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Background:
Systematic Review

GSDMB Gene Polymorphisms and Their Association with Asthma Susceptibility: A Systematic Review and Meta-Analysis of Case–Control Studies

by
Maria E. Ramos-Nino
1,* and
Prakash V. A. K. Ramdass
2
1
Department of Microbiology, Immunology, and Pharmacology, St. George’s University School of Medicine, St. George P.O. Box 7, Grenada
2
Department of Public Health and Preventive Medicine, St. George’s University School of Medicine, St. George P.O. Box 7, Grenada
*
Author to whom correspondence should be addressed.
J. Respir. 2024, 4(4), 198-209; https://doi.org/10.3390/jor4040018
Submission received: 10 September 2024 / Revised: 26 October 2024 / Accepted: 8 November 2024 / Published: 11 November 2024
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Abstract

:
Background: Asthma is a respiratory disorder influenced by genetic and environmental factors. The rs7216389 polymorphism in the gasdermin B (GSDMB) gene on chromosome 17q21 has been implicated in asthma susceptibility with conflicting results. This meta-analysis aims to bring forward new findings on the association between this polymorphism and asthma across diverse populations and its potential as a genetic marker for asthma risk. Methods: A systematic review and meta-analysis were conducted through March 2024, and odd ratios were calculated. Results: The meta-analysis included 22 studies with a total of 9012 asthma patients and 11,657 controls. The results show an OR = 1.24, 95% CI [1.13, 1.37], p < 0.00001. Subgroup analyses stratified by age and ethnicity between asthma patients with T alleles vs. C alleles demonstrated an association between having the T allele and asthma susceptibility across Asian, Caucasian, and American minorities, but not among Arabs. Young asthma patients with the dominant allele (T) showed higher asthma risk than those with C allele or heterozygote TC, and to a higher extent than for adults. Conclusions: This meta-analysis indicates the importance of genetic factors in asthma in certain ethnicities and underscores the potential utility of the rs7216389 polymorphism as a genetic marker for asthma risk assessment.

1. Introduction

Asthma is a multifactorial respiratory disorder characterized by chronic inflammation, increased airway responsiveness, and airway remodeling [1]. Asthma is influenced by genetic and environmental factors [2,3,4,5]. Epidemiologic studies have calculated asthma heritability between 35 and 95% [4,6,7]. The genetic basis of asthma involves a complex interplay between multiple genes, each contributing a small effect to overall disease susceptibility.
Genome-wide association studies (GWAS) and other genetic analyses have identified numerous genetic variants associated with asthma risk [6,8]. Genes that have been linked to the development of asthma include IL33, IL1RL1, IL13, TSLP, HLA, GATA3, and SMAD3, and genes localized to chromosome 17q12-21 (ORMDL3 and GSDMB) [9]. In addition, several genes (ADAM33, PLAUR, VEGF, IL13, CHI3L1, TSLP, GSDMB, TGFB1, POSTN, ESR1, and ARG2) have been associated with a decline in lung function in asthma and/or the features of airway remodeling [10]. The association of locus 17q12-21 genes with asthma is particularly strong in populations of diverse ethnic backgrounds and age [6,11,12,13]. In the 17q21 locus, the rs7216389 SNP is found within a large linkage disequilibrium block that contains the ORM1-like gene (ORMDL3) gene, gardermin A and B (GSDM), IKAROS family zinc finger 3 (IKZF3), and zona pellucida binding protein 2 (ZPBP2), suggesting an individual or combined action of these genes towards asthma (Figure 1 [14]) [6,7,13,14,15,16,17,18]. rs7216389 in GSDMB has shown a strong association with asthma [17,19,20]. The rs7216389 SNP typically involves two alleles, T and C, of which T is the one associated with asthma risk (references presented in this study). Gene expression results indicate roles not only for GSDMB but also for ORMDL3 in asthma [11,21] probably due to the high linkage disequilibrium within 17q12-17q21.1.
Several meta-analyses precede this study [7,22,23,24,25]. This is an update on the accumulated data of the association between asthma and SNP rs7216389 on gene GSDMB to help elucidate the overall association.

2. Materials and Methods

This systematic review and meta-analysis was conducted following PRISMA guidelines [26], with the protocol pre-registered and published in PROSPERO (545518).

