东亚人群肠道菌群、血液代谢物与荨麻疹的因果关联：一项孟德尔随机化研究

Causal relationships among gut microbiota, blood metabolites, and urticaria in East Asians: A Mendelian randomization study

摘要

目的 肠道菌群和血液代谢物与荨麻疹的发展有关，但在东亚人群中的具体因果关系尚不完全清楚。本研究拟使用孟德尔随机化(Mendelian randomization，MR)分析来阐明东亚人群中肠道菌群、血液代谢物与荨麻疹之间的因果关系和中介效应。 方法 从公开的全基因组关联研究(Genome-Wide Association Studies，GWAS)数据集中收集500种肠道菌群、112种血液代谢物和荨麻疹的汇总统计数据。使用双向MR分析探索肠道微生物群和血液代谢物与荨麻疹之间的因果关系。采用逆方差加权(inverse variance weighted，IVW)法作为主分析方法，MR-Egger、加权中位数法、简单模式法、加权模式法作为补充分析，异质性、水平多效性和留一分析进行敏感性分析。采用中介分析评估血液代谢物在肠道菌群和荨麻疹因果途径中的潜在中介作用。 结果 MR分析结果显示：有12种肠道菌群与荨麻疹有因果关联，9种肠道菌群，如MF0017_半乳糖降解(OR=1.461，95% CI 1.098~1.944，P=0.009)丰度的增加是荨麻疹的危险因素。3种肠道菌群，如MF0001_阿拉伯木聚糖降解(OR=0.846，95% CI 0.737~0.973，P=0.019)丰度增加是荨麻疹的保护因素。此外，6种血液代谢物与荨麻疹有因果关联，其中，荨麻疹的发病风险随空腹血糖(fasting plasma glucose，FPG)的升高而升高(OR=1.971，95% CI 1.089~3.567，P=0.025)。中介分析结果表明FPG介导MF0001_阿拉伯木聚糖降解对荨麻疹的影响，解释了11.30%的影响。 结论 本研究发现了东亚人群中与荨麻疹相关的特定肠道菌群和血液代谢物，其中阿拉伯木聚糖降解可能通过降低FPG来减轻荨麻疹的风险。这为通过调节肠道菌群和血糖管理干预荨麻疹的发生提供了遗传学依据。

Abstract

Objective Gut microbiota (GM) and blood metabolites are associated with the development of urticaria, yet their specific causal relationships in East Asian populations remain unclear. This study aims to elucidate the causal and mediating relationships among GM, blood metabolites, and urticaria in East Asians using Mendelian randomization (MR) analysis. Methods Summary-level statistics for 500 GM taxa, 112 blood metabolites, and urticaria were obtained from publicly available Genome-Wide Association Studies (GWAS) datasets. Bidirectional MR analyses were performed to examine causal associations among the GM, blood metabolites, and urticaria. The inverse variance weighted (IVW) method served as the primary analytical approach, supplemented by MR-Egger, weighted median, simple mode, and weighted mode methods. Sensitivity analyses included heterogeneity tests, horizontal pleiotropy assessments, and leave-one-out analyses. Mediation analysis was conducted to evaluate the potential mediating effects of blood metabolites on the causal pathways between GM and urticaria. Results MR analyses identified 12 GM taxa exhibiting significant causal effects on urticaria susceptibility. Nine taxa, such as MF0017_galactose_degradation (OR=1.461, 95% CI 1.098 to 1.944, P=0.009), were associated with increased urticaria risk. Three taxa, such as MF0001_arabinoxylan_degradation (OR=0.846, 95% CI 0.737 to 0.973, P=0.019), showed protective effects with increased abundance. Additionally, 6 blood metabolites demonstrated causal associations with urticaria. Notably, the risk of developing urticaria increases with rising fasting plasma glucose (FPG) levels (OR=1.971, 95% CI 1.089 to 3.567, P=0.025). Mediation analysis further demonstrated that FPG partially mediated the protective effect of MF0001_arabinoxylan_degradation on urticaria, accounting for 11.30% of the total effect. Conclusion This study has delineated specific GM taxa and blood metabolites that hold causal relevance to urticaria in East Asian populations. Notably, arabinogalactan degradation potentially mitigates urticaria risk via reducing FPG concentrations, offering genetic evidence to support therapeutic strategies targeting GM modulation and glucose regulation.

