PTPN22 and CTLA-4 Polymorphisms Are Associated With Polyglandular Autoimmunity

PTPN22 and CTLA-4 Polymorphisms Are Associated With Polyglandular Autoimmunity Abstract Context Single nucleotide polymorphisms (SNPs) of various genes increase susceptibility to monoglandular autoimmunity. Data on autoimmune polyglandular syndromes (APSs) are scarce. Objective Evaluate potential associations of eight SNPs with APSs. Setting Academic referral endocrine clinic. Patients A total of 543 patients with APS and monoglandular autoimmunity and controls. Intervention The SNP protein tyrosine phosphatase nonreceptor type 22 (PTPN22) rs2476601 (+1858); cytotoxic T-lymphocyte‒associated antigen 4 (CTLA-4) rs3087243 (CT60) and rs231775 (AG49); vitamin D receptor (VDR) rs1544410 (Bsm I), rs7975232 (Apa I), rs731236 (Taq I); tumor necrosis factor α rs1800630 (-863); and interleukin-2 receptor alpha rs10795791 were tested by single-base extension in all subjects. Results The PTPN22 +1858 allele and genotype distribution were markedly different between APS, type 1 diabetes [T1D; odds ratio (OR): 2.67; 95% confidence interval (CI): 1.52 to 4.68; P = 0.001], Graves disease (GD; OR: 1.94; 95% CI: 1.16 to 3.25; P = 0.011), and controls (OR: 3.31, 95% CI: 1.82 to 6.02; P < 0.001). T-allele carriers’ risk for APS was increased (OR: 3.76; 95% CI: 1.97 to 7.14; P < 0.001). T-allele frequency was higher among APS than controls (OR: 3.25; 95% CI: 1.82 to 5.82; P < 0.001), T1D (OR: 2.54; 95% CI: 1.48 to 4.36; P = 0.001), or GD (OR: 1.89; 95% CI: 1.15 to 3.11; P = 0.012). The SNP CTLA-4 CT60 G-allele carriers were more frequent in APS (85%) than controls (78%) (OR: 1.55; 95% CI: 0.81 to 2.99). Combined analysis of CTLA-4 AG49 and CT60 revealed OR 4.89; 95% CI: 1.86 to13.59; P = 0.00018 of the genotype combination AG/GG for APS vs controls. VDR polymorphisms Bsm I, Apa I, and Taq I did not, but the haplotypes differed between APS and controls (P = 0.0011). Conclusions PTPN22 and CTLA-4 polymorphisms are associated with APS and differentiate between polyglandular and monoglandular autoimmunity. Autoimmune polyglandular syndrome (APS) is defined as the concomitance of at least two autoimmune-induced endocrine diseases and is divided into juvenile monogenic and polygenic adult types (1, 2). The most frequent adult variant encompasses type 1 diabetes (T1D) and an autoimmune thyroid disease (AITD), also reported as type 3 variant (3–6). Genotyping of the human leukocyte antigens (HLAs) class II differentiates between patients with monoglandular autoimmune (MGA) diseases and those with APS (7) as well as between various APS types (8). Compared with HLA reports, several studies looked at the association between single nucleotide polymorphisms (SNPs) and MGA in different populations; however, studies pertaining to gene polymorphisms and APS are scarce. Large replication studies are lacking, and most clues are drawn from studies in patients with MGA. Indeed and in detail, the protein tyrosine phosphatase nonreceptor type 22 gene (PTPN22) encodes lymphoid tyrosine phosphatase, one of the strongest inhibitors of T-cell activation (9). A functional C→T SNP at position 1858 leads to an arginine→tryptophan amino acid substitution at codon 620. The PTPN22 +1858 polymorphism (rs2476601), especially the minor T-allele of this polymorphism (10), increases susceptibility to MGA (10–13). The cytotoxic T-lymphocyte‒associated antigen 4 (CTLA-4) is a negative regulator of T-cell activation. Two SNPs, CT60 (rs3087243) and AG49 (rs231775), are associated with a lower level of soluble CTLA-4 and therefore less regulation of T-cells, leading to increased autoimmune reactivity. The two SNPs have been associated with MGA. Furthermore, the already described CT60/AG49 haplotype variants AG, GA, AA, and GG are SNPs that significantly alter gene function (14–17). Vitamin D3 exerts its immune modulatory function through the steroid vitamin D receptor (VDR). The VDR is expressed on immune cells and directly inhibits activated T-cells and reduces the production of proinflammatory cytokines. High doses of vitamin D significantly reduced the occurrence of T1D in humans and the risk of AITD in an animal model through suppression of activated T-cells, improvement of phagocytosis, and suppression of interferon γ production (18, 19). The three SNPs Bsm I (rs1544410), Apa I (rs7975232), and Taq I (rs731236) have been associated with MGA (20–23). Interleukin (IL)-2 is a growth, survival, and differentiation factor of T-cells. It regulates the function of natural killer cells, B-cells, and T-regulatory cells by activating the IL receptor. Alterations in the α-chain of the IL2 receptor (IL2RA; rs10795791) or lower receptor expression was associated with MGA (24, 25). Tumor necrosis factor α (TNF-α) is a proinflammatory cytokine and a potent modulator of the immune response (26). A polymorphism in the promoter region [i.e.,TNF-α‒863 (rs1800630)] changes the transcription frequency and thereby increases the production of TNF-α (27). A meta-analysis including Asian and Caucasian collectives showed an association of this SNP with the occurrence of Graves disease (GD) (28). Because the previously mentioned studies refer exclusively to patients with MGA, we evaluated the potential association of eight SNPs with APS in Caucasians. We aimed to look for the potential translational value of knowing the SNP associations, such as predicting which patients with a single autoimmune endocrine disorder are likely to progress to APS, or to assist in the design of precise interventions. Material and Methods Subjects A total of 543 Caucasians [143 patients with APS; 100 each with T1D, Hashimoto thyroiditis (HT), or GD; and 100 healthy controls] followed at the referral outpatient clinic for endocrine autoimmune diseases, Gutenberg University Medical Center, were included in this study. HT was defined as the presence of at least fivefold-increased serum level of thyroid peroxidase autoantibodies, a hypoechoic ultrasonography pattern, and euthyroidism or hypothyroidism. GD was defined as hyperthyroidism, the presence of thyroid-stimulating hormone‒receptor autoantibodies, and a typical thyroid ultrasonography pattern with enhanced vascularization of the thyroid gland. T1D was defined as insulin dependency; positive autoantibodies against the islet cell antigens and/or tyrosine phosphatase and/or insulin and/or glutamic acid decarboxylase-65; a pathologic serum glycemic hemoglobin value >6.5%; and a fasting serum glucose level >120 mg/dL. The 300 patients with well-characterized MGA disorders had an average disease history of 15 years and negative family history of other autoimmune endocrine diseases and were all negative for other specific endocrine autoantibodies, thus allowing a distinction between APS and MGA. Patients with further endocrine and nonendocrine autoimmune diseases were excluded from this study. All healthy controls were unrelated to any diseased patient and were devoid of personal and family history of autoimmune, tumor, and infectious diseases. All controls had documented negative thyroid and pancreatic antibody test results. Furthermore, controls were selected on the basis of nonsmoking status and no alcohol consumption and were not taking any medication. Subsequent to clinical investigation, blood samples were collected. All subjects gave written informed consent for genetic analysis and participation in this study, which was approved by the ethical committee of the Gutenberg University Medical Center and of the state of Rhineland-Palatinate, Germany. DNA extraction, polymerase chain reaction amplification, and single-base extension The DNA from blood samples was extracted with the QIAamp® DNA Blood Mini Kit (Qiagen GmbH, Hilden, Germany) according to manufacturer’s protocol. Before polymerase chain reaction (PCR) amplification, some primers had to be newly designed using Clone Manager 9 for Windows (www.scied.com software; Cary, NC). Three primers marked with an asterisk had already been published (10, 29). All primers were checked to avoid primer dimers and secondary structures (listed in Table 1). Because of their close position, ApaI/TaqI could be amplified at one amplicon. Two multiplex PCRs (IL2RA, AG49, PTPN22, TNF-α, and CT60, Bsm I) and one single PCR (Apa I, Taq I) were implemented on a Primus 96 Advanced® Thermal Cycler (Peqlab Biotechnologie GmbH, Erlangen, Germany). Each 20-µL PCR reaction includes 2 µL DNA, 1 µL of forward and reverse primer (10 µM each, with the exception of TNF-α with 20 µM), 0.4 µL (5 U/mL) Taq polymerase (Roche, Mannheim, Germany), 0.5 µL deoxynucleotide-triphosphates (10 mM each base), and 2.5 µL PCR reaction buffer (10×). Cycling was done with an initial denaturation step for 5 minutes at 94°C, followed by 30 cycles with 30 seconds at 94°C, 10 seconds at 56°C, 1 minute at 72°C, and a final extension for 10 minutes at 72°C. The successful amplification was checked by agarose gel electrophoresis. To ensure the correctness of the PCR, each product was sequenced (BigDye Terminator sequencing reagents Version 1.1; Thermo Fisher Scientific, Darmstadt, Germany) and blasted against the National Center for Biotechnology Information database. SNP typing was performed by single-base extension (SBE) (Fig. 1). To remove remaining primers and deoxynucleotide-triphosphates, the PCR products were purified with a mixture of exonuclease 1 and shrimp alkaline phosphatase (ExoSAP-IT; USB Europe, Staufen, Germany). Table 1. Primers Designed for PCR (Forward and Reverse) and Single-Base Extension SNP/rs No.  PCR Primers  Single-Base Extension Primers  PTPN22 1858a/rs2476601  F-GGATAGCAACTGCTCCAAGGATAG  (T)14CAGCTTCCTCAACCACAATAAATGATTCAGGTGTCC  R-CTCTCACCTCCACCATCCAAATAG  CTLA-4 CT60a/rs3087243  F-AGCTTTGCACCAGCCATTACC  (T)24TCCTTTTGATTTCTTCACCACTATTTGGGATATAAC  R-GTGCCAGCTGATAGCAACATAGG  CTLA-4 AG49/rs231775  F-TAAACCCACGGCTTCCTTTCTCG  (T)45AGGCTCAGCTGAACCTGGCT  R-CACTGCCTTTGACTGCTGAAAC  VDR Bsm I/rs1544410  F-TGGCCATCTGCATCGTCTCC  (T)30GAGCAGAGCCTGATGATTGGGAATG  R-CCCTCTTCTCACCTCTAACC  VDR Apa I/rs7975232  F-GCACGGAGAAGTCACTG  (T)40AGAAGAAGGCACAGGAGCTCTCAGCTGGGC  R-CAGCGGATGTACGTCTG  VDR Taq I/rs731236  F-GCACGGAGAAGTCACTG  (T)25GTGCAGGACGCCGCGCTGAT  R-CAGCGGATGTACGTCTG  IL2RA/rs10795791  F-GATCAGGAAAGGCCCACGTATTG  (T)15TAGAAGCTAAGGGCAGAAAT  R-CGGCCTCATCATCACATCACTTG  TNF-α‒863a/rs1800630  F-ATGTGACCACAGCAATGGGTAG  (T)12CCCTCTACATGGCCCTGTCTTCGTTAAG  R-CTTCTTTCATTCTGACCCGGAGAC  SNP/rs No.  PCR Primers  Single-Base Extension Primers  PTPN22 1858a/rs2476601  F-GGATAGCAACTGCTCCAAGGATAG  (T)14CAGCTTCCTCAACCACAATAAATGATTCAGGTGTCC  R-CTCTCACCTCCACCATCCAAATAG  CTLA-4 CT60a/rs3087243  F-AGCTTTGCACCAGCCATTACC  (T)24TCCTTTTGATTTCTTCACCACTATTTGGGATATAAC  R-GTGCCAGCTGATAGCAACATAGG  CTLA-4 AG49/rs231775  F-TAAACCCACGGCTTCCTTTCTCG  (T)45AGGCTCAGCTGAACCTGGCT  R-CACTGCCTTTGACTGCTGAAAC  VDR Bsm I/rs1544410  F-TGGCCATCTGCATCGTCTCC  (T)30GAGCAGAGCCTGATGATTGGGAATG  R-CCCTCTTCTCACCTCTAACC  VDR Apa I/rs7975232  F-GCACGGAGAAGTCACTG  (T)40AGAAGAAGGCACAGGAGCTCTCAGCTGGGC  R-CAGCGGATGTACGTCTG  VDR Taq I/rs731236  F-GCACGGAGAAGTCACTG  (T)25GTGCAGGACGCCGCGCTGAT  R-CAGCGGATGTACGTCTG  IL2RA/rs10795791  F-GATCAGGAAAGGCCCACGTATTG  (T)15TAGAAGCTAAGGGCAGAAAT  R-CGGCCTCATCATCACATCACTTG  TNF-α‒863a/rs1800630  F-ATGTGACCACAGCAATGGGTAG  (T)12CCCTCTACATGGCCCTGTCTTCGTTAAG  R-CTTCTTTCATTCTGACCCGGAGAC  a Previously published primer. View Large Table 1. Primers Designed for PCR (Forward and Reverse) and Single-Base Extension SNP/rs No.  