2.1. Data Sources and Search Strategy

A comprehensive search was conducted in MEDLINE, Google Scholar, and EMBASE using the keywords “asthma” AND “rs7216389”, covering studies from inception through 31 March 2024, without language restrictions.

2.2. Study Selection and Eligibility

Citation files from each database were combined in Zotero, where duplicates were removed. Two reviewers (M.E.R. and P.R.) screened titles and abstracts for eligibility, and full texts of articles meeting inclusion criteria were further examined for final inclusion in the review. Any disagreements on study eligibility were resolved through discussion. The criteria for studies included in the meta-analysis were as follows: (1) a case–control design; (2) data sufficient to calculate odds ratios for the association between rs7216389 alleles or genotypes and asthma; and (3) a confirmed asthma diagnosis by methods other than self-report. Exclusion criteria were the following: (1) studies using cell or animal models; (2) reviews, comments, abstracts, and case reports.

2.3. Data Extraction

Two independent reviewers (M.E.R. and P.R.) extracted data from eligible studies, including the first author, study design, age group, ethnicity, asthma diagnostic criteria, allele determination methods, and allele and genotype frequencies in asthma patients and controls. Studies presenting data in distinct subgroups (e.g., by age or ethnicity) were analyzed separately. Any disagreements were resolved through discussion between the reviewers.

2.4. Quality Assessment

The quality of eligible studies was assessed by two independent reviewers (M.E.R. and P.R.) using the Newcastle–Ottawa Scale [27], evaluating selection, comparability, and outcome criteria. Studies were scored from 0 to 9 points, with scores of ≥7 indicating high quality, 4–6 medium quality, and <4 low quality.

2.5. Statistical Analysis

Data were analyzed for odds ratios using Review Manager 5.4.1 (The Cochrane Collaboration, 2014; The Nordic Cochrane Centre, Copenhagen, Denmark). Pooled odds ratios (ORs) with 95% confidence intervals (CIs) assessed the risk of asthma susceptibility associated with different alleles or genotypes. Heterogeneity among studies was evaluated using the Cochrane Q-test and the I2 index, with I2 > 50% indicating significant heterogeneity. A random-effects model was used for data pooling, with statistical significance set at p < 0.05. Sensitivity analysis was conducted by sequentially omitting individual studies to assess their impact on the overall effect. Potential publication bias was evaluated through visual inspection of funnel plots created in RevMan 5.4.1.3 and using Egger’s test in MedCalc® Statistical Software version 22.02.

3. Results

3.1. Characteristics of Identified Studies

As shown in Figure 2, the titles and abstracts of 126 articles were screened for eligibility, with 122 meeting the criteria for full-text review. After additional screening, 22 studies fulfilled the inclusion criteria for the systematic review and meta-analysis.
Characteristics of the 22 studies included in the meta-analysis appear in Table 1.

3.2. Asthma and Allele Frequencies

A total of 22 studies [11,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48] comprising 9012 patients with asthma and 11,657 controls were included in the meta-analysis. The forest plot in Figure 3 illustrates the association between GSDMB (rs7216389) gene polymorphism (T/C) and asthma risk (OR = 1.24, 95% CI [1.13, 1.37], p < 0.00001, I2 = 75%). Figure 4 shows the corresponding funnel plot for the selected studies, which indicates no publication bias. This is corroborated by the Egger’s regression test, with an intercept of −1.18, and 95% CI [−3.09, 0.7168], and p = 0.21.
Subgroup analyses stratified by age (Figure 3) and ethnicity (Figure 5) between asthma patients with T alleles vs. C alleles, demonstrates an association of having the T allele with asthma susceptibility across Asian, Caucasian, and American minorities but not among Arabs. Young asthma patients with the dominant allele (T) showed higher asthma risk than those with the C allele. This association was significantly lower for adult cohorts.
Subgroup analysis by age and ethnicity funnel plots for publication bias (Figure 4 and Figure 6) show no bias.

3.3. Asthma and Genotype Frequencies

Comparative genotype results using random models are presented in Table 2.

