A Heuristic Approach to Analysis of the Genetic Susceptibility Profile in Patients Affected by Airway Allergies
Abstract
:1. Introduction
2. Materials and Methods
2.1. Patients and Controls
2.2. SNP Genotyping SNP Molecular Typing
2.3. Statistical Analysis
2.4. Heuristic Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Voskamp, A.L.; Kormelink, T.G.; van Wijk, R.G.; Hiemstra, P.S.; Taube, C.; de Jong, E.C.; Smits, H.H. Modulating local airway immune responses to treat allergic asthma: Lessons from experimental models and human studies. Semin. Immunopathol. 2020, 42, 95–110. [Google Scholar] [CrossRef]
- Gour, N.; Wills-Karp, M. IL-4 and IL-13 signaling in allergic airway disease. Cytokine 2015, 75, 68–78. [Google Scholar] [CrossRef] [PubMed]
- Luo, W.; Hu, J.; Xu, W.; Dong, J. Distinct spatial and temporal roles for Th1, Th2, and Th17 cells in asthma. Front. Immunol. 2022, 13, 974066. [Google Scholar] [CrossRef]
- Raundhal, M.; Morse, C.; Khare, A.; Oriss, T.B.; Milosevic, J.; Trudeau, J.; Huff, R.; Pilewski, J.; Holguin, F.; Kolls, J.; et al. High IFN-γ and low SLPI mark severe asthma in mice and humans. J. Clin. Investig. 2015, 125, 3037–3050. [Google Scholar] [CrossRef] [PubMed]
- Wisniewski, J.A.; Muehling, L.M.; Eccles, J.D.; Capaldo, B.J.; Agrawal, R.; Shirley, D.A.; Patrie, J.T.; Workman, L.J.; Schuyler, A.J.; Lawrence, M.G.; et al. TH1 signatures are present in the lower airways of children with severe asthma, regardless of allergic status. J. Allergy Clin. Immunol. 2018, 141, 2048–2060. [Google Scholar] [CrossRef] [PubMed]
- Camiolo, M.J.; Kale, S.L.; Oriss, T.B.; Gauthier, M.; Ray, A. Immune responses and exacerbations in severe asthma. Curr. Opin. Immunol. 2021, 72, 34–42. [Google Scholar] [CrossRef]
- Maspero, J.; Adir, Y.; Al-Ahmad, M.; Celis-Preciado, C.A.; Colodenco, F.D.; Giavina-Bianchi, P.; Lababidi, H.; Ledanois, O.; Mahoub, B.; Perng, D.W.; et al. Type 2 inflammation in asthma and other airway diseases. ERJ Open Res. 2022, 8, 00576-2021. [Google Scholar] [CrossRef]
- Li, X.; Hawkins, G.A.; Ampleford, E.J.; Moore, W.C.; Li, H.; Hastie, A.T.; Howard, T.D.; Boushey, H.A.; Busse, W.W.; Calhoun, W.J.; et al. Genome-wide association study identifies TH1 pathway genes associated with lung function in asthmatic patients. J. Allergy Clin. Immunol. 2013, 132, 313–320.e15. [Google Scholar] [CrossRef]
- Han, Y.Y.; Celedón, J.C.; Forno, E. Serum α-Klotho level, lung function, airflow obstruction and inflammatory markers in US adults. ERJ Open Res. 2023, 9, 00471-2023. [Google Scholar] [CrossRef]
- Brandao-Rangel, M.A.R.; Moraes-Ferreira, R.; Silva-Reis, A.; Souza-Palmeira, V.H.; Almeida, F.M.; da Silva Olimpio, F.R.; Oliveira, C.R.; Damaceno-Rodrigues, N.R.; Pesquero, J.B.; Martin, L.; et al. Aerobic physical training reduces severe asthma phenotype involving kinins pathway. Mol. Biol. Rep. 2024, 51, 499. [Google Scholar] [CrossRef]
- Lal, D.; Brar, T.; Ramkumar, S.P.; Li, J.; Kato, A.; Zhang, L. Genetics and epigenetics of chronic rhinosinusitis. J. Allergy Clin. Immunol. 2023, 151, 848–868. [Google Scholar] [CrossRef] [PubMed]
