Introduction
Asthma is one of the most prevalent chronic respiratory diseases during pregnancy, with an estimated prevalence ranging from 3.7% to 8.4%.1 Evidence indicates that asthma control deteriorates in up to 40% of pregnant women,2.A phenomenon potentially attributable to pregnancy-related Th2-skewed immune deviation, fluctuations in estrogen and progesterone levels, and suboptimal medication adherence.3 Poorly controlled asthma not only increases maternal risks, including preeclampsia, gestational diabetes mellitus, and cesarean section, but also contributes to adverse fetal outcomes such as intrauterine growth restriction, preterm birth, and low birth weight, while additionally predisposing offspring to an elevated risk of developing asthma later in life.4
The clinical management of asthma during pregnancy presents multifaceted challenges, with constrained diagnostic techniques, insufficient assessment modalities, and therapeutic concerns constituting three principal obstacles. Spirometry is a key objective tool for the diagnosis and assessment of asthma. Although some guidelines list advanced pregnancy as a relative contraindication because of the potential risk of inducing uterine contractions and increasing the risk of miscarriage and preterm birth,5 a recent systematic review found no evidence of adverse events associated with spirometry during pregnancy.
However, prospective safety data remain lacking, and evidence in special populations such as multiple pregnancy and recurrent miscarriage is limited.6 Fractional exhaled nitric oxide (FeNO) is an established non-invasive biomarker of type 2 airway inflammation, with evidence supporting its use in asthma diagnosis, treatment monitoring,7 and asthma management during pregnancy.8,9 However, FeNO is influenced by factors such as diet, smoking, and respiratory infections.10 A study in pregnant women with asthma found that even in those with well-controlled disease, the intra-individual coefficient of variation for serial measurements reached 32%–35%, and this variability may affect the interpretation of a single measurement.11 Blood EOS reflects the systemic eosinophilic inflammatory burden and is primarily associated with IL-5-driven pathways, whereas FeNO reflects airway-local type 2 inflammation and is mainly linked to IL-13 signaling. These two biomarkers are indicative of distinct components and compartments of type 2 inflammation, providing independent and complementary prognostic and predictive information, their combined assessment has been increasingly used for asthma phenotype identification and prediction of clinical outcomes. Nevertheless, in asthma during pregnancy, stable and reliable serum biomarkers that can simultaneously reflect both systemic and airway inflammation remain limited.
In addition, circulating inflammatory biomarkers during pregnancy may vary dynamically with gestational age. Therefore, gestational age must be fully considered when evaluating biomarkers in pregnancy.
Asthma is a chronic inflammatory airway disease orchestrated by a complex interplay of diverse inflammatory cells, including eosinophils, mast cells, T lymphocytes, and chemokine signaling networks. Chemokines constitute a family of small pro-inflammatory cytokines that direct the targeted migration of immune cells, with their receptors predominantly expressed on the surface of leukocytes.12 Among these, CCR1 recognizes multiple CC chemokine ligands, including CCL23, and plays a pivotal role in immune cell maturation and recruitment to sites of inflammation, emerging as a promising therapeutic target for allergic diseases such as asthma.13 CCL23 is most abundantly expressed in adult lung and liver tissues, and under physiological conditions, it binds to CCR1 with high affinity and specificity, orchestrating the recruitment of immune cells to inflammatory foci and thereby exerting immunomodulatory functions.14 It is also expressed at moderate levels in the placenta, suggesting that it may have sources other than airway inflammation during pregnancy.15
Previous investigations have elucidated the potential involvement of CCL23 in asthma across multiple levels of evidence. In murine models, eosinophils have been shown to promote hematopoietic stem cell mobilization and eosinophil lineage differentiation via the CCL6/CCR1 signaling axis, establishing a positive feedback loop that perpetuates airway inflammation. In humans, CCL15 and CCL23, the functional homologs of murine CCL6, are significantly upregulated in the peripheral blood of patients during acute asthma exacerbations and exhibit a positive correlation with peripheral blood eosinophil counts.16 Population-based transcriptomic analyses have further corroborated that CCL23 is highly expressed in asthmatic peripheral blood mononuclear cell (PBMC) clusters closely associated with Th2-type inflammatory signatures.
Among circulating eosinophils from patients with severe asthma, CCL23 has been identified as one of the key significantly upregulated genes, with its expression primarily driven by type 2 cytokines, including IL-5 and IL-4, as well as the bacterial component muramyl dipeptide.17 In two independent asthma cohorts, encompassing both children and adults with asthma, CCL23 has been identified alongside classical eosinophil markers such as IL5RA and CLC as an eosinophil-associated transcript significantly correlated with serum total IgE levels.18 Furthermore, CCL23 has been proposed as a potential biomarker for predicting clinical response to anti-IL-13 therapy.19 Collectively, these findings underscore the plausibility of CCL23 serving as a serological inflammatory biomarker in asthma.
However, the current evidence of linking CCL23 to asthma is predominantly derived from non-pregnant populations or limited to transcriptomic-level screening. The actual serum protein expression of CCL23 in pregnant women with asthma, its correlation with conventional Th2 cytokines (IL-4 and IL-5) and clinical type 2 inflammatory parameters (FeNO and peripheral blood eosinophils), as well as its potential utility as a clinical adjunctive identification tool in this specific population, remain largely unexplored. Therefore, in this study, IL-4 and IL-5 were also measured as reference markers for classical Th2 cytokines to evaluate whether CCL23 reflects the inflammatory status of asthma during pregnancy more sensitively than conventional Th2 cytokines.
Based on our preliminary transcriptomic sequencing finding that CCL23 was upregulated in the peripheral blood of pregnant women with asthma (Figure 1), and on the known biological role of CCL23/CCR1 signaling in eosinophilic inflammation, we hypothesized that serum CCL23 levels would be elevated in pregnant women with asthma and would be associated with the level of eosinophilic inflammation, and that combining CCL23 with EOS might improve the adjunctive identification performance for asthma in pregnancy. To this end, this study aimed to compare the expression profile of serum CCL23 between pregnant women with asthma and healthy pregnant women, to preliminarily evaluate the potential value of CCL23 as a clinical adjunctive identification indicator, and to provide a basis for subsequent larger-scale validation. Figure 1Preliminary transcriptomic sequencing and serum levels of CCL23 in gestational asthma.
(A) The heatmap displays the expression profiles of selected differentially expressed genes (log2FC > 2) identified from preliminary transcriptomic sequencing data in peripheral blood from pregnant women with gestational asthma (GA01–GA03) and healthy pregnant controls (HP01–HP03). Rows represent individual genes and columns represent individual samples. The color scale indicates Z-score-normalized expression levels, with red representing high expression and blue representing low expression.
Genes and samples were clustered using hierarchical clustering with Euclidean distance and complete linkage. CCL23 is highlighted by a red square. (B–D):Comparison of serum CCL23 (P = 0.07), IL-4 (P = 0.12), and IL-5 (P = 0.25) levels between pregnant women with asthma (n = 37) and healthy pregnant women (n = 36).
Data are presented as adjusted mean ± SEM, with comparisons performed using ANCOVA after adjusting for gestational age at blood sampling. All P-values are adjusted, P < 0.05 was considered statistically significant, ns, non-significant.A) Heatmap with a left column labeled P and a second column labeled logFC, followed by a matrix of gene expression values. A top annotation bar is labeled Group, with categories GA and HP.
The matrix columns are labeled GA01, GA02, GA03, HP01, HP02, HP03. The gene labels are C17orf99, CCDC144A, CCL23, CHST8, CYP26B1, ELF5, LOC112268260, OR2T11, SLC9A4, TBC1D3. A boxed highlight surrounds CCL23.
A vertical numeric scale at the right has tick labels negative 2, negative 1, 0, 1, 2. B) Bar chart with x axis categories HP and GA and y axis label CCL23 (pg/ml). Y axis range 0 to 1000 with ticks at 0, 200, 400, 600, 800, 1000.
Bars: HP approximately 520; GA approximately 760. Error bars extend to about 560 for HP and about 860 for GA. Bracket label ns.