4. Discussion

The importance of the 17q21 gene locus to asthma was initially suggested from a GWAS study which identified the 17q21 region as an important asthma susceptibility locus for childhood-onset asthma [11]. Our analysis consolidates these findings and expands them by including new data.
Our meta-analysis indicates that SNP rs7216389 is significantly associated with susceptibility to asthma. The association is stronger in the young cohorts than the adult cohorts, with some conflicting studies. This association holds when analyzing different ethnicities. The ethnic background of the population must be considered, since the same polymorphism may play different roles in different environments and genetic make-up. Subgroup analysis indicates, as previously found [22], that the SNP rs7216389 in Asians, Caucasians, and other American minorities (African and Native Americans) has a clear association with asthma, but that was not the case for the Arab subgroup where no association was found. There is a limitation to this interpretation since the African, Native American, and Arab studies have small population sizes.
In the overall population analysis, three genotypic models (TT vs. CC, TT + TC vs. CC, and TT vs. TC + CC) are homozygous and heterozygous for the T risky allele and the allele model (T vs. C) and indicate a higher risk of asthma. The heterozygous TC presented in the TC vs. CC model had only a moderately higher risk in the young population and Caucasians, as observed in Table 2.
Although some genetic studies have demonstrated that GSDMB can individually, or in combination with other regions of 17q12-21, act as a risk factor for asthma, no functional studies have established the biological role of GSDMB in mediating asthma pathogenesis [14]. Using immunohistochemistry, GSDMB protein was shown to be expressed specifically on human bronchial epithelial cells and no other lung cell population, and the number of GSDMB-positive bronchial epithelial cells was higher in asthmatics compared to controls. In some studies, the gasdermin family was found to be involved in the regulation of epithelial apoptosis and GSDMB demonstrated oncogenic traits [49]. GSMs increase the activity of pyrositosis, which aggravates tissue damage and induces an exaggerated inflammatory response [50]. The mechanisms associated with the rs7216389 SNP and asthma, in particular, have not been elucidated, but some potential mechanisms have been suggested, including increased levels of IgE and severity of bronchial hyper-responsiveness, which are intermediate phenotypes of asthma [37,48]. Another mechanism proposed is that rs7216389 SNP regulates the expression of ORMDL3. ORM proteins regulate sphingolipid production [51] and the development of the unfolded protein response, a process associated with inflammation, which could explain its association with asthma [52,53,54]. ORMLD3 facilitates the endoplasmic reticulum mediating inflammatory responses, which influences the regulation of allergen sensitization [55]. As an example, respiratory infections with human rhinovirus (HRV), a powerful trigger for asthma exacerbation [56], in individuals with rs7216389 SNP, has been associated with increased odd ratios for childhood asthma and increased transcript levels of ORMDL3 [56]. Additionally, polymorphisms on chromosome 17q12-q21, including the rs7216389 SNP, have been associated with rhinovirus-induced IFN-β production, suggesting a novel mechanism where impaired IFN-β induction links 17q12-q21 risk alleles to asthma and wheezing [57]. While the overall findings support a robust association between GSDMB polymorphisms and asthma susceptibility, there are notable limitations in the current body of literature. One major limitation is the variability in study designs, including differences in sample size, age groups, and the diagnostic criteria for asthma. This heterogeneity may contribute to the variation in effect sizes observed across studies. Additionally, many studies did not account for potential confounding factors such as environmental exposures and other genetic polymorphisms that might interact with GSDMB [12]. Future research should aim to standardize methodologies and incorporate comprehensive genotyping and environmental assessments to better elucidate the role of GSDMB in asthma.

5. Conclusions

In summary, the observed association highlights the importance of genetic factors in asthma in certain ethnicities and underscores the potential utility of the rs7216389 polymorphism as a genetic marker for asthma risk assessment. Genetics plays a significant role in asthma etiology, and ongoing research efforts continue to uncover the complex genetic architecture underlying this common respiratory disorder. Integrating genetic information into clinical practice holds promise for improving asthma diagnosis, management, and patient outcomes in the era of precision medicine.

