Diabetes & Metabolism Journal

Original Article

Genetics
Identification and Potential Clinical Utility of Common Genetic Variants in Gestational Diabetes among Chinese Pregnant Women: Claudia Ha-ting Tam, Ying Wang, Chi Chiu Wang, Lai Yuk Yuen, Cadmon King-poo Lim, Junhong Leng, Ling Wu, Alex Chi-wai Ng, Yong Hou, Kit Ying Tsoi, Hui Wang, Risa Ozaki, Albert Martin Li, Qingqing Wang, Juliana Chung-ngor Chan, Yan Chou Ye, Wing Hung Tam, Xilin Yang, Ronald Ching-wan Ma; Received March 20, 2024 Accepted June 17, 2024 Published online September 20, 2024; DOI: https://doi.org/10.4093/dmj.2024.0139 [Epub ahead of print]

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Abstract PDF Supplementary Material PubReader ePub: Background
The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications.
Methods
We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants.
Results
Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; P_meta=7.6×10^-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; P_meta=3.1×10^-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals.
Conclusion
Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Review

Metabolic Risk/Epidemiology
Gestational Diabetes Mellitus and Its Implications across the Life Span: Brandy Wicklow, Ravi Retnakaran; Diabetes Metab J. 2023;47(3):333-344. Published online February 8, 2023; DOI: https://doi.org/10.4093/dmj.2022.0348

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Gestational diabetes mellitus (GDM) has historically been perceived as a medical complication of pregnancy that also serves as a harbinger of maternal risk of developing type 2 diabetes mellitus (T2DM) in the future. In recent decades, a growing body of evidence has detailed additional lifelong implications that extend beyond T2DM, including an elevated risk of ultimately developing cardiovascular disease. Furthermore, the risk factors that mediate this lifetime cardiovascular risk are evident not only after delivery but are present even before the pregnancy in which GDM is first diagnosed. The concept thus emerging from these data is that the diagnosis of GDM enables the identification of women who are already on an enhanced track of cardiometabolic risk that starts early in life. Studies of the offspring of pregnancies complicated by diabetes now suggest that the earliest underpinnings of this cardiometabolic risk profile may be determined in utero and may first manifest clinically in childhood. Accordingly, from this perspective, GDM is now seen as a chronic metabolic disorder that holds implications across the life span of both mother and child.

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Inflammation and decreased cardiovagal modulation are linked to stress and depression at 36th week of pregnancy in gestational diabetes mellitus
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Women with gestational diabetes mellitus, controlled for plasma glucose level, exhibit maternal and fetal dyslipidaemia that may warrant treatment
Barbara J. Meyer, Colin Cortie, Marloes Dekker-Nitert, Helen L. Barrett, Dilys J. Freeman
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Original Articles

Basic Research
Long Non-Coding RNA TUG1 Attenuates Insulin Resistance in Mice with Gestational Diabetes Mellitus via Regulation of the MicroRNA-328-3p/SREBP-2/ERK Axis: Xuwen Tang, Qingxin Qin, Wenjing Xu, Xuezhen Zhang; Diabetes Metab J. 2023;47(2):267-286. Published online January 19, 2023; DOI: https://doi.org/10.4093/dmj.2021.0216

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Background
Long non-coding RNAs (lncRNAs) have been illustrated to contribute to the development of gestational diabetes mellitus (GDM). In the present study, we aimed to elucidate how lncRNA taurine upregulated gene 1 (TUG1) influences insulin resistance (IR) in a high-fat diet (HFD)-induced mouse model of GDM.
Methods
We initially developed a mouse model of HFD-induced GDM, from which islet tissues were collected for RNA and protein extraction. Interactions among lncRNA TUG1/microRNA (miR)-328-3p/sterol regulatory element binding protein 2 (SREBP-2) were assessed by dual-luciferase reporter assay. Fasting blood glucose (FBG), fasting insulin (FINS), homeostasis model assessment of insulin resistance (HOMA-IR), HOMA pancreatic β-cell function (HOMA-β), insulin sensitivity index for oral glucose tolerance tests (ISOGTT) and insulinogenic index (IGI) levels in mouse serum were measured through conducting gain- and loss-of-function experiments.
Results
Abundant expression of miR-328 and deficient expression of lncRNA TUG1 and SREBP-2 were characterized in the islet tissues of mice with HFD-induced GDM. LncRNA TUG1 competitively bound to miR-328-3p, which specifically targeted SREBP-2. Either depletion of miR-328-3p or restoration of lncRNA TUG1 and SREBP-2 reduced the FBG, FINS, HOMA-β, and HOMA-IR levels while increasing ISOGTT and IGI levels, promoting the expression of the extracellular signal-regulated kinase (ERK) signaling pathway-related genes, and inhibiting apoptosis of islet cells in GDM mice. Upregulation miR-328-3p reversed the alleviative effects of SREBP-2 and lncRNA TUG1 on IR.
Conclusion
Our study provides evidence that the lncRNA TUG1 may prevent IR following GDM through competitively binding to miR-328-3p and promoting the SREBP-2-mediated ERK signaling pathway inactivation.

Citations

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The role of ncRNA regulatory mechanisms in diseases—case on gestational diabetes
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Others
Influence of Maternal Diabetes on the Risk of Neurodevelopmental Disorders in Offspring in the Prenatal and Postnatal Periods: Verónica Perea, Xavier Urquizu, Maite Valverde, Marina Macias, Anna Carmona, Esther Esteve, Gemma Escribano, Nuria Pons, Oriol Giménez, Teresa Gironés, Andreu Simó-Servat, Andrea Domenech, Núria Alonso-Carril, Carme Quirós, Antonio J. Amor, Eva López, Maria José Barahona; Diabetes Metab J. 2022;46(6):912-922. Published online April 29, 2022; DOI: https://doi.org/10.4093/dmj.2021.0340

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Background
This study aimed to evaluate the influence of maternal diabetes in the risk of neurodevelopmental disorders in offspring in the prenatal and postnatal periods.
Methods
This cohort study included singleton gestational diabetes mellitus (GDM) pregnancies >22 weeks’ gestation with live newborns between 1991 and 2008. The control group was randomly selected and matched (1:2) for maternal age, weeks of gestation and birth year. Cox regression models estimated the effect of GDM on the risk of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and maternal type 2 diabetes mellitus (T2DM). Moreover, interaction between maternal T2DM and GDM-ADHD relationship was evaluated.
Results
Children (n=3,123) were included (1,073 GDM; 2,050 control group). The median follow-up was 18.2 years (interquartile range, 14.2 to 22.3) (n=323 with ADHD, n=36 with ASD, and n=275 from women who developed T2DM). GDM exposure was associated with ADHD (hazard ratio [HR]_crude, 1.67; 95% confidence interval [CI], 1.33 to 2.07) (HR_adjusted, 1.64; 95% CI, 1.31 to 2.05). This association remained significant regardless of the treatment (diet or insulin) and diagnosis after 26 weeks of gestation. Children of mothers who developed T2DM presented higher rates of ADHD (14.2 vs. 10%, P=0.029). However, no interaction was found when T2DM was included in the GDM and ADHD models (P>0.05). GDM was not associated with an increased risk of ASD (HR_adjusted, 1.46; 95% CI, 0.74 to 2.84).
Conclusion
Prenatal exposure to GDM increases the risk of ADHD in offspring, regardless of GDM treatment complexity. However, postnatal exposure to maternal T2DM was not related to the development of ADHD.

