Abstract
Objective
Gestational diabetes mellitus (GDM) is a common metabolic complication during pregnancy. Early identification of high-risk women is critical for reducing maternal and fetal complications. This study aimed to explore the predictive value of serum pentraxin 3 (PTX3) and galectin-3 in early pregnancy for GDM among Chinese women.
Methods
This retrospective case-control study recruited pregnant women with a first prenatal visit before 14 weeks of gestation. Serum samples were collected at enrollment. All participants were followed up to 24–28 weeks, and GDM was confirmed via standard 75 g oral glucose tolerance test (OGTT). Correlation analysis, ROC curve and binary logistic regression were used to evaluate predictive efficacy. A total of 120 eligible women were divided into the GDM group (n=60) and healthy control group (n=60).
Results
FBG, FINS, PTX3 and galectin-3 levels were markedly elevated in GDM group (P < 0.05). Both biomarkers were positively correlated with glucose and insulin indexes (P < 0.05). The AUC values of PTX3 and galectin-3 were 0.821 and 0.662 respectively. The combined detection yielded an AUC of 0.877, with a sensitivity of 86.5% and a specificity of 92.3%. PTX3 and galectin-3 were verified as independent risk factors of GDM.
Conclusion
First-trimester PTX3 and galectin-3 can serve as effective biomarkers for GDM prediction. Combined detection improves diagnostic efficiency and facilitates early screening for high-risk populations. Due to the single-center design and 1:1 grouping inconsistent with actual GDM prevalence, further prospective multicenter studies are required to validate our findings.
Keywords: gestational diabetes mellitus, pentraxin 3, galectin-3, predictive value, first trimester, inflammatory biomarkers
Introduction
Gestational diabetes mellitus (GDM) is a prevalent metabolic disorder complicating pregnancy, with a global prevalence of 5–10% and an increasing trend in China in recent years. Standardized diagnostic and management criteria have been established to lower maternal and fetal adverse events.1 Early screening of high-risk population is critical for timely intervention, and inflammatory response is tightly linked with insulin resistance underlying GDM.
Existing research verifies that diverse serum biomarkers can realize effective early screening of GDM in first-trimester pregnancy.2 Secreted by endothelial cells, macrophages and adipocytes, pentraxin 3 participates in placental inflammation and disturbs glucose metabolic balance, possessing favorable predictive potential for GDM occurrence.
Galectin-3 modulates trophoblast invasion and placental vascular remodelling, and takes part in regulating insulin signaling cascade. Its early gestational concentration can well assess individual GDM susceptibility.3 The period before 14 weeks of gestation acts as an optimal intervention window before irreversible glycometabolic damage forms. Single biomarker testing has obvious defects in diagnostic performance, whereas combined detection can greatly enhance risk prediction precision.4
This study intended to investigate the predictive significance of serum PTX3 and galectin-3 levels in early pregnancy for GDM among Chinese pregnant women, and evaluate the clinical value of joint detection strategy.
Materials and Methods
As shown in Figure 1, 300 pregnant women were initially screened, and 120 eligible participants were finally enrolled and allocated into the GDM group and the control group.
Figure 1.
Flow diagram of participant recruitment and selection following STROBE guidelines. A total of 300 pregnant women with first prenatal visit before 14 weeks of gestation were initially screened. After excluding 180 ineligible subjects, 120 participants completed follow-up and 75 g OGTT at 24–28 weeks gestation. According to OGTT diagnostic results, eligible subjects were divided into GDM group (n=60) and healthy control group (n=60).