Author Contributions

M.E.R.-N., conceptualization, methodology, investigation, formal analysis, writing, and project administration; P.V.A.K.R., data curation, review, and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data are provided in the review.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Schematic representation of chromosome 17q21 genes and the location of asthma-associated SNP rs7216389 located in an intron of the GSDMB gene.
Figure 1. Schematic representation of chromosome 17q21 genes and the location of asthma-associated SNP rs7216389 located in an intron of the GSDMB gene.
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Figure 2. Flow diagram of the included studies.
Figure 2. Flow diagram of the included studies.
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Figure 3. Meta-analysis results showing the association between rs7216389 (T/C) and pooled asthma risk, categorized by age (youth: ≤18 years of age or adulthood: >18 years of age). Square boxes represent individual studies, horizontal lines indicate 95% confidence intervals (CIs), and diamond-shaped figures illustrate the 95% CIs of the pooled estimate using random-effect models [11,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48].
Figure 3. Meta-analysis results showing the association between rs7216389 (T/C) and pooled asthma risk, categorized by age (youth: ≤18 years of age or adulthood: >18 years of age). Square boxes represent individual studies, horizontal lines indicate 95% confidence intervals (CIs), and diamond-shaped figures illustrate the 95% CIs of the pooled estimate using random-effect models [11,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48].
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Figure 4. Funnel plot illustrating publication bias among the selected studies.
Figure 4. Funnel plot illustrating publication bias among the selected studies.
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Figure 5. Meta-analysis results depict the association between the rs7216389 SNP and asthma prevalence, categorized by ethnicity. The pooled risk of asthma in patients with T versus C alleles is presented. Square boxes represent individual studies, horizontal lines indicate 95% confidence intervals (CIs), and diamond-shaped figures illustrate the 95% CIs of the pooled estimate using random-effect models [11,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48].
Figure 5. Meta-analysis results depict the association between the rs7216389 SNP and asthma prevalence, categorized by ethnicity. The pooled risk of asthma in patients with T versus C alleles is presented. Square boxes represent individual studies, horizontal lines indicate 95% confidence intervals (CIs), and diamond-shaped figures illustrate the 95% CIs of the pooled estimate using random-effect models [11,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48].
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Figure 6. Funnel plot illustrating publication bias among the selected studies.
Figure 6. Funnel plot illustrating publication bias among the selected studies.
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Table 1. Included studies’ information and alleles of GSDMB (rs72163389).
Table 1. Included studies’ information and alleles of GSDMB (rs72163389).
Allele Frequency
CasesControls
YearStudyPopulationEthnicityAge GroupAsthma CasesControlsTCTCMethodQuality Score *
2007Moffatt MF(G) [11]GermanCaucasianYouth728694830626657731Illumina/Taqman6
2007Moffatt MF(B) [11]BritishCaucasianYouth306104137823410351047Illumina/Taqman6
2008Galanter J [28]AmericanAfrican AmericanYouth2611764378527676AS-PCR7
2008Hirota T [29]JapaneseAsianYouth5457388522381052424Taqman6
2008Tavendale R [30]ScottishCaucasianYouth127915411429112914311651Taqman5
2009Leung Tf [31]ChineseAsianYouth31519250612429589PCR-RFLP5
2010Jin Z [32]ChineseAsianYouth220208326114290126Taqman4
2011Binia A [33]BritishCaucasianAdult385142943233813521506Taqman7
2011Brauner EV [34]DanishCaucasianYouth111273411351089695773Taqman6
2011Huang HZ [35]ChineseAsianAdult808496647692PCR6
2011Fang Q [36]ChineseAsianAdult7106561026366882392PCR-RFLP5
