Zhou Ling, Zhao Shuhua, Luo Jiahuan, Rao Meng, Yang Shuangjuan, Wang Huawei, Tang Li
Department of Reproduction and Genetics, The First Affiliated Hospital of Kunming Medical University, Kunming, People's Republic of China.
The Core Technology Facility of Kunming Institute of Zoology (KIZ), Chinese Academy of Sciences (CAS), Kunming, People's Republic of China.
J Inflamm Res. 2024 Dec 8;17:10663-10679. doi: 10.2147/JIR.S473068. eCollection 2024.
This study aims to investigate alterations in immune cell counts within preovulatory follicles of patients with poor ovarian response (POR) during assisted reproductive technology (ART), classified according to the POSEIDON criteria.
This single-centre cross-sectional study included 543 women undergoing IVF/ICSI treatment, selected based on specific inclusion and exclusion criteria: 292 with normal ovarian response and 251 with poor response. Follicular fluid (FF) was collected on the day of oocyte retrieval and analysed by flow cytometry to determine the proportions of macrophages (Mφs), M1 and M2 Mφs, T cells (CD4 and CD8 T cells), dendritic cells (DCs), including type 1 conventional dendritic cells (cDC1) and type 2 conventional dendritic cells (cDC2), and neutrophils. Multivariable logistic regression assessed the relationship between immune cell counts and POR, Pearson correlation determined associations with the number of retrieved oocytes, and receiver operating characteristic (ROC) curves evaluated the predictive power of immune cell counts for POR.
Immune cells accounted for 52.57% (±23.90%) of the total cell population in the follicular microenvironment, which was approximately equal to that of granulosa cells, with Mφs being the most abundant, followed sequentially by T cells, DCs, and neutrophils. In patients with POR, overall Mφs infiltration in the follicular microenvironment decreased, whereas M1 and M2 polarization increased. T cell infiltration increased, with a decrease in the CD4/CD8 ratio. Both cDC1 and cDC2 were significantly elevated. Moreover, multivariable logistic regression revealed that the total macrophage count, CD4 T cell count, and cDC2 count were independent predictors of POR. Notably, cDC2 showed the largest area under the ROC curve, suggesting its strong potential as a biomarker for predicting POR.
The proportion of immune cells in preovulatory follicles were significantly altered in patients with POR. These findings suggest that immune cell dynamics in the follicular microenvironment may play a crucial role in determining ovarian response and prognosis, indicating that targeted immunomodulatory strategies could be considered in future therapeutic approaches.
本研究旨在调查根据POSEIDON标准分类的卵巢反应不良(POR)患者在辅助生殖技术(ART)过程中排卵前卵泡内免疫细胞计数的变化。
这项单中心横断面研究纳入了543名接受IVF/ICSI治疗的女性,根据特定的纳入和排除标准进行选择:292名卵巢反应正常,251名反应不良。在取卵当天收集卵泡液(FF),并通过流式细胞术分析以确定巨噬细胞(Mφs)、M1和M2 Mφs、T细胞(CD4和CD8 T细胞)、树突状细胞(DCs)(包括1型传统树突状细胞(cDC1)和2型传统树突状细胞(cDC2))以及中性粒细胞的比例。多变量逻辑回归评估免疫细胞计数与POR之间的关系,Pearson相关性确定与回收卵母细胞数量的关联,受试者操作特征(ROC)曲线评估免疫细胞计数对POR的预测能力。
免疫细胞占卵泡微环境中总细胞群的52.57%(±23.90%),这与颗粒细胞的比例大致相等,其中Mφs最为丰富,其次依次为T细胞、DCs和中性粒细胞。在POR患者中,卵泡微环境中总的Mφs浸润减少,而M1和M2极化增加。T细胞浸润增加,CD4/CD8比值降低。cDC1和cDC2均显著升高。此外,多变量逻辑回归显示,巨噬细胞总数、CD4 T细胞计数和cDC2计数是POR的独立预测因素。值得注意的是,cDC2在ROC曲线下的面积最大,表明其作为预测POR生物标志物的潜力巨大。
POR患者排卵前卵泡中免疫细胞的比例发生了显著变化。这些发现表明,卵泡微环境中的免疫细胞动态可能在决定卵巢反应和预后方面起关键作用,这表明在未来的治疗方法中可以考虑针对性的免疫调节策略。