PCR Primers  Single-Base Extension Primers  PTPN22 1858a/rs2476601  F-GGATAGCAACTGCTCCAAGGATAG  (T)14CAGCTTCCTCAACCACAATAAATGATTCAGGTGTCC  R-CTCTCACCTCCACCATCCAAATAG  CTLA-4 CT60a/rs3087243  F-AGCTTTGCACCAGCCATTACC  (T)24TCCTTTTGATTTCTTCACCACTATTTGGGATATAAC  R-GTGCCAGCTGATAGCAACATAGG  CTLA-4 AG49/rs231775  F-TAAACCCACGGCTTCCTTTCTCG  (T)45AGGCTCAGCTGAACCTGGCT  R-CACTGCCTTTGACTGCTGAAAC  VDR Bsm I/rs1544410  F-TGGCCATCTGCATCGTCTCC  (T)30GAGCAGAGCCTGATGATTGGGAATG  R-CCCTCTTCTCACCTCTAACC  VDR Apa I/rs7975232  F-GCACGGAGAAGTCACTG  (T)40AGAAGAAGGCACAGGAGCTCTCAGCTGGGC  R-CAGCGGATGTACGTCTG  VDR Taq I/rs731236  F-GCACGGAGAAGTCACTG  (T)25GTGCAGGACGCCGCGCTGAT  R-CAGCGGATGTACGTCTG  IL2RA/rs10795791  F-GATCAGGAAAGGCCCACGTATTG  (T)15TAGAAGCTAAGGGCAGAAAT  R-CGGCCTCATCATCACATCACTTG  TNF-α‒863a/rs1800630  F-ATGTGACCACAGCAATGGGTAG  (T)12CCCTCTACATGGCCCTGTCTTCGTTAAG  R-CTTCTTTCATTCTGACCCGGAGAC  SNP/rs No.  PCR Primers  Single-Base Extension Primers  PTPN22 1858a/rs2476601  F-GGATAGCAACTGCTCCAAGGATAG  (T)14CAGCTTCCTCAACCACAATAAATGATTCAGGTGTCC  R-CTCTCACCTCCACCATCCAAATAG  CTLA-4 CT60a/rs3087243  F-AGCTTTGCACCAGCCATTACC  (T)24TCCTTTTGATTTCTTCACCACTATTTGGGATATAAC  R-GTGCCAGCTGATAGCAACATAGG  CTLA-4 AG49/rs231775  F-TAAACCCACGGCTTCCTTTCTCG  (T)45AGGCTCAGCTGAACCTGGCT  R-CACTGCCTTTGACTGCTGAAAC  VDR Bsm I/rs1544410  F-TGGCCATCTGCATCGTCTCC  (T)30GAGCAGAGCCTGATGATTGGGAATG  R-CCCTCTTCTCACCTCTAACC  VDR Apa I/rs7975232  F-GCACGGAGAAGTCACTG  (T)40AGAAGAAGGCACAGGAGCTCTCAGCTGGGC  R-CAGCGGATGTACGTCTG  VDR Taq I/rs731236  F-GCACGGAGAAGTCACTG  (T)25GTGCAGGACGCCGCGCTGAT  R-CAGCGGATGTACGTCTG  IL2RA/rs10795791  F-GATCAGGAAAGGCCCACGTATTG  (T)15TAGAAGCTAAGGGCAGAAAT  R-CGGCCTCATCATCACATCACTTG  TNF-α‒863a/rs1800630  F-ATGTGACCACAGCAATGGGTAG  (T)12CCCTCTACATGGCCCTGTCTTCGTTAAG  R-CTTCTTTCATTCTGACCCGGAGAC  a Previously published primer. View Large Figure 1. View largeDownload slide Typing of the eight polymorphisms by single-base extension (SBE). Two examples for SBE typing of IL2RA, TNF-α, Taq I, PTPN22, Bsm I, CT60, AG49, and Apa I. The polymorphisms are shown in order of their respective retention time on the x-axis. In SBE, each primer is elongated by a single fluorescence-labeled nucleotide representing the corresponding polymorphism. Guanine (G) is marked in blue, adenine (A) in green, tyrosine (T) in red, and cytosine (C) in black. The intensity of the peaks is shown in relative fluorescent units (RFU) on the y-axis. The cutoff value was set at 100 RFU. Figure 1. View largeDownload slide Typing of the eight polymorphisms by single-base extension (SBE). Two examples for SBE typing of IL2RA, TNF-α, Taq I, PTPN22, Bsm I, CT60, AG49, and Apa I. The polymorphisms are shown in order of their respective retention time on the x-axis. In SBE, each primer is elongated by a single fluorescence-labeled nucleotide representing the corresponding polymorphism. Guanine (G) is marked in blue, adenine (A) in green, tyrosine (T) in red, and cytosine (C) in black. The intensity of the peaks is shown in relative fluorescent units (RFU) on the y-axis. The cutoff value was set at 100 RFU. Typing of the SNPs was done in two separate multiplex reactions with the ABI PRISM SNaP Shot Multiplex Kit (Thermo Fisher Scientific) using the SBE primers listed in Table 1. In one multiplex, the PCR products for IL2RA, AG49, PTPN22, TNF-α, and CT60 were combined; in the other multiplex, the PCR products for Bsm I, Apa I, and Taq I were chosen. The elongated SBE primers were separated by capillary gel electrophoresis using an ABI PRISM® 3100-Avant Genetic Analyzer (Applied Biosystems, Darmstadt, Germany) with POP-6. Data analysis was completed with 3100-Avant Data Collection Software and GeneMapperTM ID Software Version 3.1. To secure a clear discrimination between homozygotes and heterozygotes, a cutoff level was validated by serial dilutions of the extended primers to a minimal detection level at 100 relative fluorescent units for homozygote alleles. Statistical analysis For statistical analysis, SPSS Statistics 22.0/23.0 was used. Genotype frequencies of all SNPs were tested for Hardy-Weinberg disequilibrium by χ2 test. Statistical associations between genotypes and disease were assessed by reporting allelic odds ratios (ORs) comparing APS with all other groups and common dominant model‒based ORs with 95% confidence intervals (CIs). CIs and corresponding statistical tests emerged from fitting appropriate logistic models. For controlling family-wise type 1 error at 0.05 within SNP locus over four comparisons to different comparator groups, P values <0.0125 were statistically significant. For controlling family-wise type 1 error over nine SNPs in addition, the critical P value was 0.0014. Haplotypes were inferred from genotype combinations. Inference was certain if just one locus was heterozygous. For all others, rare or nonoccurring haplotypes were excluded, and the most likely haplotype was imputed on the basis of meta-analysis data for VDR haplotypes (30) and for CTLA-4 haplotypes (14) (Supplemental Tables 1 and 2). Homogeneity of haplotype allele frequencies across all five groups was assessed by χ2 tests for CTLA-4 haplotypes and the three common VDR haplotypes. Rare VDR haplotype allele frequencies were assessed by an exact test for contingency tables. Contrasts between APS and controls were quantified by allele-level ORs based on 2 × 2 subtables. Results The demographic data of the study collective are shown in Table 2. There were no signs of Hardy-Weinberg disequilibrium in the observed genotypes of all groups. Table 2. Demographic Data Collective  N  Gender (Male/Female)  Age (y) Median (25/75 Percentiles)  Children <18 Years  APS  143  43/100  43 (28/57)  22  T1D + HT  90  25/65  41 (19.8/55.2)  19  T1D + GD  53  35/18  49 (40.5/59)  3  T1D  100  52/48  28 (17/42.8)  27  HT  100  12/88  40.5 (30/50.8)  3  GD  100  21/79  47 (34.3/55.8)  1  C  100  43/57  29 (24/48)  0  Total  543  171/372  40 (26/52)  75  Collective  N  Gender (Male/Female)  Age (y) Median (25/75 Percentiles)  Children <18 Years  APS  143  43/100  43 (28/57)  22  T1D + HT  90  25/65  41 (19.8/55.2)  19  T1D + GD  53  35/18  49 (40.5/59)  3  T1D  100  52/48  28 (17/42.8)  27  HT  100  12/88  40.5 (30/50.8)  3  GD  100  21/79  47 (34.3/55.8)  1  C  100  43/57  29 (24/48)  0  Total  543  171/372  40 (26/52)  75  Abbreviation: C, control. View Large Table 2. Demographic Data Collective  N  Gender (Male/Female)  Age (y) Median (25/75 Percentiles)  Children <18 Years  APS  143  43/100  43 (28/57)  22  T1D + HT  90  25/65  41 (19.8/55.2)  19  T1D + GD  53  35/18  49 (40.5/59)  3  T1D  100  52/48  28 (17/42.8)  27  HT  100  12/88  40.5 (30/50.8)  3  GD  100  21/79  47 (34.3/55.8)  1  C  100  43/57  29 (24/48)  0  Total  543  171/372  40 (26/52)  75  Collective  N  Gender (Male/Female)  Age (y) Median (25/75 Percentiles)  Children <18 Years  APS  143  43/100  43 (28/57)  22  T1D + HT  90  25/65  41 (19.8/55.2)  19  T1D + GD  53  35/18  49 (40.5/59)  3  T1D  100  52/48  28 (17/42.8)  27  HT  100  12/88  40.5 (30/50.8)  3  GD  100  21/79  47 (34.3/55.8)  1  C  100  43/57  29 (24/48)  0  Total  543  171/372  40 (26/52)  75  Abbreviation: C, control. View Large PTPN22 +1858 Allele and genotype distributions were markedly different between APS, MGA [i.e., T1D (OR: 2.67; 95% CI: 1.52 to 4.68; P = 0.001), GD (OR: 1.94; 95% CI: 1.16 to 3.25; P = 0.011)], and controls (OR: 3.31; 95% CI: 1.82 to 6.02; P < 0.001) (Table 3). T-allele carriers’ risk for APS was increased nearly fourfold (OR: 3.76; 95% CI: 1.97 to 7.14; P < 0.001). Considering the 53 patients with T1D + GD, 42% were T-allele carriers compared with only 15% of controls (OR: 4.02; 95% CI: 1.85 to 8.73; P < 0.001). This also held true for the 90 patients with T1D + HT: 39% T-allele carriers vs only 15% of controls (OR: 3.61; 95% CI: 1.80 to 7.21; P < 0.001). The minor T-allele frequency was higher among APS than controls (OR: 3.25; 95% CI: 1.82 to 5.82; P < 0.001), T1D (OR: 2.54; 95% CI: 1.48 to 4.36; P = 0.001), or GD (OR: 1.89; 95% CI: 1.15 to 3.11; P = 0.012). Table 3. Genetic Associations SNP Locus  Group  Genotype Counts WW:WA:AA  Allele Frequency (%)  Allelic ORa APS vs Comparator  P Value  Common Dominant Model ORb APS vs Comparator  P Value  PTPN22 +1858 (C:T)  APS  86:51:6  22.0  —  —  —  —  T1D  80:20:0  10.0  2.67 (1.52–4.68)  0.001  2.65 (1.47–4.80)  0.001  HT  65:29:6  20.5  1.09 (0.71–1.70)  0.689  1.23 (0.72–2.09)  0.442    GD  75:24:1  13.0  1.94 (1.16–3.25)  0.011  1.99 (1.13–3.49)  0.017    C  85:14:1  8.0  3.31 (1.82–6.02)  <0.001  3.76 (1.97–7.14)  <0.001  CTLA-4 CT60c  APS  65:56:22  65.7  —  —  —  —  T1D  36:44:20  58.0  1.30 (0.92–1.85)  0.139  1.38 (0.71–2.68)  0.350  (G:A)  HT  42:42:16  63.0  1.08 (0.76–1.54)  0.664  1.05 (0.52–2.11)  0.896    GD  40:45:15  62.5  1.11 (0.77–1.58)  0.585  0.97 (0.48–1.98)  0.935    C  27:51:22  53.0  1.63 (1.13–2.33)  0.008  1.55 (0.81–2.99)  0.190  CTLA-4  APS  45:72:26  43.4  —  —  —  —  AG49  T1D  41:47:12  35.5  1.40 (0.96–2.05)  0.081  1.51 (0.89–2.58)  0.126  (A:G)  HT  30:45:16  43.0  1.02 (0.70–1.48)  0.936  0.93 (0.54–1.63)  0.808    GD  33:43:24  45.5  0.92 (0.64–1.31)  0.646  1.07 (0.62–1.85)  0.801    C  36:40:24  44.5  0.98 (0.69–1.39)  0.891  1.23 (0.71–2.10)  0.461  Bsm I  APS  55:64:24  39.2  —  —  —  —  (C:T)  T1D  34:49:17  41.5  0.91 (0.63–1.31)  0.610  0.82 (0.48–1.41)  0.478    HT  39:45:16  37.5  1.03 (0.72–1.47)  0.886  1.02 (0.61–1.73)  0.932    GD  35:46:19  42.0  0.86 (0.63–1.28)  0.542  0.86 (0.51–1.47)  0.583    C  37:50:13  38.0  1.05 (0.73–1.52)  0.797  0.94 (0.55–1.59)  0.818  Apa I  APS  42:67:34  47.2  —  —  —  —  (A:C)  T1D  30:45:25  47.5  0.99 (0.70–1.40)  0.950  1.03 (0.59–1.80)  0.916    HT  27:48:25  49.5  0.93 (0.66–1.33)  0.704  0.89 (0.50–1.57)  0.687    GD  29:45:26  48.5  0.95 (0.67–1.35)  0.786  0.98 (0.56–1.72)  0.950    C  31:45:24  46.5  1.03 (0.72–1.46)  0.883  1.08 (0.62–1.88)  0.785  Taq I  APS  52:64:27  41.3  —  —  —  —  (T:C)  T1D  36:46:18  41.0  1.01 (0.71–1.44)  0.956  0.98 (0.58–1.68)  0.954    HT  40:45:15  37.5  1.16 (0.81–1.66)  0.419  1.17 (0.69–1.97)  0.565    GD  39:43:18  39.5  1.07 (0.75–1.52)  0.709  1.12 (0.66–1.89)  0.676    C  38:49:13  37.5  1.17 (0.81–1.68)  0.412  1.07 (0.63–1.82)  0.795  IL2RA  APS  35:73:35  50.0  —  —  —  —  (A:G)  T1D  30:54:16  43.0  1.35 (0.93–1.96)  0.120  1.32 (0.75–2.35)  0.339    HT  36:44:20  42.0  1.37 (0.95–1.97)  0.088  1.74 (0.99–3.03)  0.053    GD  34:51:15  40.5  1.49 (1.02–2.17)  0.037  1.59 (0.91–2.79)  0.106    C  32:48:20  44.0  1.27 (0.88–1.83)  0.194  1.45 (0.82–2.56)  0.198  TNF-α‒863 (C:A)  APS  101:37:5  16.4  —  —  —  —  T1D  60:35:5  22.5  0.68 (0.44–1.08)  0.101  0.62 (0.36–1.07)  0.098  HT  68:26:6  19.0  0.85 (0.54–1.34)  0.486  0.88 (0.51–1.54)  0.661    GD  74:23:3  14.5  1.15 (0.71–1.87)  0.576  1.18 (0.67–2.10)  0.565    C  77:20:3  13.0  1.29 (0.78–2.13)  0.318  1.39 (0.77–2.51)  0.271  SNP Locus  Group  Genotype Counts WW:WA:AA  Allele Frequency (%)  Allelic ORa APS vs Comparator  P Value  Common Dominant Model ORb APS vs Comparator  P Value  PTPN22 +1858 (C:T)  APS  86:51:6  22.0  —  —  —  —  T1D  80:20:0  10.0  2.67 (1.52–4.68)  0.001  2.65 (1.47–4.80)  0.001  HT  65:29:6  20.5  1.09 (0.71–1.70)  0.689  1.23 (0.72–2.09)  0.442    GD  75:24:1  13.0  1.94 (1.16–3.25)  0.011  1.99 (1.13–3.49)  0.017    C  85:14:1  8.0  3.31 (1.82–6.02)  <0.001  3.76 (1.97–7.14)  <0.001  CTLA-4 CT60c  APS  65:56:22  65.7  —  —  —  —  T1D  36:44:20  58.0  1.30 (0.92–1.85)  0.139  1.38 (0.71–2.68)  0.350  (G:A)  HT  42:42:16  63.0  1.08 (0.76–1.54)  0.664  1.05 (0.52–2.11)  0.896    GD  40:45:15  62.5  1.11 (0.77–1.58)  0.585  0.97 (0.48–1.98)  0.935    C  27:51:22  53.0  