Citations

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Effects of a Diabetic Microenvironment on Neurodegeneration: Special Focus on Neurological Cells
Vishal Chavda, Dhananjay Yadav, Snehal Patel, Minseok Song
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Understanding the link between different types of maternal diabetes and the onset of autism spectrum disorders
Wenyu Shao, Yichun Su, Jiayin Liu, Yulong Liu, Jinghui Zhao, Xiaotang Fan
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Filipa I. Baptista, António F. Ambrósio
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Yunfeng Yu, Xinyu Yang, Gang Hu, Keke Tong, Jingyi Wu, Rong Yu
Frontiers in Endocrinology.2024;[Epub] CrossRef
Maternal Diabetes Deregulates the Expression of Mecp2 via miR-26b-5p in Mouse Embryonic Neural Stem Cells
Sukanya Shyamasundar, Seshadri Ramya, Deepika Kandilya, Dinesh Kumar Srinivasan, Boon Huat Bay, Suraiya Anjum Ansari, S Thameem Dheen
Cells.2023; 12(11): 1516. CrossRef
Evaluating the prospects of using gestational diabetes mellitus model to find means of pharmacological correction of the disorders in rat offspring
A. S. Solomina, A. V. Rodina, K. S. Kachalov, A. D. Zakharov, A. D. Durnev
Pharmacokinetics and Pharmacodynamics.2023; (2): 45. CrossRef
Hair and cord blood element levels and their relationship with air pollution, dietary intake, gestational diabetes mellitus, and infant neurodevelopment
Yin-Yin Xia, Jamie V. de Seymour, Xiao-Jia Yang, Lin-Wei Zhou, Yue Liu, Yang Yang, Kathryn L. Beck, Cathryn A. Conlon, Toby Mansell, Boris Novakovic, Richard Saffery, Ting-Li Han, Hua Zhang, Philip N. Baker
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Role of Excessive Weight Gain During Gestation in the Risk of ADHD in Offspring of Women With Gestational Diabetes
Verónica Perea, Andreu Simó-Servat, Carmen Quirós, Nuria Alonso-Carril, Maite Valverde, Xavier Urquizu, Antonio J Amor, Eva López, Maria-José Barahona
The Journal of Clinical Endocrinology & Metabolism.2022; 107(10): e4203. CrossRef

Metabolic Risk/Epidemiology
Higher Muscle Mass Protects Women with Gestational Diabetes Mellitus from Progression to Type 2 Diabetes Mellitus: Yujin Shin, Joon Ho Moon, Tae Jung Oh, Chang Ho Ahn, Jae Hoon Moon, Sung Hee Choi, Hak Chul Jang; Diabetes Metab J. 2022;46(6):890-900. Published online April 28, 2022; DOI: https://doi.org/10.4093/dmj.2021.0334

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Background
We evaluated whether postpartum muscle mass affects the risk of type 2 diabetes mellitus (T2DM) in Korean women with gestational diabetes mellitus (GDM).
Methods
A total of 305 women with GDM (mean age, 34.9 years) was prospectively evaluated for incident prediabetes and T2DM from 2 months after delivery and annually thereafter. Appendicular skeletal muscle mass (ASM) was assessed with bioelectrical impedance analysis at the initial postpartum visit, and ASM, either divided by body mass index (BMI) or squared height, and the absolute ASM were used as muscle mass indices. The risk of incident prediabetes and T2DM was assessed according to tertiles of these indices using a logistic regression model.
Results
After a mean follow-up duration of 3.3 years, the highest ASM/BMI tertile group had a 61% lower risk of incident prediabetes and T2DM compared to the lowest tertile group, and this remained significant after we adjusted for covariates (adjusted odds ratio, 0.37; 95% confidence interval [CI], 0.15 to 0.92; P=0.032). Equivalent findings were observed in normal weight women (BMI <23 kg/m²), but this association was not significant for overweight women (BMI ≥23 kg/m²). Absolute ASM or ASM/height² was not associated with the risk of postpartum T2DM.
Conclusion
A higher muscle mass, as defined by the ASM/BMI index, was associated with a lower risk of postpartum prediabetes and T2DM in Korean women with GDM.

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Low muscle mass index is associated with type 2 diabetes risk in a Latin-American population: a cross-sectional study
Rosario Suárez, Celina Andrade, Estefania Bautista-Valarezo, Yoredy Sarmiento-Andrade, Andri Matos, Oliver Jimenez, Martha Montalvan, Sebastián Chapela
Frontiers in Nutrition.2024;[Epub] CrossRef
More appendicular lean mass relative to body mass index is associated with lower incident diabetes in middle-aged adults in the CARDIA study
Melanie S. Haines, Aaron Leong, Bianca C. Porneala, Victor W. Zhong, Cora E. Lewis, Pamela J. Schreiner, Karen K. Miller, James B. Meigs, Mercedes R. Carnethon
Nutrition, Metabolism and Cardiovascular Diseases.2023; 33(1): 105. CrossRef
The Association of the Triglyceride and Muscle to Fat Ratio During Early Pregnancy with the Development of Gestational Diabetes Mellitus
Fang Wang, Yuan-Yuan Bao, Kang Yu
Diabetes, Metabolic Syndrome and Obesity.2023; Volume 16: 3187. CrossRef
Correlation of body composition in early pregnancy on gestational diabetes mellitus under different body weights before pregnancy
Li Xintong, Xu Dongmei, Zhang Li, Cao Ruimin, Hao Yide, Cui Lingling, Chen Tingting, Guo Yingying, Li Jiaxin
Frontiers in Endocrinology.2022;[Epub] CrossRef

Metabolic Risk/Epidemiology
Effect of Different Types of Diagnostic Criteria for Gestational Diabetes Mellitus on Adverse Neonatal Outcomes: A Systematic Review, Meta-Analysis, and Meta-Regression: Fahimeh Ramezani Tehrani, Marzieh Saei Ghare Naz, Razieh Bidhendi-Yarandi, Samira Behboudi-Gandevani; Diabetes Metab J. 2022;46(4):605-619. Published online March 8, 2022; DOI: https://doi.org/10.4093/dmj.2021.0178

