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Adipokine levels during the first or early second trimester of pregnancy and subsequent risk of gestational diabetes mellitus: A systematic review.

ABSTRACT: We aimed to systematically review available literature linking adipokines to gestational diabetes mellitus (GDM) for a comprehensive understanding of the roles of adipokines in the development of GDM.We searched PubMed/MEDLINE and EMBASE databases for published studies on adipokines and GDM through October 21, 2014. We included articles if they had a prospective study design (i.e., blood samples for adipokines measurement were collected before GDM diagnosis). Random-effects models were used to pool the weighted mean differences comparing levels of adipokines between GDM cases and non-GDM controls.Of 1523 potentially relevant articles, we included 25 prospective studies relating adipokines to incident GDM. Our meta-analysis of nine prospective studies on adiponectin and eight prospective studies on leptin indicated that adiponectin levels in the first or early second trimester of pregnancy were 2.25 ?g/ml lower (95% CI: 1.75-2.75), whereas leptin levels were 7.25 ng/ml higher (95% CI 3.27-11.22), among women who later developed GDM than women who did not. Prospective data were sparse and findings were inconsistent for visfatin, retinol binding protein (RBP-4), resistin, tumor necrosis factor-? (TNF-?), interleukin-6 (IL-6), and vaspin. We did not identify prospective studies for several novel adipokines, including chemerin, apelin, omentin, or adipocyte fatty acid-binding protein. Moreover, no published prospective studies with longitudinal assessment of adipokines and incident GDM were identified.Adiponectin levels in the first or second trimester of pregnancy are lower among pregnant women who later develop GDM than non-GDM women, whereas leptin levels are higher. Well-designed prospective studies with longitudinal assessment of adipokines during pregnancy are needed to understand the trajectories and dynamic associations of adipokines with GDM risk.

SUBMITTER: Bao W

PROVIDER: S-EPMC4625979 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Adipokine levels during the first or early second trimester of pregnancy and subsequent risk of gestational diabetes mellitus: A systematic review.

Bao Wei W Baecker Aileen A Song Yiqing Y Kiely Michele M Liu Simin S Zhang Cuilin C

Metabolism: clinical and experimental 20150129 6

<h4>Objective</h4>We aimed to systematically review available literature linking adipokines to gestational diabetes mellitus (GDM) for a comprehensive understanding of the roles of adipokines in the development of GDM.<h4>Methods</h4>We searched PubMed/MEDLINE and EMBASE databases for published studies on adipokines and GDM through October 21, 2014. We included articles if they had a prospective study design (i.e., blood samples for adipokines measurement were collected before GDM diagnosis). Ra ...[more]

PMID: 25749468

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Project description:BackgroundThe aim of this study was to evaluate whether soluble frizzled-related protein 4 (sFRP4) concentration in the first trimester of pregnancy is individually, or in combination with Leptin, Chemerin and/or Adiponectin, associated with the development of gestational diabetes (GDM).MethodsIn a nested case-control study, 50 women with GDM who spontaneously conceived and delivered a live-born infant were matched with a total of 100 uncomplicated singleton control pregnancies based on body mass index (± 2 kg/m2), gestational age at sampling (exact day) and maternal age (± 2 years). In serum samples, obtained between 70-90 days gestational age, sFRP4, Chemerin, Leptin and Adiponectin concentrations were determined by ELISA. Statistical comparisons were performed using univariate and multi-variate logistic regression analysis after logarithmic transformation of the concentrations. Discrimination of the models was assessed by the area under the curve (AUC).ResultsFirst trimester sFRP4 concentrations were significantly increased in GDM cases (2.04 vs 1.93 ng/ml; p<0.05), just as Chemerin (3.19 vs 3.15 ng/ml; p<0.05) and Leptin (1.44 vs 1.32 ng/ml; p<0.01). Adiponectin concentrations were significantly decreased (2.83 vs 2.94 ng/ml; p<0.01) in GDM cases. Further analysis only showed a weak, though significant, correlation of sFRP4 with Chemerin (R2 = 0.124; p<0.001) and Leptin (R2 = 0.145; p<0.001), and Chemerin with Leptin (R2 = 0.282; p<0.001) in the control group. In a multivariate logistic regression model of these four markers, only Adiponectin showed to be significantly associated with GDM (odds ratio 0.12, 95%CI 0.02-0.68). The AUC of this model was 0.699 (95%CI 0.605-0.793).ConclusionIn the first trimester of pregnancy, a multi-marker model with sFRP4, Leptin, Chemerin and Adiponectin is associated with the development of GDM. Therefore, this panel seems to be an interesting candidate to further evaluate for prediction of GDM in a prospective study.