C) Bar chart with x axis categories HP and GA and y axis label IL-4 (pg/ml). Y axis range 0 to 15 with ticks at 0, 5, 10, 15. Bars: HP approximately 8.5; GA approximately 12.
Error bars extend to about 9 for HP and about 13.5 for GA.A heatmap and three bar charts showing gene expression and serum marker levels for two groups.
Materials and Methods
Study Design and Ethical Approval
This was a single-center, prospective, case-control study. Pregnant women with asthma who attended the Department of Respiratory and Critical Care Medicine at Suzhou Municipal Hospital between October 2024 and June 2026 were enrolled as the asthma in pregnancy group, while healthy pregnant women from the Department of Obstetrics during the same period were recruited as the normal pregnancy control group. The study protocol was approved by the Ethics Committee of Suzhou Municipal Hospital (approval no.: K-2024-084-K02).
All participants provided written informed consent voluntarily after full understanding of the study. This study was conducted in accordance with the Declaration of Helsinki of the World Medical Association and the Chinese Thoracic Society’s Guidelines for the Prevention and Management of Bronchial Asthma (2024 Edition).20,21
Inclusion and Exclusion Criteria
Asthma in Pregnancy Group Inclusion criteria: Asthma diagnosis was based on the 2024 GINA criteria and previous clinical studies.20 (1) age between 18 and 45 years; (2) Confirmed as an intrauterine pregnancy by clinical and ultrasonographic examination; (3) Met the definition of “physician-diagnosed asthma”. For those with a pre-pregnancy diagnosis, the diagnosis was based on previous objective evidence of variable expiratory airflow limitation (eg, spirometry, bronchodilator reversibility testing, or peak expiratory flow variability); for those first diagnosed during pregnancy, spirometry was not performed in these patients, and the diagnosis was established by at least two respiratory specialists;22 (4) diagnosis was established following a comprehensive systematic evaluation by respiratory specialists prior to enrollment, which encompassed assessment of typical asthma symptoms (episodic wheezing, shortness of breath, chest tightness, and cough) and their patterns, variability, and triggers, age of onset, prior medication use and treatment response, as well as the severity and frequency of acute exacerbations; (5) voluntarily participated and provided written informed consent.
Exclusion criteria: (1) coexistence of other chronic airway diseases, including bronchiectasis or chronic obstructive pulmonary disease; (2) history of autoimmune diseases or malignancies; (3) receipt of systemic glucocorticoid therapy within 1 month prior to enrollment, or antibiotic use within 2 weeks.
Healthy Pregnancy Control Group Inclusion criteria: (1) age between 18 and 45 years; (2) Confirmed as an intrauterine pregnancy by clinical and ultrasonographic examination; (3) voluntarily participated and provided written informed consent.
Exclusion criteria: (1) prior or current diagnosis of asthma or asthma-like symptoms (episodic wheezing, chronic cough, etc), or any chronic respiratory disease; (2) history of allergic diseases, including allergic rhinitis or atopic dermatitis; (3) history of autoimmune diseases or malignancies; history of acute respiratory tract infection within 2 weeks prior to enrollment; (4) receipt of systemic glucocorticoid therapy within 1 month prior to enrollment, or antibiotic use within 2 weeks.
No participant had a documented history of a positive TB test or clinical/radiological evidence of active TB;Given that women in late pregnancy have more frequent antenatal visits and better adherence, recruitment was predominantly in late pregnancy.
Clinical Data Collection
On the day of enrollment, the following data were collected from all participants by trained researchers using structured questionnaires and the hospital’s electronic medical record system: Demographic characteristics, including age, height, pre-pregnancy weight, pre-pregnancy body mass index (BMI), smoking history, personal and family history of allergy, gravidity, parity, gestational age at blood sampling, and pregnancy-related comorbidities (preeclampsia, gestational hypertension, and gestational diabetes mellitus). The following assessments were performed by respiratory specialists: FeNO measurement, conducted in accordance with the standard procedures recommended by the American Thoracic Society/European Respiratory Society.23 Peripheral blood absolute eosinophil count (EOS), determined using an automated hematology analyzer; serum total IgE concentration; Asthma Control Questionnaire-5 (ACQ-5) score, assessing asthma control level during the 1 week prior to enrollment; and the number of asthma exacerbations during pregnancy, with an exacerbation defined as an asthma worsening event requiring emergency department visits, hospitalization, or a short course of oral glucocorticoid therapy. All enrolled pregnant women were followed up until delivery, and the following outcomes were recorded: gestational age at delivery, mode of delivery (vaginal delivery/cesarean section), preterm birth, miscarriage (pregnancy termination before 28 weeks of gestation), neonatal birth weight, admission to the neonatal intensive care unit (NICU), presence of neonatal diseases, and Apgar scores at 5 and 10 minutes.
Transcriptomic Sequencing
Prior to the establishment of the formal cohort, exploratory transcriptomic sequencing was performed on peripheral blood samples obtained from 3 pregnant women with asthma and 3 healthy pregnant controls. Total RNA was extracted from peripheral blood, and libraries were constructed following quality assessment, followed by paired-end sequencing on the Illumina NovaSeq 6000 platform. After quality control, alignment, and quantification of the raw data, differential expression analysis was performed.
Counts were normalized using the estimateSizeFactors function in the DESeq R package (2012), and the nbinomTest function was used to calculate P-values and fold changes. Differentially expressed genes were screened using a threshold of |log2FC| > 2 and nominal P < 0.05, and q values (Benjamini-Hochberg) were also calculated and reported for reference. The differentially expressed mRNAs were further subjected to Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses using the hypergeometric distribution test.
The sequencing and related analytical work were completed by Shanghai OE Biotech Co, Ltd.
Sample Size Calculation
Based on preliminary experimental results, serum CCL23 concentration was 549.21 ± 371.93 pg/mL in the asthma in pregnancy group and 175.17 ± 75.13 pg/mL in the healthy control group, with an effect size of Cohen’s d = 1.39. With α = 0.05 and power = 0.80, a two-independent-samples t-test (G*Power 3.1) was used to calculate that at least 10 participants per group were required. In addition, to analyze the correlation between CCL23 and EOS/FeNO, with an expected correlation coefficient of r = 0.4, α = 0.05, and power = 0.80, the required total sample size was calculated to be 46 participants (23 per group).
Considering an estimated 20% loss to follow-up, the final sample size was set at 30 participants per group, with a total of 60 participants.
Serum Sample Collection and ELISA
On the morning of the enrollment day, 5 mL of peripheral venous blood was collected from each participant under fasting conditions. The blood samples were allowed to clot at room temperature for 30 minutes and then centrifuged at 3000 r/min for 10 minutes. The separated serum was aliquoted and stored at −80°C in a freezer until assay, with repeated freeze-thaw cycles strictly avoided.
Serum concentrations of CCL23, IL-4, and IL-5 were measured using commercially available enzyme-linked immunosorbent assay (ELISA) kits (manufacturer: Neobioscience, Suzhou, China; assay type: double-antibody sandwich method; detection method: colorimetric method). The analytical performance for each analyte was as follows: for IL-4, the detection range was 1.56–100 pg/mL, the sensitivity was 0.78 pg/mL, and both intra- and inter-assay coefficients of variation were <10%;For IL-5, the detection range was 7.8–500 pg/mL, the sensitivity was 3.9 pg/mL, and both intra- and inter-assay coefficients of variation were <10%;For CCL23, the detection range was 15.63–1000 pg/mL, the sensitivity was 0.49 pg/mL, the intra-assay coefficient of variation was <8%, and the inter-assay coefficient of variation was <10%. All procedures were performed strictly according to the kit instructions.
Each sample was assayed in triplicate, and standard and quality control samples were used to establish standard curves. The laboratory personnel performing the assays were blinded to group assignment.
Statistical Analysis
Statistical analyses and graphical presentations were performed using SPSS version 26.0 (IBM Corp, Armonk, NY, USA) and GraphPad Prism version 11.0 (GraphPad Software, San Diego, CA, USA). The PROCESS v4.1 macro (Hayes, 2018) was employed for mediation effect analysis, and G*Power version 3.1 software was used for post hoc power analysis. All tests were two-sided, and a P-value < 0.05 was considered statistically significant.
