scholarly journals Metabolic profiling of pre-gestational and gestational diabetes mellitus identifies novel predictors of pre-term delivery

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Ilhame Diboun ◽  
Manjunath Ramanjaneya ◽  
Yasser Majeed ◽  
Lina Ahmed ◽  
Mohammed Bashir ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Pregnant Women ◽  
Metabolic Profiling ◽  
Generalized Linear Model ◽  
Regression Models ◽  
Second Trimester ◽  
Linear Regression Models ◽  
Term Delivery ◽  
Term Labor

Abstract Background Pregnant women with gestational diabetes mellitus (GDM) or type 2 diabetes mellitus (T2DM) are at increased risks of pre-term labor, hypertension and preeclampsia. In this study, metabolic profiling of blood samples collected from GDM, T2DM and control pregnant women was undertaken to identify potential diagnostic biomarkers in GDM/T2DM and compared to pregnancy outcome. Methods Sixty-seven pregnant women (21 controls, 32 GDM, 14 T2DM) in their second trimester underwent targeted metabolomics of plasma samples using tandem mass spectrometry with the Biocrates MxP® Quant 500 Kit. Linear regression models were used to identify the metabolic signature of GDM and T2DM, followed by generalized linear model (GLMNET) and Receiver Operating Characteristic (ROC) analysis to determine best predictors of GDM, T2DM and pre-term labor. Results The gestational age at delivery was 2 weeks earlier in T2DM compared to GDM and controls and correlated negatively with maternal HbA1C and systolic blood pressure and positively with serum albumin. Linear regression models revealed elevated glutamate and branched chain amino acids in GDM + T2DM group compared to controls. Regression models also revealed association of lower levels of triacylglycerols and diacylglycerols containing oleic and linoleic fatty acids with pre-term delivery. A generalized linear model ROC analyses revealed that that glutamate is the best predictors of GDM compared to controls (area under curve; AUC = 0.81). The model also revealed that phosphatidylcholine diacyl C40:2, arachidonic acid, glycochenodeoxycholic acid, and phosphatidylcholine acyl-alkyl C34:3 are the best predictors of GDM + T2DM compared to controls (AUC = 0.90). The model also revealed that the triacylglycerols C17:2/36:4 and C18:1/34:1 are the best predictors of pre-term delivery (≤ 37 weeks) (AUC = 0.84). Conclusions This study highlights the metabolite alterations in women in their second trimester with diabetes mellitus and identifies predictive indicators of pre-term delivery. Future studies to confirm these associations in other cohorts and investigate their functional relevance and potential utilization for targeted therapies are warranted.

scholarly journals Discovery of metabolic biomarkers for gestational diabetes mellitus in a Chinese population

2021 ◽  
Author(s):  
Wenqian Lu ◽  
Mingjuan Luo ◽  
Xiangnan Fang ◽  
Rong Zhang ◽  
Mengyang Tang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Pregnant Women ◽  
Regression Models ◽  
Second Trimester ◽  
Third Trimester ◽  
Logistic Regression Models ◽  
The Third ◽  
Clinical Indices

Abstract Background: Gestational diabetes mellitus (GDM), one of the most common pregnancy complications, can lead to morbidity and mortality in both the mother and the infant. Metabolomics has provided new insights into the pathology of GDM and systemic analysis of GDM with metabolites is required for providing more clues for GDM diagnosis and mechanism research. This study aims to reveal metabolic differences between normal pregnant women and GDM patients in the second- and third-trimester stages and to confirm the clinical relevance of these new findings.Methods: Metabolites were quantitated with the serum samples of 200 healthy pregnant women and 200 GDM women in the second trimester, 199 normal controls, and 199 GDM patients in the third trimester. Both function and pathway analyses were applied to explore biological roles involved in the two sets of metabolites. Then the trimester stage-specific GDM metabolite biomarkers were identified by combining machine learning approaches, and the logistic regression models were constructed to evaluate predictive efficiency. Finally, the weighted gene co-expression network analysis method was used to further capture the associations between metabolite modules with biomarkers and clinical indices. Results: This study revealed that 57 differentially expressed metabolites (DEMs) were discovered in the second-trimester group, among which the most significant one was 3-methyl-2-oxovaleric acid. Similarly, 72 DEMs were found in the third-trimester group, and the most significant metabolites were ketoleucine and alpha-ketoisovaleric acid. These DEMs were mainly involved in the metabolism pathway of amino acids, fatty acids and bile acids. The logistic regression models for selected metabolite biomarkers achieved the area under the curve values of 0.807 and 0.81 for the second- and third-trimester groups. Furthermore, significant associations were found between DEMs/biomarkers and GDM-related indices. Conclusions: Metabolic differences between healthy pregnant women and GDM patients were found. Associations between biomarkers and clinical indices were also investigated, which may provide insights into pathology of GDM.

