Abstract
Background: For patients with Graves’ disease (GD), the primary goal of antithyroid drug therapy is to temporarily restore the patient to the euthyroid state and wait for a subsequent remission of the disease. This study sought to identify the predictive markers for the relapse of disease. Methods: To do this, we studied 262 GD patients with long enough follow-up after drug withdrawal to determine treatment outcome. The patients were divided into three groups by time of relapse: early relapse group (n = 91) had an early relapse within 9 months, late relapse group (n = 65) had a relapse between 10 and 36 months, and long-term remission group (n = 106) were either still in remission after at least 3 years or relapsed after 3 years of drug withdrawal. We assessed the treatment outcome of 23 SNPs of costimulatory genes, phenotype and smoking habits. We used permutation to obtain p values for each SNP as an adjustment for multiple testing. Cox proportional hazards models was performed to assess the strength of association between the treatment outcome and clinical and laboratory variables. Results: Four SNPs were significantly associated with disease relapse: rs231775 (OR 1.96, 95% CI 1.18–3.26) at CTLA-4 and rs745307 (OR 7.97, 95% CI 1.01–62.7), rs11569309 (OR 8.09, 95% CI 1.03–63.7), and rs3765457 (OR 2.60, 95% CI 1.08–6.28) at CD40. Combining risk alleles at CTLA-4 and CD40 improved the predictability of relapse. Using 3 years as the cutoff point for multivariate analysis, we found several independent predictors of disease relapse: number of risk alleles (HR 1.30, 95% CI 1.09–1.56), a large goiter size at the end of the treatment (HR 1.30, 95% CI 1.05–1.61), persistent TSH-binding inhibitory Ig (HR 1.64, 95% CI 1.15–2.35), and smoking habit (HR 1.60, 95% CI 1.05–2.42). Conclusion: Genetic polymorphism of costimulatory genes, smoking status, persistent goiter, and TSH-binding inhibitory Ig predict disease relapse.
Introduction
For patients with Graves’ disease (GD), there are three choices of treatment, none of which is perfect. The primary goal of antithyroid drug therapy is to temporarily restore the patient to the euthyroid state while awaiting a spontaneous remission. However, hyperthyroidism recurred in 30–60% of GD patients who discontinued the antithyroid medication [1,2,3,4,5]. Understanding of predictors of relapse of disease might help clinicians better individualize their patient’s treatment plans. A review of the literature revealed that genetic markers might be used to predict the course of disease after the withdrawal of antithyroid drugs [6,7]. Goiter size, as a phenotype response to TSH-receptor stimulation, has been reported to be a significant predictor of relapse [1,8]. Environmentally, iodine intake is a known factor for disease relapse [9,10]. Smokers are also more likely to experience a relapse than nonsmokers [7,11].
In this study, we analyzed the factors influencing outcome of antithyroid drug treatment for GD patients in Taiwan, an island where iodine intake is sufficient [12,13]. Factors studied included both afferent (CTLA-4, CD28, ICOS) and efferent (CD40) costimulatory genes, smoking habits and clinical characteristics including serum levels of T4, T3, goiter size, antithyroid medication and treatment duration, and TSH-receptor antibodies at the beginning and end of treatment.
Methods
Subjects
From August 2001 until July 2007, 310 GD patients attending the Endocrine Clinic at Kaohsiung Chang Gung Memorial Hospital agreed to the research project. Until December 2010, 262 of the 310 patients (214 women and 48 men aged 38.1 ± 12.9 years) had completed the treatment course and long enough follow-up after drug withdrawal to determine treatment outcome. GD was diagnosed as when a patient had elevated serum thyroxine (T4) and/or triiodothyronine (T3) and suppressed thyroid-stimulating hormone (TSH) levels, diffusely increased thyroidal uptake of technetium-99m or iodine-131, and the presence of TSH-receptor antibodies and/or antimicrosomal antibodies. We excluded patients with a history of radioiodine therapy or previous thyroid surgery. The 200 controls (103 women and 97 men aged 51.9 ± 12.2 years) were recruited from the Health Screening Center of the hospital. They had no clinical evidence or family history of any autoimmune disease. Laboratory tests and physical examination found all controls to be euthyroid state and have no obvious goiter. Informed consent was provided by all patients and controls. This study adheres to the guidelines set forth by the Declaration of Helsinki and was approved by the review board of Chang Gung Memorial Hospital.