Descriptive Statistics and Between-Group Comparisons
Continuous variables, which were predominantly non-normally distributed as assessed by the Shapiro–Wilk test, were presented as medians with interquartile ranges (IQR), and between-group comparisons were performed using the Mann–Whitney U-test. Categorical variables were expressed as counts (percentages) and compared using the χ2-test, with Fisher’s exact test applied when expected frequencies were less than 5.
Given the significant difference in gestational age at blood sampling between the two groups (P<0.01), an analysis of covariance (ANCOVA) was additionally performed to compare CCL23 levels between groups, with group assignment as the fixed factor and gestational age at blood sampling as the covariate, to calculate adjusted means and adjusted P-values, thereby controlling for the potential confounding effect of gestational age on serum CCL23 levels.
Within the asthma group, stratification analyses were conducted according to EOS levels, FeNO levels, ACQ-5 scores, and the presence or absence of pregnancy-related comorbidities, and between-subgroup differences in serum CCL23 levels were compared using the Mann–Whitney U-test.
Correlation Analyses
Spearman’s rank correlation coefficient was employed to evaluate the correlations between serum CCL23 and EOS, FeNO, IgE, ACQ-5 scores, exacerbation frequency, IL-4, IL-5, and pregnancy outcome indicators within the asthma group. Correlation coefficients with |ρ| ≥ 0.7 were considered strong, 0.4 ≤ |ρ| < 0.7 moderate, and |ρ| < 0.4 weak.
The asthma group was further stratified into two subgroups according to EOS levels (<0.1 ×109/L vs ≥0.1 ×109/L), and Spearman correlation analyses between CCL23 and each clinical parameter were performed separately within each subgroup to assess the stability of CCL23 association patterns across different EOS contexts.
Logistic Regression Analysis
To identify independent influencing factors for asthma in pregnancy, univariate logistic regression analyses were first performed with asthma group as the dependent variable and each independent variable entered individually. Variables with P < 0.10 in the univariate analyses, together with the two prespecified covariates (gestational age at blood sampling and maternal age), were entered simultaneously into the multivariable model using the Enter method (forced entry), and odds ratios (OR) with their 95% confidence intervals (CI) were calculated. Stepwise selection was not used to avoid data-driven overfitting.
Collinearity was assessed using the variance inflation factor (VIF). Model goodness-of-fit was evaluated using the Hosmer-Lemeshow test, and the Nagelkerke R2 was reported.
Evaluation of Adjunctive Identification Performance
A binary logistic regression model was constructed with asthma status as the dependent variable and CCL23 and EOS as independent variables to generate combined predictive probabilities. The performance of CCL23 alone, EOS alone, and the combined CCL23 + EOS model in discriminating asthma in pregnancy from healthy pregnancy was evaluated separately. Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) with its 95% confidence interval (CI) was calculated.
AUC comparisons were performed using the DeLong test, comparing the combined model with CCL23 alone and with EOS alone, respectively. Model optimism was estimated by bootstrap resampling (2,000 replicates), and the optimism-corrected AUC was calculated. Internal validation was performed using repeated 10-fold cross-validation (20 repeats), and leave-one-out cross-validation, in three models (CCL23 alone, EOS alone and CCL23 + EOS).
The optimal cut-off value was determined based on the maximization of the Youden index (Youden index = sensitivity + specificity − 1), and the corresponding sensitivity and specificity were calculated.
Gestational Age-Related Sensitivity Analysis (Exploratory)
Given that gestational age at sampling differed markedly between groups and influences circulating chemokine concentrations, CCL23 was further examined in exploratory sensitivity analyses. The primary model was an ANCOVA with group as a fixed factor and gestational age as a continuous covariate, estimated marginal means were computed at the pooled mean gestational age, and the adjusted difference is reported with its 95% CI, partial η2, and observed power. Homogeneity of regression slopes was tested with a group × gestational age product term.
Seven additional specifications were examined: non-linear adjustment (gestational age + gestational age2); restriction to the common-support region (≥19 weeks); exclusion of sampling before 12 weeks; restriction to 20–40 weeks; gestational age tertile as a categorical covariate; 1:1 matching on gestational age without replacement (2-week caliper; 1 and 3 weeks as sensitivity analyses); and overlap weighting on the propensity for group membership as a function of gestational age. A centered CCL23 × gestational age term was added to the logistic model, with conditional odds ratios evaluated from 16 to 38 weeks. All tests were two-sided (α = 0.05).
As the sample size was fixed at 73, these analyses are exploratory and characterize the precision of the between-group comparison rather than provide confirmatory evidence.
Mediation and Interaction Analyses (Exploratory)
To explore the potential biological relationship between CCL23 and EOS in asthma during pregnancy, a mediation model was constructed using Hayes’ PROCESS macro (Model 4), with CCL23 as the mediator, peripheral blood EOS as the independent variable and asthma status (0 = healthy control, 1 = asthma in pregnancy) as the dependent variable. The indirect effect was estimated with 5,000 bootstrap resamples and is reported on both the coefficient (log-odds) and odds-ratio scales with a percentile 95% confidence interval. The analysis is exploratory only and no significance-based mediation inference is drawn (Supplementary Table S1).
Post Hoc Sensitivity Analysis
In view of the interaction test results, a post hoc power analysis was performed using G*Power version 3.1 software, employing an F-test (linear multiple regression: R2 increase) with the sample size set at N = 73, α=0.05, and power (1−β)=0.80. With the model comprising three predictors (EOS, CCL23, and their interaction term), the minimum detectable effect size f2 that could be reliably detected under the current sample size was 0.1106, which is reported for reference only to assess the limitation of sample size in detecting small effects.
Results
Transcriptomic Analysis
Prior to the establishment of the formal cohort, transcriptomic sequencing was performed on peripheral blood samples obtained from pregnant women with asthma (GA, n = 3) and healthy pregnant controls (HP, n = 3). Given that only 3 participants were included per group, this phase was regarded as an exploratory pilot study intended solely for hypothesis generation. A total of 15,439 expressed genes were detected across all samples.
Using a threshold of |log2FC| > 2 and P < 0.05, 573 differentially expressed genes were identified, of which 249 were upregulated and 324 were downregulated, q values were also calculated and reported for reference. Among these, CCL23 was upregulated in the GA group compared with the HP group (log2FC = 5.71, P < 0.01, q = 0.07), with a fold change of 52.43, ranking second among upregulated genes and representing one of the most highly upregulated genes (Figure 1A shows only the top 10 upregulated genes). This result suggested that CCL23 may play a potential role in the pathophysiology of asthma during pregnancy and provided a rationale for the subsequent measurement of serum CCL23 protein levels by ELISA in an independent cohort in this study.
Baseline Characteristics
A total of 73 participants were enrolled in this study, comprising 37 cases in the asthma in pregnancy group (GA group) and 36 cases in the normal pregnancy control group (HP group). The recruitment process is shown in Figure 2. There were no statistically significant differences in baseline characteristics, including age, height, and pre-pregnancy body mass index (BMI), between the two groups (all P > 0.05).
However, a significant difference was observed in gestational age at blood sampling between the two groups (P < 0.01) (Table 1). Therefore, all subsequent between-group comparisons were adjusted for gestational age.Table 1Baseline Characteristics of Asthmatic and Healthy Pregnant WomenVariablesAsthma Group (n = 37)Control Group (n = 36)Test StatisticP-valueAge (years)32.00 (27.50,37.00)32.00 (30.00,33.80)Z = −0.300.76Gestational week at sampling (weeks)22.00 (13.50, 31.00)38.00 (30.00, 39.00)Z = −5.25< 0.01Height (cm)161.00 (158.00,168.50)160.50 (158.00,165.00)Z = −0.760.45Pre-pregnancy weight (kg)60.00 (53.50, 70.00)59.30 (53.30, 63.70)Z = −0.620.54Pre-pregnancy BMI (kg/m2)22.50 (20.40, 25.70)22.50 (20.70,24.10)Z = −0.200.84Primiparous, n (%)27 (73.00%)27 (75.00%)χ2 = 0.040.84Current/former smoker, n (%)1 (2.70%)0 (0.00%)—†1.00†History of allergy, n (%)7 (18.90%)4 (11.10%)χ2 = 0.870.35Notes: Continuous variables are presented as median (Q1, Q3) and were compared using the Mann–Whitney U-test, with the test statistic reported as Z value. Categorical variables are expressed as n (%) and were compared using the chi-square test or Fisher’s exact test (†); chi-square test results are reported as χ2 values, while Fisher’s exact test does not yield a test statistic.