- Augustine, T.; Al-Aghbar, M.A.; Al-Kowari, M.; Espino-Guarch, M.; van Panhuys, N. Asthma and the Missing Heritability Problem: Necessity for Multiomics Approaches in Determining Accurate Risk Profiles. Front. Immunol. 2022, 13, 822324. [Google Scholar] [CrossRef] [PubMed]
- Li, J.; Zhang, X.; Gao, Y.; Jiao, J.; Wang, C.; Zhang, Y.; Zhang, L. Signatures of positive selection are enriched in genome-wide associated allergy alleles. Allergy 2022, 77, 3134–3137. [Google Scholar] [CrossRef] [PubMed]
- Kottyan, L.C.; Weirauch, M.T.; Rothenberg, M.E. Making it big in allergy. J. Allergy Clin. Immunol. 2015, 135, 43–45. [Google Scholar] [CrossRef]
- Dinu, V.; Zhao, H.; Miller, P.L. Integrating domain knowledge with statistical and data mining methods for high-density genomic SNP disease association analysis. J. Biomed. Inform. 2007, 40, 750–760. [Google Scholar] [CrossRef]
- Agrawal, R.; Imielinski, T.; Swami, A. Mining Association Rules Between Sets of Items in Large Databases. In Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, Washington, DC, USA, 26–28 May 1993; ACM Press: New York, NY, USA, 1993; pp. 207–216. [Google Scholar] [CrossRef]
- Liu, S.; Li, T.; Liu, J. Interleukin-4 rs2243250 polymorphism is associated with asthma among Caucasians and related to atopic asthma. Cytokine 2012, 59, 364–369. [Google Scholar] [CrossRef]
- Zhu, N.; Gong, Y.; Chen, X.D.; Zhang, J.; Long, F.; He, J.; Xia, J.W.; Dong, L. Association between the polymorphisms of interleukin-4, the interleukin-4 receptor gene and asthma. Chin. Med. J. 2013, 12, 2943–2951. [Google Scholar]
- Scola, L.; Giarratana, R.M.; Marinello, V.; Cancila, V.; Pisano, C.; Ruvolo, G.; Frati, G.; Lio, D.; Balistreri, C.R. Polymor-phisms of Pro-Inflammatory IL6 and IL-1β Cytokines in Ascending Aortic Aneurysms as Genetic Modifiers and Predictive and Prognostic Biomarkers. Biomolecules 2021, 11, 943. [Google Scholar] [CrossRef]
- Accardo Palumbo, A.; Forte, G.I.; Pileri, D.; Vaccarino, L.; Conte, F.; D’Amelio, L.; Palmeri, M.; Triolo, A.; D’Arpa, N.; Scola, L.; et al. Analysis of IL-6, IL-10 and IL-17 genetic polymorphisms as risk factors for sepsis development in burned patients. Burns 2012, 38, 208–213. [Google Scholar] [CrossRef]
- Balistreri, C.R.; Ammoscato, C.L.; Scola, L.; Fragapane, T.; Giarratana, R.M.; Lio, D.; Piccione, M. Susceptibility to Heart Defects in Down Syndrome Is Associated with Single Nucleotide Polymorphisms in HAS 21 Interferon Receptor Cluster and VEGFA Genes. Genes 2020, 11, 1428. [Google Scholar] [CrossRef]
- Omraninava, M.; Eslami, M.M.; Aslani, S.; Razi, B.; Imani, D.; Feyzinia, S. Interleukin 13 gene polymorphism and susceptibility to asthma: A meta-regression and meta-analysis. Eur. Ann. Allergy Clin. Immunol. 2022, 54, 150–167. [Google Scholar] [CrossRef] [PubMed]
- Scola, L.; Ferraro, D.; Sanfilippo, G.L.; De Grazia, S.; Lio, D.; Giammanco, G.M. Age and Cytokine Gene Variants Modulate the Immunogenicity and Protective Effect of SARS-CoV-2 mRNA-Based Vaccination. Vaccines 2023, 11, 413. [Google Scholar] [CrossRef] [PubMed]
