, Volume 49, Issue 6, pp 1198–1208

Lymphoid tyrosine phosphatase (LYP/PTPN22) Arg620Trp variant regulates insulin autoimmunity and progression to type 1 diabetes

  • R. Hermann
  • K. Lipponen
  • M. Kiviniemi
  • T. Kakko
  • R. Veijola
  • O. Simell
  • M. Knip
  • J. Ilonen



We analysed the contribution of the lymphoid protein tyrosine phosphatase (LYP) Arg620Trp variant (which corresponds to the PTPN22 C1858T polymorphism) to the emergence of beta-cell-specific humoral autoimmunity and progression to type 1 diabetes in man. We also explored the heterogeneity in the disease-predisposing effect of this polymorphism in relation to known disease loci, sex and age at disease onset.

Subjects and methods

A population-derived Finnish birth cohort with increased disease susceptibility conferred by HLA-DQB1 was monitored for the appearance of islet cell autoantibodies, and individuals found to be positive were tested for autoantibodies against insulin (IAA), glutamic acid decarboxylase and islet antigen-2 (n=574; mean follow-up time 4.9 years). Gene interaction effects on disease susceptibility were analysed in case–control and family series (546 patients, 538 controls, 245 nuclear families). All subjects were typed for HLA DR-DQ, insulin gene (INS), CTLA4 and PTPN22 C1858T polymorphisms.


The PTPN22 1858TT genotype was associated with the appearance of IAA (adjusted hazard ratio=4.6, 95% CI 2.4–9.0; p=0.000013). PTPN22, INS and HLA-DRB1 had an additive effect on the emergence of IAA. The 1858TT and CT genotypes conferred an increased risk of developing additional autoantibodies or clinical disease (hazard ratio=4.1, 95% CI 1.5–11.6; and 1.6, 95% CI 1.1–2.4, respectively; p=0.003). The strong effect of PTPN22 on disease susceptibility (p=2.1×10−8) was more pronounced in males (p=0.021) and in subjects with non-DR4-DQ8/low-risk HLA genotypes (p=0.0004).


In the pathogenesis of type 1 diabetes the underlying mechanism of the PTPN22 C1858T polymorphism appears to involve regulation of insulin-specific autoimmunity. Importantly, it strongly affects progression from prediabetes to clinical disease.


Autoantibodies Autoimmune disease Autoimmunity CTLA4 DQB1 DRB1 HLA Insulin Insulin gene PTPN22 Type 1 diabetes 



Type I Diabetes Prediction and Prevention Project


Glutamic acid decarboxylase autoantibodies


Hazard ratio


Insulin autoantibodies


Islet antigen 2 antibodies


Islet cell antibodies


Juvenile Diabetes Foundation unit


Genetic susceptibility to type 1 diabetes is defined by at least four gene loci. The HLA region is the major disease locus and the primary determinant is HLA-DQB1, a class II gene, the effect of which is profoundly modified by the adjacent HLA-DQA1 and HLA-DRB1 genes and several other loci in the class I and class III regions [1, 2, 3, 4, 5]. In addition to the HLA region, the insulin gene (INS; IDDM2 locus), the CTLA4 region (cytotoxic T-lymphocyte-associated protein 4; IDDM12 locus) and the gene PTPN22 (lymphoid tyrosine phosphatase; 1p13, OMIM 600716) are confirmed to be associated with disease susceptibility [6, 7, 8, 9, 10].

The recent finding of association between the lymphoid protein tyrosine phosphatase (LYP) Arg620Trp variant (which corresponds to the PTPN22 C1858T polymorphism) and type 1 diabetes has been reproduced in several white populations [10, 11, 12, 13, 14, 15, 16, 17]. In addition, this variant appears to be a common predisposing factor for other autoimmune diseases, such as rheumatoid arthritis, systemic lupus erythematosus, Graves disease, Hashimoto thyroiditis and autoimmune Addisons disease [11, 14, 18, 19, 20]. LYP is expressed in lymphocytes and acts by binding intracellular kinases such as C-terminal Src tyrosine kinase (Csk). LYP seems to be directly involved in setting thresholds for T cell receptor signalling [21, 22]. The Arg620Trp functional polymorphism may be the causative disease variant, as Bottini et al. [10] showed that this amino acid substitution disrupts interaction with the tyrosine kinase, which could lead to pathogenic T cell responses and may be the defect that underlies the development of autoimmunity.