P-values (p<0.05).† Fisher’s exact test.Abbreviations: Q1, first quartile; Q3, third quartile; BMI, body mass index; n, number of participants.Figure 2Study flow diagram: showing participant enrollment, group allocation, biological sample collection and testing, statistical analysis, and the actual number of participants included in each analysis. A total of 73 participants were enrolled, including 37 in the gestational asthma group (GA) and 36 in the healthy pregnancy control group (HP). Before enrollment, 3 pregnant women from each of the GA and HP groups were included in exploratory transcriptomic sequencing; all 73 participants completed serum CCL23, IL-4, and IL-5 measurements.A flowchart of recruitment, cohorts, blood collection, ELISA testing, deliveries and analysis.Abbreviations: GA, gestational asthma group; HP, healthy pregnancy control group; ELISA, enzyme-linked immunosorbent assay; CCL23, C-C motif chemokine ligand 23.
Among the 37 pregnant women with asthma, 31 (83.80%) had mild asthma, 6 (16.20%) had moderate asthma, and none had severe asthma. Regarding controller medication use within 3 months before enrollment, 8 participants (21.60%) had used controller medications: 7 used Symbicort (budesonide/formoterol), and 1 received nebulized therapy with budesonide suspension combined with formoterol fumarate inhalation solution and ipratropium bromide. The remaining 29 participants (78.40%) had not used controller medications within 3 months before enrollment.
Therefore, it is unlikely that inhaled medication use substantially affected CCL23 levels. Nevertheless, to further evaluate the potential influence of prior medication use, we compared serum CCL23 levels between pregnant women with asthma who had used controller medications before enrollment (n = 8) and those who had not (n = 29). No significant difference in CCL23 levels was observed between the two groups (P = 0.48).
However, given that the medication subgroup comprised only 8 patients, statistical power was limited; this analysis was exploratory, and a potential influence of prior medication use on CCL23 cannot be completely excluded (Table 2).Table 2Clinical Characteristics of the Gestational Asthma Group (n = 37)Clinical Characteristicsn (%)Asthma severityMild31 (83.80%)Moderate6 (16.20%)Severe0 (0.00%)Asthma medication useAny controller use8 (21.60%)Symbicort (budesonide/formoterol)7 (18.90%)Nebulize1 (2.70%)No controller use29 (78.40%)Notes: Asthma severity was classified according to GINA guidelines. Within 3 months before enrollment, 8 participants (21.60%) had used controller medications: 7 used Symbicort (budesonide/formoterol), and 1 received nebulized therapy with budesonide suspension combined with formoterol fumarate inhalation solution and ipratropium bromide. The remaining 29 participants (78.40%) had not used controller medications.
Levels of CCL23, IL-4, and IL-5 in Serum
Given the significant difference in gestational age at blood sampling between the two groups, all subsequent between-group comparisons were adjusted for gestational age, and further gestational age-related sensitivity analyses were performed (see Gestational Age-Related Sensitivity Analysis). Crude serum CCL23 levels were significantly higher in pregnant women with asthma than in healthy pregnant controls (877.08 ± 110.03 vs 408.01 ± 42.87 pg/mL; P < 0.01). However, after adjustment for gestational age using ANCOVA, the difference was attenuated and no longer statistically significant (adjusted means 775.0 ± 91.42 vs 512.92 ± 92.95 pg/mL; adjusted P = 0.07) (Figure 1B).
The classical type 2 inflammatory cytokines IL-4 (11.96 ± 1.53 pg/mL vs 8.03 ± 1.74 pg/mL, adjusted P = 0.12) (Figure 1C) and IL-5 (28.68 ± 1.99 pg/mL vs 24.89 ± 2.25 pg/mL, adjusted P = 0.25) (Figure 1D) exhibited an increasing trend in the GA group, neither reached statistical significance. These findings indicate that, after adjustment for gestational age, the crude between-group difference in CCL23 was attenuated to some extent, whereas the independent association between CCL23 and asthma in pregnancy remained stable across sensitivity analyses (see Gestational Age-Related Sensitivity Analysis).
Correlation of CCL23 with Type 2 Inflammation and Asthma Control Within the Asthma Group
We further performed correlation analyses between CCL23 and clinical parameters of asthma. The results demonstrated that CCL23 expression levels were strongly and positively correlated with peripheral blood eosinophil count (EOS) (ρ = 0.74, P < 0.01) (Figure 3A). Serum CCL23 levels differed significantly across EOS strata (Kruskal–Wallis H = 18.96, df = 2, P < 0.001) and were significantly higher in the high-EOS stratum (>0.3 ×109/L) than in the other two strata (both pairwise P < 0.01), whereas the two lower strata did not differ from each other (P = 0.87) (Figure 3B), suggesting that CCL23 expression is highly sensitive to circulating eosinophil abundance.
Given the close clinical covariance between CCL23 and EOS, to explore the potential biological relationship between CCL23 and EOS, we performed exploratory mediation and interaction analyses. An exploratory single-mediator model (EOS–CCL23–asthma in pregnancy) was specified a priori, with the direction based on CCL23 being an eosinophil-derived chemokine.15,16 The two markers were also strongly collinear (Pearson r = 0.87, n = 73). In the mediation model, the indirect effect of EOS through CCL23 was small and not statistically significant (ORNIE = 1.06, 95% CI 0.76–1.44), whereas the direct effect of EOS was essentially unchanged after adjustment for CCL23 (OR 2.48 → 2.39); CCL23 therefore did not appear to transmit the EOS–asthma association in this model.
The centred EOS × CCL23 interaction term was not significant (P = 0.49). This analysis is reported as exploratory only, and no mediation inference is drawn (see Supplementary Table S1). Figure 3Correlations of serum CCL23 with clinical parameters and subgroup analysis by eosinophil levels.
Spearman correlation analyses of serum CCL23 levels with clinical indicators in the asthma group (n = 37). Serum CCL23 showed a strong positive correlation with peripheral blood eosinophil counts (EOS) (ρ = 0.74, P < 0.01) (A); Serum CCL23 levels in the asthma group stratified by EOS category (<0.1, 0.1–0.3, and >0.3 ×109/L, n = 5, 16, and 16, respectively); CCL23 concentrations were significantly higher in the >0.3 ×109/L stratum than in the two lower strata, which did not differ from each other (B); A weak positive correlation with fractional exhaled nitric oxide (FeNO) (ρ = 0.35, P = 0.03) (C); and serum total IgE (ρ = 0.20, P = 0.36, n = 24) (D), and weak, non-significant correlations with ACQ-5 scores (ρ = 0.23, P = 0.18) (E), number of asthma exacerbations during pregnancy (ρ = 0.15, P = 0.36) (F); Pairwise comparisons: *P < 0.05, **P < 0.01; ns, not significant. Data are presented as scatter plots with Spearman correlation coefficients (ρ) and P-values, or as box plots with medians and interquartile ranges (B).A) Scatter plot of eosinophils versus CCL23 with a fitted line and shaded band.
Horizontal axis label, CCL23, picogram per milliliter, range 0 to 3000. Vertical axis label, eosinophils, times 10 to the power of 9 per liter, range 0 to 2.0. Text, rho equals 0.74, P less than 0.01.
Points span about 0 to 2800 on CCL23 and 0 to 1.6 on eosinophils. B) Box plot of CCL23 by eosinophils strata with significance brackets. Horizontal axis label, eosinophils, times 10 to the power of 9 per liter, categories eosinophils greater than 0.3, 0.1 less than or equal to eosinophils less than or equal to 0.3, eosinophils less than 0.1.
Vertical axis label, CCL23, picogram per milliliter, range 0 to 2000. Medians are approximately 1400, 550, 450.A composite of five scatter plots and one box plot relating CCL23 to asthma indicators.
