Abstract
Previous studies have suggested a potential association between allergic rhinitis (AR) and hypertension, but the genetic basis remains unclear. In this study, we aimed to explore the genetic correlation and potential causal association between AR and hypertension. Using a large-scale genome-wide association study (GWAS) public database, we conducted meticulous screening to acquire the most up-to-date GWAS data on single nucleotide polymorphisms (SNPs) relevant to AR and hypertension, with a significance threshold of P < 5 × 10-8. Then, we investigated the causal association between AR and hypertension through mendelian randomization (MR) analysis. We also performed reverse MR analysis to assess the possibility of reverse causality. Sensitivity analyses encompassed various factors, including horizontal pleiotropy, heterogeneity testing, and stepwise exclusion sensitivity checks. To investigate the causal relationship between AR and hypertension, we utilize the odds ratio (OR) and 95% confidence interval (CI) as our evaluative metric. This study leveraged a database comprising 112583 samples for AR and 461880 samples for hypertension. After meticulous screening, we identified 32 SNPs as instrumental variables. By employing the aforementioned 2-sample Mendelian randomization approaches, the estimated causal effects showed striking concordance. A discernible causal association between AR and hypertension was found using the IVW method (OR = 0.91, 95% CI: 0.86–0.98, P = .008), with horizontal pleiotropy and heterogeneity tests supporting the validity of our MR study. MR-Egger regression findings provided reassurance against bias stemming from genetic pleiotropy (intercept = -0.0006802, P = .6947). Interestingly, “leave-one-out” analysis yielded no evidence of nonspecific SNP influences, further consolidating our findings. Moreover, our reverse MR analysis yielded no indication of reverse causality from hypertension to AR, effectively discounting any influence from the latter on the former. Our study found evidence of a causal association between AR and hypertension in individuals of European ancestry. It demonstrated that AR reduced the risk of hypertension, suggesting a protective effect on hypertension due to the negative correlation with AR.
Keywords: allergic rhinitis, causal relationship, hypertension, two-sample mendelian randomization
1. Introduction
Allergic rhinitis (AR) is an upper airways disease characterized by nasal obstruction, rhinorrhea, sneezing, and nasal pruritus. These symptoms are caused by inhaled allergens, leading to mucosal inflammation. AR, with an incidence of 10% to 40% in the population, stands as one of the most common diseases worldwide, imposing a considerable burden on quality of life.[1] Additionally, variations in environmental factors and allergen exposures across different regions are likely to influence the diagnosis of patients with AR,[2] consequently contributing to differences in its prevalence. For instance, the prevalence of AR exhibits a high and escalating trend in Japan and Inner Mongolia in China.[3–5]
Hypertension represents a pervasive global predicament, bearing significant health ramifications, and its prevalence persists, as marked by suboptimal management rates.[6] The etiology of hypertension revolves around genetic predisposition and the intricate interplay of environmental and pathophysiological factors. These factors affect diverse physiological systems, while the regulatory mechanisms governing hypertension remain partially unveiled.[7–9] Population studies have demonstrated that the prevalence of both hypertension and allergic diseases continue to increase each year.[10]
The IgE-mediated type I hypersensitivity reaction is the core mechanism underlying the development of AR, involving mast cell degranulation and the release of inflammatory mediators such as histamine and leukotrienes. Histamine, a significant mediator responsible for allergic rhinitis symptoms, plays a major role in AR.[11] Being a potent vasodilator, histamine can attenuate blood pressure.[12] Leukotrienes are proinflammatory vasoactive substances that might be associated with the pathogenesis of hypertension.[13] The relationship between AR and hypertension is currently not fully elucidated. Kony et al found an association between questionnaire-reported rhinitis and measured arterial systolic blood pressure in 146 middle-aged males.[14] However, Heinrich et al found no association between AR and measured blood pressure.[15] In a separate study, Stebbings et al examined the relationship between allergic disease and hypertension among New York City transit workers. They demonstrated that transit workers with asthma and hay fever had higher systolic blood pressures and were prescribed more anti-hypertensive medications than their non-asthmatic, non-allergic colleagues.[16] The authors concluded that respiratory allergies may be risk factors for hypertension. Both AR and hypertension are complex diseases, with pathogenesis involving a myriad of intricate factors, including the immune system, genetics, and other environmental and lifestyle components. Moreover, the interplay of these factors may lead to mutual influence, emphasizing the importance of elucidating the causality between AR and hypertension and exploring potential disease mechanisms. A deep understanding of the interactions and casual relationships between AR and hypertension provides the foundation for precise control of both diseases.