- Álvarez, G.I.; Hernández Del Pino, R.E.; Barbero, A.M.; Estermann, M.A.; Celano, J.; Musella, R.M.; Palmero, D.J.; García, V.E.; Pasquinelli, V. Association of IFN-γ +874 A/T SNP and hypermethylation of the -53 CpG site with tuberculosis susceptibility. Front. Cell Infect. Microbiol. 2023, 13, 1080100. [Google Scholar] [CrossRef] [PubMed]
- Chan, M.A.; Gigliotti, N.M.; Meng, J.; Rosenwasser, L.J. Asthma-related SNP in FCER2 is associated with increased expression of IL-4R on human B cells. Int. J. Immunogenet. 2011, 38, 533–538. [Google Scholar] [CrossRef]
- Paroni, G.; Seripa, D.; Panza, F.; Addante, F.; Copetti, M.; D’Onofrio, G.; Pellegrini, F.; Fontana, L.; Pilotto, A. Klotho locus, metabolic traits, and serum hemoglobin in hospitalized older patients: A genetic association analysis. Age 2012, 34, 949–968. [Google Scholar] [CrossRef]
- Friedman, D.J.; Afkarian, M.; Tamez, H.; Bhan, I.; Isakova, T.; Wolf, M.; Ankers, E.; Ye, J.; Tonelli, M.; Zoccali, C.; et al. Klotho variants and chronic hemodialysis mortality. J. Bone Miner. Res. 2009, 24, 1847–1855. [Google Scholar] [CrossRef]
- Di Lorenzo, G.; Leto-Barone, M.S.; La Piana, S.; La Porta, G.; Montalto, G. Assessment of a qualitative serological assay to screen for allergic sensitization in elderly subjects. Allergy Asthma Proc. 2013, 34, e9–e13. [Google Scholar] [CrossRef] [PubMed]
- Asero, R.; Aruanno, A.; Bresciani, M.; Bru-sca, I.; Carollo, M.; Cecchi, L.; Cortellini, G.; Deleonardi, G.; Farsi, A.; Ferrarini, E.; et al. Evaluation of two commercial peach extracts for skin prick testing in the diagnosis of hypersensitivity to lipid trans-fer protein. A multicenter study. Eur. Ann. Allergy Clin. Immunol. 2021, 53, 168–170. [Google Scholar] [CrossRef] [PubMed]
- Available online: http://ifbg.org.ua/~files/ccu/ABI_Prism_7300_Real_Time_PCR_System_tech_spec.pdf (accessed on 15 April 2024).
- Solé, X.; Guinó, E.; Valls, J.; Iniesta, R.; Moreno, V. SNPStats: A web tool for the analysis of association studies. Bioinformatics 2006, 22, 1928–1929. [Google Scholar] [CrossRef]
- Available online: https://pypi.org/project/efficient-apriori/ (accessed on 15 April 2024).
- Moshkov, M.; Zielosko, B.; Tetteh, E.T. Selected Data Mining Tools for Data Analysis in Distributed Environment. Entropy 2022, 24, 1401. [Google Scholar] [CrossRef]
- Schoos, A.M. Atopic diseases-Diagnostics, mechanisms, and exposures. Pediatr. Allergy Immunol. 2024, 35, e14198. [Google Scholar] [CrossRef]
- Budu-Aggrey, A.; Kilanowski, A.; Sobczyk, M.K.; 23andMe Research Team; Shringarpure, S.S.; Mitchell, R.; Reis, K.; Reigo, A.; Estonian Biobank Research Team; Mägi, R.; et al. European and multi-ancestry genome-wide association meta-analysis of atopic dermatitis highlights importance of systemic immune regulation. Nat. Commun. 2023, 14, 6172. [Google Scholar] [CrossRef] [PubMed]
- Deka, H.; Siddique, M.A.; Ahmed, S.J.; Mahanta, P.; Mahanta, P. Evaluation of IL-4 and IL-13 Single Nucleotide Polymorphisms and Their Association with Childhood Asthma and Its Severity: A Hospital-Based Case-Control Study. Cureus 2024, 16, e57465. [Google Scholar] [CrossRef]
