MR is a widely used analytical approach in which genetic variants act as instrumental variables and genetic predictors serve as independent risk factors. These genetic variants are naturally randomized during meiosis, resulting in an independent distribution within the population. Consequently, the MR is theoretically immune to potential environmental confounders and disease states. There are three fundamental assumptions underlying MR: (1) genetic variants are associated with risk factors (association hypothesis), (2) these genetic variants exhibit no association with any known or unknown confounders (independence assumption), and (3) genetic variation solely influences outcomes through risk factors (exclusion restriction hypothesis) (23).

The third assumption, also known as pleiotropy without a direct effect on outcomes, occurs when genetic variants impact outcomes through alternative pathways independent of risk factors. We used a comprehensive range of methods and sensitivity tests to assess these assumptions. To evaluate hypotheses (2) and (3), we selected the sample with the lowest p-value associated with clinical outcomes.

We used classical two-sample MR as a screening method for genetic associations to describe multiple bidirectional two-sample MR studies and to estimate the causal effects, including CRS and type 1 diabetes mellitus, allergic rhinitis, rheumatoid arthritis, systemic lupus erythematosus, Crohn's disease, ulcerative colitishypothyroidism, and asthma. We employed various databases as exposures or outcomes for the same disease (as indicated in the document), and conducted a two-way Mendelian randomization analysis for the two conditions.

The analysis was performed using the software package two- sample MR with R 4.2.1, using a genome-wide threshold of p < 5 × 10-8,r2 < 0.1 to define the genetic instrument, which we relaxed to p < 1 × 10-5 in the case of fewer than 15 SNPs.

The approach for removing outliers was as follows: First, an assessment was made to determine the presence of pleiotropy and heterogeneity(p < 0.05) between exposure and outcome 24. The MR-PRESSO test was conducted as an initial step in cases where pleiotropy and/or heterogeneity were detected. Based on the results of the MR-PRESSO test, a decision was made regarding the removal of outliers and subsequent assessments of pleiotropy and heterogeneity were performed after outlier removal. If positive results persisted, the aforementioned steps were repeated until no pleiotropy or heterogeneity remained. If there was no evidence of pleiotropy or heterogeneity between the original exposure and outcome, the MR-PRESSO test was not performed and a directional test was conducted to identify and exclude outliers that exhibited an opposite causal relationship.

For the analysis, we employed five commonly used MR analysis methods: (MR Egger, inverse variance weighted, weighted median, simple mode, and weighted mode). Compared with the WME, ME, and MER methods, the IVW method demonstrated greater power. A significance level of p < 0.05 was utilized to determine positive results using the IVW method. Additionally, we used the mr_MaxLik, mr_mbe, and mr_Median methods to provide supplementary evidence for our results. Finally, left-one-out analysis was conducted to evaluate whether any single SNP disproportionately influenced the association.

We conducted LDSC analysis to investigate the genetic associations between hypothyroidism, rheumatoid arthritis, type 1 diabetes, allergic rhinitis, asthma, and chronic rhinosinusitis. The LDSC was used to estimate heritability and assess genetic associations based on single nucleotide variants. LDSC regression was employed to evaluate the genetic association between all autoimmune diseases and CRS, considering single nucleotide variants(SNV) heritability (h2) and the magnitude of correlation (rg) as indicators.

To ensure robustness and account for potential confounding factors, we employed PhenoScanner 25 (www.phenoscanner.medschl.cam.ac.uk) to verify the instruments used in the analysis and their association with autoimmune diseases and CRS. Additionally, we re-validated the results to ascertain whether the correlations were strengthened after eliminating confounders.

Simultaneously, we conducted MVMR to identify and adjust for weak instrumental variables in the two-sample estimation. Using two-sample MR 26, we explored the risk factors associated with CRS, revealing that smoking, occupational environmental dust content, anxiety, stress, and other emotional changes were significant contributors to the incidence of chronic rhinosinusitis. To further account for potential confounders and examine the impact of the PhenoScanner correction, we designed a multigroup MVMR analysis. Specifically, we used Type 1 diabetes mellitus (MVMR1), hypothyroidism (MVMR2), asthma (MVMR3), allergic rhinitis (MVMR4), and rheumatoid arthritis (MVMR5) as covariates in the analysis.

