From genes to reproductive health: Immune cell influences on abortion.

Abortion is a complex process that seriously threatens the health of women of childbearing age [ 1 ]. Approximately 15.3% of women have an abortion [ 2 ]. Common causes of abortion include anatomical abnormalities of the female reproductive tract, chromosomal abnormalities, endocrine abnormalities, and infections [ 3 ]. However, the cause of abortion is still unclear in 40–50% of patients [ 4 ]. Most abortions are thought to be related to immunological factors [ 5 ]. Therefore, further research on the interaction between abortion and immune factors is necessary. A variety of immune cells play a crucial role in maintaining immune balance during pregnancy. For example, a study showed that T cells can affect pregnancy outcomes by inducing Th-cells with different functions, such as Th1 and Th2, causing an imbalance of Th1 and Th2 [ 6 ]. In addition, it has been revealed that decreased levels of Treg cells can lead to adverse pregnancy outcomes, which can be used as a potential predictor of abortion [ 7 ]. Recent research suggests that an imbalance in the ratio between NK1 and NK2 may indicate abortion. The higher the value, the higher the risk of abortion [ 8 ]. Various immune factors secreted by different types of immune cell subtypes are crucial in maintaining a balanced immune tolerance at the immune-maternal-fetal interface [ 9 , 10 ]. This has important implications for women’s reproductive health. Understanding how immune cell phenotypes influence miscarriage risk is crucial for advancing reproductive medicine and enhancing maternal health outcomes. Prior research has established that immune cells could play a role in abortion [ 11 , 12 ]. Therefore, our study is based on the hypothesis that certain genetically determined immune cell phenotypes may be associated with the likelihood of abortion. In this case, we adopted a new approach, the epidemiological study design, the Mendelian randomization (MR) Analysis [ 13 ]. This approach is a robust way to evaluate the causal link between genetic variation and clinical outcomes. Utilizing genetic variation as instrumental variables, MR Analysis is able to isolate complex associations between exposure and outcomes while reducing the confounding and bias inherent in traditional observational studies [ 14 ]. Currently, some studies have used Mendelian randomization as a method in the study of diseases of the female reproductive system and have determined the causal relationship between immune cells and diseases such as polycystic ovary syndrome, endometriosis, and female reproductive disorders [ 15 – 17 ]. This provides new tools for understanding the basis of female reproductive diseases and immunology. Our analysis includes 731 immune cell signatures, categorizing them into seven distinct cell families: B cells, T cells, TBNK cells, Treg cells, cDC cells, bone marrow cells, and monocytes [ 18 ]. These immune cells perform immune functions, from cell counting to surface antigen expression, providing a broad lineage for analysis. Simultaneously, a two-sample Mendelian randomization (MR) analysis was conducted utilizing extensive genome-wide association study (GWAS) data from 257,561 individuals in Europe, encompassing 7,069 abortion cases and 250,492 controls [ 19 ]. We used rigorous statistical methods to obtain the results and performed a variety of sensitivity analyses to ensure the robustness of the results. We aimed to elucidate the immune cell phenotype associated with the risk of abortion and to clarify the directionality of the association. This is essential for individualized interventions, which may significantly improve reproductive health. In conclusion, this study represents a novel approach in reproductive immunology, leveraging the power of genetic epidemiology to elucidate the connections between immune cell traits and the likelihood of abortion. Our research has the potential to significantly impact clinical practices and improve outcomes for women worldwide by providing insights into the genetic basis of immune-mediated processes in reproduction.