Treatment and Follow-Up
The study group received methimazole 30 mg or propylthiouracil 300 mg daily. Dosage was decreased to two-thirds or half of the initial dose when normal levels of T4 and T3 were achieved, usually at 1–2 months after beginning treatment. The dose was then titrated gradually to reach a maintenance dose of methimazole 5–10 mg or propylthiouracil 50–100 mg daily by the third to fourth month. Low-dose block and replace therapy (methimazole 5–10 mg together with L-thyroxine 50 µg) was used in 43 patients to maintain euthyroid levels. Antithyroid drug treatment ranged from 1 to 3 years. Patients who responded to treatment well and reached euthyoid state smoothly usually stopped the medication after 12-month treatment. Patients who had big goiters and/or difficulty to taper the dosage of drugs usually continued the medication for 24 or 36 months. After drug therapy was stopped, patients were asked to return for follow-up studies every 3 months during the first year and every 6 months afterwards. Relapse was defined as a recurrence of symptoms of hyperthyroidism and laboratory data of serum T4 and/or T3 exceeding normal range. The 262 patients were divided into three groups according to the time of relapse. Early relapse group (n = 91) had an early relapse within 9 months after drug therapy was ceased, those in late relapse group (n = 65) had a relapse between 10 and 36 months after drug therapy was ceased, and those in long-term remission group (n = 106) were either still in remission after at least 3 years or relapsed after 3 years of drug withdrawal.
Evaluation of Patients
Clinical and laboratory evaluation included: the genotypes of CTLA-4, CD28, ICOS, and CD40; serum levels of T4, T3 and TSH; goiter size and TSH-binding inhibitory Ig at the beginning and end of treatment. Goiter size was determined by palpation and classified as: grade 1, a palpable goiter not reaching the medial edge of the sternocleidomastoid muscle; grade 2, a palpable goiter reaching the sternocleidomastoid muscle but not exceeding the lateral edge, and grade 3, a palpable goiter exceeding the lateral edge of the sternocleidomastoid muscle. Serum T4, T3, and TSH levels were measured by radioimmunoassay, and TSH-receptor antibody was measured as TBII by radioreceptor assay (TR-AB; CIS Bio International).
Information about the patients’ smoking habits was obtained by asking each patient, ‘Do you or have you ever smoked daily?’ All who answered ‘yes’ were classified as smokers. Smokers were defined as ex-smokers if they had refrained from smoking for more than 1 year; otherwise, they were considered current smokers. Only current smokers were defined positive for smoking regardless of how much they smoked. 38 of the 39 smokers were male. 24 of the smokers were 40 years old or younger, and 15 were over 40 years old.
SNP Selection and Genotyping
We examined eight publicly available polymorphisms for CD28, three for CTLA-4, six for ICOS, and six for CD40. The SNPs were selected according to (1) the tagging SNPs from HapMap project (http://hapmap.ncbi.nlm.nih.gov/) or (2) the minor allele frequency (MAF) ≥5% in our population based on a pilot sample of 40 GD patients and 40 controls. DNA was extracted from peripheral blood leukocytes. The SNPs of the candidate genes were genotyped by PCR-RFLP for the SNPs at CTLA-4 as previously described [6] or TaqMan technology (Applied Biosystems, Foster City, Calif., USA) for the SNPs at CD28, ICOS and CD40. The position, MAF (based on our control data) and numbers of subjects genotyped are shown in online supplementary data 1 (for all online suppl. material, see online Supplementary Materials). The genotype distributions of all SNPs in the patients and controls are shown in online supplementary data 2.