Study Participants
Clinical demographic and general clinical data were collected from January 2023 to December 2024. Data extraction was conducted simultaneously by standardized case report forms and hospital electronic health record system. Two professional clinical researchers independently extracted all data and remained blinded to group allocation throughout the whole process. Strict integrity assessment of medical records was carried out, and subjects lacking core clinical indicators were excluded directly. An observational case-control study was performed. Pregnant women with a first prenatal visit at less than 14 weeks of gestation, who received prenatal care between January 2023 and December 2024, were included. A total of 120 participants were divided into the GDM group (n=60) and the control group (n=60). The diagnostic criteria for GDM were in accordance with Obstetrics and Gynecology.5 In this study, GDM diagnosis strictly followed the clinical guidelines for gestational diabetes and the unified standards from the national textbook Obstetrics and Gynecology. The diagnosis was performed at 24–28 weeks of gestation using the standard 75 g oral glucose tolerance test (OGTT). After 8–14 hours of overnight fasting, participants ingested 75 g anhydrous glucose. Venous blood glucose was measured at fasting, 1 h and 2 h after glucose loading. The diagnostic thresholds were defined as: fasting blood glucose ≥ 5.1 mmol/L, 1-h glucose ≥ 10.0 mmol/L, 2-h glucose ≥ 8.5 mmol/L. GDM was diagnosed if any index reached the above cut-off value; participants with all indicators below the thresholds were regarded as normal glucose tolerance. All participants had a gestational age of less than 14 weeks at their first prenatal visit, when serum samples were collected.
Inclusion Criteria
Singleton pregnancy; gestational age at the first prenatal visit <14 weeks at the time of serum sampling; meeting the diagnostic criteria for GDM (normal glucose tolerance in the control group); complete clinical data and serum samples; signed informed consent.
Exclusion Criteria
Pre-gestational diabetes, thyroid disease, or severe liver/renal dysfunction; acute infection, autoimmune disease, or malignant tumor; use of medications affecting glucose metabolism within 3 months; incomplete clinical data.
This study was conducted in accordance with the Declaration of Helsinki and approved by two independent ethics committees: the Ethics Committee of Xi’an Jiaotong University Hospital (Approval No. 2022-L12). Written informed consent was obtained from all pregnant women prior to enrollment. Participants were aged 22–38 years. All serum samples (PTX3, galectin-3, FBG, FINS) were collected at 8–13+6 weeks of gestation (first trimester). GDM was diagnosed at 24–28 weeks by a 75-g oral glucose tolerance test (OGTT) according to standard criteria. The early-pregnancy markers were measured before GDM diagnosis, and participants were followed until 24–28 weeks to confirm GDM status.
Laboratory Measurements
General data including age, gravidity, and parity were collected. Fasting venous blood samples were centrifuged at 3000 r/min for 10 minutes to obtain serum. The following indicators were measured: Fasting blood glucose (FBG); Fasting insulin (FINS);Serum PTX3;Serum galectin-3. The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as: HOMA-IR = FBG (mmol/L) × FINS (μU/mL)/22.5.
Data Preprocessing
All collected data were uniformly sorted and cleaned before statistical analysis. Cases with missing core study indicators were eliminated by listwise deletion, while minor missing secondary indicators were not included in final analysis. Outliers were detected via interquartile range method. Verified valid outliers confirmed by original medical records were retained, and suspicious abnormal values were removed. The Shapiro–Wilk test combined with Q-Q plots was adopted to assess the normality of data distribution. Basic descriptive statistical analysis of baseline characteristics was performed prior to formal hypothesis testing.
Statistical Analysis
All statistical analyses were performed using SPSS 26.0 (IBM Corp., Armonk, NY, USA). Test selection depended on normality results from Shapiro–Wilk test and Q-Q plots. Independent-samples t-test and Mann–Whitney U-test were adopted for normal and non-normal data respectively. Pearson and Spearman correlation analyses were applied correspondingly. Binary logistic regression was used to screen GDM predictors. Model fitness was evaluated via Hosmer–Lemeshow test and Nagelkerke R2. The EPV ratio reached 30, meeting the stable modeling standard.6 ROC curve analysis assessed predictive efficacy. AUC with 95% CI was computed, and optimal cut-off value was determined by Youden index.7 Bonferroni correction was used to control type I error. Post-hoc power analysis verified 120 samples satisfied statistical demands at α=0.05 and 1-β=0.8. The lack of prior sample estimation was noted as study limitation.
