Zhang Yuting, Wu Yanjuan, Su Xiaofen, Gan Qiming, Ding Yutong, Wang Jingcun, Wang Xinni, Zhang Nuofu, Wu Kang
Department of Pulmonary and Critical Care Medicine, Sleep Medicine Center, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, National Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, No. 28 Qiaozhong Mid Road, Guangzhou, 510160, Guangdong, China.
AMB Express. 2025 Aug 12;15(1):116. doi: 10.1186/s13568-025-01924-3.
Alterations in skin microbiota composition have been linked to allergic diseases, but the causal relationship remains unclear. To investigate the causal relationship between skin microbiota, allergic diseases, and inflammation biomarkers using Mendelian randomization (MR). We integrated summary statistics from genome-wide association studies (GWAS) of skin microbiota inflammation biomarkers, and seven allergic diseases. Inverse variance weighting (IVW) served as the primary statistical method, with supplementary analyses using MR-Egger regression, weighted median, and Weighted mode. Sensitivity analyses, including Cochran's Q test, MR-Egger intercept test and MR-PRESSO outlier detection, were conducted to validate and stabilize our findings. Two-step MR analyses were performed to identify potential mediating inflammation biomarkers between skin microbiota and allergic diseases.We identified 43 significant causal relationships between the skin microbiota and seven allergic diseases: allergic disease as a whole, asthma (adult, pediatric, allergic), allergic conjunctivitis, allergic rhinitis, atopic dermatitis, allergic urticaria and eczema, which included 20 protective and 23 risk causal relationships, respectively. Mediation analysis showed that specific biomarkers, such as C-C motif chemokine 19 and CD40L receptor levels, Interleukin-18 and TNF-β mediated these associations. This MR study provides robust evidence supporting causal relationships between specific skin microbiota taxa and allergic diseases, as well as potential mediating roles of inflammation biomarkers.
皮肤微生物群组成的改变与过敏性疾病有关，但因果关系仍不清楚。为了使用孟德尔随机化（MR）研究皮肤微生物群、过敏性疾病和炎症生物标志物之间的因果关系。我们整合了来自皮肤微生物群炎症生物标志物以及七种过敏性疾病的全基因组关联研究（GWAS）的汇总统计数据。逆方差加权（IVW）作为主要统计方法，并使用MR-Egger回归、加权中位数和加权模式进行补充分析。进行了敏感性分析，包括Cochran's Q检验、MR-Egger截距检验和MR-PRESSO异常值检测，以验证和稳定我们的研究结果。进行了两步MR分析，以确定皮肤微生物群和过敏性疾病之间潜在的中介炎症生物标志物。我们确定了皮肤微生物群与七种过敏性疾病之间的43种显著因果关系：整体过敏性疾病、哮喘（成人、儿童、过敏性）、过敏性结膜炎、过敏性鼻炎、特应性皮炎、过敏性荨麻疹和湿疹，其中分别包括20种保护性和23种风险因果关系。中介分析表明，特定的生物标志物，如C-C基序趋化因子19和CD40L受体水平、白细胞介素-18和肿瘤坏死因子-β介导了这些关联。这项MR研究提供了有力证据，支持特定皮肤微生物群分类群与过敏性疾病之间的因果关系，以及炎症生物标志物的潜在中介作用。
