Fetal inflammatory response syndrome (FIRS) is strongly associated with neonatal morbidity and mortality and can be classified as type I or type II. Clinically, FIRS type I and type II are considered as distinct syndromes, yet the molecular underpinnings of these fetal inflammatory responses are not well understood because of their low prevalence and the difficulty of postdelivery diagnosis. In this study, we performed RNA sequencing of human cord blood samples from preterm neonates diagnosed with FIRS type I or FIRS type II. We found that FIRS type I was characterized by an upregulation of host immune responses, including neutrophil and monocyte functions, together with a proinflammatory cytokine storm and a downregulation of T cell processes. In contrast, FIRS type II comprised a mild chronic inflammatory response involving perturbation of HLA transcripts, suggestive of fetal semiallograft rejection. Integrating single-cell RNA sequencing–derived signatures with bulk transcriptomic data confirmed that FIRS type I immune responses were mainly driven by monocytes, macrophages, and neutrophils. Last, tissue- and cell-specific signatures derived from the BioGPS Gene Atlas further corroborated the role of myeloid cells originating from the bone marrow in FIRS type I. Collectively, these data provide evidence that FIRS type I and FIRS type II are driven by distinct immune mechanisms; whereas the former involves the innate limb of immunity consistent with host defense, the latter resembles a process of semiallograft rejection. These findings shed light on the fetal immune responses caused by infection or alloreactivity that can lead to deleterious consequences in neonatal life.

Infection of the amniotic cavity, also known as microbial-induced intra-amniotic inflammation, is caused by ascending invasion of bacteria from the lower genital tract into amniotic fluid (1, 2). Intra-amniotic infection is associated with multiple obstetrical complications, such as spontaneous preterm labor (38), preterm prelabor rupture of membranes (9, 10), cervical insufficiency or short cervix (11, 12), idiopathic vaginal bleeding (13), and both histological (14) and clinical (15) chorioamnionitis, among others. Moreover, intra-amniotic infection is associated with maternal morbidity (16) as well as neonatal morbidity and mortality (1719). The latter are thought to be induced by bacteria invading the amniotic cavity that, in turn, can trigger a fetal systemic inflammatory response characterized by activation of the innate immune system (2022), a condition that has been termed fetal inflammatory response syndrome (FIRS), given its similarity to the systemic inflammatory response syndrome observed in adults (23). FIRS resulting from intra-amniotic infection, referred to as FIRS type I, is defined by elevated umbilical cord blood (hereafter also referred to as cord blood) concentrations of IL-6 together with the presence of fetal acute inflammatory lesions of the umbilical cord (i.e., funisitis) (2328). Investigations of the cord blood from neonates with FIRS type I demonstrated increased innate immune activation and oxidative burst compared to those without this syndrome (29), and microarray analysis revealed altered expression of specific inflammatory genes (30). Yet, the immunological processes taking place in FIRS type I are still under investigation.

More recently, a different and rarer type of FIRS was identified in fetuses born to mothers who presented chronic inflammatory lesions of the placenta (i.e., chronic chorioamnionitis, plasma cell deciduitis, and chronic villitis) (31), which was characterized by elevated concentrations of the chemokine CXCL10 in the fetal cord blood plasma (31). This distinct fetal inflammatory response, termed FIRS type II, was proposed to occur as a result of maternal antifetal rejection rather than intra-amniotic infection (21, 31). Indeed, microarray analysis of cord blood from neonates with FIRS type II demonstrated that multiple acute inflammatory genes were unaltered or decreased compared to those without FIRS (31). Furthermore, the comparison of microarray results from neonates with FIRS type II and FIRS type I suggested that the inflammatory responses occurring in these syndromes are divergent (31). Yet, the immune pathways driving FIRS type II, and how these differ from FIRS type I, are still poorly understood.

Recently, RNA sequencing (RNAseq) has been used to shed light on the immunological mechanisms of intra-amniotic infection in the innate immune cells from amniotic fluid (32) as well as the extraplacental chorioamniotic membranes (33). Furthermore, single-cell RNAseq has revealed the maternal and fetal cellular landscape of the placental tissues in preterm and term parturition (34). However, such cutting-edge techniques have not been applied to the research of FIRS. To fill this gap in knowledge, in the current study, we performed RNAseq of cord blood samples from preterm neonates diagnosed with FIRS type I or FIRS type II. Specifically, we first investigated differential gene expression to reveal immunological processes enriched in FIRS type I and FIRS type II as well as differences between these syndromes. We further used established single-cell RNAseq signatures to deconvolve our bulk RNAseq data and determine the contribution of specific immune cell subsets to the immune responses observed in FIRS type I and FIRS type II. Last, we used the BioGPS Gene Atlas to evaluate the changes in tissue- and cell-specific signatures that occur in FIRS type I. Our findings elucidate the distinct molecular signatures underlying the inflammatory responses of FIRS type I and FIRS type II.

Umbilical cord blood samples were retrospectively obtained from the Biological Bank of the Perinatology Research Branch, an intramural program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, U.S. Department of Health and Human Services, Wayne State University (Detroit, MI), and the Detroit Medical Center (Detroit, MI). The collection and use of human materials for research purposes were approved by the Institutional Review Boards of Wayne State University and NICHD. All participating women provided written informed consent prior to sample collection. The study included umbilical cord blood samples from neonates born to women who underwent spontaneous preterm labor with intact membranes. Study groups included samples from preterm neonates: 1) with FIRS type I (n = 11) (see Clinical definitions below), 2) with FIRS type II (n = 6), and 3) without fetal inflammatory response syndrome (No FIRS) (n = 22) as controls. The demographic and clinical characteristics of the study groups are shown in Table I. Women with preterm prelabor rupture of membranes, multiple gestations, or those who had a fetus with chromosomal and/or sonographic abnormalities were excluded. Maternal and neonatal data were obtained by retrospective clinical chart review.

Preterm labor was defined as the presence of regular uterine contractions occurring at a frequency of at least two every 10 min associated with cervical change, followed by delivery before 37 completed weeks of gestation. FIRS type I was defined by an umbilical cord blood IL-6 concentration >11 pg/ml and the presence of acute funisitis (see Placental histopathological examination below). FIRS type II was defined by an umbilical cord blood CXCL10 concentration >75th percentile (82.34 pg/ml) (31), the presence of chronic placental inflammation (see Placental histopathological examination below), and an umbilical cord blood IL-6 concentration <11 pg/ml.

