Immune-related key genes CCK, CRABP2, and CXCL6 in asthma: validation through multi-dataset bioinformatics analysis and mice_Chinese Journal of Respiratory and Critical Care Medicine

Authors：

GAO Jialin ¹ , YU Haolu ¹ , SANG Jiajia ² , HAO Feng ¹ ,  HU Jun ¹

1. Nanjing University of Chinese Medicines, Nanjing, Jiangsu 210023, P. R. China;
2. Affiliated Hospital of Nanjing University of Chinese Medicine/Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu 210029, P. R. China;

Corresponding?author：

HU Jun, Email: junhu@njucm.edu.cn

Keywords：

Asthma; bioinformatics analysis; mice; cholecystokinin; cellular retinol binding protein 2; C-X-C motif chemokine ligand 6

DOI：

10.7507/1671-6205.202508008

Video：

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Objective To identify immune-related genes critical to asthma pathogenesis and construct a clinically applicable diagnostic model based on immune-gene signatures. Methods We first intersected 1639 immune-related genes (IRGs) with differentially expressed genes (DEGs) from the discovery dataset (GSE43696, n=128) to obtain differentially expressed IRGs (DE-IRGs). Expression stability was confirmed in the independent validation dataset GSE64913 (n=62). Least absolute shrinkage and selection operator (LASSO) regression and support-vector-machine (SVM) recursive feature elimination were applied to rank genes, followed by overlap with key modules identified by weighted gene co-expression network analysis (WGCNA). A logistic-regression diagnostic model was constructed using the optimal gene set, and its functional landscape was interrogated by gene-set enrichment analysis (GSEA). Finally, the model and the selected genes were cross-validated in ten transcriptomic cohorts encompassing eight distinct asthma phenotypes (total n=1137) and in lung tissue from an ovalbumin (OVA)-induced murine asthma model. Results A total of 38 DE-IRGs were identified. Among them, cholecystokinin (CCK), cellular retinol binding protein 2 (CRABP2) and C-X-C motif chemokine ligand 6 (CXCL6) were involved in immune-related processes and signaling pathways, which were of great significance in the diagnosis of asthma. The logistic regression diagnostic model based on three genes has shown good universality in various asthma samples. These three genes have also been verified to a certain extent in the lung tissues of OVA mice. Conclusion Integrative bioinformatics and in vivo validation establish CCK, CRABP2, and CXCL6 as a compact, biologically grounded immune-gene signature for asthma diagnosis and mechanistic investigation.

Citation： GAO Jialin, YU Haolu, SANG Jiajia, HAO Feng, HU Jun. Immune-related key genes CCK, CRABP2, and CXCL6 in asthma: validation through multi-dataset bioinformatics analysis and mice. Chinese Journal of Respiratory and Critical Care Medicine, 2026, 25(1): 9-20. doi: 10.7507/1671-6205.202508008 Copy