Project description:PurposeTo investigate and identify first-trimester fasting plasma glucose (FPG) is related to gestational diabetes mellitus (GDM) and other adverse pregnancy outcomes in Shenzhen population.MethodsWe used data of 48,444 pregnant women that had been retrospectively collected between 2017 and 2019. Logistic regression analysis was used to evaluated the associations between first-trimester FPG and GDM and adverse pregnancy outcomes, and used to construct a nomogram model for predicting the risk of GDM. The performance of the nomogram was evaluated by using ROC and calibration curves. Decision curve analysis (DCA) was used to determine the clinical usefulness of the first-trimester FPG by quantifying the net benefits at different threshold probabilities.ResultsThe mean first-trimester FPG was 4.62 ± 0.42 mmol/L. A total of 6998 (14.4%) pregnancies developed GDM.489(1.01%) pregnancies developed polyhydramnios, the prevalence rates of gestational hypertensive disorder (GHD), cesarean section, primary cesarean section, preterm delivery before 37 weeks (PD) and dystocia was 1130 (2.33%), 20,426 (42.16%), 7237 (14.94%), 2386 (4.93%), and 1865 (3.85%), respectively. 4233 (8.74%) of the newborns were LGA, and the number of macrosomia was 2272 (4.69%), LBW was 1701 (3.51%) and 5084 (10.49%) newborns had admission to the ICU, which all showed significances between GDM and non-GDM groups (all P < 0.05). The univariate analysis showed that first-trimester FPG was strongly associated with risks of outcomes including GDM, cesarean section, macrosomia, GHD, primary cesarean section, and LGA (all OR > 1, all P < 0.05), furthermore, the risks of GDM, primary cesarean section, and LGA was increasing with first-trimester FPG as early as it was at 4.19-4.63 mmol/L. The multivariable analysis showed that the risks of GDM (ORs for FPG 4.19-4.63, 4.63-5.11 and 5.11-7.0 mmol/L were 1.137, 1.592, and 4.031, respectively, all P < 0.05) increased as early as first-trimester FPG was at 4.19-4.63 mmol/L, and first-trimester FPG which was also associated with the risks of cesarean section, macrosomia and LGA (OR for FPG 5.11-7.0 mmol/L of cesarean section: 1.128; OR for FPG 5.11-7.0 mmol/L of macrosomia: 1.561; OR for FPG 4.63-5.11 and 5.11-7.0 mmol/L of LGA: 1.149 and 1.426, respectively, all P < 0.05) and with its increasing, the risks of LGA increased. Furthermore, the nomogram had a C-indices 0.771(95% CI: 0.763~0.779) and 0.770(95% CI:0.758~0.781) in training and testing validation respectively, which showed an acceptable consistency between the observed, validation and nomogram-predicted probabilities, the DAC curve analysis indicated that the nomogram had important clinical application value for GDM risk prediction.ConclusionsFPG in the first trimester was an independent risk factor for GDM which can be used as a screening test for identifying pregnancies at risk of GDM and adverse pregnancy outcomes.