Statistics
Allele frequencies were estimated by direct gene counting. Hardy-Weinberg equilibrium was tested for each polymorphism by the χ2 test. Comparisons of individual clinical and laboratory variables between early relapse, late relapse and long-term remission groups were assessed by one-way ANOVA for the continuous data, and the χ2 test or Fisher exact test for the categorical data. Cox proportional hazards models were performed to assess the strength of association between the length of remission and the clinical and laboratory variables. The Kaplan-Meier plot was used to compare patients who remained in remission on MedCalc software. We used permutation to obtain empirical p value for each SNP as an adjustment for multiple testing.
Results
Genes Associated with Disease Relapse
Comparison of genotype distributions of all SNPs between patients and controls and among the three subgroups of patients are shown in online supplementary data 2. The genotype distributions were found to be in Hardy-Weinberg equilibrium in the patients and controls for all SNPs, except for rs4335928 at ICOS.
Table 1 specified the 7 SNPs showing difference of genotype frequencies among the three groups of patients. Among these SNPs, rs1879877 and rs3181113 at CD28 were only associated with relapse within 9 months, while rs5742909 at CTLA-4 was only associated with relapse within 3 years. Therefore, we accounted the significant genes and SNPs associated with disease relapse as CTLA-4 (rs231775) and CD40 (rs745307, rs11569309 and rs3765457), which associated with both the 9-month- and 3-year relapses. Using the cutoff point of 3 years to define relapse and remission, a summary of the odds ratio, confidence interval and p value of the 4 relapse-susceptible genes is shown in table 1.
SNPs associated with disease relapse
Combining Risk Genotypes at CD40 and CTLA-4 Gene Improved Predictability of Relapse
As seen in table 2, a summary of genotype distributions of SNPs at CTLA-4 (afferent costimulatory pathway) and CD40 (efferent costimulatory pathway) in our patients, each patient could carry zero, one, or two risk genotypes from the combination of one risk genotype of CD40 and CTLA-4. When exon 1 +49 A/G at CTLA-4 and rs745307 at CD40 were paired, 8 patients carried two risk genotypes, 153 patients carried one risk genotype, and 100 patients did not carry any risk genotype. The relapse rate was 87.5% for patients with two risk genotypes, 66% for one risk genotype, and 48% for zero risk genotype. The relapse rates among patients with two, one and zero risk genotypes were statistically significant (p = 0.005). Similarly, when exon 1 +49 A/G at CTLA-4 and rs3765457 at CD40 were paired, the relapse rates were 72.2% for two risk genotypes, 67.3% for one, and 45.5% for no risk. The relapse rates among patients with two, one and zero risk genotypes were statistically significant (p = 0.003). When exon 1 +49 A/G at CTLA-4 and rs11569309 at CD40 was paired, the relapse rates were 87.5% for two risk genotypes, 65.8% for one, and 47.8% for no risk. The relapse rates among patients with two, one and zero risk genotypes were statistically significant (p = 0.004).
Distribution of genotypes of CTLA-4 and CD40 in the GD patients
Number of Relapse Risk Alleles and Time of Recurrence after Drug Withdrawal
Of the GD patients with known times of relapse in this series, they were divided into three subgroups according to the numbers of risk alleles they harbored: 0–1 risk alleles (90 cases), 2 risk alleles (138 cases), and 3–5 risk alleles (19 cases). The proportion of patients remaining in remission was calculated with Kaplan-Meier plot. We found a significant difference among the subgroups (p = 0.0008) (fig. 1).
Proportion of patients remaining in remission according to the number of risk alleles, calculated with Kaplan-Meier plot (p = 0.0008).
