
==== Front
BMJ Paediatr Open
BMJ Paediatr Open
bmjpo
bmjpo
BMJ Paediatrics Open
2399-9772
BMJ Publishing Group BMA House, Tavistock Square, London, WC1H 9JR

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10.1136/bmjpo-2024-002708
bmjpo-2024-002708
Original Research
Neonatology
1506
Plasma proteomic signature of neonates in the context of placental histological chorioamnionitis
Liu Jing 12liujing906@163.com

Liu Die 1liudiepku@yahoo.com

Sun Qi 1cmusunqi@163.com

Su Yunchao 3ycsuyc@foxmail.com

Tang Lijuan 1tanglijuan0620@163.com

Liang Haixiao 1418519369@qq.com

Ye Fang 1yefang@bjmu.edu.cn

Chen Yuanmei 1chen_yuanmei@yeah.net

http://orcid.org/0000-0001-5803-2556
Zhang Qi 12zhangqikeyan@163.com

1 Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
2 Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
3 Department of Pathology, China-Japan Friendship Hospital, Beijing, China
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Additional supplemental material is published online only. To view, please visit the journal online (https://doi.org/10.1136/bmjpo-2024-002708 ).

No, there are no competing interests.

Dr; zhangqikeyan@163.com
2024
04 9 2024
8 1 e00270817 4 2024
16 8 2024
Copyright © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
2024
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Abstract

Background

Placental histological chorioamnionitis (HCA) is recognised as a significant risk factor for various adverse neonatal outcomes. This study aims to explore if the inflammatory protein levels in neonates were associated with HCA.

Methods

All women with singleton births from February 2020 to November 2022 were selected and divided into three groups based on maternal placental pathology results: the HCA-stage 1 group (n=24), the HCA-stage 2 group (n=16) and the control group (n=17). Olink Target 96 Inflammation Panel was used to detect the levels of 92 inflammation-related proteins in the plasma of newborns from all three groups within 24 hours after birth. We compared the protein profiles through differential protein expression analysis.

Results

A total of six inflammation-related proteins exhibited significant differences between the HCA-stage 1 and the control group. Specifically, TRANCE and CST5 were significantly upregulated (p=0.006, p=0.025, respectively), whereas the expression of IFN-gamma, CXCL9, CXCL10 and CCL19 was significantly downregulated (p=0.040, p=0.046, p=0.007, p=0.006, respectively). HCA-stage 2 newborns had significantly elevated levels of CD5 and CD6 and decreased IFN-gamma, CXCL10 and CCL19 in comparison to controls. These differential proteins were significantly enriched in positive regulation of cytokine activity, leucocyte chemotaxis and positive regulation of T-cell activation pathway-related Gene Ontology terms. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that viral protein interaction with cytokine and cytokine receptor, interleukin-17/NF-kappa B/toll-like receptor/chemokine signalling pathway, and cytokine-cytokine receptor interaction exhibited significant differences. Spearman analysis demonstrated a significant positive connection between the levels of CD6 and CD5 proteins, not only in neonatal leucocytes but also in maternal leucocytes. Additionally, CD6 was found to be associated with neonatal birth weight.

Conclusions

In conclusion, placental histological changes associated with chorioamnionitis appear to influence the expression of inflammatory proteins in offspring. Notably, CD6 and CD5 proteins may potentially contribute to the pathogenesis of HCA-related neonatal diseases.

infant
neonatology
National High Level Hospital Clinical Research Funding 2022-NHLHCRF-LX-01-0301 the Clinical research project of Beijing research ward construction 2022-YJXBF-04-01-03
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pmcWHAT IS ALREADY KNOWN ON THIS TOPIC

WHAT THIS STUDY ADDS

This study identifies inflammatory protein profiles in neonates with HCA, including the upregulation of TRANCE and CST5 and downregulation of CXCL9 and CXCL10.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

The findings could guide the development of early diagnostic tools and targeted therapies, improving care for neonates at risk of HCA-related complications.

