Abstract
Background
Recently studies uncovered associations between polymorphisms of interleukin genes and the risk of asthma. However, the relationship between polymorphisms of interleukin‐7 gene and the risk of children asthma has not been discovered yet. This study aims to investigate the relationship between single nucleotide polymorphisms (SNPs) on interleukin‐7 gene and the risk of children asthma.
Methods
We genotyped eight SNPs of interleukin‐7 gene in blood samples from 437 asthma patients and 489 healthy controls to analyze potential associations of these SNPs with the risk of asthma in children.
Results
A missense SNP rs766736182 (odds ratio (OR) = 2.185, 95% confidence interval (CI) = 1.561‐2.252, P‐value = 8.69468E‐19) of the interleukin‐7 gene is associated with the risk of children asthma.
Conclusions
This study reveals that SNP rs766736182 of interleukin‐7 is the risk factor for children asthma and implies potential role of immune system in the pathogenesis of children asthma.
Keywords: children asthma, interleukin‐7, polymorphism
1. INTRODUCTION
Asthma is a common long‐term respiratory disease, which is characterized by variable and recurring symptoms, reversible airflow obstruction, and bronchospasm.1 Asthma typically begins in childhood and occurs throughout patients’ life. The incidence rates of asthma in children vary between regions and countries, the average of which is 11.7% and 14.1% in 6‐7 year and 13‐14 year, respectively.2 Asthma is caused by a combination of genetic and environmental factors. Exposing to air pollution and allergens are most common environmental factors. Cytokines drive the inflammatory processes and are the most important genetic factors that underlying pathophysiological mechanisms of asthma.3
Interleukin genes encode cytokines important for inflammatory processes.4, 5 The single nucleotide polymorphisms (SNPs) of several interleukin genes, such as interleukin‐1,6 interleukin‐2,7 and interleukin‐6,8 associate with the risk of asthma in childhood. Interleukin‐7 encodes a cytokine important for B‐ and T‐cell development, which functions as a pre‐pro‐B cell growth‐stimulating factor and a cofactor for V(D)J rearrangement of the T‐cell receptor beta (TCRB) during early T‐cell development. However, it is still unclear whether SNPs in interleukin‐7 are associated with asthma.
To study whether polymorphism of interleukin‐7 gene associates with the risk of asthma, we genotyped eight SNPs (rs766736182, rs762037062, rs1545228, rs2583759, rs1441850, rs1119642, rs11777564, and rs145230246) of interleukin‐7 gene in blood samples from 437 asthma patients and 489 age‐matched healthy children. The statistical analysis revealed only SNP rs766736182 of interleukin‐7 but no other seven SNPs is significantly associated with the risk of asthma, which suggested a potential role of interleukin‐7 gene polymorphism in the pathogenesis of asthma.
2. Materials and Methods
2.1. Study design and patients
The case‐control study consisted of 437 asthma patients [216 boys and 221 girls with a mean age ± SD of 4.1 ± 3.16 years] and 489 healthy controls [227 boys and 224 girls with a mean age ± SD of 4.62 ± 3.69 years] from Xuzhou Children's Hospital. Patients with asthma were diagnosed by clinical medical specialists according to diagnosis guidelines of the American Thoracic Society for asthma.9 The age‐matched healthy boys and girls in control group had no symptoms or history of allergy or asthma or other pulmonary diseases. After a full rationalization of the procedure, written consents were obtained from legal guardians of all participants. The ethics council of Xuzhou Children's Hospital approved this study according to the declaration of national capital.
2.2. Genotyping
Blood samples were drawn from patients and healthy controls to extract DNA using a QIAamp DNA Blood Mini Kit (QIAGEN, Valencia, CA). Selected eight SNPs in the interleukin‐7 gene were captured using a PCR reaction system and were confirmed by ABI‐PRISM 3730 genetic analyzer (Sequenom, Inc.) via sequencing. These eight SNPs were selected from the dbSNP database (www.ncbi.nlm.nih.gov/SNP), in which rs766736182 and rs762037062 are missense SNPs, rs1545228 and rs2583759 locate at 3'UTR, rs1441850, rs1119642, and rs11777564 locate at intron region, and rs145230246 locates at 5'UTR.
