Ji Lingfen, Li Puyu, Duan Nana, Xu Jinjin, Song Yijuan, Shu Bohui, Liang Lijun, Zhao Fuli
Department of gerontology, The First Affiliated Hospital of Henan University of Science and Technology, Guanlin Road, Luoyang, 471000, China.
Diabetol Metab Syndr. 2025 Apr 15;17(1):127. doi: 10.1186/s13098-025-01696-7.
Circulating immune cells reportedly affect diabetic neuropathy (DN). Although associations have been previously established between numerous biomarkers and diseases, elucidating their causal relationships remains challenging. Mendelian Randomization (MR) could overcome this difficulty by applying genetic instruments to discern causal links. In this study, we conducted bidirectional two-sample MR to address this problem.
We used freely available genome-wide association study summary statistics. We obtained immune cell phenotype-related summary data from a study cohort comprising 3,757 Sardinian individuals that reported data concerning 731 immune cell phenotypes. We obtained DN-related summary data from the FinnGen database and conducted sensitivity analyses. Furthermore, we assessed horizontal pleiotropy using combined MR-Egger and MR-Presso methods. We evaluated heterogeneity using Cochran's Q test and applied False Discovery Rate correction to the findings.
Our MR analysis significantly associated 24 immune cell phenotypes with DN. Specifically, the presence of CD45 on CD66b + + myeloid cells, HLA DR on CD14 + CD16- monocytes, IgD- CD24- %B cells, and CD27 on IgD- CD38br lymphocytes significantly positively correlated with the risk of DN. In contrast, the presence of CD28- DN (CD4-CD8-) %T cells, FSC-A on HLA DR + T cells, and other four T cell types negatively correlated with DN. Finally, we further confirmed the relationship between different immune cell types and DN.
We demonstrated the immunological susceptibility of DN and clarified how immune responses influence the course of DN. These findings might help inform immunological therapy techniques as well as novel targets for DN diagnosis and treatment.
据报道,循环免疫细胞会影响糖尿病神经病变(DN)。尽管先前已在众多生物标志物与疾病之间建立了关联,但阐明它们之间的因果关系仍然具有挑战性。孟德尔随机化(MR)可以通过应用遗传工具来识别因果联系来克服这一困难。在本研究中,我们进行了双向两样本MR以解决这一问题。
我们使用了免费的全基因组关联研究汇总统计数据。我们从一个包含3757名撒丁岛个体的研究队列中获得了免疫细胞表型相关的汇总数据,该队列报告了有关731种免疫细胞表型的数据。我们从芬兰基因组数据库中获得了与DN相关的汇总数据,并进行了敏感性分析。此外,我们使用MR-Egger和MR-Presso联合方法评估水平多效性。我们使用 Cochr an's Q检验评估异质性,并对研究结果应用错误发现率校正。
我们的MR分析发现24种免疫细胞表型与DN显著相关。具体而言,CD66b++髓样细胞上CD45的存在、CD14+CD16-单核细胞上HLA DR的存在、IgD-CD24-%B细胞以及IgD-CD38br淋巴细胞上CD27的存在与DN风险显著正相关。相比之下,CD28-DN(CD4-CD8-)%T细胞、HLA DR+T细胞上的FSC-A以及其他四种T细胞类型与DN呈负相关。最后,我们进一步证实了不同免疫细胞类型与DN之间的关系。
我们证明了DN的免疫易感性,并阐明了免疫反应如何影响DN的病程。这些发现可能有助于为DN的免疫治疗技术以及诊断和治疗的新靶点提供信息。