Disease Markers

On this page

Abstract Introduction Materials and Methods Results Discussion Conclusion Data Availability Conflicts of Interest Acknowledgments Supplementary Materials References Copyright Related Articles

Research Article | Open Access

Volume 2019 | Article ID 2193835 | https://doi.org/10.1155/2019/2193835

PTPN22 Gene Polymorphisms Are Associated with Susceptibility to Large Artery Atherosclerotic Stroke and Microembolic Signals

Lingyan Zhou,¹Kun Wang,¹Junhong Wang,¹Zhenfeng Zhou,¹Yufei Cheng,¹Xudong Pan,¹and Aijun Ma¹

Academic Editor: Timo Sorsa

Received08 Mar 2019

Revised24 Mar 2019

Accepted01 Apr 2019

Published05 May 2019

Abstract

Large artery atherosclerotic stroke (LAAS) is the most common ischemic stroke (IS) subtype, and microemboli may be clinically important for indicating increased risk of IS. The inflammatory process of atherosclerosis is well known, and lymphoid phosphatase (Lyp), which is encoded by the protein tyrosine phosphatase nonreceptor type 22 (PTPN22) gene, plays an important role in the inflammatory response. Our study was intended to evaluate the relationship between PTPN22 gene and LAAS and microembolic signals (MES). Three loci of the PTPN22 gene (rs2476599, rs1217414, and rs2488457) were analyzed in 364 LAAS patients and 369 control subjects. A genotyping determination was performed using the TaqMan assay. The G allele of rs2488457 might be related to a higher risk for developing LAAS and MES (odds ratio , 95% confidence interval (CI) 1.156-1.833, ; , 95% CI 1.177-2.319, , respectively). In the LAAS group, the prevalence of the GTG haplotype was higher () and the prevalence of the GCC haplotype was lower (). An interaction analysis of rs2488457 with smoking showed that smokers with the CG/GG genotypes had a higher risk of LAAS, compared to nonsmokers with the rs2488457 CC genotype (, 95% CI 1.510–4.114, ). Our research indicated that the PTPN22 rs2488457 might be related to the occurrence of LAAS and MES in the Han Chinese population. In addition, the rs2488457 polymorphism and the environmental factor of smoking jointly influenced the susceptibility of LAAS.

1. Introduction

Stroke is considered the most general cause of adult-acquired deformity [1]. In all stroke events worldwide, ischemic stroke (IS) comprises 80−85% [1, 2]. It is logical that ischemic stroke is a complicated and multifactorial disease that is influenced by several risk factors, including environmental and genetic factors [3]. In the age of precision medicine, much research focused on the relationship between genetic factors, such as single-nucleotide polymorphisms (SNPs), and susceptibility to IS [4]. On the basis of the TOAST (Trial of ORG 10172 in Acute Stroke Treatment) [5] classification system, the main subtype of ischemic stroke is large artery atherosclerotic stroke (LAAS) [6]. Therefore, it will be of great significance to study the relationship between SNPs and LAAS for the prevention, diagnosis, treatment, and prognosis of IS [7].

It is generally accepted that LAAS is mainly triggered by atherosclerosis. The inflammatory process of atherosclerosis has been recognized as early as the 19th century. Substantial evidence has suggested that the inflammatory mechanisms involved in the pathogenesis of atherosclerosis are regulated by both adaptive and innate immunity [8–10]. The protein tyrosine phosphatase nonreceptor (PTPN22) gene is located on chromosome 1p13.2 and encodes the cytoplasmic lymphoid phosphatase (Lyp). Lyp is required for the immune system function to be well balanced [11, 12]. In recent years, the PTPN22 gene and its susceptibility to a variety of inflammatory diseases have been recognized [13–16]. Furthermore, genetic variants of PTPN22 increased the risk of atherosclerosis in people with autoinflammatory disorders [17, 18]. In patients with large arterial occlusive disease, microemboli that are released from atherosclerotic plaques can result in acute ischemic stroke [19]. Microembolic signals (MES) can be detected through the transcranial Doppler ultrasonography (TCD). MES suggest that atherosclerotic plaques may be unstable and may be potential risk markers for ischemic stroke [20]. In addition, smoking and drinking are considered significant environmental risk factors for LAAS. Therefore, our research was designed to evaluate whether three SNPs of the PTPN22 gene are correlated with LAAS and MES as well as the interaction of these SNPs with smoking and drinking.