In type 1 diabetes, the initiation of the beta-cell-specific immune process often occurs early in life, and several years later it results in clinical disease in most individuals. Early histological and functional studies indicate that the disease is caused by T lymphocytes infiltrating the pancreatic islets [23, 24]. The disease-specific immune events are, however, reflected in the appearance of beta-cell-specific autoantibodies, which are useful tools for the prediction of progression to clinical disease [25, 26, 27]. To understand the disease pathomechanism, it is crucial to explore the role of genetic factors in the emergence of beta cell autoimmunity. Previously, it has been shown that the DR4-DQ8 haplotype is associated with the appearance of insulin autoantibodies (IAA) and islet antigen-2 autoantibodies (IA-2A), whereas glutamic acid decarboxylase autoantibodies (GADA) develop more frequently in individuals carrying the DR3-DQ2 haplotype [28, 29, 30, 31]. Recently, in a large Finnish birth cohort we observed a differential contribution of the DRB1*04 alleles to the development of beta cell autoimmunity. Importantly, we also found that the INS locus plays a central role in the emergence of IAA and that the subsequent appearance of multiple autoantibodies is linked to IAA [32]. Our findings suggested that, in children who develop IAA, insulin autoimmunity may represent the primary event that is controlled, at least in part, by the INS locus.

In this study we examined the role of PTPN22 in the development of type 1 diabetes-associated autoimmunity and its contribution to the genetic control of progression to clinical disease. For this purpose we employed a large population-based cohort of infants who are prospectively followed from birth in the framework of the Type I Diabetes Prediction and Prevention Project (DIPP). This study population carries risk HLA genotypes and is well characterised in terms of clinical data and for genetic and immunological disease markers [33].

In addition, we explored the heterogeneity of the disease-predisposing effect of PTPN22 in relation to HLA genes, INS and CTLA4 genotypes, sex and age.

Subjects and methods

Study design

Firstly, the effect of the LYP Arg620Trp (PTPN22 C1858T; rs2476601) polymorphism on humoral beta cell autoimmunity and disease progression was evaluated in a population-based prospective follow-up cohort of young children with increased type 1 diabetes susceptibility—the DIPP cohort. In the framework of the DIPP, screening for risk-associated HLA genotypes is performed in all infants born at three university hospitals in Finland: Turku, Tampere and Oulu [33]. Infants (about 7500 by May 2004) with risk HLA-DQB1 genotypes (DR3-DQ2/DR4-DQ8, DR4-DQ8/X, DR3-DQ2/Y, where XDR3-DQ2, DQB1*0301, DQB1*0602 and YDR7-DQ2, DQB1*0301, *0302, *0602 or *0603), were followed and sampled at intervals of 3–12 months, as described [33]. Islet cell antibodies (ICA) were analysed from all serum samples; if positive, IAA, GADA and IA-2A were tested in all samples available from that ICA-positive subject (Fig. 1).
Fig. 1

Population screening and follow-up scheme in the Type I Diabetes Prediction and Prevention (DIPP) project (status in May, 2004). For the definition of the at-risk individuals, see Methods section in Subjects and methods

Secondly, we explored the heterogeneity of the disease-predisposing effect of PTPN22 in relation to HLA, the insulin gene, CTLA4 genotypes, sex and age at disease onset. To avoid population stratification effects we used both case–control and family-based designs.

The gene–gene interactions between PTPN22, HLA class II, INS and CTLA4 were explored first in stratified data sets and then tested for significance using regression analyses.

The WHO criteria were used for the diagnosis of type 1 diabetes [34].

The local ethics committees approved the study and informed consent was obtained from the parents of the participating subjects. The study was conducted according to the principles of the Declaration of Helsinki.

Study populations

Antibody-positive children (DIPP cohort)

All children who had developed ICA by May 2004 (n=574, 180 with the DR3-DQ2/DR4-DQ8 high-risk, 368 with the DR4-DQ8/X and 26 with the DR3-DQ2/Y moderate-risk genotypes; 53.5% boys) were tested for autoantibodies (IAA, GADA and IA-2A) and for genetic markers (PTPN22 C1858T, HLA-DRB1-DQA1-DQB1, INS −23 HphI and CTLA4 CT60 polymorphisms). Two hundred and sixty-two infants developed biochemical autoantibodies, in addition to ICA, among whom 190 had multiple (≥2) autoantibodies. At the time of this analysis the mean (±SD) follow-up time in the DR3-DQ2/DR4-DQ8 and DR4-DQ8/X groups was 4.9±2.2 years (range 0.5–9.3 years), and somewhat shorter in those carrying the DR3-DQ2/Y combination (mean 3.9±1.4 years, range 0.5–6.1 years). By May 2004, 74 of these children (12.9%) had progressed to clinical type 1 diabetes.