Mendelian Randomization (MR) is a powerful tool in genetic epidemiology used to assess the causal effects.[17] By utilizing genetic variations, such as Single Nucleotide Polymorphisms (SNPs), as instrumental variables to modify disease risk factors or exposures, MR can strengthen the causal inference of exposure-outcome associations. The MR method is based on 3 main assumptions. Firstly, risk factors should be associated with the genetic variation used as instrumental variables. Secondly, confounding factors should not be associated with the genetic variation. Thirdly, genetic pleiotropy should affect the risk factor rather than the outcome through other pathways.[18] According to Mendelian Genetics Law, genetic variations are randomly allocated during gamete formation, making them less likely to be affected by confounders. Moreover, as genotypes cannot change with the development of the disease, reverse causality bias can be minimized. In this study, we conducted bidirectional MR analysis using the latest Genome-Wide Association Studies (GWAS) data to elucidate the causal relationship between AR and hypertension, as well as to assess the directionality of this relationship.[19]
2. Methods
2.1. Study design
In this study, we utilized AR as the exposure factor and employed SNPs significantly correlated with AR as instrumental variables (IVs). hypertension was selected as the outcome variable for the causal association analysis, which was carried out using the Two-Sample MR R package (version 4.3.0).[20] Furthermore, we validated our results through Cochran Q heterogeneity test, tests for multiple effects, and sensitivity analyses. The overall study design is illustrated in Figure 1.[21]
Figure 1.
The core assumptions of MR. The fundamental tenets of MR can be summarized as follows in the context of the study: MR postulates that Z, representing the genetic instruments (SNPs), serves as the exogenous variable, while X denotes the exposure of interest (AR), and Y stands for the outcome of interest (hypertension). Furthermore, U signifies the latent confounders that influence the relationship between X and Y. To elaborate on the assumptions: It is assumed that a strong association exists between the genetic variation (Z) and the exposure of interest (X), indicated by γ ≠ 0. Additionally, it is postulated that the genetic variation (Z) has no direct influence on the confounding factors (U), as represented by the condition ϕ1 = 0. Moreover, the assumption posits that the effect of the genetic variation (Z) on the outcome (Y) operates solely through exposure (X), characterized by ϕ2 = 0. AR = allergic rhinitis, MR = mendelian randomization, SNPs = single nucleotide polymorphisms.
2.2. Data sources
This research study obtained full genome association data for AR and hypertension respectively from the https://gwas.mrcieu.ac.uk/ website. The genomic data for AR (ukb-b-7178) were derived from the published GWAS statistical results of 2018. This dataset encompassed 112,583 individuals, consisting of 25,486 cases and 87,097 controls, and included 9851,867 SNPs. The data retrieved for hypertension (ukb-b-14177) were derived from the published 2018 GWAS statistical results. The sample pool comprised 461,880 individuals, including 124,227 cases and 337,653 controls, and included at a comparable amount of 9851,867 SNPs. Both AR and hypertension participant findings were drawn from the European population and were representative of both male and female genders, as detailed in Table 1. This study constitutes a reanalysis of publicly disseminated open-access data, obviating the need for ethical approval.
Table 1.
Data sources.
| Disease/Trait | N case | N control | Sample size | Population | Consortium |
|---|---|---|---|---|---|
| AR | 25486 | 87097 | 112583 | EUR | MR-base |
| Hypertension | 124227 | 337653 | 461880 | EUR | MR-base |
N case, number of cases; N control, number of control groups; population, ethnic population (European population, EUR); consortium, source organization.
AR = allergic rhinitis.
