Asthma is a common chronic disease, characterized by airway constriction, inflammation, bronchial hyper-responsiveness as well as recurrent coughing, wheezing, dyspnoea and chest tightness(Reference Hosseini, Berthon and Wark1). The rise in prevalence and medical costs of asthma are a major public health burden in both developed and developing counties(Reference Hosseini, Berthon and Wark1–Reference Eder, Ege and von Mutius3). It is generally thought that antioxidants play a vital role in maintaining the health of the airways, thus being associated with asthma(Reference Misso, Brooks-Wildhaber and Ray4). Enzymatic antioxidants, including superoxide dismutase and glutathione peroxidase, require Cu, Zn, Se and others to catalyse the conversion of oxygen radicals into hydrogen peroxide and then to water and oxygen(Reference Bishopp, Sathyamurthy and Manney5). Therefore, the concentration of these trace elements in serum or plasma might change the efficiency of the antioxidant system and further impact the inflammation and hyper-responsiveness status of the respiratory tract.
Higher level of Cu in asthma patients than in healthy controls has been well documented by previous studies(Reference Mao, Wu and Shi6). However, the observational studies on the associations of circulating Zn and Se levels with asthma have drawn conflicting conclusions. Some of them reported significantly lower levels of Zn(Reference Mohamed, Rushdy and Abdel-Rehim7,Reference Yousef and Elmorsy8) and Se(Reference Fabian, Poloskey and Kosa9–Reference Kocabas, Adalioglu and Coskun11) in asthma patients than in controls, while others found no significant difference(Reference Bishopp, Sathyamurthy and Manney5,Reference Johnkennedy, Constance and Emmanuel12–Reference Ariaee, Farid and Shabestari16) and a few suggested the opposite association(Reference Oluwole, Arinola and Adu13,Reference Uysalol, Uysalol and Yilmaz17) .
Given that individual studies may have insufficient power to obtain a definitive conclusion, we performed the current meta-analysis to: (i) assess the associations of circulating Zn and Se levels with asthma; (ii) explore the potential between-study heterogeneity; and (iii) investigate the potential publication bias.
Materials and methods
We referred to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines(Reference Moher, Liberati and Tetzlaff18) for reporting the current meta-analysis.
Literature search and selection
A literature search from inception to May 2019 was conducted for relevant available articles published from three databases: PubMed, Web of Science and Scopus. Studies were limited to human studies in the English language. The search process was conducted using the following keywords: (microelement OR trace element OR selenium OR zinc) AND (asthma OR wheeze OR airway inflammation OR respiratory symptoms OR respiratory disease OR airway obstruction). Moreover, we reviewed the reference lists of retrieved articles to search for further relevant studies. The detailed steps for the literature search are shown in Fig. 1.
Inclusion criteria
To be included in the meta-analysis, studies had to meet the following criteria: (i) observational study design; (ii) the cases were asthma patients who were diagnosed according to the Global Initiative for Asthma (GINA) guidelines(Reference Bateman, Hurd and Barnes19); (iii) the controls were healthy people without any respiratory disease; and (iv) data for the level of Zn or Se in serum or plasma were presented as means and standard deviations (or data were available to calculate them). The following exclusion criteria were also used: (i) reviews; (ii) participants were pregnant women or professional groups; and (iii) samples were infants’ umbilical cord blood.
If data were duplicated in more than one study, we included the one that was most recently published and/or had the largest number of cases. Two investigators searched for the articles and reviewed all possible studies independently. If the eligibility of an article was controversial, it was resolved by consensus.
Data extraction
The following data were extracted from each study independently by two investigators: the first author’s name, publication year, country where the study was performed, study type, the number of cases and controls, mean and standard deviation for level of Zn or Se, data units, sample type, treatment status in the case group, average age for the case and control groups, as well as matching of potential confounders. If the standard error of the mean was provided in a study, the standard deviation was calculated by the following formula: sem = sd/√n.
The quality of the included literature was assessed by the Agency for Healthcare Research and Quality (AHRQ) methodology checklist for cross-sectional studies and by the Newcastle–Ottawa Scale (NOS) for case–control studies, respectively(Reference Zeng, Zhang and Kwong20).