2. Materials and Methods

2.1. Study Population

We recruited 364 LAAS patients and 369 healthy control subjects from unrelated ethnic Han Chinese populations. LAAS patients were diagnosed by two experienced neurologists on the basis of TOAST [5] criteria and had lesions that were restricted to the middle cerebral artery or internal carotid artery areas. All the patients were hospitalized in the Neurology Department of the Affiliated Hospital of Qingdao University between 2013 and 2017. The inclusion criteria of the cases were the presence of ischemic stroke, which was confirmed by magnetic resonance imaging (MRI) or computer tomography (CT), and the presence of cardiac and cerebral vascular lesions, which were confirmed by echocardiography, TCD, brain magnetic resonance angiography (MRA), or whole-brain digital subtraction angiography (DSA). All patients were subjected to microembolism monitoring. The patients were divided into MES-negative and MES-positive groups according to the presence of MES. The exclusion criteria were patients who were diagnosed with any other subtype of IS (small artery occlusion, cardioembolic stroke, stroke of undetermined etiology, and stroke of other determined etiology) or who had severe infection, severe heart disease (recent myocardial infarction, angina pectoris disease, and valvular heart disease), severe hepatic and renal insufficiency, chronic inflammation, a malignant tumor, or autoimmune disease. Healthy control subjects were enrolled from the health examination center at our hospital during the same time period. The inclusion criteria were as follows: participants who had no clinical features or neuroimaging evidence of cerebral infarction, nor obvious cerebral atherosclerosis or angiostenosis, nor any history of ischemic stroke. The exclusion criteria were similar to the criteria applied to the LAAS group.

The research was carried out according to the ethical guidelines within the Helsinki declaration for experiments involving human participants. This study protocol was authorized by the ethical committee of the Affiliated Hospital of Qingdao University (QDDXYXYFSXY-2014-005). Informed consent was acquired from each participant in this study.

2.2. Data Collection

Clinical data and demographic information from all the subjects were collected by well-trained investigators. Structured questionnaire surveys were administered to acquire the general statuses of the subjects, including body mass index (BMI); age; sex; history of smoking, drinking, hypertension, diabetes, coronary artery disease (CAD), and dyslipidemia; and family history of ischemic stroke events. After one night of fasting, antecubital venous blood (4 mL) samples were collected from all participants and were later placed into EDTA tubes followed by a 10-minute centrifugation at 3000 rpm. Levels of serum blood glucose (GLU), triglycerides (TG), total cholesterol (TC), low-density lipoproteins (LDL), and high-density lipoproteins (HDL) were measured in the clinical laboratory of our hospital.

2.3. SNP Selection

PTPN22 gene was selected based on exploring previously reported genes that might be involved in inflammatory responses or related to inflammatory diseases. To the best of our knowledge, the association between PTPN22 gene and LAAS and MES has not been reported so far. According to minimum allele frequency, minor allele frequency (MAF) was greater than 5% in the Chinese Beijing Han population (CHB) from the 1000 Genomes Browser and previously reported gene loci that might be related to inflammatory responses. Finally, three SNPs (rs2476599, rs1217414, and rs2488457) were selected.

2.4. Genotyping

Following the manufacturer’s instructions of TIANamp Blood DNA Kit (Tiangen Biotech, Beijing, China), we extracted genomic DNA from the blood samples. TaqMan technology was used to explore the PTPN22 rs2476599, rs1217414, and rs2488457 gene polymorphisms. The specific primers and probes were designed and synthesized by the Sangon Biotech Company (Shanghai, China). The sequences of the primers and probes are shown in Supplementary 1. Each PCR reaction consisted of 5 μL 2x TaqMan Fast qPCR Master Mix (Sangon Biotech, Shanghai, China), 0.25 μL forward and 0.25 μL reverse primer (10 μM), 0.2 μL (10 μM) FAM-labeled probe, 0.2 μL (10 μM) VIC-labeled probe, 2.0 μL template DNA, and 2.1 μL double-distilled H₂O (ddH₂O). The PCR cycling conditions were as follows: predegeneration for 3 min at 94°C and then denaturation at 94°C for 5 s and 40 cycles of annealing and extension for 30 s at 60°C. Reactions were performed on the LightCycler® 480 II Real-Time PCR System (Roche Diagnostics, Manheim, Germany) according to the manufacturer’s protocols. Afterwards, we analyzed the genotypes on the LightCycler® 480 software version 1.5.0. To ensure accuracy of genotyping, 20% of the samples for each polymorphism were randomly selected for direct sequencing. Supplementary 2 shows the sequences of primers for DNA sequencing. The results that were achieved by the two methods were absolutely concordant.

