Single-cell atlas of peripheral blood mononuclear cells from pregnant women

Answering open questions in biology using spatial genomics and structured methods

Genomics methods have uncovered patterns in a range of biological systems, but obscure important aspects of cell behavior: the shapes, relative locations, movement, and interactions of cells in space. Spatial technologies that collect genomic or epigenomic data while preserving spatial information have begun to overcome these limitations. These new data promise a deeper understanding of the factors that affect cellular behavior, and in particular the ability to directly test existing theories about cell state and variation in the context of morphology, location, motility, and signaling that could not be tested before. Rapid advancements in resolution, ease-of-use, and scale of spatial genomics technologies to address these questions also require an updated toolkit of statistical methods with which to interrogate these data. We present a framework to respond to this new avenue of research: four open biological questions that can now be answered using spatial genomics data paired with methods for analysis. We outline spatial data modalities for each open question that may yield specific insights, discuss how conflicting theories may be tested by comparing the data to conceptual models of biological behavior, and highlight statistical and machine learning-based tools that may prove particularly helpful to recover biological understanding.

Novel biomarkers for prediction of atonic postpartum hemorrhage among 'low-risk' women in labor

Background

Postpartum hemorrhage (PPH) is the primary cause of maternal mortality globally, with uterine atony being the predominant contributing factor. However, accurate prediction of PPH in the general population remains challenging due to a lack of reliable biomarkers.

Methods

Using retrospective cohort data, we quantified 48 cytokines in plasma samples from 40 women diagnosed with PPH caused by uterine atony. We also analyzed previously reported hemogram and coagulation parameters related to inflammatory response. The least absolute shrinkage and selection operator (LASSO) and logistic regression were applied to develop predictive models. Established models were further evaluated and temporally validated in a prospective cohort.

Results

Fourteen factors showed significant differences between the two groups, among which IL2Rα, IL9, MIP1β, TNFβ, CTACK, prenatal Hb, Lymph%, PLR, and LnSII were selected by LASSO to construct predictive model A. Further, by logistic regression, model B was constructed using prenatal Hb, PLR, IL2Rα, and IL9. The area under the curve (AUC) values of model A in the training set, internal validation set, and temporal validation set were 0.846 (0.757-0.934), 0.846 (0.749-0.930), and 0.875 (0.789-0.961), respectively. And the corresponding AUC values for model B were 0.805 (0.709-0.901), 0.805 (0.701-0.894), and 0.901 (0.824-0.979). Decision curve analysis results showed that both nomograms had a high net benefit for predicting atonic PPH.

Conclusion

We identified novel biomarkers and developed predictive models for atonic PPH in women undergoing "low-risk" vaginal delivery, providing immunological insights for further exploration of the mechanism underlying atonic PPH.

Impact of previous pregnancy and BMI on cellular and serum immune activity from early to late pregnancy

Immunological adaptions during pregnancy play a crucial role in healthy fetal development. Aberrant immune modifications however contribute to adverse pregnancy outcomes, which may be driven by maternal factors such as previous pregnancies and BMI. This secondary analysis of the MicrobeMom2 RCT investigates the changes to maternal inflammatory biomarkers derived from serum and stimulated peripheral blood mononuclear cells (PBMCs) during pregnancy, and the effects of previous pregnancies (parity) and BMI on maternal immune responses. Changes in immune and metabolic biomarkers from early (11-15 weeks' gestation) to late (28-32 weeks' gestation) pregnancy were compared using paired t-tests. Participants were then split by parity (nulliparous, parous) and BMI (BMI < 25, BMI > = 25), and the relationship between parity and BMI with immune biomarker levels was examined using independent t-tests, paired t-tests, ANCOVA, and linear regression. Equivalent non-parametric tests were used for skewed data. Recruited women (n = 72) were on average 31.17 (SD ± 4.53) years of age and 25.11 (SD ± 3.82) BMI (kg/m2). Of these, 51 (70.8%) had a previous term pregnancy. Throughout gestation, PBMC cytokines displayed contrasting trends to serum, with a dampening of immune responses noted in PBMCs, and enhanced production of cytokines observed in the serum. Significant decreases in PBMC derived TNF-α, IL-10 and IFN-γ were seen from early to late pregnancy. Serum C3, IL-17A, IL-6, TNF-α, CD163, GDF-15 and leptin increased throughout gestation. First pregnancy was associated with higher levels of leptin in late pregnancy, while parous women showed significant decreases in PBMC derived TNF-α, IL10, and IFN-γ with gestation. Differences in levels of C3, IL-17A, TNF-α, GDF-15 and leptin were observed across BMI groups. Overall, serum-derived cytokines exhibit contrasting levels to those derived from stimulated PBMCs. Maternal immune responses undergo significant changes from early to late pregnancy, which are influenced by parity and BMI. These differences aid our understanding as to why first-time mothers are at greater risk of placental disease such as pre-eclampsia and fetal growth restriction.

