87urn:lsid:arphahub.com:pub:A116C711-4C18-5A38-8F1E-5E97753A8A64Folia MedicaFM0204-80431314-2143Plovdiv Medical University10.3897/folmed.66.e137403137403Research NoteNursing & MidwiferyMetabolomic biomarkers in amniotic fluid for early diagnosis of preterm birth and fetal growth restrictionKolvatzisCharalamposcharis_kolv@hotmail.com1TsiantasKonstantinos2TsakiridisIoannishttps://orcid.org/0000-0003-4337-78711ChristodoulouParis2CheilariAntigoni3KalogiannidisIoannis1ZoumpoulakisPanagiotis2AthanasiadisApostolos1Third Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, GreeceAristotle University of ThessalonikiThessalonikiGreeceDepartment of Food Science and Technology, University of West Attica, Athens, GreeceUniversity of West AtticaAthensGreeceDepartment of Pharmacognosy and Natural Products Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens, Athens, GreeceNational and Kapodistrian University of AthensAthensGreece
Corresponding author: Charalampos Kolvatzis, Third Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece; Email: charis_kolv@hotmail.com
2024311020246657177207D182750-4F15-5EC8-81E9-79DFED8610F92009202420092024Charalampos Kolvatzis, Konstantinos Tsiantas, Ioannis Tsakiridis, Paris Christodoulou, Antigoni Cheilari, Ioannis Kalogiannidis, Panagiotis Zoumpoulakis, Apostolos AthanasiadisThis is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Preterm birth, affecting about 10% of pregnancies, significantly contributes to perinatal morbidity and mortality. Recent research indicates that metabolomics could enhance pregnancy outcomes and reduce costs by identifying biomarkers related to common pregnancy complications. Our team focused on analyzing amniotic fluid collected during the second trimester to identify potential biomarkers for preterm birth using 1H-NMR metabolomic analysis. We compared amniotic fluid samples from women who delivered prematurely with those who delivered at term. Multivariate principal component analysis revealed dimethylglycine, glucose, myo-inositol, and succinic acid as potential biomarkers for preterm birth prognosis and early diagnosis. Further analysis demonstrated distinct regulation patterns of these metabolites in relation to fetal growth centiles. For instance, dimethylglycine and glucose were upregulated in fetuses above the 20th centile, while citrate and succinate were upregulated in those below it. With Area Under the Curve (AUROC) values over 0.75 and p-values less than 0.05, these metabolites show promise as reliable biomarkers for predicting fetal growth restriction. This approach could significantly impact maternal-fetal medicine by facilitating early diagnosis and personalized interventions. Future research should focus on validating these findings in larger populations and exploring the underlying mechanisms of metabolite regulation.
Kolvatzis C, Tsiantas K, Tsakiridis I, Christodoulou P, Cheilari A, Kalogiannidis I, Zoumpoulakis P, Athanasiadis A. Metabolomic biomarkers in amniotic fluid for early diagnosis of preterm birth and fetal growth restriction. Folia Med (Plovdiv) 2024;66(5):717-720. doi: 10.3897/folmed.66.e137403.
Preterm birth is a major contributor of perinatal morbidity and mortality, complicating about one out of ten pregnancies.[1] Several studies of metabolomics are currently available regarding common complications of pregnancy; their use could improve pregnancy outcomes and lead to cost reduction.[2–4]
Recently, our team investigated whether the analysis of the metabolic composition of amniotic fluid collected from pregnant women in the second trimester could provide valuable information on preterm birth. We used 1H-NMR metabolomic analysis to examine amniotic fluid samples from women who delivered prematurely and those who delivered at term. Using multivariate principal component analysis, dimethylglycine, glucose, myo-inositol and succinic acid were identified as potential biomarkers for the prognosis and early diagnosis of preterm birth.[5]
Following further analyses, utilizing the same methodology[5], we found that the previously identified metabolites show distinct patterns of regulation that correlate with specific pregnancy milestones. This means that the levels of these metabolites change predictably, according to the fetal growth centile. For example, according to Fig. 1, dimethylglycine and glucose are upregulated in fetuses >20 centile, while citrate and succinate are upregulated in those <20 centile. Based on the fact that these metabolites are validated (Area Under the Curve, AUROC >0.75 and p-value <0.05), this regulation pattern suggests that the above metabolites could be used as reliable biomarkers to predict fetal growth restriction. This may have a significant impact in maternal-fetal medicine since accurate prediction of birthweight could favor early diagnosis of implications related to prenatal monitoring, allowing personalized and timely interventions to ensure the health and safety of the fetus/neonate.
AF7BB38C-FF90-5A57-93AE-E403C77CCE6B
Metabolites of interest derived by discriminant analysis of fetal growth centile.
https://binary.pensoft.net/fig/1169071
Herein, by combining NMR metabolomics and a unique multivariate statistical approach, we provided new insights into amniotic fluid biomarker discovery anhighlighted the potential for metabolomics to contribute to improving maternal and neonatal outcomes. Future studies should aim to validate these biomarkers in larger and more diverse populations and investigate the mechanisms driving these regulatory changes.
Acknowledgements
The authors have no support to report.
Funding
The authors have no funding to report.
Competing Interests
The authors have declared that no competing interests exist.
Author contributions
Conceptualization: A.A., I.K., P.Z., C.K., and P.C.; methodology: P.C., I.T., K.T., A.C., P.Z., A.A., and C.K.; software: P.C., K.T., and A.C.; investigation: C.K., I.T., K.T., and P.C.; data curation: C.K., P.C., K.T., and A.C.; resources: P.Z., A.A., and C.K.; visualization: P.C.; writing original draft preparation: C.K., I.T., P.C., K.T., and A.C.; writing review and editing: C.K., I.T., P.C., K.T., N.S.T., A.A., and I.K.; supervision: A.A., I.K., and P.Z.; project administration: P.Z. and A.A. All authors have read and agreed to the published version of the manuscript.
Ethical statement
Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki and approved by the Aristotle University of Thessaloniki Research Ethics Committee (Prot. No. 1.662/21 November 2018) for studies involving humans. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
References1. Kolvatzis C, Tsakiridis I, Kalogiannidis IA, et al. Utilizing amniotic fluid metabolomics to monitor fetal well-being: a narrative review of the literature. Cureus 2023;15(3):e36986.2. Bardanzellu F, Fanos V. How could metabolomics change pediatric health? Italian J Pediat 2020; 46(1):1–13.3. Fattuoni C, Palmas F, Noto A, et al. Primary HCMV infection in pregnancy from classic data towards metabolomics: an exploratory analysis. Clinica Chimica Acta 2016; 460:23–32.4. Fattuoni C, Mandò C, Palmas F, et al. Preliminary metabolomics analysis of placenta in maternal obesity. Placenta 2018; 61:89–95.5. Kolvatzis C, Christodoulou P, Kalogiannidis I, et al. Metabolomic profiling of second-trimester amniotic fluid for predicting preterm delivery: insights from NMR analysis. Metabolites 2023; 13(11):1147.