2.3. Selection of genetic instruments
The genetic instrumental variables employed in the MR analysis must adhere to 3 assumptions: strong correlation with the exposure variable, independence from confounding factors, and sole correlation with the outcome variable through the exposure variable.[22] In the GWAS, the necessity for a stringent statistical correction method arises due to the potential escalation of false-positive results stemming from multiple comparisons. The judicious selection of a significance threshold below P < 5 × 10-8 is considered a conservative approach, efficaciously mitigating the risk of spurious associations and rendering the observed correlations more likely to be authentic. Based on the first assumption of MR analysis, this study selected SNPs from the exposure variable GWAS dataset, reaching genome-wide significant associations (P < 5 × 10-8) and excluding those in linkage disequilibrium (r2 threshold = 0.001, window size = 1000 kb) as instrumental variables. When extracting information for instrumental variables from the outcome variable dataset, reverse SNPs with inconsistent allelic frequencies between the exposure and outcome datasets were removed. The instrumental variable effects for each SNP were evaluated using the F-statistic. SNPs with an F-value >10 were primarily chosen for subsequent MR analysis.[23] To satisfy the second and third assumptions, the MR-Egger method was ultimately employed, and horizontal pleiotropy testing of instrumental variables was conducted based on the MR-Egger regression intercept and corresponding P-value.
2.4. Statistical analysis
All MR analyses and visualizations were conducted using TwoSampleMR package in R software 4.3.0.[24] This study employed 5 distinct methodologies, namely the inverse-variance weighted (IVW) method, weighted median, weighted mode, simple mode, MR-Egger regression, and MR pleiotropy residual sum and outlier (MR-PRESSO) test, to evaluate the causal relationship between AR and the risk of hypertension.[25] The IVW method assumes all SNPs to be valid genetic instruments, thereby assuming no horizontal pleiotropy. The weighted median method allows for the presence of horizontal pleiotropy in instrumental variables but considers over 50% of SNPs as effective instruments.[26] The MR-Egger method permits the assessment of causal relationships even when all SNPs are invalid instrumental variables. The MR-PRESSO method offers a corrected estimate after eliminating outliers.[27]
Furthermore, to fulfill the second and third assumptions of MR analysis, Cochran Q test and global analysis using MR-PRESSO were conducted to examine the heterogeneity and presence of outliers in the instrumental variables.[28] Additionally, a leave-one-out sensitivity analysis was performed. Each instrumental SNP was sequentially removed, and the remaining SNPs were used for IVW causal association evaluation. An effect estimate crossing the zero point indicated the potential impact of the removed SNP on the MR analysis results.
3. Results
3.1. There was a causal relationship between AR and hypertension
Based on the selection criteria for instrumental variables in this study, 32 SNPs were identified as instrumental variables for analyzing the causal relationship between AR and hypertension risks. The F-statistic reveals that each SNP F-value exceeds 10, indicative of strong associations between each instrumental variable and the exposure, thereby ruling out weak instrument bias, as shown in Table 2.
Table 2.
Correlation between instrumental variables SNPs and AR.
| SNP | sd | R2 | F |
|---|---|---|---|
| rs72823641 | 0.855856392 | 0.00100861 | 113.6650084 |
| rs34290285 | 0.676181342 | 0.000702247 | 79.11520057 |
| rs9879150 | 0.620408897 | 0.000313463 | 35.30108594 |
| rs541115 | 0.62212012 | 0.000386627 | 43.54368414 |
| rs72669169 | 0.645792037 | 0.000521404 | 58.7307569 |
| rs5743618 | 0.687519033 | 0.000870999 | 98.14342527 |
| rs6871748 | 0.663511582 | 0.000725728 | 81.76257286 |
| rs4957317 | 0.639658477 | 0.000330097 | 37.17494524 |
| rs1898671 | 0.617899104 | 0.000567485 | 63.92425974 |
| rs7735355 | 0.8302518 | 0.000682827 | 76.92591934 |
| rs3129907 | 0.686519142 | 0.000695158 | 78.3160769 |
| rs3130235 | 0.81323352 | 0.00036862 | 41.51491216 |
| rs4538748 | 0.610769008 | 0.000311548 | 35.08532828 |
| rs7774620 | 0.594391598 | 0.000269572 | 30.35683542 |
| rs10245867 | 0.628431513 | 0.000316424 | 35.63457561 |
| rs9297768 | 0.628038938 | 0.000374286 | 42.1532375 |
| rs2066362 | 0.820219336 | 0.000365597 | 41.17429359 |
| rs1930778 | 0.617056913 | 0.000298579 | 33.62439663 |
| rs12782153 | 0.596851062 | 0.000283963 | 31.97794062 |
| rs7893324 | 0.833191077 | 0.000354129 | 39.88236987 |