To analyze the genetic mechanisms shared between autoimmune phenotypes and chronic rhinosinusitis, we performed TWAS. Initially, we generated GWAS summary statistics for CRS and autoimmune diseases using the sumstats.py script provided by LDSC. FUSION is a suite of tools for performing transcriptome-wide and regulome-wide association studies. Following that, we utilized the FUSION pipeline in its preset mode to calculate the transcriptomic profiles linked to each respective outcome. Through this application of FUSION, cross-tissue cis-genetic markers of gene expression were detected (32). These signatures were used, along with our gene expression weights, to construct linear predictors for the SNP-based expression levels of each cis-genetic signature. The TWAS test statistics were then calculated based on linear predictors and summary GWAS z-scores. This allowed us to further investigate the shared genetic mechanisms underlying autoimmune phenotypes and chronic rhinosinusitis.

Single-trait TWAS Analysis We employed a threshold of PPH3 + PPH4 > 0.8 as the criterion for identifying co-localization of significant genes, assessing the mapping relationship between each gene and trait. Proceeding to the gene level, we investigated the existence of gene expression associated with chronic sinusitis and autoimmune diseases. The findings from TWAS indicate a considerable degree of shared significant correlations within organs including the nervous, endocrine, cardiovascular, and gastrointestinal systems, reinforcing the idea that the intricate regulatory nexus between chronic sinusitis and traits of autoimmune diseases is multifaceted.

Bivariate bidirectional MR was employed to construct multiple groups of exposures and outcomes for MR analysis, which revealed significant associations with various autoimmune conditions. Our findings indicate that the risk of AR (p = 9.55E-10, OR = 2,711.019278702), asthma (p = 1.81E-23, OR = 33.9964343413), rheumatoid arthritis (p = 9.55E-10, OR = 1.11552606451696), hypothyroidism (p = 0.0208828, OR = 4.84925374492983), and Type 1 diabetes (p = 0.0208828, OR = 1.04848968536672) is genetically influenced (Table 2).

Furthermore, LDSC analysis revealed a significant genetic association between each autoimmune phenotype and CRS. Specifically, AR demonstrated a strong correlation (rg = 0.344724754, p = 0.000000394), as did asthma (rg = 0.43703672, p = 1.86E-10), rheumatoid arthritis (rg = 0.27834931, p = 0.035376), and hypothyroidism (rg = −0.213201473, p = 0.000383093). Type 1 diabetes also showed a moderate genetic association with CRS (rg = 0.263510473, p = 0.273648571).

These results corroborate the theory suggesting a genetic overlap between these autoimmune disorders and CRS, thereby emphasizing their possible involvement in the onset and progression of this concurrent condition.

Through PhenoScanner analysis, associations were identified between certain SNPs and chronic sinusitis. Notably, these SNPs were also associated with confounding factors such as fat distribution and body weight. In response to potential sources of confusion, a subsequent magnetic resonance examination was carried out post-adjustment for such elements. Post-adjustment, the link between asthma, hypothyroidism, and chronic sinusitis was found to be more pronounced. Additionally, body mass index (BMI) was considered a variable in the study due to its potential role in influencing this relationship (Figure 2).

Subsequently, MVMR analysis was performed to explore the relationship between autoimmune diseases and chronic sinusitis in the presence of additional confounding factors. The MVMR analysis revealed associations between BMI, smoking behavior, and mood factors, as well as an association between autoimmune diseases and chronic sinusitis. This implies that such interfering elements might be intermediary variables that influence the link between the immunological profiles and sinusitis to some extent (Figure 3).

In essence, our research underscores the significance of accounting for confounders in genetic research on chronic sinusitis and points to the possible intermediary influence of elements like body mass index, smoking habits, and emotional state in the nexus between autoimmune disorders and chronic sinusitis.