2.5. Microembolic Signal Monitoring

Within 72 hours of the onset of stroke, TCD (EMS- Doppler box/EMS-9EB MHz probe) was used for monitoring the MES in all patients. The 2 MHz probe was fixed to the patient’s head, and the MES monitoring was performed in the initial segment and distal segment of the symptomatic middle cerebral artery (MCA) (distance between two points, ≥6 mm; sampling depth, 50–65 mm; sample volume, 8 mm; MES threshold, ≥5 dB; and monitoring time, 60 min). The criteria for microembolic signals were based on a study by Ringelstein et al. [21]. Microembolism monitoring was conducted by two trained and experienced neurologists.

2.6. Statistical Analysis

Count data are presented as the number of cases and percentages and were analyzed by using chi-squared test. Quantitative variables were recorded as the deviations (SDs) with normal distributions, and Student’s -test was applied to analyze the differences. Hardy-Weinberg equilibrium (HWE) testing was carried out by using chi-squared tests for each locus. Pearson’s test or Fisher’s exact test was used for comparisons of genotypes and allele frequencies. Logistic regression analyses were performed to compute odds ratios (OR) with 95% confidence intervals (CI) after adjusting the covariates (sex, age, history of smoking and drinking, diabetes, hypertension, dyslipidemia, and family history of ischemic stroke events) to assess the correlation between LAAS and PTPN22 gene polymorphisms. Linkage disequilibrium (LD) and haplotype distributions were estimated using the SHEsis software platform [22, 23]. Tests for interactions with drinking or smoking were only focused on the SNPs that were significantly associated with LAAS. All statistical analyses were performed using the SPSS 20.0 software. value < 0.05 (two-tailed) was considered statistically significant. Power calculation was performed at the 0.05 level of type I error probability using the GPower software version 3.1.

3. Results

3.1. Characteristics of the Subjects

Table 1 summarizes the clinical characteristics of LAAS patients and control subjects. There were no differences between two cohorts in the aspects of age, sex, BMI, history of CAD, and the levels of LDL, TG, and HDL (). The levels of GLU and TC, diabetes, hypertension, dyslipidemia, alcohol consumption, family history of ischemic stroke events, and smoking are higher in the LAAS group ().

3.2. Association between PTPN22 Gene Polymorphisms and LAAS

The distributions of the alleles and genotypes were in accordance with Hardy-Weinberg equilibrium in both groups (). When compared to the reference (CC), we observed that the GG genotype of rs2488457 was associated with a significantly increased risk of LAAS after controlling for other covariates selected in our study (adjusted , 95% CI 1.395-3.709, ). Furthermore, patients carrying the G allele showed an increased risk of LAAS compared with carriers of the C allele (adjusted , 95% CI 1.156-1.833, ). However, the genotypes and allele frequencies for rs1217414 and rs2476599 were not significantly different (Table 2). The statistical power for detecting the relation between rs2488457 and LAAS was over 90%.

3.3. Association between PTPN22 Gene Polymorphisms and Microembolic Signals

Ninety-five patients presented with microembolic signals in the LAAS group. There were no differences in the clinical characteristics between the MES-positive and MES-negative groups (Table 3). The outcomes showed that patients carrying the rs2488457 GG genotypes had a higher risk of developing microembolic signals (adjusted , 95% CI 1.339-5.011, ). Patients carrying the G allele were more likely to have microembolic signals (adjusted , 95% CI 1.177-2.319, ). There was no association between microembolic signals and either rs1217414 or rs2476599 polymorphism (Table 4).

3.4. Haplotype Analysis

Using the linkage disequilibrium (LD) test results, we conducted haplotype analyses for three SNPs using the SHEsis software platform (Figure 1). The results revealed that the prevalence of the GCC haplotype was higher in the control group. In contrast, the frequency of the GTG haplotype was less than the frequency in the LAAS group. The haplotype distributions indicated that the GTG haplotype was related to higher risk of LAAS (, 95% CI, 1.631–4.731, ). Nevertheless, the GCC haplotype may play a protective role against LAAS (, 95% CI, 0.547–0.850, ) (Table 5).

