Introduction

Allergies conjunctivitis as a major challenge of healthcare

Allergic conjunctivitis is one of the most common allergic diseases affecting 10–20% of the population [1]. They are induced by the ocular reaction to environmental allergens and come in many forms. Allergic conjunctivitis usually causes itching, redness, and swelling symptoms, impacting the quality of life and being an economic burden [2]. Some severe forms can negatively impact vision when corneal scarring and pannus develop. As a T helper 2 (Th2) paradigm disease, the allergen reaches the conjunctiva and causes a response in persons with allergic conjunctivitis: Th2 cells secrete cytokines that activate immunoglobulin E (IgE), which binds to the membranes of mast cells and allergen and stimulates the release of inflammatory mediators [3]. Currently, the management of allergic conjunctivitis begins with non-pharmacological treatments and progresses to pharmacological treatments, such as antihistamines, mast cell stabilizers, corticosteroids, and other types of immune-therapy. Identifying the immunological factors associated with allergic conjunctivitis and developing advanced interventions is crucial. This can lead to the discovery of specific immune-related indicators for allergic conjunctivitis, which can strongly encourage the transition from reactive to predictive, preventive, and personalized medicine (PPPM) [4].

Gut microbiota serves as the hub in holistic PPPM approach

Recently, the human gut microbiota’s role as a host partner has been acknowledged [5]. The microbiota in the gut, which are thought to constitute a new organ, influence metabolism and other organs such as the brain, skin, lungs, and liver, by the microbiota and their metabolites [6]. It has been shown that eubiosis has a beneficial effect on human health and has an anti-inflammatory nature. In contrast, microbial dysbiosis may trigger an inflammatory response through Th1, Th2, and Th17 cells [7]. There have been new studies between microbial dysbiosis with allergic diseases. Infants who were given antibiotics in the first 6 months of their lives were more likely to develop allergies later in childhood. This included a greater risk of developing food allergy, food allergy, anaphylaxis, asthma, atopic dermatitis, allergic rhinitis, allergic conjunctivitis, urticaria, contact dermatitis, medication allergy, and other allergies [8]. However, additional allergy symptoms, such as allergic conjunctivitis, may be mitigated by administering a probiotic supplement containing the Lactobacillus rhamnosus GG in the form of an extensively hydrolyzed casein formula [9]. Moreover, probiotics supplementation is believed to prevent allergic disease via improving intestinal barrier mechanisms, modulating the immune system towards anti-inflammatory response, and synthesizing beneficial anti-inflammatory metabolites [10]. Thus far, several studies have established and analyzed the difference in gut microbiota in some allergic diseases compared with healthy population, such as allergic asthma and allergic dermatitis [11, 12]. Nonetheless, there is no study elucidate the genus associated with allergic conjunctivitis by predictive, preventive, and personalized approach.

Mendelian randomization method helps to implement PPPM

Microorganisms of all shapes and sizes, including bacteria, eukarya, archaea, viruses, and parasites, are found in the human gut microbiota, with the greatest number of microbes in the human body. Gut microbiota composition and function may be altered by various host factors, including but not limited to food, age, delivery method, geographical impacts, and drug [13]. Therefore, small observational studies make it difficult to interpret and compare the microbiota between healthy individuals and disease states. Mendelian randomization (MR) is a widely used method to assess causal relationships by exploiting genetic variants as instrumental exposure variables, which overcomes the bias due to most acquired confounding factors [14]. Some host genetic variations have been shown in recent studies to affect the gut microbiota’s composition and function [15]. Evidence linking gut microbiota to immunological and inflammatory diseases such as osteoarthritis, systemic lupus erythematosus, and chronic widespread pain has been derived using MR [16,17,18]. This study aims to establish a causal relationship between specific gut microbiota and allergic conjunctivitis using MR analysis. Through the lens of PPPM, understanding the role of gut microbial imbalance in the development of allergic conjunctivitis and identifying allergic conjunctivitis-related gut microbiota can aid in early screening of high-risk individuals, timely implementation of targeted prevention, and personalized clinical therapy to alleviate inflammatory responses and allergic symptoms, improve quality of life, and reduce economic burden.