Histopathological examination of the placenta was performed by perinatal pathologists blinded to clinical diagnoses and obstetrical outcomes according to standardized Perinatology Research Branch protocols. Acute inflammatory lesions of the placenta (maternal inflammatory response), defined as the invasion of maternal neutrophils, were diagnosed according to established criteria, including staging and grading (28). Severity is reported as stages, where stage 1 indicates early acute subchorionitis or chorionitis, stage 2 indicates acute chorioamnionitis, and stage 3 indicates necrotizing chorioamnionitis (28). Early acute subchorionitis or chorionitis (stage 1) may not be representative of infection but rather the inflammatory processes associated with labor (35); therefore, only stages 2 and 3 were considered as acute histologic chorioamnionitis. Chronic placental inflammation was defined upon observation of one or more findings of chronic chorioamnionitis, chronic villitis, and chronic deciduitis diagnosed according to previously established criteria (36).

Fetal inflammatory responses were histologically evaluated by the presence and severity of acute lesions (i.e., neutrophil invasion) into the umbilical cord (funisitis) or chorionic plate (chorionic vasculitis) (26, 28). Severity was reported as stages, where stage 1 indicates umbilical phlebitis and/or chorionic vasculitis (mild inflammation), stage 2 indicates umbilical arteritis (severe inflammation), and stage 3 indicates necrotizing funisitis (total inflammation and necrosis in the umbilical cord) (28). Stages 2 and 3 are considered as acute funisitis.

The umbilical cord blood plasma was assessed for concentrations of IL-6, IL-1β, TNF, and IL-8 with sensitive and specific V-PLEX immunoassays (Meso Scale Discovery, Gaithersburg, MD), according to the manufacturer’s instructions. CXCL10 was assessed with the Human CXCL10/IP-10 Quantikine ELISA Kit (R&D Systems, Minneapolis, MN), according to the manufacturer’s instructions.

RNA was isolated from umbilical cord blood collected in PAXgene Blood RNA Tubes using the PAXgene Blood miRNA Kit (QIAGEN; Hilden, Germany), according to the manufacturer’s instructions. The RNA concentrations were measured on a Trinean DropSense96 spectrophotometer (Trinean, Pleasanton, CA), and the RNA quality was assessed with the Agilent 2200 TapeStation (Agilent Technologies, Wilmington, DE). The RNAseq library was prepared with the TruSeq Stranded Total RNA Library Prep Kit (Illumina, San Diego, CA). Paired-end sequence reads of 100-bp length were generated by using the HiSeq 2500 sequencer (Illumina). RNAseq was performed at the Applied Genomics Technological Center of Wayne State University (https://genomesciencescore.wayne.edu/).

Paired-end RNASeq FASTQ files were aligned with Salmon (37) in mapping mode by using a transcriptome index prepared from Homo sapiens genome assembly GRCh38 (hg38), release 101, published by Ensembl. Transcripts per million count data were used to test for differential expression based on negative binomial models implemented in the DESeq2 (38) package from Bioconductor (39). Gestational age at delivery was included as a covariate in the models to adjust for potential confounding effects. Genes with a minimum fold change of 1.25-fold and an adjusted p value of <0.1 were considered as differentially expressed. The differentially expressed genes (DEGs) from each comparison were used as input in iPathwayGuide (Advaita, Ann Arbor, MI) (4042) to determine the significantly impacted pathways. Volcano plots were used to display the evidence of differential expression for each comparison. iPathwayGuide pathway annotations were derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, release 96.0+/11-21, November 2020 (43, 44). The top 10 most significantly enriched Gene Ontology (GO) biological processes in strictly upregulated or downregulated genes are also shown. Predicted upstream regulators based on differential expression results were inferred using iPathwayGuide based on regulatory network definitions from BioGRID (45, 46) and iPathwayGuide’s proprietary knowledge base. Tissue-specific genes (tissue signatures) were defined as those with a median expression >30 times higher in a given tissue than the median expression of all other tissues described in the BioGPS Human U133A/GNF1H Gene Atlas (47, 48) (http://www.biogps.org). Read count data were adjusted to remove the effect of gestational age at delivery based on the effects of gestational age in the control (No FIRS) group; then, counts were used to compute Z-scores averaged across tissue signatures to compare the groups. Box plots of the average Z-scores in each group were drawn for comparisons that resulted in significant differences. Similar analyses were performed with single-cell signatures derived from Tsang et al. (49).

Principal component analysis (PCA) (50) of bulk RNAseq gene expression data was performed by using a subset of cell type-specific genes derived from single-cell RNAseq studies. Briefly, we extracted the genes from prior reports (34, 5153) to create a binary matrix G indicating which gene (column) is present in each cell type (row) for each of the following immune cell types: B cell, eosinophil, erythroid, macrophage-1, macrophage-2, monocyte, neutrophil, NK cell, progenitor, and T cell. The cell type binary matrix G and the bulk RNAseq data matrix B were multiplied together to create a cell signature matrix C = GB, where each row represents cell type metagenes and each column represents a study sample from which bulk RNAseq data were obtained. Next, PCA was performed on this matrix C, using the prcomp() function from the stats R package to extract the top two principal components (PC) and to identify the cell signatures with the strongest contribution to PC1 and PC2 (PCA loading analysis). A t test was performed to compare each study group based on PC1 and PC2, and p values were adjusted by the Bonferroni method (54). The R package factoextra (55) was used to visualize the study sample distribution within PC1/PC2 as well as the correlations between cell type signatures and PC1/PC2. This procedure was performed twice, using two different B matrices: 1) the bulk gene expression matrix without any adjustment and 2) after adjusting the gene expression matrix by the gestational age at delivery.

GraphPad Prism version 8.0.1 for Windows (GraphPad Software, San Diego, CA) was used to conduct statistical analyses of patient demographic characteristics and cytokine data. The Kruskal–Wallis test or one-way ANOVA on ranks with post hoc multiple comparisons was used to compare continuous variables. The Fisher exact test was used for nominal variables. The Mann–Whitney U test was used to compare cytokine concentrations and tissue-signature Z-scores between groups. A p value <0.05 was considered statistically significant.