Citation: European Thyroid Journal 1, 4; 10.1159/000342621
Independent Predictors of Disease Recurrence
Univariate analysis of predictors of disease relapse (age, sex, initial serum levels of T4, antithyroid drug, treatment duration, presence of ophthalmopathy, goiter size and TSH-receptor antibodies at the beginning and end of treatment, smoking habits, and number of relapse risk alleles) revealed the significant predictors of relapse to be big goiter size at end of treatment (p < 0.001), positive TSH-receptor antibodies at the end of treatment (p < 0.001), smoking habit (p = 0.025), and number of risk alleles (p = 0.015), while longer periods of treatment were associated with higher rate of relapse (p = 0.001) (table 3).
Univariate analysis of factors affecting relapse of disease
Using the cutoff point of 3 years to define relapse and remission, multivariate analysis revealed that the number of risk alleles, goiter size and TBII level at the end of treatment, and smoking to be independent predictors of relapse. One additional risk allele the patient harbored increased the hazard ratio (HR) by 1.30 (95% CI 1.09–1.56). The HR for each grade of goiter size was 1.30 (95% CI 1.05–1.61), for positive TBII at the end of the treatment 1.64 (95% CI 1.15–2.35), and for smoking habit 1.60 (95% CI 1.05–2.42) (table 4). Further dividing the patients into two subgroups: those below the age of 40 and those above the age of 40, we found the genetic risk alleles (HR 1.24, 95% CI 1.01–1.53) and positive TBII (HR 1.93, 95% CI 1.22–3.06) to be independent predictors in the younger subgroup, but only goiter size at the end of treatment (HR 1.56, 95% CI 1.09–2.22) to be an independent predictor in the older subgroup.
Cox proportional hazard models for determinants of risk of relapse
Discussion
In this study, the genetic factors we chose to analyze were the costimulatory genes, which are not involved in the initiating of autoimmune response to thyroid antigens, but required to generate subsequent cytokines and cell surface molecules after initial binding of T-cell receptor to the antigenic peptide-MHC complex [14,15]. Because this study focused on the relapse of GD, costimulatory genes play a more crucial role than the genes responsible for disease susceptibility such as HLA or TSHR [16,17,18]. HLA-DR typing has been proven to be unsuitable for predicting the clinical course of GD patients in a prospective multicenter study [8]. We found associations between 4 SNPs of the costimulatory genes and disease relapse after antithyroid drug withdrawal. In the afferent signal of costimulatory molecules, SNP exon 1 +49A/G (rs231775) of the CTLA-4 gene was found to be a risk allele for the recurrence of GD. In the efferent signal, we found three risk alleles at the CD40 to be associated with relapse. Furthermore, pairing risk alleles at CTLA-4 (afferent signal) and CD40 (efferent signal) improved the predictability of relapse. These findings suggest coordination among afferent and efferent pathways in autoimmune regulation.
In the afferent signal, members of the CD28 gene family (CD28, CTLA-4 and ICOS) are major costimulators located within a stretch of 300 kb on human chromosome 2q33. Linkage of the 2q33 region to thyroid antibodies production has been demonstrated by a genome-wide scan in 56 [19] and 99 families [20] with autoimmune thyroid diseases. The three genes have overlapping and distinct functions in signaling pathways [21]. CD28 is expressed constitutively on CD4 T cells, and its ligand, the B7 family, is present or induced on most activated antigen-presenting cells [22,23]. In general, naive or primary T-cell responses are more dependent on CD28 than are secondary responses [24]. CTLA-4, which is expressed after T-cell activation, is homologous to CD28 and binds to the B7, which in turn delivers a negative signal to the T cell [25]. CD28 and CTLA-4 represent the ‘general switches’ and strongly influence the expression of many downstream costimulators [15].