Working hypothesis in the framework of PPPM

In this study, we hypothesize that individuals with microbial dysbiosis may have a higher incidence of allergic conjunctivitis due to the triggering of an inflammatory response and the induction of an imbalance in the immune system, resulting in the activation of Th2 cells with varying levels of severity. Additionally, our analysis aims to identify specific gut microbial genera that may contribute to the onset of allergic conjunctivitis, and potentially provide new indicators for this condition. To test our hypothesis, our analysis selected genetic variants associated with gut microbiota features (N = 18,340) and allergic conjunctivitis (4513 cases, 649,376 controls). We performed a two-sample MR to assess the impact of gut microbiota on the risk of developing allergic conjunctivitis.

Methods

Ethics approval

The published or publicly available data were not involved in primary studies. Nonetheless, each study’s ethical clearance may be found in corresponding primary articles. Furthermore, the 1975 Declaration of Helsinki was adhered to throughout all research projects to ensure ethical conduct.

Assessment of assumptions

The valid genetic instrumental variables (IVs) in the MR study must fulfill the 3 assumptions [19] (Fig. 1): (1) The IVs must be associated with gut microbiota. (2) The IVs must not be associated with factors that confound the relationship between gut microbiota and allergic conjunctivitis. (3) The IVs are only associated with allergic conjunctivitis through gut microbiota.

Fig. 1
figure 1

Acyclic graph interpretation of Mendelian randomization analysis

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The data source for gut microbiota

Genome-wide association studies (GWAS) by Kurilshikov et al. provided the gut microbiota genetic variations used here [20]. The MiBioGen consortium was used for this GWAS investigation, and it included 18,340 participants from 24 cohorts in the USA, Canada, Israel, South Korea, Germany, Denmark, the Netherlands, Belgium, Sweden, Finland, and the UK. By comparing GM taxa variation across several populations, the GWAS investigation uncovered a total of 122,110 variant sites representing 211 taxa across five taxonomic levels (phylum, class, order, family, genus), whereas 15 bacterial taxa of these 211 were unknown. Thus, we analyzed the 196 taxa which were already known. We used this massive GWAS to get IVs of GM taxa; further information about the GM data could be obtained in the corresponding original articles.

Selection of genetic instruments

The gut microbiota–related single nucleotide polymorphisms (SNPs) were screened to get the required IVs. First, there was a locus-wide significance (P<5×10−5) for the SNPs related to the gut microbiota. Additionally, SNPs with linkage disequilibrium (LD) were removed (R2 <0.001) in the LD data from the 1000 Genomes Project [21]. Furthermore, we eliminated SNPs that included palindromes. The F-statistic was then utilized to exclude low-powered IVs (F<10). Finally, all SNPs were analyzed using MR Steiger, and the SNPs potentially leading to causation were included.

The data source for allergic conjunctivitis

We got the summary statistics for allergic conjunctivitis from the GWAS conducted by Sakaue et al [22]. This GWAS data came from 475,270 people in Europe and 178,619 people in East Asia. There were 4513 cases of allergic conjunctivitis (613 European origin cases and 3,900 East Asian origin cases) and 649,376 controls (474,657 European origin controls and 174,719 East Asian origin controls) used for the analysis, with the data normalized by age, sex, genetic relatedness, genotyping batch, and the first 10 principal components.

Sensitivity analysis

We applied sensitivity analysis to test and correct for horizontal pleiotropy and heterogeneity and examine the robustness of the MR estimates. Unbalanced pleiotropic effects on the result were first evaluated using MR-Egger’s intercept values [23]. The closer the intercept to zero, the lower the unbalanced pleiotropic was considered. Meanwhile, SNPs with anomalies were filtered out using MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), a method for assessing the pleiotropy of causative SNPs [24]. To determine heterogeneity, however, we employed Cochran’s Q test [25]. After completing the analysis, the leave-one-out test was used to evaluate the results’ robustness further [16].