A total of 39 umbilical cord blood samples was collected from neonates born to women with spontaneous preterm labor and intact membranes who delivered preterm. Among these neonates, 11 were diagnosed with FIRS type I (see Clinical definitions section), 6 were diagnosed with FIRS type II (see Clinical definitions section), and the remaining 22 neonates without FIRS or acute placental inflammation served as controls (No FIRS) (Table I). Neonates with FIRS type I were delivered at an earlier gestational age than those with FIRS type II or without FIRS; therefore, count data were adjusted for this covariate. The birthweight and Apgar scores at 1 and 5 min were consistently lower in FIRS type I compared to the other study groups (Table I). As the FIRS type I diagnosis included the presence of acute fetal and maternal inflammatory responses, such parameters were significantly higher in neonates with FIRS type I than the other study groups. Moreover, as the FIRS type II diagnosis included the presence of chronic maternal inflammatory response, such lesions were significantly more prevalent in neonates with FIRS type II than the other study groups. No differences in maternal age, body mass index, primiparity, race, or mode of delivery were found among the study groups (Table I).

Table I.

Clinical and demographic characteristics of the study groups

No FIRS (n = 22)FIRS Type I (n = 11)FIRS Type II (n = 6)p Value
Maternal age (y; median [IQR])a 23 (20.5–25) 23 (22–35) 21.5 (21–27.3) 0.5 
Body mass index (kg/m2; median [IQR])a 24.8 (20.2–27.6)b 24.8 (21.6–29.4)b 24 (23.4–25.1) 0.7 
Primiparityc 13.6% (3/22) 9.1% (1/11) 16.7% (1/6) 1.0 
Race/ethnicityc    0.9 
 African-American 81.8% (18/22) 81.8% (9/11) 83.3% (5/6)  
 White 9.1% (2/22) 9.1% (1/11) 0% (0/6)  
 Other 9.1% (2/22) 9.1% (1/11) 16.7% (1/6)  
Gestational age at delivery (wk; median [IQR])a 35.6 (33.7–36.2) 29.3 (27.2–33.4) 34.8 (33.3–36.6) <0.001 
Cesarean sectionc 13.6% (3/22) 36.4% (4/11) 16.7% (1/6) 0.3 
Birthweight (g; median [IQR])a 2532.5 (2210-2759) 1170 (1075-2153) 2270 (2026-2679) <0.001 
Apgar score at 1 min (median [IQR])a 8 (8–8) 5 (2.5–7.5) 8 (7.3–8.8) 0.009 
Apgar score at 5 min (median [IQR])a 9 (9–9) 7 (5.5–8.5) 9 (8.3–9) <0.001 
Acute maternal inflammatory responsec     
 Stage 1 (early acute subchorionitis or chorionitis) 0% (0/22) 0% (0/10)b 16.7% (1/6) 0.2 
 Stage 2 (acute chorioamnionitis) 0% (0/22) 50% (5/10)b 0% (0/6) <0.001 
 Stage 3 (necrotizing chorioamnionitis) 0% (0/22) 50% (5/10)b 0% (0/6) <0.001 
Acute fetal inflammatory responsec     
 Stage 1 (chorionic vasculitis or umbilical phlebitis) 0% (0/22) 0% (0/10)b 16.7% (1/6) 0.06 
 Stage 2 (umbilical arteritis) 0% (0/22) 80% (8/10)b 0% (0/6) <0.001 
 Stage 3 (necrotizing funisitis) 0% (0/22) 20% (2/10)b 0% (0/6) 0.09 
Chronic maternal inflammatory responsec     
 Chronic deciduitis 0% (0/22) 36.4% (4/11) 100% (6/6) <0.001 
 Chronic villitis 0% (0/22) 0% (0/11) 50% (3/6) 0.002 
 Chronic chorioamnionitis 0% (0/22) 0% (0/11) 66.7% (4/6) <0.001 
No FIRS (n = 22)FIRS Type I (n = 11)FIRS Type II (n = 6)p Value
Maternal age (y; median [IQR])a 23 (20.5–25) 23 (22–35) 21.5 (21–27.3) 0.5 
Body mass index (kg/m2; median [IQR])a 24.8 (20.2–27.6)b 24.8 (21.6–29.4)b 24 (23.4–25.1) 0.7 
Primiparityc 13.6% (3/22) 9.1% (1/11) 16.7% (1/6) 1.0 
Race/ethnicityc    0.9 
 African-American 81.8% (18/22) 81.8% (9/11) 83.3% (5/6)  
 White 9.1% (2/22) 9.1% (1/11) 0% (0/6)  
 Other 9.1% (2/22) 9.1% (1/11) 16.7% (1/6)  
Gestational age at delivery (wk; median [IQR])a 35.6 (33.7–36.2) 29.3 (27.2–33.4) 34.8 (33.3–36.6) <0.001 
Cesarean sectionc 13.6% (3/22) 36.4% (4/11) 16.7% (1/6) 0.3 
Birthweight (g; median [IQR])a 2532.5 (2210-2759) 1170 (1075-2153) 2270 (2026-2679) <0.001 
Apgar score at 1 min (median [IQR])a 8 (8–8) 5 (2.5–7.5) 8 (7.3–8.8) 0.009 
Apgar score at 5 min (median [IQR])a 9 (9–9) 7 (5.5–8.5) 9 (8.3–9) <0.001 
Acute maternal inflammatory responsec     
 Stage 1 (early acute subchorionitis or chorionitis) 0% (0/22) 0% (0/10)b 16.7% (1/6) 0.2 
 Stage 2 (acute chorioamnionitis) 0% (0/22) 50% (5/10)b 0% (0/6) <0.001 
 Stage 3 (necrotizing chorioamnionitis) 0% (0/22) 50% (5/10)b 0% (0/6) <0.001 
Acute fetal inflammatory responsec     
 Stage 1 (chorionic vasculitis or umbilical phlebitis) 0% (0/22) 0% (0/10)b 16.7% (1/6) 0.06 
 Stage 2 (umbilical arteritis) 0% (0/22) 80% (8/10)b 0% (0/6) <0.001 
 Stage 3 (necrotizing funisitis) 0% (0/22) 20% (2/10)b 0% (0/6) 0.09 
Chronic maternal inflammatory responsec     
 Chronic deciduitis 0% (0/22) 36.4% (4/11) 100% (6/6) <0.001 
 Chronic villitis 0% (0/22) 0% (0/11) 50% (3/6) 0.002 
 Chronic chorioamnionitis 0% (0/22) 0% (0/11) 66.7% (4/6) <0.001 

Data are given as median (IQR) and percentage (n/N).

a

Kruskal–Wallis/one-way ANOVA test with multiple comparison.

b

One missing datum.

c

Fisher exact test.