In the efferent signal, CD40, on chromosome 20q11.2, is mainly expressed in the B cells and thyrocytes. CD40 interacts with the CD40 ligand (CD40L) on the T cells [26]. CD40L, a member of the TNF family, is the most important mediator of efferent signals that come from the T-helper cells. CD40L is expressed briefly on CD4 T cells after they are activated through the T-cell receptor. CD40 promotes the formation of germinal centers and memory B cells and contributes to B-cell proliferation. CD40L is essential for the crosstalk of T cells with B cells [14,27]. Based on the above description, it is reasonable to assume that CD40 can affect both the development and progress of GD. In humans, the SNP (rs1883832) C>T at position –1 at the CD40 gene has been linked with GD susceptibility [28,29,30,31]. The present study of a Taiwanese population found SNPs at this CD40 for both disease susceptibility (rs3765457, rs4810485 in online suppl. data 2) and disease relapse (rs745307, rs11569309, rs3765457 in table 1).
Kim et al. [32] did not find an association between relapse of GD and the disease-susceptible alleles of CD40 and CTLA-4 genes. Their lack of such a finding may be due to the fact that they divided the GD patients into remission and failure groups with a cutoff point of euthyroid status for 12 months after withdrawal of treatment. Theoretically, an autoimmune disease should be viewed as probable recurring disease. Because of this probable recurrence, length of remission may be a more suitable evaluation method than dichotomizing the patients into success and failure.
This study found smoking to be a strong predictor of relapse of GD. Although smoking has been recognized as a risk for the development of clinically overt thyroid disease [33], increased risk for the development of more severe ophthalmopathy [34,35] and decreased effectiveness of medical treatment of eye problems [36], few studies have compared response of smoking status to antithyroid drug treatment of GD patients [37,38]. In one study, using a decline of TSH-receptor antibody and thyroid hormones as a measure, patients with GD who smoked have been reported to respond more slowly to treatment with carbimazole [37]. In another, smoking and male gender were associated with propylthiouracil treatment failure [38]. This study confirms the previous reports of smoking on recurrence after drug withdrawal in Belgian [11] and Taiwanese [7] patients with GD. The prevalence of smoking among Taiwanese men is high (39.0–62.6%), but low among Taiwanese women (2.3–5.3%) [39]. Based on our findings and those of others, patients should be told the importance of quitting smoking before antithyroid drug treatment is initiated.
In our study, clinical parameters of persistent large goiter and high TBII levels at the end of treatment are very useful predictors of disease relapse; a large goiter and a high TBII level at the beginning of treatment, however, were not predictors of disease relapse. Our finding that only persistent high TSH-receptor antibodies titer after therapy predict relapse are supported by previous studies [7,8,11,40] and a meta-analysis of 18 published reports [41]. We found that the relapse rate was higher for longer periods of treatment (table 3). This finding might well be related to our policy of prolongation of antithyroid drug treatment in patients with big goiters and/or difficulties with maintaining euthyroidism with tapering antithyroid drugs. Anyway, our results are in agreement with previous meta-analyses indicating that prolonged treatment with antithyroid drugs beyond 12–24 months does not lower relapse rate. Clinical parameters or phenotype usually reflects the overall interaction between genetic and environmental factors, and are, thus, related to outcome of drug treatment. However, they cannot, as a rule, be assessed at the very beginning of the disease.
In our subgroup analysis by age, genetic factors (risk alleles) were found to be better predictors of recurrence in the younger group, while clinical sign (goiter size) was more useful in the older group. These results are consistent with the genetic studies of type 2 diabetes [42,43], which have also reported that genetic factors are useful for disease prediction for younger populations. When an individual carrying the risk alleles gets old enough to develop the characteristic phenotypes, the predictive value of genotype will not override the predictive value of the phenotype.
This study has some limitations. The sample size was small. Because long-term follow-up was needed to clarify the outcomes, we could only include the patients who had been followed up for sufficient time to classify them into the early relapse, late relapse, or long-term remission groups. In addition, we did not analyze all the candidate genes involved in the autoimmune process (e.g. HLA, TSHR, thyroglobulin) [44] and the interaction between the costimulatory genes. These genes and their interaction may have their own impact on outcomes.