Graphical abstract

关键词

荨麻疹 / 肠道菌群 / 血液代谢物 / 孟德尔随机化 / 中介分析

Key words

urticaria / gut microbiota / blood metabolites / Mendelian randomization / mediation analysis

Urticaria is a common inflammatory skin condition characterized by symptoms such as wheals, angioedema, or both^[1]. Clinically, it is differentiated into acute urticaria (AU), lasting 6 weeks or less, and chronic urticaria (CU), persisting for periods exceeding 6 weeks and potentially much longer^[2]. Patients frequently experience significant negative impacts on life quality, including disruptions in sleep, decreased work productivity, impaired sexual health, and deterioration of both emotional and physical health^[3-4]. The involvement of mast cells in urticaria pathogenesis is well-recognized, mainly mediated through immunoglobulin (Ig)E and IgG autoimmune reactions, which individually or jointly trigger mast cell activation and subsequent degranulation in the skin in over 50% of cases^[5-6]. Nonetheless, comprehensive details regarding urticaria’s underlying mechanisms remain incomplete.

The human body hosts an extensive array of microorganisms collectively known as the microbiome, with the gastrointestinal tract being particularly abundant, containing around 100 trillion microorganisms^[7-8]. Emerging evidence indicates that alterations in gut microbiota (GM) may be implicated in urticaria pathogenesis^[9]. Researches^[10-11] have consistently shown significant deviations in GM composition among urticaria patients, characterized predominantly by reduced bacterial diversity^[12]. Alterations in microbiome composition could reduce short-chain fatty acids (SCFAs) synthesis, possibly intensifying mast cell-driven inflammatory reactions within the skin^[12-13]. Additionally, several studies^[14-15] have associated microbiota changes with urticaria severity, inflammation intensity, duration, and response to treatment. However, precise causal links between GM and urticaria have not yet been clearly elucidated, indicating the necessity for further investigation.

Metabolomics involves the comprehensive analysis of small molecular compounds that play pivotal roles in metabolic pathways, aiming to detect and quantify metabolites to identify disease biomarkers for diagnostic and prognostic purposes^[16-18]. Earlier study^[12] has highlighted substantial disruptions in serum metabolite profiles in urticaria patients, particularly polyunsaturated fatty acids (PUFAs), arachidonic acid (ARA), and docosahexaenoic acid (DHA).

Mendelian randomization (MR) is a sophisticated analytical technique leveraging genetic variants as instrumental variables (IVs) to explore causal influences of modifiable risk factors on disease outcomes^[19-20]. Random allocation of genetic variants in MR investigations helps mitigate biases from confounders and reverse causality, thus offering credible insights into genetic correlations between risk factors and disease conditions^[21].

To date, there has been insufficient evidence demonstrating the causal interactions among GM, blood metabolites, and urticaria, specifically within East Asian cohorts. Moreover, the exact mechanisms through which GM variations influence blood metabolites and thereby contribute to urticaria development remain unclear. This study aims to elucidate the causal relationships among GM, blood metabolites, and urticaria specifically within East Asian populations, additionally exploring the mediating roles of blood metabolites. Ultimately, the goal is to uncover potential new therapeutic targets to improve urticaria management.

1 Materials and methods

1.1 Study design

This study used MR analysis to look for connections between urticaria, GM, and metabolites in the bloodstream. The intravenous markers used were single nucleotide polymorphisms (SNPs). The MR methodology relies on 3 essential assumptions: Firstly, that the IVs have a direct correlation with the exposure (GM). Secondly, that the IVs are not affected by potential confounders. Thirdly, that the IVs only affect the outcome (urticaria) through the designated exposure, without any other pathways^[19]. Figure 1 shows the general outline of the study.

