Accuracy of glycosylated fibronectin-based cut-off levels for predicting gestational diabetes mellitus
DOI:
https://doi.org/10.18203/2320-1770.ijrcog20260539Keywords:
Early pregnancy biomarker, Gestational diabetes mellitus, Glycosylated fibronectinAbstract
Background: Gestational diabetes mellitus (GDM) is a common metabolic complication of pregnancy and is associated with adverse maternal and neonatal outcomes. Early identification of women at risk remains challenging, as routine screening is typically performed in mid-pregnancy. This study aimed to assess the accuracy of first-trimester maternal serum glycosylated fibronectin cut-off levels for predicting GDM.
Methods: A prospective cohort study was conducted at the Department of Obstetrics and Gynecology at Dhaka Medical College Hospital, Dhaka, Bangladesh, from December 2020 to November 2021. Ninety-five pregnant women with singleton pregnancies between 10 and 15 weeks of gestation were enrolled. Maternal serum glycosylated fibronectin was measured using ELISA. Participants were followed until delivery and GDM was diagnosed using WHO criteria at 24-28 weeks. Statistical analysis was performed using SPSS version 23.
Results: Most participants were aged 21–30 years (66.3%) and overweight (75.8%). Women who developed GDM had significantly higher mean glycosylated fibronectin levels than non-GDM women (226.7±73.3 vs. 114.2±57.9 µg/ml; p<0.001). Among women with glycosylated fibronectin ≥145.0 µg/ml, 83.3% developed GDM, whereas only 16.7% of GDM cases occurred below this threshold. Mean body mass index was also significantly higher among women with elevated glycosylated fibronectin levels (p=0.01).
Conclusions: Elevated first-trimester maternal serum glycosylated fibronectin is strongly associated with subsequent development of GDM and may serve as an effective early screening biomarker for identifying high-risk pregnancies.
References
Guariguata L, Linnenkamp U, Beagley J, Whiting DR, Cho NH. Global estimates of the prevalence of hyperglycaemia in pregnancy. Diabet Res Clin Pract. 2014;103(2):176-85. DOI: https://doi.org/10.1016/j.diabres.2013.11.003
Behboudi-Gandevani S, Amiri M, Bidhendi Yarandi R, Ramezani Tehrani F. The impact of diagnostic criteria for gestational diabetes on its prevalence: a systematic review and meta-analysis. Diabetol Metabol Syndr. 2019;11(1):11. DOI: https://doi.org/10.1186/s13098-019-0406-1
Zhu WW, Yang HX, Wang C, Su RN, Feng H, Kapur A. High prevalence of gestational diabetes mellitus in Beijing: effect of maternal birth weight and other risk factors. Chin Med J. 2017;130(09):1019-25. DOI: https://doi.org/10.4103/0366-6999.204930
Begum IA. Gestational diabetes mellitus in Primi gravida of Bangladesh in different trimesters. Int J Biol. 2014;6(3):18. DOI: https://doi.org/10.5539/ijb.v6n3p18
Jesmin S, Akter S, Akashi H, Al-Mamun A, Rahman MA, Islam MM, et al. Screening for gestational diabetes mellitus and its prevalence in Bangladesh. Diabet Res Clin Pract. 2014;103(1):57-62. DOI: https://doi.org/10.1016/j.diabres.2013.11.024
Damm P. Future risk of diabetes in mother and child after gestational diabetes mellitus. Int J Gynecol Obstetr. 2009;104:S25-6. DOI: https://doi.org/10.1016/j.ijgo.2008.11.025
Chen LW, Soh SE, Tint MT, Loy SL, Yap F, Tan KH, et al. Combined analysis of gestational diabetes and maternal weight status from pre-pregnancy through post-delivery in future development of type 2 diabetes. Sci Rep. 2021;11(1):5021. DOI: https://doi.org/10.1038/s41598-021-82789-x