Conclusion
We found genetic polymorphism of costimulatory genes and smoking to contribute to the recurrence of GD, and persistent large goiter and high TBII levels at the end of treatment to be useful predictors of disease relapse (table 4).
Acknowledgement
This work was supported by a grant (NSC 95-2314-B-182-065) from the National Science Council (ROC).
Disclosure Statement
The authors have no conflicts of interest to disclose.
Footnotes
verified
References
- 1↑
Hershman JM, Givens JR, Cassidy CE, Astwood EB: Long-term outcome of hyperthyroidism treated with antithyroid drugs. J Clin Endocrinol Metab 1966;26:803–807.
- 2↑
Reinwein D, Benker G, Lazarus JH, Alexander WD: A prospective randomized trial of antithyroid drug dose in Graves’ disease therapy. European Multicenter Study Group on Antithyroid Drug Treatment. J Clin Endocrinol Metab 1993;76:1516–1521.
- 3↑
Wang PW, Liu RT, Tung SC, Chien WY, Lu YC, Chen CH, Kuo MC, Hsieh CR, Wang ST: Outcome of Graves’ disease after antithyroid drug treatment in Taiwan. J Formos Med Assoc 1998;97:619–625.
- 4↑
Léger J, Gelwane G, Kaguelidou F, Benmerad M, Alberti C; French Childhood Graves’ Disease Study Group: Positive impact of long-term antithyroid drug treatment on the outcome of children with Graves’ disease: national long-term cohort study. J Clin Endocrinol Metab 2012;97:110–119.
- 5↑
Allannic H, Fauchet R, Orgiazzi J, Madec AM, Genetet B, Lorcy Y, Le Guerrier AM, Delambre C, Derennes V: Antithyroid drugs and Graves’ disease: a prospective randomized evaluation of the efficiency of treatment duration. J Clin Endocrinol Metab 1990;70: 675–679.
- 6↑
Wang PW, Liu RT, Juo SH H, Wang ST, Hu YH, Hsieh CJ, Chen MH, Chen IY, Wu CL: Cytotoxic T lymphocyte-associated molecule-4 polymorphism and relapse of Graves’ hyperthyroidism after antithyroid withdrawal. J Clin Endocrinol Metab 2004;89:169–173.
- 7↑
Hsiao JY, Hsieh MC, Tien KJ, Hsu SC, Shin SJ, Lin SR: Association between a C/T polymorphism in exon 33 of the thyroglobulin gene is associated with relapse of Graves’ hyperthyroidism after antithyroid withdrawal in Taiwanese. J Clin Endocrinol Metab 2007;92:3197–3201.
- 8↑
Schleusener H, Schwander J, Fisher C, Holle R, Holl G, Badenhoop K, Hensen J, Finke R, Bogner U, Mayr WR, et al: Prospective multicenter study on the prediction of relapse after antithyroid drug treatment in patients with Graves’ disease. Acta Endocrinol 1989;120:689–701.
- 9↑
Alexander WD, Harden RM, Koutras DA, Wayne E: Influence of iodine intake after treatment with antithyroid drugs. Lancet 1965;ii:866–868.
- 10↑
Solomon BL, Evaul JE, Burman KD, Wartofsky L: Remission rates with antithyroid drug therapy: continuing influence of iodine intake. Ann Intern Med 1987;107:510–512.
- 11↑
Glinoer D, de Nayer P, Bex M; the Belgian Collaborative Study Group on Graves’ Disease: Effect of <span style="font-variant:small-caps; text-transform:lowercase">L</span>-thyroxine administration, TSH-receptor antibodies and smoking on the risk of recurrence in Graves’ hyperthyroidism treated with antithyroid drugs: a double-blind prospective randomized study. Eur J Endocrinol 2001;144:475–483.
