Department of Oncology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong, China.
Guangdong Provincial Hospital of Chinese Medicine Postdoctoral Research Workstation, Guangzhou, Guangdong, China.
Cancer Immunol Immunother. 2024 Nov 2;74(1):1. doi: 10.1007/s00262-024-03854-8.
Immune-related adverse events (irAEs) pose substantial challenges in the realm of cancer immunotherapy, frequently affecting treatment efficacy and patient safety. To address the urgent need for identifying risk factors associated with irAEs, we conducted a comprehensive phenotype-wide Mendelian randomization analysis (MR-PheWAS).
Utilizing publicly accessible genome-wide association study (GWAS) data, this investigation evaluated the impact of over 5000 exposure variables on susceptibility to irAEs using univariate Mendelian randomization (MR). We categorized these correlations and further explored potential mechanisms by which associated traits might influence irAEs through multivariate MR.
MR-PheWAS identified numerous risk factors for irAEs, encompassing both previously documented and novel associations. Specifically, we identified 105 traits with probable causal relationships to all-grade irAEs and 119 traits with suggestive associations. For high-grade irAEs, we categorized 122 traits as probably associated and 141 as suggestively associated. Notably, multivariate MR analyses uncovered intricate interactions, particularly highlighting how diabetes impacts all-grade irAEs through mediators such as body mass index and sex hormone-binding globulin.
This study has not only identified new risk factors for irAEs but also confirmed several well-established ones. Further investigation is crucial to validate and assess these identified risk factors within clinical trials. A mechanistic understanding of these causal factors is essential for improving the management and prevention of irAEs.
免疫相关不良事件（irAEs）在癌症免疫治疗领域带来了巨大挑战，经常影响治疗效果和患者安全。为了解决确定 irAEs 相关风险因素的迫切需求，我们进行了全面的表型全基因组关联研究（MR-PheWAS）。
利用公开的全基因组关联研究（GWAS）数据，本研究使用单变量 Mendelian 随机化（MR）评估了 5000 多个暴露变量对 irAEs 易感性的影响。我们对这些相关性进行了分类，并通过多变量 MR 进一步探讨了相关特征可能通过哪些潜在机制影响 irAEs。
MR-PheWAS 确定了许多 irAEs 的风险因素，包括先前记录的和新的关联。具体来说，我们确定了 105 个与所有等级 irAEs 可能有因果关系的特征，以及 119 个有提示关联的特征。对于高级别 irAEs，我们将 122 个特征归类为可能相关，141 个特征归类为提示相关。值得注意的是，多变量 MR 分析揭示了复杂的相互作用，特别是突出了糖尿病如何通过身体质量指数和性激素结合球蛋白等介质影响所有等级 irAEs。
本研究不仅确定了 irAEs 的新风险因素，还证实了一些已确立的风险因素。进一步的研究对于在临床试验中验证和评估这些已确定的风险因素至关重要。对这些因果因素的机制理解对于改善 irAEs 的管理和预防至关重要。