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34.	Panganiban RAM, Yang Z, Sun M, et al. Antagonizing cholecystokinin A receptor in the lung attenuates obesity-induced airway hyperresponsiveness. Nat Commun, 2023, 14(1): 47.
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37.	Andreev D, Liu M, Kachler K, et al. Regulatory eosinophils induce the resolution of experimental arthritis and appear in remission state of human rheumatoid arthritis. Ann Rheum Dis, 2021, 80(4): 451-468.
38.	Pacholewska A, Marti E, Leeb T, et al. LPS-induced modules of co-expressed genes in equine peripheral blood mononuclear cells. BMC Genomics, 2017, 18(1): 34.
39.	Asayama K, Kobayashi T, D'Alessandro-Gabazza CN, et al. Protein S protects against allergic bronchial asthma by modulating Th1/Th2 balance. Allergy, 2020, 75(9): 2267-2278.
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1. Cote A, Russell RJ, Boulet L, et al. Managing chronic cough due to asthma and NAEB in Adults and adolescents: CHEST Guideline and Expert Panel Report. Chest, 2020, 158(1): 68-96.
2. Kaplan A, van Boven JFM, Ryan D, et al. GINA 2020: Potential impacts, opportunities, and challenges for primary Care. J Allergy Clin Immunol Pract, 2021, 9(4): 1516-1519.
3. Hakansson KEJ, Backer V, Ulrik CS. Socioeconomic biases in asthma control and specialist referral of possible severe asthma. Eur Respir J, 2021, 58(6): 2100741.
4. Corren J, Katelaris CH, Castro M, et al. Effect of exacerbation history on clinical response to dupilumab in moderate-to-severe uncontrolled asthma. Eur Respir J, 2021, 58(4): 2004498.
5. Wills TA, Soneji SS, Choi K, et al. E-cigarette use and respiratory disorders: an integrative review of converging evidence from epidemiological and laboratory studies. Eur Respir J, 2021, 57(1): 1901815.
6. Burte E, Leynaert B, Marcon A, et al. Long-term air pollution exposure is associated with increased severity of rhinitis in 2 European cohorts. J Allergy Clin Immunol, 2020, 145(3): 834-842.
7. Brokamp C, Brandt E B, Ryan PH. Assessing exposure to outdoor air pollution for epidemiological studies: Model-based and personal sampling strategies. J Allergy Clin Immunol, 2019, 143(6): 2002-2006.
8. Camoretti-Mercado B, Lockey RF. Airway smooth muscle pathophysiology in asthma. J Allergy Clin Immunol, 2021, 147(6): 1983-1995.
9. Liu G, Philp A M, Corte T, et al. Therapeutic targets in lung tissue remodelling and fibrosis. Pharmacol Ther, 2021, 225: 107839.
10. Patel DF, Gaggar A, Blalock JE, et al. Response to comment on "An extracellular matrix fragment drives epithelial remodeling and airway hyperresponsiveness". Sci Transl Med, 2019, 11(497): eaaw0462.
11. Nobs SP, Pohlmeier L, Li F, et al. GM-CSF instigates a dendritic cell-T-cell inflammatory circuit that drives chronic asthma development. J Allergy Clin Immunol, 2021, 147(6): 2118-2133.
12. Winter NA, Qin L, Gibson PG, et al. Sputum mast cell/basophil gene expression relates to inflammatory and clinical features of severe asthma. J Allergy Clin Immunol, 2021, 148(2): 428-438.
13. Boyce JA. Aspirin sensitivity: Lessons in the regulation (and dysregulation) of mast cell function. J Allergy Clin Immunol, 2019, 144(4): 875-881.
14. Bayo J, Fiore EJ, Dominguez L M, et al. Bioinformatic analysis of RHO family of GTPases identifies RAC1 pharmacological inhibition as a new therapeutic strategy for hepatocellular carcinoma. Gut, 2021, 70(7): 1362-1374.
15. Tu H, Wu M, Huang W, et al. Screening of potential biomarkers and their predictive value in early stage non-small cell lung cancer: a bioinformatics analysis. Transl Lung Cancer Res, 2019, 8(6): 797-807.
16. Lee J, Hyon J, Min JY, et al. Mitochondrial carnitine palmitoyltransferase 2 is involved in N(epsilon)-(carboxymethyl)-lysine-mediated diabetic nephropathy. Pharmacol Res, 2020, 152: 104600.
17. Huang Y, Liu H, Zuo L, et al. Key genes and co-expression modules involved in asthma pathogenesis. PeerJ, 2020, 8: e8456.
18. He L, Xu F, Zhan X, et al. Identification of critical genes associated with the development of asthma by co-expression modules construction. Mol Immunol, 2020, 123: 18-25.
