Marilen Benner

CHAPTER 5 110 ABSTRACT The underlying cause of recurrent pregnancy loss (RPL) remains largely unknown. As successful implantation and placentation depends on a tightly regulated immune response to facilitate adequate interaction with trophoblast cells, dysregulation of immunitymight account for idiopathic RPL. So far, studies focusing on single parameter analysis did not allow for clear classification of immunity in women with RPL versus healthy pregnancies. We here defined immune profiles in peripheral blood (PB) as well as menstrual blood (MB), a source of endometrial cells, of RPL patients and compared them to those of women with healthy pregnancies. Frequencies of 63 immune cell types defined by flow cytometry were included in the analysis, next to age and CMV status. By harnessing the combined value of 8 machine learning classifiers in an ensemble strategy and recursive feature selection, we were able to determine a combination of immune parameters that separated RPL from controls. In PB, the combination of four cell types (non-switched memory B cells, CD8 + CD4 - T cells, CD56 bright CD16 - Natural Killer (NKbright) cells, CD4 + effector T cells) classified samples correctly to their respective cohort. The identified classifying cell types in PB differed from the results observed in MB, where a combination of 6 cell types (Ki67 + CD8 + T cells, (HLA-DR + ) regulatory T cells, CD27 + B cells, NKbright cells, Treg cells, CD24 Hi CD38 Hi B cells) plus age allowed for assigning samples correctly to their respective cohort. This unbiased phenotyping approach focusing on immune profiles rather than single parameters might be of promising diagnostic value and deserves further large-scale validation.