1.63 (1.13–2.33)  0.008  1.55 (0.81–2.99)  0.190  CTLA-4  APS  45:72:26  43.4  —  —  —  —  AG49  T1D  41:47:12  35.5  1.40 (0.96–2.05)  0.081  1.51 (0.89–2.58)  0.126  (A:G)  HT  30:45:16  43.0  1.02 (0.70–1.48)  0.936  0.93 (0.54–1.63)  0.808    GD  33:43:24  45.5  0.92 (0.64–1.31)  0.646  1.07 (0.62–1.85)  0.801    C  36:40:24  44.5  0.98 (0.69–1.39)  0.891  1.23 (0.71–2.10)  0.461  Bsm I  APS  55:64:24  39.2  —  —  —  —  (C:T)  T1D  34:49:17  41.5  0.91 (0.63–1.31)  0.610  0.82 (0.48–1.41)  0.478    HT  39:45:16  37.5  1.03 (0.72–1.47)  0.886  1.02 (0.61–1.73)  0.932    GD  35:46:19  42.0  0.86 (0.63–1.28)  0.542  0.86 (0.51–1.47)  0.583    C  37:50:13  38.0  1.05 (0.73–1.52)  0.797  0.94 (0.55–1.59)  0.818  Apa I  APS  42:67:34  47.2  —  —  —  —  (A:C)  T1D  30:45:25  47.5  0.99 (0.70–1.40)  0.950  1.03 (0.59–1.80)  0.916    HT  27:48:25  49.5  0.93 (0.66–1.33)  0.704  0.89 (0.50–1.57)  0.687    GD  29:45:26  48.5  0.95 (0.67–1.35)  0.786  0.98 (0.56–1.72)  0.950    C  31:45:24  46.5  1.03 (0.72–1.46)  0.883  1.08 (0.62–1.88)  0.785  Taq I  APS  52:64:27  41.3  —  —  —  —  (T:C)  T1D  36:46:18  41.0  1.01 (0.71–1.44)  0.956  0.98 (0.58–1.68)  0.954    HT  40:45:15  37.5  1.16 (0.81–1.66)  0.419  1.17 (0.69–1.97)  0.565    GD  39:43:18  39.5  1.07 (0.75–1.52)  0.709  1.12 (0.66–1.89)  0.676    C  38:49:13  37.5  1.17 (0.81–1.68)  0.412  1.07 (0.63–1.82)  0.795  IL2RA  APS  35:73:35  50.0  —  —  —  —  (A:G)  T1D  30:54:16  43.0  1.35 (0.93–1.96)  0.120  1.32 (0.75–2.35)  0.339    HT  36:44:20  42.0  1.37 (0.95–1.97)  0.088  1.74 (0.99–3.03)  0.053    GD  34:51:15  40.5  1.49 (1.02–2.17)  0.037  1.59 (0.91–2.79)  0.106    C  32:48:20  44.0  1.27 (0.88–1.83)  0.194  1.45 (0.82–2.56)  0.198  TNF-α‒863 (C:A)  APS  101:37:5  16.4  —  —  —  —  T1D  60:35:5  22.5  0.68 (0.44–1.08)  0.101  0.62 (0.36–1.07)  0.098  HT  68:26:6  19.0  0.85 (0.54–1.34)  0.486  0.88 (0.51–1.54)  0.661    GD  74:23:3  14.5  1.15 (0.71–1.87)  0.576  1.18 (0.67–2.10)  0.565    C  77:20:3  13.0  1.29 (0.78–2.13)  0.318  1.39 (0.77–2.51)  0.271  Locus with (wild-type:alternative type) indicated in parentheses. Genotype frequencies given counts for WW:WA:AA, with W (A) indicating a wild-type (alternative type) allele. For controlling family-wise type 1 error at 0.05 within SNP locus over four comparisons to different comparator sets, P values <0.0125 are statistically significant. For controlling family-wise type 1 error over nine SNPs in addition, the critical P value is 0.0014. Abbreviations: AA, alternative/alternative genotype; C, control; WA, wild-type/alternative genotype; WW, wild-type/wild-type genotype. a Allelic OR based on multiplicative risk model. b OR for common dominant model. c ORs are defined with alternative type (A) considered as reference. View Large Table 3. Genetic Associations SNP Locus  Group  Genotype Counts WW:WA:AA  Allele Frequency (%)  Allelic ORa APS vs Comparator  P Value  Common Dominant Model ORb APS vs Comparator  P Value  PTPN22 +1858 (C:T)  APS  86:51:6  22.0  —  —  —  —  T1D  80:20:0  10.0  2.67 (1.52–4.68)  0.001  2.65 (1.47–4.80)  0.001  HT  65:29:6  20.5  1.09 (0.71–1.70)  0.689  1.23 (0.72–2.09)  0.442    GD  75:24:1  13.0  1.94 (1.16–3.25)  0.011  1.99 (1.13–3.49)  0.017    C  85:14:1  8.0  3.31 (1.82–6.02)  <0.001  3.76 (1.97–7.14)  <0.001  CTLA-4 CT60c  APS  65:56:22  65.7  —  —  —  —  T1D  36:44:20  58.0  1.30 (0.92–1.85)  0.139  1.38 (0.71–2.68)  0.350  (G:A)  HT  42:42:16  63.0  1.08 (0.76–1.54)  0.664  1.05 (0.52–2.11)  0.896    GD  40:45:15  62.5  1.11 (0.77–1.58)  0.585  0.97 (0.48–1.98)  0.935    C  27:51:22  53.0  1.63 (1.13–2.33)  0.008  1.55 (0.81–2.99)  0.190  CTLA-4  APS  45:72:26  43.4  —  —  —  —  AG49  T1D  41:47:12  35.5  1.40 (0.96–2.05)  0.081  1.51 (0.89–2.58)  0.126  (A:G)  HT  30:45:16  43.0  1.02 (0.70–1.48)  0.936  0.93 (0.54–1.63)  0.808    GD  33:43:24  45.5  0.92 (0.64–1.31)  0.646  1.07 (0.62–1.85)  0.801    C  36:40:24  44.5  0.98 (0.69–1.39)  0.891  1.23 (0.71–2.10)  0.461  Bsm I  APS  55:64:24  39.2  —  —  —  —  (C:T)  T1D  34:49:17  41.5  0.91 (0.63–1.31)  0.610  0.82 (0.48–1.41)  0.478    HT  39:45:16  37.5  1.03 (0.72–1.47)  0.886  1.02 (0.61–1.73)  0.932    GD  35:46:19  42.0  0.86 (0.63–1.28)  0.542  0.86 (0.51–1.47)  0.583    C  37:50:13  38.0  1.05 (0.73–1.52)  0.797  0.94 (0.55–1.59)  0.818  Apa I  APS  42:67:34  47.2  —  —  —  —  (A:C)  T1D  30:45:25  47.5  0.99 (0.70–1.40)  0.950  1.03 (0.59–1.80)  0.916    HT  27:48:25  49.5  0.93 (0.66–1.33)  0.704  0.89 (0.50–1.57)  0.687    GD  29:45:26  48.5  0.95 (0.67–1.35)  0.786  0.98 (0.56–1.72)  0.950    C  31:45:24  46.5  1.03 (0.72–1.46)  0.883  1.08 (0.62–1.88)  0.785  Taq I  APS  52:64:27  41.3  —  —  —  —  (T:C)  T1D  36:46:18  41.0  1.01 (0.71–1.44)  0.956  0.98 (0.58–1.68)  0.954    HT  40:45:15  37.5  1.16 (0.81–1.66)  0.419  1.17 (0.69–1.97)  0.565    GD  39:43:18  39.5  1.07 (0.75–1.52)  0.709  1.12 (0.66–1.89)  0.676    C  38:49:13  37.5  1.17 (0.81–1.68)  0.412  1.07 (0.63–1.82)  0.795  IL2RA  APS  35:73:35  50.0  —  —  —  —  (A:G)  T1D  30:54:16  43.0  1.35 (0.93–1.96)  0.120  1.32 (0.75–2.35)  0.339    HT  36:44:20  42.0  1.37 (0.95–1.97)  0.088  1.74 (0.99–3.03)  0.053    GD  34:51:15  40.5  1.49 (1.02–2.17)  0.037  1.59 (0.91–2.79)  0.106    C  32:48:20  44.0  1.27 (0.88–1.83)  0.194  1.45 (0.82–2.56)  0.198  TNF-α‒863 (C:A)  APS  101:37:5  16.4  —  —  —  —  T1D  60:35:5  22.5  0.68 (0.44–1.08)  0.101  0.62 (0.36–1.07)  0.098  HT  68:26:6  19.0  0.85 (0.54–1.34)  0.486  0.88 (0.51–1.54)  0.661    GD  74:23:3  14.5  1.15 (0.71–1.87)  0.576  1.18 (0.67–2.10)  0.565    C  77:20:3  13.0  1.29 (0.78–2.13)  0.318  1.39 (0.77–2.51)  0.271  SNP Locus  Group  Genotype Counts WW:WA:AA  Allele Frequency (%)  Allelic ORa APS vs Comparator  P Value  Common Dominant Model ORb APS vs Comparator  P Value  PTPN22 +1858 (C:T)  APS  86:51:6  22.0  —  —  —  —  T1D  80:20:0  10.0  2.67 (1.52–4.68)  0.001  2.65 (1.47–4.80)  0.001  HT  65:29:6  20.5  1.09 (0.71–1.70)  0.689  1.23 (0.72–2.09)  0.442    GD  75:24:1  13.0  1.94 (1.16–3.25)  0.011  1.99 (1.13–3.49)  0.017    C  85:14:1  8.0  3.31 (1.82–6.02)  <0.001  3.76 (1.97–7.14)  <0.001  CTLA-4 CT60c  APS  65:56:22  65.7  —  —  —  —  T1D  36:44:20  58.0  1.30 (0.92–1.85)  0.139  1.38 (0.71–2.68)  0.350  (G:A)  HT  42:42:16  63.0  1.08 (0.76–1.54)  0.664  1.05 (0.52–2.11)  0.896    GD  40:45:15  62.5  1.11 (0.77–1.58)  0.585  0.97 (0.48–1.98)  0.935    C  27:51:22  53.0  1.63 (1.13–2.33)  0.008  1.55 (0.81–2.99)  0.190  CTLA-4  APS  45:72:26  43.4  —  —  —  —  AG49  T1D  41:47:12  35.5  1.40 (0.96–2.05)  0.081  1.51 (0.89–2.58)  0.126  (A:G)  HT  30:45:16  43.0  1.02 (0.70–1.48)  0.936  0.93 (0.54–1.63)  0.808    GD  33:43:24  45.5  0.92 (0.64–1.31)  0.646  1.07 (0.62–1.85)  0.801    C  36:40:24  44.5  0.98 (0.69–1.39)  0.891  1.23 (0.71–2.10)  0.461  Bsm I  APS  55:64:24  39.2  —  —  —  —  (C:T)  T1D  34:49:17  41.5  0.91 (0.63–1.31)  0.610  0.82 (0.48–1.41)  0.478    HT  39:45:16  37.5  1.03 (0.72–1.47)  0.886  1.02 (0.61–1.73)  0.932    GD  35:46:19  42.0  0.86 (0.63–1.28)  0.542  0.86 (0.51–1.47)  0.583    C  37:50:13  38.0  1.05 (0.73–1.52)  0.797  0.94 (0.55–1.59)  0.818  Apa I  APS  42:67:34  47.2  —  —  —  —  (A:C)  T1D  30:45:25  47.5  0.99 (0.70–1.40)  0.950  1.03 (0.59–1.80)  0.916    HT  27:48:25  49.5  0.93 (0.66–1.33)  0.704  0.89 (0.50–1.57)  0.687    GD  29:45:26  48.5  0.95 (0.67–1.35)  0.786  0.98 (0.56–1.72)  0.950    C  31:45:24  46.5  1.03 (0.72–1.46)  0.883  1.08 (0.62–1.88)  0.785  Taq I  APS  52:64:27  41.3  —  —  —  —  (T:C)  T1D  36:46:18  41.0  1.01 (0.71–1.44)  0.956  0.98 (0.58–1.68)  0.954    HT  40:45:15  37.5  1.16 (0.81–1.66)  0.419  1.17 (0.69–1.97)  0.565    GD  39:43:18  39.5  1.07 (0.75–1.52)  0.709  1.12 (0.66–1.89)  0.676    C  38:49:13  37.5  1.17 (0.81–1.68)  0.412  1.07 (0.63–1.82)  0.795  IL2RA  APS  35:73:35  50.0  —  —  —  —  (A:G)  T1D  30:54:16  43.0  1.35 (0.93–1.96)  0.120  1.32 (0.75–2.35)  0.339    HT  36:44:20  42.0  1.37 (0.95–1.97)  0.088  1.74 (0.99–3.03)  0.053    GD  34:51:15  40.5  1.49 (1.02–2.17)  0.037  1.59 (0.91–2.79)  0.106    C  32:48:20  44.0  1.27 (0.88–1.83)  0.194  1.45 (0.82–2.56)  0.198  TNF-α‒863 (C:A)  APS  101:37:5  16.4  —  —  —  —  T1D  60:35:5  22.5  0.68 (0.44–1.08)  0.101  0.62 (0.36–1.07)  0.098  HT  68:26:6  19.0  0.85 (0.54–1.34)  0.486  0.88 (0.51–1.54)  0.661    GD  74:23:3  14.5  1.15 (0.71–1.87)  0.576  1.18 (0.67–2.10)  0.565    C  77:20:3  13.0  1.29 (0.78–2.13)  0.318  1.39 (0.77–2.51)  0.271  Locus with (wild-type:alternative type) indicated in parentheses. Genotype frequencies given counts for WW:WA:AA, with W (A) indicating a wild-type (alternative type) allele. For controlling family-wise type 1 error at 0.05 within SNP locus over four comparisons to different comparator sets, P values <0.0125 are statistically significant. For controlling family-wise type 1 error over nine SNPs in addition, the critical P value is 0.0014. Abbreviations: AA, alternative/alternative genotype; C, control; WA, wild-type/alternative genotype; WW, wild-type/wild-type genotype. a Allelic OR based on multiplicative risk model. b OR for common dominant model. c ORs are defined with alternative type (A) considered as reference. View Large CTLA-4 CT60 and AG49 The SNP CTLA-4 CT60 G-allele carriers were present in 85%, 80%, and 78% of patients with APS, patients with T1D (OR: 1.55; 95% CI: 0.81 to 2.99; P = 0.190), and controls (OR: 1.38; 95% CI: 0.71 to 2.68; P = 0.350), respectively. The GG genotype was more common in APS (46%) than in controls (27%; OR: 2.25; 95% CI: 1.30 to 3.91; P = 0.004). The G-allele frequency was highest in APS and lowest in controls (OR: 1.68; 95% CI: 1.18 to 2.46; P = 0.005). In comparison, no significant differences were noted for the SNP CTLA-4 AG49. Considering genotype combinations, the AG/GG combination was more common in APS than in controls (OR: 4.89; 95% CI: 1.86 to 13.59; P = 0.00018). Differences were also found comparing APS with GD (OR: 2.52; 95% CI: 1.15 to 5.64; P = 0.0116). The genotype combination AG/AG was equally frequent in all collectives. The haplotype distribution is shown in Table 4. The haplotype AG occurred more frequently in APS (OR: 2.33; 95% CI: 1.34 to 4.07; P = 0.00122), whereas the AA haplotype was rare vs controls (OR: 0.64; 95% CI: 0.43 to 0.94; P = 0.0168). Table 4. Haplotype Allele Frequency of Both CTLA-4 SNPs CT60 and AG49 Haplotype CT60/AG49  APS 
N (%)  T1D 
N (%)  HT 
N (%)  GD 
N (%)  C 
N (%)  APS/C Comparator Haplotype vs AA Haplotype OR (95% CI)/P Value  AA  98 (34.3)  82 (41.0)  74 (37.0)  74 (37.0)  90 (45.0)  n.a.  AG  64 (22.4)  47 (23.5)  40 (20.0)  35 (17.5)  22 (11.0)  2.67 (1.52–4.69)/0.0013  GA  2 (0.7)  2 (1.0)    1 (0.5)  5 (2.5)  0.37 (0.07–1.94)/0.0902  GG  122 (42.7)  69 (34.5)  86 (43.0)  90 (45.0)  83 (41.5)  1.35 (0.91–2.01)/0.3495  All  286  200  200  200  200    Haplotype CT60/AG49  APS 
N (%)  T1D 
N (%)  HT 
N (%)  GD 
N (%)  C 
N (%)  APS/C Comparator Haplotype vs AA Haplotype OR (95% CI)/P Value  AA  98 (34.3)  82 (41.0)  74 (37.0)  74 (37.0)  90 (45.0)  n.a.  AG  64 (22.4)  47 (23.5)  40 (20.0)  35 (17.5)  22 (11.0)  2.67 (1.52–4.69)/0.0013  GA  2 (0.7)  2 (1.0)    1 (0.5)  5 (2.5)  0.37 (0.07–1.94)/0.0902  GG  122 (42.7)  69 (34.5)  86 (43.0)  90 (45.0)  83 (41.5)  1.35 (0.91–2.01)/0.3495  All  286  200  200  200  200    The AA and GG haplotypes predominate, whereas GA is very rare. The AG haplotype conferred risk to APS compared with the AA haplotype (P = 0.0013) and was significantly more common in APS than in Cs (P = 0.00122). Abbreviations: C, control; n.a., not applicable. View Large Table 4. Haplotype Allele Frequency of Both CTLA-4 SNPs CT60 and AG49 Haplotype CT60/AG49  APS 