Project description:BackgroundImprovement in the accuracy of identifying women who are at risk to develop gestational diabetes mellitus (GDM) is warranted, since timely diagnosis and treatment improves the outcomes of this common pregnancy disorder. Although prognostic models for GDM are externally validated and outperform current risk factor based selective approaches, there is little known about the impact of such models in day-to-day obstetric care.MethodsA prognostic model was implemented as a directive clinical prediction rule, classifying women as low- or high-risk for GDM, with subsequent distinctive care pathways including selective midpregnancy testing for GDM in high-risk women in a prospective multicenter birth cohort comprising 1073 pregnant women without pre-existing diabetes and 60 obstetric healthcare professionals included in nine independent midwifery practices and three hospitals in the Netherlands (effectiveness-implementation hybrid type 2 study). Model performance (c-statistic) and implementation outcomes (acceptability, adoption, appropriateness, feasibility, fidelity, penetration, sustainability) were evaluated after 6 months by indicators and implementation instruments (NoMAD; MIDI).ResultsThe adherence to the prognostic model (c-statistic 0.85 (95%CI 0.81-0.90)) was 95% (n = 1021). Healthcare professionals scored 3.7 (IQR 3.3-4.0) on implementation instruments on a 5-point Likert scale. Important facilitators were knowledge, willingness and confidence to use the model, client cooperation and opportunities for reconfiguration. Identified barriers mostly related to operational and organizational issues. Regardless of risk-status, pregnant women appreciated first-trimester information on GDM risk-status and lifestyle advice to achieve risk reduction, respectively 89% (n = 556) and 90% (n = 564)).ConclusionsThe prognostic model was successfully implemented and well received by healthcare professionals and pregnant women. Prognostic models should be recommended for adoption in guidelines.

Project description:Background: Dysbiosis of human gut microbiota is associated with a wide range of metabolic disorders, including gestational diabetes mellitus (GDM). Yet whether gut microbiota dysbiosis participates in the etiology of GDM remains largely unknown. Objectives: Our study was initiated to determine whether the alternations in gut microbial composition during early pregnancy linked to the later development of GDM, and explore the feasibility of microbial biomarkers for the early prediction of GDM. Study design: This nested case-control study was based upon an early pregnancy follow-up cohort (ChiCTR1900020652). Gut microbiota profiles of 98 subjects with GDM and 98 matched healthy controls during the early pregnancy (10-15 weeks) were assessed via 16S rRNA gene amplicon sequencing of V4 region. The data set was randomly split into a discovery set and a validation set, the former was used to analyze the differences between GDM cases and controls in gut microbial composition and functional annotation, and to establish an early identification model of GDM, then the performance of the model was verified by the external validation set. Results: Bioinformatic analyses revealed changes to gut microbial composition with significant differences in relative abundance between the groups. Specifically, Eisenbergiella, Tyzzerella 4, and Lachnospiraceae NK4A136 were enriched in the GDM group, whereas Parabacteroides, Megasphaera, Eubacterium eligens group, etc. remained dominant in the controls. Correlation analysis revealed that GDM-enriched genera Eisenbergiella and Tyzzerella 4 were positively correlated with fasting blood glucose levels, while three control-enriched genera (Parabacteroides, Parasutterella, and Ruminococcaceae UCG 002) were the opposite. Further, GDM functional annotation modules revealed enrichment of modules for sphingolipid metabolism, starch and sucrose metabolism, etc., while lysine biosynthesis and nitrogen metabolism were reduced. Finally, five genera and two clinical indices were included in the linear discriminant analysis model for the prediction of GDM; the areas under receiver operating characteristic curves of the training and validation sets were 0.736 (95% confidence interval: 0.663-0.808) and 0.696 (0.575-0.818), respectively. Conclusions: Gut bacterial dysbiosis in early pregnancy was found to be associated with the later development of GDM, and gut microbiota-targeted biomarkers might be utilized as potential predictors of GDM.

Dataset Information

Adipokine levels during the first or early second trimester of pregnancy and subsequent risk of gestational diabetes mellitus: A systematic review.

Publications

Adipokine levels during the first or early second trimester of pregnancy and subsequent risk of gestational diabetes mellitus: A systematic review.

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