scholarly journals Discovery of metabolic biomarkers for gestational diabetes mellitus in a Chinese population

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Wenqian Lu ◽  
Mingjuan Luo ◽  
Xiangnan Fang ◽  
Rong Zhang ◽  
Shanshan Li ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Pregnant Women ◽  
Regression Models ◽  
Second Trimester ◽  
Third Trimester ◽  
Logistic Regression Models ◽  
The Third ◽  
Clinical Indices

Abstract Background Gestational diabetes mellitus (GDM), one of the most common pregnancy complications, can lead to morbidity and mortality in both the mother and the infant. Metabolomics has provided new insights into the pathology of GDM and systemic analysis of GDM with metabolites is required for providing more clues for GDM diagnosis and mechanism research. This study aims to reveal metabolic differences between normal pregnant women and GDM patients in the second- and third-trimester stages and to confirm the clinical relevance of these new findings. Methods Metabolites were quantitated with the serum samples of 200 healthy pregnant women and 200 GDM women in the second trimester, 199 normal controls, and 199 GDM patients in the third trimester. Both function and pathway analyses were applied to explore biological roles involved in the two sets of metabolites. Then the trimester stage-specific GDM metabolite biomarkers were identified by combining machine learning approaches, and the logistic regression models were constructed to evaluate predictive efficiency. Finally, the weighted gene co-expression network analysis method was used to further capture the associations between metabolite modules with biomarkers and clinical indices. Results This study revealed that 57 differentially expressed metabolites (DEMs) were discovered in the second-trimester group, among which the most significant one was 3-methyl-2-oxovaleric acid. Similarly, 72 DEMs were found in the third-trimester group, and the most significant metabolites were ketoleucine and alpha-ketoisovaleric acid. These DEMs were mainly involved in the metabolism pathway of amino acids, fatty acids and bile acids. The logistic regression models for selected metabolite biomarkers achieved the area under the curve values of 0.807 and 0.81 for the second- and third-trimester groups. Furthermore, significant associations were found between DEMs/biomarkers and GDM-related indices. Conclusions Metabolic differences between healthy pregnant women and GDM patients were found. Associations between biomarkers and clinical indices were also investigated, which may provide insights into pathology of GDM.

Changes of Serum Sex Hormone-Binding Globulin, Homocysteine, and Hypersensitive CRP Levels during Pregnancy and Their Relationship with Gestational Diabetes Mellitus

2021 ◽  
pp. 1-7
Author(s):  
Wenhua Liu ◽  
Zheren Huang ◽  
Shanshan Tang ◽  
Zhifen Zhang ◽  
Qing Yu ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Pregnant Women ◽  
Serum Levels ◽  
First Trimester ◽  
Sex Hormone Binding Globulin ◽  
Control Group ◽  
Second Trimester ◽  
Hormone Binding ◽  
Hs Crp