- Bai, S.; Lu, J.; Hua, L.; Liu, Q.; Chen, M.; Gu, Y.; Zhang, J.; Ma, D.; Bao, Y. Prediction of asthma using a four-locus gene model including IL13, IL4, FCER1B, and ADRB2 in children of Kazak nationality. Ital. J. Pediatr. 2023, 49, 162. [Google Scholar] [CrossRef] [PubMed]
- Jiang, F.; Yan, A. IL-4 rs2243250 polymorphism associated with susceptibility to allergic rhinitis: A meta-analysis. Biosci. Rep. 2021, 41, BSR20210522. [Google Scholar] [CrossRef] [PubMed]
- Kousha, A.; Mahdavi Gorabi, A.; Forouzesh, M.; Hosseini, M.; Alexander, M.; Imani, D.; Razi, B.; Mousavi, M.J.; Aslani, S.; Mikaeili, H. Interleukin 4 gene polymorphism (-589C/T) and the risk of asthma: A meta-analysis and met-regression based on 55 studies. BMC Immunol. 2020, 21, 55. [Google Scholar] [CrossRef]
- Li, L.; Li, Y.; Zeng, X.C.; Li, J.; Du, X.Y. Role of interleukin-4 genetic polymorphisms and environmental factors in the risk of asthma in children. Gen. Mol. Res. 2016, 15, 10.4238/gmr15048873. [Google Scholar] [CrossRef]
- Movahedi, M.; Amirzargar, A.A.; Nasiri, R.; Hirbod-Mobarakeh, A.; Farhadi, E.; Tavakol, M.; Behniafard, N.; Ansaripour, B.; Moradi, B.; Zare, A.; et al. Gene polymorphisms of Interleukin-4 in allergic rhinitis and its association with clinical phenotypes. Am. J. Otolaryngol. 2013, 34, 676–681. [Google Scholar] [CrossRef]
- Ying, X.; Zhang, R.; Yu, S.; Wu, J.; Wang, H. Association of interleukin-13 SNP rs1800925 with allergic rhinitis risk: A meta-analysis based on 1,411 cases and 3169 controls. Gene 2012, 506, 179–183. [Google Scholar] [CrossRef]
- Palaniyandi, S.; Liu, X.; Periasamy, S.; Ma, A.; Tang, J.; Jenkins, M.; Tuo, W.; Song, W.; Keegan, A.D.; Conrad, D.H.; et al. Inhibition of CD23-mediated IgE transcytosis suppresses the initiation and development of allergic airway inflammation.Inhibition of CD23-mediated IgE transcytosis suppresses the initiation and development of allergic airway inflammation. Mucosal Immunol. 2015, 8, 1262–1274. [Google Scholar] [CrossRef]
- Li, F.; Xie, X.; Li, S.; Ke, R.; Zhu, B.; Yang, L.; Li, M. Interleukin-6 gene -174G/C polymorphism and bronchial asthma risk: A meta-analysis. Int. J. Clin. Exp. Med. 2015, 8, 12601–12608. [Google Scholar] [PubMed]
- Settin, A.; Zedan, M.; Farag, M.; Ezz El Regal, M.; Osman, E. Gene polymorphisms of IL-6(-174) G/C and IL-1Ra VNTR in asthmatic children. Indian. J. Pediatr. 2008, 75, 1019–1023. [Google Scholar] [CrossRef]
- Koefoed, H.J.L.; Vonk, J.M.; Koppelman, G.H. Predicting the course of asthma from childhood until early adulthood. Curr. Opin. Allergy Clin. Immunol. 2022, 22, 115–122. [Google Scholar] [CrossRef] [PubMed]
- Peters, M.C.; McGrath, K.W.; Hawkins, G.A.; Hastie, A.T.; Levy, B.D.; Israel, E.; Phillips, B.R.; Mauger, D.T.; Comhair, S.A.; Erzurum, S.C.; et al. Plasma interleukin-6 concentrations, metabolic dysfunction, and asthma severity: A cross-sectional analysis of two co-horts. Lancet Respir. Med. 2016, 4, 574–584. [Google Scholar] [CrossRef]
