Feature gene mining for prediction of paucigranulocytic asthma_Chinese Journal of Respiratory and Critical Care Medicine

Authors：

HUANG Yuyi ,  ZHANG Junyan

Allergy Department, the Second Affiliated Hospital of Guangzhou Medical University, China Guangdong Provincial Key Laboratory of Allergy & Clinical Immunology, Guangzhou, Guangdong 510260, P. R. China;

Corresponding author：

ZHANG Junyan, Email: kuhn2000@163.com

Keywords：

Paucigranulocytic asthma; gene; regulatory network; bioinformatics

DOI：

10.7507/1671-6205.202207052

Video：

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Objective To explore the mechanism of paucigranulocytic asthma and to find therapeutic target for paucigranulocytic asthma.Methods GSE143303 data and platform information were downloaded from GEO. Gene Set Enrichment Analysis were performed to construct positive and negative gene-gene interaction network correlation with paucigranulocytic asthma. Differential expression analysis, pathway commonality analysis were performed with R language.Results GSE143303 data set contained 47 endobronchial biopsies from adult (16 cases of paucigranulocytic asthma, 13 cases of healthy control). Compared with control group, the paucigranulocytic asthma group had 115 differential genes set (37 positive and 78 negative). The results of pathway commonality analysis showed that the crosslink existed within the negative gene-gene interaction network correlation with paucigranulocytic asthma. Among these, most of the genes belonged to the protein HLA gene family. Differential expression analysis show that HLA-DQB1, HLA-DRB5 were differential genes and TNFRSF13B was significantly downregulated genes in the intersect genes.Conclusion TNFRSF13B, HLA-DQB1, HLA-DRB5 and regulatory networks associated with them are the crucial factors contributing to paucigranulocytic asthma.

Citation： HUANG Yuyi, ZHANG Junyan. Feature gene mining for prediction of paucigranulocytic asthma. Chinese Journal of Respiratory and Critical Care Medicine, 2022, 21(12): 849-854. doi: 10.7507/1671-6205.202207052 Copy

1.	Deng K, Zhang X, Liu Y, et al. Heterogeneity of paucigranulocytic asthma: a prospective cohort study with hierarchical cluster analysis. J Allergy Clin Immunol Pract, 2021, 9(6): 2344-2355.
2.	Demarche S, Schleich F, Henket M, et al. Detailed analysis of sputum and systemic inflammation in asthma phenotypes: are paucigranulocytic asthmatics really non-inflammatory?. BMC Pulm Med, 2016, 16: 46.
3.	Ntontsi P, Loukides S, Bakakos P, et al. Clinical, functional and inflammatory characteristics in patients with paucigranulocytic stable asthma: comparison with different sputum phenotypes. Allergy, 2017, 72(11): 1761-1767.
4.	Papaioannou AI, Fouka E, Ntontsi P, et al. Paucigranulocytic asthma: potential pathogenetic mechanisms, clinical features and therapeutic management. J Pers Med, 2022, 12(5): 850.
5.	Li M, Zhu WY, Wang C, et al. Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma. BMC Pulm Med, 2021, 21(1): 343.
6.	Steinke JW, Lawrence MG, Teague WG, et al. Bronchoalveolar lavage cytokine patterns in children with severe neutrophilic and paucigranulocytic asthma. J Allergy Clin Immunol, 2021, 147(2): 686-693.
7.	Zhou J, Zhou Y, Lin LH, et al. Association of polymorphisms in the promoter region of FCER1A gene with atopic dermatitis, chronic uticaria, asthma, and serum immunoglobulin E levels in a Han Chinese population. Hum Immunol, 2012, 73(3): 301-305.
8.	Potaczek DP, Michel S, Sharma V, et al. Different FCER1A polymorphisms influence IgE levels in asthmatics and non-asthmatics. Pediatr Allergy Immunol, 2013, 24(5): 441-449.
9.	Sharma V, Michel S, Gaertner V, et al. A role of FCER1A and FCER2 polymorphisms in IgE regulation. Allergy, 2014, 69(2): 231-236.
10.	Yang HJ, Zheng L, Zhang XF, et al. Association of the MS4A2 gene promoter C-109T or the 7th exon E237G polymorphisms with asthma risk: a meta-analysis. Clin Biochem, 2014, 47(7-8): 605-611.
11.	Sharma S, Ghosh B. Promoter polymorphism in the MS4A2 gene and asthma in the Indian population. Int Arch Allergy Immunol, 2009, 149(3): 208-218.
12.	Kim SH, Bae JS, Holloway JW, et al. A polymorphism of MS4A2 (–109T>C) encoding the β-chain of the high-affinity immunoglobulin E receptor (FcεR1β) is associated with a susceptibility to aspirin-intolerant asthma. Clin Exp Allergy, 2006, 36(7): 877-883.
13.	Cho SH, Kim YK, Oh HB, et al. Association of HLA-DRB1^07 and DRB1^04 to citrus red mite (Panonychus citri) and house dust mite sensitive asthma. Clin Exp Allergy, 2000, 30(11): 1568-1575.
14.	Vince N, Limou S, Daya M, et al. Association of HLA-DRB109:01* with tIgE levels among African-ancestry individuals with asthma. J Allergy Clin Immunol, 2020, 146(1): 147-155.
15.	Kim JH, Park BL, Cheong HS, et al. HLA-DRA polymorphisms associated with risk of nasal polyposis in asthmatic patients. Am J Rhinol Allergy, 2012, 26(1): 12-17.
16.	Muro M, Mondejar-López P, Moya-Quiles MR, et al. HLA-DRB1 and HLA-DQB1 genes on susceptibility to and protection from allergic bronchopulmonary aspergillosis in patients with cystic fibrosis. Microbiol Immunol, 2013, 57(3): 193-197.
17.	Madore AM, Vaillancourt VT, Asai Y, et al. HLA-DQB102* and DQB106:03P* are associated with peanut allergy. Eur J Hum Genet, 2013, 21(10): 1181-1184.
18.	Rezaieyazdi Z, Tavakkol-Afshari J, Esmaili E, et al. Association of HLA-DQB1 allelic sequence variation with susceptibility to systemic lupus erythematosus. Iran J Allergy Asthma Immunol, 2008, 7(2): 91-95.
19.	Karaca NE, Severcan EU, Guven B, et al. TNFRSF13B/TACI alterations in Turkish patients with common variable immunodeficiency and IgA deficiency. Avicenna J Med Biotechnol, 2018, 10(3): 192-195.
20.	Janzi M, Melén E, Kull I, et al. Rare mutations in TNFRSF13B increase the risk of asthma symptoms in Swedish children. Genes Immun, 2012, 13(1): 59-65.