Case–control series

Samples from cases were collected from the Departments of Pediatrics at the Universities of Turku and Oulu (n=546, 55.7% boys; mean age at diagnosis 8.2±4.1 years). The control group comprised consecutive healthy infants born in the University Hospitals of Turku and Oulu (n=538, 51.2% boys).

Nuclear family series

Families with one affected child were recruited mainly from the Departments of Pediatrics at the Universities of Turku and Oulu (n=245, 52.9% boys; mean age at diagnosis 8.6±4.4 years).



The PTPN22 C1858T (LYP Arg620Trp; rs2476601) polymorphism was genotyped with a homogeneous genotyping method [35]. The oligonucleotide sequences and reaction conditions are available upon request. Genotyping accuracy was evaluated by DNA sequencing 140 samples (MegaBace1000; GE Healthcare, Chalfont St Giles, UK). The genotypes obtained with the two methods were 100% identical. The methods for the HLA-DQB1 ‘full house’ and for DQA1 and DRB1*04 typing have been described [36, 37, 38]. For the gene–gene interaction analysis in the case–control material, HLA genotypes were grouped among cases according to the presence or absence of the two major HLA risk haplotypes, as follows: HLA DR3-DQ2/DR4-DQ8, DR4-DQ8/non-DR3-DQ2, DR3-DQ2/non-DR4-DQ8, non-DR4-DQ8/non-DR3-DQ2. In the ICA-positive DIPP cohort, the heterogeneity of PTPN22 effects was tested between HLA genotype groups defined according to the screening classification criteria: DR3-DQ2/DR4-DQ8, DR4-DQ8/X and DR3-DQ2/Y. The INS −23 HphI polymorphism was typed as described previously [32, 36, 39]. The CTLA4 CT60 polymorphism was genotyped using minisequencing (SnuPe Kit, MegaBace1000; GE Healthcare).

Autoantibody assays

The antibody assay parameters used have been described in detail [40]. The detection limit for ICA was 2.5 Juvenile Diabetes Foundation units (JDFU; sensitivity 100%, specificity 98%). IAA levels were quantified with a microassay [41, 42]. GADA and IA-2A were measured using specific radioligand assays [43, 44]. The cut-off values for IAA, GADA and IA-2A positivity were 1.56, 5.36 and 0.43 RU (relative units), respectively, being the 99th percentiles in a series comprising more than 370 non-diabetic Finnish children and adolescents. The disease sensitivities of the IAA, GADA and IA-2A assays were 44, 82 and 62%, respectively, and the specificities were 98, 98 and 100%, respectively, based on the 2002 Diabetes Autoantibody Standardization Program Workshop.

Statistical analysis

Kaplan–Meier survival analysis was applied to evaluate genetic effects on the appearance of various autoantibodies. Differences between the survival curves were tested with the log rank test. Cox regression was employed to analyse the effects of various factors (antibody status, genotypes) on autoantibody-free survival. Disease associations of gene variants were evaluated by forward stepwise logistic regression analysis and, in some comparisons, using the χ2 statistic with Yates’ correction. All statistical analyses were performed using SPSS for Windows (version 11.0.1; SPSS, Chicago, IL, USA). The transmission disequilibrium test was performed using Unphased software [45]. Values of p lower than 0.05 were considered statistically significant.


The effect of the PTPN22 C1858T variant on the emergence of beta-cell-specific autoimmunity and progression to clinical type 1 diabetes in the DIPP cohort

Figure 2 shows the Kaplan–Meier survival analysis of progression to type 1 diabetes in the ICA-positive DIPP follow-up cohort. Clinical disease appeared at a higher rate in children with the TT and TC genotypes than in those carrying the CC variant (hazard ratio [HR]=5.5, 95% CI 2.3–13.2 and HR=1.6, 95% CI 1.0–2.7, respectively; p=0.0001). Using logistic regression analysis, we observed that the PTPN22 C1858T variant showed association with progression of autoimmunity reflected by the number of autoantibodies appearing during follow-up. Children carrying the TT and CT genotypes had an increased risk of developing additional autoantibodies (HRs for developing an additional antibody were 4.1 [95% CI 1.5–11.6] and 1.64 [95% CI 1.1–2.4], respectively; p=0.003).
Fig. 2

The effect of PTPN22 on progression to clinical type 1 diabetes in children with risk HLA genotypes. Cumulative disease frequencies are shown for different PTPN22 C1858T genotypes. Median disease-free survival was shorter in individuals carrying the TT genotype (5.6 years; 95% CI 3.9–7.3 years; n=16) than in those with the TC or CC variant (8.0 years, 95% CI 7.6–8.6; n=151 and 8.4 years, 95% CI 8.2–8.7; n=384, respectively, p=0.0001). All children carried the HLA DR3-DQ2/DR4-DQ8 or DR4-DQ8/X combination, in which XDR3-DQ2, DQB1*0301 or DQB1*0602. Solid line subjects with the TT genotype; dotted line subjects carrying the CT combination; dashed line subjects with the CC variant


The effect of the PTPN22 variant on the emergence of ICA was estimated by comparing the genotype frequencies of the children with ICA only (TT 1.3%, CT 24.1%, CC 74.6%) with those seen in healthy controls (see data in Table 3). No difference was observed.


