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Suthon S, Tangjittipokin W. Mechanisms and Physiological Roles of Polymorphisms in Gestational Diabetes Mellitus. Int J Mol Sci 2024; 25:2039. [PMID: 38396716 PMCID: PMC10888615 DOI: 10.3390/ijms25042039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 02/03/2024] [Accepted: 02/05/2024] [Indexed: 02/25/2024] Open
Abstract
Gestational diabetes mellitus (GDM) is a significant pregnancy complication linked to perinatal complications and an elevated risk of future metabolic disorders for both mothers and their children. GDM is diagnosed when women without prior diabetes develop chronic hyperglycemia due to β-cell dysfunction during gestation. Global research focuses on the association between GDM and single nucleotide polymorphisms (SNPs) and aims to enhance our understanding of GDM's pathogenesis, predict its risk, and guide patient management. This review offers a summary of various SNPs linked to a heightened risk of GDM and explores their biological mechanisms within the tissues implicated in the development of the condition.
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Affiliation(s)
- Sarocha Suthon
- Department of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand;
- Siriraj Center of Research Excellence for Diabetes and Obesity, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Center of Research Excellence Management, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Watip Tangjittipokin
- Department of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand;
- Siriraj Center of Research Excellence for Diabetes and Obesity, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
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Luiro K, Auvinen AM, Auvinen J, Jokelainen J, Järvelä I, Knip M, Tapanainen JS. Autoantibodies predict type 1 diabetes after gestational diabetes - a 23-year cohort study. Front Endocrinol (Lausanne) 2023; 14:1286375. [PMID: 38192417 PMCID: PMC10773701 DOI: 10.3389/fendo.2023.1286375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 12/04/2023] [Indexed: 01/10/2024] Open
Abstract
Objective To study the predictive value of autoantibodies for type 1 (T1DM) and type 2 (T2DM) diabetes morbidity after gestational diabetes (GDM) in a 23-year follow-up study. Design Prospective population-based cohort study. Methods We studied 391 women with GDM, and 391 age- and parity-matched controls, who delivered in 1984-1994. Four autoantibodies were analysed in first-trimester blood samples: islet cell autoantibodies (ICAs), glutamic acid decarboxylase autoantibodies (GADAs), insulin autoantibodies (IAAs) and insulinoma-associated antigen-2 autoantibodies (IA-2As). Two follow-up questionnaires (1995-1996, 2012-2013) were sent to assess development of T1DM and T2DM. Predictive value of autoantibodies and clinical factors were analysed by conditional linear regression and ROC analyses. Results Single autoantibody positivity was detected in 12% (41/342) of the GDM cohort and in 2.3% (8/353) of the control cohort. In the GDM cohort, 2.6% (9/342) tested positive for two autoantibodies and 2.3% (8/342) for three autoantibodies, whereas only one subject in the control cohort had two autoantibodies. ICA positivity was found in 12.5% of the cases, followed by GADA (6.0%), IA-2A (4.9%) and IAA (1.2%). In the control cohort, GADA positivity was found in 1.4%, IA-2A in 0.8%, IAA in 0.6%, and ICA in 0.3% of the subjects. Detection of ICA, GADA and/or IA-2A autoantibodies decreased T1DM-free survival time and time to diagnosis. All subjects with three positive autoantibodies developed T1DM within seven years from the GDM pregnancy. Development of T2DM after GDM occurred independent of autoantibody positivity. Conclusion Development of T1DM can be reliably predicted with GADA and ICA autoantibodies during early pregnancy.