Introduction

The perinatal period is a critical window for fetal development. An unfavourable intrauterine environment, marked by conditions such as placental inflammation may have far-reaching and enduring effects on the subsequent health of newborns, extending into their adulthood.1 2 Among the various inflammatory conditions affecting the placenta, chorioamnionitis stands as the most common and widely studied inflammatory lesion. Histological chorioamnionitis (HCA) is pathologically confirmed as inflammation of the chorionic villi and/or amniotic membrane, characterised by predominant neutrophil infiltration.3 Although histological evidence of chorioamnionitis is found in up to 40% of preterm placentas and is particularly prevalent in placentas before 24 weeks of gestation, affecting approximately 90% of cases,4 it is noteworthy that this condition still complicates up to 3% to 5% of term deliveries.5 The majority of affected mothers do not present with clinical symptoms of infection, such as fever. In fact, only a small minority, approximately 13% of women exhibit such clinical manifestations.6

HCA is intricately linked to a spectrum of adverse neonatal outcomes, heightening the risk of premature birth, pneumonia, bronchopulmonary dysplasia, respiratory distress syndrome, sepsis, and even encephalitis and brain injury.712 Furthermore, research has revealed that individuals exposed to chorioamnionitis during fetal development may confront an elevated vulnerability to chronic inflammatory diseases later in life, such as asthma and neurodevelopmental disorders.13 14 These lines of evidence collectively underscore the profound influence of inflammation on immune programming during pivotal developmental windows. Nevertheless, the pathogenesis of HCA-related neonatal disease remains enigmatic and insufficiently elucidated.

There has been a growing emphasis on investigating changes in inflammatory mediators. HCA has been found to elevate proinflammatory cytokines in both amniotic fluid and fetal cord blood. Notably, studies have revealed that patients with severe chorioamnionitis exhibit increased levels of inflammatory cytokines, including interleukin 1β (IL-1β), IL-6, IL-8, tumour necrosis factor-α (TNF-α) MCP-1 and G-CSF, in the cord blood.15 16 Additionally, Wong et al identified a robust association between the loss of CXCR1 immune expression in umbilical cord endothelial cells and fetal death.17 Their findings suggest that CXCR1 may serve as a promising biomarker for predicting adverse perinatal outcomes in pregnancies complicated by chorioamnionitis. Studies have underscored the pivotal role of IL-1 in driving the intricate pathogenesis of fetal inflammatory responses triggered by chorioamnionitis.18 Despite these notable advancements, a comprehensive understanding of the intricate network of inflammatory mediators in HCA-related neonatal complications remains an ongoing research endeavour.

Proteins play a pivotal role as signalling molecules in orchestrating immune responses and vital cellular processes. Perturbations in their profile may offer crucial insights into the systemic effects of HCA on neonates. In this study, we set out to examine disparities in plasma inflammatory protein levels among neonates born to mothers with varying degrees of HCA. By deciphering the altered protein profiles and understanding their biological roles, we aim to shed light on the complex mechanisms underlying HCA-related neonatal complications.

Materials and methods

Study design and participants

This prospective study enrolled neonates and their mothers who gave birth at a tertiary general hospital in Beijing between February 2020 and November 2022. The following inclusion criteria were applied: (1) single live birth; (2) conception occurring through natural means; (3) maternal age >18 years; (4) placenta, fetal membranes and umbilical cord were intact and sent for pathological examination and (5) complete clinical data. Exclusion criteria encompassed: (1) neonates with congenital abnormalities or genetic metabolic diseases; (2) cases with missing clinical records and (3) instances where family members did not cooperate in completing relevant laboratory tests. Ultimately, a total of 57 eligible participants meeting these criteria were included in the study. Participants were categorised into three groups based on placental pathological results: the HCA-stage 1 group (n=24), the HCA-stage 2 group (n=16) and the control group (n=17). This study received ethical approval from the ethics committee of our hospital (2023-KY-057). Informed consent forms were obtained from their legal guardians.

Maternal and fetal clinical information was retrieved from the hospital’s electronic medical record system. Maternal parameters included age, mode of delivery and blood routine results before treatment. Neonatal parameters included gender, gestational age at birth, birth weight and parity (if applicable).

Placental pathology

Trained pathologists followed standardised protocols in accordance with Amsterdam standards to sample the placenta, fetal membranes and umbilical cord tissue. These specimens were subsequently fixed in 10% formaldehyde, embedded in paraffin, sectioned and stained with H&E for pathological examination. The classification of chorioamnionitis stages adhered to Amsterdam criteria: acute subchorionitis or chorionitis was assigned to HCA stage 1 group, while acute chorioamnionitis, characterised by polymorphonuclear leucocytes extending into the fibrous chorion and/or amnion, was designated as HCA stage 2 group.19 Participants without HCA were assigned to the normal control group.