Genetic effects on the appearance of these autoantibodies were estimated by survival analysis. The cumulative frequencies of IAA were higher and antibody-free survival was shorter among children with the TT genotype (76.0%, 3.0 years, 95% CI 1.3–4.6 years) compared with those with the genotypes CT (46.5%, 5.9 years, 95% CI 5.3–6.6 years) and CC (42.0%, 6.5 years, 95% CI 6.2–6.9; p=0.00007). The hazard ratio for the emergence of IAA in subjects with the TT combination was 3.7 (95% CI 2.0–6.9) and was 1.3 (95% CI 1.0–1.8) in those with the CT genotype. The effect of the T allele on the emergence of IAA was strongly significant also when the study group was stratified according to the presence of IA-2A and GADA (adjusted p=0.0001; Table 1). Accordingly, in Cox regression the effect of the PTPN22 TT variant was significant after adjusting for GADA and IA-2A carrier status (adjusted HR for the appearance of IAA in the C1858T TT group was 3.2, 95% CI 1.7–5.9; reference genotype, CC, p=0.001).
Table 1

Survival analysis of the effect of the PTPN22 C1858T polymorphism on the appearance of autoantibodies in the ICA-positive DIPP cohort

Autoantibody analysed

Study subjects

PTPN22 C1858T genotype (n)

Cumulative frequencies of autoantibodies (%)

Antibody-free survival (years): meana (95% CI)

PTPN22 effect: adjusted p valueb



TT (9)


1.2 (1.0–1.4)


TC (72)


3.2 (2.6–4.0)

CC (131)


3.5 (2.9–3.8)


TT (6)


5.8 (2.9–8.7)

TC (80)


8.2 (7.7–8.8)

CC (254)


8.3 (8.0–9.0)



TT (11)


2.0 (1.4–2.7)


TC (64)


3.0 (2.4–3.6)

CC (132)


4.1 (3.5–4.7)


TT (4)


TC (87)


7.9 (7.4–8.5)

CC (253)


8.6 (8.3–8.8)


IAA positives

TT (11)


2.2 (1.6–2.7)


TC (64)


3.4 (2.7–4.1)

CC (132)


4.3 (3.7–4.8)

IAA negatives

TT (4)


TC (87)


8.5 (8.2–8.9)

CC (253)


8.8 (8.5–9.0)

The number of children in each genotype category is shown in parentheses

aMedian values for antibody-free survival could not be calculated in some cases because the cumulative antibody frequencies were lower than 50%; therefore, the mean values are reported

bLog rank test; df=2 for all p values

When the effect of the PTPN22 on the appearance of GADA was analysed, the TT variant appeared to be associated with a higher cumulative frequency of GADA; however, when adjusted for IAA status, the effect was not significant (Table 1; p=0.073). Similarly, the emergence of IA-2A was not significantly influenced by the PTPN22 genotype after adjusting for IAA status (adjusted p=0.17).

The effect of the PTPN22 was also analysed in relation to which autoantibody reactivity appeared first during the follow-up (Fig. 3). The 1858TT genotype was associated with higher cumulative IAA frequency and shorter IAA-free survival than the CC variant (median IAA-free survival with TT genotype was 3.2 years, 95% CI 1.5–5.0 versus 7.0 years, 95% CI 6.7–7.4 years in the group with CC combination; log rank 21.4, p=0.00008, df=2; Fig. 3a). However, no effect of PTPN22 was seen on the emergence of GADA (p=0.27; Fig. 3b) or IA-2A (p=0.57; Fig. 3c).
Fig. 3

The effect of PTPN22 on the appearance of IAA, GADA and IA-2A as first autoantibody during follow-up. a Appearance of IAA as the first autoantibody during follow-up in children carrying different PTPN22 C1858T genotypes. Cumulative frequency of IAA was higher in the TT and CT groups than in children with the CC genotype (73.6 and 38.7 vs 33.5%; log rank 21.4, df=2, p=0.00008; n=168). b Emergence of GADA as the first autoantibody in subjects carrying different PTPN22 C1858T genotypes (p=0.27; n=96). c Development of IA-2A as the first autoantibody in different PTPN22 C1858T genotype groups (p=0.57; n=42). Solid lines subjects with the TT genotype; dotted lines subjects carrying the CT combination; dashed lines subjects with the CC variant

We also evaluated how PTPN22 influenced the transient appearance of autoantibodies (ICA n=84, 14.6%; IAA n=77, 13.4%; GADA n=37, 6.4%; IA-2A n=7, 1.2%). No significant effects were found, although, an increase in the cumulative frequency of transient IAA was suspected in subjects with the 1858TT genotype (p=0.11).

