Research has demonstrated the efficacy of targeted drug therapy in improving asthma control; however, significant variations in drug responses exist among patients, underscoring the pressing need for more effective targeted therapies. Therefore, the quest for viable for asthma treatment targets is paramount. To date, Li et al.35 have identified asthma genes through eQTL analysis of bronchial epithelial cells and bronchoalveolar lavage fluid; Zaid et al.36 and Nieuwenhuis et al.37 have identified a series of asthma drug targets based on GWAS and eQTL analysis; Wang et al.38 have identified a series of asthma drug targets based on GWAS and pQTL analysis. In our study, using a larger cerebrospinal fluid protein database and plasma protein identification, we identified more comprehensive asthma-targeted protein sites. We identified seven proteins associated with asthma risk, three of which may serve as new asthma treatment targets. Furthermore, using protein-protein interaction networks and DrugBank, we identified drugs that may have therapeutic potential for patients with asthma. Our study complements previous related research by identifying seven proteins with a causal relationship with asthma risk. Through colocalization analysis of the seven initially identified proteins, three proteins were identified as potential drug targets for asthma, including ECM1, IL-6 sRa, and layilin. Additionally, using the same analysis method in the FinnGen database, we found that IL1-R1, ADAM19, and IL7R were associated with asthma risk, further demonstrating the stability of the results obtained in this study.
Asthma is characterised by airway hyper-responsiveness and excessive bronchoconstriction39. Brain-derived neurotrophic factors actively recruit eosinophils, stimulate their degranulation, and release major basic proteins, thereby enhancing parasympathetic nerve-mediated bronchoconstriction40. Simultaneously, neurogenic inflammation can trigger asthma attacks by releasing neuropeptides via local axon reflexes41. This further prompted us to conduct an MR analysis of cerebrospinal fluid proteins associated with asthma risk to explore the causal relationship between cerebrospinal fluid proteins and asthma and to identify potential drug targets. The cerebrospinal fluid proteins IL-6, sRa, and layilin have been identified as potential drug targets. In the PPI network analysis, lililin was found to be associated with three asthma drug targets (IgE, IL-5, and IL-4), further indicating that lililin may be a potential therapeutic target for asthma.
IL1-R1 is a cytokine receptor that serves as the receptor for IL-1α, IL-1β, and IL-1RA. When bound to IL-1α and IL-1β, it activates intracellular signalling pathways42. A previous study indicated that during periods of psychological stress in patients with asthma, there is increased glucose metabolism in the amygdala, which is associated with increased IL-1 signalling in the airways, suggesting the existence of a brain immune pathway in asthma43. IL1-R1 exhibited a strong interaction with IL-33 in the PPI analysis. Studies have shown that IL-33 encodes a cytokine released during cellular damage, whereas IL1-RL1 encodes a part of the IL-33 receptor complex44. Recent advances in functional studies in human participants and mouse models of allergic airway disease suggest that IL-33 signalling plays a central role in driving TH2 inflammation, which is the core of eosinophilic allergic asthma45. Based on pharmacogenomic screening, IL-33 is a potential small-molecule therapeutic target. Currently, data from two Phase II clinical trials have shown that targeting IL-33 monoclonal antibodies or IL-33R monoclonal antibodies reduces acute asthma attacks compared to placebo46,47. Additionally, IL1-R1-targeting drugs were found in DrugBank, including Anakinra, SD118, OMS-103HP, and Foreskin fibroblasts (neonatal). As the concept of drug repositioning has been applied to drugs currently marketed or under development, this method can be used to investigate whether the aforementioned four drugs can also effectively treat asthma48. As the safety of these drugs has been established, this approach can enhance the efficiency of drug development, while reducing costs and time. IL-7R is also a cytokine receptor that binds to IL-7 or thymic stromal lymphopoietin (TSLP), activates JAK-STAT and other pathways and regulate type 2 inflammation49. In ovalbumin-induced allergic asthma mouse models, IL-7 signaling has been shown to be necessary for the survival of allergen-specific CD4 + T cells50. Additionally, IL1-R1 was found to interact with IL-7R in the PPI analysis. Currently, there are no studies on combined therapy targeting IL1-R1 and IL-7R, providing new insights for our research on targeted asthma medications.
ECM1 was initially identified as an 85 kDa glycoprotein secreted by the mouse osteoblastic cell line MN7. The human homologue regulates endochondral bone formation, stimulates endothelial cell proliferation, and induces angiogenesis51. Li et al. confirmed that ECM1 was elevated and specifically expressed in Th2 cells, leading to exacerbated allergic airway inflammation52. Another study found that ECM1 inhibits the differentiation of Th17 cells in inflammatory diseases of the central nervous system; however, inhibiting Th17 cell differentiation can reduce the occurrence of asthma53. CD200R1 is an immunoregulatory receptor on the surface of myeloid cells. Upon binding to the cell surface glycoprotein CD200, it transmits immune inhibitory signals, resulting in the suppression of mast cell and eosinophil degranulation and modulation of macrophage function54. Lauzon-Joset et al. have demonstrated in animal models that CD200R1 activation eliminates airway hyperresponsiveness in experimental asthma55. Combined with previous research, our study found that ECM1 and CD200R1 are risk factors for asthma, indicating that we can systematically obtain more experimental data, including GWAS and basic research, to elucidate this further. Additionally, the colocalization analysis of plasma ECM1 and asthma-shared causal variant sites suggests a higher likelihood of it becoming a potential therapeutic target.
Our study has some limitations. First, we tested the effects of proteins from different studies, and inconsistencies in the measurements between different studies may lead to biased results. Additionally, patients with different types of asthma may exhibit different genetic variations. Second, most proteins have only one cis-acting SNP that is significantly associated with the whole genome (P < 5 × 10− 8), lacking trans-acting pQTLs, which limits the application of analysis, including alternative MR algorithms, heterogeneity testing, and pleiotropy testing. However, our investigation of the main discovered SNPs suggested that most SNPs had F-statistics > 10. Furthermore, the effect allele frequencies of the plasma pQTLs retrieved from matched human genome constructs for ADAM19 were close to 0.5, indicating low reliability in the direction of its effect. Therefore, the effects of ADAM19 should be interpreted with caution. Third, our analysis was conducted on populations of European ancestry, making it difficult to generalise the results to other races. Further research in non-European populations is required to translate these findings to clinical applications. Finally, although we found some interactions between the pathogenic proteins of current asthma medications and drug targets, the results of the PPI analysis were suggestive rather than conclusive, and more research, such as studies using cell lines, animal models, and clinical samples, is needed to validate these findings.