This study identified 34 immune phenotypes that were causally related to the occurrence of abortion (p < 0.05), including 5 B cell subtypes, 4 T cell subtypes, 9 TBNK cell subtypes, 7 Treg cell subtypes, 7 cDC cell subtypes, and 2 monocyte subtypes (as shown in Fig 2 and S1 Table ). Among the B cell populations identified as being significantly associated with abortion in this study (p 1), whereas CD20 on IgD- CD27- was associated with a decreased risk of abortion (OR < 1). In Maturation stages of T cell group, Naive CD8br %T cell, CD4 on CD45RA+ CD4+ and CCR7 on naive CD4+ were negatively associated with abortion (OR 1). In TBNK cell group, CD4+ AC was negatively associated with abortion (OR < 1). CD8br %T cell, CD4+ CD8dim AC, CD4+ CD8dim %lymphocyte, CD4+ CD8dim %leukocyte, HLA DR+ CD4+ %lymphocyte, HLA DR+ NK AC, CD45 on lymphocyte and CD45 on CD8br were positively associated with abortion (OR > 1). *Abbreviations: IVW, inverse variance weighting; CI, confidence interval. In Treg cells, Resting Treg % CD4 Treg, Resting Treg %CD4, CD28-CD127-CD25 ++ CD8br %T cell and CD127 on CD28+ CD45RA+ CD8br were positively associated with abortion (OR > 1). CD3 on activated & secreting Treg, CD4 on CD28+ CD4+ and CD4 on resting Treg were negatively associated with abortion (OR 1). DC AC, CD62L-DC AC, CD62L-DC %DC, CD86+ myeloid DC AC and CD62L-myeloid DC AC were negatively associated with abortion (OR < 1). In the Monocyte group, the following immunophenotypes all have negative causal relationships with abortion: Monocyte AC and CCR2 on CD14+ CD16+ monocyte were negatively associated with abortion (OR < 1). We further confirmed the robustness of this causal relationship using sensitivity analysis ( S1 File and S2 Table ). Scatter plot and funnel plot also show the stability of the results ( S2 and S3 Files ). We also conducted a reverse Mendelian randomization analysis to investigate the impact of abortion on immune cell phenotype. The Inverse Variance Weighted method was utilized as the primary approach, with other methods serving as supplementary analyses ( Fig 3 and S3 Table ). We further confirmed the robustness of this causal relationship using sensitivity analysis ( S4 Table ). The results showed that abortion could promote PB/ PC% B cell and CD4 on resting the expression of Treg showed a positive causal relationship (p 1). abortion can inhibit CD62L-HLA DR++ monocyte %monocyte and CD20on IgD- The expression of CD27-(P = 0.043,OR = 0.811,95%CI = 0.662~0.993) showed a negative causal relationship (p < 0.05, OR < 1). *Abbreviations: IVW, inverse variance weighting; CI, confidence interval.

Our study delves into the causal relationship between different immune cell signatures and abortion through a bidirectional two-sample MR, shedding light on the intricate role of the immune system in pregnancy. And specific immune cell phenotypes may contribute to Abortion. In conclusion, our study opens new avenues for the prevention of Abortion and provides new testing indicators for pregnant women.

By employing bidirectional two-sample Mendelian randomization (MR) Analysis, we investigated the causal relationship between abortion and 731 immune cell characteristics, which were grouped into 7 categories. In the realm of causal inference, MR leverages genetic variations as proxies for potential risk factors, with instrumental variables (IVs) needing to satisfy three crucial assumptions for valid causal inference: (1) There was a strong correlation between genetic instrumental variables and the risk factors studied. (2) genetic instrumental variables were not correlated with any confounding factors. (3) genetic instrumental variables only affected outcomes through risk factors. The study analyzed GWAS data from 257,561 Europeans, comprising 7,069 cases and 250,492 controls. The GWAS encompassed 24,139,422 single nucleotide polymorphisms (SNPs) [ 19 ]. Each immune cell trait involved in our study is available in the publicly available GWAS database directory (registration numbers from GCST90001391 to GCST90002121) [ 20 ]. The catalog includes 731 immunophenotypes, categorizing them into seven distinct cell families: B cells, T cells, TBNK cells, Treg cells, cDC cells, bone marrow cells, and monocytes. The GWAS for initial immune characterization utilized data from 3,757 Europeans with no overlapping cohorts. Using a Sardinian sequence-based reference panel, SNPs for approximately 22 million high-density array genotypes were calculated. Correlations were analyzed after adjusting for covariates such as sex and age [ 21 ]. Genetic variation is closely associated with exposure factors. The significance level of the instrumental variable (IV) for immune signatures is typically set at 5×10 −6 . Researchers often utilize the ’TwoSampleMR’ package data to identify independent instrumental variables and set R 2 <0.001, kb = 10,000 to remove linkage disequilibrium (LD). When investigating the association between genetic factors and abortion, we adjusted the significance level and chose a higher threshold of 5 × 10 −8 for genome-wide association studies (GWAS). Additionally, the LD threshold was set to R 2 <0.001, kb = 10,000 to uphold the accuracy and reliability of the research findings. We utilized R software version 4.2.1 for all procedures ( http://www.Rproject.org ). To investigate the causal relationship between 731 immune phenotypes and abortion, we primarily employed the ’TwoSampleMR’ package (version 0.5.7) for MR analysis. In our study, the IVW method was used as the primary statistical method for MR analysis, in addition to the weighted median method as a complementary method, which provides robust causal estimates even when certain instrumental variables may not be valid if certain assumptions are satisfied. To enhance the robustness and reliability of our findings on the causal relationship between immune phenotype and miscarriage, sensitivity analyses were conducted. Furthermore, Cochran’s Q test was utilized to evaluate heterogeneity among instrumental variables. This statistical assessment, based on the comprehensive available data, enhances the accuracy and confidence of our results. The entire process is illustrated in Fig 1 . *Abbreviations: SNPs, single-nucleotide polymorphisms; IVW, inverse variance weighted; MR, Mendelian Randomization; MR Presso, Mendelian Randomization Pleiotropy RESidual Sum and Outlier.

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