IQR, interquartile range.

To determine the inflammatory and transcriptomic differences between neonates diagnosed with FIRS type I and those without FIRS, we evaluated the cord blood plasma concentrations of proinflammatory mediators and performed RNAseq of cord blood samples (Fig. 1A). In addition to the expected increase in IL-6 concentrations, higher levels of IL-8, CXCL10, IL-1β, and TNF were detected in neonates with FIRS type I compared to those without FIRS (Fig. 1B), which is consistent with the severe acute inflammatory nature of this syndrome. In line to these high levels of inflammatory mediators, RNAseq analysis revealed 1,385 DEGs in the cord blood of neonates with FIRS type I compared to those without FIRS, with 955 being upregulated (red dots) and 430 downregulated (blue dots), as shown in the volcano plot (Fig. 1C). Notably, gene expression changes in FIRS type I were highly correlated with those previously reported using microarrays (30); yet, the larger sample size and increased sensitivity of RNAseq allowed us to identify twice as many DEGs as previously reported (Supplemental Fig. 1A, 1B). The DEGs were then analyzed to determine impacted KEGG database pathways. Among the 149 pathways with significant enrichment, T cell receptor signaling pathway, Th17 differentiation, and Th1 and Th2 cell differentiation were among the top 10 (Fig. 1D), suggesting that T cell responses are affected in neonates with FIRS type I. Next, such DEGs were used to perform upstream regulator analysis to predict the activation or inhibition of specific upstream molecules. Upstream regulators predicted as activated included cytoskeletal and chromosomal genes, whereas upstream regulators predicted as inhibited were mainly related to cell proliferation (Fig. 1E). The GO biological processes that were enriched among genes upregulated in neonates with FIRS type I included host response terms, such as neutrophil degranulation, defense response to other organism, phagocytosis, FcγR signaling pathway, Fc receptor–mediated stimulatory signaling pathway, and regulation of IL-8 production (Fig. 1F). In contrast, downregulated genes were enriched for terms related to adaptive immunity, such as adaptive immune response, T cell receptor signaling pathway, T cell differentiation, T cell costimulation, and positive regulation of lymphocyte proliferation (Fig. 1G). These results demonstrate that the transcriptome of FIRS type I is characterized by the upregulation of host innate immune processes, indicative of acute inflammation, together with suppressed T cell responses.

FIGURE 1.

FIRS type I involves the upregulation of host immune responses.

(A) Experimental design showing the transcriptomic comparison between cord blood from neonates diagnosed with FIRS type I (n = 11) and those without FIRS (n = 22). (B) Plasma concentrations of IL-6, IL-8, CXCL10, IL-1β, and TNF in the cord blood of neonates with FIRS type I (red dots) or No FIRS (blue dots). Data are presented as box plots in which midlines indicate medians, boxes indicate interquartile range, and whiskers indicate minimum/maximum range. The p values were obtained using Mann–Whitney U tests. ****p < 0.0001. (C) Volcano plot showing the DEGs between cord blood from neonates diagnosed with FIRS type I and No FIRS. Red dots indicate upregulation and blue dots indicate downregulation. (D) KEGG pathway impact analysis evidence showing significantly enriched pathways based on DEGs from the cord blood of neonates diagnosed with FIRS type I and No FIRS. (E) Predicted activated and inhibited upstream regulators of DEGs in cord blood from neonates diagnosed with FIRS type I and No FIRS. (F and G) Overrepresentation analysis of GO annotations using genes significantly upregulated (F) or downregulated (G) in cord blood from neonates diagnosed with FIRS type I compared to that of No FIRS. The top 10 most enriched biological processes are shown. NS, not significant.

FIGURE 1.

FIRS type I involves the upregulation of host immune responses.

(A) Experimental design showing the transcriptomic comparison between cord blood from neonates diagnosed with FIRS type I (n = 11) and those without FIRS (n = 22). (B) Plasma concentrations of IL-6, IL-8, CXCL10, IL-1β, and TNF in the cord blood of neonates with FIRS type I (red dots) or No FIRS (blue dots). Data are presented as box plots in which midlines indicate medians, boxes indicate interquartile range, and whiskers indicate minimum/maximum range. The p values were obtained using Mann–Whitney U tests. ****p < 0.0001. (C) Volcano plot showing the DEGs between cord blood from neonates diagnosed with FIRS type I and No FIRS. Red dots indicate upregulation and blue dots indicate downregulation. (D) KEGG pathway impact analysis evidence showing significantly enriched pathways based on DEGs from the cord blood of neonates diagnosed with FIRS type I and No FIRS. (E) Predicted activated and inhibited upstream regulators of DEGs in cord blood from neonates diagnosed with FIRS type I and No FIRS. (F and G) Overrepresentation analysis of GO annotations using genes significantly upregulated (F) or downregulated (G) in cord blood from neonates diagnosed with FIRS type I compared to that of No FIRS. The top 10 most enriched biological processes are shown. NS, not significant.