| rs7936323 | 0.592069704 | 0.000716656 | 80.73967996 |
| rs11513729 | 0.607618345 | 0.000364318 | 41.03028912 |
| rs668622 | 0.596166573 | 0.000389183 | 43.83172237 |
| rs4759228 | 0.648238079 | 0.000340316 | 38.32614584 |
| rs7140939 | 0.610497226 | 0.000388534 | 43.7585144 |
| rs3540 | 0.633397415 | 0.000272667 | 30.7055463 |
| rs34753162 | 0.876729956 | 0.000308613 | 34.7547192 |
| rs56062135 | 0.695075257 | 0.000359925 | 40.53525377 |
| rs11644510 | 0.621334971 | 0.000467252 | 52.62825595 |
| rs71368508 | 2.084873459 | 0.000313852 | 35.34483906 |
| rs8067124 | 2.292277031 | 0.000594212 | 66.93670514 |
| rs3985697 | 0.774455867 | 0.000284579 | 32.04729414 |
| rs8125525 | 0.67724834 | 0.000368887 | 41.54494216 |
In our investigation, employing AR as the exposure variable and hypertension as the outcome variable, we conducted the MR analysis. We uncovered a distinct and compelling causal link between AR and hypertension using the IVW method (OR = 0.91, 95% CI: 0.86–0.98, P = .008), as detailed in Figure 2. The findings demonstrate a significant statistical significance in the causal relationship between AR and hypertension risks. Our study robustness was supported by the results of horizontal pleiotropy, reaffirming the validity of our MR approach. The results of the heterogeneity test reveal diversity among the variables (Cochran Q analysis: Q = 219.56, P < .05). However, this heterogeneity does not exert any influence on the Inverse IVW outcomes, thereby confirming the reliability of our conclusions (Table 3). The MR-Egger regression, in turn, allayed concerns of genetic pleiotropy-induced bias, as evidenced by the negligible intercept (-6.80E-04, P = .6947). Intriguingly, the “leave-one-out” analysis yielded no evidence of nonspecific SNP influences, thus fortifying the reliability of our findings (Fig. 3).
Figure 2.
MR analysis of the impact of AR on hypertension. OR, odds ratio; 95%CI, confidence intervals. AR = allergic rhinitis, MR = mendelian randomization.
Table 3.
Sensitivity testing (AR and hypertension).
| Exposure | Method | Q | Q_df | Pval | MR-Egger intercept | Se | Pval |
|---|---|---|---|---|---|---|---|
| AR | hypertension as the outcome | ||||||
| MR-Egger | 218.42 | 30 | 0 | - | - | - | |
| IVW | 219.56 | 31 | 0 | -6.80E-04 | 1.72E-03 | 6.95E-01 | |
| hypertension | AR as the outcome | ||||||
| MR-Egger | 379.45 | 219 | 0 | - | - | - | |
| IVW | 381.29 | 220 | 0 | 5.25E-04 | 5.10E-04 | 3.04E-01 |
In Cochran Q, the test showed heterogeneity (P < .05), and the MR-Egger intercept showed no horizontal pleiotropic effect (P > .05) during bidirectional Mendelian randomization Se, sample standard error; Egger_Intercept, intercept term (evaluate pleiotropy); Q, normalized weighted sum of squares; Q_df, degree of freedom.–, no data.
Figure 3.
The scatter plot/funnel plot and leave-one-out results of the MR analysis. (A) Scatter plot of causal effects of AR on hypertension risk. (B) Funnel plot of causal effects of AR on hypertension risk. (C) The results of “leave one method” sensitivity analysis of the causal effect of AR on hypertension risk. AR = allergic rhinitis.
3.2. Reverse MR analysis yielded no indication of reverse causality from hypertension to AR
After eliminating SNPs in linkage disequilibrium, a total of 232 SNPs associated with hypertension were selected as instrumental variables, ensuring the robustness of our study against weak instrument bias (F = 29.82~459.96). Following the harmonization of AR and hypertension data, a refined set of 221 SNPs was incorporated as instrumental variables for our investigation. Utilizing the IVW method, we found that hypertension does not confer an increased risk of arterial hypertension (AR) (OR = 0.98, 95% CI = 0.94~1.03, P = .44) (Fig. 4). Moreover, other analytical techniques yielded concordant results, reinforcing the notion that hypertension does not augment the risk of AR. Sensitivity analysis of the MR revealed heterogeneity among the SNPs (Cochran Q analysis: Q = 381.29, P < .05). Nevertheless, this heterogeneity did not impact the IVW results, thus underpinning the reliability of our conclusions (Table 3). The scatter plot results graphically exhibit the stability of SNPs closely associated with hypertension and AR. Furthermore, the funnel plot demonstrates the symmetry of SNPs, signifying the absence of pleiotropy in the MR analysis. The MR-Egger intercept test further accentuates that our study is devoid of horizontal pleiotropic effects (intercept value: 5.26E-04, P = .30). Employing the “leave-one-out” sensitivity analysis, we establish that no individual SNP significantly influences the overall outcomes, as depicted in Figure 5.