Heterogeneity in the effect of PTPN22 on the emergence of IAA according to HLA class II, INS, CTLA4, age and sex

The appearance of IAA in the three PTPN22 genotype groups stratified according to HLA class II, INS and CTLA4 genotypes is shown in Table 2. IAA appeared at a higher rate in children carrying the TT genotype both in the DR3-DQ2/DR4-DQ8 and in the DR4-DQ8/X risk category (adjusted p=0.0003). In addition, Cox regression revealed a higher risk of developing IAA in the DR3-DQ2/DR4-DQ8 category in all PTPN22 genotype groups compared with the DR4-DQ8/X group (HR=1.5, 95% CI 1.1–2.1; p=0.015). The emergence of IAA could not be estimated reliably among boys with the DR3-DQ2/Y genotype because of the small numbers.
Table 2

Survival analysis of the effect of the PTPN22 C1858T polymorphism on the appearance of insulin autoantibodies in ICA-positive children carrying various HLA-DQB1, INS and CTLA4 genotypes


PTPN22 C1858T genotype (n)

Cumulative IAA frequency (%)

IAA-free survival in years: meana (95% CI)

PTPN22 effect: adjusted p valueb


TT (5)


1.3 (0.8–1.7)


TC (49)


5.3 (4.2–6.4)

CC (120)


5.9 (5.3–6.6)


TT (10)


3.9 (1.6–6.2)

TC (95)


6.0 (5.2–6.7)

CC (250)


6.8 (6.3–7.3)


TT (9)


1.3 (0.9–1.52)


CT (96)


4.7 (4.0–5.5)

CC (241)


6.1 (5.6–6.6)


TT (0)

CT (9)


CC (13)


7.9 (6.8–9.0)


TT (4)



CT (36)


7.3 (6.2–8.3)


CC (106)


6.9 (6.2–7.5)


INS (−23) HphI AAf

TT (9)


2.9 (0.9–4.8)


TC (92)


5.4 (4.6–6.2)


CC (258)


6.1 (5.7–6.6)


INS (−23) HphI AT and TT

TT (4)


1.2 (1.0–1.4)


TC (49)


6.8 (5.8–7.9)


CC (108)


7.6 (7.1–8.2)



TT (6)


4.8 (1.8–7.7)


TC (28)


5.4 (4.0–6.7)


CC (83)


6.7 (5.9–7.4)



TT (4)


2.8 (0.4–5.3)


TC (81)


5.7 (4.9–6.6)


CC (182)


6.2 (5.7–6.8)



TT (5)


1.2 (0.9–1.4)


TC (43)


5.7 (4.7–6.6)


CC (121)


6.6 (6.0–7.3)


The number of children in each genotype category is shown in parentheses

aMedian values for the antibody-free survival could not be calculated in some cases because the cumulative antibody frequencies were lower than 50%; therefore, the mean values are reported

bLog rank test; df=2 for all p values

cp=0.015 vs DR4-DQ8/X (df=1)

dXDR3-DQ2, DQB1*0301, DQB1*0602

ep=0.00004 vs DRB1*0403 and DRB1*0404 (df=2)

All DRB1*04 subtypes carry DQ8

fp=0.00007 vs INS (−23) HphI AT and TT (df=1)

gp=0.53 vs CTLA4 CT60 AG and GG (df=2)

We analysed the effect of PTPN22 on the development of IAA in data sets stratified according to the DRB1 subtype on the DR4-DQ8 haplotypes. We observed that the effect of PTPN22 was present both in the DRB1*0401 and *0404 groups (adjusted p=0.0002), with a higher cumulative IAA frequency in all PTPN22 categories in the DRB1*0401 group (p=0.00004). Only one child developed IAA in the DRB1*0403 group.

The strong effect of PTPN22 on the emergence of IAA was present both in the INS (−23) HphI AA and AT/TT INS genotype groups. In addition, IAA appeared at a higher rate in the INS (−23) HphI AA group (HR=2.1, 95% CI 1.5–3.0; p=0.00007).

The PTPN22 C1858T polymorphism affected the appearance of IAA in all three CTLA4 CT60 genotype groups in a similar way (p=0.0005), and we did not observe any interaction between PTPN22 and CTLA4 in this respect (p=0.53).