Results
Comparison of Clinical Data and Serum Indexes Between the Two Groups
These preliminary results are only applicable to enrolled participants and cannot be generalized to all Chinese pregnant women. Gravidity, fasting blood-glucose (FBG), fasting insulin (FINS), serum PTX3 and Galectin-3 levels were markedly elevated in the GDM group relative to the healthy group (P<0.05). No obvious differences in age and parity were observed between the two groups (P>0.05). Detailed data are shown in Table 1.
Table 1.
Comparison of Clinical Data and Serum Indexes Between the Two Groups
| Index | GDM Group (n=60) | Healthy Group (n=60) | t/χ2 | P |
|---|---|---|---|---|
| Age (years) | 28.01±3.58 | 28.02±3.11 | 0.015 | 0.988 |
| Gravidity | 1.98±0.82 | 2.35±0.95 | 2.126 | 0.036 |
| Parity, n (%) | 0.357 | 0.550 | ||
| Primipara | 37 (61.7) | 34 (56.7) | ||
| Multipara | 23 (38.3) | 26 (43.3) | ||
| Gestational age at GDM diagnosis (weeks) | 25.7±1.1 | 25.6±1.2 | 0.471 | 0.639 |
| FBG (mmol/L) | 5.53±0.48 | 4.42±0.39 | 12.942 | 0.000 |
| FINS (μU/mL) | 13.29±2.15 | 10.74±2.09 | 6.133 | 0.000 |
| HOMA-IR | 3.27±0.72 | 2.11±0.58 | 9.456 | 0.000 |
| PTX3 (ng/mL) | 9.11±1.95 | 6.94±1.79 | 5.911 | 0.000 |
| Galectin-3 (ng/mL) | 10.03±2.14 | 7.84±2.53 | 4.766 | 0.000 |
Correlation between Serum Inflammatory Markers and Blood Glucose/Insulin Indicators
Pearson correlation analysis was performed to evaluate the association between serum PTX3/Galectin-3 and blood glucose metabolism indicators. The results showed that in the GDM group, serum PTX3 level in early pregnancy was positively correlated with FBG (r=0.624, P<0.001) and FINS (r=0.587, P<0.001); serum Galectin-3 level was positively correlated with FBG (r=0.412, P<0.001) and FINS (r=0.385, P<0.001). All correlation coefficients are shown in Table 2.
Table 2.
Pearson Correlation Analysis Between Serum Inflammatory Markers and Blood Glucose/Insulin Indicators in the GDM Group
| Inflammatory Marker | Metabolic Indicator | Correlation Coefficient r | 95% Confidence Interval CI | P value |
|---|---|---|---|---|
| PTX3 | FBG | 0.624 | 0.458–0.752 | <0.001 |
| PTX3 | FINS | 0.587 | 0.412–0.721 | <0.001 |
| Galectin-3 | FBG | 0.412 | 0.205–0.587 | <0.001 |
| Galectin-3 | FINS | 0.385 | 0.176–0.564 | <0.001 |
Notes: All correlation analyses were performed using Pearson’s correlation test. A P value <0.05 was considered statistically significant.
Predictive Value of Serum PTX3 and Galectin-3 for GDM
ROC analysis was performed to assess the predictive ability of PTX3 and Galectin-3 for GDM. The corresponding ROC curves are presented in Figure 2. The optimal diagnostic cut-off value was determined according to the Youden index. The 95% confidence interval of Galectin-3 AUC ranges from 0.505 to 0.816, with the lower limit approaching the random level of 0.5. This wide interval indicates that the single predictive performance of Galectin-3 is unstable and limited. Detailed outcomes are displayed in Table 3.
Figure 2.
ROC curves of serum PTX3, Galectin-3, and their combination for predicting GDM.
Table 3.