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Background
Evidence supporting various diagnostic criteria for diagnose gestational diabetes mellitus (GDM) are consensus-based, needs for additional evidence related to outcomes. Therefore, the aim of this systematic-review and meta-analysis was to assess the impact of different GDM diagnostic-criteria on the risk of adverse-neonatal-outcomes.
Methods
Electronic databases including Scopus, PubMed, and Web of Sciences were searched to retrieve English original, population-based studies with the universal GDM screening approach, up to January-2020. GDM diagnostic criteria were classified in seven groups and International Association of the Diabetes and Pregnancy Study Groups (IADPSG) was considered as reference one. We used the Mantel–Haenszel method to calculate the pooled odds of events. The possibility of publication bias was examined by Begg’s test.
Results
A total of 55 population-based studies consisting of 1,604,391 pregnant women with GDM and 7,770,855 non-GDM counterparts were included. Results showed that in all diagnostic-criteria subgroups, the risk of adverse neonatal outcomes including macrosomia, hyperbilirubinemia, respiratory distress syndrome, neonatal hypoglycemia, neonatal intensive care unit admission, preterm birth, and birth-trauma were significantly higher than the non-GDM counterparts were significantly higher than non-GDM counterparts. Meta-regression analysis revealed that the magnitude of neonatal risks in all diagnostic-criteria subgroups are similar.
Conclusion
Our results showed that the risk of adverse-neonatal-outcome increased among women with GDM, but the magnitude of risk was not different among those women who were diagnosed through more or less intensive strategies. These findings may help health-care-providers and policy-makers to select the most cost-effective approach for the screening of GDM among pregnant women.

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Review

Metabolic Risk/Epidemiology
Gestational Diabetes Mellitus: Diagnostic Approaches and Maternal-Offspring Complications: Joon Ho Moon, Hak Chul Jang; Diabetes Metab J. 2022;46(1):3-14. Published online January 27, 2022; DOI: https://doi.org/10.4093/dmj.2021.0335

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Gestational diabetes mellitus (GDM) is the most common complication during pregnancy and is defined as any degree of glucose intolerance with onset or first recognition during pregnancy. GDM is associated with adverse pregnancy outcomes and long-term offspring and maternal complications. For GDM screening and diagnosis, a two-step approach (1-hour 50 g glucose challenge test followed by 3-hour 100 g oral glucose tolerance test) has been widely used. After the Hyperglycemia and Adverse Pregnancy Outcome study implemented a 75 g oral glucose tolerance test in all pregnant women, a one-step approach was recommended as an option for the diagnosis of GDM after 2010. The one-step approach has more than doubled the incidence of GDM, but its clinical benefit in reducing adverse pregnancy outcomes remains controversial. Long-term complications of mothers with GDM include type 2 diabetes mellitus and cardiovascular disease, and complications of their offspring include childhood obesity and glucose intolerance. The diagnostic criteria of GDM should properly classify women at risk for adverse pregnancy outcomes and long-term complications. The present review summarizes the strengths and weaknesses of the one-step and two-step approaches for the diagnosis of GDM based on recent randomized controlled trials and observational studies. We also describe the long-term maternal and offspring complications of GDM.

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Short Communication

Metabolic Risk/Epidemiology
Influence of Pre-Pregnancy Underweight Body Mass Index on Fetal Abdominal Circumference, Estimated Weight, and Pregnancy Outcomes in Gestational Diabetes Mellitus: Minji Kim, Kyu-Yeon Hur, Suk-Joo Choi, Soo-Young Oh, Cheong-Rae Roh; Diabetes Metab J. 2022;46(3):499-505. Published online January 24, 2022; DOI: https://doi.org/10.4093/dmj.2021.0059

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Abstract PDF Supplementary Material PubReader ePub

This study aimed to determine the influence of pre-pregnancy body mass index on pregnancy outcomes in gestational diabetes mellitus (GDM), comparing underweight patients with GDM with normal weight patients with GDM. Maternal baseline characteristics, ultrasonographic results, and pregnancy and neonatal outcomes were reviewed in 946 women with GDM with singleton pregnancies. Underweight patients with GDM showed a benign course in most aspects during pregnancy, except for developing a higher risk of giving birth to small for gestational age neonates. Underweight women with GDM required less insulin treatment, had a higher rate of vaginal delivery, and had a lower rate of cesarean delivery. In addition, their neonates were more likely to have fetal abdominal circumference and estimated fetal weight below the 10th percentile both at the time of GDM diagnosis and before delivery. Notably, their risk for preeclampsia and macrosomia were lower. Collectively, our data suggest that underweight women with GDM may require a different approach in terms of diagnosis and management throughout their pregnancy.

Citations

Citations to this article as recorded by

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Original Articles

Metabolic Risk/Epidemiology
Postprandial Free Fatty Acids at Mid-Pregnancy Increase the Risk of Large-for-Gestational-Age Newborns in Women with Gestational Diabetes Mellitus: So-Yeon Kim, Young Shin Song, Soo-Kyung Kim, Yong-Wook Cho, Kyung-Soo Kim; Diabetes Metab J. 2022;46(1):140-148. Published online August 9, 2021; DOI: https://doi.org/10.4093/dmj.2021.0023

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Graphical Abstract Abstract PDF Supplementary Material PubReader ePub

Background
To investigate the association between free fatty acid (FFA) level at mid-pregnancy and large-for-gestational-age (LGA) newborns in women with gestational diabetes mellitus (GDM).
Methods
We enrolled 710 pregnant women diagnosed with GDM from February 2009 to October 2016. GDM was diagnosed by a ‘two-step’ approach with Carpenter and Coustan criteria. We measured plasma lipid profiles including fasting and 2-hour postprandial FFA (2h-FFA) levels at mid-pregnancy. LGA was defined if birthweights of newborns were above the 90th percentile for their gestational age.
Results
Mean age of pregnant women in this study was 33.1 years. Mean pre-pregnancy body mass index (BMI) was 22.4 kg/m². The prevalence of LGA was 8.3% (n=59). Levels of 2h-FFA were higher in women who delivered LGA newborns than in those who delivered non-LGA newborns (416.7 μEq/L vs. 352.5 μEq/L, P=0.006). However, fasting FFA was not significantly different between the two groups. The prevalence of delivering LGA newborns was increased with increasing tertile of 2h-FFA (T1, 4.3%; T2, 9.8%; T3, 10.7%; P for trend <0.05). After adjustment for maternal age, pre-pregnancy BMI, and fasting plasma glucose, the highest tertile of 2h-FFA was 2.38 times (95% confidence interval, 1.11 to 5.13) more likely to have LGA newborns than the lowest tertile. However, there was no significant difference between groups according to fasting FFA tertiles.
Conclusion
In women with GDM, a high 2h-FFA level (but not fasting FFA) at mid-pregnancy is associated with an increasing risk of delivering LGA newborns.