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Fetal inflammatory response type II has been proposed to occur in the context of a distinct maternal–fetal reaction that resembles graft-versus-host disease (GVHD) (36, 56). Therefore, we next evaluated the cord blood inflammatory response and transcriptome in neonates with FIRS type II (Fig. 2A). The acute inflammation that characterizes FIRS type I was absent in neonates with FIRS type II, as indicated by the similar levels of IL-6, IL-8, IL-1β, and TNF compared to those without FIRS (Fig. 2B). Consistent with a mild chronic inflammatory response, only 40 DEGs were identified in neonates with FIRS type II compared to those without FIRS, with 3 being upregulated and 37 being downregulated (Fig. 2C). Notably, several HLA genes were identified among these DEGs, namely HLA-F, HLA-C, and HLA-DRA, with the first being upregulated and the latter two downregulated (Fig. 2C). Based on these three transcripts, multiple KEGG pathways were identified as enriched, including GVHD, allograft rejection, and Ag processing and presentation, as well as several viral response-related pathways (Fig. 2D). Therefore, the transcriptome of FIRS type II is characterized by a mild state of systemic inflammation that is suggestive of fetal semiallograft rejection.

FIGURE 2.

FIRS type II is suggestive of fetal semiallograft rejection.

(A) Experimental design showing the transcriptomic comparison between cord blood from neonates diagnosed with FIRS type II (n = 6) and those without FIRS (n = 22). (B) Plasma concentrations of IL-6, IL-8, CXCL10, IL-1β, and TNF in the cord blood of neonates with FIRS type II (orange dots) or No FIRS (blue dots). Data are presented as box plots in which midlines indicate medians, boxes indicate interquartile range, and whiskers indicate minimum/maximum range. The p values were obtained using Mann–Whitney U tests. ****p < 0.0001. (C) Volcano plot showing the DEGs between cord blood from neonates diagnosed with FIRS type II and No FIRS. Red dots indicate upregulation and blue dots indicate downregulation. (D) KEGG pathway impact analysis evidence plot showing gene overrepresentation evidence (pORA) and total pathway accumulation evidence (pAcc) based on differential expression between cord blood from neonates with FIRS type II and No FIRS. Significantly impacted pathways are shown as red dots.

FIGURE 2.

FIRS type II is suggestive of fetal semiallograft rejection.

(A) Experimental design showing the transcriptomic comparison between cord blood from neonates diagnosed with FIRS type II (n = 6) and those without FIRS (n = 22). (B) Plasma concentrations of IL-6, IL-8, CXCL10, IL-1β, and TNF in the cord blood of neonates with FIRS type II (orange dots) or No FIRS (blue dots). Data are presented as box plots in which midlines indicate medians, boxes indicate interquartile range, and whiskers indicate minimum/maximum range. The p values were obtained using Mann–Whitney U tests. ****p < 0.0001. (C) Volcano plot showing the DEGs between cord blood from neonates diagnosed with FIRS type II and No FIRS. Red dots indicate upregulation and blue dots indicate downregulation. (D) KEGG pathway impact analysis evidence plot showing gene overrepresentation evidence (pORA) and total pathway accumulation evidence (pAcc) based on differential expression between cord blood from neonates with FIRS type II and No FIRS. Significantly impacted pathways are shown as red dots.

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Neonates with FIRS type I displayed a distinct inflammatory profile and transcriptome in the cord blood compared to No FIRS neonates, whereas neonates with FIRS type II demonstrated subtle yet specific changes. Thus, we next directly compared FIRS type I and FIRS type II to further unravel the differences between these two syndromes (Fig. 3A). The plasma concentrations of IL-6, IL-8, IL-1β, and TNF were increased in neonates with FIRS type I compared to those with FIRS type II, highlighting the acute inflammatory nature of the former (Supplemental Fig. 2). Interestingly, only 130 DEGs were identified, likely because of the smaller sample size for this comparison as well as potentially shared immune processes between FIRS type I and FIRS type II (Fig. 3B). Among these DEGs, pathways, such as allograft rejection, GVHD, Ag processing and presentation, Th17 cell differentiation, and Th1 and Th2 cell differentiation were enriched (Fig. 3C), emphasizing that a key difference between FIRS type I and FIRS type II is the regulation of T cell responses. Upstream regulators predicted as activated in FIRS type I included multiple G protein–related molecules (e.g., GNAI3, GNAO1, GNAZ, RGS1, and GNAI2), potentially indicating increased transmembrane signaling, whereas predicted inhibited regulators included several molecules involved in T cell function, such as CCL5, TNFSF4, PTPR, and CIITA (Fig. 3D). Last, we performed overrepresentation analysis of GO annotations using only upregulated or downregulated DEGs to allow a closer look into the specific processes associated with FIRS type I or FIRS type II. Among the upregulated DEGs (i.e., increased in FIRS type I), notable enriched processes included negative regulation of chronic inflammatory response and monocyte activation, although these did not reach statistical significance (Fig. 3E). Notably, downregulated DEGs (i.e., increased in FIRS type II) showed enrichment of adaptive immune response, negative regulation of NK cell cytokine production, and regulation of IL-4 production (Fig. 3F). Other biological processes, such as peptide Ag assembly with MHC class II protein complex, negative regulation of IFN-γ production, IFN-γ–mediated signaling pathway, and negative regulation of B cell activation, were also enriched among downregulated DEGs, although not significantly (Fig. 3F). These observations demonstrate key differences between the immune responses involved in FIRS type I and FIRS type II that point to the proposed divergent etiologies of these two syndromes.

FIGURE 3.

FIRS type I and FIRS type II involve distinct immunological processes.

(A) Experimental design showing the transcriptomic comparison between cord blood from neonates diagnosed with FIRS type I (n = 11) and those with FIRS type II (n = 6). (B) Volcano plot showing the DEGs between cord blood from neonates diagnosed with FIRS type I and those with FIRS type II. Red dots indicate upregulation, and blue dots indicate downregulation. (C) KEGG pathway impact analysis evidence showing the top 10 significantly enriched pathways based on DEGs from the cord blood of neonates diagnosed with FIRS type I and those with FIRS type II. (D) Predicted activated and inhibited upstream regulators of DEGs in cord blood from neonates diagnosed with FIRS type I and those with FIRS type II. (E and F) Overrepresentation analysis of GO annotations using genes significantly upregulated (E) or downregulated (F) in cord blood from neonates diagnosed with FIRS type I compared to those with FIRS type II. The top 10 most enriched biological processes are shown. NS, not significant.

FIGURE 3.

FIRS type I and FIRS type II involve distinct immunological processes.