Statistical analyses
All statistical analyses were performed using standardized mean difference (SMD) with 95 % CI to assess the strength of the association of circulating Zn and Se levels with asthma. The SMD is the ratio of the mean difference to the pooled standard deviation by using the random-effects model. The I 2 statistic was used to evaluate the heterogeneity among the studies, with I 2 values of 25, 50 and 75 % representing low, moderate and high heterogeneity, respectively(Reference Higgins and Thompson21). We conducted meta-regression and subgroup analyses to explore potential sources of heterogeneity. A sensitivity analysis(Reference Gutteridge22) was performed to evaluate the key studies that have substantial impact on the between-study heterogeneity. An influence analysis was also performed in which one study at a time was removed and the rest were analysed to evaluate whether the results could have been affected markedly by a single study. Egger’s regression asymmetry test and visual inspection were used to evaluate the potential effects of small studies(Reference Egger, Davey Smith and Schneider23). In the presence of a potential small-study effect, we used the trim-and-fill technique to assess its influence on results(Reference Duval and Tweedie24), with the assumption that this effect was mainly due to publication bias. All statistical analyses were performed with the statistical software package Stata version 15.0. All reported probabilities (P values) were two-sided, with P < 0·05 considered statistically significant.
Results
A total of 9084 articles from PubMed, 1286 articles from Web of Science, 2304 articles from Scopus and one article from the reference lists were identified. After exclusion of duplicate and non-relevant articles, 127 articles were reviewed in full. Another ninety-one articles were excluded for other reasons (Fig. 1) and thirty-six eligible articles were finally included in the meta-analysis. If one article reported two separate results according to sex(Reference Urushidate, Matsuzaka and Okubo25,Reference Anetor, Ajose and Ige26) or asthma classification(Reference Mohamed, Rushdy and Abdel-Rehim7,Reference Sagdic, Sener and Bulucu27) or treatment status(Reference Ford, Mannino and Redd28), then it was considered as two studies. A pooled analysis of Se conducted in fourteen European centres was considered as fourteen studies in data extraction(Reference Burney, Potts and Makowska29). Thus, twenty-two articles with twenty-six studies provided results for Zn level(Reference Bishopp, Sathyamurthy and Manney5,Reference Mohamed, Rushdy and Abdel-Rehim7,Reference Yousef and Elmorsy8,Reference Guo, Liu and Hsia10,Reference Johnkennedy, Constance and Emmanuel12–Reference Uysalol, Uysalol and Yilmaz17,Reference Urushidate, Matsuzaka and Okubo25–Reference Sagdic, Sener and Bulucu27,Reference Khanbabaee, Omidian and Imanzadeh30–Reference Hussein, Yousif and Saeed38) and twenty-four articles with forty studies provided results for Se level(Reference Bishopp, Sathyamurthy and Manney5,Reference Fabian, Poloskey and Kosa9–Reference Kocabas, Adalioglu and Coskun11,Reference Oluwole, Arinola and Adu13,Reference Ariaee, Farid and Shabestari16,Reference Urushidate, Matsuzaka and Okubo25,Reference Ford, Mannino and Redd28,Reference Burney, Potts and Makowska29,Reference Kocyigit, Armutcu and Gurel31,Reference Picado, Deulofeu and Lleonart32,Reference Malvy, Lebranchu and Richard35,Reference Razi, Akin and Harmanci37–Reference Misso, Powers and Gillon48) . The detailed characteristics of the included studies are shown in the online supplementary material, Supplemental File S1 for Zn and Supplemental File S2 for Se.
The quality assessment showed that the NOS score ranged from 6 to 8 for the case–control studies. The quality score of the AHRQ methodology checklist ranged from 7 to 10 for the cross-sectional studies. The detailed quality assessment is shown in the online supplementary material, Supplemental File S3 and Supplemental File S4, respectively.
Quantitative synthesis
The main results are summarized in Table 1.
SMD, standardized mean difference; N/A, not applicable.
* P value from meta-regression.
Zinc
A total of twenty-six studies involving 1027 cases and 2150 controls were included in the Zn meta-analysis. The overall result suggested lower Zn level in the asthma group than in the control group (SMD = −0·40; 95 % CI −0·77, −0·03; Z = 2·13, P for Z = 0·033; I 2 = 94·1 %, P for I 2 < 0·001; Fig. 2). In subgroup analysis, the pooled measures did not change materially in studies conducted in Africa (SMD = −1·01; 95 % CI −1·99, −0·03), studies conducted in adults (SMD = −0·66; 95 % CI −1·21, −0·12), studies with case–control design (SMD = −0·47; 95 % CI −0·85, −0·09) and studies with treatment in patients (SMD = −0·67; 95 % CI −1·35, 0·00).