<b><i>Background:</i></b> Inflammatory response state is related to the pathogenesis of gestational diabetes mellitus (GDM). <b><i>Objective:</i></b> To investigate the changes of serum sex hormone-binding globulin (SHBG), homocysteine (Hcy), and hypersensitive CRP (hs-CRP) levels during pregnancy and their relationship with GDM. <b><i>Methods:</i></b> The nested case-control study method was used. Sixty nonobese single pregnant women diagnosed with GDM were divided into the GDM group (GDM, <i>n</i> = 60), together with another 60 pregnant women with normal glucose tolerance who were matched in the same period and divided into the control group (control, <i>n</i> = 60). The serum Hcy, hs-CRP, and SHBG levels were measured. <b><i>Results:</i></b> The serum levels of Hcy and hs-CRP were significantly higher in the GDM group compared with the control group, and serum levels of SHBG was significantly lower in the GDM group compared with the control group at different stages of pregnancy. The serum levels of Hcy and hs-CRP in pregnant women increased with the increase of gestational age, and serum levels of SHBG decreased with the increase of gestational age. Increased Hcy and hs-CRP levels in the second trimester and decreased SHBG levels in the first trimester were related to GDM. The odds ratio (OR) and 95% confidence interval (CI) were as follows: OR: 4.5, 95% CI: 1.5–13.0; OR: 4.2, 95% CI: 1.5–10.1; and OR: 0.4, 95% CI: 0.3–0.7, respectively. <b><i>Conclusion:</i></b> Increased Hcy and hs-CRP in the second trimester and decreased SHBG in the first trimester were independent predictors of GDM, which provides a new idea for early prevention and treatment of GDM.

scholarly journals Cost effectiveness of different screening strategies for gestational diabetes mellitus screening: study protocol of a randomized community non-inferiority trial

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Fahimeh Ramezani Tehrani ◽  
Keyword(s):  
Diabetes Mellitus ◽  
Health Care ◽  
Cost Effectiveness ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Pregnant Women ◽  
Standard Care ◽  
First Trimester ◽  
Trial Registration ◽  
Second Trimester

Abstract Background There is lack of ideal and comprehensive economic evaluations of various GDM strategies. The aim of this study is to the compare efficacy and cost-effectiveness of five different methods of screening for gestational diabetes mellitus (GDM). Methods This study is a randomized community non-inferiority trial among 30,000 pregnant women in five different geographic regions of Iran, who were randomly assigned to one of the five GDM screening methods. All first trimester pregnant women, seeking prenatal care in governmental health care systems, who met our eligibility criteria were enrolled. The criteria suggested by the International-Association-of-Diabetes-in-Pregnancy-Study-Group, the most intensive approach, were used as reference. We used the non-inferiority approach to compare less intensive strategies to the reference one. Along with routine prenatal standard care, all participants were scheduled to have two phases of GDM screening in first and second-trimester of pregnancy, based on five different pre-specified protocols. The screening protocol included fasting plasma glucose in the first trimester and either a one step or a two-step screening method in the second trimester of pregnancy. Pregnant women were classified in three groups based on the results: diagnosed with preexisting pre-gestational overt diabetes; gestational diabetes and non-GDM women. Each group received packages for standard-care and all participants were followed till delivery; pregnancy outcomes, quality of life and cost of health care were recorded in detail using specific standardized questionnaires. Primary outcomes were defined as % birth-weight > 90th percentile and primary cesarean section. In addition, we assessed the direct health care direct and indirect costs. Results This study will enable us to compare the cost effectiveness of different GDM screening protocols and intervention intensity (low versus high). Conclusion Results which if needed, will also enable policy makers to optimize the national GMD strategy as a resource for enhancing GDM guidelines. Trial registration Name of the registry: Iranian Registry of Clinical Trials. Trial registration number: IRCT138707081281N1. Date of registration: 2017-02-15. URL of trial registry record: https://www.irct.ir/trial/518

scholarly journals FGF21 Serum Levels in the Early Second Trimester Are Positively Correlated With the Risk of Subsequent Gestational Diabetes Mellitus: A Propensity-Matched Nested Case-Control Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhiheng Wang ◽  
Min Yuan ◽  
Chengjie Xu ◽  
Yang Zhang ◽  
Chunmei Ying ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Pregnant Women ◽  
Case Control Study ◽  
Case Control ◽  
Fibroblast Growth Factor 21 ◽  
Second Trimester ◽  
Nested Case Control ◽  
Control Study

