Department of Otorhinolaryngology, Dongfang Hospital Affiliated to Beijing University of Chinese Medicine, Beijing, China.
Department of Otorhinolaryngology, Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine, Beijing, China.
Front Immunol. 2023 Sep 21;14:1240517. doi: 10.3389/fimmu.2023.1240517. eCollection 2023.
Asthma is a heterogeneous disease, and the involvement of neurogenic inflammation is crucial in its development. The standardized treatments focus on alleviating symptoms. Despite the availability of medications for asthma, they have proven to be inadequate in controlling relapses and halting the progression of the disease. Therefore, there is a need for novel drug targets to prevent asthma.
We utilized Mendelian randomization to investigate potential drug targets for asthma. We analyzed summary statistics from the UK Biobank and then replicated our findings in GWAS data by Demenais et al. and the FinnGen cohort. We obtained genetic instruments for 734 plasma and 73 brain proteins from recently reported GWAS. Next, we utilized reverse causal relationship analysis, Bayesian co-localization, and phenotype scanning as part of our sensitivity analysis. Furthermore, we performed a comparison and protein-protein interaction analysis to identify causal proteins. We also analyzed the possible consequences of our discoveries by the given existing asthma drugs and their targets.
Using Mendelian randomization analysis, we identified five protein-asthma pairs that were significant at the Bonferroni level ( < 6.35 × 10). Specifically, in plasma, we found that an increase of one standard deviation in IL1R1 and ECM1 was associated with an increased risk of asthma, while an increase in ADAM19 was found to be protective. The corresponding odds ratios were 1.03 (95% CI, 1.02-1.04), 1.00 (95% CI, 1.00-1.01), and 0.99 (95% CI, 0.98-0.99), respectively. In the brain, per 10-fold increase in ECM1 (OR, 1.05; 95% CI, 1.03-1.08) and PDLIM4 (OR, 1.05; 95% CI, 1.04-1.07) increased the risk of asthma. Bayesian co-localization found that ECM1 in the plasma (coloc.abf-PPH4 = 0.965) and in the brain (coloc.abf-PPH4 = 0.931) shared the same mutation with asthma. The target proteins of current asthma medications were found to interact with IL1R1. IL1R1 and PDLIM4 were validated in two replication cohorts.
Our integrative analysis revealed that asthma risk is causally affected by the levels of IL1R1, ECM1, and PDLIM4. The results suggest that these three proteins have the potential to be used as drug targets for asthma, and further investigation through clinical trials is needed.
哮喘是一种异质性疾病，神经炎症的参与对其发展至关重要。标准化治疗侧重于缓解症状。尽管有治疗哮喘的药物，但它们在控制复发和阻止疾病进展方面被证明是不够的。因此，需要寻找新的药物靶点来预防哮喘。
我们利用孟德尔随机化研究哮喘的潜在药物靶点。我们分析了英国生物库的汇总统计数据，然后在 Demenais 等人的 GWAS 数据和 FinnGen 队列中复制了我们的发现。我们从最近报道的 GWAS 中获得了 734 种血浆和 73 种脑蛋白的遗传工具。接下来，我们利用反向因果关系分析、贝叶斯共定位和表型扫描作为敏感性分析的一部分。此外，我们进行了比较和蛋白质-蛋白质相互作用分析，以确定因果蛋白。我们还通过现有哮喘药物及其靶点分析了我们发现的可能后果。
使用孟德尔随机化分析，我们确定了五个与哮喘显著相关的蛋白质-哮喘对（<6.35×10）。具体来说，在血浆中，我们发现 IL1R1 和 ECM1 增加一个标准差与哮喘风险增加有关，而 ADAM19 增加则具有保护作用。相应的比值比分别为 1.03（95%置信区间，1.02-1.04）、1.00（95%置信区间，1.00-1.01）和 0.99（95%置信区间，0.98-0.99）。在大脑中，ECM1 每增加 10 倍（OR，1.05；95%置信区间，1.03-1.08）和 PDLIM4 （OR，1.05；95%置信区间，1.04-1.07）都会增加哮喘的风险。贝叶斯共定位发现，血浆中的 ECM1（coloc.abf-PPH4=0.965）和大脑中的 ECM1（coloc.abf-PPH4=0.931）与哮喘共享相同的突变。当前哮喘药物的靶蛋白被发现与 IL1R1 相互作用。IL1R1 和 PDLIM4 在两个复制队列中得到验证。
我们的综合分析表明，哮喘风险受到 IL1R1、ECM1 和 PDLIM4 水平的因果影响。结果表明，这三种蛋白有可能成为哮喘的药物靶点，需要通过临床试验进一步研究。