(A) Experimental design showing the transcriptomic comparison between cord blood from neonates diagnosed with FIRS type I (n = 11) and those with FIRS type II (n = 6). (B) Volcano plot showing the DEGs between cord blood from neonates diagnosed with FIRS type I and those with FIRS type II. Red dots indicate upregulation, and blue dots indicate downregulation. (C) KEGG pathway impact analysis evidence showing the top 10 significantly enriched pathways based on DEGs from the cord blood of neonates diagnosed with FIRS type I and those with FIRS type II. (D) Predicted activated and inhibited upstream regulators of DEGs in cord blood from neonates diagnosed with FIRS type I and those with FIRS type II. (E and F) Overrepresentation analysis of GO annotations using genes significantly upregulated (E) or downregulated (F) in cord blood from neonates diagnosed with FIRS type I compared to those with FIRS type II. The top 10 most enriched biological processes are shown. NS, not significant.

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Given the observed differences in the transcriptomes of FIRS type I and FIRS type II, we next performed PCA of single-cell gene expression signatures to further reveal the relationship among the three groups in a multidimensional gene expression space. Such analysis showed that the FIRS type I transcriptome was distinct from that of FIRS type II or No FIRS, according to the second PC (PC2) (Fig. 4A). Consistently, the PCA plot demonstrated that the transcriptome of FIRS type I clustered separately from that of FIRS type II or No FIRS, an effect that was driven by PC2 (Fig. 4B). However, the transcriptome of FIRS type II was indistinguishable from that of No FIRS (Fig. 4A, 4B). PCA loading analysis showed that the FIRS type I immune responses that aligned with PC2 were mainly driven by myeloid cells, such as monocytes, macrophages (macrophage-1 and macrophage-2), and, to a lesser extent, neutrophils, together with a decrease in T cells and NK cells (Fig. 4C). Hence, the immune responses in FIRS type I are associated with the innate limb of immunity, whereas FIRS type II may be more closely related to adaptive immunity.

FIGURE 4.

Single-cell RNAseq-derived signatures in FIRS type I and FIRS type II.

(A) Experimental design showing the PCA analysis of single-cell RNAseq-derived signatures performed using the cord blood transcriptomes of neonates diagnosed with FIRS type I (n = 11), those with FIRS type II (n = 6), and those without FIRS (n = 22). The table shows the results of the pairwise comparisons of PC1 and PC2 between study groups. Comparisons were performed using t tests, and p values were adjusted using Bonferroni method. (B) PCA plot showing the distribution of cord blood transcriptomes from those with FIRS type I, FIRS type II, and No FIRS according to PC1 and PC2. (C) PCA loading vector plot showing the individual contribution (contrib) and correlation of immune cell signatures with PC1 (Dim1) and PC2 (Dim2). Vector length and color indicate contribution, and vector direction indicates correlation with PC1 and PC2.

FIGURE 4.

Single-cell RNAseq-derived signatures in FIRS type I and FIRS type II.

(A) Experimental design showing the PCA analysis of single-cell RNAseq-derived signatures performed using the cord blood transcriptomes of neonates diagnosed with FIRS type I (n = 11), those with FIRS type II (n = 6), and those without FIRS (n = 22). The table shows the results of the pairwise comparisons of PC1 and PC2 between study groups. Comparisons were performed using t tests, and p values were adjusted using Bonferroni method. (B) PCA plot showing the distribution of cord blood transcriptomes from those with FIRS type I, FIRS type II, and No FIRS according to PC1 and PC2. (C) PCA loading vector plot showing the individual contribution (contrib) and correlation of immune cell signatures with PC1 (Dim1) and PC2 (Dim2). Vector length and color indicate contribution, and vector direction indicates correlation with PC1 and PC2.

Close modal

We sought to determine the effect of gestational age on the immune responses implicated in FIRS type I and FIRS type II. Therefore, the PCA and loading analysis were repeated by using RNAseq data without adjustment for gestational age. The monocyte cell signature remained the primary driver of the FIRS type I immune response (Supplemental Fig. 3A, 3B). Yet, both FIRS type II and No FIRS were associated with erythroid cell signature loading aligned with PC1, indicating that the function of these immune cells is influenced by gestational age (Supplemental Fig. 3A, 3B).

Last, we used cell- and tissue-specific signatures derived from the BioGPS Gene Atlas and overlaid these with our bulk RNAseq data to further explore the cord blood transcriptome in FIRS type I (Fig. 5A). In line with our previous findings, a monocyte cell signature was identified as upregulated in neonates with FIRS type I compared to No FIRS neonates (Fig. 5B), as were signatures for CD14+ monocytes and CD33+ myeloid cells (Supplemental Fig. 4A, 4B). Notably, a dendritic cell signature was found to be downregulated in FIRS type I compared to No FIRS neonates (Fig. 5C), which may be linked to the lack of Ag-presentation T cell responses observed in this syndrome. In addition, tissue-specific signatures corresponding to bone marrow and whole blood were also upregulated in neonates with FIRS type I (Supplemental Fig. 4C, 4D). The increased bone marrow signature may reflect accelerated hematopoietic processes in this compartment leading to elevated myeloid cells, particularly monocytes, in the cord blood, whereas the whole blood signature may be indicative of the general upregulation of systemic immune and cellular metabolic processes occurring in FIRS type I.

FIGURE 5.

FIRS type I comprises cell- and tissue-specific RNAseq signatures.

(A) Experimental design showing tissue-specific RNAseq signatures derived from the BioGPS Gene Atlas (http://www.biogps.org) in neonates diagnosed with FIRS type I (n = 11) and those without FIRS (n = 22). (B) Box plot showing the Z-scores of the monocyte cell signature in neonates with FIRS type I and No FIRS. (C) Box plot showing the Z-scores of the dendritic cell signature in neonates with FIRS type I and No FIRS. Data are presented as box plots in which midlines indicate medians, boxes indicate interquartile range, and whiskers indicate minimum/maximum range. The p values were obtained using Mann–Whitney U tests.

FIGURE 5.

FIRS type I comprises cell- and tissue-specific RNAseq signatures.