The value between rs1217414 and rs2488457 is 0.71, the value between rs2476599 and rs1217414 is 0.43, and the value between rs2476599 and rs2488457 is 0.33.

3.5. Stratified Analysis

Stratified analyses based on age, gender, and BMI were performed. According to the results, we failed to find any association between these factors and rs2488457 polymorphism (Table 6).

3.6. Interaction Analysis

Only the rs2488457 polymorphism was significantly associated with LAAS among the three SNPs. The interaction analysis of the rs2488457 polymorphism with drinking or smoking was performed by means of logistic regression. Compared to nonsmokers with rs2488457 CC genotype, smokers with CG+GG genotype had a distinctly higher risk of LAAS (adjusted , 95% CI 1.510–4.114, ). However, there were no any differences in the risk of LAAS among the CG+GG genotype nonsmokers and the CC genotype smokers (adjusted , 95% CI 0.987–2.172, ; adjusted , 95% CI 0.972–3.251, , respectively). No interaction was observed between the rs2488457 polymorphism and drinking (Table 7).

4. Discussion

To date, our research was the first to explore the relationship between PTPN22 SNPs (rs2476599, rs1217414, and rs2488457) and LAAS. The results demonstrated that the frequency of G allele in the PTPN22 rs2488457 was higher in the LAAS group, which suggested that G allele might be a potential risk marker for the prediction of LAAS. However, the present study failed to find any effect of rs2476599 and rs1217414 on LAAS. In the linkage disequilibrium analysis, an incomplete linkage disequilibrium of the three loci was identified. Haplotype analysis revealed that the GTG haplotype might be responsible for the susceptibility to LAAS and that the GCC haplotype might confer a decreased risk of LAAS.

The PTPN22 gene encodes Lyp, which regulates the production of inflammatory cytokines by participating in the TLR (Toll like receptor) signaling pathway [24–26]. Several SNPs of the PTPN22 gene, related to a variety of inflammatory diseases, have been found in previous studies [27–29]. In a multicenter cohort study of the Finns, Pertovaara et al. discovered that PTPN22 polymorphisms were significantly related to increased carotid artery intima-media thickness (IMT) [30]. Saccucci et al. showed that PTPN22 genetic polymorphisms were related to the occurrence of CAD [31]. In our study, a correlation between the rs2488457 polymorphism and LAAS was found. Nevertheless, the molecular mechanism of how PTPN22 gene polymorphisms affect atherosclerosis remains unclear. Studies have shown that PTPN22 increases both the inflammatory response and IL1B (interleukin 1 beta) secretion by dephosphorylating NLRP3 (NLR family pyrin domain-containing 3) inflammasome to protect NLRP3 from degradation, which leads to the occurrence of many inflammatory diseases [32, 33]. The NLRP3 inflammasome and the IL (interleukin) family cytokines are central mediators of vascular inflammation during the process of atherosclerosis [34]. The activation of NLRP3 inflammasome demands an initial priming signal via receptors that activate NF-κB-mediated transcription, such as TLR or IL [35]. When the NLRP3 inflammasome is activated, it triggers the excretion of mature, proinflammatory cytokines [36]. Therefore, we speculate that this may be the molecular mechanism of the PTPN22 genetic variations that influence the occurrence of LAAS.

To study the relationship between PTPN22 gene polymorphisms and the stability of atherosclerotic plaques, LAAS subjects were split into MES-negative and MES-positive groups according to the presence of MES. Additional analysis showed that patients carrying the G allele were more likely to have MES, thus demonstrating that the rs2488457 polymorphism was involved in the generation of MES. MES indicate that the plaque is unstable. Aubry et al. [37] reported that patients with rheumatoid arthritis (RA) have an increased incidence of vulnerable plaques in the left anterior descending coronary artery, compared with controls, along with a greater evidence of inflammation and plaque instability. Therefore, we hypothesized that the rs2488457 polymorphism results in the instability of atherosclerotic plaques via the acceleration of inflammation.