1.2 Overview of Genome-Wide Association Studies

Genome-Wide Association Studies (GWAS) provided the data on GM and blood metabolites, sourced from large-scale datasets encompassing 2 002 blood samples and 1 539 fecal samples from Chinese individuals^[22]. The fecal samples were processed utilizing the MGIEasy kit, with DNA extraction performed according to the MetaHIT standard protocols. The dataset comprised extensive whole-genome sequencing information derived from 2 002 blood samples, yielding GWAS outcomes for 500 GM taxa and 112 blood metabolites. Summary-level GWAS data related to urticaria, including 9 893 cases alongside 162 190 controls, were obtained from a recent Meta-analysis^[23] collaboration involving the Biobank of Japan (BBJ).

1.3 Identification of IVs

Initially, genetic variants demonstrating associations with the exposure were identified to satisfy MR criteria. While increasing the number of IVs enhances statistical power, excessive IVs can introduce multiplicity bias^[24]. Consequently, due to typically modest GWAS sample sizes for GM and blood metabolites^{[22, 25]}, forward MR analyses selected IVs using a significance threshold of P<1×10^-5. Conversely, for reverse MR analyses, SNPs significantly associated with urticaria (P<5×10^-8) were utilized. Independent SNPs were identified through linkage disequilibrium (LD) pruning using criteria of r²<0.001 and a clumping window less than 10 Mb^[26]. Subsequently, the strength of each IV was determined by computing F-statistics using the formula [(N-K-1)/K]×[R²/(1-R²)], where N denotes the sample size of the exposure, K represents the number of IVs, and R² indicates the variance explained by the IVs. SNPs with an F-statistic below 10 were discarded, as those with values exceeding 10 are considered strong instruments^[27].

1.4 Two-sample MR analysis

The primary analytical method employed to assess causal relationships among urticaria, GM, and blood metabolites was the inverse variance weighted (IVW) method, which synthesizes Wald ratios from individual SNPs into an aggregate causal estimate. MR-Egger, weighted median, simple mode and weighted mode analyses were additionally conducted to further substantiate causal inferences between urticaria and GM or metabolites.

1.5 Mediation analysis

To evaluate the mediating role of blood metabolites in associations between GM and urticaria, a two-step MR mediation analysis was implemented. Figure 1 provides a schematic representation of this analysis, indicating β1 for the GM-to-metabolite pathway, β2 for the metabolite-to-urticaria relationship, and β3 for the direct GM-to-urticaria association. The mediation effect was quantified as the product of coefficients (β1×β2), while the proportion mediated was determined by dividing this indirect effect by the total effect (β1× β2)/β3^[28].

1.6 Sensitivity analysis

Several sensitivity analyses were undertaken to ensure MR result reliability, encompassing assessments of heterogeneity, horizontal pleiotropy, and leave-one-out procedures. Heterogeneity was examined via Cochran’s Q statistic, whereas MR-Egger regression intercept tests were utilized to detect potential pleiotropy. Additionally, leave-one-out analyses sequentially excluded each SNP to evaluate individual influences on the overall outcomes.

1.7 Statistical analysis

All statistical analyses were performed using R software (version 4.2.3), specifically employing the TwoSample MR package. A statistical significance level was defined as P<0.05, with false discovery rate (FDR) adjustments applied to analyses involving GM and metabolites. Findings were classified as strong evidence when FDR<0.05, and suggestive evidence when FDR ranged from 0.05 to 0.20^[29-30].