Citations

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Advances in free fatty acid profiles in gestational diabetes mellitus
Haoyi Du, Danyang Li, Laura Monjowa Molive, Na Wu
Journal of Translational Medicine.2024;[Epub] CrossRef
Modulation of gut microbiota and lipid metabolism in rats fed high-fat diets by Ganoderma lucidum triterpenoids
Aijun Tong, Weihao Wu, Zhengxin Chen, Jiahui Wen, Ruibo Jia, Bin Liu, Hui Cao, Chao Zhao
Current Research in Food Science.2023; 6: 100427. CrossRef
Fetal Abdominal Obesity Detected at 24 to 28 Weeks of Gestation Persists until Delivery Despite Management of Gestational Diabetes Mellitus (Diabetes Metab J 2021;45:547-57)
Wonjin Kim, Soo Kyung Park, Yoo Lee Kim
Diabetes & Metabolism Journal.2021; 45(6): 970. CrossRef

Metabolic Risk/Epidemiology
Fetal Abdominal Obesity Detected At 24 to 28 Weeks of Gestation Persists Until Delivery Despite Management of Gestational Diabetes Mellitus: Wonjin Kim, Soo Kyung Park, Yoo Lee Kim; Diabetes Metab J. 2021;45(4):547-557. Published online March 5, 2021; DOI: https://doi.org/10.4093/dmj.2020.0078

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Background
Fetal abdominal obesity (FAO) has been reported to be affected at gestational diabetes mellitus (GDM) diagnosis at 24 to 28 weeks of gestation in older and/or obese women. This study investigated whether the management of GDM improves FAO in GDM subjects near term.
Methods
Medical records of 7,099 singleton pregnant women delivering at CHA Gangnam Medical Center were reviewed retrospectively. GDM was diagnosed by 100-g oral glucose tolerance test after 50-g glucose challenge test based on Carpenter–Coustan criteria. GDM subjects were divided into four study groups according to maternal age and obesity. FAO was defined as ≥90th percentile of fetal abdominal overgrowth ratios (FAORs) of the ultrasonographically estimated gestational age (GA) of abdominal circumference per actual GA by the last menstruation period, biparietal diameter, or femur length, respectively.
Results
As compared with normal glucose tolerance (NGT) subjects near term, FAORs and odds ratio for FAO were significantly higher in old and/or obese women with GDM but not in young and nonobese women with GDM. For fetuses of GDM subjects with FAO at the time of GDM diagnosis, the odds ratio for exhibiting FAO near term and being large for GA at birth were 7.87 (95% confidence interval [CI], 4.38 to 14.15) and 10.96 (95% CI, 5.58 to 20.53) compared with fetuses of NGT subjects without FAO at GDM diagnosis.
Conclusion
Despite treatment, FAO detected at the time of GDM diagnosis persisted until delivery. Early diagnosis and treatment might be necessary to prevent near term FAO in high-risk older and/or obese women.

Citations

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Gestational diabetes mellitus management according to ultrasound fetal growth versus strict glycemic treatment in singleton pregnancies: A systematic review and meta‐analysis of clinical trials
Ana M. Fernández‐Alonso, Angélica Monterrosa‐Blanco, Álvaro Monterrosa‐Castro, Faustino R. Pérez‐López
Journal of Obstetrics and Gynaecology Research.2024; 50(10): 1759. CrossRef
The effects of gestational diabetes mellitus on fetal growth: is it different for low-risk and medium–high-risk pregnant women?
Jie Wang, Xin Cheng, Zhen-Hua Li, Yi-Cheng Mao, Xin-Qiang Wang, Kang-Di Zhang, Wen-Jie Yu, Ying-Qing Li, Jia-wen Zhao, Mao-Lin Chen, Guo-peng Gao, Cheng-Yang Hu, Xiu-Jun Zhang
Archives of Gynecology and Obstetrics.2023; 310(2): 833. CrossRef
Fetal abdominal obesity and the ensuing adverse perinatal outcomes in older obese pregnant women with or without obesity and with normal glucose tolerance
Wonjin Kim, Soo Kyung Park, Yoo Lee Kim
Scientific Reports.2023;[Epub] CrossRef
Early-life exposure to gestational diabetes mellitus predisposes offspring to pediatric nonalcoholic fatty liver disease
Qian-Ren Zhang, Yan Dong, Jian-Gao Fan
Hepatobiliary & Pancreatic Diseases International.2023;[Epub] CrossRef
Gestational diabetes mellitus and adverse pregnancy outcomes: systematic review and meta-analysis
Wenrui Ye, Cong Luo, Jing Huang, Chenglong Li, Zhixiong Liu, Fangkun Liu
BMJ.2022; : e067946. CrossRef
Fetal abdominal overgrowth is already present at 20–24 gestational weeks prior to diagnosis of gestational diabetes mellitus
Wonjin Kim, Soo Kyung Park, Yoo Lee Kim
Scientific Reports.2021;[Epub] CrossRef

Metabolic Risk/Epidemiology
Maternal Hyperglycemia during Pregnancy Increases Adiposity of Offspring: Hye Rim Chung, Joon Ho Moon, Jung Sub Lim, Young Ah Lee, Choong Ho Shin, Joon-Seok Hong, Soo Heon Kwak, Sung Hee Choi, Hak Chul Jang; Diabetes Metab J. 2021;45(5):730-738. Published online February 22, 2021; DOI: https://doi.org/10.4093/dmj.2020.0154

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Background
The effect of intrauterine hyperglycemia on fat mass and regional fat proportion of the offspring of mothers with gestational diabetes mellitus (OGDM) remains to be determined.
Methods
The body composition of OGDM (n=25) and offspring of normoglycemic mothers (n=49) was compared using dualenergy X-ray absorptiometry at age 5 years. The relationship between maternal glucose concentration during a 100 g oral glucose tolerance test (OGTT) and regional fat mass or proportion was analyzed after adjusting for maternal prepregnancy body mass index (BMI).
Results
BMI was comparable between OGDM and control (median, 16.0 kg/m² vs. 16.1 kg/m² ). Total, truncal, and leg fat mass were higher in OGDM compared with control (3,769 g vs. 2,245 g, P=0.004; 1,289 g vs. 870 g, P=0.017; 1,638 g vs. 961 g, P=0.002, respectively), whereas total lean mass was lower in OGDM (15,688 g vs. 16,941 g, P=0.001). Among OGDM, total and truncal fat mass were correlated with fasting and 3-hour glucose concentrations of maternal 100 g OGTT during pregnancy (total fat mass, r=0.49, P=0.018 [fasting], r=0.473, P=0.023 [3-hour]; truncal fat mass, r=0.571, P=0.004 [fasting], r=0.558, P=0.006 [3-hour]), but there was no correlation between OGDM leg fat mass and maternal OGTT during pregnancy. Regional fat indices were not correlated with concurrent maternal 75 g OGTT values.
Conclusion
Intrauterine hyperglycemia is associated with increased fat mass, especially truncal fat, in OGDM aged 5 years.