Blumer I, Hadar E, Hadden DR, Jovanovič L, Mestman JH, Murad MH, et al. Diabetes and pregnancy: an endocrine society clinical practice guideline. J Clin Endocrinol Metabol. 2013;98(11):4227-49. DOI: https://doi.org/10.1210/jc.2013-2465
Plows JF, Stanley JL, Baker PN, Reynolds CM, Vickers MH. The pathophysiology of gestational diabetes mellitus. Int J Molec Sci. 2018;19(11):3342. DOI: https://doi.org/10.3390/ijms19113342
Lappas M, Hiden U, Desoye G, Froehlich J, Mouzon SH, Jawerbaum A. The role of oxidative stress in the pathophysiology of gestational diabetes mellitus. Antioxid Redox Signal. 2011;15(12):3061-100. DOI: https://doi.org/10.1089/ars.2010.3765
Powe CE. Early pregnancy biochemical predictors of gestational diabetes mellitus. Curr Diabet Rep. 2017;17(2):12. DOI: https://doi.org/10.1007/s11892-017-0834-y
Iliodromiti S, Sassarini J, Kelsey TW, Lindsay RS, Sattar N, Nelson SM. Accuracy of circulating adiponectin for predicting gestational diabetes: a systematic review and meta-analysis. Diabetologia. 2016;59(4):692-9. DOI: https://doi.org/10.1007/s00125-015-3855-6
Alanbay I, Coksuer H, Ercan M, Keskin U, Karasahin E, Ozturk M, et al. Can serum gamma-glutamyltransferase levels be useful at diagnosing gestational diabetes mellitus?. Gynecolog Endocrinol. 2012;28(3):208-11. DOI: https://doi.org/10.3109/09513590.2011.588756
Magnusson MK, Mosher DF. Fibronectin: structure, assembly and cardiovascular implications. Arterioscl Thromb Vasc Biol. 1998;18(9):1363-70. DOI: https://doi.org/10.1161/01.ATV.18.9.1363
Ruoslahti E. Fibronectin and its receptors. Ann Rev Biochem. 1988;57(1):375-413. DOI: https://doi.org/10.1146/annurev.bi.57.070188.002111
Rasanen JP, Snyder CK, Rao PV, Mihalache R, Heinonen S, Gravett MG, et al. Glycosylated fibronectin as a first-trimester biomarker for prediction of gestational diabetes. Obstetr Gynecol. 2013;122(3):586-94. DOI: https://doi.org/10.1097/AOG.0b013e3182a0c88b
Alanen J, Appelblom H, Korpimaki T, Kouru H, Sairanen M, Gissler M, et al. Glycosylated fibronectin as a first trimester marker for gestational diabetes. Arch Gynecol Obstetr. 2020;302(4):853-60. DOI: https://doi.org/10.1007/s00404-020-05670-8
Huhn EA, Fischer T, Göbl CS, Bernasconi MT, Kreft M, Kunze M, et al. Screening of gestational diabetes mellitus in early pregnancy by oral glucose tolerance test and glycosylated fibronectin: study protocol for an international, prospective, multicentre cohort trial. BMJ open. 2016;6(10):e012115. DOI: https://doi.org/10.1136/bmjopen-2016-012115
Nagalla SR, Snyder CK, Michaels JE, Laughlin MJ, Roberts CT, Balaji M, et al. Maternal serum biomarkers for risk assessment in gestational diabetes. A potential universal screening test to predict GDM status. Ind J Endocrinol Metabol. 2015;19(1):155-9. DOI: https://doi.org/10.4103/2230-8210.140226
Mazumder T, Akter E, Rahman SM, Islam MT, Talukder MR. Prevalence and risk factors of gestational diabetes mellitus in Bangladesh: findings from demographic health survey 2017-2018. Int J Environm Res Publ Heal. 2022;19(5):2583. DOI: https://doi.org/10.3390/ijerph19052583
Zhao D, Shen L, Wei Y, Xie J, Chen S, Liang Y, et al. Identification of candidate biomarkers for the prediction of gestational diabetes mellitus in the early stages of pregnancy using iTRAQ quantitative proteomics. PROTEOMICS-Clin Applicat. 2017;11(7-8):1600152. DOI: https://doi.org/10.1002/prca.201600152
Shah A, Stotland NE, Cheng YW, Ramos GA, Caughey AB. The association between body mass index and gestational diabetes mellitus varies by race/ethnicity. Am J Perinatol. 2011;28(07):515-20. DOI: https://doi.org/10.1055/s-0031-1272968