BackgroundAs an important endocrine hormone regulating glucose metabolism, fibroblast growth factor 21 (FGF21) is increased in individuals with gestational diabetes mellitus (GDM) after 24 gestational weeks. However, it is unknown whether the increase in FGF21 precedes the diagnosis of GDM.MethodsIn this nested case-control study, 133 pregnant women with GDM and 133 pregnant women with normal glucose tolerance (NGT) were identified through propensity score matching, and serum FGF21 levels were measured at 14 to 21 gestational weeks, before GDM is routinely identified. The differences in FGF21 levels were compared. The association between FGF21 and the occurrence of GDM was evaluated using logistic regression models with adjustment for confounders.ResultsThe serum FGF21 levels of the GDM group at 14 to 21 gestational weeks were significantly higher than those of the NGT group overall (P &lt; 0.001), with similar results observed between the corresponding BMI subgroups (P &lt; 0.05). The 2nd (OR 1.224, 95% CI 0.603–2.485), 3rd (OR 2.478, 1.229–5.000), and 4th (OR 3.419, 95% CI 1.626–7.188) FGF21 quartiles were associated with greater odds of GDM occurrence than the 1st quartile after multivariable adjustments.ConclusionsThe serum FGF21 levels in GDM groups increased in the early second trimester, regardless of whether participants were stratified according to BMI. After adjusting for confounding factors, the FGF21 levels in the highest quartile were associated with more than three times higher probability of the diagnosis of GDM in the pregnancy as compared to levels in the first quartile.

scholarly journals Higher mean amplitude of glycaemic excursion in the second trimester of pregnancy is associated with the subsequent development of gestational diabetes mellitus: an observational study

2021 ◽  
Author(s):  
Phaik Ling Quah ◽  
Kok Hian Tan ◽  
Nurul Razali ◽  
Nurul Sakinah Razali
Keyword(s):  
Diabetes Mellitus ◽  
Blood Glucose ◽  
Gestational Diabetes ◽  
Observational Study ◽  
Gestational Diabetes Mellitus ◽  
Pregnant Women ◽  
Subsequent Development ◽  
Mean Amplitude ◽  
First Trimester ◽  
Second Trimester

Objective: To examine glycaemic variability (GV) and glycaemic control (GC) parameters in early pregnancy with subsequent development of gestational diabetes mellitus (GDM). Design: Longitudinal observational study. Setting: Pregnant women from KK Women and Children’s Hospital in Singapore Participants: 51 study participants in the first trimester (9-13 weeks’ gestational), and 44 participants (18-23 weeks’ gestation) in the second trimester of pregnancy. Methods: Independent t-tests were used to examine the differences in the parameters between participants who developed GDM and those who did not. Main outcome measure: GDM was determined at 24-30 weeks’ gestation using oral glucose tolerance test (OGTT). GV parameters examined were, mean amplitude of glycaemic excursion (MAGE), standard deviation of blood glucose (SDBG) and mean of daily continuous 24 h blood glucose (MBG) and coefficient of variation (CV). GC parameters measured were, J-Index and % time spent in glucose target ranges. Results: In the second trimester of pregnancy, mean amplitude of glycaemic excursions (MAGE) was significantly higher in participants who subsequently developed GDM, compared to those who did not (mean (SD): 3.18(0.68) vs 2.60(0.53), p=0.02). Other study parameters measured in the second trimester of pregnancy were not significantly different between groups. There were no significant associations between all the GV and GC parameters determined from the CGM in the first trimester with subsequent development of GDM (p>0.05). Conclusion: MAGE is an important GV parameter associated to the development of subsequent GDM in pregnant women. The findings highlight the potential value of CGM in gestational glycaemic profiling.

scholarly journals Higher Parity, Pre-Pregnancy BMI and Rate of Gestational Weight Gain Are Associated with Gestational Diabetes Mellitus in Food Insecure Women