Figure 4.
MR analysis of the impact of hypertension on AR. OR, odds ratio; 95%CI, confidence intervals. AR = allergic rhinitis, MR = mendelian randomization.
Figure 5.
The scatter plot/funnel plot and leave-one-out results of the MR analysis. (A) Scatter plot of causal effects of hypertension on AR risk. (B) Funnel plot of causal effects of hypertension on AR risk. (C) The results of “leave one method” sensitivity analysis of the causal effect of hypertension on AR risk. AR = allergic rhinitis, MR = mendelian randomization.
4. Discussion
In this study, we conducted a bidirectional 2-sample MR analysis, employing genetic variation as a potent non-confounding instrument to delve into the intricate interplay between AR and hypertension. Our focus was the examination of the causal connection between AR and hypertension. Utilizing a suite of 5 complementary single-variable MR methodologies, each grounded on distinct potential assumptions, we unearthed compelling evidence suggesting that heightened genetic predisposition to AR exerts a mitigating influence on the risk of hypertension. Furthermore, through a comprehensive reverse MR analysis, we discerned no semblance of reverse causality emanating from hypertension to AR, thereby effectively negating any influence the latter may have over the former.
Involvement in research concerning Japanese adolescents reveals that the diastolic blood pressure of participants without nasal inflammation was higher than that of participants with nasal inflammation, aligning well with our findings.[29] However, Joachim Heinrich et al did not observe any correlation between AR and recorded blood pressure levels using data from a population-based sample of 896 subjects participating in the European Respiratory Health Survey and data from the “Monitoring of Trends and Determinants of Cardiovascular Diseases” study conducted in Erfurt, Germany.[30] Interestingly, Kony et al concluded that systolic blood pressure exhibited higher values in men affected by AR compared to those unaffected (130 ± 12.7 vs 123.5 ± 13.9 mm Hg, P = .002).[31] Nevertheless, in the replicative study conducted by Heinrich et al, no association was found between the 2 variables.[32] Our study provides genetic evidence to affirm AR can mitigate the risk of hypertension. While the precise mechanism through which AR achieves this effect remains unclear, previous research has proposed several potential underlying mechanisms. AR is a condition characterized by an excessive immune system response, primarily directed towards certain typically harmless substances (allergens). This results in an exaggerated immune reaction, leading to inflammation in the nasal cavity and sinuses.[33] Within this process, mast cell degranulation can release inflammatory mediators such as histamine. Histamine, being a potent vasodilator, can attenuate blood pressure.[34]
AR may have an impact on cardiovascular health by influencing the production and release of anti-inflammatory factors. Some studies suggest that AR patients might have higher levels of certain anti-inflammatory factors, such as IL-10, under certain circumstances. IL-10 is an anti-inflammatory cytokine that can alleviate inflammatory reactions and reduce the degree of immune system overactivity. By releasing more anti-inflammatory factors, AR might to some extent inhibit inflammatory responses,[35] thereby positively affecting cardiovascular health. The release of anti-inflammatory factors may have a protective effect on heart function. Reducing the level of inflammation helps maintain the health of blood vessels, reduces the risk of atherosclerosis and vascular damage, thus contributing to a lower risk of hypertension. Furthermore, some studies have suggested that AR patients may have lower levels of C-reactive protein (CRP) under certain circumstances. Lower CRP levels could indicate relatively milder inflammatory responses in AR patients, which might contribute to maintaining the health of blood vessels, potentially reducing the risk of hypertension.[32]
AR may impact the balance of the autonomic nervous system, thereby affecting the cardiovascular system. Autonomic dysfunction is involved AR patients, manifesting as reduced sympathetic nervous system activity and excessive parasympathetic nervous system activity.[32,33] Ozsutcu et al also assessed the autonomic nervous system function in perennial AR children using various heart rate measurement methods and found that these children had disrupted autonomic nervous system function, closely related to the severity of symptoms.[34] The reduction in sympathetic nervous system activity may lead to physiological effects such as slower heart rate and vasodilation, which could contribute to blood pressure reduction to some extent.[35]