N (%)  T1D 
N (%)  HT 
N (%)  GD 
N (%)  C 
N (%)  APS/C Comparator Haplotype vs AA Haplotype OR (95% CI)/P Value  AA  98 (34.3)  82 (41.0)  74 (37.0)  74 (37.0)  90 (45.0)  n.a.  AG  64 (22.4)  47 (23.5)  40 (20.0)  35 (17.5)  22 (11.0)  2.67 (1.52–4.69)/0.0013  GA  2 (0.7)  2 (1.0)    1 (0.5)  5 (2.5)  0.37 (0.07–1.94)/0.0902  GG  122 (42.7)  69 (34.5)  86 (43.0)  90 (45.0)  83 (41.5)  1.35 (0.91–2.01)/0.3495  All  286  200  200  200  200    Haplotype CT60/AG49  APS 
N (%)  T1D 
N (%)  HT 
N (%)  GD 
N (%)  C 
N (%)  APS/C Comparator Haplotype vs AA Haplotype OR (95% CI)/P Value  AA  98 (34.3)  82 (41.0)  74 (37.0)  74 (37.0)  90 (45.0)  n.a.  AG  64 (22.4)  47 (23.5)  40 (20.0)  35 (17.5)  22 (11.0)  2.67 (1.52–4.69)/0.0013  GA  2 (0.7)  2 (1.0)    1 (0.5)  5 (2.5)  0.37 (0.07–1.94)/0.0902  GG  122 (42.7)  69 (34.5)  86 (43.0)  90 (45.0)  83 (41.5)  1.35 (0.91–2.01)/0.3495  All  286  200  200  200  200    The AA and GG haplotypes predominate, whereas GA is very rare. The AG haplotype conferred risk to APS compared with the AA haplotype (P = 0.0013) and was significantly more common in APS than in Cs (P = 0.00122). Abbreviations: C, control; n.a., not applicable. View Large VDR The SNPs Bsm I, Apa I, and Taq I were not significantly different in APS vs controls and MGA. In contrast, the haplotypes TAT, TCT, CCC, and CAC were different between the various collectives, with an overall value of P = 0.007. The distribution of the haplotypes is shown in Table 5; the CAC haplotype was more common in APS than in controls (P = 0.045). Table 5. Haplotype Allele Frequency of the VDR SNPs BSM I, APA I, and TAQ I Haplotype Bsm I, Apa I, Taq I  APS
N (%)  T1D
N (%)  HT
N (%)  GD
N (%)  C
N (%)  P Value  CCT  135 (47.2)  91 (45.9)  98 (49.0)  97 (48.5)  93 (46.5)  0.866  TAC  111 (38.8)  79 (39.5)  73 (36.5)  79 (39.5)  75 (37.5)  CAT  32 (11.2)  23 (11.5)  23 (11.5)  19 (9.5)  31 (15.5)  TAT  1 (0.4)  2 (1.0)  4 (2.0)  5 (2.5)  1 (0.5)  0.0011  TCT  —  2 (1.0)  —  —  —  CCC  —  2 (1.0)  —  —  —  CAC  7 (2.5)  1 (0.5)  2 (1.0)  —  —  All  286  200  200  200  200    Haplotype Bsm I, Apa I, Taq I  APS
N (%)  T1D
N (%)  HT
N (%)  GD
N (%)  C
N (%)  P Value  CCT  135 (47.2)  91 (45.9)  98 (49.0)  97 (48.5)  93 (46.5)  0.866  TAC  111 (38.8)  79 (39.5)  73 (36.5)  79 (39.5)  75 (37.5)  CAT  32 (11.2)  23 (11.5)  23 (11.5)  19 (9.5)  31 (15.5)  TAT  1 (0.4)  2 (1.0)  4 (2.0)  5 (2.5)  1 (0.5)  0.0011  TCT  —  2 (1.0)  —  —  —  CCC  —  2 (1.0)  —  —  —  CAC  7 (2.5)  1 (0.5)  2 (1.0)  —  —  All  286  200  200  200  200    CCT, TAC, CAT are the most common haplotypes and showed no significant differences in the distribution between the collectives (χ2 test, excluding rare haplotype, 8 degrees of freedom; P = 0.866). The other haplotypes were rare in this study and showed significant differences in the collective distribution (exact χ2 test for 5 × 5 table, grouping frequent haplotypes into one category; P = 0.0011). View Large Table 5. Haplotype Allele Frequency of the VDR SNPs BSM I, APA I, and TAQ I Haplotype Bsm I, Apa I, Taq I  APS
N (%)  T1D
N (%)  HT
N (%)  GD
N (%)  C
N (%)  P Value  CCT  135 (47.2)  91 (45.9)  98 (49.0)  97 (48.5)  93 (46.5)  0.866  TAC  111 (38.8)  79 (39.5)  73 (36.5)  79 (39.5)  75 (37.5)  CAT  32 (11.2)  23 (11.5)  23 (11.5)  19 (9.5)  31 (15.5)  TAT  1 (0.4)  2 (1.0)  4 (2.0)  5 (2.5)  1 (0.5)  0.0011  TCT  —  2 (1.0)  —  —  —  CCC  —  2 (1.0)  —  —  —  CAC  7 (2.5)  1 (0.5)  2 (1.0)  —  —  All  286  200  200  200  200    Haplotype Bsm I, Apa I, Taq I  APS
N (%)  T1D
N (%)  HT
N (%)  GD
N (%)  C
N (%)  P Value  CCT  135 (47.2)  91 (45.9)  98 (49.0)  97 (48.5)  93 (46.5)  0.866  TAC  111 (38.8)  79 (39.5)  73 (36.5)  79 (39.5)  75 (37.5)  CAT  32 (11.2)  23 (11.5)  23 (11.5)  19 (9.5)  31 (15.5)  TAT  1 (0.4)  2 (1.0)  4 (2.0)  5 (2.5)  1 (0.5)  0.0011  TCT  —  2 (1.0)  —  —  —  CCC  —  2 (1.0)  —  —  —  CAC  7 (2.5)  1 (0.5)  2 (1.0)  —  —  All  286  200  200  200  200    CCT, TAC, CAT are the most common haplotypes and showed no significant differences in the distribution between the collectives (χ2 test, excluding rare haplotype, 8 degrees of freedom; P = 0.866). The other haplotypes were rare in this study and showed significant differences in the collective distribution (exact χ2 test for 5 × 5 table, grouping frequent haplotypes into one category; P = 0.0011). View Large IL2RA and TNF-α No associations for the SNP IL2RA and TNF-α‒863 were found among APS, MGA, and controls regarding allele frequency and genotype distribution. Discussion This study evaluated numerous SNPs in a large group of Caucasian patients with APS. We also compared SNP findings in large groups of patients with APS and three different, well-characterized collectives of MGA diseases (i.e., T1D, HT, and GD). Our patients and controls were carefully selected; patients with MGA had a long disease history and both a negative family history as well as a negative antibody profile for other endocrine/nonendocrine autoimmune disorders. Furthermore, this study involved haplotype and genotype analyses in APS. The presented results emphasize the role of the PTPN22 and CTLA-4CT60 SNPs in increasing the susceptibility risk for APS and potentially differentiating (especially PTPN22) between polyglandular and monoglandular autoimmune diseases. However, this article also underlines that although allele and/or carrier frequency may be similar within the tested collectives, a haplotype and/or genotype analysis may offer different results (15). We identified PTPN22 +1858 as a strong susceptibility polymorphism, increasing the risk for T-allele carriers approximately fourfold for APS and thereby confirming the results of a preliminary study from our own laboratory (10). Compared with the previous report, the current study differentiated between the individual AITDs (GD and HT), showing significant differences in APS vs GD and T1D, thus indicating that the SNP is more relevant in the overall risk for APS than for MGA. In addition, a genotype analysis was performed in markedly larger APS and MGA cohorts. Pertaining to the individual patient collectives, the SNP +1858 appears to also play a role in the etiology of HT, as statistical significance was lost when APS and HT were compared. However, because a higher percentage of our APS patients had HT (63%) than GD (37%), the separate comparisons of APS-HT and APS-GD vs controls were highly significant. Comparable conclusions were drawn from two other studies focusing on T1D and indicating the T-allele as a risk factor for MGA and additional autoimmune diseases (11, 31). Finally, in the first performed genome-wide association study in patients with APS, the PTPN gene on chromosome one was recognized as a susceptibility gene with a significantly increased log score (32). The current study also demonstrated a clear association of the SNP CT60 on the CTLA-4 gene with APS, resulting in a twofold-increased risk for GG genotype carriers. Only a homozygous wild-type genotype seemed to have a sufficiently negative influence on the protein function of CTLA-4, promoting the development of an autoimmune disease and suggesting a recessive mode of inheritance, whereas the alternative type was similarly protective in the homozygous and heterozygous genotypes. Dissecting the joint genetic susceptibility in large cohorts of patients with mono- and polyglandular autoimmunity, the current study confirmed preliminary data from our laboratory (29) and others (33) that the G-allele was preferably given to children with AITD and/or T1D in multiplex families. In comparison, CTLA-4 was not associated with endocrine autoimmunity in a small study from Japan (15). Although associations of the SNP AG49 with autoimmune diseases are described in the literature, we did not observe an association between AG49 and APS. Thus, results from MGA studies cannot be transferred to polyglandular diseases. Conflicting results with Asian studies may be due to genetic and geographical differences (16, 17) as well as to linkage disequilibrium and a smaller number of examined Asian subjects. Of note, haplotype analysis of the two CTLA-4 SNPs was informative and showed enhanced susceptibility to APS for the AG haplotype, whereas the AA haplotype was protective. These results are in line with those highlighting the GG and AG haplotypes as susceptibility haplotypes for the two MGA diseases HT and GD in contrast to the AA haplotype (14). The prevalence of the SNPs vitamin D, IL2RA, and TNF-α did not differ in the various collectives. In comparison, associations between Apa I and Taq I with AITD (not APS) have been reported (34, 35), and the CAC and TAT haplotypes were protective for T1D (36) and GD (37), respectively, again emphasizing the genetic difference between APS and MGA. Finally, and in contrast to our findings, a Tunisian study looking at a small group of patients with APS reported that the AA genotype of IL2RA could be considered a potential susceptibility gene (38). The ethnic background and the small number of subjects may explain the discrepancy. One may speculate on the potential translational utility of the study’s findings, how they fit into our current understanding of endocrine autoimmunity, and/or how we think these data will eventually translate to clinical practice. A comparison with the well-known association of the HLA class II “super” antigens DR3 and DR4 as universally acknowledged strong susceptibility genes for T1D (especially) and AITD in general (39, 40) could lead to an “immunogenetic screening package” encompassing the HLA class II DR antigens with the PTPN22 and CTLA-4 polymorphisms, thus helping to predict which patients with a single autoimmune endocrine disorder are likely to progress to APS. This proposed immunogenic profile could be offered to patients with MGA disease and, on the basis of proven prevalent positive family history and familiar clustering (41), also to first-degree relatives of subjects with APS. In conclusion, this study of eight SNPs in a large number of patients with APS, patients with three MGA diseases, and healthy controls demonstrated that the PTPN and CTLA-4 polymorphisms were susceptibility genes for APS and emphasized their role in potential differentiation between polyglandular and MGA. Abbreviations: Abbreviations: AITD autoimmune thyroid disease APS autoimmune polyglandular syndrome CI confidence interval CTLA-4 cytotoxic T-lymphocyte-associated antigen 4 GD Graves disease HLA human leukocyte antigen HT Hashimoto thyroiditis IL interleukin IL2RA interleukin-2 receptor α MGA monoglandular autoimmunity OR odds ratio PCR polymerase chain reaction PTPN22 protein tyrosine phosphatase non-receptor type 22 SBE single-base extension SNP single nucleotide polymorphism T1D type 1 diabetes TNF-α tumor necrosis factor α VDR vitamin D receptor Acknowledgments We thank T. Diana, JGU Thyroid Research Laboratory, M. Kanitz, and P. 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Increased familial clustering of autoimmune thyroid diseases. Horm Metab Res . 2011; 43( 3): 200– 204. Google Scholar CrossRef Search ADS PubMed  Copyright © 2018 Endocrine Society http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Clinical Endocrinology and Metabolism Oxford University Press

PTPN22 and CTLA-4 Polymorphisms Are Associated With Polyglandular Autoimmunity

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Publisher
Endocrine Society
Copyright
Copyright © 2018 Endocrine Society
ISSN
0021-972X
eISSN
1945-7197
D.O.I.