2021 ◽  
Vol 18 (5) ◽  
pp. 2694
Author(s):  
Heng Yaw Yong ◽  
Zalilah Mohd Shariff ◽  
Barakatun Nisak Mohd Yusof ◽  
Zulida Rejali ◽  
Yvonne Yee Siang Tee ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Weight Gain ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Food Insecurity ◽  
Pregnant Women ◽  
Household Food Insecurity ◽  
Second Trimester ◽  
Gestational Weight ◽  
Household Food

Food insecurity may exacerbate adverse maternal health outcomes during pregnancy, however, this association has not been well established, particularly in the context of developing countries. This study aimed to identify the associations between household food insecurity and gestational diabetes mellitus (GDM) risk among urban pregnant women. Household food insecurity was assessed using the translated 10-item Radimer/Cornell hunger scale. Logistic regression models were used to estimate the associations between food insecurity status and GDM risk. About 35.6% of women experienced food insecurity, with 25.2% reported household food insecurity, 8.0% individual food insecurity, and 2.4% child hunger. Food insecure women were at significantly higher risk of developing GDM compared to food secure women (AOR = 16.65, 95% CI = 6.17–24.98). The significant association between food insecurity and GDM risk was influenced by pre-pregnancy BMI, parity and rate of GWG at second trimester. Food insecure women with parity ≥ 2 (AOR = 4.21, 95% CI = 1.98–8.92), overweight/obese BMI prior to pregnancy (AOR = 12.11, 95% CI = 6.09–24.10) and excessive rate of GWG in the second trimester (AOR = 9.66, 95% CI = 4.27–21.83) were significantly more likely to develop GDM compared to food secure women. Food insecurity showed strong association with GDM risk in that the association was influenced by maternal biological and physical characteristics. Multipronged interventions may be necessary for food insecure pregnant women who are not only at risk of overweight/obesity prior to pregnancy but also may have excessive gestational weight gain, in order to effectively reduce GDM risk.

scholarly journals Diagnostic Accuracy of First and Early Second Trimester Multiple Biomarkers for Prediction of Gestational Diabetes Mellitus: A Multivariate Longitudinal Approach

2021 ◽  
Author(s):  
Elham Shaarbaf Eidgahi ◽  
Malihe Nasiri ◽  
Nourossadat Kariman ◽  
Nastaran Safavi Ardebili ◽  
Masoud Salehi ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Diagnostic Accuracy ◽  
Pregnant Women ◽  
Repeated Measures ◽  
Early Prediction ◽  
Second Trimester ◽  
Multiple Indicators ◽  
Concurrent Use

Abstract Background Gestational Diabetes Mellitus (GDM) is an underlying cause of maternal and newborn morbidity and mortality all around the world. Timely diagnosis of GDM plays an important role in reducing its adverse consequences and burden. This study aimed to determine diagnostic accuracy of multiple indicators in complete blood count (CBC) test for early prediction of GDM. Methods In this prospective cohort study, the data from 600 pregnant women was analyzed. In the study sample, the two-step approach was utilized for the diagnosis of GDM at 24–28 weeks of gestation. We also used the repeated measures of hemoglobin (Hb), hematocrit (Hct), fasting blood sugar (FBS) and red blood cell count (RBC) in the first and early second trimesters of pregnancy as the longitudinal multiple indicators for early diagnosis of GDM. The classification of pregnant women to GDM and non-GDM groups was performed using a statistical technique based on the random-effects modeling framework. Results Among the sample, 49 women (8.2%) were diagnosed with GDM. In the first and early second trimester of pregnancy, the mean HcT, Hb and FBS of women with GDM was significantly higher than non-GDMs (P < 0.001). The concurrent use of multiple longitudinal data from HcT, Hb, RBC and FBS in the first and early second trimester of pregnancy resulted in a sensitivity, specificity and area under the curve (AUC) of 87%, 70% and 83%, respectively, for early prediction of GDM. Conclusions In general, our findings showed that the concurrent use of repeated measures data on Hct, Hb, FBS and RBC in the first and early second trimester of pregnancy might be utilized as an acceptable tool to predict GDM in the earlier stages.

Sign in / Sign up

Export Citation Format

Share Document