Inflammation-related proteins quantification

Blood samples were obtained from newborns within 4 hours after birth and before feeding and clinical treatment to assess standard biochemical and routine blood parameters. Additionally, some samples were collected into EDTA tubes, followed by centrifugation to separate the plasma component. The isolated plasma was subsequently stored in a −80°C refrigerator until it was ready for further analysis.

Using the Proximity Extension Assay technology, we employed the Olink Target 96 Inflammation (V.3024) Panels for the simultaneous detection of 92 inflammation-related proteins. 92 oligonucleotide-labelled antibody probe pairs were allowed to bind to their respective target proteins, if present in the sample.20 On binding, complementary oligonucleotide pairs are extended by DNA polymerase, forming amplified PCR reporter sequences. Quantitative PCR (qPCR detects these sequences, and the resulting data are transformed into normalised protein expression (NPX) values using logarithmic transformation of qPCR CT values. NPX values provide a relative quantitative measure on a Log2 scale.

Each detection panel is subject to two primary quality control systems: internal and external. The internal quality controls include two immunoassay controls, one extension control and one detection control. The external quality control involves eight samples that serve for within-batch and between-batch coefficient of variation calculations, limit of detection determination and data normalisation. Deviate <0.3 NPX from the median value of all samples on the plate median pass the quality control. Scatterplots displaying the NPX distributions for all samples are generated to identify any outliers within the dataset.

Bioinformatics analysis

Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses were conducted using the R package ‘ClusterProfiler’.21 To investigate the correlation and interactions among the differential proteins, a protein network interaction graph was constructed using the online tool String (V.11.5).

Statistical analysis

Differences in baseline and clinical variables were assessed using appropriate statistical tests, including χ2 test or Fisher’s exact test for categorical variables, Mann-Whitney U test or t-test for continuous variables. NPX data were statistically compared using the standard two-tailed t-test. To evaluate the associations and correlations between differential proteins and maternal and fetal clinical parameters, Spearman rank correlation analysis was used. All statistical analyses were carried out using R software (V.4.1.1).

Results

Demographic and clinical characterisation of the participants

A total of 57 eligible participants were categorised into three groups based on placental pathological results: HCA-stage 1 (n=24), HCA-stage 2 (n=16) and control (n=17). Table 1 summarises the clinical characteristics of the mothers in this study. Maternal age showed no statistically significant differences among the groups (31.54±3.43 vs 32.63±4.49 vs 32.18±3.38, p=0.659). However, maternal leucocyte and neutrophil counts differed significantly, with the HCA-stage 2 group having higher counts compared with the control group (16.79±5.28 vs 11.35±4.07, p=0.009; 14.64±5.19 vs 8.79±2.93, p=0.004, respectively). No significant variations were noted in other blood parameters. Table 2 presents the clinical characteristics of the neonates. Gestational age, gender distribution, birth weight and parity did not significantly differ among the groups. Neonatal leucocyte levels, however, were notably higher in the HCA-stage 2 group compared with the control group (12.88±5.44 vs 9.06±3.21, p=0.025). Other neonatal blood parameters did not exhibit significant differences.