10.1210/jc.2017-02577
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Abstract

Abstract Context Single nucleotide polymorphisms (SNPs) of various genes increase susceptibility to monoglandular autoimmunity. Data on autoimmune polyglandular syndromes (APSs) are scarce. Objective Evaluate potential associations of eight SNPs with APSs. Setting Academic referral endocrine clinic. Patients A total of 543 patients with APS and monoglandular autoimmunity and controls. Intervention The SNP protein tyrosine phosphatase nonreceptor type 22 (PTPN22) rs2476601 (+1858); cytotoxic T-lymphocyte‒associated antigen 4 (CTLA-4) rs3087243 (CT60) and rs231775 (AG49); vitamin D receptor (VDR) rs1544410 (Bsm I), rs7975232 (Apa I), rs731236 (Taq I); tumor necrosis factor α rs1800630 (-863); and interleukin-2 receptor alpha rs10795791 were tested by single-base extension in all subjects. Results The PTPN22 +1858 allele and genotype distribution were markedly different between APS, type 1 diabetes [T1D; odds ratio (OR): 2.67; 95% confidence interval (CI): 1.52 to 4.68; P = 0.001], Graves disease (GD; OR: 1.94; 95% CI: 1.16 to 3.25; P = 0.011), and controls (OR: 3.31, 95% CI: 1.82 to 6.02; P < 0.001). T-allele carriers’ risk for APS was increased (OR: 3.76; 95% CI: 1.97 to 7.14; P < 0.001). T-allele frequency was higher among APS than controls (OR: 3.25; 95% CI: 1.82 to 5.82; P < 0.001), T1D (OR: 2.54; 95% CI: 1.48 to 4.36; P = 0.001), or GD (OR: 1.89; 95% CI: 1.15 to 3.11; P = 0.012). The SNP CTLA-4 CT60 G-allele carriers were more frequent in APS (85%) than controls (78%) (OR: 1.55; 95% CI: 0.81 to 2.99). Combined analysis of CTLA-4 AG49 and CT60 revealed OR 4.89; 95% CI: 1.86 to13.59; P = 0.00018 of the genotype combination AG/GG for APS vs controls. VDR polymorphisms Bsm I, Apa I, and Taq I did not, but the haplotypes differed between APS and controls (P = 0.0011). Conclusions PTPN22 and CTLA-4 polymorphisms are associated with APS and differentiate between polyglandular and monoglandular autoimmunity. Autoimmune polyglandular syndrome (APS) is defined as the concomitance of at least two autoimmune-induced endocrine diseases and is divided into juvenile monogenic and polygenic adult types (1, 2). The most frequent adult variant encompasses type 1 diabetes (T1D) and an autoimmune thyroid disease (AITD), also reported as type 3 variant (3–6). Genotyping of the human leukocyte antigens (HLAs) class II differentiates between patients with monoglandular autoimmune (MGA) diseases and those with APS (7) as well as between various APS types (8). Compared with HLA reports, several studies looked at the association between single nucleotide polymorphisms (SNPs) and MGA in different populations; however, studies pertaining to gene polymorphisms and APS are scarce. Large replication studies are lacking, and most clues are drawn from studies in patients with MGA. Indeed and in detail, the protein tyrosine phosphatase nonreceptor type 22 gene (PTPN22) encodes lymphoid tyrosine phosphatase, one of the strongest inhibitors of T-cell activation (9). A functional C→T SNP at position 1858 leads to an arginine→tryptophan amino acid substitution at codon 620. The PTPN22 +1858 polymorphism (rs2476601), especially the minor T-allele of this polymorphism (10), increases susceptibility to MGA (10–13). The cytotoxic T-lymphocyte‒associated antigen 4 (CTLA-4) is a negative regulator of T-cell activation. Two SNPs, CT60 (rs3087243) and AG49 (rs231775), are associated with a lower level of soluble CTLA-4 and therefore less regulation of T-cells, leading to increased autoimmune reactivity. The two SNPs have been associated with MGA. Furthermore, the already described CT60/AG49 haplotype variants AG, GA, AA, and GG are SNPs that significantly alter gene function (14–17). Vitamin D3 exerts its immune modulatory function through the steroid vitamin D receptor (VDR). The VDR is expressed on immune cells and directly inhibits activated T-cells and reduces the production of proinflammatory cytokines. High doses of vitamin D significantly reduced the occurrence of T1D in humans and the risk of AITD in an animal model through suppression of activated T-cells, improvement of phagocytosis, and suppression of interferon γ production (18, 19). The three SNPs Bsm I (rs1544410), Apa I (rs7975232), and Taq I (rs731236) have been associated with MGA (20–23). Interleukin (IL)-2 is a growth, survival, and differentiation factor of T-cells. It regulates the function of natural killer cells, B-cells, and T-regulatory cells by activating the IL receptor. Alterations in the α-chain of the IL2 receptor (IL2RA; rs10795791) or lower receptor expression was associated with MGA (24, 25). Tumor necrosis factor α (TNF-α) is a proinflammatory cytokine and a potent modulator of the immune response (26). A polymorphism in the promoter region [i.e.,TNF-α‒863 (rs1800630)] changes the transcription frequency and thereby increases the production of TNF-α (27). A meta-analysis including Asian and Caucasian collectives showed an association of this SNP with the occurrence of Graves disease (GD) (28). Because the previously mentioned studies refer exclusively to patients with MGA, we evaluated the potential association of eight SNPs with APS in Caucasians. We aimed to look for the potential translational value of knowing the SNP associations, such as predicting which patients with a single autoimmune endocrine disorder are likely to progress to APS, or to assist in the design of precise interventions. Material and Methods Subjects A total of 543 Caucasians [143 patients with APS; 100 each with T1D, Hashimoto thyroiditis (HT), or GD; and 100 healthy controls] followed at the referral outpatient clinic for endocrine autoimmune diseases, Gutenberg University Medical Center, were included in this study. HT was defined as the presence of at least fivefold-increased serum level of thyroid peroxidase autoantibodies, a hypoechoic ultrasonography pattern, and euthyroidism or hypothyroidism. GD was defined as hyperthyroidism, the presence of thyroid-stimulating hormone‒receptor autoantibodies, and a typical thyroid ultrasonography pattern with enhanced vascularization of the thyroid gland. T1D was defined as insulin dependency; positive autoantibodies against the islet cell antigens and/or tyrosine phosphatase and/or insulin and/or glutamic acid decarboxylase-65; a pathologic serum glycemic hemoglobin value >6.5%; and a fasting serum glucose level >120 mg/dL. The 300 patients with well-characterized MGA disorders had an average disease history of 15 years and negative family history of other autoimmune endocrine diseases and were all negative for other specific endocrine autoantibodies, thus allowing a distinction between APS and MGA. Patients with further endocrine and nonendocrine autoimmune diseases were excluded from this study. All healthy controls were unrelated to any diseased patient and were devoid of personal and family history of autoimmune, tumor, and infectious diseases. All controls had documented negative thyroid and pancreatic antibody test results. Furthermore, controls were selected on the basis of nonsmoking status and no alcohol consumption and were not taking any medication. Subsequent to clinical investigation, blood samples were collected. All subjects gave written informed consent for genetic analysis and participation in this study, which was approved by the ethical committee of the Gutenberg University Medical Center and of the state of Rhineland-Palatinate, Germany. DNA extraction, polymerase chain reaction amplification, and single-base extension The DNA from blood samples was extracted with the QIAamp® DNA Blood Mini Kit (Qiagen GmbH, Hilden, Germany) according to manufacturer’s protocol. Before polymerase chain reaction (PCR) amplification, some primers had to be newly designed using Clone Manager 9 for Windows (www.scied.com software; Cary, NC). Three primers marked with an asterisk had already been published (10, 29). All primers were checked to avoid primer dimers and secondary structures (listed in Table 1). Because of their close position, ApaI/TaqI could be amplified at one amplicon. Two multiplex PCRs (IL2RA, AG49, PTPN22, TNF-α, and CT60, Bsm I) and one single PCR (Apa I, Taq I) were implemented on a Primus 96 Advanced® Thermal Cycler (Peqlab Biotechnologie GmbH, Erlangen, Germany). Each 20-µL PCR reaction includes 2 µL DNA, 1 µL of forward and reverse primer (10 µM each, with the exception of TNF-α with 20 µM), 0.4 µL (5 U/mL) Taq polymerase (Roche, Mannheim, Germany), 0.5 µL deoxynucleotide-triphosphates (10 mM each base), and 2.5 µL PCR reaction buffer (10×). Cycling was done with an initial denaturation step for 5 minutes at 94°C, followed by 30 cycles with 30 seconds at 94°C, 10 seconds at 56°C, 1 minute at 72°C, and a final extension for 10 minutes at 72°C. The successful amplification was checked by agarose gel electrophoresis. To ensure the correctness of the PCR, each product was sequenced (BigDye Terminator sequencing reagents Version 1.1; Thermo Fisher Scientific, Darmstadt, Germany) and blasted against the National Center for Biotechnology Information database. SNP typing was performed by single-base extension (SBE) (Fig. 1). To remove remaining primers and deoxynucleotide-triphosphates, the PCR products were purified with a mixture of exonuclease 1 and shrimp alkaline phosphatase (ExoSAP-IT; USB Europe, Staufen, Germany). Table 1. Primers Designed for PCR (Forward and Reverse) and Single-Base Extension SNP/rs No.  PCR Primers  Single-Base Extension Primers  PTPN22 1858a/rs2476601  F-GGATAGCAACTGCTCCAAGGATAG  (T)14CAGCTTCCTCAACCACAATAAATGATTCAGGTGTCC  R-CTCTCACCTCCACCATCCAAATAG  CTLA-4 CT60a/rs3087243  F-AGCTTTGCACCAGCCATTACC  (T)24TCCTTTTGATTTCTTCACCACTATTTGGGATATAAC  R-GTGCCAGCTGATAGCAACATAGG  CTLA-4 AG49/rs231775  F-TAAACCCACGGCTTCCTTTCTCG  (T)45AGGCTCAGCTGAACCTGGCT  R-CACTGCCTTTGACTGCTGAAAC  VDR Bsm I/rs1544410  F-TGGCCATCTGCATCGTCTCC  (T)30GAGCAGAGCCTGATGATTGGGAATG  R-CCCTCTTCTCACCTCTAACC  VDR Apa I/rs7975232  F-GCACGGAGAAGTCACTG  (T)40AGAAGAAGGCACAGGAGCTCTCAGCTGGGC  R-CAGCGGATGTACGTCTG  VDR Taq I/rs731236  F-GCACGGAGAAGTCACTG  (T)25GTGCAGGACGCCGCGCTGAT  R-CAGCGGATGTACGTCTG  IL2RA/rs10795791  F-GATCAGGAAAGGCCCACGTATTG  (T)15TAGAAGCTAAGGGCAGAAAT  R-CGGCCTCATCATCACATCACTTG  TNF-α‒863a/rs1800630  F-ATGTGACCACAGCAATGGGTAG  (T)12CCCTCTACATGGCCCTGTCTTCGTTAAG  R-CTTCTTTCATTCTGACCCGGAGAC  SNP/rs No.  PCR Primers  Single-Base Extension Primers  PTPN22 1858a/rs2476601  F-GGATAGCAACTGCTCCAAGGATAG  (T)14CAGCTTCCTCAACCACAATAAATGATTCAGGTGTCC  R-CTCTCACCTCCACCATCCAAATAG  CTLA-4 CT60a/rs3087243  F-AGCTTTGCACCAGCCATTACC  (T)24TCCTTTTGATTTCTTCACCACTATTTGGGATATAAC  R-GTGCCAGCTGATAGCAACATAGG  CTLA-4 AG49/rs231775  F-TAAACCCACGGCTTCCTTTCTCG  (T)45AGGCTCAGCTGAACCTGGCT  R-CACTGCCTTTGACTGCTGAAAC  VDR Bsm I/rs1544410  F-TGGCCATCTGCATCGTCTCC  (T)30GAGCAGAGCCTGATGATTGGGAATG  R-CCCTCTTCTCACCTCTAACC  VDR Apa I/rs7975232  F-GCACGGAGAAGTCACTG  (T)40AGAAGAAGGCACAGGAGCTCTCAGCTGGGC  R-CAGCGGATGTACGTCTG  VDR Taq I/rs731236  F-GCACGGAGAAGTCACTG  (T)25GTGCAGGACGCCGCGCTGAT  R-CAGCGGATGTACGTCTG  IL2RA/rs10795791  F-GATCAGGAAAGGCCCACGTATTG  (T)15TAGAAGCTAAGGGCAGAAAT  R-CGGCCTCATCATCACATCACTTG  TNF-α‒863a/rs1800630  F-ATGTGACCACAGCAATGGGTAG  (T)12CCCTCTACATGGCCCTGTCTTCGTTAAG  R-CTTCTTTCATTCTGACCCGGAGAC  a Previously published primer. View Large Table 1. Primers Designed for PCR (Forward and Reverse) and Single-Base Extension SNP/rs No.  