ROC Curve Analysis of Serum Inflammatory Markers for Predicting Gestational Diabetes Mellitus
| Inflammatory Marker | AUC | 95% Confidence Interval CI | Optimal Cut-off Value | Sensitivity | Specificity | P value |
|---|---|---|---|---|---|---|
| PTX3 | 0.821 | 0.745–0.897 | 3.25 ng/mL | 76.7% | 78.3% | <0.001 |
| Galectin-3 | 0.662 | 0.505–0.816 | 15.8 ng/mL | 63.3% | 61.7% | 0.032 |
Notes: The optimal diagnostic cut-off value was determined according to the Youden index7. The 95% confidence interval of Galectin-3 AUC ranges from 0.505 to 0.816, with the lower limit approaching the random level of 0.5, indicating unstable and limited independent predictive performance of Galectin-3 alone. An AUC >0.7 was considered to have good predictive efficacy; an AUC of 0.5–0.7 was considered to have limited predictive efficacy.
Multivariate Logistic Regression Analysis of GDM
Binary logistic regression analysis was conducted to identify independent predictors of GDM, with PTX3 and Galectin-3 as independent variables and GDM diagnosis as the dependent variable. The results showed that both PTX3 (OR=2.391, 95% CI 1.568–3.647, P<0.001) and Galectin-3 (OR=1.679, 95% CI 1.127–2.503, P=0.011) were independent risk factors for GDM. The model had a Nagelkerke R2 of 0.324, and the Hosmer–Lemeshow test indicated good model fit (χ2=8.762, P=0.363). The overall classification accuracy of the model was 78.3% (95% CI 70.2–85.1%). Detailed regression results are presented in Table 4.
Table 4.
Results of Binary Logistic Regression Analysis for Influencing Factors of Gestational Diabetes Mellitus
| Variable | Regression Coefficient β | Standard Error SE | Wald χ2 | P value | Odds Ratio OR | 95% Confidence Interval CI |
|---|---|---|---|---|---|---|
| Constant | −1.235 | 0.321 | 14.782 | <0.001 | 0.291 | 0.155–0.546 |
| PTX3 | 0.872 | 0.215 | 16.453 | <0.001 | 2.391 | 1.568–3.647 |
| Galectin-3 | 0.518 | 0.203 | 6.521 | 0.011 | 1.679 | 1.127–2.503 |
Notes: (Model Fitting and Overall Efficacy Supplementary Indicators). Nagelkerke R2: 0.324. Hosmer–Lemeshow Goodness-of-Fit Test: χ2=8.762, P=0.363 (P>0.05 indicates good model fit). Overall classification accuracy of the model: 78.3% (95% CI 70.2–85.1%).
Discussion
Gestational diabetes mellitus is a common metabolic complication during pregnancy with insidious onset and atypical early clinical manifestations. It not only increases the risks of adverse pregnancy outcomes such as macrosomia, polyhydramnios, cesarean section, and neonatal hypoglycemia, but also significantly elevates the risk of postpartum type 2 diabetes mellitus in mothers and long-term metabolic syndrome in offspring, thus seriously threatening maternal and infant health.8 The core pathogenesis of GDM involves insulin resistance, pancreatic β-cell dysfunction, chronic low-grade inflammation, and vascular endothelial injury, which interact and contribute to the development of the disease.9 Therefore, identifying sensitive and specific biomarkers in early pregnancy for early prediction and stratified intervention of GDM has important clinical significance.