- Imani, D.; Dashti, N.; Parvari, A.; Shafiekhani, S.; Alebrahim, F.; Razi, B.; Makoui, M.H.; Motallebnezhad, M.; Aslani, S.; Aliyu, M. Interleukin-10 Gene Promoter Polymorphisms and Susceptibility to Asthma: Systematic Review and Meta-analysis. Biochem. Genet. 2021, 59, 1089–1115. [Google Scholar] [CrossRef]
- Ahn, D.; Prince, A. Participation of the IL-10RB Related Cytokines, IL-22 and IFN-λ in Defense of the Airway Mucosal Barrier. Front. Cell Infect. Microbiol. 2020, 10, 300. [Google Scholar] [CrossRef] [PubMed]
- Bali, V.; Bebok, Z. De-coding mechanisms by which silent codon changes influence protein biogenesis and function. Int. J. Biochem. Cell biol. 2016, 64, 58–74. [Google Scholar] [CrossRef]
- Keating, S.M.; Waltemath, D.; König, M.; Zhang, F.; Dräger, A.; Chaouiya, C.; Bergmann, F.T.; Finney, A.; Gillespie, C.S.; Helikar, T.; et al. SBML Level 3: An extensible format for the exchange and reuse of biological models. Mol. Syst. Biol. 2020, 16, e9110. [Google Scholar] [CrossRef]
- Reigada-Rivera, M.L.; Lozano, C.S.; Rodilla, E.M.; García-Sánchez, A.; García-Solaesa, V.; Toledano, F.L.; González, I.D.; Isidoro-García, M. Polymorphisms in Human IL4, IL10, and TNF Genes Are Associated with an Increased Risk of Developing NSAID-Exacerbated Respiratory Disease. Genes 2022, 13, 605. [Google Scholar] [CrossRef]
- de Guia, R.M.; Echavez, M.D.; Gaw, E.L.; Gomez, M.R.; Lopez, K.A.; Mendoza, R.C.; Rapsing, J.M.; Retreta, D.P.; Tubog, C.M.; Ventolero, M.H.; et al. Multifactor-dimensionality reduction reveals interaction of important gene variants involved in allergy. Int. J. Immunogenet. 2015, 42, 182–189. [Google Scholar] [CrossRef]
- Daley, D.; Lemire, M.; Akhabir, L.; Chan-Yeung, M.; He, J.Q.; McDonald, T.; Sandford, A.; Stefanowicz, D.; Tripp, B.; Zamar, D.; et al. Analyses of associations with asthma in four asthma population samples from Canada and Australia. Hum. Genet. 2009, 125, 445–459. [Google Scholar] [CrossRef] [PubMed]
- Hijikata, M.; Shojima, J.; Matsushita, I.; Tokunaga, K.; Ohashi, J.; Hang, N.T.; Horie, T.; Sakurada, S.; Hoang, N.P.; Thuong, P.H.; et al. Association of IFNGR2 gene polymorphisms with pulmonary tuberculosis among the Vietnamese. Hum. Genet. 2012, 131, 675–682. [Google Scholar] [CrossRef] [PubMed]
- Krick, S.; Grabner, A.; Baumlin, N.; Yanucil, C.; Helton, S.; Grosche, A.; Sailland, J.; Geraghty, P.; Viera, L.; Russell, D.W.; et al. Fibroblast growth factor 23 and Klotho contribute to airway inflammation. Eur. Respir. J. 2018, 52, 1800236. [Google Scholar] [CrossRef] [PubMed]
- Garth, J.; Easter, M.; Skylar Harris, E.; Sailland, J.; Kuenzi, L.; Chung, S.; Dennis, J.S.; Baumlin, N.; Adewale, A.T.; Rowe, S.M.; et al. The Effects of the Anti-aging Protein Klotho on Mucociliary Clearance. Front. Med. 2020, 6, 339. [Google Scholar] [CrossRef]
Gene | SNP | Chr Location | Major Allele | Minor Allele | Minor Allele Functional Association | Ref. |
---|---|---|---|---|---|---|
IL-4 | rs2243250 | 5:132673462 | C | T | Upregulation of gene expression | [17] |
IL-4R | rs1801275 | 16:27363079 | A | G | Enhanced IL-4 receptor function | [18] |