Predicting Spontaneous Preterm Birth Using the Immunome

Throughout pregnancy, the maternal peripheral circulation contains valuable information reflecting pregnancy progression, detectable as tightly regulated immune dynamics. Local immune processes at the maternal-fetal interface and other reproductive and non-reproductive tissues are likely to be the pacemakers for this peripheral immune "clock." This cellular immune status of pregnancy can be leveraged for the early risk assessment and prediction of spontaneous preterm birth (sPTB). Systems immunology approaches to sPTB subtypes and cross-tissue (local and peripheral) interactions, as well as integration of multiple biological data modalities promise to improve our understanding of preterm birth pathobiology and identify potential clinically actionable biomarkers.

Identification of circRNA Expression Profile and Potential Systemic Immune Imbalance Modulation in Premature Rupture of Membranes

Premature rupture of membrane (PROM) refers to the rupture of membranes before the onset of labor which increases the risk of perinatal morbidity and mortality. Recently, circular RNAs (circRNAs) have emerged as promising regulators of diverse diseases. However, the circRNA expression profiles and potential circRNA-miRNA-mRNA regulatory mechanisms in PROM remain enigmatic. In this study, we displayed the expression profiles of circRNAs and mRNAs in plasma and fetal membranes of PROM and normal control (NC) groups based on circRNA microarray, the Gene Expression Omnibus database, and NCBI's Sequence Read Archive. A total of 1,459 differentially expressed circRNAs (DECs) in PROM were identified, with 406 upregulated and 1,053 downregulated. Then, we constructed the circRNA-miRNA-mRNA network in PROM, encompassing 22 circRNA-miRNA pairs and 128 miRNA-mRNA pairs. Based on the analysis of gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene set enrichment analysis (GSEA), DECs were implicated in immune-related pathways, with certain alterations persisting even postpartum. Notably, 11 host genes shared by DECs of fetal membrane tissue and prenatal plasma in PROM were significantly implicated in inflammatory processes and extracellular matrix regulation. Our results suggest that structurally stable circRNAs may predispose to PROM by mediating systemic immune imbalances, including peripheral leukocyte disorganization, local immune imbalance at the maternal-fetal interface, and local collagen disruption. This is the first time to decipher a landscape on circRNAs of PROM, reveals the pathogenic cause of PROM from the perspective of circRNA, and opens up a new direction for the diagnosis and treatment of PROM.

Analytical Workflows for Single-Cell Multiomic Data Using the BD Rhapsody Platform

The conversion of raw sequencing reads to biologically relevant data in high-throughput single-cell RNA sequencing experiments is a complex and involved process. Drawing meaning from thousands of individual cells to provide biological insight requires ensuring not only that the data are of the highest quality but also that the signal can be separated from noise. In this article, we describe a detailed analytical workflow, including six pipelines, that allows high-quality data analysis in single-cell multiomics. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Image analysis Basic Protocol 2: Sequencing quality control and generation of a gene expression matrix Basic Protocol 3: Gene expression matrix data pre-processing and analysis Basic Protocol 4: Advanced analysis Basic Protocol 5: Conversion to flow cytometry standard (FCS) format Basic Protocol 6: Visualization using graphical interfaces.