Citations

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Advances in free fatty acid profiles in gestational diabetes mellitus
Haoyi Du, Danyang Li, Laura Monjowa Molive, Na Wu
Journal of Translational Medicine.2024;[Epub] CrossRef
2023 Clinical Practice Guidelines for Diabetes Management in Korea: Full Version Recommendation of the Korean Diabetes Association
Jun Sung Moon, Shinae Kang, Jong Han Choi, Kyung Ae Lee, Joon Ho Moon, Suk Chon, Dae Jung Kim, Hyun Jin Kim, Ji A Seo, Mee Kyoung Kim, Jeong Hyun Lim, Yoon Ju Song, Ye Seul Yang, Jae Hyeon Kim, You-Bin Lee, Junghyun Noh, Kyu Yeon Hur, Jong Suk Park, Sang
Diabetes & Metabolism Journal.2024; 48(4): 546. CrossRef
Type 1 Diabetes and Pregnancy: Challenges in Glycemic Control and Maternal–Fetal Outcomes
Tejumola Apata, Dennis Samuel, Laticia Valle, Sarah D. Crimmins
Seminars in Reproductive Medicine.2024;[Epub] CrossRef
High-fat diet during pregnancy lowers fetal weight and has a long-lasting adverse effect on brown adipose tissue in the offspring
Mihoko Yamaguchi, Jun Mori, Nozomi Nishida, Satoshi Miyagaki, Yasuhiro Kawabe, Takeshi Ota, Hidechika Morimoto, Yusuke Tsuma, Shota Fukuhara, Takehiro Ogata, Takuro Okamaura, Naoko Nakanishi, Masahide Hamaguchi, Hisakazu Nakajima, Michiaki Fukui, Tomoko I
Journal of Developmental Origins of Health and Disease.2023; 14(2): 261. CrossRef
Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms
Byung Soo Kang, Seon Ui Lee, Subeen Hong, Sae Kyung Choi, Jae Eun Shin, Jeong Ha Wie, Yun Sung Jo, Yeon Hee Kim, Kicheol Kil, Yoo Hyun Chung, Kyunghoon Jung, Hanul Hong, In Yang Park, Hyun Sun Ko
Scientific Reports.2023;[Epub] CrossRef
Effects of early standardized management on the growth trajectory of offspring with gestational diabetes mellitus at 0–5 years old: a preliminary longitudinal study
Bingbing Guo, Jingjing Pei, Yin Xu, Yajie Wang, Xinye Jiang
Scientific Reports.2023;[Epub] CrossRef
Gestational Diabetes Mellitus: Diagnostic Approaches and Maternal-Offspring Complications
Joon Ho Moon, Hak Chul Jang
Diabetes & Metabolism Journal.2022; 46(1): 3. CrossRef
Increased Pro-Inflammatory T Cells, Senescent T Cells, and Immune-Check Point Molecules in the Placentas of Patients With Gestational Diabetes Mellitus
Yea Eun Kang, Hyon-Seung Yi, Min-Kyung Yeo, Jung Tae Kim, Danbit Park, Yewon Jung, Ok Soon Kim, Seong Eun Lee, Ji Min Kim, Kyong Hye Joung, Ju Hee Lee, Bon Jeong Ku, Mina Lee, Hyun Jin Kim
Journal of Korean Medical Science.2022;[Epub] CrossRef

Metabolic Risk/Epidemiology
A Vegetable Dietary Pattern Is Associated with Lowered Risk of Gestational Diabetes Mellitus in Chinese Women: Qiong Chen, Weiwei Wu, Hailan Yang, Ping Zhang, Yongliang Feng, Keke Wang, Ying Wang, Suping Wang, Yawei Zhang; Diabetes Metab J. 2020;44(6):887-896. Published online September 11, 2020; DOI: https://doi.org/10.4093/dmj.2019.0138

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Background
Identification of modifiable dietary factors, which are involved in the development of gestational diabetes mellitus (GDM), could inform strategies to prevent GDM.
Methods
We examined the dietary patterns in a Chinese population and evaluated their relationship with GDM risk using a case-control study including 1,464 cases and 8,092 control subjects. Propensity score matching was used to reduce the imbalance of covariates between cases and controls. Dietary patterns were identified using factor analysis while their associations with GDM risk were evaluated using logistic regression models.
Results
A “vegetable” dietary pattern was characterized as the consumption of green leafy vegetables (Chinese little greens and bean seedling), other vegetables (cabbages, carrots, tomatoes, eggplants, potatoes, mushrooms, peppers, bamboo shoots, agarics, and garlic), and bean products (soybean milk, tofu, kidney beans, and cowpea). For every quartile increase in the vegetables factor score during 1 year prior to conception, the first trimester, and the second trimester of pregnancy, the GDM risk lowered by 6% (odds ratio [OR], 0.94; 95% confidence interval [CI], 0.89 to 0.99), 7% (OR, 0.94; 95% CI, 0.88 to 0.99), and 9% (OR, 0.91; 95% CI, 0.86 to 0.96).
Conclusion
In conclusion, our study suggests that the vegetable dietary pattern is associated with lower GDM risk; however, the interpretation of the result should with caution due to the limitations in our study, and additional studies are necessary to explore the underlying mechanism of this relationship.