This study employs a bidirectional 2-sample Mendelian randomization approach to systematically evaluate the reciprocal causal effects between AR and hypertension. The data sources are derived from large GWAS datasets, thereby ensuring sufficient statistical power. Furthermore, to mitigate potential bias stemming from pleiotropy, this investigation meticulously excludes SNPs displaying heterogeneity during the selection of instrumental variables. Employing an array of methodologies, including Mendelian randomization analysis and pleiotropy assessment, effectively bolsters the credibility of our findings. Hence, in contrast to observational and randomized controlled trials, the analytical methods employed in this study precisely pinpoint disease risk factors with enhanced accuracy and effectiveness. Nevertheless, our investigation has certain limitations. Firstly, the participant cohort is exclusively sourced from the GWAS database representing European ancestry, thereby constraining the extrapolation of the results. Augmenting the dependability of the findings necessitates the execution of meticulous data analyses and comparisons encompassing populations of varied ethnicities. Consequently, the veracity of the inferred causal associations must be corroborated across diverse populations. Secondly, the publicly available GWAS data on AR and hypertension lack information on specific characteristics such as age. The incorporation of such nuanced variables could substantially contribute to the fine-tuning of AR and hypertension classifications, thereby elevating precision while concurrently mitigating the influence of confounding variables. It is imperative to acknowledge that the process of data accrual may be susceptible to selective biases, potentially resulting in the preferential inclusion of participants from specific typologies, thereby exerting influence on the generalizability of outcomes. Thirdly, while we establish an association between AR and hypertension, we are unable to discern the specific subtype of hypertension linked to AR, owing to the absence of subgroup data. Additionally, the inclusion of a limited number of SNPs exclusive to certain diseases may introduce a degree of uncertainty into the confidence of the results. Therefore, the causal relationships between AR and the risk of hypertension development requires further research.
5. Conclusion
In conclusion, this study utilizes a bidirectional 2-sample Mendelian randomization framework and the statistical results data of GWAS to conduct a comprehensive assessment of causal effect between AR and hypertension. We compellingly indicate a significant causal relationship between AR and an reduced risk of hypertension. In contrast, no evidence supports that hypertension affects the risk of AR, either positively or negatively. The findings suggest a potential reduction in the risk of hypertension associated with AR. However, these outcomes warrant further experimental validation, followed by an in-depth exploration of the underlying molecular mechanisms. This groundwork not only holds promise for refining early screening methods for hypertension but also serves as a foundational step toward potential drug target discovery.
Acknowledgments
The authors wish to express their gratitude to the IEU and GWAS catalog databases for generously providing the platforms, as well as to the dedicated contributors who uploaded their invaluable datasets. We acknowledge all the workers involved in study searching, data extraction, statistical analysis and writing.
Author contributions
Conceptualization: Yanhua Zhang, Xia Li, Youdong Yang.
Data curation: Yanhua Zhang.
Methodology: Zhizhou Song.
Project administration: Youdong Yang.
Software: Yanhua Zhang.
Supervision: Xia Li, Youdong Yang.
Writing – original draft: Yanhua Zhang.
Writing – review & editing: Xia Li, Zhizhou Song, Youdong Yang.
Abbreviations:
- AR
- allergic rhinitis
- CI
- confidence interval
- GWAS
- genome-wide association study
- IVW
- inverse-variance weighted
- MR
- mendelian randomization
- MR-PRESSO
- MR pleiotropy residual sum and outlier
- OR
- odds ratio
- SNPs
- single nucleotide polymorphisms
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
The authors have no funding and conflicts of interest to disclose.
Ethical approval was not required since this study used datasets from publicly available databases.
How to cite this article: Zhang Y, Li X, Song Z, Yang Y. Association between allergic rhinitis and hypertension risk: A bidirectional 2-sample mendelian randomization study. Medicine 2023;102:50(e36700).
Contributor Information
Yanhua Zhang, Email: 827578421@qq.com.
Xia Li, Email: lixia@sxtcm.edu.cn.
Zhizhou Song, Email: songzhizhou@163.com.
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