(A) Experimental design showing tissue-specific RNAseq signatures derived from the BioGPS Gene Atlas (http://www.biogps.org) in neonates diagnosed with FIRS type I (n = 11) and those without FIRS (n = 22). (B) Box plot showing the Z-scores of the monocyte cell signature in neonates with FIRS type I and No FIRS. (C) Box plot showing the Z-scores of the dendritic cell signature in neonates with FIRS type I and No FIRS. Data are presented as box plots in which midlines indicate medians, boxes indicate interquartile range, and whiskers indicate minimum/maximum range. The p values were obtained using Mann–Whitney U tests.

Close modal

Intra-amniotic infection is strongly associated with obstetrical complications, including spontaneous preterm labor and birth (38), clinical chorioamnionitis (15), sepsis (16), and hemorrhage (16), of which the latter two can lead to maternal death (57, 58). In severe cases, intra-amniotic infection can result in an exaggerated inflammatory response in the fetus, presenting as FIRS type I (23). In this study, we found that neonates with FIRS type I display upregulation of host innate immune responses that are largely associated with neutrophils and monocytes.

Neutrophils act as the first line of defense against invading pathogens by performing phagocytosis, degranulation, release of antimicrobial molecules, and cytokine production, and by forming neutrophil extracellular traps (NETs) as a last resort (59). Prior studies have shown that fetal neutrophils present in the amniotic cavity carry out phagocytosis of bacteria commonly associated with intra-amniotic infection (e.g., Ureaplasma spp., Gardnerella vaginalis, group B Streptococcus, and Escherichia coli) (60), degranulate (6163), release proinflammatory cytokines (e.g., TNF, IL-1β, and MIP-1β) (64, 65), and form NETs (6567). In the cord blood, neutrophils can also perform phagocytosis (68) and release NETs (66), albeit at a reduced capacity. This impairment, at least partially, results from the presence of inhibitory molecules, such as neonatal NET-inhibitory factor (nNIF) (69), potentially as a means of controlling aberrant inflammatory responses. Microarray analyses similarly indicated downregulated chemotactic and phagocytic processes in cord blood neutrophils from term neonates (70). Yet, transcriptomic investigation of fetal neutrophils with RNAseq indicated that these innate immune cells do not drastically differ from maternal neutrophils (32); thus, their functional impairment may be a result of the microenvironment (e.g., the fetal circulation) rather than intrinsic deficiencies. Regardless, cord blood neutrophils display higher basal levels of intracellular reactive oxygen species production in fetuses with FIRS type I compared to those without this syndrome (29).

Monocytes are traditionally considered as a primary source of inflammatory mediators (71) but are also highly plastic, and their effector functions depend on the microenvironment (7274). During bacterial infection, monocytes can also act as professional phagocytes (75, 76) and may participate in Ag presentation (77). In the amniotic cavity, fetal monocytes are primary responders to bacterial infection and display upregulation of cytokine signaling, including the IL-6 and IL-1β pathways (32, 64, 65, 78). Furthermore, fetal monocytes are highly abundant in the umbilical cord and chorionic vessels in cases of intra-amniotic infection (i.e., funisitis and chorionic vasculitis), and may therefore migrate from these compartments into the amniotic cavity (78). In the cord blood, monocytes carry out effector functions, such as phagocytosis (79, 80), cytokine release (8184), and Ag presentation, (85) that are comparable to adult peripheral monocytes (80, 83). However, differences in functionality between fetal and adult monocytes have also been documented (8082, 8486), further supporting the influence of the microenvironment on their activity. In women with preterm delivery whose placentas displayed funisitis, cord blood monocytes are elevated (87) and exhibit increased intracellular reactive oxygen species production (29). Moreover, we recently proposed that fetal monocytes are also capable of orchestrating cellular trafficking in the amniotic cavity, contributing to the inflammatory milieu taking place during local infection (32).

In the fetus, the primary niche for hematopoietic stem cells is the liver, which is also a major source of monocytes (88, 89). Yet, hematopoietic stem cells and monocytes are also found in the bone marrow by the second trimester of pregnancy (9093). Therefore, the upregulated bone marrow signature described in the current study may indicate altered or accelerated hematopoiesis in neonates with FIRS type I, leading to elevated myeloid lineage cells and monocytes in the circulation. This phenomenon could be explained by the hyperinflammatory state taking place in neonates with FIRS type I (21, 23, 30), similar to that observed in adults with systemic inflammatory response syndrome. Such a state of inflammation could activate bone marrow hematopoiesis, given that under high-stress conditions this process can be altered by cytokines or microbial products to accommodate the demand for myeloid cells (i.e., emergency myelopoiesis) (94, 95). Future mechanistic studies may explore the contribution of emergency myelopoiesis to the systemic inflammation taking place in neonates with FIRS type I.

Notably, in the current study, neonates with FIRS type I displayed downregulation of T cell processes. One potential explanation for this phenomenon could be thymic involution, which is frequently observed in neonates with acute illness (96). Importantly, thymic involution has also been described in fetuses exposed to intra-amniotic infection (97101) and can be used as a sonographic marker of FIRS type I (97, 101). Consistently, fetuses of mothers with histological chorioamnionitis and neonates who died of sepsis within 48 h of life both displayed reduced thymus volume, decreased corticomedullary ratio, significant depletion of thymocytes, and altered architecture between the thymic parenchyma and interstitial tissue (102). Animal studies have also shown that endotoxin-induced intra-amniotic inflammation was associated with a reduced fetal thymus/body weight ratio (103) and thymic corticomedullary ratio (104) accompanied by decreased numbers of Foxp3+ cells (103105), CD8+ cells (106), and MHC class II+ cells (106) in the thymic cortex as well as increased cellular apoptosis (104) and upregulation of proinflammatory cytokines (104) in the fetal thymus. Furthermore, reduced lymphocyte numbers and increased cortisol concentrations were observed in the cord blood of fetal lambs (103). The latter finding, which reflects the activation of the hypothalamic–pituitary–adrenal (HPA) axis, suggests that one of the possible mechanisms of thymic involution in FIRS type I is through the activation of this axis by elevated cord blood proinflammatory cytokine concentrations. Indeed, IL-1, IL-6, and TNF are effective stimulators of the HPA axis (107, 108). Moreover, the postnatal administration of IL-1 in rats was associated with adrenal gland enlargement, higher plasma concentrations of corticosterone, and increased thymic involution compared to controls (109). Yet, whether such HPA axis activation and thymic involution are associated with the transcriptomic changes observed in neonates with FIRS type I in this study requires further investigation.