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Analyzing Protein and Glucose Levels in Pregnant Women Attending Antenatal Care at Health Centers in Port Harcourt, Rivers State
BIEBUMA Tamunoitekena Blessing, Aleruchi Owhonka, Egbono Frank Fubara
International Journal of Advanced Research in Science, Communication and Technology.2024; : 512. CrossRef
Association of Vegetables-Fruits Dietary Patterns with Gestational Diabetes Mellitus: Mediating Effects of Gut Microbiota
Xiaoxi Shan, Caixia Peng, Hanshuang Zou, Yunfeng Pan, Minchan Wu, Qingqing Xie, Qian Lin
Nutrients.2024; 16(14): 2300. CrossRef
Maternal dietary components in the development of gestational diabetes mellitus: a systematic review of observational studies to timely promotion of health
Victoria Lambert, Sonia Edith Muñoz, Carla Gil, María Dolores Román
Nutrition Journal.2023;[Epub] CrossRef
Fruit, vegetable, and fruit juice consumption and risk of gestational diabetes mellitus: a systematic review and meta-analysis
Yan-Ping Liao, Qing-Xiang Zheng, Xiu-Min Jiang, Xiao-Qian Chen, Xiao-Xia Gao, Yu-Qing Pan
Nutrition Journal.2023;[Epub] CrossRef
The effects of plant-based dietary patterns on the risk of developing gestational diabetes mellitus: A systematic review and meta-analysis
Yu Zhu, QingXiang Zheng, Ling Huang, XiuMin Jiang, XiaoXia Gao, JiaNing Li, RuLin Liu, Kent Lai
PLOS ONE.2023; 18(10): e0291732. CrossRef
Molecular pathways and nutrigenomic review of insulin resistance development in gestational diabetes mellitus
Patricia Guevara-Ramírez, Elius Paz-Cruz, Santiago Cadena-Ullauri, Viviana A. Ruiz-Pozo, Rafael Tamayo-Trujillo, Maria L. Felix, Daniel Simancas-Racines, Ana Karina Zambrano
Frontiers in Nutrition.2023;[Epub] CrossRef
Effectiveness of pre-pregnancy lifestyle in preventing gestational diabetes mellitus—a systematic review and meta-analysis of 257,876 pregnancies
Swetha Sampathkumar, Durga Parkhi, Yonas Ghebremichael-Weldeselassie, Nithya Sukumar, Ponnusamy Saravanan
Nutrition & Diabetes.2023;[Epub] CrossRef
Gestational Diabetes Mellitus: The Crosslink among Inflammation, Nitroxidative Stress, Intestinal Microbiota and Alternative Therapies
Elaine Luiza Santos Soares de Mendonça, Marilene Brandão Tenório Fragoso, Jerusa Maria de Oliveira, Jadriane Almeida Xavier, Marília Oliveira Fonseca Goulart, Alane Cabral Menezes de Oliveira
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Jie Gao, Xue Gu, Manqian Zhang, Xingwang Zu, Fukui Shen, Xiaotao Hou, Erwei Hao, Gang Bai
Journal of Functional Foods.2022; 91: 105009. CrossRef
Effect of dietary pattern on pregnant women with gestational diabetes mellitus and its clinical significance
Jianping Wang, Zuoliang Xie, Peipei Chen, Yuhuan Wang, Baoqing Li, Fen Dai
Open Life Sciences.2022; 17(1): 202. CrossRef
Dietary Protein Patterns during Pregnancy Are Associated with Risk of Gestational Diabetes Mellitus in Chinese Pregnant Women
Weijia Wu, Nu Tang, Jingjing Zeng, Jin Jing, Li Cai
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Dietary Acid Load Is Positively Associated With Risk of Gestational Diabetes Mellitus in a Prospective Cohort of Chinese Pregnant Women
Rui Zhao, Leilei Zhou, Gang Lei, Shanshan Wang, Yan Li, Xuefeng Yang, Guoping Xiong, Liping Hao
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Metabolic Risk/Epidemiology
A Comparison of Predictive Performances between Old versus New Criteria in a Risk-Based Screening Strategy for Gestational Diabetes Mellitus: Subeen Hong, Seung Mi Lee, Soo Heon Kwak, Byoung Jae Kim, Ja Nam Koo, Ig Hwan Oh, Sohee Oh, Sun Min Kim, Sue Shin, Won Kim, Sae Kyung Joo, Errol R. Norwitz, Souphaphone Louangsenlath, Chan-Wook Park, Jong Kwan Jun, Joong Shin Park; Diabetes Metab J. 2020;44(5):726-736. Published online April 13, 2020; DOI: https://doi.org/10.4093/dmj.2019.0126

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Background

The definition of the high-risk group for gestational diabetes mellitus (GDM) defined by the American College of Obstetricians and Gynecologists was changed from the criteria composed of five historic/demographic factors (old criteria) to the criteria consisting of 11 factors (new criteria) in 2017. To compare the predictive performances between these two sets of criteria.

Methods

This is a secondary analysis of a large prospective cohort study of non-diabetic Korean women with singleton pregnancies designed to examine the risk of GDM in women with nonalcoholic fatty liver disease. Maternal fasting blood was taken at 10 to 14 weeks of gestation and measured for glucose and lipid parameters. GDM was diagnosed by the two-step approach.

Results

Among 820 women, 42 (5.1%) were diagnosed with GDM. Using the old criteria, 29.8% (n=244) of women would have been identified as high risk versus 16.0% (n=131) using the new criteria. Of the 42 women who developed GDM, 45.2% (n=19) would have been mislabeled as not high risk by the old criteria versus 50.0% (n=21) using the new criteria (1-sensitivity, 45.2% vs. 50.0%, P>0.05). Among the 778 patients who did not develop GDM, 28.4% (n=221) would have been identified as high risk using the old criteria versus 14.1% (n=110) using the new criteria (1-specificity, 28.4% vs. 14.1%, P<0.001).

Conclusion

Compared with the old criteria, use of the new criteria would have decreased the number of patients identified as high risk and thus requiring early GDM screening by half (from 244 [29.8%] to 131 [16.0%]).

Citations

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Predicting the Risk of Insulin-Requiring Gestational Diabetes before Pregnancy: A Model Generated from a Nationwide Population-Based Cohort Study in Korea
Seung-Hwan Lee, Jin Yu, Kyungdo Han, Seung Woo Lee, Sang Youn You, Hun-Sung Kim, Jae-Hyoung Cho, Kun-Ho Yoon, Mee Kyoung Kim
Endocrinology and Metabolism.2023; 38(1): 129. CrossRef
Metabolic Dysfunction-Associated Fatty Liver Disease and Subsequent Development of Adverse Pregnancy Outcomes
Seung Mi Lee, Young Mi Jung, Eun Saem Choi, Soo Heon Kwak, Ja Nam Koo, Ig Hwan Oh, Byoung Jae Kim, Sun Min Kim, Sang Youn Kim, Gyoung Min Kim, Sae Kyung Joo, Bo Kyung Koo, Sue Shin, Errol R. Norwitz, Chan-Wook Park, Jong Kwan Jun, Won Kim, Joong Shin Park
Clinical Gastroenterology and Hepatology.2022; 20(11): 2542. CrossRef
Nonalcoholic fatty liver disease and early prediction of gestational diabetes mellitus using machine learning methods
Seung Mi Lee, Suhyun Hwangbo, Errol R. Norwitz, Ja Nam Koo, Ig Hwan Oh, Eun Saem Choi, Young Mi Jung, Sun Min Kim, Byoung Jae Kim, Sang Youn Kim, Gyoung Min Kim, Won Kim, Sae Kyung Joo, Sue Shin, Chan-Wook Park, Taesung Park, Joong Shin Park
Clinical and Molecular Hepatology.2022; 28(1): 105. CrossRef
Nonalcoholic fatty liver disease-based risk prediction of adverse pregnancy outcomes: Ready for prime time?
Seung Mi Lee, Won Kim
Clinical and Molecular Hepatology.2022; 28(1): 47. CrossRef
Postprandial Free Fatty Acids at Mid-Pregnancy Increase the Risk of Large-for-Gestational-Age Newborns in Women with Gestational Diabetes Mellitus
So-Yeon Kim, Young Shin Song, Soo-Kyung Kim, Yong-Wook Cho, Kyung-Soo Kim
Diabetes & Metabolism Journal.2022; 46(1): 140. CrossRef
Effect of Different Types of Diagnostic Criteria for Gestational Diabetes Mellitus on Adverse Neonatal Outcomes: A Systematic Review, Meta-Analysis, and Meta-Regression
Fahimeh Ramezani Tehrani, Marzieh Saei Ghare Naz, Razieh Bidhendi-Yarandi, Samira Behboudi-Gandevani
Diabetes & Metabolism Journal.2022; 46(4): 605. CrossRef
Development of early prediction model for pregnancy-associated hypertension with graph-based semi-supervised learning
Seung Mi Lee, Yonghyun Nam, Eun Saem Choi, Young Mi Jung, Vivek Sriram, Jacob S. Leiby, Ja Nam Koo, Ig Hwan Oh, Byoung Jae Kim, Sun Min Kim, Sang Youn Kim, Gyoung Min Kim, Sae Kyung Joo, Sue Shin, Errol R. Norwitz, Chan-Wook Park, Jong Kwan Jun, Won Kim,
Scientific Reports.2022;[Epub] CrossRef
The Clinical Characteristics of Gestational Diabetes Mellitus in Korea: A National Health Information Database Study
Kyung-Soo Kim, Sangmo Hong, Kyungdo Han, Cheol-Young Park
Endocrinology and Metabolism.2021; 36(3): 628. CrossRef
The risk of pregnancy‐associated hypertension in women with nonalcoholic fatty liver disease
Young Mi Jung, Seung Mi Lee, Subeen Hong, Ja Nam Koo, Ig Hwan Oh, Byoung Jae Kim, Sun Min Kim, Sang Youn Kim, Gyoung Min Kim, Sae Kyung Joo, Sue Shin, Errol R. Norwitz, Chan‐Wook Park, Jong Kwan Jun, Won Kim, Joong Shin Park
Liver International.2020; 40(10): 2417. CrossRef