2 Results

2.1 Overall causal impact of GM on urticaria

The MR analysis identified 12 GM taxa significantly or suggestively linked with urticaria risk (Figure 2 and Figure 3). Among these, 9 taxa emerged as risk factors. Specifically, elevated levels of MF0017_galactose_degradation corresponded to a 46.1% higher likelihood of urticaria (OR=1.461, 95% CI 1.098 to 1.944, P=0.009). Additionally, increased abundance of eight other taxa, including MF0080_lactate consumption_II, s_Bifidobacterium_longum, s_Butyrivibrio_crossotus s_unclassified_Prevotella_sp_oral_taxon_472, s_Lactobacillus_ruminis, MF0102_sulfate_reduction_dissimilatory, s_Bifidobacterium_catenulatum-Bifidobacterium_pseudocatenulatum_com-plex, and g_Citrobacter were associated with enhanced urticaria risk. In contrast, 3 microbiota taxa exhibited protective effects. Notably, increased abundance of MF0001_arabinoxylan_degradation (OR=0.846, 95% CI 0.737 to 0.973, P=0.019) significantly lowered urticaria risk. Moreover, s_Desulfovibrio_alaskensis and s_Bifidobacterium_animalis also exhibited protective associations.

After FDR adjustment of GM characteristics derived from the IVW method, 11 taxa presented strong evidence (FDR<0.05), while MF0017_galactose_degradation showed suggestive evidence (FDR<0.2; Supplementary Table 1, https://doi.org/10.57760/sciencedb.30157). Reverse MR analysis revealed causal relationships of urticaria with 8 GM taxa (Supplementary Table 2, https://doi.org/10. 57760/sciencedb.30157). In subsequent mediation analysis, taxa that exhibited reverse causal effects were removed. In the sensitivity analysis, the Cochran’s Q test showed no substantial heterogeneity (Q_IVW=1.417 to 23.365, P_IVW=0.143 to 0.965, Q_Egger=1.414 to 23.144, P_Egger=0.110 to 0.954; Supplementary Table 3, https://doi.org/10. 57760/sciencedb.30157). The MR-Egger intercept ranged from -0.0125 to 0.0115 (P=0.358 to 0.973), ruling out horizontal pleiotropy (Supplementary Table 3, https://doi.org/10.57760/sciencedb.30157). Leave- one-out analysis further demonstrated no individual SNP significantly impacted the overall causal associations between GM and urticaria (Supplementary Figure 1, https://doi.org/10. 57760/sciencedb.30157).

2.2 Overall causal impact of blood metabolites on urticaria

The MR analysis identified associations between 6 blood metabolites and urticaria risk within the East Asian population (Figure 4 and Figure 5). Increased susceptibility to urticaria was associated with elevated levels of fasting plasma glucose (FPG), low-density lipoprotein cholesterol (LDL-C), and hydrocortisone. Notably, heightened FPG concentrations were linked to approximately double the risk of developing urticaria (OR=1.971, 95% CI 1.089 to 3.567, P=0.025). Conversely, increased concentrations of deoxycortisol, cadmium, and 1-methylhistidine exhibited inverse relationships with urticaria risk. After applying FDR adjustments, FPG, 1-methylhistidine, and deoxycortisol presented strong evidence (FDR<0.05), whereas the other three metabolites displayed suggestive evidence (FDR<0.20) (Supplementary Table 4,https://doi.org/10. 57760/sciencedb.30157). Reverse MR analysis revealed causal relationships of urticaria with 5 blood metabolites (Supplementary Table 5, https://doi.org/10.57760/sciencedb. 30157). Sensitivity analyses, including Cochran’s Q test, indicated no substantial heterogeneity between blood metabolites and urticaria (Q_IVW=1.723 to 30.193, P_IVW=0.134 to 0.988, Q_Egger=1.599 to 29.291, P_Egger=0.107 to 0.979; Supplementary Table 6, https://doi.org/10. 57760/sciencedb.30157). Moreover, MR-Egger intercept values varied from -0.0120 to 0.0096, with corresponding P-values between 0.367 and 0.890, indicating no substantial evidence for horizontal pleiotropy (Supplementary Table 6, https://doi.org/10.57760/sciencedb.30157). Leave-one-out analyses further confirmed the stability of causal associations, as no single SNP significantly altered the overall outcomes (Supplementary Figure 2, https://doi.org/10.57760/sciencedb.30157).

