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Nesfatin-1 and Vaspin as Potential Novel Biomarkers for the Prediction and Early Diagnosis of Gestational Diabetes Mellitus.

ABSTRACT: Gestational diabetes mellitus (GDM) is considered to be one of the most frequent medical complication observed among pregnant women. The role of adipokines in the pathogenesis of GDM remains strictly unknown. Different adipokines have been studied throughout gestation, and they have been proposed as biomarkers of GDM and other pregnancy-related complications; however, there is no biomarker reported for GDM screening at present. The aim of this study was to evaluate serum nesfatin-1 and vaspin levels in GDM and non-GDM women, to characterize the correlation between these adipokines, and to assess the potential role of circulating adipokines in the prediction of risk of gestational diabetes mellitus. Serum concentrations of nesfatin-1 and vaspin were measured in 153 women with GDM, and in 84 patients with uncomplicated pregnancy by enzyme-linked immunosorbent assay (ELISA) kits, according to the manufacturer's instructions. Circulating levels of nesfatin-1 and vaspin were significantly lower in the GDM group than in the control group. Nesfatin-1 levels were negatively correlated with vaspin levels. The results of this study point out the possible role of nesfatin-1 and vaspin as potential novel biomarkers for the prediction and early diagnosis of GDM. Further studies are necessary to evaluate the influence of nesfatin-1 and vaspin on glucose metabolism in the early stages of GDM.

SUBMITTER: Mierzynski R

PROVIDER: S-EPMC6337752 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Nesfatin-1 and Vaspin as Potential Novel Biomarkers for the Prediction and Early Diagnosis of Gestational Diabetes Mellitus.

Mierzyński Radzisław R Poniedziałek-Czajkowska Elżbieta E Dłuski Dominik D Patro-Małysza Jolanta J Kimber-Trojnar Żaneta Ż Majsterek Maciej M Leszczyńska-Gorzelak Bożena B

International journal of molecular sciences 20190104 1

Gestational diabetes mellitus (GDM) is considered to be one of the most frequent medical complication observed among pregnant women. The role of adipokines in the pathogenesis of GDM remains strictly unknown. Different adipokines have been studied throughout gestation, and they have been proposed as biomarkers of GDM and other pregnancy-related complications; however, there is no biomarker reported for GDM screening at present. The aim of this study was to evaluate serum nesfatin-1 and vaspin le ...[more]

PMID: 30621139

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Project description:IntroductionGestational 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.MethodsPlasma 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.ResultsWe 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 Hosmer-Lemeshow test = 0.897).ConclusionThe 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.

Project description:Introduction: Gestational diabetes (GDM), defined as hyperglycemia with onset or initial recognition during pregnancy, has a rising prevalence paralleling the rise in type 2 diabetes (T2DM) and obesity. GDM is associated with short-term and long-term consequences for both mother and child. Therefore, it is crucial we efficiently identify all cases and initiate early treatment, reducing fetal exposure to hyperglycemia and reducing GDM-related adverse pregnancy outcomes. For this reason, GDM screening is recommended as part of routine pregnancy care. The current screening method, the oral glucose tolerance test (OGTT), is a lengthy, cumbersome and inconvenient test with poor reproducibility. Newer biomarkers that do not necessitate a fasting sample are needed for the prompt diagnosis of GDM. The aim of this scoping review is to highlight and describe emerging protein biomarkers that fulfill these requirements for the diagnosis of GDM. Materials and Methods: This scoping review was conducted according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for scoping reviews using Cochrane Central Register of Controlled Trials (CENTRAL), the Cumulative Index to Nursing & Allied Health Literature (CINAHL), PubMed, Embase and Web of Science with a double screening and extraction process. The search included all articles published in the literature to July 2020. Results: Of the 3519 original database citations identified, 385 were eligible for full-text review. Of these, 332 (86.2%) were included in the scoping review providing a total of 589 biomarkers studied in relation to GDM diagnosis. Given the high number of biomarkers identified, three post hoc criteria were introduced to reduce the items set for discussion: we chose only protein biomarkers with at least five citations in the articles identified by our search and published in the years 2017-2020. When applied, these criteria identified a total of 15 biomarkers, which went forward for review and discussion. Conclusions: This review details protein biomarkers that have been studied to find a suitable test for GDM diagnosis with the potential to replace the OGTT used in current GDM screening protocols. Ongoing research efforts will continue to identify more accurate and practical biomarkers to take GDM screening and diagnosis into the 21st century.

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Nesfatin-1 and Vaspin as Potential Novel Biomarkers for the Prediction and Early Diagnosis of Gestational Diabetes Mellitus.

Publications

Nesfatin-1 and Vaspin as Potential Novel Biomarkers for the Prediction and Early Diagnosis of Gestational Diabetes Mellitus.

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