Metabolic Risk/Epidemiology
Glucose Effectiveness from Short Insulin-Modified IVGTT and Its Application to the Study of Women with Previous Gestational Diabetes Mellitus: Micaela Morettini, Carlo Castriota, Christian Göbl, Alexandra Kautzky-Willer, Giovanni Pacini, Laura Burattini, Andrea Tura; Diabetes Metab J. 2020;44(2):286-294. Published online January 13, 2020; DOI: https://doi.org/10.4093/dmj.2019.0016

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Background

This study aimed to design a simple surrogate marker (i.e., predictor) of the minimal model glucose effectiveness (S_G), namely calculated S_G (CS_G), from a short insulin-modified intravenous glucose tolerance test (IM-IVGTT), and then to apply it to study women with previous gestational diabetes mellitus (pGDM).

Methods

CS_G was designed using the stepwise model selection approach on a population of subjects (n=181) ranging from normal tolerance to type 2 diabetes mellitus (T2DM). CS_G was then tested on a population of women with pGDM (n=57). Each subject underwent a 3-hour IM-IVGTT; women with pGDM were observed early postpartum and after a follow-up period of up to 7 years and classified as progressors (PROG) or non-progressors (NONPROG) to T2DM. The minimal model analysis provided a reference S_G.

Results

CS_G was described as CS_G=1.06×10⁻²+5.71×10⁻²×K_G/G_peak, K_G being the mean slope (absolute value) of loge glucose in 10–25- and 25–50-minute intervals, and G_peak being the maximum of the glucose curve. Good agreement between CS_G and S_G in the general population and in the pGDM group, both at baseline and follow-up (even in PROG and NONPROG subgroups), was shown by the Bland-Altman plots (<5% observations outside limits of agreement), and by the test for equivalence (equivalence margin not higher than one standard deviation). At baseline, the PROG subgroup showed significantly lower S_G and CS_G values compared to the NONPROG subgroup (P<0.03).

Conclusion

CS_G is a valid S_G predictor. In the pGDM group, glucose effectiveness appeared to be impaired in women progressing to T2DM.

Citations

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Postprandial Free Fatty Acids at Mid-Pregnancy Increase the Risk of Large-for-Gestational-Age Newborns in Women with Gestational Diabetes Mellitus
So-Yeon Kim, Young Shin Song, Soo-Kyung Kim, Yong-Wook Cho, Kyung-Soo Kim
Diabetes & Metabolism Journal.2022; 46(1): 140. CrossRef
Unraveling the Factors Determining Development of Type 2 Diabetes in Women With a History of Gestational Diabetes Mellitus Through Machine-Learning Techniques
Ludovica Ilari, Agnese Piersanti, Christian Göbl, Laura Burattini, Alexandra Kautzky-Willer, Andrea Tura, Micaela Morettini
Frontiers in Physiology.2022;[Epub] CrossRef
The Clinical Characteristics of Gestational Diabetes Mellitus in Korea: A National Health Information Database Study
Kyung-Soo Kim, Sangmo Hong, Kyungdo Han, Cheol-Young Park
Endocrinology and Metabolism.2021; 36(3): 628. CrossRef

Clinical Diabetes & Therapeutics
Early Assessment of the Risk for Gestational Diabetes Mellitus: Can Fasting Parameters of Glucose Metabolism Contribute to Risk Prediction?: Veronica Falcone, Grammata Kotzaeridi, Melanie Hanne Breil, Ingo Rosicky, Tina Stopp, Gülen Yerlikaya-Schatten, Michael Feichtinger, Wolfgang Eppel, Peter Husslein, Andrea Tura, Christian S. Göbl; Diabetes Metab J. 2019;43(6):785-793. Published online March 12, 2019; DOI: https://doi.org/10.4093/dmj.2018.0218

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Background

An early identification of the risk groups might be beneficial in reducing morbidities in patients with gestational diabetes mellitus (GDM). Therefore, this study aimed to assess the biochemical predictors of glycemic conditions, in addition to fasting indices of glucose disposal, to predict the development of GDM in later stage and the need of glucose-lowering medication.

Methods

A total of 574 pregnant females (103 with GDM and 471 with normal glucose tolerance [NGT]) were included. A metabolic characterization was performed before 15⁺⁶ weeks of gestation by assessing fasting plasma glucose (FPG), fasting insulin (FI), fasting C-peptide (FCP), and glycosylated hemoglobin (HbA1c). Thereafter, the patients were followed-up until the delivery.

Results

Females with NGT had lower levels of FPG, FI, FCP, or HbA1c at the early stage of pregnancy, and therefore, showed an improved insulin action as compared to that in females who developed GDM. Higher fasting levels of FPG and FCP were associated with a higher risk of developing GDM. Moreover, the predictive accuracy of this metabolic profiling was also good to distinguish the patients who required glucose-lowering medications. Indices of glucose disposal based on C-peptide improved the predictive accuracy compared to that based on insulin. A modified quantitative insulin sensitivity check index (QUICKIc) showed the best differentiation in terms of predicting GDM (area under the receiver operating characteristics curve [ROC-AUC], 72.1%) or need for pharmacotherapy (ROC-AUC, 83.7%).

Conclusion

Fasting measurements of glucose and C-peptide as well as the surrogate indices of glycemic condition could be used for stratifying pregnant females with higher risk of GDM at the beginning of pregnancy.