IL-6 | rs1800795 | 7:22727026 | G | C | Reduced production of IL-6 | [19] |
IL-10 | rs1800896 | 1:206773552 | A | G | Increased production of IL-10 | [20] |
rs1800872 | 1:206773062 | C | A | Reduced production of IL-10 | ||
IL-10RB | rs2834167 | 21:33268483 | A | G | Higher expression of IL-10Rβ | [21] |
IL-13 | rs1800925 | 5:132657117 | C | T | Increased production of IL-13 | [22] |
IL-18 | rs187238 | 11:112164265 | G | C | Increased IL-18 gene transcription | [23] |
IFNγ | rs2430561 | 12:68158742 | T | A | Lowered IFN-γ production | [24] |
IFNγR2 | rs2834213 | 21:3342060 | A | G | Hyper responsiveness to Type II IFN | [21] |
CD23 | rs2228137 | 19:7698362 | C | T | Increased activity of the receptor | [25] |
Klotho | rs577912 | 13:33036014 | C | A | Increased Klotho expression | [26,27] |
rs564481 | 13:33060846 | C | T | mRNA stability modification |
Demographic and Clinical Characteristics | Allergy | Controls | p | ||
---|---|---|---|---|---|
N. | % | N. | % | ||
Age, mean ± SD | 51.03 ± 10.01 | 49.78 ± 12.32 | 0.227 a | ||
Women | 167 | 54.22 | 117 | 57.07 | 0.527 b |
Clinical features of allergic patients | |||||
Rhinitis | 109 | 35.39 | 0 | 0 | -- |
Rhinitis and asthma | 93 | 30.19 | 0 | 0 | -- |
Asthma | 106 | 34.41 | 0 | 0 | -- |
Positive familiarity | 91 | 29.54 | 0 | 0 | -- |
Positive prick test for ≥3 allergens | 122 | 39.62 | -- | -- | -- |
Atopy | 172 | 55.84 | 0 | 0 | -- |
GENE | SNP | Alleles/ Genotypes | Controls | Allergy | OR (95% CI) | 1 p-Value | ||
---|---|---|---|---|---|---|---|---|
Nr | Freq. | Nr | Freq. | |||||
IL-4 | rs2243250 | C | 363 | 0.89 | 560 | 0.91 | 1.29(0.86–1.95) | 0.243 |
T | 47 | 0.11 | 56 | 0.09 | ||||
C/C | 162 | 0.79 | 259 | 0.84 | 1.40 (0.89–2.21) | 0.159 | ||
C/T | 39 | 0.19 | 42 | 0.14 | 0.67 (0.42–1.08) | 0.264 | ||
T/T | 4 | 0.02 | 7 | 0.02 | 1.17 (0.34–4.05) | 1 | ||
IL-4R | rs1801275 | A | 330 | 0.8 | 507 | 0.82 | 1.13 (0.82–1.55) | 0.461 |
G | 80 | 0.2 | 109 | 0.18 | ||||
A/A | 135 | 0.66 | 210 | 0.68 | 1.11 (0.76–1.62) | 0.631 | ||
A/G | 60 | 0.29 | 87 | 0.28 | 0.93 (0.63–1.38) | 0.733 | ||
G/G | 10 | 0.05 | 11 | 0.04 | 0.72 (0.30–1.73) | 0.499 | ||
IL-6 | rs1800795 | G | 278 | 0.68 | 484 | 0.79 | 1.74 (1.31–2.31) | 0.0001 |
C | 132 | 0.32 | 132 | 0.21 | ||||
G/G | 98 | 0.48 | 201 | 0.65 | 2.05 (1.43–2.94) | 0.0001 | ||
G/C | 82 | 0.4 | 82 | 0.27 | 0.49 (0.33–0.72) | 0.0019 | ||
C/C | 25 | 0.12 | 25 | 0.08 | 0.64 (0.35–1.14) | 0.132 | ||
IL-10 | rs1800896 | A | 259 | 0.63 | 426 | 0.69 | 1.31 (1.00–1.70) | 0.049 |
G | 151 | 0.37 | 190 | 0.31 | ||||
A/A | 79 | 0.38 | 147 | 0.48 | 1.46 (1.02–2.09) | 0.046 | ||
A/G | 101 | 0.49 | 132 | 0.43 | 0.70 (0.48–1.02) | 0.114 | ||
G/G | 25 | 0.12 | 29 | 0.09 | 0.63 (0.34–1.14) | 0.378 | ||
rs1800872 | C | 292 | 0.71 | 424 | 0.69 | 0.89 (0.68–1.17) | 0.445 | |
A | 118 | 0.29 | 192 | 0.31 | ||||
C/C | 101 | 0.49 | 144 | 0.47 | 0.90 (0.64.1.29) | 0.589 | ||
C/A | 90 | 0.44 | 136 | 0.44 | 1.06 (0.73–1.53) | 0.623 | ||
A/A | 14 | 0.07 | 28 | 0.09 | 1.40 (0.70–2.80) | 0.413 | ||
IL-10RB | rs2834167 | A | 301 | 0.73 | 285 | 0.46 | 0.31 (0.24–0.41) | <0.0001 |