Statistical method

Both the “Two Sample MR” and “MR-PRESSO” packages in R software (version 1.4.1717) were used to estimate the MR and sensitivity findings. A causal impact of individual SNPs was evaluated using the Wald ratio. Inverse variance weighting (IVW) was the main method to obtaining a global estimate as long as sensitivity analysis was successful. Additionally, the findings of IVW were analyzed using the weighted median (WM) estimator and the MR-Egger. The WM estimator provided a consistent estimate when over 50% of the weight came from valid IVs [26]. For the MR-Egger, it allows for little evidence of a violation of the IV3 assumption (instrumental variable assumption 3), which means permitting a low degree of evidence of the pleiotropic effects and still obtaining an unbiased causal estimate [27]. However, its statistical power decreased. Thus, it is generally believed that the results of IVW are the most meaningful when passing the sensitivity analysis. Additionally, we employed the maximum likelihood estimator (MLE) [28] and MR robust adjusted profile score (MR.RAPS) [29] to validate MR results. MLE assumes the linear correlation of allergic conjunctivitis and each gut microbiota taxa with normal distribution and allows for uncertainty in both gene–gut microbiota taxa and gene–allergic conjunctivitis associations. MR.RAPS was calculated for the causal estimate to provide higher statistical power if weak IVs existence. Consequently, all valid SNPs’ combined MR estimates were shown as a circular map. The MR findings were presented using odds ratio (OR) and confidence interval (CI). Assuming a significance level of P < 0.05, we inferred the possibility of a causal relationship.

Results

Instrumental variable selection

Using the MiBioGen consortium, we identified 2166 SNPs as IVs linked with 196 bacterial taxa for allergic conjunctivitis (P<1×10−5); quality control processes via LD effects and palindromic were performed to ensure their accuracy. There were 9 phyla, 16 classes, 20 orders, 32 families, and 119 genera. The F values for each SNP varied from 14.59 to 88.43, demonstrating that they all had sufficient validity. Supplementary Table 1 displays the most crucial data for all IVs.

Causal associations of gut microbiota with allergic conjunctivitis

Figure 2 and Supplementary Table 2 show the impact of changes in 196 bacterial taxa abundance on allergic conjunctivitis risk based on data from the GWAS of the Sakaue et al.’s study. After MR analysis, the overall estimate calculated with IVW revealed that 5 genera of gut microbiota were genetically predicted for the causal association with allergic conjunctivitis. Our results suggest the decrease of allergic conjunctivitis risk could attribute to the increase of Ruminococcaceae_UCG_002 (OR, 0.83; 95% CI, 0.70–0.99; P = 4.04×10−2), Holdemanella (OR, 0.78; 95% CI, 0.64–0.96; P = 2.04×10−2), Catenibacterium (OR, 0.69; 95% CI, 0.56–0.86; P = 1.09×10−3), and Senegalimassilia (OR, 0.71; 95% CI, 0.55–0.93; P = 1.23×10−2) genus, whereas the host-genetic-driven increases in the Oscillospira genus were potentially related to a higher risk of allergic conjunctivitis (OR, 1.41; 95% CI, 1.00–2.00; P = 4.63×10−2) (Fig. 2). The results of weight median also provide the evidence of a protective effect of the genetic-driven increase in Holdemanella (OR, 0.83; 95% CI, 0.63–1.11; P =0.21), and Ruminococcaceae_UCG_002 (OR, 0.86; 95% CI, 0.66–1.13; P = 0.29) on the risk of allergic conjunctivitis. MR-Egger had not shown a causal association between the five genera and allergic conjunctivitis (P ≥ 0.21). Furthermore, MR.RAPS and MLE were employed to confirm the IVW results, and the results of these methods evidenced that Ruminococcaceae_UCG_002, Holdemanella, Catenibacterium, Senegalimassilia, and Oscillospira genus are significantly associated with allergic conjunctivitis development (P≤ 0.043), which strengthened the confidence of the causal associations (Table 1).