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MIDO GDM: an innovative artificial intelligence-based prediction model for the development of gestational diabetes in Mexican women
Héctor Gallardo-Rincón, María Jesús Ríos-Blancas, Janinne Ortega-Montiel, Alejandra Montoya, Luis Alberto Martinez-Juarez, Julieta Lomelín-Gascón, Rodrigo Saucedo-Martínez, Ricardo Mújica-Rosales, Victoria Galicia-Hernández, Linda Morales-Juárez, Lucía Ma
Scientific Reports.2023;[Epub] CrossRef
Progress in the Prediction of Gestational Diabetes Mellitus by the Combined Detection of Fasting Blood Glucose and Hemoglobin in Early Pregnancy
欢欢赵
Advances in Clinical Medicine.2023; 13(06): 9980. CrossRef
HOMA‐IR as a risk factor of gestational diabetes mellitus and a novel simple surrogate index in early pregnancy
Shuoning Song, Yuemei Zhang, Xiaolin Qiao, Yanbei Duo, Jiyu Xu, Zhenyao Peng, Jing Zhang, Yan Chen, Xiaorui Nie, Qiujin Sun, Xianchun Yang, Zechun Lu, Shixuan Liu, Tianyi Zhao, Tao Yuan, Yong Fu, Yingyue Dong, Weigang Zhao, Wei Sun, Ailing Wang
International Journal of Gynecology & Obstetrics.2022; 157(3): 694. CrossRef
The diagnostic value of glycosylated hemoglobin for gestational diabetes mellitus in Asian populations: A systematic review and meta‐analysis
Jiani Zhang, Fan Zhou, Tingting Xu, Jinfeng Xu, Yaqian Li, Li Lin, Qi Cao, Xiaodong Wang
Journal of Obstetrics and Gynaecology Research.2022; 48(4): 902. CrossRef
Postprandial Free Fatty Acids at Mid-Pregnancy Increase the Risk of Large-for-Gestational-Age Newborns in Women with Gestational Diabetes Mellitus
So-Yeon Kim, Young Shin Song, Soo-Kyung Kim, Yong-Wook Cho, Kyung-Soo Kim
Diabetes & Metabolism Journal.2022; 46(1): 140. CrossRef
Gestational Diabetes Mellitus in Pregnant Women with Beta-Thalassemia Minor: A Matched Case-Control Study
Veronica Falcone, Florian Heinzl, Bianca Karla Itariu, Theresa Reischer, Stephanie Springer, Dana Anaïs Muin, Petra Pateisky, Philipp Foessleitner, Johannes Ott, Alex Farr, Klara Rosta
Journal of Clinical Medicine.2022; 11(7): 2050. CrossRef
Maternal metabolic factors and the association with gestational diabetes: A systematic review and meta‐analysis
Nahal Habibi, Aya Mousa, Chau Thien Tay, Mahnaz Bahri Khomami, Rhiannon K. Patten, Prabha H. Andraweera, Molla Wassie, Jared Vandersluys, Ali Aflatounian, Tina Bianco‐Miotto, Shao J. Zhou, Jessica A. Grieger
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Impact Of Prepregnancy Overweight And Obesity On Treatment Modality And Pregnancy Outcome In Women With Gestational Diabetes Mellitus
Tina Linder, Anna Eder, Cécile Monod, Ingo Rosicky, Daniel Eppel, Katharina Redling, Franziska Geissler, Evelyn A. Huhn, Irene Hösli, Christian S. Göbl
Frontiers in Endocrinology.2022;[Epub] CrossRef
Identification of potential gene markers in gestational diabetes mellitus
Weichun Tang, Xiaoyu Wang, Liping Chen, Yiling Lu, Xinyi Kang
Journal of Clinical Laboratory Analysis.2022;[Epub] CrossRef
Association between early-pregnancy serum C-peptide and risk of gestational diabetes mellitus: a nested case–control study among Chinese women
Xue Yang, Yi Ye, Yi Wang, Ping Wu, Qi Lu, Yan Liu, Jiaying Yuan, Xingyue Song, Shijiao Yan, Xiaorong Qi, Yi-Xin Wang, Ying Wen, Gang Liu, Chuanzhu Lv, Chun-Xia Yang, An Pan, Jianli Zhang, Xiong-Fei Pan
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Early Predictors of Gestational Diabetes Mellitus in IVF-Conceived Pregnancies
Ayla Coussa, Hayder A. Hasan, Thomas M. Barber
Endocrine Practice.2021; 27(6): 579. CrossRef
The Clinical Characteristics of Gestational Diabetes Mellitus in Korea: A National Health Information Database Study
Kyung-Soo Kim, Sangmo Hong, Kyungdo Han, Cheol-Young Park
Endocrinology and Metabolism.2021; 36(3): 628. CrossRef
Early Gestational Diabetes Mellitus: Diagnostic Strategies and Clinical Implications
Saptarshi Bhattacharya, Lakshmi Nagendra, Aishwarya Krishnamurthy, Om J. Lakhani, Nitin Kapoor, Bharti Kalra, Sanjay Kalra
Medical Sciences.2021; 9(4): 59. CrossRef
Early markers of gestational diabetes mellitus
Vedrana Ivić, Jasenka Wagner, Andrijana Müller, Lada Zibar, Marta Kadivnik, Barbara Viljetić, Jelena Omazić
Biochemia medica.2021; 31(3): 416. CrossRef
Response: Early Assessment of the Risk for Gestational Diabetes Mellitus: Can Fasting Parameters of Glucose Metabolism Contribute to Risk Prediction? (Diabetes Metab J 2019;43:785–93)
Christian S. Göbl, Andrea Tura
Diabetes & Metabolism Journal.2020; 44(1): 209. CrossRef
First-trimester fasting glycemia as a predictor of gestational diabetes (GDM) and adverse pregnancy outcomes
G. Sesmilo, P. Prats, S. Garcia, I. Rodríguez, A. Rodríguez-Melcón, I. Berges, B. Serra
Acta Diabetologica.2020; 57(6): 697. CrossRef
Letter: Early Assessment of the Risk for Gestational Diabetes Mellitus: Can Fasting Parameters of Glucose Metabolism Contribute to Risk Prediction? (Diabetes Metab J 2019;43:785–93)
Ye Seul Yang, Hye Seung Jung
Diabetes & Metabolism Journal.2020; 44(1): 199. CrossRef
Auch schon im 1. Trimenon ist Nüchternglukose Prädiktor für Gestationsdiabetes
Jens Stupin
Info Diabetologie.2020; 14(2): 14. CrossRef
Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study
Yunzhen Ye, Yu Xiong, Qiongjie Zhou, Jiangnan Wu, Xiaotian Li, Xirong Xiao
Journal of Diabetes Research.2020; 2020: 1. CrossRef
Predictive Power of Unconjugated Estriol in Diagnosis of Gestational Diabetes: A Cohort Study
Azam Amirian, Nourossadat Kariman, Mehdi Hedayati, Nasrin Borumandnia, Zohre Sheikhan
Iranian Red Crescent Medical Journal.2019;[Epub] CrossRef

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