» Articles » PMID: 36788507

Maternal Circulating Metabolic Biomarkers and Their Prediction Performance for Gestational Diabetes Mellitus Related Macrosomia

Overview
Publisher Biomed Central
Date 2023 Feb 15
PMID 36788507
Authors
Affiliations
Soon will be listed here.
Abstract

Introduction: Gestational diabetes mellitus (GDM), a metabolism-related pregnancy complication, is significantly associated with an increased risk of macrosomia. We hypothesized that maternal circulating metabolic biomarkers differed between women with GDM and macrosomia (GDM-M) and women with GDM and normal neonatal weight (GDM-N), and had good prediction performance for GDM-M.

Methods: Plasma samples from 44 GDM-M and 44 GDM-N were analyzed using Olink Proseek multiplex metabolism assay targeting 92 biomarkers. Combined different clinical characteristics and Olink markers, LASSO regression was used to optimize variable selection, and Logistic regression was applied to build a predictive model. Nomogram was developed based on the selected variables visually. Receiver operating characteristic (ROC) curve, calibration plot, and clinical impact curve were used to validate the model.

Results: We found 4 metabolism-related biomarkers differing between groups [CLUL1 (Clusterin-like protein 1), VCAN (Versican core protein), FCRL1 (Fc receptor-like protein 1), RNASE3 (Eosinophil cationic protein), FDR <  0.05]. Based on the different clinical characteristics and Olink markers, a total of nine predictors, namely pre-pregnancy body mass index (BMI), weight gain at 24 gestational weeks (gw), parity, oral glucose tolerance test (OGTT) 2 h glucose at 24 gw, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) at 24 gw, and plasma expression of CLUL1, VCAN and RNASE3 at 24 gw, were identified by LASSO regression. The model constructed using these 9 predictors displayed good prediction performance for GDM-M, with an area under the ROC of 0.970 (sensitivity = 0.955, specificity = 0.886), and was well calibrated (P  = 0.897).

Conclusion: The Model included pre-pregnancy BMI, weight gain at 24 gw, parity, OGTT 2 h glucose at 24 gw, HDL and LDL at 24 gw, and plasma expression of CLUL1, VCAN and RNASE3 at 24 gw had good prediction performance for predicting macrosomia in women with GDM.

Citing Articles

Identification and validation of palmitoylation-related biomarkers in gestational diabetes mellitus.

Zhang K, Shi X, Bian R, Shi W, Yang L, Ren C Sci Rep. 2025; 15(1):8019.

PMID: 40055514 PMC: 11889268. DOI: 10.1038/s41598-025-93046-w.


Association of the triglyceride-glucose index and the ratio of triglyceride to high-density lipoprotein cholesterol with fetal macrosomia in nulliparous pregnant women: a prospective case-control study.

Firatligil F, Tuncdemir S, Sucu S, Akdas Reis Y, Ozkan S, Dereli M BMC Pregnancy Childbirth. 2025; 25(1):175.

PMID: 39962459 PMC: 11834243. DOI: 10.1186/s12884-025-07317-5.


Early Prediction of Fetal Macrosomia Through Maternal Lipid Profiles.

Chagovets V, Frankevich N, Starodubtseva N, Tokareva A, Derbentseva E, Yuryev S Int J Mol Sci. 2025; 26(3).

PMID: 39940917 PMC: 11818448. DOI: 10.3390/ijms26031149.


Maternal inflammatory, lipid and metabolic markers and associations with birth and breastfeeding outcomes.

Hilario Christensen S, Rom A, Greve T, Lewis J, Frokiaer H, Allen L Front Nutr. 2023; 10:1223753.

PMID: 37731394 PMC: 10507339. DOI: 10.3389/fnut.2023.1223753.


Prevalence of abnormal glucose values and gestational diabetes mellitus among pregnant women in Xi'an from 2015 to 2021.

Meng G, Wang Q, Kang R, Cheng X, Yang J, Xie Y BMC Pregnancy Childbirth. 2023; 23(1):471.

PMID: 37355571 PMC: 10290305. DOI: 10.1186/s12884-023-05798-w.

References
1.
Sirico A, DellAquila M, Tartaglione L, Moresi S, Fari G, Pitocco D . PTH-rP and PTH-R1 Expression in Placentas from Pregnancies Complicated by Gestational Diabetes: New Insights into the Pathophysiology of Hyperglycemia in Pregnancy. Diagnostics (Basel). 2021; 11(8). PMC: 8394866. DOI: 10.3390/diagnostics11081356. View

2.
Bi S, Zhang L, Chen J, Huang L, Zeng S, Jia J . Development and Validation of Predictive Models for Vaginal Birth After Cesarean Delivery in China. Med Sci Monit. 2020; 26:e927681. PMC: 7722770. DOI: 10.12659/MSM.927681. View

3.
Lekva T, Sugulle M, Moe K, Redman C, Dechend R, Staff A . Multiplex Analysis of Circulating Maternal Cardiovascular Biomarkers Comparing Preeclampsia Subtypes. Hypertension. 2020; 75(6):1513-1522. DOI: 10.1161/HYPERTENSIONAHA.119.14580. View

4.
Khosrowbeygi A, Shiamizadeh N, Taghizadeh N . Maternal circulating levels of some metabolic syndrome biomarkers in gestational diabetes mellitus. Endocrine. 2015; 51(2):245-55. DOI: 10.1007/s12020-015-0697-4. View

5.
Du J, Zhang X, Chai S, Zhao X, Sun J, Yuan N . Nomogram-based risk prediction of macrosomia: a case-control study. BMC Pregnancy Childbirth. 2022; 22(1):392. PMC: 9074352. DOI: 10.1186/s12884-022-04706-y. View