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Affiliation(s)
- Kaisu Luiro
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Anna-Maaria Auvinen
- Research Unit of Clinical Medicine, University of Oulu, Oulu, Finland
- Medical Research Center, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Juha Auvinen
- Medical Research Center, Oulu University Hospital and University of Oulu, Oulu, Finland
- Research Unit of Population Health, University of Oulu, Oulu, Finland
| | - Jari Jokelainen
- Northern Finland Birth Cohorts, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Ilkka Järvelä
- Department of Obstetrics and Gynecology, Kuopio University Hospital, Kuopio, Finland
| | - Mikael Knip
- Pediatric Research Center, New Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Tampere Center for Child Health Research, Tampere University Hospital, Tampere, Finland
| | - Juha S. Tapanainen
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Unit of Clinical Medicine, University of Oulu, Oulu, Finland
- Medical Research Center, Oulu University Hospital and University of Oulu, Oulu, Finland
- Department of Obstetrics and Gynecology, HFR – Cantonal Hospital of Fribourg and University of Fribourg, Fribourg, Switzerland
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Xie W, Zhang L, Wang J, Wang Y. Association of HHEX and SLC30A8 Gene Polymorphisms with Gestational Diabetes Mellitus Susceptibility: A Meta-analysis. Biochem Genet 2023; 61:2203-2221. [PMID: 37103601 DOI: 10.1007/s10528-023-10385-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 04/14/2023] [Indexed: 04/28/2023]
Abstract
Genetics plays a role in the development of gestational diabetes mellitus (GDM), which poses serious risks to pregnant women and their children. Several studies have demonstrated a link between GDM susceptibility and rs13266634 C/T polymorphism in SLC30A8 gene and rs1111875 C/T and rs5015480 C/T, which are located near the linkage disequilibrium block containing the IDE, HHEX, and KIF11 genes. However, the results are conflicting. Therefore, we aimed to investigate the association between susceptibility to GDM and HHEX and SLC30A8 gene polymorphisms. PubMed, Web of Science, EBSCO, CNKI, Wanfang Data, VIP, and SCOPUS were used to search for research articles. The quality of the selected literature was evaluated using the Newcastle-Ottawa scale. A meta-analysis was performed using Stata 15.1. Allelic, dominant, recessive, homozygote, and heterozygote models were used for the analysis. Nine articles with 15 studies were included. (1) Four studies about HHEX rs1111875 showed that the C allele was associated with the susceptibility to GDM; (2) three studies on HHEX rs5015480 indicated that the C allele in rs5015480 was significantly associated with GDM; (3) eight studies about SLC30A8 rs13266634 showed that the C allele was significantly associated with the susceptibility to GDM; and (4) a subgroup analysis showed that the rs5015480 polymorphism in HHEX and rs13266634 polymorphism in SLC30A8 gene were associated with GDM susceptibility in Asians. The meta-analysis provided evidence that the C allele in rs1111875 and rs5015480 in HHEX and rs13266634 in SLC30A8 can increase the risk of GDM.PROSPERO registration number CRD42022342280.
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Affiliation(s)
- Wanting Xie
- Department of Physical Fitness and Health, School of Sport Science, Beijing Sport University, No.48, Xinxi Road, Haidian District, Beijing, 100084, China
| | - Liuwei Zhang
- Department of Physical Fitness and Health, School of Sport Science, Beijing Sport University, No.48, Xinxi Road, Haidian District, Beijing, 100084, China.
- Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing, 100084, China.