PCR Primers  Single-Base Extension Primers  PTPN22 1858a/rs2476601  F-GGATAGCAACTGCTCCAAGGATAG  (T)14CAGCTTCCTCAACCACAATAAATGATTCAGGTGTCC  R-CTCTCACCTCCACCATCCAAATAG  CTLA-4 CT60a/rs3087243  F-AGCTTTGCACCAGCCATTACC  (T)24TCCTTTTGATTTCTTCACCACTATTTGGGATATAAC  R-GTGCCAGCTGATAGCAACATAGG  CTLA-4 AG49/rs231775  F-TAAACCCACGGCTTCCTTTCTCG  (T)45AGGCTCAGCTGAACCTGGCT  R-CACTGCCTTTGACTGCTGAAAC  VDR Bsm I/rs1544410  F-TGGCCATCTGCATCGTCTCC  (T)30GAGCAGAGCCTGATGATTGGGAATG  R-CCCTCTTCTCACCTCTAACC  VDR Apa I/rs7975232  F-GCACGGAGAAGTCACTG  (T)40AGAAGAAGGCACAGGAGCTCTCAGCTGGGC  R-CAGCGGATGTACGTCTG  VDR Taq I/rs731236  F-GCACGGAGAAGTCACTG  (T)25GTGCAGGACGCCGCGCTGAT  R-CAGCGGATGTACGTCTG  IL2RA/rs10795791  F-GATCAGGAAAGGCCCACGTATTG  (T)15TAGAAGCTAAGGGCAGAAAT  R-CGGCCTCATCATCACATCACTTG  TNF-α‒863a/rs1800630  F-ATGTGACCACAGCAATGGGTAG  (T)12CCCTCTACATGGCCCTGTCTTCGTTAAG  R-CTTCTTTCATTCTGACCCGGAGAC  SNP/rs No.  PCR Primers  Single-Base Extension Primers  PTPN22 1858a/rs2476601  F-GGATAGCAACTGCTCCAAGGATAG  (T)14CAGCTTCCTCAACCACAATAAATGATTCAGGTGTCC  R-CTCTCACCTCCACCATCCAAATAG  CTLA-4 CT60a/rs3087243  F-AGCTTTGCACCAGCCATTACC  (T)24TCCTTTTGATTTCTTCACCACTATTTGGGATATAAC  R-GTGCCAGCTGATAGCAACATAGG  CTLA-4 AG49/rs231775  F-TAAACCCACGGCTTCCTTTCTCG  (T)45AGGCTCAGCTGAACCTGGCT  R-CACTGCCTTTGACTGCTGAAAC  VDR Bsm I/rs1544410  F-TGGCCATCTGCATCGTCTCC  (T)30GAGCAGAGCCTGATGATTGGGAATG  R-CCCTCTTCTCACCTCTAACC  VDR Apa I/rs7975232  F-GCACGGAGAAGTCACTG  (T)40AGAAGAAGGCACAGGAGCTCTCAGCTGGGC  R-CAGCGGATGTACGTCTG  VDR Taq I/rs731236  F-GCACGGAGAAGTCACTG  (T)25GTGCAGGACGCCGCGCTGAT  R-CAGCGGATGTACGTCTG  IL2RA/rs10795791  F-GATCAGGAAAGGCCCACGTATTG  (T)15TAGAAGCTAAGGGCAGAAAT  R-CGGCCTCATCATCACATCACTTG  TNF-α‒863a/rs1800630  F-ATGTGACCACAGCAATGGGTAG  (T)12CCCTCTACATGGCCCTGTCTTCGTTAAG  R-CTTCTTTCATTCTGACCCGGAGAC  a Previously published primer. View Large Figure 1. View largeDownload slide Typing of the eight polymorphisms by single-base extension (SBE). Two examples for SBE typing of IL2RA, TNF-α, Taq I, PTPN22, Bsm I, CT60, AG49, and Apa I. The polymorphisms are shown in order of their respective retention time on the x-axis. In SBE, each primer is elongated by a single fluorescence-labeled nucleotide representing the corresponding polymorphism. Guanine (G) is marked in blue, adenine (A) in green, tyrosine (T) in red, and cytosine (C) in black. The intensity of the peaks is shown in relative fluorescent units (RFU) on the y-axis. The cutoff value was set at 100 RFU. Figure 1. View largeDownload slide Typing of the eight polymorphisms by single-base extension (SBE). Two examples for SBE typing of IL2RA, TNF-α, Taq I, PTPN22, Bsm I, CT60, AG49, and Apa I. The polymorphisms are shown in order of their respective retention time on the x-axis. In SBE, each primer is elongated by a single fluorescence-labeled nucleotide representing the corresponding polymorphism. Guanine (G) is marked in blue, adenine (A) in green, tyrosine (T) in red, and cytosine (C) in black. The intensity of the peaks is shown in relative fluorescent units (RFU) on the y-axis. The cutoff value was set at 100 RFU. Typing of the SNPs was done in two separate multiplex reactions with the ABI PRISM SNaP Shot Multiplex Kit (Thermo Fisher Scientific) using the SBE primers listed in Table 1. In one multiplex, the PCR products for IL2RA, AG49, PTPN22, TNF-α, and CT60 were combined; in the other multiplex, the PCR products for Bsm I, Apa I, and Taq I were chosen. The elongated SBE primers were separated by capillary gel electrophoresis using an ABI PRISM® 3100-Avant Genetic Analyzer (Applied Biosystems, Darmstadt, Germany) with POP-6. Data analysis was completed with 3100-Avant Data Collection Software and GeneMapperTM ID Software Version 3.1. To secure a clear discrimination between homozygotes and heterozygotes, a cutoff level was validated by serial dilutions of the extended primers to a minimal detection level at 100 relative fluorescent units for homozygote alleles. Statistical analysis For statistical analysis, SPSS Statistics 22.0/23.0 was used. Genotype frequencies of all SNPs were tested for Hardy-Weinberg disequilibrium by χ2 test. Statistical associations between genotypes and disease were assessed by reporting allelic odds ratios (ORs) comparing APS with all other groups and common dominant model‒based ORs with 95% confidence intervals (CIs). CIs and corresponding statistical tests emerged from fitting appropriate logistic models. For controlling family-wise type 1 error at 0.05 within SNP locus over four comparisons to different comparator groups, P values <0.0125 were statistically significant. For controlling family-wise type 1 error over nine SNPs in addition, the critical P value was 0.0014. Haplotypes were inferred from genotype combinations. Inference was certain if just one locus was heterozygous. For all others, rare or nonoccurring haplotypes were excluded, and the most likely haplotype was imputed on the basis of meta-analysis data for VDR haplotypes (30) and for CTLA-4 haplotypes (14) (Supplemental Tables 1 and 2). Homogeneity of haplotype allele frequencies across all five groups was assessed by χ2 tests for CTLA-4 haplotypes and the three common VDR haplotypes. Rare VDR haplotype allele frequencies were assessed by an exact test for contingency tables. Contrasts between APS and controls were quantified by allele-level ORs based on 2 × 2 subtables. Results The demographic data of the study collective are shown in Table 2. There were no signs of Hardy-Weinberg disequilibrium in the observed genotypes of all groups. Table 2. Demographic Data Collective  N  Gender (Male/Female)  Age (y) Median (25/75 Percentiles)  Children <18 Years  APS  143  43/100  43 (28/57)  22  T1D + HT  90  25/65  41 (19.8/55.2)  19  T1D + GD  53  35/18  49 (40.5/59)  3  T1D  100  52/48  28 (17/42.8)  27  HT  100  12/88  40.5 (30/50.8)  3  GD  100  21/79  47 (34.3/55.8)  1  C  100  43/57  29 (24/48)  0  Total  543  171/372  40 (26/52)  75  Collective  N  Gender (Male/Female)  Age (y) Median (25/75 Percentiles)  Children <18 Years  APS  143  43/100  43 (28/57)  22  T1D + HT  90  25/65  41 (19.8/55.2)  19  T1D + GD  53  35/18  49 (40.5/59)  3  T1D  100  52/48  28 (17/42.8)  27  HT  100  12/88  40.5 (30/50.8)  3  GD  100  21/79  47 (34.3/55.8)  1  C  100  43/57  29 (24/48)  0  Total  543  171/372  40 (26/52)  75  Abbreviation: C, control. View Large Table 2. Demographic Data Collective  N  Gender (Male/Female)  Age (y) Median (25/75 Percentiles)  Children <18 Years  APS  143  43/100  43 (28/57)  22  T1D + HT  90  25/65  41 (19.8/55.2)  19  T1D + GD  53  35/18  49 (40.5/59)  3  T1D  100  52/48  28 (17/42.8)  27  HT  100  12/88  40.5 (30/50.8)  3  GD  100  21/79  47 (34.3/55.8)  1  C  100  43/57  29 (24/48)  0  Total  543  171/372  40 (26/52)  75  Collective  N  Gender (Male/Female)  Age (y) Median (25/75 Percentiles)  Children <18 Years  APS  143  43/100  43 (28/57)  22  T1D + HT  90  25/65  41 (19.8/55.2)  19  T1D + GD  53  35/18  49 (40.5/59)  3  T1D  100  52/48  28 (17/42.8)  27  HT  100  12/88  40.5 (30/50.8)  3  GD  100  21/79  47 (34.3/55.8)  1  C  100  43/57  29 (24/48)  0  Total  543  171/372  40 (26/52)  75  Abbreviation: C, control. View Large PTPN22 +1858 Allele and genotype distributions were markedly different between APS, MGA [i.e., T1D (OR: 2.67; 95% CI: 1.52 to 4.68; P = 0.001), GD (OR: 1.94; 95% CI: 1.16 to 3.25; P = 0.011)], and controls (OR: 3.31; 95% CI: 1.82 to 6.02; P < 0.001) (Table 3). T-allele carriers’ risk for APS was increased nearly fourfold (OR: 3.76; 95% CI: 1.97 to 7.14; P < 0.001). Considering the 53 patients with T1D + GD, 42% were T-allele carriers compared with only 15% of controls (OR: 4.02; 95% CI: 1.85 to 8.73; P < 0.001). This also held true for the 90 patients with T1D + HT: 39% T-allele carriers vs only 15% of controls (OR: 3.61; 95% CI: 1.80 to 7.21; P < 0.001). The minor T-allele frequency was higher among APS than controls (OR: 3.25; 95% CI: 1.82 to 5.82; P < 0.001), T1D (OR: 2.54; 95% CI: 1.48 to 4.36; P = 0.001), or GD (OR: 1.89; 95% CI: 1.15 to 3.11; P = 0.012). Table 3. Genetic Associations SNP Locus  Group  Genotype Counts WW:WA:AA  Allele Frequency (%)  Allelic ORa APS vs Comparator  P Value  Common Dominant Model ORb APS vs Comparator  P Value  PTPN22 +1858 (C:T)  APS  86:51:6  22.0  —  —  —  —  T1D  80:20:0  10.0  2.67 (1.52–4.68)  0.001  2.65 (1.47–4.80)  0.001  HT  65:29:6  20.5  1.09 (0.71–1.70)  0.689  1.23 (0.72–2.09)  0.442    GD  75:24:1  13.0  1.94 (1.16–3.25)  0.011  1.99 (1.13–3.49)  0.017    C  85:14:1  8.0  3.31 (1.82–6.02)  <0.001  3.76 (1.97–7.14)  <0.001  CTLA-4 CT60c  APS  65:56:22  65.7  —  —  —  —  T1D  36:44:20  58.0  1.30 (0.92–1.85)  0.139  1.38 (0.71–2.68)  0.350  (G:A)  HT  42:42:16  63.0  1.08 (0.76–1.54)  0.664  1.05 (0.52–2.11)  0.896    GD  40:45:15  62.5  1.11 (0.77–1.58)  0.585  0.97 (0.48–1.98)  0.935    C  27:51:22  53.0  1.63 (1.13–2.33)  0.008  1.55 (0.81–2.99)  0.190  CTLA-4  APS  45:72:26  43.4  —  —  —  —  AG49  T1D  41:47:12  35.5  1.40 (0.96–2.05)  0.081  1.51 (0.89–2.58)  0.126  (A:G)  HT  30:45:16  43.0  1.02 (0.70–1.48)  0.936  0.93 (0.54–1.63)  0.808    GD  33:43:24  45.5  0.92 (0.64–1.31)  0.646  1.07 (0.62–1.85)  0.801    C  36:40:24  44.5  0.98 (0.69–1.39)  0.891  1.23 (0.71–2.10)  0.461  Bsm I  APS  55:64:24  39.2  —  —  —  —  (C:T)  T1D  34:49:17  41.5  0.91 (0.63–1.31)  0.610  0.82 (0.48–1.41)  0.478    HT  39:45:16  37.5  1.03 (0.72–1.47)  0.886  1.02 (0.61–1.73)  0.932    GD  35:46:19  42.0  0.86 (0.63–1.28)  0.542  0.86 (0.51–1.47)  0.583    C  37:50:13  38.0  1.05 (0.73–1.52)  0.797  0.94 (0.55–1.59)  0.818  Apa I  APS  42:67:34  47.2  —  —  —  —  (A:C)  T1D  30:45:25  47.5  0.99 (0.70–1.40)  0.950  1.03 (0.59–1.80)  0.916    HT  27:48:25  49.5  0.93 (0.66–1.33)  0.704  0.89 (0.50–1.57)  0.687    GD  29:45:26  48.5  0.95 (0.67–1.35)  0.786  0.98 (0.56–1.72)  0.950    C  31:45:24  46.5  1.03 (0.72–1.46)  0.883  1.08 (0.62–1.88)  0.785  Taq I  APS  52:64:27  41.3  —  —  —  —  (T:C)  T1D  36:46:18  41.0  1.01 (0.71–1.44)  0.956  0.98 (0.58–1.68)  0.954    HT  40:45:15  37.5  1.16 (0.81–1.66)  0.419  1.17 (0.69–1.97)  0.565    GD  39:43:18  39.5  1.07 (0.75–1.52)  0.709  1.12 (0.66–1.89)  0.676    C  38:49:13  37.5  1.17 (0.81–1.68)  0.412  1.07 (0.63–1.82)  0.795  IL2RA  APS  35:73:35  50.0  —  —  —  —  (A:G)  T1D  30:54:16  43.0  1.35 (0.93–1.96)  0.120  1.32 (0.75–2.35)  0.339    HT  36:44:20  42.0  1.37 (0.95–1.97)  0.088  1.74 (0.99–3.03)  0.053    GD  34:51:15  40.5  1.49 (1.02–2.17)  0.037  1.59 (0.91–2.79)  0.106    C  32:48:20  44.0  1.27 (0.88–1.83)  0.194  1.45 (0.82–2.56)  0.198  TNF-α‒863 (C:A)  APS  101:37:5  16.4  —  —  —  —  T1D  60:35:5  22.5  0.68 (0.44–1.08)  0.101  0.62 (0.36–1.07)  0.098  HT  68:26:6  19.0  0.85 (0.54–1.34)  0.486  0.88 (0.51–1.54)  0.661    GD  74:23:3  14.5  1.15 (0.71–1.87)  0.576  1.18 (0.67–2.10)  0.565    C  77:20:3  13.0  1.29 (0.78–2.13)  0.318  1.39 (0.77–2.51)  0.271  SNP Locus  Group  Genotype Counts WW:WA:AA  Allele Frequency (%)  Allelic ORa APS vs Comparator  P Value  Common Dominant Model ORb APS vs Comparator  P Value  PTPN22 +1858 (C:T)  APS  86:51:6  22.0  —  —  —  —  T1D  80:20:0  10.0  2.67 (1.52–4.68)  0.001  2.65 (1.47–4.80)  0.001  HT  65:29:6  20.5  1.09 (0.71–1.70)  0.689  1.23 (0.72–2.09)  0.442    GD  75:24:1  13.0  1.94 (1.16–3.25)  0.011  1.99 (1.13–3.49)  0.017    C  85:14:1  8.0  3.31 (1.82–6.02)  <0.001  3.76 (1.97–7.14)  <0.001  CTLA-4 CT60c  APS  65:56:22  65.7  —  —  —  —  T1D  36:44:20  58.0  1.30 (0.92–1.85)  0.139  1.38 (0.71–2.68)  0.350  (G:A)  