2.3. PCR system
The 50 μL PCR reaction system is as follows: 2 μL DNA, 2 μL of primers, 0.25 μL Taq enzyme, 4 μL dNTP, 5 μL PCR buffer, and add water to a final volume of 50 μL to build the reaction mixture. Thereafter, initial denaturation for 5 minutes at 94°C. Thirty‐nine amplification cycles were performed using the following conditions: 94°C for 30 s, 52.7°C for 50 s, 72°C for 45 s. Finally, it is the 5 minutes extension at 72°C.
2.4. Statistical analysis
The chi‐squared test was performed to decide genotype frequencies and allele differences between asthma patients and healthy controls, and the odds ratio (OR) with a 95% confidence interval (CI) was used to decide relative risk. Hardy‐Weinberg equilibrium (HWE) tests were for data quality control using R. linkage disequilibrium (LD) was measured by R 2. All P‐values are two‐tailed value and are statistical significant when <0.05.
3. RESULTS
3.1. rs766736182 associates with the risk of asthma
The case‐control study involved 437 asthma patients (216 boys and 221 girls with a mean age ± SD of 4.1 ± 3.16 years) and 489 age‐matched healthy controls (227 boys and 224 girls with a mean age ± SD of 4.62 ± 3.69 years (Table 1). Distributions of the genotypes of the eight SNPs in all age‐matched healthy controls and in most of the patients were in Hardy‐Weinberg equilibrium (HWE), except for rs766736182 in asthma patients (Table 2). The rs766736182 showed significant differences between asthma patients and healthy controls in both allele frequencies and genotype frequencies (P‐value < 0.05). The other seven of tested SNPs showed no significant differences in either allele frequencies or genotype frequencies between asthma patients (n = 437) and controls (n = 489) for seven of tested SNPs (Table 2). The G allele frequency of rs766736182 was higher in asthma patients than that in controls (P‐value = 8.69468E‐19, OR = 2.185, 95% confidence interval CI = 1.561‐2.252). The genotype frequencies of rs766736182 (P‐value = 8.69468E‐19) was significantly different between asthma patients and controls, respectively. The other seven of the tested SNPs showed no significant differences in allele frequencies or genotype frequencies between asthma patients (n = 437) and controls (n = 489) for seven of the tested SNPs (Table 2). Moreover, no significant differences in allele frequencies or genotype frequencies of rs766736182 were observed between asthma patients in different stages (Table 3).
Table 1.
Information of asthma patients and age‐matched controls
| Patients (n = 437) | Control (n = 451) | |
|---|---|---|
| Age (y) | 4.1 ± 3.16 | 4.62 ± 3.69 |
| Male | 216 | 227 |
| Female | 221 | 224 |
| Mild asthma | 239 | NA |
| Moderate asthma | 157 | NA |
| Severe asthma | 41 | NA |
| Population | ||
| Han | 428 | 436 |
| Others | 9 | 15 |
| Family history | ||
| Yes | 5 | 0 |
| No | 432 | 451 |
NA, Not available.
Table 2.