Fig. 2
figure 2

SNPs influence the causal-effect with five MR methods. Each red dot represents the causal effect on allergic conjunctivitis of each SNP with IVW, and each region corresponds to a different level of gut microbiota, including phylum, class, order, family, and genus. The gray dashed line represents OR=1. Circles from outside are the P-value of IVW, the P-value for MR-Egger, the P-value for WM, the P-value for MLE, and the P-value for MR-RAPS. The outermost circle is the ID of each gut microbiota, which corresponds to the bacterial taxon name in Supplementary Table 1. Abbreviations: OR, odds ratio; IVW, inverse-variance-weighted estimate; WM, weighted median estimator; MLE, maximum likelihood estimator; MR.RAPS, MR robust adjusted profile score

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Table 1 MR estimate for the association between gut microbiota and allergic conjunctivitis
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Sensitivity analyses

The results of all sensitivity assessments are then tallied and shown in Fig. 3. Cochrane’s Q reveals no heterogeneity for the SNPs that genetically predict allergic conjunctivitis, and the MR-Egger regression intercept indicated no unbalanced pleiotropy for risk of allergic conjunctivitis (all P>0.05; Table 2). Additionally, horizontal pleiotropy, which was not rectified by MR-Egger regression, was tested using MR-PRESSO (Table 2). No single SNP was found to notably impact our MR findings using the “leave-one-out” evaluation, as indicated in Supplementary Figure 1. Thus, the IVW, MLE, and MR.RAPS should be considered the main results, given that no substantial heterogeneity or unbalanced pleiotropy is present for allergic conjunctivitis risk. Therefore, the risk of allergic conjunctivitis may be strongly linked to the presence of the bacteria of the genera Ruminococcaceae_UCG_002, Holdemanella, Catenibacterium, Senegalimassilia, and Oscillospira, as shown by the MR power calculation (Fig. 3 and Table 1).

Table 2 Sensitivity analyses of MR analyses of gut microbiota on allergic conjunctivitis
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Fig. 3
figure 3

Sensitivity analysis results of all SNPs. Each green dot represents the intercept of MR-Egger, and each region corresponds to a different level of gut microbiota, including phylum, class, order, family, and genus. The gray dashed line represents intercept =0. Circles from outside are the P-values for Cochrane’s Q (MR-Egger), Cochrane’s Q (IVW), and the P-values for the MR-PRESSO, the P-values for the MR-Egger regression. The outermost circle is the ID of each gut microbiota, which corresponds to the bacterial taxon name in Supplementary Table 1. Abbreviations: IVW, inverse-variance-weighted estimate; MR, Mendelian randomization. MR-PRESSO, MR-Pleiotropy RESidual Sum and Outlier