HT  42:42:16  63.0  1.08 (0.76–1.54)  0.664  1.05 (0.52–2.11)  0.896    GD  40:45:15  62.5  1.11 (0.77–1.58)  0.585  0.97 (0.48–1.98)  0.935    C  27:51:22  53.0  1.63 (1.13–2.33)  0.008  1.55 (0.81–2.99)  0.190  CTLA-4  APS  45:72:26  43.4  —  —  —  —  AG49  T1D  41:47:12  35.5  1.40 (0.96–2.05)  0.081  1.51 (0.89–2.58)  0.126  (A:G)  HT  30:45:16  43.0  1.02 (0.70–1.48)  0.936  0.93 (0.54–1.63)  0.808    GD  33:43:24  45.5  0.92 (0.64–1.31)  0.646  1.07 (0.62–1.85)  0.801    C  36:40:24  44.5  0.98 (0.69–1.39)  0.891  1.23 (0.71–2.10)  0.461  Bsm I  APS  55:64:24  39.2  —  —  —  —  (C:T)  T1D  34:49:17  41.5  0.91 (0.63–1.31)  0.610  0.82 (0.48–1.41)  0.478    HT  39:45:16  37.5  1.03 (0.72–1.47)  0.886  1.02 (0.61–1.73)  0.932    GD  35:46:19  42.0  0.86 (0.63–1.28)  0.542  0.86 (0.51–1.47)  0.583    C  37:50:13  38.0  1.05 (0.73–1.52)  0.797  0.94 (0.55–1.59)  0.818  Apa I  APS  42:67:34  47.2  —  —  —  —  (A:C)  T1D  30:45:25  47.5  0.99 (0.70–1.40)  0.950  1.03 (0.59–1.80)  0.916    HT  27:48:25  49.5  0.93 (0.66–1.33)  0.704  0.89 (0.50–1.57)  0.687    GD  29:45:26  48.5  0.95 (0.67–1.35)  0.786  0.98 (0.56–1.72)  0.950    C  31:45:24  46.5  1.03 (0.72–1.46)  0.883  1.08 (0.62–1.88)  0.785  Taq I  APS  52:64:27  41.3  —  —  —  —  (T:C)  T1D  36:46:18  41.0  1.01 (0.71–1.44)  0.956  0.98 (0.58–1.68)  0.954    HT  40:45:15  37.5  1.16 (0.81–1.66)  0.419  1.17 (0.69–1.97)  0.565    GD  39:43:18  39.5  1.07 (0.75–1.52)  0.709  1.12 (0.66–1.89)  0.676    C  38:49:13  37.5  1.17 (0.81–1.68)  0.412  1.07 (0.63–1.82)  0.795  IL2RA  APS  35:73:35  50.0  —  —  —  —  (A:G)  T1D  30:54:16  43.0  1.35 (0.93–1.96)  0.120  1.32 (0.75–2.35)  0.339    HT  36:44:20  42.0  1.37 (0.95–1.97)  0.088  1.74 (0.99–3.03)  0.053    GD  34:51:15  40.5  1.49 (1.02–2.17)  0.037  1.59 (0.91–2.79)  0.106    C  32:48:20  44.0  1.27 (0.88–1.83)  0.194  1.45 (0.82–2.56)  0.198  TNF-α‒863 (C:A)  APS  101:37:5  16.4  —  —  —  —  T1D  60:35:5  22.5  0.68 (0.44–1.08)  0.101  0.62 (0.36–1.07)  0.098  HT  68:26:6  19.0  0.85 (0.54–1.34)  0.486  0.88 (0.51–1.54)  0.661    GD  74:23:3  14.5  1.15 (0.71–1.87)  0.576  1.18 (0.67–2.10)  0.565    C  77:20:3  13.0  1.29 (0.78–2.13)  0.318  1.39 (0.77–2.51)  0.271  Locus with (wild-type:alternative type) indicated in parentheses. Genotype frequencies given counts for WW:WA:AA, with W (A) indicating a wild-type (alternative type) allele. For controlling family-wise type 1 error at 0.05 within SNP locus over four comparisons to different comparator sets, P values <0.0125 are statistically significant. For controlling family-wise type 1 error over nine SNPs in addition, the critical P value is 0.0014. Abbreviations: AA, alternative/alternative genotype; C, control; WA, wild-type/alternative genotype; WW, wild-type/wild-type genotype. a Allelic OR based on multiplicative risk model. b OR for common dominant model. c ORs are defined with alternative type (A) considered as reference. View Large Table 3. Genetic Associations SNP Locus  Group  Genotype Counts WW:WA:AA  Allele Frequency (%)  Allelic ORa APS vs Comparator  P Value  Common Dominant Model ORb APS vs Comparator  P Value  PTPN22 +1858 (C:T)  APS  86:51:6  22.0  —  —  —  —  T1D  80:20:0  10.0  2.67 (1.52–4.68)  0.001  2.65 (1.47–4.80)  0.001  HT  65:29:6  20.5  1.09 (0.71–1.70)  0.689  1.23 (0.72–2.09)  0.442    GD  75:24:1  13.0  1.94 (1.16–3.25)  0.011  1.99 (1.13–3.49)  0.017    C  85:14:1  8.0  3.31 (1.82–6.02)  <0.001  3.76 (1.97–7.14)  <0.001  CTLA-4 CT60c  APS  65:56:22  65.7  —  —  —  —  T1D  36:44:20  58.0  1.30 (0.92–1.85)  0.139  1.38 (0.71–2.68)  0.350  (G:A)  HT  42:42:16  63.0  1.08 (0.76–1.54)  0.664  1.05 (0.52–2.11)  0.896    GD  40:45:15  62.5  1.11 (0.77–1.58)  0.585  0.97 (0.48–1.98)  0.935    C  27:51:22  53.0  1.63 (1.13–2.33)  0.008  1.55 (0.81–2.99)  0.190  CTLA-4  APS  45:72:26  43.4  —  —  —  —  AG49  T1D  41:47:12  35.5  1.40 (0.96–2.05)  0.081  1.51 (0.89–2.58)  0.126  (A:G)  HT  30:45:16  43.0  1.02 (0.70–1.48)  0.936  0.93 (0.54–1.63)  0.808    GD  33:43:24  45.5  0.92 (0.64–1.31)  0.646  1.07 (0.62–1.85)  0.801    C  36:40:24  44.5  0.98 (0.69–1.39)  0.891  1.23 (0.71–2.10)  0.461  Bsm I  APS  55:64:24  39.2  —  —  —  —  (C:T)  T1D  34:49:17  41.5  0.91 (0.63–1.31)  0.610  0.82 (0.48–1.41)  0.478    HT  39:45:16  37.5  1.03 (0.72–1.47)  0.886  1.02 (0.61–1.73)  0.932    GD  35:46:19  42.0  0.86 (0.63–1.28)  0.542  0.86 (0.51–1.47)  0.583    C  37:50:13  38.0  1.05 (0.73–1.52)  0.797  0.94 (0.55–1.59)  0.818  Apa I  APS  42:67:34  47.2  —  —  —  —  (A:C)  T1D  30:45:25  47.5  0.99 (0.70–1.40)  0.950  1.03 (0.59–1.80)  0.916    HT  27:48:25  49.5  0.93 (0.66–1.33)  0.704  0.89 (0.50–1.57)  0.687    GD  29:45:26  48.5  0.95 (0.67–1.35)  0.786  0.98 (0.56–1.72)  0.950    C  31:45:24  46.5  1.03 (0.72–1.46)  0.883  1.08 (0.62–1.88)  0.785  Taq I  APS  52:64:27  41.3  —  —  —  —  (T:C)  T1D  36:46:18  41.0  1.01 (0.71–1.44)  0.956  0.98 (0.58–1.68)  0.954    HT  40:45:15  37.5  1.16 (0.81–1.66)  0.419  1.17 (0.69–1.97)  0.565    GD  39:43:18  39.5  1.07 (0.75–1.52)  0.709  1.12 (0.66–1.89)  0.676    C  38:49:13  37.5  1.17 (0.81–1.68)  0.412  1.07 (0.63–1.82)  0.795  IL2RA  APS  35:73:35  50.0  —  —  —  —  (A:G)  T1D  30:54:16  43.0  1.35 (0.93–1.96)  0.120  1.32 (0.75–2.35)  0.339    HT  36:44:20  42.0  1.37 (0.95–1.97)  0.088  1.74 (0.99–3.03)  0.053    GD  34:51:15  40.5  1.49 (1.02–2.17)  0.037  1.59 (0.91–2.79)  0.106    C  32:48:20  44.0  1.27 (0.88–1.83)  0.194  1.45 (0.82–2.56)  0.198  TNF-α‒863 (C:A)  APS  101:37:5  16.4  —  —  —  —  T1D  60:35:5  22.5  0.68 (0.44–1.08)  0.101  0.62 (0.36–1.07)  0.098  HT  68:26:6  19.0  0.85 (0.54–1.34)  0.486  0.88 (0.51–1.54)  0.661    GD  74:23:3  14.5  1.15 (0.71–1.87)  0.576  1.18 (0.67–2.10)  0.565    C  77:20:3  13.0  1.29 (0.78–2.13)  0.318  1.39 (0.77–2.51)  0.271  SNP Locus  Group  Genotype Counts WW:WA:AA  Allele Frequency (%)  Allelic ORa APS vs Comparator  P Value  Common Dominant Model ORb APS vs Comparator  P Value  PTPN22 +1858 (C:T)  APS  86:51:6  22.0  —  —  —  —  T1D  80:20:0  10.0  2.67 (1.52–4.68)  0.001  2.65 (1.47–4.80)  0.001  HT  65:29:6  20.5  1.09 (0.71–1.70)  0.689  1.23 (0.72–2.09)  0.442    GD  75:24:1  13.0  1.94 (1.16–3.25)  0.011  1.99 (1.13–3.49)  0.017    C  85:14:1  8.0  3.31 (1.82–6.02)  <0.001  3.76 (1.97–7.14)  <0.001  CTLA-4 CT60c  APS  65:56:22  65.7  —  —  —  —  T1D  36:44:20  58.0  1.30 (0.92–1.85)  0.139  1.38 (0.71–2.68)  0.350  (G:A)  HT  42:42:16  63.0  1.08 (0.76–1.54)  0.664  1.05 (0.52–2.11)  0.896    GD  40:45:15  62.5  1.11 (0.77–1.58)  0.585  0.97 (0.48–1.98)  0.935    C  27:51:22  53.0  1.63 (1.13–2.33)  0.008  1.55 (0.81–2.99)  0.190  CTLA-4  APS  45:72:26  43.4  —  —  —  —  AG49  T1D  41:47:12  35.5  1.40 (0.96–2.05)  0.081  1.51 (0.89–2.58)  0.126  (A:G)  HT  30:45:16  43.0  1.02 (0.70–1.48)  0.936  0.93 (0.54–1.63)  0.808    GD  33:43:24  45.5  0.92 (0.64–1.31)  0.646  1.07 (0.62–1.85)  0.801    C  36:40:24  44.5  0.98 (0.69–1.39)  0.891  1.23 (0.71–2.10)  0.461  Bsm I  APS  55:64:24  39.2  —  —  —  —  (C:T)  T1D  34:49:17  41.5  0.91 (0.63–1.31)  0.610  0.82 (0.48–1.41)  0.478    HT  39:45:16  37.5  1.03 (0.72–1.47)  0.886  1.02 (0.61–1.73)  0.932    GD  35:46:19  42.0  0.86 (0.63–1.28)  0.542  0.86 (0.51–1.47)  0.583    C  37:50:13  38.0  1.05 (0.73–1.52)  0.797  0.94 (0.55–1.59)  0.818  Apa I  APS  42:67:34  47.2  —  —  —  —  (A:C)  T1D  30:45:25  47.5  0.99 (0.70–1.40)  0.950  1.03 (0.59–1.80)  0.916    HT  27:48:25  49.5  0.93 (0.66–1.33)  0.704  0.89 (0.50–1.57)  0.687    GD  29:45:26  48.5  0.95 (0.67–1.35)  0.786  0.98 (0.56–1.72)  0.950    C  31:45:24  46.5  1.03 (0.72–1.46)  0.883  1.08 (0.62–1.88)  0.785  Taq I  APS  52:64:27  41.3  —  —  —  —  (T:C)  T1D  36:46:18  41.0  1.01 (0.71–1.44)  0.956  0.98 (0.58–1.68)  0.954    HT  40:45:15  37.5  1.16 (0.81–1.66)  0.419  1.17 (0.69–1.97)  0.565    GD  39:43:18  39.5  1.07 (0.75–1.52)  0.709  1.12 (0.66–1.89)  0.676    C  38:49:13  37.5  1.17 (0.81–1.68)  0.412  1.07 (0.63–1.82)  0.795  IL2RA  APS  35:73:35  50.0  —  —  —  —  (A:G)  T1D  30:54:16  43.0  1.35 (0.93–1.96)  0.120  1.32 (0.75–2.35)  0.339    HT  36:44:20  42.0  1.37 (0.95–1.97)  0.088  1.74 (0.99–3.03)  0.053    GD  34:51:15  40.5  1.49 (1.02–2.17)  0.037  1.59 (0.91–2.79)  0.106    C  32:48:20  44.0  1.27 (0.88–1.83)  0.194  1.45 (0.82–2.56)  0.198  TNF-α‒863 (C:A)  APS  101:37:5  16.4  —  —  —  —  T1D  60:35:5  22.5  0.68 (0.44–1.08)  0.101  0.62 (0.36–1.07)  0.098  HT  68:26:6  19.0  0.85 (0.54–1.34)  0.486  0.88 (0.51–1.54)  0.661    GD  74:23:3  14.5  1.15 (0.71–1.87)  0.576  1.18 (0.67–2.10)  0.565    C  77:20:3  13.0  1.29 (0.78–2.13)  0.318  1.39 (0.77–2.51)  0.271  Locus with (wild-type:alternative type) indicated in parentheses. Genotype frequencies given counts for WW:WA:AA, with W (A) indicating a wild-type (alternative type) allele. For controlling family-wise type 1 error at 0.05 within SNP locus over four comparisons to different comparator sets, P values <0.0125 are statistically significant. For controlling family-wise type 1 error over nine SNPs in addition, the critical P value is 0.0014. Abbreviations: AA, alternative/alternative genotype; C, control; WA, wild-type/alternative genotype; WW, wild-type/wild-type genotype. a Allelic OR based on multiplicative risk model. b OR for common dominant model. c ORs are defined with alternative type (A) considered as reference. View Large CTLA-4 CT60 and AG49 The SNP CTLA-4 CT60 G-allele carriers were present in 85%, 80%, and 78% of patients with APS, patients with T1D (OR: 1.55; 95% CI: 0.81 to 2.99; P = 0.190), and controls (OR: 1.38; 95% CI: 0.71 to 2.68; P = 0.350), respectively. The GG genotype was more common in APS (46%) than in controls (27%; OR: 2.25; 95% CI: 1.30 to 3.91; P = 0.004). The G-allele frequency was highest in APS and lowest in controls (OR: 1.68; 95% CI: 1.18 to 2.46; P = 0.005). In comparison, no significant differences were noted for the SNP CTLA-4 AG49. Considering genotype combinations, the AG/GG combination was more common in APS than in controls (OR: 4.89; 95% CI: 1.86 to 13.59; P = 0.00018). Differences were also found comparing APS with GD (OR: 2.52; 95% CI: 1.15 to 5.64; P = 0.0116). The genotype combination AG/AG was equally frequent in all collectives. The haplotype distribution is shown in Table 4. The haplotype AG occurred more frequently in APS (OR: 2.33; 95% CI: 1.34 to 4.07; P = 0.00122), whereas the AA haplotype was rare vs controls (OR: 0.64; 95% CI: 0.43 to 0.94; P = 0.0168). Table 4. Haplotype Allele Frequency of Both CTLA-4 SNPs CT60 and AG49 Haplotype CT60/AG49  APS 
N (%)  T1D 
N (%)  HT 
N (%)  GD 
N (%)  C 
N (%)  APS/C Comparator Haplotype vs AA Haplotype OR (95% CI)/P Value  AA  98 (34.3)  82 (41.0)  74 (37.0)  74 (37.0)  90 (45.0)  n.a.  AG  64 (22.4)  47 (23.5)  40 (20.0)  35 (17.5)  22 (11.0)  2.67 (1.52–4.69)/0.0013  GA  2 (0.7)  2 (1.0)    1 (0.5)  5 (2.5)  0.37 (0.07–1.94)/0.0902  GG  122 (42.7)  69 (34.5)  86 (43.0)  90 (45.0)  83 (41.5)  1.35 (0.91–2.01)/0.3495  All  286  200  200  200  200    Haplotype CT60/AG49  APS 
N (%)  T1D 
N (%)  HT 
N (%)  GD 
N (%)  C 
N (%)  APS/C Comparator Haplotype vs AA Haplotype OR (95% CI)/P Value  AA  98 (34.3)  82 (41.0)  74 (37.0)  74 (37.0)  90 (45.0)  n.a.  AG  64 (22.4)  47 (23.5)  40 (20.0)  35 (17.5)  22 (11.0)  2.67 (1.52–4.69)/0.0013  GA  2 (0.7)  2 (1.0)    1 (0.5)  5 (2.5)  0.37 (0.07–1.94)/0.0902  GG  122 (42.7)  69 (34.5)  86 (43.0)  90 (45.0)  83 (41.5)  1.35 (0.91–2.01)/0.3495  All  286  200  200  200  200    The AA and GG haplotypes predominate, whereas GA is very rare. The AG haplotype conferred risk to APS compared with the AA haplotype (P = 0.0013) and was significantly more common in APS than in Cs (P = 0.00122). Abbreviations: C, control; n.a., not applicable. View Large Table 4. Haplotype Allele Frequency of Both CTLA-4 SNPs CT60 and AG49 Haplotype CT60/AG49  APS 
