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Updated: Sep 23, 2025
Multiplexed Fluorescent Immunohistochemical Staining of Four Endometrial Immune Cell Types in Recurrent Miscarriage
Published on: August 4, 2021
A combination of immune cell types identified through ensemble machine learning strategy detects altered profile in
Marilen Benner1, Dorien Feyaerts1, Alejandro Lopez-Rincon2
1Radboud Institute of Molecular Life Sciences, Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Center, Nijmegen, the Netherlands.
Insights
Immune cell profiles in peripheral and menstrual blood can distinguish women with recurrent pregnancy loss. Menstrual blood offers a promising, noninvasive method for assessing reproductive health and immune function.
Area of Science:
- Reproductive Immunology
- Immunology
- Flow Cytometry
Background:
- Recurrent pregnancy loss (RPL) affects women without clear causes.
- Understanding the immune system's role in RPL is crucial for diagnosis and treatment.
- Comparing immune profiles in different blood sources may reveal novel biomarkers.
Purpose of the Study:
- To compare the immunologic profiles of peripheral blood and menstrual blood (MB) in women with RPL versus controls.
- To identify specific immune cell subsets that can differentiate between these groups.
- To explore the potential of MB as a noninvasive diagnostic tool for reproductive health.
Main Methods:
- An explorative case-control study design was employed.
- Flow cytometry was used for cross-sectional assessment of immunologic profiles.
- Machine learning classifiers in an ensemble strategy with recursive feature selection were applied to analyze immune cell data.
Main Results:
- Peripheral blood analysis identified 4 key cell types differentiating cohorts (e.g., B cells, CD8+ T cells, NK cells).
- Menstrual blood analysis identified 6 cell types plus age as discriminators (e.g., regulatory T cells, B cells, NK cells).
- Both peripheral blood and MB analyses achieved high accuracy (>0.8 AUC) in cohort classification.
Conclusions:
- Combinations of immune cell subsets can robustly identify women with RPL, suggesting diagnostic potential.
- Menstrual blood provides a noninvasive and valuable source for assessing and monitoring reproductive health.
- Further research into these immune parameters could lead to improved diagnostics and management of RPL.
Objective:
To compare the immunologic profiles of peripheral and menstrual blood (MB) of women who experience recurrent pregnancy loss and women without pregnancy complications.
Design:
Explorative case-control study. Cross-sectional assessment of flow cytometry-derived immunologic profiles.
Setting:
Academic medical center.
Patient(S):
Women who experienced more than 2 consecutive miscarriages.
Intervention(S):
None.
Main Outcome Measure(S):
Flow cytometry-based immune profiles of uterine and systemic immunity (recurrent pregnancy loss, n = 18; control, n = 14) assessed by machine learning classifiers in an ensemble strategy, followed by recursive feature selection.
Result(S):
In peripheral blood, the combination of 4 cell types (nonswitched memory B cells, CD8+ T cells, CD56bright CD16- natural killer [NKbright] cells, and CD4+ effector T cells) classified samples correctly to their respective cohort. The identified classifying cell types in peripheral blood differed from the results observed in MB, where a combination of 6 cell types (Ki67+CD8+ T cells, (Human leukocyte antigen-DR+) regulatory T cells, CD27+ B cells, NKbright cells, regulatory T cells, and CD24HiCD38Hi B cells) plus age allowed for assigning samples correctly to their respective cohort. Based on the combination of these features, the average area under the curve of a receiver operating characteristic curve and the associated accuracy were >0.8 for both sample sources.
Conclusion(S):
A combination of immune subsets for cohort classification allows for robust identification of immune parameters with possible diagnostic value. The noninvasive source of MB holds several opportunities to assess and monitor reproductive health.
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