We identified multiple genes shared between chronic sinusitis and AR, predominantly located within the endocrine/exocrine system (149 genes in thyroid tissue, 137 in testes, and 128 in subcutaneous tissue), digestive system (120 genes in esophageal mucosa and 105 in esophageal muscular layer), skin (288 shared genes), and nervous system (146 shared genes in tibial nerve) tissues. Notably, the skin tissue exhibited a relatively higher number of key shared genes (Figure 4).

In the context of AT and CRS, numerous genes were shared across various tissues, with the endocrine/exocrine system showing the highest distribution. Genes such as TSLP/WDR36 (CHR5, Best SNP: rs1837253), ORMDL3(CHR13, Best SNP: rs11557467), and IL1RL1/IL18R1(CHR2,Best SNP: rs12905) demonstrated a higher degree of concordance in sharing between AT, AR, and CRS, suggesting a relatively stronger genetic association among these traits compared to other autoimmune diseases (Figure 5).

Fewer shared genes were identified between RA, HYO, T1D, and CRS. PSMB7 was found to be a shared gene between CRS and HYO in multiple tissues, including the cardiovascular system (atrial and aortic tissue), digestive system (stomach and esophageal mucosa), and endocrine system (subcutaneous fat, oral, and mammary gland). PGAP3 was identified as a shared gene between CRS and T1D in tissues such as esophageal mucosa, transverse colon, and brain. To date, no significant shared genes have been found between RA and CRS (Figures 6–8).

Persistent forms of rhinosinusitis, allergic nasal inflammation, and skin conditions characterized by atopy demonstrate a marked coherence in their expression characteristics linked to the TSLP gene located on the fifth chromosome. The TSLP gene is responsible for producing a protein that facilitates the activation of Type 2 T helper (TH2) cell activities and plays a role in the initiation and advancement of numerous chronic inflammatory disorders, a conclusion that is in agreement with the research presented by Hong and colleagues (33). TSLP has been shown to modulate the production of eotaxin-1 by nasal epithelial cells in eosinophilic CRS with nasal polyps (CRSwNP), thereby facilitating the development of eosinophilic sinus inflammation (34) and TSLP plays a critical role in initiating allergen sensitization (35). Our study suggests that TSLP may serve as a common genetic mechanism underlying sinusitis and autoimmune diseases.

ORMDL3 represents a shared genetic component between CRS, AR, and AT as well. OEMDL3 serves as a significant indicator for asthma and contributes to the development of multiple inflammatory disorders. Imbalance in ceramide levels may worsen the manifestations of allergic asthma and associated ailments (36, 37). It exacerbates symptoms of allergic asthma and other diseases by disrupting the ceramide homeostasis (38). However, no current research has established a correlation between ORMDL3 and CRS. Our study suggests that ORMDL3 may serve as a genetic marker for CRS, a hypothesis that requires further study for validation.

Previous research has associated IL1RL1 and IL18R1 with asthma and other atopic diseases (39). The Castano R team found that the expression of IL1RL1 is related to chronic rhinosinusitis (40). Our study confirms that these genes are expressed in multiple tissues of patients with CRS, AT, and AR, further indicating a potential genetic basis shared among the three conditions.

WDR36 is co-expressed in multiple tissues of patients with chronic sinusitis, asthma, and allergic rhinitis. It has been identified as a locus for eosinophilic esophagitis (41); however, no research has linked WDR36 to CRS. Our study suggests a correlation between TSLP, WDR36 and CRS, AT, and AR.

Our research reveals that the PGAP3 gene is expressed in multiple tissues of patients with CRS, AR, AT, and type 1 diabetes, indicating it may serve as a common genetic basis for chronic sinusitis and autoimmune diseases. This finding is consistent with the conclusions of the Zerun Song team (42) and the Cristina T Vicente team (39).