In this study, we found that neonates with FIRS type II displayed enrichment of allograft rejection and GVHD processes, which is consistent with prior studies (31, 56, 110). The hallmark characteristic of FIRS type II is the elevated level of CXCL10 in the fetal circulation in the absence of increased concentrations of proinflammatory cytokines (e.g., IL-6, IL-8, and TNF) (31), as reported in this study. Similarly, systemic CXCL10 concentrations are increased in cases of GVHD (111113) and allograft rejection (e.g., heart, kidney, lung, et cetera) (114122). CXCL10 is primarily a T cell chemokine that induces the migration of lymphocytes to sites of inflammation (123), mediates the induction of apoptosis, and regulates cell growth and proliferation as well as angiogenesis through the CXCR3 receptor (124); thus, this chemokine is implicated in the cellular mechanisms of allograft rejection. Specifically, CXCL10, together with the other CXCR3 ligands CXCL9 and CXCL11, is hypothesized to modulate maternal antifetal rejection (125127). Alternatively, the elevated cord blood CXCL10 levels in FIRS type II might indicate a fetal response toward the mother. In line with this reasoning, previous reports have shown that fetal T cells are responsive toward maternal alloantigens (128131), and dysregulation of this process could lead to disease, including preterm birth (130). Indeed, we have shown that fetal T cells are activated in a subset of women with spontaneous preterm labor in the absence of acute intra-amniotic inflammation (132). Moreover, the intra-amniotic injection of activated neonatal T cells resulted in preterm birth in mice (132). Together, these findings represent a novel mechanism of disease in which the fetus drives the premature process of labor (132). Nonetheless, whether such a process is implicated in the pathophysiology of FIRS type II requires additional research.

We found that neonates with FIRS type II displayed increased expression of HLA-F together with decreased expression of HLA-C and HLA-DRA. HLA-F is a nonclassical MHC class I molecule that can bind activating and inhibitory receptors on NK cells and other subsets and may also present Ag to T cells (133, 134). HLA-F is expressed by extravillous trophoblasts (135), and its reduced expression is associated with pregnancy complications (134, 136), suggesting that dysregulation of this molecule is involved in the chronic inflammatory process that characterizes FIRS type II. Unlike HLA-F, HLA-C and HLA-DRA are associated with immunological tolerance (137141); therefore, the downregulation of these molecules may represent a pathological state in neonates with FIRS type II. However, the involvement of these HLA molecules in the pathophysiology of FIRS type II requires further investigation.

An interesting observation from the current study was that an erythroid cell signature was highly affected by gestational age. Nucleated erythrocyte precursors or erythroid cells have been proposed to play a role in neonatal immunity (142144). More recently, CD71+ erythroid cells were shown to display immunomodulatory functions in the cord blood from humans and mice (145, 146), although their effectiveness in this regard has also been questioned (147). Such nucleated erythroid cells tend to diminish with gestational age (148) and continue to decrease during the neonatal period (149). Yet, cord blood CD71+ erythroid cells may also be involved in the pathophysiology of spontaneous preterm labor, as neonates born to women with this obstetrical syndrome displayed reduced proportions of these cells compared to neonates delivered preterm because of medical indications (148). Thus, CD71+ erythroid cells may not strongly contribute to the pathophysiology of FIRS type I or FIRS type II but rather to gestational age-dependent fetal immune responses.

A limitation of the current study is the absence of functional and immunophenotyping assays of cord blood immune cells to confirm the transcriptomic findings obtained by RNAseq. Yet, it is worth mentioning that the samples included in this study were collected over a period of several years, given the difficulty of obtaining cord blood samples from preterm neonates. In addition, the above determinations would require freshly collected samples, which does not fit with the current study design because the diagnosis of FIRS is performed after histological evaluation of the placenta and determination of cord blood cytokine concentrations.

In summary, we found that FIRS type I was characterized by an upregulation of host immune responses, including neutrophil and monocyte functions, together with a proinflammatory cytokine storm and a downregulation of T cell processes. In contrast, FIRS type II comprised a mild chronic inflammatory response involving perturbation of HLA transcripts, suggestive of fetal semiallograft rejection. By using single-cell RNAseq-derived signatures and PCA loading analysis, we further implicated monocytes, macrophages, and neutrophils in the immune responses of FIRS type I. Last, tissue- and cell-specific signatures derived from the BioGPS Gene Atlas further corroborated the role of myeloid cells originating from the bone marrow in FIRS type I. Taken together, these findings shed light on the fetal immune responses caused by infection or alloreactivity that can lead to deleterious consequences in neonatal life.

We thank the physicians and nurses from the Center for Advanced Obstetrical Care and Research and the Intrapartum Unit of the Perinatology Research Branch for help in collecting human samples. The authors also thank the staff members of the Perinatology Research Branch Clinical Laboratory and Histology/Pathology Unit for the processing and examination of the pathological sections.

This work was supported in part by the Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), U.S. Department of Health and Human Services (DHHS) and, in part, with federal funds from NICHD/NIH/DHHS under Contract HHSN275201300006C. R.R. has contributed to this work as part of his official duties as an employee of the U.S. Federal Government. This research was also supported by the Wayne State University Perinatal Initiative in Maternal, Perinatal and Child Health. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The sequences presented in this article have been submitted to Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE176127.

The online version of this article contains supplemental material.

Abbreviations used in this article

DEG

differentially expressed gene

FIRS

fetal inflammatory response syndrome

GO

Gene Ontology

GVHD

graft-versus-host disease

HPA

hypothalamic–pituitary–adrenal

KEGG

Kyoto Encyclopedia of Genes and Genomes

NET

neutrophil extracellular trap

No FIRS

neonate without fetal inflammatory response syndrome

PC

principal component

PCA

principal component analysis

RNAseq

RNA sequencing

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The authors have no financial conflicts of interest.

This article is distributed under the terms of the CC BY 4.0 Unported license.

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