Interestingly, sex influenced the appearance of IAA, as boys carrying the PTPN22 1858TT genotype had a higher risk of developing IAA than girls (HR=1.4, 95% CI 1.1–1.8; p=0.033).

Additionally, we observed that at the time of IAA seroconversion children with the TT genotype were younger (2.4±0.7 years) than those with CT or CC genotype (3.8±0.2 and 4.1±0.1 years, respectively; p=0.016). No age-dependent heterogeneity in the PTPN22 genotype distribution was detected in the DIPP cohort (p=0.37).

Using Cox regression analysis, we estimated the effect of the PTPN22 variant on the emergence of IAA adjusted for the effects of HLA, INS, CTLA4 and sex. Individuals with the TT and CT genotypes had a strongly increased probability of developing IAA (adjusted HR=4.6, 95% CI 2.4–9.0; and HR=1.5, 95% CI 1.5–3.0, respectively; p=0.000013).

Heterogeneity of the effect of PTPN22 on type 1 diabetes susceptibility

In the case–control series, the disease association of PTPN22 and its interaction with HLA DR-DQ, CTLA4, INS, sex and age at disease onset were analysed using forward stepwise logistic regression analysis (Table 3). As expected, the PTPN22 C1858T polymorphism showed a strong disease association (p=2.1×10−8). The odds ratios (OR) for the TT and CT genotypes were 3.1 (95% CI 1.4–5.2) and 2.9 (95% CI 2.0–4.2), respectively. The frequency of the T allele was 23.9% in cases and 13.9% in controls (p=8×10−6). In the cases, the exploratory analysis of the distribution of PTPN22 C1858T genotypes stratified according to HLA-DQB1, CTLA4 CT60 and INS (−23 HphI) genotypes, age at disease presentation and sex indicated heterogeneity for HLA, INS and sex. The significance of these interactions was estimated using a case-only regression model (Table 3). A significant effect of sex on PTPN22-encoded disease susceptibility was observed, as affected boys with the TT genotype had higher disease risk than girls (OR 1.5, 95% CI 1.1–2.2; p=0.021). We found no significant effect of the age at diagnosis, although the TT genotype appeared to be more prevalent among patients at a young age. However, we detected heterogeneity in the disease-predisposing effect of PTPN22 among different HLA class II genotypes, as the 1858TT and CT genotypes were found at higher frequencies in patients carrying the HLA DR3-DQ2/non-DR4-DQ8 and non-DR3-DQ2/non-DR4-DQ8 combinations compared with those with the DR3-DQ2/DR4-DQ8 or DR4-DQ8/non-DR3-DQ2 variants (p=0.0004). The data also suggested that the effect of PTPN22 is stronger in children who carry INS (−23) HphI AT or TT compared with the AA group (p=0.04). No significant heterogeneity in the effect of PTPN22 was observed in relation to CTLA4.
Table 3

Analysis of heterogeneity in the type 1 diabetes predisposing effect of PTPN22 in the Finnish population


PTPN22 C1858T genotype n (%)

p value




All cases

30 (5.5)

200 (36.6)

316 (57.9)



17 (5.9)

118 (40.8)

154 (53.3)



13 (5.1)

82 (31.9)

162 (63.0)

Age at diagnosis


 0–4.99 years

9 (7.6)

48 (40.3)

62 (52.1)


 5–9.99 years

11 (6.3)

64 (36.8)

99 (56.9)

 10–14.99 years

9 (4.0)

82 (36.8)

132 (59.2)


3 (3.1)

33 (33.7)

62 (63.3)


HLA DR4-DQ8/non-DR3-DQ2

16 (5.4)

97 (33.0)

181 (61.6)

HLA DR3-DQ2/non-DR4-DQ8

7 (7.3)

45 (46.9)

44 (45.8)

HLA non-DR3-DQ2/non-DR4-DQ8

4 (6.9)

25 (43.1)

29 (50.0)

INS (−23) HphI AA

21 (5.3)

142 (36.1)

230 (58.5)


INS (−23) HphI AT and TT

8 (7.4)

45 (41.7)

55 (50.9)


6 (13.3)

16 (35.6)

23 (51.1)



7 (3.5)

76 (38.4)

115 (58.1)


15 (5.6)

94 (35.1)

159 (59.3)


14 (2.6)

122 (22.7)

402 (74.7)


The global effect of PTPN22 was estimated using a logistic regression model comprising both cases and controls

Effects of sex, age at diagnosis, HLA, INS and CTLA4 were estimated with a case-only regression model

In the controls, no heterogeneity was observed in the distribution of PTPN22 genotypes, when stratified according to factors listed in Table 3.