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Discussion

Implementing PPPM for prevention and management of ocular diseases

Severe non-communicable disorders pose a significant social and economic burden on healthcare and society. This has prompted a shift towards implementing PPPM medicine, which focuses on preventative measures rather than reactive treatment [30]. Recently, PPPM provides a new approach to manage the ocular related diseases. One important example is the highlighting of protein profiles in tears and the exemplification of corresponding biomarkers for several relevant pathologies, such as dry eye disease and diabetic retinopathy. These biomarkers could predict disease development, target preventive measures, and facilitate the creation of treatment algorithms tailored to individual patient profiles [31]. Another prominent example is the strong recommendation to apply the “Flammer Syndrome Phenotype” questionnaire to select potential Sjögren’s syndrome patients, who can be detected early in life during the reversible phase of health adverse effects. This can lead to cost-effective targeted prevention [32]. In the context of PPPM, identifying reliable risk factors is crucial for effective disease management and control. In this direction, we can evaluate the risk factors and enforce effective interventions to suppress the disease initiation and progression. Previous researches have reported parental history of allergic disease, city residence at birth, regular meat, margarine consumption, and passive smoking are risk factors for allergic conjunctivitis [33, 34]. However, the current treatment of allergic conjunctivitis, which includes both non-pharmacological and pharmacological measures, is primarily reactive in nature and does not focus on preventative measures. Non-pharmacological measures for managing allergic conjunctivitis involve taking specific actions to reduce exposure to environmental allergens. Topical measures, such as non-steroidal anti-inflammatory agents and corticosteroids, as well as systemic pharmacological measures and immunotherapy, are also commonly used [2]. Therefore, it is need to seek special risk factors could also guide subsequent precise and individualized treatment for allergic conjunctivitis. In this study, the causal associations comprehensively and deeply between gut microbiota and allergic conjunctivitis based on publicly available genetic databases in multi-populations were investigated for the first time, and we established 5 distinct microbial genera are pivotal in the development of allergic conjunctivitis.

Allergic conjunctivitis reflects systemic impairments

The World Health Organization has reported that individuals with allergies often experience a suboptimal quality of life, which can lead to an adverse economic impact [35]. The World Allergy Organization has expressed concern over the increasing global burden of allergic diseases, especially in children and developing countries [36]. Allergic conjunctivitis refers to a group of heterogeneous ocular inflammatory conditions that are modulated by mast cells activation and can affect the conjunctiva, eyelids, and cornea. The most prevalent symptoms are ocular itching and blurred vision. Recently, the Ocular Allergy group of the European Academy of Allergy and Clinical Immunology revised the classification of allergic conjunctivitis, distinguishing between two types of ocular surface hypersensitivity disorders: ocular allergy and ocular non-allergic hypersensitivity. Ocular allergy is divided into IgE-mediated or non-IgE-mediated mechanisms. The IgE-mediated type includes seasonal allergic conjunctivitis (SAC), perennial allergic conjunctivitis (PAC), vernal keratoconjunctivitis (VKC), and atopic keratoconjunctivitis (AKC). The non-IgE-mediated forms include contact blepharoconjunctivitis, VKC, and AKC. Included in the category of ocular non-allergic hypersensitivity are various conditions such as giant papillary conjunctivitis, irritative conjunctivitis, irritative blepharitis, and other mixed or borderline forms. Currently, approximately 20% of the world population is affected by some form of allergy, with up to 40–60% of allergic patients experiencing ocular symptoms [37, 38]. Furthermore, allergic conjunctivitis is often associated with other allergic symptoms and diseases, such as asthma, rhinitis, and atopic dermatitis, indicating an abnormal immune system response to certain substances that leads to systemic inflammation and tissue damage [34]. For instance, SAC and PAC are the ocular forms of a systemic allergic disorder (a type 1 IgE-dependent hypersensitivity), which is typically manifested in the respiratory system as allergic rhinitis and/or asthma [39]. Additionally, VKC children have a higher prevalence of Ig deficiency and vitamin D deficiency, and 15–60% of affected children may also present with other atopic diseases [40, 41]. Moreover, AKC involves IgE-mediated, Th1-mediated allergy, and delayed-type hypersensitivity mechanisms, and can cause more severe ocular symptoms and signs, as well as a higher prevalence of atopic dermatitis and asthma [40]. Numerous studies have demonstrated that ocular disorders can indicate systemic impairments in the holistic PPPM approach [42, 43], such as diabetic retinopathy serving as an early event and a reliable predictor of severe complications associated with diabetes mellitus [44]. Therefore, allergic conjunctivitis may serve as an early indicator and reliable predictor of systemic dysfunction, making it crucial for predicting and preventing associated systemic pathologies.