We found that PSMB7 is expressed in multiple tissues of CRS and HYO patients, and GLDC is expressed in multiple tissues of CRS, AT, and AR patients. Although no current research has established a link between PSMB7 and these conditions, our study suggests that these genes may be potential genetic markers for the common genetic basis of CRS and autoimmune diseases.

GSDMB, a diagnostic gene for type 1 diabetes (43), actively participates in the onset and progression of metabolic disorders by influencing body fat distribution (44). Moreover, it regulates genetic activity via targeted methylation of DNA, playing a role in the progression of autoimmune conditions such as rheumatoid arthritis and asthma, among others, as noted in reference (45). Some studies have also revealed a relationship between GSDMB and chronic sinusitis (46).

In line with prior research, our investigation corroborated that GSDMB is a common genetic link between the trio of ailments. This discovery provides a valuable basis for the identification of therapeutic targets for autoimmune diseases and chronic rhinosinusitis. Using MR analysis, our study suggested that rheumatoid arthritis and type 1 diabetes mellitus are risk factors for chronic rhinosinusitis. Nevertheless, further research is required to clarify the causal relationship linking these three disorders.

Th-17 cells are a critical type of immune cell that play a pivotal role in the development and progression of autoimmune diseases and chronic rhinosinusitis (CRS). These cells primarily secrete cytokines such as interleukin (IL)-17 and IL-22, which are essential in regulating immune responses and maintaining tissue homeostasis. However, the abnormal activation of Th-17 cells can lead to the onset of autoimmune diseases (47, 48). Cytokines like IL-17 can promote the recruitment and activation of inflammatory cells, resulting in tissue damage. In autoimmune diseases such as rheumatoid arthritis and multiple sclerosis, the levels of Th-17 cells and their secreted cytokines are typically elevated. Th-17 cells may be involved in abnormal immune responses against self-antigens, leading to an attack on the body's own tissues and thereby triggering autoimmune diseases.

In patients with chronic rhinosinusitis, the expression of Th-17 cells and their secreted cytokine IL-17A is upregulated in the sinus mucosa, leading to intensified inflammatory responses, subsequent mucosal damage, and pathological remodeling. The imbalance between Th-17 cells and regulatory T cells (Tregs) in the bodies of chronic rhinosinusitis patients may contribute to the persistence of inflammation and the chronic nature of the disease (49).

Th-17 cells and their cytokines are involved in the same inflammatory pathways in both autoimmune diseases and chronic rhinosinusitis, such as the IL-17/IL-23 axis (50). During the progression of these diseases, Th-17 cells may act as a bridge, exacerbating the disease process.

In summary, the correlation between Th-17 cells and autoimmune diseases and chronic rhinosinusitis is primarily manifested in immune regulation, inflammation mediation, and tissue remodeling. Delving into the mechanisms of Th-17 cells in these diseases can provide new targets and methods for clinical treatment.

Recent studies on allergic respiratory diseases and sinusitis have shown that the association between these conditions may be attributed to the destruction of the epithelial barrier or the production of cytokines. The protective layer of epithelium coating the nasal mucosa acts as an innate safeguard against inflammation within the nasal cavity (51). It seems that the onset of conditions such as allergic rhinitis, asthma, and chronic rhinosinusitis is associated with a dysfunction of this epithelial defense (52).

Persistent engagement of type 2 immune responses within the upper airways may result in allergic swelling, culminating in enduring rhinosinusitis spanning a spectrum of seriousness from mild rhinitis to intense nasal polyp formation (53). A hypothesis has been put forth highlighting the significance of epithelium-derived cytokines, including IL-25, IL-33, and TSLP, as key regulators that connect epithelial-mesenchymal communication and induce pathophysiological changes in the airways (33).

Continued examination of these cytokines originating from epithelial cells is expected to provide deep understanding of the processes that drive inflammation in the respiratory tract. Consequently, employing agents that act upon these cytokines could accelerate progress in the therapy and control of allergic rhinitis, chronic sinus infections, and related disorders, thereby improving the health outcomes for individuals suffering from asthma and allergic reactions.