CCL23 demonstrated a weak positive correlation with fractional exhaled nitric oxide (FeNO) (ρ = 0.35, P = 0.03) (Figure 3C). In a subset of 24 pregnant women with asthma for whom IgE results were available, CCL23 showed a weak positive correlation with serum total IgE that did not reach statistical significance (ρ = 0.20, P = 0.36) (Figure 3D). Collectively, these findings indicate that CCL23 is positively correlated, to varying degrees, with currently used clinical type 2 inflammatory biomarkers (EOS and FeNO), with the strongest association observed with EOS, while the correlation with IgE was relatively weak.
Of note, this strong EOS-CCL23 association was not significant in the healthy control group, suggesting that it may be a specific manifestation under the pathological state of asthma.
With respect to clinical symptoms and disease control, CCL23 levels exhibited only weak, non-significant correlations with ACQ-5 scores (ρ = 0.23, P = 0.18) (Figure 3E) and the number of asthma exacerbations during the index pregnancy (ρ = 0.15, P = 0.36) (Figure 3F). This suggests that, within the current sample size, no direct significant association was observed between CCL23 and recent clinical asthma control status.
Correlation of CCL23 with Pregnancy Outcomes
As of June 28, 2026, delivery data were available for 33 of 36 women in the control group and 27 of 37 women in the asthma group. At the level of maternal complications and overall pregnancy outcomes, CCL23 levels exhibited a positive correlation trend with the presence of pregnancy-related comorbidities (gestational hypertension, preeclampsia, and gestational diabetes mellitus) (ρ = 0.34, P = 0.07), though this did not reach statistical significance. No significant correlations were observed between CCL23 and preterm birth (n = 5, ρ = −0.05, P = 0.83), mode of delivery (cesarean section, n = 11 vs vaginal delivery, n = 12, ρ = −0.18, P = 0.40), or miscarriage (n = 4, ρ = −0.15, P = 0.46).
Given the extremely small sample sizes within these pregnancy outcome subgroups, these negative findings should be interpreted with caution and considered as exploratory references only.
Neonatal outcomes were followed up in 60 delivered women (27 in the asthma group and 33 in the healthy control group). No statistically significant difference was observed in neonatal birth weight between the two groups (P = 0.96). Within the asthma group, Spearman correlation analysis revealed no significant correlation between CCL23 and birth weight (ρ = 0.09, P = 0.64).
All neonates had 5-minute and 10-minute Apgar scores ≥ 8, and none required admission to the neonatal intensive care unit (NICU). A total of 4 perinatal neonatal complications were documented, including 3 in the asthma group (1 case of neonatal jaundice and 2 cases of neonatal conjunctivitis) and 1 in the healthy control group (neonatal hyperbilirubinemia with conjunctivitis). All were mild complications that resolved following symptomatic treatment.
One additional neonate in the asthma group was diagnosed with congenital anal atresia, which was considered an independent congenital structural anomaly and was not counted among perinatal complications. Given the absence of within-group variability in Apgar scores and NICU admission, as well as the extremely low number of perinatal complications (n = 4), further correlation analyses between CCL23 and these indicators were not performed. In summary, no linear association between serum CCL23 levels and birth weight was observed in this study.
It should be noted that, constrained by the sample size and the low frequency of clinical endpoint events, the power of this study to analyze the correlation between CCL23 and neonatal short-term outcomes is limited, and the robustness of these conclusions warrants further validation in large-scale prospective cohort studies.
Independent Association of CCL23 with Asthma in Pregnancy
To investigate whether elevated CCL23 levels are independently associated with an increased risk of asthma in pregnancy, univariate analysis was first performed. Gestational age at blood sampling differed significantly between the two groups (P < 0.01), whereas maternal age (P = 0.76), height (P = 0.45), pre-pregnancy weight (P = 0.54), pre-pregnancy BMI (P = 0.84), allergy history (P = 0.35) and primiparity (P = 0.84) did not differ significantly. CCL23 and the two prespecified covariates, gestational age at blood sampling and maternal age, were therefore entered simultaneously using the Enter method (Table 3).
After adjustment for both, serum CCL23 remained independently associated with asthma in pregnancy (OR = 1.002 per pg/mL, 95% CI 1.000–1.004, P = 0.04), whereas maternal age was not (OR = 0.96 per year, 95% CI 0.85–1.08, P = 0.49). Inclusion of maternal age did not materially change the CCL23 estimate. Model fit was good (Hosmer-Lemeshow χ2 = 9.72, df = 8, P = 0.29), with Nagelkerke R2 = 0.53.Table 3Multivariable Logistic Regression Analysis of Factors Associated with Gestational AsthmaVariableBSEWald χ2P-valueOR (95% CI)Gestational age at blood sampling (per 1-week increase)−0.160.0413.30<0.010.85 (0.78–0.93)CCL23 (per 1 pg/mL increase)0.0020.0014.220.041.002 (1.000–1.004)Maternal age (per 1-year increase)−0.040.060.480.490.96 (0.85–1.08)Constant5.182.633.880.05178.03Notes: The dependent variable was gestational asthma (1 = asthma, 0 = healthy).
CCL23, gestational age at blood sampling and maternal age were entered into the model using the Enter method (forced entry). Nagelkerke R2 = 0.53.Abbreviations: OR, odds ratio; CI, confidence interval; SE, standard error.
To further evaluate the dose-response relationship between CCL23 levels and the risk of asthma in pregnancy, serum CCL23 concentrations from all participants were stratified by quartiles (Q1–Q4), and a multivariable logistic regression model was constructed with Q1 (lowest group) as the reference, adjusting for gestational age and age (Table 4). All included variables had VIF values ranging from 1.02 to 1.29, all <5, indicating no significant multicollinearity. We found that CCL23 quartile groups as a whole were significantly associated with asthma in pregnancy (overall P<0.01), Using Q1 as the reference, the Q4 group (OR = 23.76, 95% CI 2.38–237.80, P<0.01) and the Q2 group (OR = 12.62, 95% CI 1.85–85.95, P = 0.01) had significantly increased risk of asthma, whereas the difference between the Q3 group and the Q1 group was not statistically significant (OR = 2.29, 95% CI 0.33–15.81, P = 0.40).
This association showed a non-monotonic trend, which may reflect a non-linear or saturation effect, and may also be related to the small sample size and wide confidence intervals within each quartile group. Collectively, these results indicate that, after excluding confounding by age and gestational age, elevated serum CCL23 levels were significantly associated with an increased risk of asthma in pregnancy. However, further validation in larger samples is still needed.Table 4Multivariable Logistic Regression Analysis of Serum CCL23 Levels and the Risk of Gestational AsthmaCCL23 QuartileCut-off (pg/mL)BSEWald χ2P-valueOR (95% CI)Q1 (lowest)≤257.39Reference———1.000Q2 (low-medium)257.39–506.172.540.986.710.0112.62 (1.85–85.95)Q3 (medium-high)506.17–792.620.830.990.710.402.29 (0.33–15.81)Q4 (highest)>792.623.171.187.27<0.0123.76 (2.38–237.80)Notes: The model was adjusted for gestational age at blood sampling and maternal age.
The overall P-value for the four CCL23 subgroups was 0.008. Q1–Q4 were determined based on the quartiles of serum CCL23 levels in the entire study population (N = 73). Q1 (the lowest level group) was set as the reference category.
B, regression coefficient; SE, standard error; Wald χ2, Wald chi-square statistic; OR, odds ratio; 95% CI, 95% confidence interval. P < 0.05 was considered statistically significant.
Adjunctive Identification Performance and Internal Validation of CCL23 (Exploratory)
After evaluating the association between CCL23 and peripheral inflammation, we assessed its potential adjunctive identification value (Table 5). ROC analysis showed an AUC of 0.74 (95% CI 0.63–0.86) for CCL23 alone (Figure 4A) and 0.87 (95% CI 0.79–0.95) for the CCL23 + EOS model (Figure 4B), the improvement over CCL23 alone was statistically significant (DeLong P = 0.01). EOS alone, however, showed a similar AUC (0.88, 95% CI 0.80–0.95) (Figure 4C), and the difference between the combined model and EOS alone was not statistically significant (DeLong P = 0.13), the incremental discriminatory value of CCL23 beyond EOS was therefore not demonstrated in this cohort.