The systemic impact of gut microbiota

The gut microbiota is established before birth, and seven bacterial classes—Firmicutes, Bacteroidetes, Actinobacteria, Fusobacteria, Proteobacteria, Verrucomicrobia, and Cyanobacteria—tend to thrive in this environment [45]. Recent research has demonstrated that the mammalian gut microbiota positively impacts the host, including food provision, catabolism of indigestible chemicals, suppression of opportunistic pathogen colonization, and even participation in the growth and development of gut structures [13]. In addition, pattern recognition receptors—detection of pathogen-associated molecular patterns, antigen exposure and presentation, and epigenetic modification through metabolic by gut microbiota’s products such as short-chain fatty acids (SCFAs)—mediated interactions between gut commensal bacteria and the developing characteristics and functions of the human immune system [46]. It also contributes to the enhancement of the immune system, plays a vital role in digestion and metabolism, regulates epithelial cell proliferation and differentiation, modifies insulin resistance, and affects its secretion [47]. Furthermore, the gut microbiota influences brain-gut communication, impacting the mental and neurological functions of the host [48]. Therefore, the gut microbiota plays a significant role in maintaining normal gut physiology and overall health. Tachalov and colleagues recently demonstrated the crucial role of maintaining optimal oral hygiene practices for improving individual outcomes and reducing morbidity during the COVID-19 pandemic, within the context of PPPM. Their suggested pathomechanisms consider potential preferences in the interaction between the viral particles and the host microbiota including oral cavity, and the respiratory and gastrointestinal tracts [49]. It is known that alterations to the innate immune system, which may result from gut microbiota dysbiosis, have been linked to various illnesses, including allergies and autoimmune disorders [50]. Hence, from the perspective of PPPM, correcting gut microbiota imbalance should be taken into consideration when developing targeted interventions and preventative measures for immunity-related diseases, such as allergic conjunctivitis [51].

Link between gut microbiota and allergic disorders

Food allergy, atopic dermatitis, eczema, asthma, hay fever, allergic rhinitis, and allergic conjunctivitis are among the many types of allergic illnesses affecting an ever-increasing number of individuals throughout the globe. Strachan proposed the “hygiene hypothesis” in 1989, which states that the incidence of allergy diseases is correlated with decreasing exposure to environmental microbes [52]. Researchers back up this hypothesis with data from animal research and many epidemiological investigations [53]. An IgE-mediated Th2 immune response is significantly linked to allergic disorders. When allergens stimulate antigen-presenting cells, they deliver allergens to Th0 cells, which then develop into Th2 cells in response to cytokines like IL-4. Th2 cells, on the other hand, secrete cytokines, including interleukin-4 (IL-4), interleukin-5 (IL-5), and interleukin-13 (IL-13), which encourage B cells to make IgE and attach to the surface of sensitized effector cells like mast cells and basophils. Cell-mediated immunity, notably against intracellular bacterial and viral infections, autoimmunity, and tumor defense, were linked instead to Th1 responses. Furthermore, Th1-derived cytokines such as IFN-γ may stifle the differentiation of Th2 cells. As a bonus, IL-23 signaling may activate Th17, characterized by IL-17A production. So far, we have known the dynamic cross regulation between the mediators directing lymphocyte polarization exists, and dominant Th2 cell differentiation is one of the immunological bases of IgE-mediated allergic reactions [54]. Based on these evidences, it is not hard to conclude the factors that affect the immunity system homestasis, and enhanced IL4/IL13-driven response is the essential for allergy. Recently, genetic predisposition associated with a preponderance of type 2 immunity was confirmed contribute to the development of allergic disorders [55]. Further, the microbiota in one’s digestive tract may have a role in developing allergic disorders [56]. In light of these facts, we suggest that a hereditary predisposition to the effects of altered gut flora contributes to allergic disorders. In addition, Delday et al. [57] found fewer species of the genus Bacteroides and more species of the genus Firmicutes in infants with atopic dermatitis. Similarly, Stokholm et al. [11] found that children who developed asthma had reduced relative abundances of Lachnospiraceae (including Lachnospiraceae incertae sedis and Roseburia) and Ruminococcaceae (including Ruminococcus and Faecalibacterium). However, the mechanism connecting certain gut microbiota with allergic conjunctivitis has not been explored till now and warrants more study.