In the nuclear family series, the T allele was preferentially transmitted to affected offspring (transmission disequilibrium test; 109 transmitted, 61.6%; p=0.001). The transmission rate to affected boys was higher (67.1%; p=0.0004) than that to girls (55.3%; p=0.317). This difference was valid both for paternal and maternal transmission (to boys, 70.2 and 65.3%; to girls, 50.83 and 55.6%, respectively). In the nuclear family series, the parental T allele frequency was 17.6%. There was no difference in parental T allele frequency between families with affected boys and girls.


This study revealed several important novel findings on the effect of the PTPN22 C1858T (LYP Arg620Trp) polymorphism on the development of humoral beta cell autoimmunity and disease progression.

Firstly, we observed that the PTPN22 C1858T variant was strongly associated with progression of beta-cell-specific autoimmunity, as ICA-positive children carrying the TT genotype had a four-fold higher risk of developing an additional molecular autoantibody than those with the CC genotype. This implies that the PTPN22 1858TT genotype defines a more homogeneous high-risk population within the given HLA risk group, which is more suitable for future prevention trials than those identified by the genetic screening criteria used so far.

Importantly, the emergence of IAA showed a strong association with the PTPN22 TT genotype, which underlines the significance of this variant in the regulation of beta-cell-specific autoimmunity. In contrast, the development of GADA and IA-2A was not significantly influenced by this polymorphism. It should be noted that the analysis of genetic effects on various autoantibodies was complicated by the fact that most (81.7%) of the IA-2A- and GADA-positive children also tested positive for IAA. However, the Cox regression that enabled us to adjust for the presence of other autoantibodies, and also the analysis of the autoantibody reactivity that appeared first during follow-up, indicated that the PTPN22 TT variant was primarily associated with the emergence of IAA (Fig. 3). Notably, individuals with the TT genotype had a considerably higher probability of developing IAA or other additional autoantibodies than those with the CT heterozygous genotype, which is consistent with a possible gene dose effect.

The effect of PTPN22 on the appearance of IAA was more pronounced in the high-risk HLA DR3-DQ2/DR4-DQ8 genotype group than in the medium-risk DR4-DQ8/X category, which could be explained by the higher number of disease-predisposing HLA heterodimer molecules, which promotes the autoimmune process in the former individuals. We also observed another HLA class II effect on PTPN22-encoded beta-cell-specific autoimmunity. The DRB1*04 allele present in the DR4-DQ8 HLA haplotype influenced the emergence of IAA in children with the TT and CT PTPN22 genotypes, as those carrying the DRB1*0401 variant had a higher probability of developing this autoantibody compared with subjects with the DRB1*0404 and *0403 alleles. This effect could be caused by differences in the peptide binding specificity of the encoded DR molecule. The differential effect of DRB1*04 alleles on the emergence of IAA is probably related to the different degrees of type 1 diabetes risk they confer [2, 46].

We have reported previously an association of IAA with the INS locus in the same cohort [32], and similar observations were made in two other studies on patients with newly diagnosed type 1 diabetes and on first-degree relatives [30, 47]. Therefore, we stratified the data set according to the INS genotype and observed that the effect of PTPN22 was present in both INS risk categories. In addition, the appearance of IAA was more frequent in children in the INS (−23) HphI AA risk group in all PTPN22 genotype categories, which implicates an additive effect of these two loci on the emergence of IAA. Our data also suggest not only that PTPN22 is associated with the emergence of IAA, but also that it seems to accelerate insulin-specific autoimmunity, as children with the 1858TT genotype developed IAA at an earlier age than others.

We found no evidence of heterogeneity in the effect of PTPN22 on the appearance of IAA in relation to the CTLA4 genotype. This is in accordance with previous observations from us and from other groups indicating a lack of association of CTLA4 with the emergence of diabetes-specific autoantibodies [30, 48].

Previously, we proposed the existence of two different pathways that lead to the emergence of beta cell autoimmunity [32]. In the INS-dependent pathway, insulin autoimmunity seems to play a central role in the initiation of the disease process, whereas in IAA-negative individuals the initiation of beta cell autoimmunity and the development of GADA and IA-2A are probably controlled by factors other than the INS locus. Data from the present study indicate that the PTPN22 C1858T polymorphism, which corresponds to the LYP Arg620Trp variant, may be primarily involved in the INS-dependent pathway by modulating insulin-specific humoral autoimmunity. Since PTPN22 is associated with other autoimmune diseases in addition to type 1 diabetes, such as Graves disease and rheumatoid arthritis [11, 14, 19], it is likely that the LYP protein is involved in antigen-driven, disease-specific immune phenomena. Accordingly, our data suggest that insulin could be a target antigen for the action of PTPN22 in type 1 diabetes.