Allele and genotype frequencies of SNPs in patients and age‐matched controls
| Group | Allele frequency | P | Genotype frequency | P | H‐ W | |||
|---|---|---|---|---|---|---|---|---|
| rs766736182 | A | G | AA | AG | GG | |||
| Patients | 629 | 245 | 8.6947E‐19 | 215 | 199 | 23 | 2.5015E‐18 | 0.026926 |
| Control | 751 | 151 | 312 | 127 | 12 | 0.976958 | ||
| rs1545228 | A | G | AA | AG | GG | |||
| Patients | 540 | 334 | 0.35107282 | 155 | 230 | 52 | 0.47801731 | 0.056868 |
| Control | 557 | 345 | 165 | 227 | 59 | 0.379922 | ||
| rs2583759 | A | G | AA | AG | GG | |||
| Patients | 581 | 293 | 0.14481981 | 187 | 207 | 43 | 0.34335729 | 0.422815 |
| Control | 583 | 319 | 179 | 225 | 47 | 0.152863 | ||
| rs1441850 | A | G | AA | AG | GG | |||
| Patients | 543 | 331 | 0.153396 | 167 | 209 | 61 | 0.35699542 | 0.943474 |
| Control | 544 | 358 | 159 | 226 | 66 | 0.611194 | ||
| rs1119642 | C | T | CC | CT | TT | |||
| Patients | 489 | 385 | 0.20223551 | 139 | 211 | 87 | 0.34278251 | 0.912631 |
| Control | 518 | 384 | 146 | 226 | 79 | 0.870155 | ||
| rs11777564 | A | G | AA | AG | GG | |||
| Patients | 717 | 157 | 0.3511808 | 299 | 119 | 19 | 0.79955693 | 0.282424 |
| Control | 740 | 162 | 309 | 122 | 20 | 0.219136 | ||
| rs762037062 | C | T | CC | TC | TT | |||
| Patients | 705 | 169 | 0.067751 | 285 | 135 | 17 | 0.15504635 | 0.979676 |
| Control | 746 | 156 | 307 | 132 | 12 | 0.886651 | ||
| rs145230246 | G | T | GG | TG | TT | |||
| Patients | 489 | 385 | 0.14238464 | 135 | 219 | 83 | 0.33764696 | 0.940992 |
| Control | 522 | 380 | 153 | 216 | 82 | 0.931151 | ||
SNP, single nucleotide polymorphism.
Table 3.
Subgroup comparisons of allele and genotype frequencies of rs766736182
| Group | P‐value | |
|---|---|---|
| Allele frequency | Genotype frequency | |
| Mild asthma vs Moderate asthma | 0.128723 | 0.237615 |
| Mild asthma vs Severe asthma | 0.688137 | 0.380183 |
| Moderate asthma vs Severe asthma | 0.761681 | 0.397457 |
3.2. Linkage disequilibrium analysis
The linkage disequilibrium (LD) analysis revealed that only rs1441850 and rs1545228 showed strong LD with each other (R 2 > 0.8) (Table 4). Other SNP pairs only showed modest or weak LD, as evidenced by low R2 value, especially for SNP pairs involving rs145230246, rs766736182, and rs762037062 (Table 4). It suggests that most of analyzed SNPs perform their function independently in the studied population, which make building haplotypes unnecessary in this study.
Table 4.
The linkage disequilibrium(R 2) among the SNPs
| R 2 | rs1545228 | rs2583759 | rs145230246 | rs1441850 | rs1119642 | rs11777564 | rs766736182 | rs762037062 |
|---|---|---|---|---|---|---|---|---|
| rs1545228 | 1 | 0.649 | 0 | 0.995 | 0.014 | 0.061 | 0 | 0 |
| rs2583759 | 0.649 | 1 | 0 | 0.647 | 0 | 0 | 0 | 0.013 |
| rs145230246 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
| rs1441850 | 0.995 | 0.647 | 0 | 1 | 0.014 | 0.062 | 0.215 | 0 |
| rs1119642 | 0.014 | 0 | 0 | 0.014 | 1 | 0.001 | 0 | 0 |
| rs11777564 | 0.061 | 0 | 0 | 0.062 | 0.001 | 1 | 0 | 0 |
| rs766736182 | 0 | 0 | 0 | 0.215 | 0 | 1 | 0 | |
| rs762037062 | 0 | 0.013 | 0 | 0 | 0 | 0 | 0 | 1 |
SNP, single nucleotide polymorphism.
4. DISCUSSION
Asthma is a long‐term respiratory disease characterized by variable and recurring symptoms, reversible airflow obstruction, and bronchospasm, and begins in childhood.1 Recent studies suggested that genetic factors, such as single nucleotide polymorphisms (SNPs) of genes, might contribute to the risk of many diseases,10, 11, 12 as well as children asthma.13 In this study, we found significant association between missense SNP rs766736182(P‐value = 8.69468E‐19, OR = 2.185, 95% confidence interval CI = 1.561‐2.252) of interleukin‐7 gene and the risk of children asthma.