Immunomodulatory functions of Ruminococcaceae_UCG_002, Holdemanella, Catenibacterium, and Oscillospira genera

Changes in Firmicutes and Bacteroidetes are particularly significant in many pathological states since these two constitute the vast majority of the bacterial population. Trans-differentiation of Th17 cells into regulatory T cells (Tregs) is connected with the ratio of Firmicutes to Bacteroidetes, which could be used as a disease predictor [58]. Our investigation revealed that the genera Ruminococcaceae_UCG_002, Holdemanella, Catenibacterium, and Oscillospira, all of the phylum Firmicutes, are associated with the onset of allergic conjunctivitis. Ruminococcaceae_UCG_002 can convert certain primary bile acids into secondary bile acids since it is a member of the bile salt hydrolase and 7-dehydroxylase-active family Ruminococcaceae [59]. As we know, bile acids exert hormone-like functions by activating FXR and TGR5 and the dysregulated bile acid pool may lead to perturbations in multiple pathological processes, such as immune regulation and lipid and glucose homeostasis. In addition, prior research has linked the Ruminococcaceae_UCG_002 genera to immune regulation and shown an inverse association between their level and C-reactive protein [59, 60]. Holdemanella biformis is inversely correlated with C-reactive protein levels [61]. Several researchers discovered that Holdemanella could create a high quantity of C18-3OH, and mice treated orally with C18-3OH were less likely to develop colitis after being given dextran sulfate sodium [62]. Thus, it was hypothesized that Holdemanella, through C18-3OH, may influence the host’s immunological and neuroendocrine communication pathways. Recurrent oral and vaginal ulcers, skin lesions, and uveitis are classic symptoms of Behçet’s illness, a Th1 paradigm disease. Behçet’s disease patients have significantly greater levels of Catenibacterium than the general population [63]. Due to its prevalence, Catenibacterium was likely linked to Th1 trans-differentiation, which IL-6 controls. These results suggest that the bacterial genera Ruminococcaceae_UCG_002, Holdemanella, and Catenibacterium are all engaged in immunomodulation via regulating lymphocyte polarization and affecting the dynamic cross-regulation of immune cells.

Comparatively, the functions of the three other genera of gut microbes that demonstrate pathogenic potential are consistent except for the Oscillospira genus. Consistent with our findings, Canani et al. [64] reported that after treatment with Lactobacillus rhamnosus GG, the only species substantially different between tolerant and allergic babies with cow’s milk allergy was Oscillospira and that there was a large quantity of Oscillospira in the allergic samples. Oscillospira overabundance was also positively correlated with the onset of diabetes and inflammation in animals with obesity, type 2 diabetes mellitus, and dextran sulfate sodium-induced ulcerative colitis [65]. Recent research has shown that Oscillospira may create a wide variety of SCFAs, with butyrate being the most abundant and strongly correlated to inflammatory disorders [66]. As described previously, early intestinal dysbiosis activates pro-allergic processes and increases the risk of allergy by the mechanisms disrupting the balance between Th1 and Th2 cells. Taken together, suppressing Th17 cells, enhancing IL-10 production, and activating the Treg/Th2 are the essential factors which induce the immune system balance, and might be the pathology mechanics of enriched Oscillospira and impoverished Ruminococcaceae_UCG_002, Holdemanella, and Catenibacterium in allergic conjunctivitis. Future molecular and clinical studies are needed to understand the underlying processes better.