Selenium
A total of forty studies involving 3138 cases and 33 534 controls were included in the Se meta-analysis. The overall result showed lower Se level in the asthma group than in the control group (SMD = −0·32; 95 % CI −0·48, −0·17; Z = 4·04, P for Z < 0·001; I 2 = 90·9 %, P for I 2 < 0·001; Fig. 3). In subgroup analysis, the pooled measures did not change materially in studies conducted in Europe (SMD = −0·22; 95 % CI −0·40, −0·04), studies conducted in adults (SMD = −0·33; 95 % CI −0·56, −0·10) and children (SMD = −0·40; 95 % CI −0·74, −0·06), studies with case–control design (SMD = −0·41; 95 % CI −0·67, −0·14), studies with samples of serum (SMD = −0·39; 95 % CI −0·63, −0·15) and plasma (SMD = −0·28; 95 % CI −0·49, −0·06), studies with treatment in patients (SMD = −0·39; 95 % CI −0·64, −0·15), as well as studies with age-matched design (SMD = −0·39; 95 % CI −0·69, −0·10).
Sources of heterogeneity, sensitivity analysis and publication bias
Strong evidence of heterogeneity among studies was demonstrated for the associations of these trace elements with asthma. However, subgroup analysis and univariate meta-regression analysis suggested that continent, age, study design, sample type, treatment in patients and age-matched design had no significant impact on between-study heterogeneity (Figs 2 and 3, Table 1). In the influence analysis, all of the point estimates lay within the 95 % CI of the combined analysis, indicating that no individual study had an excessive influence on the pooled measure for Zn or Se. Visual inspection of the funnel plot and Egger’s test suggested that there was a potential small-study effect (P = 0·036 for Zn, P = 0·024 for Se).
Considering the unexplained heterogeneity and potential small-study effect, sensitivity analysis using I 2 > 50 % as the criterion was conducted to assess the robustness of conclusion. Six and seven studies contributed to the high heterogeneity of Zn(Reference Mohamed, Rushdy and Abdel-Rehim7,Reference Yousef and Elmorsy8,Reference Guo, Liu and Hsia10,Reference Uysalol, Uysalol and Yilmaz17,Reference Urushidate, Matsuzaka and Okubo25,Reference Hussein, Yousif and Saeed38) and Se(Reference Guo, Liu and Hsia10,Reference Kocabas, Adalioglu and Coskun11,Reference Malvy, Lebranchu and Richard35,Reference Hussein, Yousif and Saeed38,Reference Qujeq, Hidari and Bijani42,Reference Kadrabova, Mad’aric and Kovacikova45,Reference Stone, Hinks and Beasley47) , respectively. After excluding these studies, low heterogeneity and robust results without small-study effect were found for Zn (SMD = −0·26; 95 % CI −0·40, −0·13; I 2 = 37·42 %; P for Egger’s test = 0·400). However, the pooled SMD for Se had no statistical significance (SMD = −0·06; 95 % CI −0·13, 0·02; I 2 = 43·54 %; P for Egger’s test = 0·382). After running the trim-and-fill technique, no trimming was performed for Zn or Se.
Discussion
The current meta-analysis based on observational evidence, including 3177 participants for Zn and 36 672 participants for Se, indicated that asthma patients had lower circulating Zn and Se levels compared with healthy controls. Significant differences were found in most subgroup analyses by study characteristics and population characteristics. Different from our conclusion, the most recent meta-analysis by Mao et al.(Reference Mao, Wu and Shi6) including twelve studies for Zn and eighteen studies for Se reported no significant differences in Zn and Se between asthma patients and controls. Considering the small effects of Zn and Se on asthma, our meta-analysis that included a larger number of studies could enhance the test power to obtain a definitive conclusion and conduct subgroup analyses.
According to previous literatures, diet and supplements are the main sources of Zn exposure in the general population, accounting for 90–95 %(Reference Sandstead, Nordberg and Fowler49). Meanwhile, an experimental study showed that restriction of dietary Se and supplements could decrease the Se level in plasma(Reference Janghorbani, Xia and Ha50). In addition, accumulating evidence suggests that deficiency in dietary antioxidants such as Zn and Se might increase the risk of asthma(Reference Shaheen, Sterne and Thompson51,Reference Devereux and Seaton52) . The mechanisms underlying the associations of Zn and Se with asthma are still not fully understood. Zn is known to exhibit powerful antioxidant activity in the lungs and several body organs(Reference Abdul Wahab, Zeidan and Avades15), and is one of the components of superoxide dismutase. It is possible that the absence of Zn can disturb the imbalance between type 1 and type 2 T-helpers(Reference Honscheid, Rink and Haase53), which leads to increased inflammation and eosinophilia. This is the same mechanism as for allergic airway hypersensitivity(Reference Truong-Tran, Ruffin and Foster54). In addition, the increase of Cu:Zn can be occasionally seen in inflammatory disease. It has been postulated that the increase in serum Cu might be associated with decrease in serum Zn. The changes in these levels will affect enzyme activity and further implicitly cause inflammation by decreasing the capacity of the antioxidant system(Reference Uysalol, Uysalol and Yilmaz17). Se is necessary for the adequate function of the glutathione peroxidase, which is an important antioxidant to prevent the airway from being damaged by reactive oxygen species(Reference Burney, Potts and Makowska29).
