Altered Immune Cell Profiles in the Follicular Fluid of Patients with Poor Ovarian Response According to the POSEIDON Criteria

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.

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.

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.

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.