| | - Jiawei Wang
- Department of Physical Fitness and Health, School of Sport Science, Beijing Sport University, No.48, Xinxi Road, Haidian District, Beijing, 100084, China
| | - Yirui Wang
- Department of Physical Fitness and Health, School of Sport Science, Beijing Sport University, No.48, Xinxi Road, Haidian District, Beijing, 100084, China
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Zeng Q, Tan B, Han F, Huang X, Huang J, Wei Y, Guo R. Association of solute carrier family 30 A8 zinc transporter gene variations with gestational diabetes mellitus risk in a Chinese population. Front Endocrinol (Lausanne) 2023; 14:1159714. [PMID: 37324267 PMCID: PMC10266221 DOI: 10.3389/fendo.2023.1159714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 05/12/2023] [Indexed: 06/17/2023] Open
Abstract
Background The solute carrier family 30 A8 zinc transporter (SLC30A8) plays a crucial role in insulin secretion. This study aimed to investigate the impact of SLC30A8 gene polymorphisms on gestational diabetes mellitus (GDM). Methods The research objective was to select 500 patients with GDM and 502 control subjects. Rs13266634 and rs2466293 were genotyped using the SNPscan™ genotyping assay. Statistical tests, such as the chi-square test, t-test, logistic regression, ANOVA, and meta-analysis, were conducted to determine the differences in genotypes, alleles, and their associations with GDM risk. Results Statistically significant differences were observed in age, pregestational BMI, SBP, DBP, and parity between individuals with GDM and healthy subjects (P < 0.05). After adjusting for these factors, rs2466293 remained significantly associated with an increased risk of GDM in overall subjects (GG+AG vs. AA: OR = 1.310; 95% CI: 1.005-1.707; P = 0.046, GG vs. AA: OR = 1.523; 95% CI: 1.010-2.298; P = 0.045 and G vs. A: OR = 1.249; 95% CI: 1.029-1.516; P = 0.024). Rs13266634 was still found to be significantly associated with a decreased risk of GDM in individuals aged ≥ 30 years (TT vs. CT+CC: OR = 0.615; 95% CI: 0.392-0.966; P = 0.035, TT vs. CC: OR = 0.503; 95% CI: 0.294-0.861; P = 0.012 and T vs. C: OR =0.723; 95% CI: 0.557-0.937; P = 0.014). Additionally, the haplotype CG was found to be associated with a higher risk of GDM (P < 0.05). Furthermore, pregnant women with the CC or CT genotype of rs13266634 exhibited significantly higher mean blood glucose levels than those with the TT genotype (P < 0.05). Our findings were further validated by the results of a meta-analysis. Conclusion The SLC30A8 rs2466293 polymorphism was found to be associated with an increased risk of GDM, while rs13266634 was associated with a decreased risk of GDM in individuals aged ≥ 30 years. These findings provide a theoretical basis for GDM testing.
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Affiliation(s)
- Qiaoli Zeng
- Department of Internal Medicine, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical University, Foshan, Guangdong, China
- Key Laboratory of Research in Maternal and Child Medicine and Birth Defects, Guangdong Medical University, Foshan, Guangdong, China
- Maternal and Child Research Institute, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical University, Foshan, Guangdong, China
| | - Bing Tan
- Department of Internal Medicine, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical University, Foshan, Guangdong, China
- Key Laboratory of Research in Maternal and Child Medicine and Birth Defects, Guangdong Medical University, Foshan, Guangdong, China
- Department of Endocrinology, Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Fengqiong Han
- Department of Obstetric, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical University, Foshan, Guangdong, China
| | - Xiujuan Huang
- Department of Children’s Health, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical University, Foshan, Guangdong, China
| | - Jinzhi Huang
- Department of Gynaecology, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical University, Foshan, Guangdong, China
| | - Yue Wei
- Department of Ultrasound, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical University, Foshan, Guangdong, China
| | - Runmin Guo
- Department of Internal Medicine, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical University, Foshan, Guangdong, China
- Key Laboratory of Research in Maternal and Child Medicine and Birth Defects, Guangdong Medical University, Foshan, Guangdong, China
- Maternal and Child Research Institute, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical University, Foshan, Guangdong, China
- Department of Endocrinology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
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Wang N, Guo H, Jing Y, Zhang Y, Sun B, Pan X, Chen H, Xu J, Wang M, Chen X, Song L, Cui W. Development and validation of risk prediction models for large for gestational age infants using logistic regression and two machine learning algorithms. J Diabetes 2023; 15:338-348. [PMID: 36890429 PMCID: PMC10101839 DOI: 10.1111/1753-0407.13375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 02/09/2023] [Accepted: 02/20/2023] [Indexed: 03/10/2023] Open
Abstract
BACKGROUND Large for gestational age (LGA) is one of the adverse outcomes during pregnancy that endangers the life and health of mothers and offspring. We aimed to establish prediction models for LGA at late pregnancy. METHODS Data were obtained from an established Chinese pregnant women cohort of 1285 pregnant women. LGA was diagnosed as >90th percentile of birth weight distribution of Chinese corresponding to gestational age of the same-sex newborns. Women with gestational diabetes mellitus (GDM) were classified into three subtypes according to the indexes of insulin sensitivity and insulin secretion. Models were established by logistic regression and decision tree/random forest algorithms, and validated by the data. RESULTS A total of 139 newborns were diagnosed as LGA after birth. The area under the curve (AUC) for the training set is 0.760 (95% confidence interval [CI] 0.706-0.815), and 0.748 (95% CI 0.659-0.837) for the internal validation set of the logistic regression model, which consisted of eight commonly used clinical indicators (including lipid profile) and GDM subtypes. For the prediction models established by the two machine learning algorithms, which included all the variables, the training set and the internal validation set had AUCs of 0.813 (95% CI 0.786-0.839) and 0.779 (95% CI 0.735-0.824) for the decision tree model, and 0.854 (95% CI 0.831-0.877) and 0.808 (95% CI 0.766-0.850) for the random forest model. CONCLUSION We established and validated three LGA risk prediction models to screen out the pregnant women with high risk of LGA at the early stage of the third trimester, which showed good prediction power and could guide early prevention strategies.