- 12↑
Lin HD, Lo JG, Ching KN: Amount of urinary iodine excretion in residents of Taipei City – a hospital-based study. Zhonghuaa Yi Xue Za Zhi (Taipei) 1991;48:20–24.
- 13↑
Lin HD, Lo JG, Ching KN: Etiology of adult goiter in Taiwan – a hospital-based study. Zhonghuaa Yi Xue Za Zhi (Taipei) 1991;47:154–160.
- 14↑
Crow MK: Costimulatory molecules and T-cell-B-cell interaction. Rheum Dis Clin N Am 2004;30:175–191.
- 15↑
Kroczek RA, Mages HW, Hutloff A: Emerging paradigms of T-cell co-stimulation. Curr Opin Immunol 2004;16:321–327.
- 16↑
Jacobson EM, Huber A, Tomer Y: The HLA gene complex in thyroid autoimmunity: from epidemiology to etiology. J Autoimmun 2008;30:58–62.
- 17↑
Liu L, Wu HQ, Wang Q, Zu YF, Zhang W, Guan LJ, Zhang JA: Association between thyroid-stimulating hormone receptor gene intron polymorphisms and autoimmune thyroid disease in a Chinese Han population. Endocr J, E-pub ahead of print.
- 18↑
Lo FS, Lee YJ, Huang CY, Lin CH, Chang SC, Dang CW, Liu HF: Polymorphism in the transmembrane region of the major histocompatibility complex class I chain-related gene A: association of five GCT repetitions with Graves’ disease in children. Thyroid 2003;13:839–843.
- 19↑
Tomer Y, Greenberg DA, Barbesino G, Concepcion ES, Davies TF: CTLA-4 and not CD28 is a susceptibility gene for thyroid autoantibody production. J Clin Endocrinol Metab 2001;86:1687–1693.
- 20↑
Ban Y, Davies TF, Greenberg DA, Kissin A, Marder B, Murphy B, Concepcion ES, Villanueva RB, Barbesino G, Ling V, Tomer Y: Analysis of the CTLA-4, CD28, and inducible costimulator (ICOS) genes in autoimmune thyroid disease. Genes Immun 2003;4:586–593.
- 21↑
Rudd CE, Schneider H: Unifying concepts in CD28, ICOS and CTLA-4 co-receptor signaling. Nat Rev Immunol 2003;3:544–556.
- 22↑
Schwartz RH: Costimulation of T lymphocytes: the role of CD28, CTLA-4 and B7/BB1 in interleukin-2 production and immunotherapy. Cell 1992;71:1065–1068.
- 23↑
Freeman GJ, Gray GS, Gimmi CD, Lombard DB, Zhou L, White M, Fingeroth JD, Gribben JG, Nadler LM: Structure, expression and T cell costimulatory activity of the murine homologue of the human B lymphocyte activation antigen B7. J Exp Med 1991;174:625–631.
- 24↑
Blestone J: New perspectives of CD28-B7 mediated T-cell co-stimulation. Immunity 1995;2:555–559.
- 25↑
Walunas TL, Lenschow DJ, Bakker CY, Linsley PS, Freeman GJ, Greene JM, Thompson CB, Bluestone JA: CTLA-4 can function as a negative regulator of T-cell activation. Immunity 1994;1:405–413.
- 26↑
Metcalfe RA, Mclntosh RS, Marelli-Berg F, Lombardi G, Lechler R, Weetman AP: Detection of CD40 on human thyroid cells: analysis of expression and function. J Clin Endocrinol Metab 1998;83:1268–1274.
- 27↑
Dittmar M, Kahaly GJ: Immunoregulatory and susceptibility genes in thyroid and polyglandular autoimmunity. Thyroid 2005;15:239–250.
- 28↑
Tomer Y, Concepcion E, Greenberg DA: A C/T single-nucleotide polymorphism in the region of the CD40 gene is associated with Graves’ disease. Thyroid 2000;12:1129–1135.