Between-study heterogeneity is common in meta-analysis(Reference Munafo and Flint55). In the present study, high heterogeneities were found for both element analyses. Subgroup analyses and meta-regressions with the covariates of several study and population characteristics did not successfully explain the heterogeneity. The further ‘leave-one-out’ sensitivity analyses using I 2 > 50 % as the criterion suggested that six studies(Reference Mohamed, Rushdy and Abdel-Rehim7,Reference Yousef and Elmorsy8,Reference Guo, Liu and Hsia10,Reference Uysalol, Uysalol and Yilmaz17,Reference Urushidate, Matsuzaka and Okubo25,Reference Hussein, Yousif and Saeed38) in Zn analysis and seven studies(Reference Guo, Liu and Hsia10,Reference Kocabas, Adalioglu and Coskun11,Reference Malvy, Lebranchu and Richard35,Reference Hussein, Yousif and Saeed38,Reference Qujeq, Hidari and Bijani42,Reference Kadrabova, Mad’aric and Kovacikova45,Reference Stone, Hinks and Beasley47) in Se analysis contributed to the high between-study heterogeneities. After excluding these studies, no significant association of Se with asthma was found, which needs to be confirmed. However, the significant difference in Zn between cases and controls was still found, supporting the robustness of conclusions of the current meta-analysis. In ‘leave-one-out’ sensitivity analysis, the reasons for excluding these studies may be the low quality assessment score, the small sample size and the sample sources mostly from hospitals.
The visual inspection of funnel plots and Egger’s test showed funnel plot asymmetry for both trace elements. After running the trim-and-fill technique, no trimming was performed for Zn or Se. This might indicate that the asymmetric funnel patterns of Zn and Se were not caused by the small-study effect. The causes of funnel plot asymmetry or other shapes might be heterogeneity, reporting bias and chance(Reference Sterne, Sutton and Ioannidis56). When we excluded the studies that contributed to the high between-study heterogeneity assessed by the sensitivity analysis, no significant small-study effect was found. This further demonstrated that the funnel plot asymmetry might be caused by heterogeneity.
In addition to the large number of studies involved, another major strength of the current meta-analysis should be considered. To address the issue of inconsistency of measurement conditions and units for trace elements in different studies, we estimated the pooled SMD by using a random-effects model, which could draw more convincing results. Nevertheless, as a meta-analysis of published observational studies, our findings have several limitations. First, high between-study heterogeneity was discovered in each trace element analysis, but it was not explained by subgroup analysis or meta-regression. The lack of relevant study-level covariates in the reported articles precluded a more accurate assessment for sources of the heterogeneity. For example, most included studies(Reference Yousef and Elmorsy8,Reference Kocabas, Adalioglu and Coskun11,Reference Johnkennedy, Constance and Emmanuel12,Reference Elevli, Bozaci and Sahin14–Reference Uysalol, Uysalol and Yilmaz17,Reference Jacobson, Yee and Ng39) did not report stratified results according to asthma classification. Second, although the results in most subgroup analyses did not change materially compared with the overall analysis, the sensitivity analysis showed that the result for Se was not robust. Third, we were unable to explore the dose–response relationship between circulating Zn and Se levels and asthma or the association of Cu:Zn with the risk of asthma, due to the limited data availability. Fourth, confounders adjusted for in the involved studies were different, which might affect the observed associations. Finally, after hard work searching, we were unable to find the full text for twelve articles. Nine of them were conference papers and the other three were too old to be well preserved. Those missing articles would definitely have an impact on the overall results.
Conclusion
The current meta-analysis provides evidence that lower circulating Zn and Se levels are associated with an increased risk of asthma. This finding might contribute to the understanding of the pathogenesis of asthma. Considering the important role of diet and supplements in determining circulating Zn and Se levels, attention should be paid to daily intake of Zn and Se in the prevention of asthma. More large observational studies are required to confirm the association between Se level and asthma.
Acknowledgements
Financial support: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Conflict of interest: None. Authorship: M.C. and Y.W. conceived the study, participated in its design and coordination, carried out the literature searching and data extraction, and were involved in drafting the manuscript or revising it critically for important intellectual content. Y.S. carried out the literature searching and data extraction. All the authors have read and approved the final version of the manuscript. Ethics of human subject participation: Not applicable.
Supplementary material
To view supplementary material for this article, please visit https://doi.org/10.1017/S1368980019003021