Using the Youden index, the optimal cut-off in this exploratory analysis was 263.18 pg/mL for CCL23 alone (sensitivity 91.90%, specificity 50.00%) and a predicted probability of 0.29 for the combined model (sensitivity 94.60%, specificity 66.70%). Internal validation was performed for all three models. Optimism was estimated by bootstrap resampling (2,000 replicates; Efron-Tibshirani), and discrimination was additionally assessed by repeated 10-fold cross-validation (20 repeats) and leave-one-out cross-validation.
The apparent AUCs were 0.74 for CCL23 alone, 0.88 for EOS alone, and 0.87 for the CCL23 + EOS model; the optimism-corrected AUCs were 0.74, 0.88, and 0.86 (optimism −0.001 to 0.01), and the cross-validated AUCs were 0.71, 0.85, and 0.83 for 10-fold cross-validation and 0.71, 0.85, and 0.84 for leave-one-out cross-validation. These findings suggest that none of the models was materially overfitted despite the small sample size. On both metrics, the combined model performed no better than EOS alone: the increment in AUC attributable to adding CCL23 to EOS was −0.008 (95% CI −0.018 to +0.002; DeLong P = 0.13), indicating that an increment above approximately 0.002 is unlikely.
Internal validation cannot, however, substitute for external validation, and the case–control design precludes estimation of PPV and NPV.Table 5Receiver Operating Characteristic (ROC) Analysis of Serum CCL23, EOS, and Their Combination for the Identification of Gestational Asthma (n = 73)ModelAUC (95% CI)Cut-offYouden indexSensitivity (%)Specificity (%)Optimism-corrected AUC10-fold CV AUCCCL23 alone0.74 (0.63–0.86)263.18 pg/mL0.4291.9050.000.740.71EOS alone0.88 (0.80–0.95)————0.880.85CCL23 + EOS0.87 (0.79–0.95)0.29 (predicted probability)0.6194.6066.700.860.83Notes: AUCs are presented with 95% CIs. Cut-off values were determined by the Youden index, and the Youden index, sensitivity, and specificity were calculated at the corresponding optimal cut-off. For the CCL23 + EOS model, the cut-off is expressed as the predicted probability derived from logistic regression.
Optimism-corrected AUC was estimated by bootstrap resampling to correct for overfitting, and 10-fold CV AUC represents the mean AUC from 10-fold cross-validation. Cut-off, Youden index, sensitivity, and specificity were not calculated for EOS alone (“—”). Because this study used a case-control design, the prevalence was artificially set.
PPV and NPV are dependent on the true population prevalence and therefore cannot be directly estimated; thus, they were not reported.Abbreviations: AUC, area under the receiver operating characteristic curve; CI, confidence interval; CV, cross-validation; EOS, blood eosinophil count; CCL23, C-C motif chemokine ligand 23.Figure 4ROC curves of CCL23 alone, EOS alone, and the combined CCL23 + EOS model for distinguishing asthma in pregnancy. (A) ROC curves for CCL23 alone (AUC 0.74, 95% CI 0.63–0.86); (B) ROC curve for the logistic regression-derived prediction probability model combining CCL23 and EOS (AUC 0.87, 95% CI 0.79–0.95); (C)EOS alone (AUC 0.88, 95% CI 0.80–0.95). The combined model was significantly superior to CCL23 alone (DeLong test, P = 0.01) but not significantly superior to EOS alone (DeLong test, P = 0.13).
For CCL23 alone, the optimal cut-off value in this study was 263.18 pg/mL (sensitivity 91.90%, specificity 50.00%); for the combined model, the optimal predicted probability cut-off was 0.29 (sensitivity 94.60%, specificity 66.70%). The diagonal line represents the reference line (AUC = 0.50, no discrimination).A) Receiver operating characteristic curve plot. Horizontal axis label, 1 minus Specificity, unit not shown, range 0.0 to 1.0.
Vertical axis label, Sensitivity, unit not shown, range 0.0 to 1.0. Text, CCL23 AUC equals 0.74. Diagonal reference line from (0.0, 0.0) to (1.0, 1.0).
Curve is step-like; vertices not legible as exact coordinates. B) Same axes and ranges as A). Text, CCL23 plus EOS AUC equals 0.87.
Step-like curve rises earlier and reaches near 1.0 Sensitivity by about 0.7 on 1 minus Specificity. C) Horizontal axis label, 1 minus Specificity, unit not shown, range 0.0 to 1.0. Vertical axis label, 1 minus Sensitivity, unit not shown, range 0.0 to 1.0.
Text, EOS AUC equals 0.88. Step-like curve rises earlier and reaches near 1.0 on 1 minus Sensitivity by about 0.8 on 1 minus Specificity. Diagonal reference line from (0.0, 0.0) to (1.0, 1.0).A multi-line graph showing three receiver operating characteristic curves for CCL23, CCL23 plus EOS and EOS.
Gestational Age-Related Sensitivity Analysis
To further test the robustness of the primary findings, we conducted exploratory sensitivity analyses. Gestational age at sampling was higher in controls than in the asthma group (median 38.0 vs 22.0 weeks, P < 0.01) and was strongly correlated with group (r = −0.60, 35.5% of variance shared). The crude difference in CCL23 was 469.10 pg/mL (P < 0.01).
After linear ANCOVA adjustment for gestational age, it was attenuated to 262.10 pg/mL (adjusted means 775.0 ± 91.42 vs 512.92 ± 92.95 pg/mL) and was not statistically significant (F(1,70) = 3.32, P = 0.07; 95% CI −24.60 to 548.80 pg/mL), but the analysis was underpowered (observed power = 0.44) and the confidence interval did not exclude a clinically relevant difference. Gestational age was itself an independent predictor of CCL23 (B = −17.0 pg/mL per week, P = 0.02).
Across the seven remaining prespecified specifications, the adjusted difference ranged from 254.80 to 391.30 pg/mL (P = 0.01–0.09; Supplementary Table S2), including non-linear adjustment (gestational age + gestational age2: +303.60 pg/mL, P = 0.04, with the quadratic term itself non-significant, P = 0.12), restriction to the common-support region, gestational-age matching, tertile stratification, exclusion of participants sampled before 12 weeks (P = 0.07, ie, unchanged), and overlap weighting. Homogeneity of regression slopes was satisfied (P = 0.54), and the CCL23 × gestational age interaction was not significant (P = 0.39). In contrast, the association between CCL23 and asthma status was stable across all specifications (OR 1.002 per pg/mL, 95% CI 1.000–1.004; P = 0.03–0.06).
The between-group difference in CCL23 is therefore imprecisely estimated rather than absent, and residual confounding by gestational age cannot be completely excluded.
Discussion
The findings of this study are directionally consistent with our group’s previous transcriptomic sequencing results: the CCL23 gene was upregulated in the peripheral blood of pregnant women with asthma, and this study further validated the elevation of its serum protein level in an independent cohort. The effect directions of the two methods were fully consistent, providing preliminary support for the potential role of CCL23 in asthma during pregnancy. Nevertheless, as both the previous transcriptomic analysis and the present study had small sample sizes and were exploratory, this consistency still requires further validation in larger samples.
In this study, we systematically evaluated the serum expression profile of CCL23 and its potential clinical adjunctive identification value in pregnant women with asthma, and further incorporated exploratory mediation and interaction analyses to preliminarily explore the potential biological relationship between CCL23 and peripheral blood eosinophil count (EOS).
The key findings are as follows: serum CCL23 levels were elevated in patients with asthma in pregnancy compared to healthy pregnant controls; Elevated CCL23 levels were independently associated with an increased risk of asthma in pregnancy (overall P<0.01). The Q4 group (OR = 23.76, 95% CI 2.38–237.80, P<0.01) and the Q2 group (OR = 12.62, 95% CI 1.85–85.95, P = 0.01) had significantly increased risk, whereas the Q3 group did not reach statistical significance, showing a non-monotonic trend; CCL23 demonstrated significant positive correlations with EOS (ρ=0.74, P<0.01) and FeNO (ρ=0.35, P = 0.03), but no significant associations were observed with ACQ-5 scores, exacerbation frequency, or pregnancy outcomes; The CCL23 + EOS model showed better discrimination than CCL23 alone (AUC 0.87 vs 0.74), but not than EOS alone (AUC 0.88). Internal validation yielded an optimism-corrected AUC of 0.86 and a 10-fold CV AUC of 0.83 for the combined model, but external validation is still lacking, and the performance may be overestimated.