Table 1 Maternal characteristics

Variables	HCA-stage 1 (n=24)	HCA-stage 2 (n=16)	Controls (n=17)	P value	
Age at delivery (years), mean±SD	31.54±3.43	32.63±4.49	32.18±3.38	0.659	
Delivery mode, n (%)				0.124	
 Forceps delivery	4 (16.67)	1 (6.25)	0		
 Spontaneous vaginal delivery	12 (50.00)	6 (37.5)	5 (29.41)		
 Caesarean section	8 (33.33)	9 (56.25)	12 (70.59)		
Gravidity, mean±SD	1.38±0.49	1.69±1.25	1.35±0.79	0.442	
Parity, mean±SD	1.13±0.34	1.25±0.58	1.12±0.33	0.584	
PROM, n (%)	13 (54.2)	5 (31.2)	7 (41.2)	0.347	
Placental abruption, n (%)	1 (4.2)	0 (0.0)	1 (5.9)	0.840	
Low-lying placenta, n (%)	1 (4.2)	0 (0.0)	1 (5.9)	0.840	
Placenta previa, n (%)	1 (4.2)	0 (0.0)	0 (0.0)	0.709	
GDM, n (%)	5 (20.8)	8 (50.0)	6 (35.3)	0.156	
Gestational hypertension, n (%)	0 (0.0)	0 (0.0)	2 (11.8)	0.087	
Pre-eclampsia, n (%)	1 (4.2)	0 (0.0)	1 (5.9)	0.639	
GBS (+), n (%)	1 (4.2)	0 (0.0)	0 (0.0)	0.497	
Antenatal antibiotics, n (%)	1 (4.2)	0 (0.0)	1 (5.9)	0.639	
Antenatal corticosteroids, n (%)	3 (12.5)	0 (0.0)	1 (5.9)	0.309	
WBC (109 /L), mean±SD	13.06±5.42	16.79±5.28*	11.35±4.07	0.009	
NEUT (109 /L), mean±SD	11.02±5.55	14.64±5.19*	8.79±2.93	0.004	
LYMPH (109 /L), mean±SD	1.41±0.67	1.38±0.51	1.81±1.73	0.420	
MONO (109 /L), mean±SD	0.55±0.17	0.69±0.26	0.57±0.29	0.169	
RBC (1012 /L), mean±SD	3.81±0.37	4.02±0.61	3.77±0.27	0.188	
HGB (g/L), mean±SD	115.17±15.42	119.13±14.40	118.71±13.62	0.635	
PLT (109 /L), mean±SD	200.46±63.49	238.38±70.54	194.35±35.91	0.072	
* P value <0.05 for the comparison between HCA-stage 2 and Ccontrols.

GBS, group B streptococcus; GDM, gestational diabetes mellitus; HCA, histological chorioamnitis; HGB, haemoglobin; LYMPH, lymphocyte; MONO, monocytes; NEUT, neutrophil; PLT, plateletPROM, premature rupture of membranes; RBC, red blood cell; WBC, white blood cell

Table 2 Neonatal outcomes

Variables	HCA-stage 1 (n=24)	HCA-stage 2 (n=16)	Controls (n=17)	P value	
Gestational age (days), mean±SD	252.13±24.49	258.75±23.01	249.94±17.08	0.493	
Sex, n (%)				0.763	
 Male	14 (58.33)	9 (56.25)	8 (47.06)		
 Female	10 (41.67)	7 (43.75)	9 (52.94)		
Preterm birth	13 (76.5)	16 (66.7)	7 (43.8)	0.135	
Birth weight (g), mean±SD	2569.79±682.31	2825.31±747.46	2415.29±590.35	0.222	
WBC (109 /L), mean±SD	10.73±2.39	12.88±5.44*	9.06±3.21	0.025	
NEUT (109 /L), mean±SD	5.06±1.56	6.52±3.55	4.51±2.19	0.077	
LYMPH (109 /L), mean±SD	3.97±1.63	4.39±1.96	3.22±1.25	0.142	
MONO (109 /L), mean±SD	1.17±0.41	1.36±0.67	0.93±0.31	0.056	
RBC (1012 /L), mean±SD	3.89±0.52	4.30±0.58	4.03±0.59	0.110	
HGB (g/L), mean±SD	135.33±21.32	149.86±21.75	140.75±23.43	0.174	
PLT (109 /L), mean±SD	320.52±117.53	270.93±92.13	285.56±100.38	0.363	
MAO(U/L), mean±SD	5.92±1.60	5.21±1.88	6.34±1.90	0.240	
LAP(U/L), mean±SD	62.25±15.18	70.50±22.58	61.50±14.67	0.300	
AFU(U/L), mean±SD	33.80±9.31	28.07±7.33	32.56±11.51	0.225	
SA (mg/dl), mean±SD	30.20±4.05	30.93±5.50	28.88±5.50	0.516	
SOD (U/ml), mean±SD	195.66±68.56	223.53±90.89	203.29±44.09	0.527	
For an explanation of other abbreviations, please refer to table 1.

* P value <0.05 for the comparison between HCA-stage 2 and Ccontrols.

AFU, α-l-fucosidase; HGBhaemoglobinLAP, leucine aminopeptidase; LYMPHlymphocyteMAO, monoamine oxidase; MONOmonocytesPLTplateletRBCred blood cellSA, sialic acid; SOD, superoxide dismutaseWBCwhite blood cell

Olink inflammation proteomic signature in offspring plasma

We assessed the levels of inflammation-related proteins using the Olink Target 96 Inflammation Panel (online supplemental table S1). Quality control checks revealed that three samples triggered warnings, but their deviation remained within an acceptable range, so we included them in the analysis (online supplemental figure S1).