19. Ritchie ME, Phipson B, Wu D, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res, 2015, 43(7): e47.
20. Shi H, Liu S, Chen J, et al. Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure. Genomics, 2019, 111(6): 1839-1852.
21. Fishburn FA, Hlutkowsky CO, Bemis LM, et al. Irritability uniquely predicts prefrontal cortex activation during preschool inhibitory control among all temperament domains: a LASSO approach. Neuroimage, 2019, 184: 68-77.
22. Li Q, Wen Z, He B. Adaptive kernel value caching for SVM Training. IEEE Trans Neural Netw Learn Syst, 2020, 31(7): 2376-2386.
23. Zhang X, Liu S. RBPPred: predicting RNA-binding proteins from sequence using SVM. Bioinformatics, 2017, 33(6): 854-862.
24. Niemira M, Collin F, Szalkowska A, et al. Molecular signature of subtypes of non-small-cell lung cancer by large-scale transcriptional profiling: identification of key modules and genes by weighted gene co-expression network analysis (WGCNA). Cancers (Basel), 2019, 12(1): 37.
25. Pu L, Wang M, Li K, et al. Identification micro-RNAs functional modules and genes of ischemic stroke based on weighted gene co-expression network analysis (WGCNA). Genomics, 2020, 112(4): 2748-2754.
26. Sachs M C. plotROC: A Tool for Plotting ROC Curves. J Stat Softw, 2017, 79: 2.
27. Liu C, He Y, Luo J. Application of chest CT imaging feature model in distinguishing squamous cell carcinoma and adenocarcinoma of the lung. Cancer Manag Res, 2024, 16: 547-557.
28. Wu T, Hu E, Xu S, et al. clusterProfiler 4. 0: a universal enrichment tool for interpreting omics data. Innovation (Camb), 2021, 2(3): 100141.
29. Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res, 2003, 13(11): 2498-2504.
30. Seeliger D, de Groot BL. Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J Comput Aided Mol Des, 2010, 24(5): 417-422.
31. Guo Y, Mishra A, Howland E, et al. Platelet-derived Wnt antagonist Dickkopf-1 is implicated in ICAM-1/VCAM-1-mediated neutrophilic acute lung inflammation. Blood, 2015, 126(19): 2220-2229.
32. Movassagh H, Koussih L, Shan L, et al. The regulatory role of semaphorin 3E in allergic asthma. Int J Biochem Cell Biol, 2019, 106: 68-73.
33. Tatari N, Movassagh H, Shan L, et al. Semaphorin 3E inhibits house dust mite-induced angiogenesis in a mouse model of allergic asthma. Am J Pathol, 2019, 189(4): 762-772.
34. Panganiban RAM, Yang Z, Sun M, et al. Antagonizing cholecystokinin A receptor in the lung attenuates obesity-induced airway hyperresponsiveness. Nat Commun, 2023, 14(1): 47.
35. Morita H, Kubo T, Ruckert B, et al. Induction of human regulatory innate lymphoid cells from group 2 innate lymphoid cells by retinoic acid. J Allergy Clin Immunol, 2019, 143(6): 2190-2201.
36. Chen F, Shao F, Hinds A, et al. Retinoic acid signaling is essential for airway smooth muscle homeostasis. JCI Insight, 2018, 3(16): e120398.
37. Andreev D, Liu M, Kachler K, et al. Regulatory eosinophils induce the resolution of experimental arthritis and appear in remission state of human rheumatoid arthritis. Ann Rheum Dis, 2021, 80(4): 451-468.
38. Pacholewska A, Marti E, Leeb T, et al. LPS-induced modules of co-expressed genes in equine peripheral blood mononuclear cells. BMC Genomics, 2017, 18(1): 34.
39. Asayama K, Kobayashi T, D'Alessandro-Gabazza CN, et al. Protein S protects against allergic bronchial asthma by modulating Th1/Th2 balance. Allergy, 2020, 75(9): 2267-2278.
40. Li X, Hawkins GA, Ampleford EJ, et al. Genome-wide association study identifies TH1 pathway genes associated with lung function in asthmatic patients. J Allergy Clin Immunol, 2013, 132(2): 313-320.
41. Danan LM, Yu Z, Hoffhines AJ, et al. Mass spectrometric kinetic analysis of human tyrosylprotein sulfotransferase-1 and -2. J Am Soc Mass Spectrom, 2008, 19(10): 1459-1466.

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Chinese Journal of Respiratory and Critical Care Medicine

Immune-related key genes CCK, CRABP2, and CXCL6 in asthma: validation through multi-dataset bioinformatics analysis and mice

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