Characterizing immune variation and diagnostic indicators of preeclampsia by single-cell RNA sequencing and machine learning

Preeclampsia is a multifactorial and heterogeneous complication of pregnancy. Here, we utilize single-cell RNA sequencing to dissect the involvement of circulating immune cells in preeclampsia. Our findings reveal downregulation of immune response in lymphocyte subsets in preeclampsia, such as reduction in natural killer cells and cytotoxic genes expression, and expansion of regulatory T cells. But the activation of naïve T cell and monocyte subsets, as well as increased MHC-II-mediated pathway in antigen-presenting cells were still observed in preeclampsia. Notably, we identified key monocyte subsets in preeclampsia, with significantly increased expression of angiogenesis pathways and pro-inflammatory S100 family genes in VCAN+ monocytes and IFN+ non-classical monocytes. Furthermore, four cell-type-specific machine-learning models have been developed to identify potential diagnostic indicators of preeclampsia. Collectively, our study demonstrates transcriptomic alternations of circulating immune cells and identifies immune components that could be involved in pathophysiology of preeclampsia.

Lupus and recurrent pregnancy loss: the role of female sex hormones and B cells

Systemic lupus erythematosus is a debilitating autoimmune disease characterized by uncontrolled activation of adaptive immunity, particularly B cells, which predominantly affects women in a 9 to 1 ratio compared to men. This stark sex disparity strongly suggests a role for female sex hormones in the disease's onset and progression. Indeed, it is widely recognized that estradiol not only enhances the survival of autoreactive B cells but also stimulates the production of autoantibodies associated with systemic lupus erythematosus, such as anti-nuclear antibodies and anti-dsDNA antibodies. Clinical manifestations of systemic lupus erythematosus typically emerge after puberty and persist throughout reproductive life. Furthermore, symptoms often exacerbate during the premenstrual period and pregnancy, as increased levels of estradiol can contribute to disease flares. Despite being fertile, women with lupus face a heightened risk of pregnancy-related complications, including pregnancy loss and stillbirth, which significantly surpass the rates observed in the healthy population. Therefore, this review aims to summarize and discuss the existing literature on the influence of female sex hormones on B-cell activation in patients with systemic lupus erythematosus, with a particular emphasis on their impact on pregnancy loss.

Challenges of clinical translation from single-cell sequencing to measures in clinical biochemistry of haematology: Definition of immune cell identities

Peripheral immune cells play important roles in the maintenance of systemic and microenvironmental hemostasis. Measurements of circulating blood cells by single-cell RNA sequencing (scRNA-seq) were proposed as one of the routine measures in clinical biochemistry of hematology. Out of translational challenges, defining precise identities of cell subsets and states is more difficult, due to the complexity of immune cell development, location, regulation, function, and metabolism. It is also a challenge to precisely interpret clinical significance and impact of each cell identity marker gene panel (ciMGPs). ciMGPs have potential to advance the understanding of systemic responses of the disease, identify disease-specific biomarkers, and to define cell heterogeneity. Recently, a large number of peripheral cell subsets and expending/activating states have been identified and validated for use in the fast developments in clinical single cell biomedicine. Defining specificity, measurability, and repeatability of cell subsets/states is important for translation of peripheral scRNA-seq in clinical hematology and biochemistry. The development of standard operating procedure and performance of clinical trials in large populations at various ages, diseases, and therapies will promote the clinical translation of ciMGPs to measures. Thus, defining cell subset/state identities will provide the multi-dimensional and comprehensive readouts of systemic immune cells, the precision monitoring of immune dynamics, and deeper-understanding of the disease and response to therapy.

Prominent epigenetic and transcriptomic changes in CD4+ and CD8+ T cells during and after pregnancy in women with multiple sclerosis and controls

BACKGROUND

Multiple sclerosis (MS) is a neuroinflammatory disease in which pregnancy leads to a temporary amelioration in disease activity as indicated by the profound decrease in relapses rate during the 3rd trimester of pregnancy. CD4⁺ and CD8⁺ T cells are implicated in MS pathogenesis as being key regulators of inflammation and brain lesion formation. Although Tcells are prime candidates for the pregnancy-associated improvement of MS, the precise mechanisms are yet unclear, and in particular, a deep characterization of the epigenetic and transcriptomic events that occur in peripheral T cells during pregnancy in MS is lacking.