Smoking and drinking are known to have marked impacts on the progression of atherosclerosis. The proportions of drinking and smoking individuals were larger in the LAAS group, and a strong interaction between smoking and the rs2488457 polymorphism was observed, whereas there was no interaction between the rs2488457 polymorphism and drinking in our study. Nordskog et al. [38] revealed that the expression of proinflammatory mediators was significantly increased in the endothelial cells after exposure to cigarette smoke. An increasing number of scholars believe that vascular inflammation is induced by smoking [39]. Notably, our study revealed that only the combination of smoking status with the rs2488477 G allele (CG+GG) increased the risk of LAAS. This result seemed to imply that individual responses to environmental factors varied by different genetic backgrounds. Genetic and environmental factors are related to each other and can jointly affect the occurrence and development of diseases. However, the potential mechanism of the rs2488457-smoking interaction in LAAS risk is not understood. Future studies focusing on this interaction should be carried out.

5. Conclusion

In conclusion, our study indicated that the rs2488457 polymorphism was likely to be associated with LAAS and MES, and this polymorphism had an interaction with smoking in terms of the impacts on LAAS risk. These results could lead to a potential treatment strategy for LAAS, such as gene therapy. However, the current study contains a relatively small sample size, which may be a limitation. Additionally, there were only three SNP loci analyzed, which did not reflect the function of the entire gene. Moreover, the distributions and functions of genes among different ethnicities are different. Our study was only conducted in the Han Chinese population; thus, these conclusions may not represent the whole population. The replication of our study in different populations and the complete analysis of genetic changes in vivo are required to better clarify the effects of PTPN22 gene polymorphisms on LAAS and MES.

Data Availability

The data used to support the findings of this study are available from the corresponding authors upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This study was supported by the National Key R&D Program of China (No. 2017YFC1310903) and the National Natural Science Foundation of China (No. 81771259 and No. 81571112).

Supplementary Materials

Supplementary 1. Table S1: the sequences of the primers and probes for TaqMan technology.

Supplementary 2. Table S2: the sequences of the primers for DNA sequencing.