The present study showed that serum PTX3 and Galectin-3 levels in early pregnancy were significantly higher in the GDM group than in the healthy group, and were positively correlated with FBG and FINS, suggesting that both indicators are involved in the pathophysiological process of GDM and are closely related to glucose metabolism disorder and insulin resistance. As a tissue-specific inflammatory marker and vascular endothelial injury indicator, PTX3 is mainly secreted by endothelial cells, monocytes, and adipocytes. It directly reflects local vascular inflammation and plays an important regulatory role in metabolic diseases and vascular lesions.10 Previous studies confirmed that serum PTX3 level is significantly increased in GDM patients during the second and third trimesters and is closely related to postpartum blood glucose outcome.11 Other studies reported that elevated serum PTX3 level in early pregnancy is an independent risk factor for GDM and can be used as an early predictor.12 Our results are consistent with those of previous studies, further supporting that PTX3 participates in the pathogenesis of GDM by reflecting vascular inflammation and endothelial injury.13 Significant ethnic differences exist in inflammatory biomarker expression and predictive performance. PTX3 baseline levels vary obviously among South Asian, Middle Eastern, African and European pregnant populations, which directly leads to discrepant diagnostic efficiency for GDM. Our PTX3 AUC value differs from results reported in foreign cohorts, which is largely attributed to inherent racial inflammatory physiological characteristics. For Galectin-3, the present AUC outcome is basically consistent with partial domestic researches, while showing deviations from European studies. The disparity is mainly related to population genetic background and metabolic differences. Compared with common first-trimester predictive indicators including adiponectin, PAPP-A, SHBG and HbA1c, PTX3 and Galectin-3 possess moderate predictive capacity. The combined detection of the two markers presents competitive diagnostic value, occupying a favorable position among existing screening biomarkers. Chinese Han population owns distinctive high-carb dietary structure and regional obesity prevalence. Unique ethnic insulin resistance mechanism also contributes to inconsistent biomarker performance between this study and international researches, further explaining the divergence of predictive results.14
Galectin-3 is a multifunctional β-galactoside-binding protein that is widely involved in cell apoptosis, inflammatory response, immune regulation, angiogenesis, insulin signaling, and other biological processes. It is regarded as a broad-spectrum biomarker for metabolic and cardiovascular risks.15 Studies have confirmed that Galectin-3 is significantly elevated in patients with type 2 diabetes and prediabetes, and is positively correlated with the degree of insulin resistance.16,17 During pregnancy, Galectin-3 is mainly expressed in extravillous trophoblasts and participates in placental vascular remodeling. Its abnormally high expression can promote the occurrence of GDM by aggravating insulin resistance and vascular dysfunction.18,19 The present study showed that serum Galectin-3 level was significantly increased in the GDM group in early pregnancy and was an independent risk factor for GDM, which is consistent with previous findings, indicating that Galectin-3 can be used as a potential biomarker for early prediction of GDM.
ROC curve analysis showed that the AUC of serum PTX3 and Galectin-3 for predicting GDM was 0.821 and 0.662, respectively, and the combined detection achieved an AUC of 0.877 with significantly improved sensitivity and specificity, suggesting that combined detection can improve early predictive efficiency.20,21 Multivariate Logistic regression analysis further confirmed that PTX3 and Galectin-3 were independent risk factors for GDM, indicating that combined detection of the two indicators in early pregnancy can provide a more reliable basis for clinical screening.
This study still exists several unavoidable limitations. Firstly, no prospective power calculation was implemented before subject enrollment. Secondly, the adopted 1:1 case-control ratio fails to conform to actual 5–10% GDM prevalence, which may overestimate positive predictive value. Thirdly, no external validation cohort is applied to verify the stability of research results. Fourthly, potential confounding factors such as pre-pregnancy BMI, diabetes family history, daily diet and physical activity were not corrected in statistical analysis. Finally, retrospective research design cannot confirm definite temporal causality between inflammatory markers and GDM occurrence.
Conclusion
This study suggests that first-trimester serum PTX3 and Galectin-3 exhibit promising predictive potential for GDM. The relevant results are only statistically applicable to pregnant women treated at Xi’an Jiaotong University Hospital from 2023 to 2024, and cannot be directly generalized to all Chinese pregnant population without external validation. Further large-sample, multicenter prospective studies with standardized detection schemes and multi-regional ethnic subgroups enrollment are required to confirm its clinical value and support clinical intervention application.
Funding Statement
Project Title: Digitalized MDT Management of Non-Cesarean Scar Uterus Throughout Pregnancy2024SF-YBXM-232.
Ethics
Committee of Xi’an Jiaotong University Hospital (Approval No.2022-L12).
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
The authors report no conflicts of interest in this work.
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