2.3 Mediation analysis

An MR-based mediation analysis was conducted to explore potential mediating effects involving GM, blood metabolites, and urticaria (Figure 6; Supplementary Table 8, https://doi.org/10.57760/sciencedb.30157). Initially, MR analyses identified 4 significant associations between GM and urticaria-related metabolites (Supplementary Table 7, https://doi.org/10.57760/sciencedb.30157). Subsequent mediation analyses revealed a significant mediation pathway where fasting plasma glucose mediated the relationship between MF0001_arabinoxylan_degradation and urticaria (β=-0.0189), accounting for 11.30% of the total observed effect.

3 Discussion

This study investigated the causal interplay among GM, blood metabolites, and urticaria. Utilizing MR techniques, this study established 12 causal links between specific GM taxa and urticaria risk, along with 6 associations involving blood metabolites, within an East Asian population. Additionally, blood metabolites were shown to mediate connections between GM and urticaria, underscoring the complexity of these biological relationships.

Previous studies^[31-32] emphasizes that GM diversity plays an essential role in systemic immune regulation, particularly through enhancing regulatory T-cell functions, promoting immune tolerance, and generating beneficial metabolites, notably SCFAs. Animal experiments indicate that certain Lactobacilli strains can significantly enhance skin condition, reinforcing the “gut-skin axis” hypothesis. Moreover, CU patients reportedly exhibit decreased abundance of beneficial bacterial taxa such as Acinetobacter, Clostridium leptum, Faecalibacterium prausnitzii, Entero-bacteriaceae, Lactobacilli, and Bifidobacteria^{[12, 33]}.

Our analysis identified specific GM, including MF0017_galactose degradation, MF0080_lactate consumption II, and s_Bifidobacterium longum, as risk factors for urticaria. In contrast, MF0001_arabinoxylan degradation, s_Bifidobacterium animalis, and s_Desulfovibrio alaskensis exhibited protective effects. Previous research established that galactose-α-1,3-galactose (alpha-gal), an allergen introduced through tick bites, is significantly associated with delayed urticaria and allergic reactions^[34]. Notably, our findings revealed MF0001_arabinoxylan degradation as having the strongest protective effect, reducing urticaria risk by 15.4%. Earlier findings^[35-36] have indicated that arabinoxylan enhances SCFAs production, which in turn reduces Th2-mediated immune responses by activating G protein-coupled receptors and facilitating regulatory T-cell differentiation. Additionally, arabinoxylan induces “trained immunity” within human macrophage-intestinal epithelial co-culture systems by activating the Dectin-1 receptor and stimulating cytokine production, including tumor necrosis factor-alpha (TNF-α), thereby strengthening immune adaptability and resilience^[37].

Our study observed a reduced abundance of Bifidobacterium animalis and increased lactate consumption in urticaria cases. Previous study^[38] has demonstrated protective effects of Lactobacilli and Bifidobacteria in CU. Bifidobacteria may exert a protective effect by regulating the Th1/Th2 immune balance^[39]. However, other study^[40] has reported no significant impact of probiotics on allergic disease incidence or atopic sensitization. The effects of Bifidobacteria and Lactobacilli on allergic diseases, including urticaria, may differ across populations and microbiota compositions. Additionally, our results indicated that certain intestinal bacteria (e.g., g_Citrobacter) were positively correlated with urticaria, but the corresponding odds ratios were relatively low, and their direct or indirect relationships with urticaria have not been reported. Therefore, further studies are required to investigate the roles of these bacteria in urticaria. Moreover, after FDR adjustment, MF0017_galactose_degradation showed a suggestive association with urticaria, warranting additional research. In conclusion, current knowledge regarding GM taxa associated with urticaria remains limited, highlighting the need for further clinical and experimental validation.