References

B. Norrving and B. Kissela, “The global burden of stroke and need for a continuum of care,” Neurology, vol. 80, 3 Supplement 2, pp. S5–S12, 2013.
View at: Publisher Site | Google Scholar
E. V. Kuklina, X. Tong, M. G. George, and P. Bansil, “Epidemiology and prevention of stroke: a worldwide perspective,” Expert Review of Neurotherapeutics, vol. 12, no. 2, pp. 199–208, 2012.
View at: Publisher Site | Google Scholar
T. Hachiya, Y. Kamatani, A. Takahashi et al., “Genetic predisposition to ischemic stroke: a polygenic risk score,” Stroke, vol. 48, no. 2, pp. 253–258, 2017.
View at: Publisher Site | Google Scholar
S. Bevan, M. Traylor, P. Adib-Samii et al., “Genetic heritability of ischemic stroke and the contribution of previously reported candidate gene and genomewide associations,” Stroke, vol. 43, no. 12, pp. 3161–3167, 2012.
View at: Publisher Site | Google Scholar
H. P. Adams Jr, B. H. Bendixen, L. J. Kappelle et al., “Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment,” Stroke, vol. 24, no. 1, pp. 35–41, 1993.
View at: Publisher Site | Google Scholar
M. Mirzaei, A. S. Truswell, K. Arnett, A. Page, R. Taylor, and S. R. Leeder, “Cerebrovascular disease in 48 countries: secular trends in mortality 1950–2005,” Journal of Neurology, Neurosurgery & Psychiatry, vol. 83, no. 2, pp. 138–145, 2012.
View at: Publisher Site | Google Scholar
P. Sharma, S. Yadav, and J. F. Meschia, “Genetics of ischaemic stroke,” Journal of Neurology, Neurosurgery & Psychiatry, vol. 84, no. 12, pp. 1302–1308, 2013.
View at: Publisher Site | Google Scholar
J. L. Witztum and A. H. Lichtman, “The influence of innate and adaptive immune responses on atherosclerosis,” Annual Review of Pathology: Mechanisms of Disease, vol. 9, no. 1, pp. 73–102, 2014.
View at: Publisher Site | Google Scholar
B. Legein, L. Temmerman, E. A. L. Biessen, and E. Lutgens, “Inflammation and immune system interactions in atherosclerosis,” Cellular and Molecular Life Sciences, vol. 70, no. 20, pp. 3847–3869, 2013.
View at: Publisher Site | Google Scholar
G. K. Hansson and A. Hermansson, “The immune system in atherosclerosis,” Nature Immunology, vol. 12, no. 3, pp. 204–212, 2011.
View at: Publisher Site | Google Scholar
S. M. Stanford and N. Bottini, “PTPN22: the archetypal non-HLA autoimmunity gene,” Nature Reviews Rheumatology, vol. 10, no. 10, pp. 602–611, 2014.
View at: Publisher Site | Google Scholar
G. Fousteri, S.-N. C. Liossis, and M. Battaglia, “Roles of the protein tyrosine phosphatase PTPN22 in immunity and autoimmunity,” Clinical Immunology, vol. 149, no. 3, pp. 556–565, 2013.
View at: Publisher Site | Google Scholar
K. Yamamoto, Y. Okada, A. Suzuki, and Y. Kochi, “Genetics of rheumatoid arthritis in Asia--present and future,” Nature Reviews Rheumatology, vol. 11, no. 6, pp. 375–379, 2015.
View at: Publisher Site | Google Scholar
T. Umemura, S. Joshita, T. Yamazaki et al., “Genetic association of PTPN22 polymorphisms with autoimmune hepatitis and primary biliary cholangitis in Japan,” Scientific Reports, vol. 6, no. 1, article 29770, 2016.
View at: Publisher Site | Google Scholar
N. Manjarrez-Orduño, E. Marasco, S. A. Chung et al., “CSK regulatory polymorphism is associated with systemic lupus erythematosus and influences B-cell signaling and activation,” Nature Genetics, vol. 44, no. 11, pp. 1227–1230, 2012.
View at: Publisher Site | Google Scholar
G. L. Burn, L. Svensson, C. Sanchez-Blanco, M. Saini, and A. P. Cope, “Why is PTPN22 a good candidate susceptibility gene for autoimmune disease?” FEBS Letters, vol. 585, no. 23, pp. 3689–3698, 2011.
View at: Publisher Site | Google Scholar
G. C. Wu, H. R. Liu, R. X. Leng et al., “Subclinical atherosclerosis in patients with systemic lupus erythematosus: a systemic review and meta-analysis,” Autoimmunity Reviews, vol. 15, no. 1, pp. 22–37, 2016.
View at: Publisher Site | Google Scholar
E. Matsuura, F. Atzeni, P. Sarzi-Puttini, M. Turiel, L. R. Lopez, and M. T. Nurmohamed, “Is atherosclerosis an autoimmune disease?” BMC Medicine, vol. 12, no. 1, p. 47, 2014.
View at: Publisher Site | Google Scholar
J. Jiang, Y. Jiang, S. Feng et al., “Microembolic signal monitoring of TOAST-classified cerebral infarction patients,” Molecular Medicine Reports, vol. 8, no. 4, pp. 1135–1142, 2013.
View at: Publisher Site | Google Scholar
Q. Hao, W. H. Leung, C. Leung et al., “The significance of microembolic signals and new cerebral infarcts on the progression of neurological deficit in acute stroke patients with large artery stenosis,” Cerebrovascular Diseases, vol. 29, no. 5, pp. 424–430, 2010.
View at: Publisher Site | Google Scholar
E. Bernd Ringelstein, D. W. Droste, V. L. Babikian et al., “Consensus on microembolus detection by TCD,” Stroke, vol. 29, no. 3, pp. 725–729, 1998.