G | 109 | 0.27 | 331 | 0.54 | ||||
A/A | 108 | 0.53 | 79 | 0.26 | 0.49 (0.39–0.61) | <0.0001 | ||
A/G | 85 | 0.41 | 127 | 0.41 | 2.06 (1.38–3.07) | <0.0001 | ||
G/G | 12 | 0.06 | 102 | 0.33 | 5.66 (3.19–10.02) | <0.0001 | ||
IL-13 | rs1800925 | C | 294 | 0.72 | 502 | 0.81 | 1.74 (1.29–2.34) | 0.0003 |
T | 116 | 0.28 | 114 | 0.19 | ||||
C/C | 105 | 0.51 | 204 | 0.66 | 1.29 (1.11–1.51) | 0.0009 | ||
C/T | 84 | 0.41 | 94 | 0.3 | 0.58 (0.40–0.84) | 0.0013 | ||
T/T | 16 | 0.08 | 10 | 0.03 | 0.42 (0.19–0.89) | 0.024 | ||
IL-18 | rs187238 | G | 284 | 0.69 | 457 | 0.74 | 1.27 (0.97–1.68) | 0.088 |
C | 126 | 0.31 | 159 | 0.26 | ||||
G/G | 100 | 0.49 | 170 | 0.55 | 1.13 (0.95–1.35) | 0.176 | ||
G/C | 84 | 0.41 | 117 | 0.38 | 0.82 (0.56–1.19) | 0.231 | ||
C/C | 21 | 0.1 | 21 | 0.07 | 0.59 (0.31–1.14) | 0.183 | ||
IFNγ | rs24030561 | T | 210 | 0.51 | 329 | 0.53 | 1.09 (0.85–1.40) | 0.523 |
A | 200 | 0.49 | 287 | 0.47 | ||||
T/T | 52 | 0.25 | 86 | 0.28 | 1.10 (0.82–1.48) | 0.543 | ||
T/A | 106 | 0.52 | 157 | 0.51 | 0.90 (0.59–1.37) | 0.785 | ||
A/A | 47 | 0.23 | 65 | 0.21 | 0.84 (0.50–1.39) | 0.663 | ||
IFNγR | rs2834213 | A | 249 | 0.61 | 403 | 0.65 | 1.22 (0.94–1.58) | 0.128 |
G | 161 | 0.39 | 213 | 0.35 | ||||
A/A | 71 | 0.35 | 119 | 0.39 | 1.12 (0.88–1.41) | 0.401 | ||
A/G | 107 | 0.52 | 165 | 0.54 | 0.92 (0.63–1.34) | 0.135 | ||
G/G | 27 | 0.13 | 24 | 0.08 | 0.53 (0.28–0.99) | 0.051 | ||
CD23 | rs2228137 | C | 324 | 0.79 | 436 | 0.71 | 0.64 (0.48–0.86) | 0.0036 |
T | 86 | 0.21 | 180 | 0.29 | ||||
C/C | 125 | 0.61 | 181 | 0.59 | 0.96 (0.83–1.11) | 0.647 | ||
C/T | 74 | 0.36 | 74 | 0.24 | 0.67 (0.51–0.87) | 0.0039 | ||
T/T | 6 | 0.03 | 53 | 0.17 | 6.15 (2.57–14.76) | <0.0001 | ||
Klotho | rs577912 | C | 356 | 0.87 | 525 | 0.85 | 0.87 (0.61–1.26) | 0.522 |
A | 54 | 0.13 | 91 | 0.15 | ||||
C/C | 154 | 0.75 | 221 | 0.72 | 0.95 (0.86–1.06) | 0.418 | ||
C/A | 48 | 0.23 | 83 | 0.27 | 1.21 (0.80–1.82) | 0.654 | ||
A/A | 3 | 0.02 | 4 | 0.01 | 0.90 (0.20–4.09) | 1 | ||
rs564481 | T | 145 | 0.35 | 376 | 0.61 | 2.86 (2.21–3.71) | <0.0001 | |
C | 265 | 0.65 | 240 | 0.39 | ||||
T/T | 25 | 0.12 | 122 | 0.4 | 3.25 (2.19–4.81) | <0.0001 | ||
C/T | 95 | 0.46 | 132 | 0.43 | 0.28 (0.17–0.47) | <0.0001 | ||
C/C | 85 | 0.42 | 54 | 0.18 | 0.42 (0.32–0.57) | <0.0001 |
Rule N. | Rules | Conf | Supp | Li | Conv |
---|---|---|---|---|---|
Allergy 01 | IFNγR2 rs2834213A/G; IL-10RB rs2834167G/G | 0.934 | 0.111 | 1.556 | 6.094 |
Allergy 02 | Klotho rs577912C/C; IL-10RB rs2834167G/G | 0.900 | 0.140 | 1.499 | 3.996 |
Allergy 03 | IL-10 rs1800896A/A; IL-10RB rs2834167G/G | 0.917 | 0.107 | 1.527 | 4.795 |
Allergy 04 | IL-10RB rs2834167G/G; IL-4 rs2243250C/C | 0.901 | 0.160 | 1.501 | 4.041 |
Allergy 05 | IL-10RB rs2834167G/G; IL-4R rs1801275A/A | 0.903 | 0.127 | 1.504 | 4.110 |
Allergy 06 | Klotho rs577912C/C; IL-10RB rs2834167G/G; IL-4 rs2243250C/C | 0.906 | 0.113 | 1.509 | 4.263 |
Allergy 07 | Klotho rs564481T/T; IL-6 rs1800795G/G; IL-13 rs1800925C/C | 0.941 | 0.125 | 1.568 | 6.793 |
Allergy 08 | IL-10RB rs2834167G/G; IL-6 rs1800795G/G; IL-4 rs2243250C/C | 0.906 | 0.113 | 1.509 | 4.263 |