Between the HCA-1 group and the control group, we identified six differential inflammation-related proteins (figure 1A, online supplemental table S2). These proteins included interferon gamma (IFN-gamma 7.47±1.71 vs 8.54±1.51, p=0.040), TNF ligand superfamily member 11(TRANCE, 6.00±0.57 vs 5.44±0.62, p=0.006), C-X-C motif chemokine 9 (CXCL9, 5.20±0.97 vs 5.76±0.77, p=0.046), C-X-C motif chemokine 10 (CXCL10, 6.75±0.89 vs 7.62±0.99, p=0.007), cystatin-D (CST5, 7.74±0.60 vs 7.32±0.52, p=0.025) and C-C motif chemokine 19 (CCL19, 10.21±0.69 vs 10.74±0.47, p=0.006).

Figure 1 Comparative analysis of plasma proteins in HCA and control groups (A) Venn diagram of differential proteins. (B) PCA plot of plasma proteins in HCA-stage 1 group versus controls. (C) PCA plot of plasma proteins in HCA-stage 2 group versus controls. HCA, histological chorioamnitis; PCA, principal component analysis.

We identified five differentially expressed inflammation-related proteins between the HCA-2 group and the control group (figure 1B, online supplemental table S3). These proteins included IFN-gamma (7.45±1.37 vs 8.54±1.51, p=0.036), T-cell differentiation antigen CD6 (5.07±0.65 vs 4.52±0.45, p=0.010), CXCL10 (6.98±0.64 vs 7.62±0.99, p=0.034), CCL19 (10.30±0.47 vs 10.74±0.47, p=0.013) and T-cell surface glycoprotein CD5 (6.38±0.44 vs 6.03±0.36, p=0.019). CD6 and CD5 proteins were significantly upregulated, while three proteins (IFN-gamma, CXCL10 and CCL19) displayed downregulation (figure 2B).

Figure 2 Boxplots were made to present the differential inflammation-related proteins between (A) HCA-stage 1 group vs controls and (B) HCA-stage 2 group vs controls. HCA, histological chorioamnitis.

No significant differences in inflammatory proteins were observed between the HCA-1 and HCA-2 groups. The Venn diagram shows the overlap of differential proteins among the three groups (figure 3A). Principal component analysis results are depicted in figure 1B,C, showing the explained variances of PC1 and PC2.

Figure 3 Volcano plot of offspring differentially expressed proteins comparing HCA versus control offspring plasma samples. (A) HCA-stage 1 group versus controls. (B) HCA-stage 2 group versus controls. The abscissa is the difference of the mean NPX between the two groups and the ordinate represents −log10 (p value). The red dots indicate the upregulated proteins, the blue dots represent the downregulated proteins and the grey dots indicate the non-significant differentially expressed proteins. HCA, histological chorioamnitis; NPX, normalised protein expression.

Functional analysis of differential inflammation-related proteins

The GO enrichment analysis of the differentially expressed proteins revealed significant enrichment in several biological processes, including leucocyte chemotaxis, positive regulation of T-cell activation and cell adhesion, T-cell activation and regulation of cell adhesion (figure 4A,B). Molecular function analysis indicated that these proteins were involved in cytokine activity, signalling receptor activity, receptor ligand activity and protein kinase activity. Cellular component analysis showed that the differential proteins were mainly enriched in the extracellular space. KEGG pathway enrichment analysis unveiled the involvement of these differential proteins in several crucial pathways, including viral protein interaction with cytokine and cytokine receptor, IL-17 signalling pathway, NF-kappa B signalling pathway, toll-like receptor signalling pathway, chemokine signalling pathway and cytokines–cytokine receptor interactions (figure 4C,D).

Figure 4 Functional analysis of differential inflammation-related proteins. (A) Gene ontology (GO) enrichment analysis based on the differentially expressed proteins in HCA-stage 1 group versus controls. (B) GO enrichment analysis based on the differentially expressed proteins in HCA-stage 2 group versus controls. (C) Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis based on the differentially expressed proteins in HCA-stage 1 group versus controls. (D) KEGG enrichment analysis based on the differentially expressed proteins in HCA-stage 1 group versus controls. HCA, histological chorioamnitis.