N (%)  T1D 
N (%)  HT 
N (%)  GD 
N (%)  C 
N (%)  APS/C Comparator Haplotype vs AA Haplotype OR (95% CI)/P Value  AA  98 (34.3)  82 (41.0)  74 (37.0)  74 (37.0)  90 (45.0)  n.a.  AG  64 (22.4)  47 (23.5)  40 (20.0)  35 (17.5)  22 (11.0)  2.67 (1.52–4.69)/0.0013  GA  2 (0.7)  2 (1.0)    1 (0.5)  5 (2.5)  0.37 (0.07–1.94)/0.0902  GG  122 (42.7)  69 (34.5)  86 (43.0)  90 (45.0)  83 (41.5)  1.35 (0.91–2.01)/0.3495  All  286  200  200  200  200    Haplotype CT60/AG49  APS 
N (%)  T1D 
N (%)  HT 
N (%)  GD 
N (%)  C 
N (%)  APS/C Comparator Haplotype vs AA Haplotype OR (95% CI)/P Value  AA  98 (34.3)  82 (41.0)  74 (37.0)  74 (37.0)  90 (45.0)  n.a.  AG  64 (22.4)  47 (23.5)  40 (20.0)  35 (17.5)  22 (11.0)  2.67 (1.52–4.69)/0.0013  GA  2 (0.7)  2 (1.0)    1 (0.5)  5 (2.5)  0.37 (0.07–1.94)/0.0902  GG  122 (42.7)  69 (34.5)  86 (43.0)  90 (45.0)  83 (41.5)  1.35 (0.91–2.01)/0.3495  All  286  200  200  200  200    The AA and GG haplotypes predominate, whereas GA is very rare. The AG haplotype conferred risk to APS compared with the AA haplotype (P = 0.0013) and was significantly more common in APS than in Cs (P = 0.00122). Abbreviations: C, control; n.a., not applicable. View Large VDR The SNPs Bsm I, Apa I, and Taq I were not significantly different in APS vs controls and MGA. In contrast, the haplotypes TAT, TCT, CCC, and CAC were different between the various collectives, with an overall value of P = 0.007. The distribution of the haplotypes is shown in Table 5; the CAC haplotype was more common in APS than in controls (P = 0.045). Table 5. Haplotype Allele Frequency of the VDR SNPs BSM I, APA I, and TAQ I Haplotype Bsm I, Apa I, Taq I  APS
N (%)  T1D
N (%)  HT
N (%)  GD
N (%)  C
N (%)  P Value  CCT  135 (47.2)  91 (45.9)  98 (49.0)  97 (48.5)  93 (46.5)  0.866  TAC  111 (38.8)  79 (39.5)  73 (36.5)  79 (39.5)  75 (37.5)  CAT  32 (11.2)  23 (11.5)  23 (11.5)  19 (9.5)  31 (15.5)  TAT  1 (0.4)  2 (1.0)  4 (2.0)  5 (2.5)  1 (0.5)  0.0011  TCT  —  2 (1.0)  —  —  —  CCC  —  2 (1.0)  —  —  —  CAC  7 (2.5)  1 (0.5)  2 (1.0)  —  —  All  286  200  200  200  200    Haplotype Bsm I, Apa I, Taq I  APS
N (%)  T1D
N (%)  HT
N (%)  GD
N (%)  C
N (%)  P Value  CCT  135 (47.2)  91 (45.9)  98 (49.0)  97 (48.5)  93 (46.5)  0.866  TAC  111 (38.8)  79 (39.5)  73 (36.5)  79 (39.5)  75 (37.5)  CAT  32 (11.2)  23 (11.5)  23 (11.5)  19 (9.5)  31 (15.5)  TAT  1 (0.4)  2 (1.0)  4 (2.0)  5 (2.5)  1 (0.5)  0.0011  TCT  —  2 (1.0)  —  —  —  CCC  —  2 (1.0)  —  —  —  CAC  7 (2.5)  1 (0.5)  2 (1.0)  —  —  All  286  200  200  200  200    CCT, TAC, CAT are the most common haplotypes and showed no significant differences in the distribution between the collectives (χ2 test, excluding rare haplotype, 8 degrees of freedom; P = 0.866). The other haplotypes were rare in this study and showed significant differences in the collective distribution (exact χ2 test for 5 × 5 table, grouping frequent haplotypes into one category; P = 0.0011). View Large Table 5. Haplotype Allele Frequency of the VDR SNPs BSM I, APA I, and TAQ I Haplotype Bsm I, Apa I, Taq I  APS
N (%)  T1D
N (%)  HT
N (%)  GD
N (%)  C
N (%)  P Value  CCT  135 (47.2)  91 (45.9)  98 (49.0)  97 (48.5)  93 (46.5)  0.866  TAC  111 (38.8)  79 (39.5)  73 (36.5)  79 (39.5)  75 (37.5)  CAT  32 (11.2)  23 (11.5)  23 (11.5)  19 (9.5)  31 (15.5)  TAT  1 (0.4)  2 (1.0)  4 (2.0)  5 (2.5)  1 (0.5)  0.0011  TCT  —  2 (1.0)  —  —  —  CCC  —  2 (1.0)  —  —  —  CAC  7 (2.5)  1 (0.5)  2 (1.0)  —  —  All  286  200  200  200  200    Haplotype Bsm I, Apa I, Taq I  APS
N (%)  T1D
N (%)  HT
N (%)  GD
N (%)  C
N (%)  P Value  CCT  135 (47.2)  91 (45.9)  98 (49.0)  97 (48.5)  93 (46.5)  0.866  TAC  111 (38.8)  79 (39.5)  73 (36.5)  79 (39.5)  75 (37.5)  CAT  32 (11.2)  23 (11.5)  23 (11.5)  19 (9.5)  31 (15.5)  TAT  1 (0.4)  2 (1.0)  4 (2.0)  5 (2.5)  1 (0.5)  0.0011  TCT  —  2 (1.0)  —  —  —  CCC  —  2 (1.0)  —  —  —  CAC  7 (2.5)  1 (0.5)  2 (1.0)  —  —  All  286  200  200  200  200    CCT, TAC, CAT are the most common haplotypes and showed no significant differences in the distribution between the collectives (χ2 test, excluding rare haplotype, 8 degrees of freedom; P = 0.866). The other haplotypes were rare in this study and showed significant differences in the collective distribution (exact χ2 test for 5 × 5 table, grouping frequent haplotypes into one category; P = 0.0011). View Large IL2RA and TNF-α No associations for the SNP IL2RA and TNF-α‒863 were found among APS, MGA, and controls regarding allele frequency and genotype distribution. Discussion This study evaluated numerous SNPs in a large group of Caucasian patients with APS. We also compared SNP findings in large groups of patients with APS and three different, well-characterized collectives of MGA diseases (i.e., T1D, HT, and GD). Our patients and controls were carefully selected; patients with MGA had a long disease history and both a negative family history as well as a negative antibody profile for other endocrine/nonendocrine autoimmune disorders. Furthermore, this study involved haplotype and genotype analyses in APS. The presented results emphasize the role of the PTPN22 and CTLA-4CT60 SNPs in increasing the susceptibility risk for APS and potentially differentiating (especially PTPN22) between polyglandular and monoglandular autoimmune diseases. However, this article also underlines that although allele and/or carrier frequency may be similar within the tested collectives, a haplotype and/or genotype analysis may offer different results (15). We identified PTPN22 +1858 as a strong susceptibility polymorphism, increasing the risk for T-allele carriers approximately fourfold for APS and thereby confirming the results of a preliminary study from our own laboratory (10). Compared with the previous report, the current study differentiated between the individual AITDs (GD and HT), showing significant differences in APS vs GD and T1D, thus indicating that the SNP is more relevant in the overall risk for APS than for MGA. In addition, a genotype analysis was performed in markedly larger APS and MGA cohorts. Pertaining to the individual patient collectives, the SNP +1858 appears to also play a role in the etiology of HT, as statistical significance was lost when APS and HT were compared. However, because a higher percentage of our APS patients had HT (63%) than GD (37%), the separate comparisons of APS-HT and APS-GD vs controls were highly significant. Comparable conclusions were drawn from two other studies focusing on T1D and indicating the T-allele as a risk factor for MGA and additional autoimmune diseases (11, 31). Finally, in the first performed genome-wide association study in patients with APS, the PTPN gene on chromosome one was recognized as a susceptibility gene with a significantly increased log score (32). The current study also demonstrated a clear association of the SNP CT60 on the CTLA-4 gene with APS, resulting in a twofold-increased risk for GG genotype carriers. Only a homozygous wild-type genotype seemed to have a sufficiently negative influence on the protein function of CTLA-4, promoting the development of an autoimmune disease and suggesting a recessive mode of inheritance, whereas the alternative type was similarly protective in the homozygous and heterozygous genotypes. Dissecting the joint genetic susceptibility in large cohorts of patients with mono- and polyglandular autoimmunity, the current study confirmed preliminary data from our laboratory (29) and others (33) that the G-allele was preferably given to children with AITD and/or T1D in multiplex families. In comparison, CTLA-4 was not associated with endocrine autoimmunity in a small study from Japan (15). Although associations of the SNP AG49 with autoimmune diseases are described in the literature, we did not observe an association between AG49 and APS. Thus, results from MGA studies cannot be transferred to polyglandular diseases. Conflicting results with Asian studies may be due to genetic and geographical differences (16, 17) as well as to linkage disequilibrium and a smaller number of examined Asian subjects. Of note, haplotype analysis of the two CTLA-4 SNPs was informative and showed enhanced susceptibility to APS for the AG haplotype, whereas the AA haplotype was protective. These results are in line with those highlighting the GG and AG haplotypes as susceptibility haplotypes for the two MGA diseases HT and GD in contrast to the AA haplotype (14). The prevalence of the SNPs vitamin D, IL2RA, and TNF-α did not differ in the various collectives. In comparison, associations between Apa I and Taq I with AITD (not APS) have been reported (34, 35), and the CAC and TAT haplotypes were protective for T1D (36) and GD (37), respectively, again emphasizing the genetic difference between APS and MGA. Finally, and in contrast to our findings, a Tunisian study looking at a small group of patients with APS reported that the AA genotype of IL2RA could be considered a potential susceptibility gene (38). The ethnic background and the small number of subjects may explain the discrepancy. One may speculate on the potential translational utility of the study’s findings, how they fit into our current understanding of endocrine autoimmunity, and/or how we think these data will eventually translate to clinical practice. A comparison with the well-known association of the HLA class II “super” antigens DR3 and DR4 as universally acknowledged strong susceptibility genes for T1D (especially) and AITD in general (39, 40) could lead to an “immunogenetic screening package” encompassing the HLA class II DR antigens with the PTPN22 and CTLA-4 polymorphisms, thus helping to predict which patients with a single autoimmune endocrine disorder are likely to progress to APS. This proposed immunogenic profile could be offered to patients with MGA disease and, on the basis of proven prevalent positive family history and familiar clustering (41), also to first-degree relatives of subjects with APS. In conclusion, this study of eight SNPs in a large number of patients with APS, patients with three MGA diseases, and healthy controls demonstrated that the PTPN and CTLA-4 polymorphisms were susceptibility genes for APS and emphasized their role in potential differentiation between polyglandular and MGA. Abbreviations: Abbreviations: AITD autoimmune thyroid disease APS autoimmune polyglandular syndrome CI confidence interval CTLA-4 cytotoxic T-lymphocyte-associated antigen 4 GD Graves disease HLA human leukocyte antigen HT Hashimoto thyroiditis IL interleukin IL2RA interleukin-2 receptor α MGA monoglandular autoimmunity OR odds ratio PCR polymerase chain reaction PTPN22 protein tyrosine phosphatase non-receptor type 22 SBE single-base extension SNP single nucleotide polymorphism T1D type 1 diabetes TNF-α tumor necrosis factor α VDR vitamin D receptor Acknowledgments We thank T. Diana, JGU Thyroid Research Laboratory, M. Kanitz, and P. 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Journal of Clinical Endocrinology and MetabolismOxford University Press

Published: Feb 1, 2018

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