It must be emphasized that the clinical role of this model is currently limited to a potential adjunctive tool for identification and risk stratification in prenatal outpatient settings. It is intended to provide an exploratory supplement to address the gap created by the limited feasibility of lung function assessment during pregnancy, rather than as a substitute for diagnostic evaluation. These findings are exploratory and require external validation in multicenter, large-scale prospective studies.
This study found that CCL23 was strongly positively correlated with peripheral blood EOS (ρ=0.74), whereas it showed only a weak positive correlation with FeNO (ρ=0.35). This difference may reflect the activation of distinct compartments and pathways of type 2 inflammation: blood EOS primarily reflects the IL-5-driven eosinophilic inflammatory burden in the systemic circulation, whereas FeNO mainly reflects airway-local IL-13/IL-4-driven type 2 inflammatory activity.24. Therefore, CCL23 may be more closely associated with systemic eosinophilic inflammatory pathways while also having some relationship with airway-local inflammation.
However, this inference is based solely on cross-sectional association analysis and cannot determine its cellular origin or causal relationship. The “bomb (blood EOS) meets magnet (FeNO)” framework proposed by Couillard et al provides a conceptual basis for understanding the complementary relationship between these biomarkers: FeNO represents the airway-local chemotactic “pull” (magnet), whereas blood EOS represents the systemic effector cell pool (bomb). These two biomarkers correspond to different compartments and provide independent and complementary prognostic and predictive information, and their combined assessment has been used for asthma phenotyping and clinical outcome prediction.
Recently, Pianigiani et al also found in a real-world cohort that dual elevation of baseline FeNO and blood EOS was significantly associated with 12-month clinical remission in patients with severe eosinophilic asthma (multivariable OR = 12.67, P<0.01), whereas elevation of either marker alone was not significantly associated with remission, suggesting that combined assessment may identify a patient subgroup with more pronounced T2-driven features. However, the classification performance of that study was only moderate (sensitivity 73.33%, specificity 62.45%), and the authors therefore regarded it as an exploratory stratification tool rather than a definitive predictive indicator.25 In our present study, the strong association between CCL23 and EOS suggests that incorporating CCL23 into the biomarker framework composed of FeNO and EOS may help provide a more comprehensive assessment of type 2 inflammatory status in asthma during pregnancy. However, pregnancy-specific immune deviation and gestational age-related changes may reshape the relationships among these biomarkers, and the cross-sectional design of this study cannot establish causality.
On this basis, the above interpretation represents only an exploration at the level of biological plausibility, and the exact role of CCL23 in the inflammatory network of asthma during pregnancy still requires further validation in larger prospective cohorts and mechanistic studies.
In the present study, neither IL-4 nor IL-5 showed significant differences between the two groups. Although this negative finding appears to contradict the Th2-driven inflammatory model of asthma, it may have important pathophysiological implication. IL-4 and IL-5 primarily exert their effects within the airway mucosal microenvironment,26 and the elevated estrogen and progesterone levels during pregnancy are known to influence the expression and clearance kinetics of Th2 cytokines.27 Studies suggest that estrogen, via estrogen receptor α (ER-α) signaling, can enhance the production of alarmins such as IL-33 and TSLP, while also promoting the expression of type 2 cytokines including IL-4, IL-5, and IL-13.
Progesterone has similarly been shown to facilitate Th2 cell production of IL-4 and IL-5.28–30 In fact, in women with asthma, pregnancy-induced immunological changes are dysregulated, manifesting as an elevated Th17/Treg ratio, a Th1-to-Th2 immune shift, and increased pro-inflammatory cytokine production.31 This pregnancy-driven Th2 deviation, when superimposed upon the pre-existing Th2 inflammation inherent to asthma, may cause serum IL-4 and IL-5 levels to dual regulation by both “ asthma status” and “ pregnancy status”, thereby compromising their stability and reliability as asthma-specific biomarkers. This may represent one of the key reasons for the absence of significant differences in serum IL-4 and IL-5 between the asthma and healthy control groups in our study. Nevertheless, it should be noted that the primary purpose of measuring IL-4 and IL-5 in this study was not to validate their biomarker value in asthma during pregnancy, but rather to serve as “ reference indicators.” CCL23, a key chemokine within the inflammatory network, has been implicated in asthma and type 2 (T2) inflammation by multiple lines of evidence, however, whether it acts as a central driver has not been established.
Previous studies have demonstrated that the markedly elevated CCL23 in adult patients with asthma originates primarily from eosinophils (EOS), and its expression level not only correlates positively with peripheral blood absolute EOS counts but also serves as a core node in the transcriptomic networks of severe asthma and T2-high asthma.16,17 At the mechanistic level, CCL23 may bind to and activate CCR1 receptors on hematopoietic stem cells and inflammatory cells, thereby not only directly mediating airway inflammation but also potentially promoting EOS differentiation and maturation in a targeted manner; the newly generated eosinophils in turn secrete additional CCL23, establishing a continuously amplifying feedforward inflammatory loop in asthma pathophysiology.32,33 Notably, CCL15 and CCL23 have been identified as endogenous agonists of CCR1 that are elevated in patients with asthma, and the CCR1 antagonist BX471 has been shown to significantly reduce eosinophil differentiation and airway inflammation.16 The pregnancy-specific maternal Th2 immune deviation, when superimposed upon the pre-existing T2 inflammatory background of asthma, may further reshape or even amplify chemokine-related inflammatory signals. Of particular interest, CCL23 is also expressed at moderate levels in the placenta,15 suggesting that its sources in asthma during pregnancy may be more complex, potentially involving not only airway eosinophils but also placental tissue. Yet this study measured only serum CCL23 and did not directly verify its tissue origin.
The statistical results of the present study are highly consistent with the findings of the above studies: serum CCL23 levels were significantly higher in pregnant women with asthma than in healthy pregnant controls and were strongly positively correlated with peripheral blood EOS counts (ρ=0.74, P<0.01). But this result only suggests a statistical association between CCL23 and eosinophil-related inflammation, it cannot infer causality, nor can it prove that CCL23 is a driver of asthma in pregnancy. Whether this association is generalizable across pregnancy states still requires further validation in larger samples and mechanistic studies.Although CCL23 and peripheral blood EOS were statistically highly associated, the two could not be separated statistically in our exploratory mediation model.
The model was specified a priori in the direction EOS-CCL23-asthma, because CCL23 is an eosinophil-derived chemokine. The two markers were also strongly collinear (Pearson r = 0.87, n = 73). In this model, the indirect effect of EOS through CCL23 was close to the null (ORNIE = 1.06, 95% CI 0.76–1.44), and adjustment for CCL23 barely changed the EOS–asthma association (OR 2.48 → 2.39); conversely, the association between CCL23 and asthma was no longer evident after adjustment for EOS (OR 1.04, 95% CI 0.82–1.33).
We therefore do not interpret the strong CCL23–EOS correlation as evidence of a causal pathway, and the present data cannot distinguish whether the two act in sequence, in parallel, or jointly (Supplementary Table S1). We therefore do not interpret the strong CCL23-EOS correlation as evidence of a causal pathway, and the present data cannot distinguish whether the two act in sequence, in parallel, or jointly. It should be noted that, given the observational case-control design and limited sample size of this study, this analysis should be regarded as exploratory.
This negative finding cannot prove that the two act through independent or parallel biological pathways, nor can it exclude the possibility of weak mediation or synergistic effects. A more reasonable explanation is that, at the current sample size (N = 73), the model has limited power to detect weak effects (post hoc power analysis showed a minimum detectable effect size of f2=0.11). The exact biological relationship between the two, whether causal progression, parallel independence, or mutual synergy, still needs to be further elucidated in larger prospective cohort and mechanistic studies.