1. Deng K, Zhang X, Liu Y, et al. Heterogeneity of paucigranulocytic asthma: a prospective cohort study with hierarchical cluster analysis. J Allergy Clin Immunol Pract, 2021, 9(6): 2344-2355.
2. Demarche S, Schleich F, Henket M, et al. Detailed analysis of sputum and systemic inflammation in asthma phenotypes: are paucigranulocytic asthmatics really non-inflammatory?. BMC Pulm Med, 2016, 16: 46.
3. Ntontsi P, Loukides S, Bakakos P, et al. Clinical, functional and inflammatory characteristics in patients with paucigranulocytic stable asthma: comparison with different sputum phenotypes. Allergy, 2017, 72(11): 1761-1767.
4. Papaioannou AI, Fouka E, Ntontsi P, et al. Paucigranulocytic asthma: potential pathogenetic mechanisms, clinical features and therapeutic management. J Pers Med, 2022, 12(5): 850.
5. Li M, Zhu WY, Wang C, et al. Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma. BMC Pulm Med, 2021, 21(1): 343.
6. Steinke JW, Lawrence MG, Teague WG, et al. Bronchoalveolar lavage cytokine patterns in children with severe neutrophilic and paucigranulocytic asthma. J Allergy Clin Immunol, 2021, 147(2): 686-693.
7. Zhou J, Zhou Y, Lin LH, et al. Association of polymorphisms in the promoter region of FCER1A gene with atopic dermatitis, chronic uticaria, asthma, and serum immunoglobulin E levels in a Han Chinese population. Hum Immunol, 2012, 73(3): 301-305.
8. Potaczek DP, Michel S, Sharma V, et al. Different FCER1A polymorphisms influence IgE levels in asthmatics and non-asthmatics. Pediatr Allergy Immunol, 2013, 24(5): 441-449.
9. Sharma V, Michel S, Gaertner V, et al. A role of FCER1A and FCER2 polymorphisms in IgE regulation. Allergy, 2014, 69(2): 231-236.
10. Yang HJ, Zheng L, Zhang XF, et al. Association of the MS4A2 gene promoter C-109T or the 7th exon E237G polymorphisms with asthma risk: a meta-analysis. Clin Biochem, 2014, 47(7-8): 605-611.
11. Sharma S, Ghosh B. Promoter polymorphism in the MS4A2 gene and asthma in the Indian population. Int Arch Allergy Immunol, 2009, 149(3): 208-218.
12. Kim SH, Bae JS, Holloway JW, et al. A polymorphism of MS4A2 (–109T>C) encoding the β-chain of the high-affinity immunoglobulin E receptor (FcεR1β) is associated with a susceptibility to aspirin-intolerant asthma. Clin Exp Allergy, 2006, 36(7): 877-883.
13. Cho SH, Kim YK, Oh HB, et al. Association of HLA-DRB1^*07 and DRB1^*04 to citrus red mite (Panonychus citri) and house dust mite sensitive asthma. Clin Exp Allergy, 2000, 30(11): 1568-1575.
14. Vince N, Limou S, Daya M, et al. Association of HLA-DRB1*09:01 with tIgE levels among African-ancestry individuals with asthma. J Allergy Clin Immunol, 2020, 146(1): 147-155.
15. Kim JH, Park BL, Cheong HS, et al. HLA-DRA polymorphisms associated with risk of nasal polyposis in asthmatic patients. Am J Rhinol Allergy, 2012, 26(1): 12-17.
16. Muro M, Mondejar-López P, Moya-Quiles MR, et al. HLA-DRB1 and HLA-DQB1 genes on susceptibility to and protection from allergic bronchopulmonary aspergillosis in patients with cystic fibrosis. Microbiol Immunol, 2013, 57(3): 193-197.
17. Madore AM, Vaillancourt VT, Asai Y, et al. HLA-DQB1*02 and DQB1*06:03P are associated with peanut allergy. Eur J Hum Genet, 2013, 21(10): 1181-1184.
18. Rezaieyazdi Z, Tavakkol-Afshari J, Esmaili E, et al. Association of HLA-DQB1 allelic sequence variation with susceptibility to systemic lupus erythematosus. Iran J Allergy Asthma Immunol, 2008, 7(2): 91-95.
19. Karaca NE, Severcan EU, Guven B, et al. TNFRSF13B/TACI alterations in Turkish patients with common variable immunodeficiency and IgA deficiency. Avicenna J Med Biotechnol, 2018, 10(3): 192-195.
20. Janzi M, Melén E, Kull I, et al. Rare mutations in TNFRSF13B increase the risk of asthma symptoms in Swedish children. Genes Immun, 2012, 13(1): 59-65.

Chinese Journal of Respiratory and Critical Care Medicine

Feature gene mining for prediction of paucigranulocytic asthma

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