- 29↑
Ban Y, Tozaki T, Taniyama M, Tomita M, Ban Y: Association of a C/T single-nucleotide polymorphism in the 5′-untranslated region of the CD40 gene with Graves’ disease in Japanese. Thyroid 2006;16:443–446.
- 30↑
Kim TY, Park YJ, Hwang JK, Song JY, Park KS, Cho BY, Park DJ: A C/T polymorphism in the 5′-untranslated region of the CD40 gene is associated with Graves’ disease in Koreans. Thyroid 2003;13:919–925.
- 31↑
Kurylowicz A, Kula D, Ploski R, Skorka A, Jurecka-Lubieniecka B, Zebracka J, Steinhof-Radwanska K, Hasse-Lazar K, Hiromatsu Y, Jarzab B, Bednarczuk T: Association of CD40 gene polymorphism (C-1T) with susceptibility and phenotype of Graves’ disease. Thyroid 2005;15:1119–1124.
- 32↑
Kim KW, Park YJ, Kim TY, Park DJ, Park KS, Cho BY: Susceptible alleles of the CD40 and CTLA-4 genes are not associated with the relapse after antithyroid withdrawal in Graves’ disease. Thyroid 2007;17:1229–1233.
- 33↑
Brix TH, Hansen PS, Kyvik KO, Hegedüs L: Cigarette smoking and risk of clinically overt thyroid disease. A population-based twin case-control study. Arch Intern Med 2000;160:661–666.
- 35↑
Stan MN, Bahn RS: Risk factors for development or deterioration of Graves’ ophthalmopathy. Thyroid 2010;7:777–783.
- 36↑
Wiersinga WM, Bartalena L: Epidemiology and prevention of Graves’ ophthalmopathy. Thyroid 2002;10:855–860.
- 37↑
Nyirenda MJ, Taylor PN, Stoddart M, Toft AD: Thyroid-stimulating hormone-receptor antibody and thyroid hormone concentrations in smokers vs. nonsmokers with Graves’ disease treated with carbimazole. JAMA 2009;301:162–164.
- 38↑
Cinemre H, Bilir C, Gokosmanoglu F, Akdemir N, Erdogmus B, Buyukkaya R: Predictors of time to remission and treatment failure in patients with Graves’ disease treated with propylthiouracil. Clin Invest Med 2009;32:E199–E205.
- 39↑
Bureau of Health Promotion: Taiwan Tobacco Control Annual Report. Taipei, Taiwan, Bureau of Health Promotion, Department of Health, 2008.
- 40↑
Torring O, Tallstedt L, Wallin G, Lundell G, Ljunggren JG, Taube A, Saaf M, Hamberger B: Graves’ hyperthyroidism: treatment with antithyroid drugs, surgery, or radioiodine – a prospective randomized study. J Clin Endocrinol Metab 1996;81:2986–2993.
- 41↑
Feldt-Rasmussen U, Schleusener H, Carayon P: Meta-analysis evaluation of the impact of thyrotropin receptor antibodies on long-term remission after medical therapy of Graves’ disease. J Clin Endocrinol Metab 1994;78:98–102.
- 42↑
Meigs JB, Shrader P, Sullivan LM, McAteer JB, Fox CS, Dupuis J, Manning AK, Florez JC, Wilson PF, D’Agostino RB, Cupples AC: Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med 2008;359:2208–2219.
- 43↑
Lyssenko V, Jonsson A, Almgren P, Pulizzi N, Isomaa B, Tuomi T, Berglund G, Altshuler D, Nilsson P, Groop L: Clinical risk factors, DNA variants, and the development of type 2 diabetes. N Engl J Med 2008;359:2220–2232.
- 44↑
Davies TF, Latif R, Yin X: New genetic insights from autoimmune thyroid disease. J Thyroid Res 2012;2012:623852.