Our study also uncovered significant causal relationships between 6 blood metabolites and urticaria susceptibility among East Asian individuals. Prior study^[41] linked several serum metabolites with urticaria, with recent metabolomics research identifying maleic acid and pyruvate as biomarkers capable of predicting disease activity, therapeutic response, and prognosis in CU patients. Specifically, our results showed a robust positive association between elevated FPG and urticaria risk, with a 1.971-fold increase. Diabetic patients typically exhibit increased skin mast cell density, potentially attributed to oxidative stress induced by hyperglycemia^[42-43]. Moreover, a cross-sectional analysis^[44] indicated higher FPG levels were associated with elevated risks of allergic symptoms and specific allergen sensitization. LDL-C was also determined as a risk factor for urticaria, consistent with previous evidence demonstrating that pro-inflammatory cytokines (e.g., IL-6 and TNF-α) secreted by visceral adipose tissue facilitate mast cell activation and histamine release^[45]. Our results also indicated that 1-methylhistidine has a minor protective effect on urticaria. The association between 1-methylhistidine and urticaria has not been previously reported, requiring additional studies for validation. After FDR adjustment, cadmium, hydrocortisone, and LDL-C showed suggestive associations necessitating further investigation into their relationships with urticaria.

To better understand how GM influence urticaria, we investigated the critical mediating role of blood metabolites. Our findings suggest that FPG mediates 11.30% of the relationship between MF0001_arabinoxylan degradation and urticaria. Previous study^[46] reported a 6% to 20% prevalence of metabolic syndrome among urticaria patients. Metabolic syndrome, characterized by elevated FPG and obesity, is frequently linked to GM dysbiosis^[47] and abnormal lipid metabolism^[48], implying these factors may collectively contribute to urticaria onset. Arabinoxylan provides health benefits, including immune modulation^[37], antioxidant activity^[49], glucose regulation^[50], and GM balancing^[51]. Prior research^[50] has shown that arabinoxylan fermentation produces SCFAs, especially butyrate and propionate, which enhance insulin sensitivity and mitigate blood glucose elevation. Elevated FPG promotes the formation of advanced glycation end products (AGEs)^[52], activating the nuclear factor kappa-B (NF-κB) pathway, and subsequently induces pro-inflammatory cytokines (TNF-α and IL-6) release^[53]. The activation of the NF-κB pathway may cause mast cells to degranulate and induce the occurrence of urticaria^[54]. Thus, MF0001_arabinoxylan degradation may reduce urticaria risk by inhibiting FPG elevation. However, given that FPG only partially mediates this relationship (11.30%), other undiscovered mechanisms likely exist and warrant further exploration.

MR analysis is a robust method for identifying causal relationships between exposures and outcomes while accounting for potential confounding variables. This study underscores several significant strengths of MR analysis, particularly its ability to provide novel evidence supporting causal associations between GM and urticaria among East Asian populations. These results offer a foundation for future investigations into the regulatory roles of specific bacterial strains in atopic diseases and the mediating effects of blood metabolites. Additionally, our findings were consistent across 5 analytical methods, and sensitivity analyses confirmed the reliability of causal estimates.

Nevertheless, our study has certain limitations. First, our data were derived exclusively from East Asian populations, potentially restricting generalizability to other ethnic groups. Second, despite employing rigorous selection criteria for eligible SNPs to minimize confounding and horizontal pleiotropy, we cannot fully eliminate pleiotropy, as many genetic variants lack clear biological functions. Furthermore, our conclusions remain theoretical and require empirical validation through additional experimental and clinical studies.

In summary, this study clarified causal relationships among GM, blood metabolites, and urticaria, identifying 12 GM taxa and 6 blood metabolites linked causally to urticaria risk. Furthermore, arabinogalactan degradation potentially mitigates urticaria risk via reducing FPG concentrations. These findings offer compelling genetic support for these relationships and suggest that controlling blood glucose levels and employing probiotics for targeted microbiota modulation could represent valuable supplementary treatment approaches for managing urticaria.

Contributions: HUANG Yuzhou Data collection, data analysis, and manuscript drafting; Wang Dan Data collection and manuscript drafting; LU Jianyun Study design, manuscript drafting and modifying. The final version of the manuscript has been approved and read by all authors.

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基金资助

the Natural Science Foundation of Hunan Province, China(2024JJ7627)

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Open access: This is an open access article under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International(https://creativecommons.org/licenses/by-nc-nd/4.0/)

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