Study limitations

Although large-scale GWAS studies allow for more solid inferences, they are not without flaws. For one, the majority of participants in the GWAS were of European ancestry, the causal relationship between gut microbiota alteration and allergic conjunctivitis might be limited in others ethnic group. Secondly, we selected the GWAS data of exposure (gut microbiota) and outcome (allergic conjunctivitis) from publicly available summary data; however, it is impossible to establish whether overlapping subjects were engaged in the two samples’ MR analyses. Third, due to the limitation of the database, we could not distinguish different forms of allergic conjunctivitis. Further research is needed to test the gut microbiota alteration in different types of allergic conjunctivitis, aiming to promote a PPPM in patients with allergic conjunctivitis. Fourth, we did not account for multiple testing because a rigorous multiple testing correction may neglect potential strains that are causally related to allergic conjunctivitis.

Conclusions and expert recommendations

To summarize, our results give an insight into the gut microbiota alteration role in the pathophysiology of allergic diseases and broaden our knowledge of allergic conjunctivitis and gut microbiota. Our study is the first study to comprehensively assess the causal effects of the gut microbiota on allergic conjunctivitis and identified that the reduction of Ruminococcaceae_UCG_002, Holdemanella, Catenibacterium, and Senegalimassilia genus made a causal contribution to allergic conjunctivitis, whereas the genera Oscillospira are potentially increased the occurrence of allergic conjunctivitis, which could provide new indicators for early prediction of allergic conjunctivitis.

Innovative screening and targeted interventions

Stool samples can be obtained noninvasively, making them an idea source for analyzing the human gut microbial. With the advent of high-throughput sequencing technologies targeting the 16S rDNA gene, it is now possible to quickly and conveniently analyze the microbial communities in the gut using stool samples [67]. Knowing the change of gut microbial is crucial for predictive diagnosis and targeted prevention. Moreover, allergic conjunctivitis may serve as an early indicator and reliable predictor of systemic dysfunction, such as atopic dermatitis and asthma. Effective early identification of allergic conjunctivitis can provide targeted protection for patients to avoid the impact of allergic conjunctivitis and potential systemic diseases that may exist. Therefore, 16S rDNA high-throughput sequencing is strongly recommended to select individuals at high risk, and targeted preventive measures can be triggered early in life, which conforms to the claim of primary prevention. Individuals who are at risk of a decrease in Ruminococcaceae_UCG_002, Holdemanella, Catenibacterium, and Senegalimassilia and an increase in Oscillospira levels should be a priority for healthcare providers. Early aggressive treatment to correct microbial dysbiosis, such as dietary changes, taking probiotic and prebiotic supplements, and targeted antibiotics, should be considered [68]. For example, direct addition of Ruminococcaceae_UCG_002 probiotics can be given to boost its levels, while targeted antibiotics can be used to suppress the growth of Oscillospira. In addition, high-throughput sequencing of 16S rDNA can be a routine examination to identify changes in gut microbial in patients with allergic conjunctivitis. The novel personalized treatments such as detecting the gut microbiota individually, designing person-related probiotic strains, changing diet, and taking specific antibiotics may help ameliorate the inflammatory response and symptoms, and improve the quality of life in the early stages of allergic conjunctivitis. This is important for secondary prevention of the disease.

Future directions for research on gut microbiota and allergic conjunctivitis

Our understanding of the role of gut microbiota in balancing and modulating the immune response, particularly in the pathophysiology of autoimmune and allergic diseases, has advanced significantly in recent years. As a result, specific gut microbial dysbiosis can induce immune system dysregulation, leading to the activation of Th2 cells and the development of allergic conjunctivitis. Therefore, a comprehensive understanding of the biomolecular modifications responsible for gut microbial dysbiosis is crucial in the discovery of effective preventive and predictive measures. Further research is necessary not only to verify specific allergic conjunctivitis-related gut microbes, but also to confirm the mechanism and causal association in animal models and clinical trials. Ultimately, this will lead to the transition from reactive medical services to PPPM in the management of allergic conjunctivitis.