Interleukin‐7 is a cytokine important for B‐ and T‐cell development. It stimulates the differentiation of multipotent (pluripotent) hematopoietic stem cells into lymphoid progenitor cells and plays important roles in many types of diseases.14, 15, 16, 17, 18 Interleukin‐7 binds to the interleukin‐7 receptor, a heterodimer consisting of interleukin‐7 receptor alpha and common gamma chain receptor, which results in a cascade of signals important for T‐cell development within the thymus and survival within the periphery.19 The airway response to allergen is associated with the generation of interleukin‐7, which may contribute to airway inflammation in asthma by promoting enhanced eosinophil activation and survival.20 However, it is still unclear whether SNPs of interleukin‐7 gene are associated with asthma. This study aims to investigate whether SNPs of interleukin‐7 are associated with risk of asthma in 437 asthma patients and 489 healthy controls. The results show that SNPs rs766736182 of interleukin‐7 but no other SNPs are associated with the risk of asthma in Chinese Han population.
The SNP rs766736182 on interleukin‐7 gene is a missense variation, which causes a substitution of Lys to Glu on the 175th position of the amino acid sequence of interleukin‐7 protein. This study implies that this Lys175Glu substitution may alter the function of interleukin‐7 protein, thereafter alters the progress of airway inflammation and affect the incidence of asthma. Moreover, it further suggests that polymorphisms of interleukin‐7 are involved in immune‐mediated mechanisms underlying pathological process of children asthma, which would promotes novel potential therapeutics of children asthma.21, 22, 23
In conclusion, this study reveals the association of interleukin‐7 SNP rs766736182 with the risk of children asthma, which improves our knowledge on the pathogenesis of children asthma and promotes future diagnosis and therapeutics for asthma in children.
Authors Contribution
Junhua Cao, Zhenguang Li, Chonglin Zhang, Qiang Ji, Chuanling Zhang, and Tong Qian performed the experiments. Junhua Cao, Zhenguang Li, and Chonglin Zhang analyzed the data. Junhua Cao and Lijun Tian wrote and edited the article.
Cao J, Tian L, Li Z, et al. Interleukin‐7 gene polymorphism rs766736182 associates with the risk of asthma in children. J Clin Lab Anal. 2019;33:e22675 10.1002/jcla.22675
REFERENCES
- 1. Guilbert TW, Bacharier LB, Fitzpatrick AM. Severe asthma in children. J Allergy Clin Immunol Pract. 2014;2(5):489‐500. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Mallol J, Crane J, von Mutius E, Odhiambo J, Keil U, Stewart A, Group IPTS . The international study of asthma and allergies in childhood (ISAAC) phase three: a global synthesis. Allergol Immunopathol (Madr). 2013;41(2):73‐85. [DOI] [PubMed] [Google Scholar]
- 3. Chung KF. Targeting the interleukin pathway in the treatment of asthma. Lancet. 2015;386(9998):1086‐1096. [DOI] [PubMed] [Google Scholar]
- 4. Zheng Y, Wang M, Tian T, et al. Role of interleukin‐12 gene polymorphisms in the onset risk of cancer: a meta‐analysis. Oncotarget. 2017;8(18):29795‐29807. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Zhou L, Zheng Y, Tian T, et al. Associations of interleukin‐6 gene polymorphisms with cancer risk: evidence based on 49 408 cancer cases and 61 790 controls. Gene. 2018;670:136‐147. [DOI] [PubMed] [Google Scholar]
- 6. Krause K, Metz M, Makris M, Zuberbier T, Maurer M. The role of interleukin‐1 in allergy‐related disorders. Curr Opin Allergy Clin Immunol. 2012;12(5):477‐484. [DOI] [PubMed] [Google Scholar]