To explore the interactions among these proteins, we constructed a protein–protein interaction network. CD6 and CXCL10 emerged as the proteins with the most significant interactions with other proteins in the network (figure 5).

Figure 5 Protein−protein interaction (PPI) network analysis of the differentially expressed proteins in (A) HCA-stage 1 group versus controls and (B) HCA-stage 2 group versus controls. HCA, histological chorioamnitis.

Correlation between clinical features and differential inflammation-related proteins

We further investigated the potential correlations between the clinical features of both mothers and neonates and the differential inflammation-related proteins identified in this study (figure 6). The results showed that TRANCE was positively correlated with neonatal leucocytes, and CST5 was negatively correlated with maternal leucocytes. CD6 and CD5 exhibited positive correlations not only with neonatal leucocytes but also with maternal leucocytes. CXCL9, CCL19 and CXCL10 were positively correlated with neonatal red blood cell counts. CXCL9, CXCL10 and IFN-gamma displayed negative correlations with neonatal platelet counts. Conversely, CD6 and TRANCE were positively correlated with neonatal platelet counts. TRANCE was also associated with neonatal α-L-fucosidase levels. And CD6 levels were positively correlated with neonatal birth weight.

Figure 6 Heatmap of Spearman correlations between differential inflammation-related proteins and neonatal or maternal characteristics.

Discussion

The exploration of placental pathology and its potential implications on neonatal outcomes has been a longstanding area of interest within the realm of perinatal medicine. Maternal inflammation, as seen in HCA, often results in fetal inflammation, characterised by elevated inflammatory markers and changes in immune cell profiles. Our study is the first to prospectively analyse a comprehensive panel of inflammation-related protein profiles in neonates presenting with HCA.

Our study involved a cohort of 57 participants stratified into three distinct groups (HCA-stage 1, HCA-stage 2 and controls) based on placental pathology results. Foremost, our analysis revealed no statistically significant variations in maternal age among the three groups, suggesting that maternal age may not be a contributing factor to the development of HCA in our study population. Significant changes were observed in the inflammatory cells of both mothers and offspring at HCA-stage 2, particularly in the white blood cell count. Although no statistically significant differences were noted in other haematological parameters, such as red blood cell indices, platelets and various metabolic and enzymatic markers, this suggests that the inflammatory cascade associated with HCA may specifically impact neonatal inflammatory cells. Higher levels of white blood cells and C reactive protein were also detected in very low birth weight premature infants with HCA.22 The broader implications for neonatal outcomes may include potential effects on growth, development and long-term health. For instance, elevated inflammatory markers are linked to adverse neurodevelopmental outcomes, such as cerebral palsy and cognitive impairment.23 Additionally, systemic inflammatory responses can influence multiple organ systems, potentially leading to complications like bronchopulmonary dysplasia and necrotising enterocolitis.24

We identified a total of eight differentially expressed proteins. Notably, we observed the upregulation of CD6 and CD5 proteins exclusively in the HCA-stage 2 group, while TRANCE and CST5 proteins were exclusively upregulated in the HCA-stage 1 group. Moreover, three downregulated proteins (IFN-gamma, CXCL10 and CCL19) were found to overlap between the two groups.

TRANCE, a member of the TNF family, and its two receptors, TRANCE-R and osteoprotegerin, constitute the TNF superfamily signalling pathway.25 Intriguingly, our GO pathway analysis substantiates the enrichment of the receptor ligand pathway. Further, we noted that TRANCE exhibited associations with neonatal leucocyte, lymphocyte and monocyte levels. TRANCE is expressed on activated T cells and possesses the capacity to activate mature dendritic cells.26 Studies have elucidated that plasma TRANCE/RANKL levels exhibit correlations with several distinct T-cell populations, encompassing CD8 + TEMRA and its CD28 RANKL subset.27 This intriguing connection raises the possibility that the immune response orchestrated by TRANCE in HCA offspring might undergo alterations.