We also observed in this study that the appearance of ICA alone was not associated with PTPN22. Most of the children who developed ICA had an antibody titre below 20 JDFU (median 5.0 JDFU; interquartile range 4.0–8.0 JDFU), which is much lower than the ICA titre in those who had additional autoantibodies (44 JDFU, 8.0–219.0 JDFU; p<10−6). This observation is in accordance with our recent findings implicating that the emergence of low-titre ICA alone is not related to the diabetes-specific autoimmune process [32].

The analysis of the heterogeneity of the effect of PTPN22 on type 1 diabetes susceptibility corroborated previous observations that the PTPN22 1858T allele is associated with type 1 diabetes [10, 11, 12, 14, 15, 16]. However, unlike in other studies, in both the case–control and the family series we observed that boys carrying the T allele were at higher risk of disease than girls. This sex-specific bias in the action of PTPN22 was underlined by the findings in the antibody-positive cohort, which indicated that males carrying the TT genotype had a higher risk of developing IAA than females. In addition, the effect of PTPN22 appeared to be stronger in individuals carrying non-DR4-DQ8 genotypes. Such findings have not been reported before and suggest a particular molecular mechanism that may play a more important role in males, and involves PTPN22 and HLA DR3-DQ2 or neutral HLA haplotypes. A similar sex-specific HLA effect was implicated by our data in Finns [37, 49] and also by Cucca et al. [50], indicating that males with the DR3-DQ2 haplotype have a higher disease risk than girls. The regression analysis also suggested heterogeneity in the effect of PTPN22 on type 1 diabetes susceptibility in children with different INS genotypes, while no interaction between PTPN22 and CTLA4 was detected. Since the regression analysis in the case–control series had limited statistical power to detect gene–gene interaction phenomena between loci with such weak (OR<2) disease association, these findings require replication in larger series.

In conclusion, the present study provides strong evidence that the PTPN22 C1858T polymorphism regulates diabetes-specific autoimmunity and is a marker of disease progression. In addition, it appears to be primarily associated with insulin-specific humoral autoimmunity, indicating an underlying mechanism for the LYP 620Trp variant protein. Importantly, this polymorphism seems to have an additive effect with the INS locus on the emergence of IAA. We also observed a complex interaction pattern of PTPN22 with certain HLA class II genotype combinations and with sex. It should be noted that in the present analysis all children in the autoantibody positive cohort were ICA-positive; therefore, the role of the PTPN22 C1858T variant on the emergence of humoral beta cell autoimmunity in ICA-negative subjects needs further investigation. Further functional studies are also required to refine our knowledge on the multifaceted molecular mechanisms by which PTPN22 contributes to the development of type 1 diabetes.



This study was supported by the Juvenile Diabetes Research Foundation (JDRF grants 4-1998-274 and 4-1999-731), the JDRF/European Foundation for the Study of Diabetes/Novo Nordisk Focused Research Grant for Type 1 Diabetes, Novo Nordisk Foundation, Turku, Oulu and Tampere University Hospitals and the Academy of Finland. We thank all the personnel of the DIPP, particularly E. Nirhamo, P. Nurmi, J. Mantere, M. Karlson, R. Suominen, T. Laakso, S. Anttila, S. Heikkilä, R. Päkkilä and P. Salmijärvi for their skilful technical assistance. We wish to thank T. Vahlberg for valuable help with the statistics. We are most grateful to all the children who participated in the DIPP and their families for their contribution.


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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • R. Hermann
    • 1
    • 2
    • 3
  • K. Lipponen
    • 1
    • 2
    • 3
  • M. Kiviniemi
    • 1
    • 2
    • 3
  • T. Kakko
    • 1
    • 2
    • 3
  • R. Veijola
    • 1
    • 4
  • O. Simell
    • 1
    • 5
  • M. Knip
    • 1
    • 6
    • 7
  • J. Ilonen
    • 1
    • 2
    • 3
  1. 1.JDRF Centre for Prevention of Type 1 Diabetes in FinlandTurkuFinland
  2. 2.Department of VirologyUniversity of TurkuTurkuFinland
  3. 3.Immunogenomics Laboratory, CellScreen Applied Biomedical Research CenterSemmelweis UniversityBudapestHungary
  4. 4.Department of PaediatricsUniversity of OuluOuluFinland
  5. 5.Department of PaediatricsUniversity of TurkuTurkuFinland
  6. 6.Department of PaediatricsTampere University HospitalTampereFinland
  7. 7.Hospital for Children and AdolescentsUniversity of HelsinkiHelsinkiFinland

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