- 7. Park BL, Kim LH, Choi YH, et al. Interleukin 3 (IL3) polymorphisms associated with decreased risk of asthma and atopy. J Hum Genet. 2004;49(10):517‐527. [DOI] [PubMed] [Google Scholar]
- 8. Tavakol M, Amirzargar AA, Movahedi M, et al. Interleukin‐6 and tumor necrosis factor‐alpha gene polymorphisms in chronic idiopathic urticaria. Allergol Immunopathol (Madr). 2014;42(6):533‐538. [DOI] [PubMed] [Google Scholar]
- 9. Reddel HK, Taylor DR, Bateman ED, et al. An official American Thoracic Society/European Respiratory Society statement: asthma control and exacerbations: standardizing endpoints for clinical asthma trials and clinical practice. Am J Respir Crit Care Med. 2009;180(1):59‐99. [DOI] [PubMed] [Google Scholar]
- 10. He B, Lu P, Guan L, et al. Identifying key regulating miRNAs in hepatocellular carcinomas by an omics’ method. Oncotarget. 2017;8(61):103919‐103930. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Ramirez‐Bello J, Vargas‐Alarcon G, Tovilla‐Zarate C, Fragoso JM. Single nucleotide polymorphisms (SNPs): functional implications of regulatory‐SNP (rSNP) and structural RNA (srSNPs) in complex diseases. Gac Med Mex. 2013;149(2):220‐228. [PubMed] [Google Scholar]
- 12. He B, Li T, Guan L, et al. CTNNA3 is a tumor suppressor in hepatocellular carcinomas and is inhibited by miR‐425. Oncotarget. 2016;7(7):8078‐8089. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Guo X, Zheng H, Mao C, Guan E, Si H. An association and meta‐analysis study of 4 SNPs from beta‐2 adrenergic receptor (ADRB2) gene with risk of asthma in children. Asian Pac J Allergy Immunol. 2016;34(1):11‐20. [DOI] [PubMed] [Google Scholar]
- 14. Lundstrom W, Fewkes NM, Mackall CL. IL‐7 in human health and disease. Semin Immunol. 2012;24(3):218‐224. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. He B, Qiu XJ, Li P, Wang LS, Lv Q, Shi TL. HCCNet: an integrated network database of hepatocellular carcinoma. Cell Res. 2010;20(6):732‐734. [DOI] [PubMed] [Google Scholar]
- 16. He B, Zhang ZK, Liu J, et al. Bioinformatics and microarray analysis of mirnas in aged female mice model implied new molecular mechanisms for impaired fracture healing. Int J Mol Sci. 2016;17(8). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Zhu QG, Zhang SM, Ding XX, He B, Zhang HQ. Driver genes in non‐small cell lung cancer: characteristics, detection methods, and targeted therapies. Oncotarget. 2017;8(34):57680‐57692. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. He B, Lu C, Zheng G, et al. Combination therapeutics in complex diseases. J Cell Mol Med. 2016;20(12):2231‐2240. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Noguchi M, Nakamura Y, Russell SM, et al. Interleukin‐2 receptor gamma chain: a functional component of the interleukin‐7 receptor. Science. 1993;262(5141):1877‐1880. [DOI] [PubMed] [Google Scholar]
- 20. Kelly EA, Koziol‐White CJ, Clay KJ, et al. Potential contribution of IL‐7 to allergen‐induced eosinophilic airway inflammation in asthma. J Immunol. 2009;182(3):1404‐1410. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. He B, Lu C, Wang ML, et al. Drug discovery in traditional Chinese medicine: from herbal fufang to combinatory drugs. Science. 2015;350(6262):S74‐S76. [Google Scholar]
- 22. Ding XX, Zhu QG, Zhang SM, et al. Precision medicine for hepatocellular carcinoma: driver mutations and targeted therapy. Oncotarget. 2017;8(33):55715‐55730. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Raedler D, Schaub B. Immune mechanisms and development of childhood asthma. Lancet Respir Med. 2014;2(8):647‐656. [DOI] [PubMed] [Google Scholar]