Allergy 09 | IL-10RB rs2834167G/G; IL-4 rs2243250C/C; IL-4R rs1801275A/A | 0.912 | 0.101 | 1.519 | 4.556 |
Allergy 10 | Klotho rs564481T/T; IL-6 rs1800795G/G; IL-4 rs2243250C/C; IL-13 rs1800925C/C | 0.930 | 0.103 | 1.549 | 5.694 |
Rule | Allergic Subjects | Control Subjects | OR (95% C.I) | p | Sens. | Spec. | PPV | NPV | |||
---|---|---|---|---|---|---|---|---|---|---|---|
N. | % | N. | % | ||||||||
Allergy 01 | Pos | 57 | 18.51 | 4 | 1.95 | 11.41 (4.07–31.99) | 0.0001 | 0.185 | 0.985 | 0.934 | 0.445 |
Neg | 251 | 81.49 | 201 | 98.05 | |||||||
Allergy 02 | Pos | 72 | 23.37 | 8 | 3.90 | 12.10 (4.97–30.76) | <0.0001 | 0.234 | 0.961 | 0.900 | 0.455 |
Neg | 236 | 76.63 | 197 | 96.10 | |||||||
Allergy 03 | Pos | 55 | 17.86 | 5 | 2.44 | 8.70 (3.42–22.1) | <0.0001 | 0.179 | 0.976 | 0.917 | 0.445 |
Neg | 253 | 82.14 | 200 | 97.56 | |||||||
Allergy 04 | Pos | 82 | 26.62 | 9 | 4.39 | 7.90 (3.87–16.14) | <0.0001 | 0.266 | 0.956 | 0.901 | 0.464 |
Neg | 226 | 73.38 | 196 | 95.61 | |||||||
Allergy 05 | Pos | 65 | 21.10 | 7 | 3.41 | 7.57 (3.39–16.87) | <0.0001 | 0.211 | 0.966 | 0.903 | 0.449 |
Neg | 243 | 79.90 | 198 | 96.59 | |||||||
Allergy 06 | Pos | 58 | 18.83 | 6 | 2.91 | 7.69 (3.25–18.20) | <0.0001 | 0.188 | 0.971 | 0.906 | 0.453 |
Neg | 250 | 81.17 | 199 | 97.09 | |||||||
Allergy 07 | Pos | 64 | 20.78 | 4 | 1.95 | 13.18 (4.72–36.83) | <0.0001 | 0.208 | 0.981 | 0.941 | 0.452 |
Neg | 244 | 79.22 | 201 | 98.05 | |||||||
Allergy 08 | Pos | 58 | 18.83 | 6 | 2.91 | 7.69 (3.25–18.20) | <0.0001 | 0.188 | 0.971 | 0.906 | 0.443 |
Neg | 250 | 81.17 | 199 | 97.09 | |||||||
Allergy 09 | Pos | 52 | 16.88 | 5 | 2.44 | 8.12 (3.18–20.72) | <0.0001 | 0.169 | 0.976 | 0.912 | 0.439 |
Neg | 256 | 83.12 | 200 | 97.56 | |||||||
Allergy 10 | Pos | 53 | 17.21 | 4 | 1.95 | 10.44 3.72–29.35) | <0.0001 | 0.172 | 0.981 | 0.929 | 0.441 |
Neg | 255 | 82.79 | 201 | 98.05 | |||||||
All. RULES | Pos | 144 | 46.75 | 14 | 6.83 | 11.98 (6.66–21.55) | <0.0001 | 0.468 | 0.932 | 0.911 | 0.538 |
Neg | 164 | 53.25 | 191 | 93.17 |
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Lio, D.; Di Lorenzo, G.; Brusca, I.; Scola, L.; Bellia, C.; La Piana, S.; Barrale, M.; Bova, M.; Vaccarino, L.; Forte, G.I.; et al. A Heuristic Approach to Analysis of the Genetic Susceptibility Profile in Patients Affected by Airway Allergies. Genes 2024, 15, 1105. https://doi.org/10.3390/genes15081105
Lio D, Di Lorenzo G, Brusca I, Scola L, Bellia C, La Piana S, Barrale M, Bova M, Vaccarino L, Forte GI, et al. A Heuristic Approach to Analysis of the Genetic Susceptibility Profile in Patients Affected by Airway Allergies. Genes. 2024; 15(8):1105. https://doi.org/10.3390/genes15081105
Chicago/Turabian StyleLio, Domenico, Gabriele Di Lorenzo, Ignazio Brusca, Letizia Scola, Chiara Bellia, Simona La Piana, Maria Barrale, Manuela Bova, Loredana Vaccarino, Giusi Irma Forte, and et al. 2024. "A Heuristic Approach to Analysis of the Genetic Susceptibility Profile in Patients Affected by Airway Allergies" Genes 15, no. 8: 1105. https://doi.org/10.3390/genes15081105