CST5, a member of cystatin family II, partakes in degrading multiple targets, encompassing matrix components, adhesion proteins and other proteases.28 29 Our investigation revealed an intricate network of interactions, with CST5 upregulated in neonatal plasma, and a notable positive correlation with maternal leucocyte counts. CST5 has previously been identified as an early inflammatory marker in traumatic brain injury. However, this study is the first to report its elevation in newborns with HCA.30

Our study also unearthed downregulation of CXCL9 and CXCL10, both of which are Th1 chemokines closely associated with Th1-type responses and various diseases. Notably, these chemokines, along with CXCL11 and their coreceptor CXCR3, have a strong proinflammatory response, often induced by IFN-gamma, a crucial proinflammatory cytokine.3133 In our study, IFN-gamma displayed significant decreases in both the HCA-1 and HCA-2 groups. IFN-gamma, a soluble cytokine produced by various immune cells, holds a pivotal role in innate and adaptive immunity.34 35 The observed negative correlations between CXCL9, CXCL10, IFN-gamma and neonatal platelet counts suggest a downregulation of Th1-type immune responses. Interestingly, increases in CXCL9 and CXCL10 have been noted in children with multisystem severe syndrome,36 highlighting the diverse roles these chemokines play in immune regulation.

The significant downregulation of CCL19 in both the HCA-1 and HCA-2 groups sheds light on its potential role in the context of HCA. CCL19, a chemokine with abundant expression in the thymus and lymph nodes, forms a crucial component of the CCR7 chemokine axis, along with its ligand CCL21 and the CCR7 receptor. This axis plays a pivotal role in regulating various aspects of immune responses, including immune homeostasis, inflammation and immune tolerance.37 38 The downregulation of CCL19 within the HCA groups suggests potential alterations in immune regulation and immune cell trafficking. Our pathway analysis reinforces these findings, highlighting enrichment in pathways related to leucocyte chemotaxis, positive regulation of T-cell activation, receptor–ligand interactions and chemokine signalling pathways.

Our study revealed the significant upregulation of CD6 and CD5 in the HCA-2 group. CD5 and CD6, two closely related class I scavenger receptors, are primarily expressed on T cells and B1a cell subsets. These receptors are known to potentially provide similar or complementary signals in immune responses.39 40 Furthermore, our findings indicate positive correlations between CD6 and CD5 protein levels and white blood cell counts in both neonates and their mothers, underscoring their potential roles in immune responses. Pathway analysis supports the involvement of positive regulation of T-cell activation, further highlighting the immune implications of these upregulated proteins. Notably, CD6 also exhibited a positive correlation with birth weight, suggesting a potential link between CD6 expression and neonatal growth. However, the precise role of T-cell activation signalling pathways in the immunity of HCA offspring warrants further investigation.

This study holds significance in unravelling the plasma inflammatory protein profiles within offspring affected by HCA, shedding light on the potential associations between these differential proteins and various clinical parameters. However, we acknowledge certain limitations, such as a relatively small sample size and the potential confounding factors that may influence our study results. Therefore, confirming the expression levels of inflammatory proteins warrants the incorporation of data from larger sample sets in future endeavours.

Conclusions

In summary, our study delved into the impact of HCA on neonatal immune responses through an analysis of inflammation-related proteins. Notably, we identified significant alterations in key inflammatory proteins, including TRANCE, CST5, CXCL9, CXCL10, CCL19 and IFN-gamma. Additionally, our findings suggest that CD6 and CD5 proteins may play pivotal roles in the pathogenesis of neonatal diseases associated with HCA. Our results underscore the intricate nature of immune dysregulation in HCA offspring and emphasise the importance of examining broader inflammatory protein networks and pathways in future research. Further investigations, particularly larger-scale studies and mechanistic inquiries, are warranted to validate and expand on our discoveries.

supplementary material

10.1136/bmjpo-2024-002708 online supplemental file 1

Data availability statement

Data are available upon reasonable request.

Review Process File
04 09 2024

Funding: This work was funded by National High Level Hospital Clinical Research Funding (2022-NHLHCRF-LX-01-0301) and the Clinical research project of Beijing research ward construction (2022-YJXBF-04-01-03).

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient consent for publication: Consent obtained from parent(s)/guardian(s).

Ethics approval: This study was approved by the China–Japan Friendship Hospital ethics committee board (number: 2023-KY-057). All methods were carried out in accordance with relevant guidelines and regulations. Parental informed consent was obtained in writing from each participant.

Data availability free text: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Patient and public involvement: Patients and/or the public were not involved in the design, conduct, reporting or dissemination plans of this research.
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