2011Yu J [37]KoreanAsianYouth7865221216356762282PCR-RFLP6
2012Ding YP [38]ChineseAsianAdult1201501835721882PCR-RFLP6
2012Sy HY [39] ChineseAsianAdult345464537153695233Taqman6
2012Yang FF [40]ChineseAsianYouth15219023767259121MassArray6
2013Balantic M [41]SlovakCaucasianAdult131170107155173167Taqman6
2014Miyake Y [42]JapaneseAsianAdult2021290306981878702Taqman5
2016Zihlif M (Y) [43]JordanianArabYouth981121415513391PCR-RFLP5
2016Zihlif M (A) [43]JordanianArabAdult12911115210612894PCR-RFLP5
2016Hu H [44]ChineseAsianAdult39439564314347152SnapShot technology4
2016Zavbi M [45]SlovakCaucasianAdult418288450386279297Taqman6
2017Best LG [46]AmericanNative AmericanYouth10821514175242176Taqman6
2019Dytiatkovsky VO [47]UkrainianCaucasianYouth19342992939PCR-RFLP5
2022Imraish A (Y) [48]JordanianArabYouth46112256792132PCR-RFLP5
2022Imraish A (A) [48]JordanianArabAdult12311110014694128PCR-RFLP5
Y = Youth; A = Adult; G = German; B = British; AS-PCR = allele-specific PCR; PCR-RFLP = polymerase chain reaction-restricted fragment length polymorphism. * Quality score: Newcastle–Ottawa Scale.
Table 2. Summary of Genotype Random Models.
Table 2. Summary of Genotype Random Models.
Comparison Asthma (Events/Total)Control (Events/Total)ORCIpI2
TT vs. TC + CC 3394/75953556/95121.391.26, 1.54<0.0000147
AgeYouth1987/45721516/43831.471.26, 1.72<0.0000154
Adult1407/30232040/51291.321.15, 1.520.000139
EthnicityCaucasian962/3344955/41961.320.99, 1.750.0579
Asian2309/38552484/48701.451.32, 1.59<0.000010
Arab123/396117/4461.150.72, 1.860.5650
CC vs. TC + TT 4200/75955822/95120.800.67, 0.950.0182
AgeYouth2585/45722867/43830.680.58, 0.79<0.0000154
Adult1615/30232955/51290.930.69, 1.270.6687
EthnicityCaucasian2382/33443241/41960.760.57, 1.010.0579
Asian1545/38552252/48700.810.62, 1.050.1187
Arab273/396329/4460.870.54, 1.400.5950
TC vs. TT + CC 3140/75954172/95120.89 0.77, 1.030.1276
AgeYouth1922/45722006/43830.810.69, 0.940.00455
Adult1218/30232166/51290.990.77, 1.290.9784
EthnicityCaucasian1658/33442049/41961.030.94, 1.140.500
Asian1310/38551910/48700.860.67, 1.110.2584
Arab172/396213/4460.800.60, 1.050.1276
TT vs. CC 3394/44553556/53411.561.19, 2.050.00181
AgeYouth1987/26501516/23771.591.16, 2.180.00468
Adult1407/18052040/29641.520.95, 2.440.0887
EthnicityCaucasian962/1686955/21471.531.03, 2.260.0383
Asian2309/25452484/29611.761.10, 2.810.0283
Arab123/224117/2331.040.46, 2.320.9370
TT + TC vs. CC 6534/75957728/95121.371.07, 1.760.0183
AgeYouth3909/45723522/43831.331.03, 1.720.0362
Adult2625/30234206/51291.400.89, 2.220.1589
EthnicityCaucasian2620/33443004/41961.371.06, 1.790.0275
Asian3619/38554394/48701.550.93, 2.600.0987
Arab295/396330/4460.940.52, 1.670.8265
TC vs. CC 3140/41314349/59561.040.87, 1.230.6949
AgeYouth1922/25852006/28671.170.94, 1.460.1745
Adult1218/15462343/30890.910.73, 1.150.4328
EthnicityCaucasian1658/22982049/32411.251.01, 1.550.0447
Asian1310/15602087/23860.940.75, 1.180.6220
Arab172/273213/3290.870.55, 1.370.5537
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Ramos-Nino, M.E.; Ramdass, P.V.A.K. GSDMB Gene Polymorphisms and Their Association with Asthma Susceptibility: A Systematic Review and Meta-Analysis of Case–Control Studies. J. Respir. 2024, 4, 198-209. https://doi.org/10.3390/jor4040018

AMA Style

Ramos-Nino ME, Ramdass PVAK. GSDMB Gene Polymorphisms and Their Association with Asthma Susceptibility: A Systematic Review and Meta-Analysis of Case–Control Studies. Journal of Respiration. 2024; 4(4):198-209. https://doi.org/10.3390/jor4040018

Chicago/Turabian Style

Ramos-Nino, Maria E., and Prakash V. A. K. Ramdass. 2024. "GSDMB Gene Polymorphisms and Their Association with Asthma Susceptibility: A Systematic Review and Meta-Analysis of Case–Control Studies" Journal of Respiration 4, no. 4: 198-209. https://doi.org/10.3390/jor4040018

APA Style

Ramos-Nino, M. E., & Ramdass, P. V. A. K. (2024). GSDMB Gene Polymorphisms and Their Association with Asthma Susceptibility: A Systematic Review and Meta-Analysis of Case–Control Studies. Journal of Respiration, 4(4), 198-209. https://doi.org/10.3390/jor4040018

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