METHODS

Women with MS and healthy controls were longitudinally sampled before, during (1st, 2nd and 3rd trimesters) and after pregnancy. DNA methylation array and RNA sequencing were performed on paired CD4⁺ and CD8⁺ T cells samples. Differential analysis and network-based approaches were used to analyze the global dynamics of epigenetic and transcriptomic changes.

RESULTS

Both DNA methylation and RNA sequencing revealed a prominent regulation, mostly peaking in the 3rd trimester and reversing post-partum, thus mirroring the clinical course with improvement followed by a worsening in disease activity. This rebound pattern was found to represent a general adaptation of the maternal immune system, with only minor differences between MS and controls. By using a network-based approach, we highlighted several genes at the core of this pregnancy-induced regulation, which were found to be enriched for genes and pathways previously reported to be involved in MS. Moreover, these pathways were enriched for in vitro stimulated genes and pregnancy hormones targets.

CONCLUSION

This study represents, to our knowledge, the first in-depth investigation of the methylation and expression changes in peripheral CD4⁺ and CD8⁺ T cells during pregnancy in MS. Our findings indicate that pregnancy induces profound changes in peripheral T cells, in both MS and healthy controls, which are associated with the modulation of inflammation and MS activity.

Single-cell analysis reveals novel clonally expanded monocytes associated with IL1β-IL1R2 pair in acute inflammatory demyelinating polyneuropathy

Guillain-Barré syndrome (GBS) is an autoimmune disorder wherein the composition and gene expression patterns of peripheral blood immune cells change significantly. It is triggered by antigens with similar epitopes to Schwann cells that stimulate a maladaptive immune response against peripheral nerves. However, an atlas for peripheral blood immune cells in patients with GBS has not yet been constructed. This is a monocentric, prospective study. We collected 5 acute inflammatory demyelinating polyneuropathy (AIDP) patients and 3 healthy controls hospitalized in the First Affiliated Hospital of Harbin Medical University from December 2020 to May 2021, 3 AIDP patients were in the peak stage and 2 were in the convalescent stage. We performed single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) from these patients. Furthermore, we performed cell clustering, cell annotation, cell-cell communication, differentially expressed genes (DEGs) identification and pseudotime trajectory analysis. Our study identified a novel clonally expanded CD14+ CD163+ monocyte subtype in the peripheral blood of patients with AIDP, and it was enriched in cellular response to IL1 and chemokine signaling pathways. Furthermore, we observed increased IL1β-IL1R2 cell-cell communication between CD14+ and CD16+ monocytes. In short, by analyzing the single-cell landscape of the PBMCs in patients with AIDP we hope to widen our understanding of the composition of peripheral immune cells in patients with GBS and provide a theoretical basis for future studies.

Current Status and Prospects of the Single-Cell Sequencing Technologies for Revealing the Pathogenesis of Pregnancy-Associated Disorders

Single-cell RNA sequencing (scRNA-seq) is a method that focuses on the analysis of gene expression profile in individual cells. This method has been successfully applied to answer the challenging questions of the pathogenesis of multifactorial diseases and open up new possibilities in the prognosis and prevention of reproductive diseases. In this article, we have reviewed the application of scRNA-seq to the analysis of the various cell types and their gene expression changes in normal pregnancy and pregnancy complications. The main principle, advantages, and limitations of single-cell technologies and data analysis methods are described. We discuss the possibilities of using the scRNA-seq method for solving the fundamental and applied tasks related to various pregnancy-associated disorders. Finally, we provide an overview of the scRNA-seq findings for the common pregnancy-associated conditions, such as hyperglycemia in pregnancy, recurrent pregnancy loss, preterm labor, polycystic ovary syndrome, and pre-eclampsia.