View at: Publisher Site | Google Scholar
Y. Yong and L. He, “SHEsis, a powerful software platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci,” Cell Research, vol. 15, no. 2, pp. 97-98, 2005.
View at: Publisher Site | Google Scholar
Z. Li, Z. Zhang, Z. He et al., “A partition-ligation-combination-subdivision EM algorithm for haplotype inference with multiallelic markers: update of the SHEsis (http://analysis.bio-x.cn),” Cell Research, vol. 19, no. 4, pp. 519–523, 2009.
View at: Publisher Site | Google Scholar
N. Bottini and E. J. Peterson, “Tyrosine phosphatase PTPN22: multifunctional regulator of immune signaling, development, and disease,” Annual Review of Immunology, vol. 32, pp. 83–119, 2014.
View at: Publisher Site | Google Scholar
J. Zhang, N. Zahir, Q. Jiang et al., “The autoimmune disease-associated PTPN22 variant promotes calpain-mediated Lyp/Pep degradation associated with lymphocyte and dendritic cell hyperresponsiveness,” Annual Review of Immunology, vol. 43, no. 9, pp. 902–907, 2011.
View at: Publisher Site | Google Scholar
Y. Wang, I. Shaked, S. M. Stanford et al., “The autoimmunity-associated gene PTPN22 potentiates toll-like receptor-driven, type 1 interferon-dependent immunity,” Immunity, vol. 39, no. 1, pp. 111–122, 2013.
View at: Publisher Site | Google Scholar
X. Dai, R. G. James, T. Habib et al., “A disease-associated PTPN22 variant promotes systemic autoimmunity in murine models,” Journal of Clinical Investigation, vol. 123, no. 5, pp. 2024–2036, 2013.
View at: Publisher Site | Google Scholar
L. Diaz-Gallo, P. Gourh, J. Broen et al., “Analysis of the influence of PTPN22 gene polymorphisms in systemic sclerosis,” Annals of the Rheumatic Diseases, vol. 70, no. 3, pp. 454–462, 2011.
View at: Publisher Site | Google Scholar
L. Rodríguez-Rodríguez, W. R. W. Taib, R. Topless et al., “The PTPN22 R263Q polymorphism is a risk factor for rheumatoid arthritis in Caucasian case-control samples,” Arthritis & Rheumatism, vol. 63, no. 2, pp. 365–372, 2011.
View at: Publisher Site | Google Scholar
M. Pertovaara, A. Raitala, M. Juonala et al., “Autoimmunity and atherosclerosis: functional polymorphism of PTPN22 is associated with phenotypes related to the risk of atherosclerosis. The Cardiovascular Risk in Young Finns Study,” Clinical & Experimental Immunology, vol. 147, no. 2, pp. 265–269, 2007.
View at: Publisher Site | Google Scholar
P. Saccucci, M. Banci, E. Cozzoli et al., “Atherosclerosis and PTPN22: a study in coronary artery disease,” Cardiology, vol. 119, no. 1, pp. 54–56, 2011.
View at: Publisher Site | Google Scholar
M. R. Spalinger, S. Lang, C. Gottier et al., “PTPN22 regulates NLRP3-mediated IL1B secretion in an autophagy-dependent manner,” Autophagy, vol. 13, no. 9, pp. 1590–1601, 2017.
View at: Publisher Site | Google Scholar
M. R. Spalinger, S. Kasper, C. Gottier et al., “NLRP3 tyrosine phosphorylation is controlled by protein tyrosine phosphatase PTPN22,” Journal of Clinical Investigation, vol. 126, no. 5, pp. 1783–1800, 2016.
View at: Publisher Site | Google Scholar
C. A. Dinarello, “Overview of the IL-1 family in innate inflammation and acquired immunity,” Immunological Reviews, vol. 281, no. 1, pp. 8–27, 2018.
View at: Publisher Site | Google Scholar
M. G. Ghonime, O. R. Shamaa, S. Das et al., “Inflammasome priming by lipopolysaccharide is dependent upon ERK signaling and proteasome function,” The Journal of Immunology, vol. 192, no. 8, pp. 3881–3888, 2014.
View at: Publisher Site | Google Scholar
D. Y.-W. Fann, S. Y. Lee, S. Manzanero, P. Chunduri, C. G. Sobey, and T. V. Arumugam, “Pathogenesis of acute stroke and the role of inflammasomes,” Ageing Research Reviews, vol. 12, no. 4, pp. 941–966, 2013.
View at: Publisher Site | Google Scholar
M.-C. Aubry, H. Maradit-Kremers, M. S. Reinalda, C. S. Crowson, W. D. Edwards, and S. E. Gabriel, “Differences in atherosclerotic coronary heart disease between subjects with and without rheumatoid arthritis,” The Journal of rheumatology, vol. 34, no. 5, pp. 937–942, 2007.
View at: Google Scholar
B. K. Nordskog, A. D. Blixt, W. T. Morgan, W. R. Fields, and G. M. Hellmann, “Matrix-degrading and pro-inflammatory changes in human vascular endothelial cells exposed to cigarette smoke condensate,” Cardiovascular Toxicology, vol. 3, no. 2, pp. 101–118, 2003.
View at: Publisher Site | Google Scholar
J. A. Ambrose and R. S. Barua, “The pathophysiology of cigarette smoking and cardiovascular disease: an update,” Journal of the American College of Cardiology, vol. 43, no. 10, pp. 1731–1737, 2004.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2019 Lingyan Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

1263

Downloads

827

Citations