0.241–5.252) 1
Trs733618Trs16840252370.293 (0.064–1.348)0.152
OR: odds ratio; 95%CI: 95% confidence interval; NA: Not applicable. ** indicates p < 0.05.
Table 6. Summary of rs733618 and rs16840252-related disease.
Table 6. Summary of rs733618 and rs16840252-related disease.
SNPDiseaseSubjects and ResultsRef.
rs733618Systemic lupusAsian:[23]
erythematosusC allele was strongly associated with SLE and also CC genotype was significantly associated with the risk of SLE, p = 0.000).
Breast cancerChinese:[27]
CC genotype and C allele showed an increased risk of breast cancer (p = 0.030, odds ratio (OR) = 1.457, 95% confidence internal (CI) 1.036–2.051; p = 0.024, OR = 1.214, 95% CI 1.026–1.436, respectively).
Polycystic ovary syndromeChinese Han population:[28]
significantly different between case and control groups in either genotypic or allelic distribution, p = 0.01 and 0.009, respectively.
Survival in patients with sepsisAdult Caucasian patients with sepsis:[29]
lower 90-day mortality was observed for Trs733618 Ars231775 Ars3087243 haplotype-negative patients than for patients carrying the TAA haplotype, p = 0.0265.
Survival in patients with multiple myeloma receiving bortezomib-based regimensUnrelated Chinese Han population: GG genotype reduced the progression-free survival and the overall survival of patients with multiple myeloma who received bortezomib-based therapy, p = 0.002.[30]
Non-small-cell lung cancerChinese:[31]
(NSCLC)T > C polymorphism was associated with the development of NSCLC in ≥60 years and even drinking subgroups.
Myasthenia gravis (MG)Chinese Han population:[32]
C allele were more frequent in MG patients, p = 0.042.
Urinary schistosomiasisGabonese children:[33]
T allele and TT genotype were significantly overrepresented in the patient group, p = 0.001.
Lymphatic filariasis (LF)Sarawak, Malaysia:[34]
CT genotype (p = 0.02) and those with combined minor allele C carriers (CT + CC; p = 0.01) exhibited a significantly decreased risk for LF.
rs16840252Colorectal cancerChinese:[35]
polymorphism was associated with an increased risk of colon cancer in homozygote model p = 0.040 and recessive model p = 0.037.
Recurrent schizophreniaChinese Han population:[36]
A significant association with schizophrenia, p (allele) = 0.0081, p (genotype) = 0.0117.
Table 7. Summary of several studies for CTLA4 SNPs associated with Graves’ disease.
Table 7. Summary of several studies for CTLA4 SNPs associated with Graves’ disease.
SNPSubjectsResultsRef.
rs733617Han population of Taiwan (family-based)C allele over-transmitted to affected individuals (χ2 = 6.714, nominal p = 0.0096).[17]
rs5742909Polish Caucasiangenotype and allele were differentially distributed (p = 0.0002; p = 4.07 × 10−5), and lack of the rare T allele increased GD in patients with familial autoimmune thyroid incidence (p = 0.00005).[37]
Chinesegenotype frequencies of CT and allele frequencies of T were much higher in GD patients with ophthalmopathy than that in the group without ophthalmopathy (p = 0.020, p = 0.019).[39]
Chinesevariant allele carriers might have decreased risks of GD when compared with the homozygote carriers TT + TC vs. CC: OR = 0.78, 95% CI = 0.62–0.97.[44]
rs231775Han population of Taiwan (family-based)CTLA4_+49_G/A (p = 0.0219), with its minor allele (G allele) over-transmitted to affected individuals (χ2 = 5.252, nominal p = 0.0219).[17]
Taiwanesesignificant differences in the frequencies of the genotypes and alleles, p < 0.05.[18]
Polish populationsa significantly lower frequency of the AA genotype in the group of patients with clinically evident GO (p = 0.02, OR = 2.6).[38]
Chinesegenotype GG and allele frequencies of G in patients with Graves’ disease were significantly increased as compared with control group (p = 0.008, p = 0.007).[39]
Han population of Chinese (unrelated)allele G was significantly associated with GD in adults (p < 0.001) and children (p = 0.002)).[40]
Chinese children < 16 years old (unrelated)genotype GG (p = 0.005) and allele G (p = 0.03) were more prevalent in GD.[41]
Chinese childrengenotype and allele frequencies of children with GD differed significantly from those of the controls (p = 0.0023 and p = 0.022, respectively).[42]
Saudi ArabianG allele was more frequent in patients with GD than in the control group, p = 0.003.[45]
IranianG allele was significantly higher in patients with Graves’ disease than in the control group (27.1% vs. 15.1%, OR = 2.096, 95%CI = 1.350–3.253 and p < 0.01).[47]
Iraniana significant increase of GG genotype and G allele was observed in patients (p = 0.012 and p = 0.025, respectively).[48]
ItalianG allele frequency was significantly higher compared to control subjects (p = 0.04).[49]
Caucasian and AsianG allele vs. A allele, p < 0.00001; genotype: GG vs. AG + AA, P < 0.00001; GG + AG vs. AA, p < 0.00001; GG vs. AA, p < 0.00001; AG vs. AA, p < 0.00001.[50]
rs3087243Taiwanese childrengenotype GG was significantly associated with GD (OR = 1.71, 95% CI 1.20–2.44, p = 0.006); Allele G was significantly more frequent (OR = 1.61, 95% CI 1.18–2.19, p = 0.0049).[19]
TaiwaneseG allele is associated with susceptibility to Graves’ disease (p = 0.011).[18]
Han population of Chinese (unrelated)allele G was significantly associated with GD in adults (p < 0.001) and children (p < 0.001).[40]
Chinese children < 16 years old (unrelated)G allele was more prevalent in GD p = 0.02.[41]
Southern ChinaG allele was significantly associated with an increased risk of GD development, p < 0.001.[43]
ChineseG > A allele frequencies between the patient and control groups, p = 0.014.[44]
RussianA allele and the AA genotypes were significantly increased in patients with GD.[45]
Saudi ArabianG allele was higher in GD patients than those in controls, p = 0.004.[46]
Italianallelic frequency of the G allele was also significantly higher in patients with GD (p = 0.02).[49]
Japanesefor the TBII-positive GD, G allele carriers in patients had significant association with GD, OR = 2.97, 95%CI = 1.29–6.87, p = 0.008.[51]
Russiansignificantly higher frequencies of A allele and AA genotype and a lower proportion of G allele and GG genotype.[52]

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MDPI and ACS Style

Chen, D.-P.; Chu, Y.-C.; Wen, Y.-H.; Lin, W.-T.; Hour, A.-L.; Wang, W.-T. Investigation of the Correlation between Graves’ Ophthalmopathy and CTLA4 Gene Polymorphism. J. Clin. Med. 2019, 8, 1842. https://doi.org/10.3390/jcm8111842

AMA Style

Chen D-P, Chu Y-C, Wen Y-H, Lin W-T, Hour A-L, Wang W-T. Investigation of the Correlation between Graves’ Ophthalmopathy and CTLA4 Gene Polymorphism. Journal of Clinical Medicine. 2019; 8(11):1842. https://doi.org/10.3390/jcm8111842

Chicago/Turabian Style

Chen, Ding-Ping, Yen-Chang Chu, Ying-Hao Wen, Wei-Tzu Lin, Ai-Ling Hour, and Wei-Ting Wang. 2019. "Investigation of the Correlation between Graves’ Ophthalmopathy and CTLA4 Gene Polymorphism" Journal of Clinical Medicine 8, no. 11: 1842. https://doi.org/10.3390/jcm8111842

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