In the special context of pregnancy, the abnormal elevation of CCL23 may not be simply a downstream event driven by EOS, the two may jointly reflect the systemic T2 inflammatory burden in patients with asthma during pregnancy, but this inference still requires verification.Notably, the association between CCL23 quartile groups and asthma risk in pregnancy showed a non-monotonic trend, with significantly increased risk in the Q2 and Q4 groups, whereas the Q3 group did not reach statistical significance. It may reflect multiple factors: a potential non-linear relationship or saturation effect between CCL23 and asthma risk, such that beyond a certain level, the pro-inflammatory effect of CCL23 may plateau or no longer increase linearly due to negative feedback regulation; and the small sample size within each quartile group (approximately 18 participants per group), leading to unstable OR estimates and wide confidence intervals, which may have diluted the effect in the Q3 group and rendered it non-significant. Thus, the quartile-based findings should be interpreted with caution, and the precise dose-response relationship requires further exploration using non-linear models such as restricted cubic splines in larger samples.ROC curve analysis in this study demonstrated that CCL23 alone yielded an AUC of 0.74, which improved to 0.87 when combined with EOS, with the DeLong test confirming a statistically significant improvement (DeLong P = 0.01).
However, EOS alone achieved a similar AUC (0.88), and the combined model did not significantly outperform EOS alone (DeLong P = 0.13). From a preliminary clinical perspective, when CCL23 was used alone at a cut-off value of 263.18 pg/mL, the sensitivity was 91.90% but the specificity was only 50.0%, indicating a low missed-diagnosis rate but a high misclassification rate, with a substantial number of healthy pregnant women falsely identified as positive. When EOS was added to the model, the specificity increased to 66.70% while maintaining a high sensitivity of 94.60%, corresponding to a reduction in the false positive rate from 50% to 33.30%.
That said, EOS alone already showed comparable discrimination, the incremental benefit of adding CCL23 to EOS was not demonstrated. A lower false positive rate may be relevant in prenatal outpatient settings by reducing unnecessary referrals to respiratory specialists, thereby conserving healthcare resources and alleviating anxiety for pregnant women. Even so, this potential advantage should be interpreted cautiously given the lack of incremental value over EOS alone.
Both CCL23 (measured by ELISA) and EOS (measured by routine complete blood count) can be obtained from the same tube of peripheral blood, without the need for additional pulmonary function testing or FeNO measurement, making the approach operationally simple and cost-effective. For primary care facilities without access to spirometry equipment, or for pregnant women in the second or third trimester who are unable to perform forced expiratory maneuvers, serum-based markers such as EOS, either alone or in combination with CCL23, may offer an objective and quantifiable preliminary assessment tool. Those who test positive could then be referred to higher-level hospitals for confirmatory diagnosis via pulmonary function testing, potentially forming a tiered pathway of serological preliminary identification followed by pulmonary function confirmation.
Nevertheless, it must be emphasized that the above clinical positioning is currently preliminary and exploratory, and before this model can be applied clinically, it requires external validation in larger, multicenter, independent pregnancy cohorts. This study positions these markers as potential “adjunctive identification tools” rather than “diagnostic replacements”. Yet their clinical value still needs to be confirmed in future studies.
In our study, no significant correlations were observed between CCL23 and ACQ-5 scores (P = 0.18) or exacerbation frequency (P = 0.36). This negative result may be attributable to the fact that the pregnant women with asthma enrolled in this study were generally in a stable or mildly controlled state (31 with mild asthma, 6 with moderate asthma, and none with severe asthma), with limited overall symptom variability and a low frequency of acute exacerbations, making it statistically difficult to detect a weak correlation. We postulate that CCL23 may reflect the persistent systemic inflammatory burden rather than transient symptomatic fluctuations.
But this hypothesis still requires validation. With regard to pregnancy outcomes, the extremely small number of events, including preterm birth (n = 5) and miscarriage (n = 4), rendered the statistical power of the relevant analyses severely insufficient. Therefore, all association analyses between CCL23 and pregnancy outcomes should be interpreted as exploratory only and should not be overinterpreted.
Future studies specifically designed with large-scale prospective cohorts focusing on pregnancy outcomes are warranted to clarify the predictive value of CCL23 for maternal and neonatal safety.
Limitations
The exploratory transcriptomic pilot included only three participants per group, and CCL23 therefore did not reach statistical significance after correction for multiple testing (q = 0.07), so that its selection for validation rested on effect size and nominal significance rather than on a transcriptome-wide significant result. This was a single-center study with a total sample size of only 73 participants, and some subgroups (eg, only 5 participants in the EOS < 0.1 group) were extremely small. Due to insufficient delivery data and the rarity of some endpoint events, the pregnancy outcome analyses were exploratory only and had limited statistical power; the results should not be overinterpreted, and validation in large prospective cohort studies is needed in the future.
Given that CCL23, EOS, and asthma status were all measured concurrently at enrollment, causal inference cannot be established. The mediation analysis was only a cross-sectional statistical exploration, and future longitudinal cohort studies are needed to clarify the temporal relationship between dynamic changes in CCL23 and asthma control outcomes. Finally, the AUC was 0.74 for CCL23 alone and 0.87 for the CCL23 + EOS model.
The combined model performed better than CCL23 alone but not better than EOS alone (AUC 0.88), indicating that the incremental discriminatory value of CCL23 over EOS was not demonstrated. Although the combined model underwent internal validation, external validation is still lacking. Therefore, this combined model should not yet be regarded as an established diagnostic or screening tool and requires further validation in larger, multicenter, independent pregnancy cohorts.
Due to practical limitations and safety concerns associated with pulmonary function testing during pregnancy, some patients did not undergo pulmonary function testing and therefore lacked objective evidence of variable expiratory airflow limitation. In these patients, the diagnosis was based on a detailed clinical assessment.
In addition, only a single measurement of serum CCL23 levels was obtained in this study, without tracking its dynamic trajectory across different stages of pregnancy (first, second, and third trimesters) or during episodes of asthma exacerbation and remission, which limits the assessment of CCL23’s value as a therapeutic monitoring biomarker. Furthermore, CCL23 was measured exclusively in serum, and induced sputum or bronchoalveolar lavage fluid samples were not collected, precluding direct validation of the plasma–airway gradient and the local pulmonary origin of CCL23. Whether CCL23 is truly derived from the airways and enters the systemic circulation remains inferential and requires confirmation through paired sample studies.
Although multiple gestational age adjustment approaches were applied, including linear ANCOVA (the primary model), non-linear adjustment (gestational age + gestational age2), overlap weighting based on gestational age, and 1:1 matching, together with interaction analysis, residual confounding related to gestational age cannot be completely excluded. In addition, 1:1 matching substantially reduced the sample size and limited statistical power. Therefore, these findings are exploratory, and future studies should sample at similar gestational ages, or perform gestational age matching and stratified analyses, to further validate the association between CCL23 and asthma in pregnancy.
Conclusions
This study suggested that serum CCL23 is elevated in pregnant women with asthma and is positively correlated with peripheral blood EOS and FeNO, suggesting its potential involvement in type 2 inflammatory pathways during pregnancy. Multivariable regression analysis showed that elevated CCL23 was independently associated with an increased risk of asthma in pregnancy; However, after adjustment for gestational age, the between-group difference in CCL23 was no longer statistically significant in most models, but the independent association between CCL23 and the risk of asthma in pregnancy remained relatively stable across most sensitivity analyses. In ROC analysis, CCL23 alone yielded an AUC of 0.74, EOS alone 0.88, and the CCL23 + EOS model 0.87.
The combined model significantly outperformed CCL23 alone (DeLong P = 0.01) but did not significantly outperform EOS alone (DeLong P = 0.13); The incremental discriminatory value of CCL23 beyond EOS was therefore not demonstrated. Internal validation showed no material overfitting, but external validation in larger, multicenter, independent pregnancy cohorts is still required. These findings are exploratory, and the potential adjunctive identification value of these markers, particularly EOS alone or in combination with CCL23, requires further confirmation across different gestational stages and asthma phenotypes.