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Affiliation(s)
- Ning Wang
- Department of EndocrinologyThe Second Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Haonan Guo
- Department of Endocrinology and Second Department of GeriatricsThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Yingyu Jing
- Department of Endocrinology and Second Department of GeriatricsThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Yifan Zhang
- Department of Endocrinology and Second Department of GeriatricsThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Bo Sun
- Department of Physiology and Pathophysiology, School of Basic Medical SciencesXi'an Jiaotong University Health Science CenterXi'anChina
| | | | - Huan Chen
- Department of Endocrinology and Second Department of GeriatricsThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Jing Xu
- Department of EndocrinologyThe Second Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | | | - Xi Chen
- Department of Epidemiology and Statistics, School of Public Health, Medical CollegeZhejiang UniversityHangzhouChina
| | - Lin Song
- Department of Physiology and Pathophysiology, School of Basic Medical SciencesXi'an Jiaotong University Health Science CenterXi'anChina
| | - Wei Cui
- Department of Endocrinology and Second Department of GeriatricsThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
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Wang N, Guo H, Jing Y, Song L, Chen H, Wang M, Gao L, Huang L, Song Y, Sun B, Cui W, Xu J. Development and Validation of Risk Prediction Models for Gestational Diabetes Mellitus Using Four Different Methods. Metabolites 2022; 12:1040. [PMID: 36355123 PMCID: PMC9697464 DOI: 10.3390/metabo12111040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 09/26/2022] [Accepted: 10/25/2022] [Indexed: 09/21/2023] Open
Abstract
Gestational diabetes mellitus (GDM), a common perinatal disease, is related to increased risks of maternal and neonatal adverse perinatal outcomes. We aimed to establish GDM risk prediction models that can be widely used in the first trimester using four different methods, including a score-scaled model derived from a meta-analysis using 42 studies, a logistic regression model, and two machine learning models (decision tree and random forest algorithms). The score-scaled model (seven variables) was established via a meta-analysis and a stratified cohort of 1075 Chinese pregnant women from the Northwest Women's and Children's Hospital (NWCH) and showed an area under the curve (AUC) of 0.772. The logistic regression model (seven variables) was established and validated using the above cohort and showed AUCs of 0.799 and 0.834 for the training and validation sets, respectively. Another two models were established using the decision tree (DT) and random forest (RF) algorithms and showed corresponding AUCs of 0.825 and 0.823 for the training set, and 0.816 and 0.827 for the validation set. The validation of the developed models suggested good performance in a cohort derived from another period. The score-scaled GDM prediction model, the logistic regression GDM prediction model, and the two machine learning GDM prediction models could be employed to identify pregnant women with a high risk of GDM using common clinical indicators, and interventions can be sought promptly.
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Affiliation(s)
- Ning Wang
- Department of Endocrinology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, China
- International Center for Obesity and Metabolic Disease Research of Xi’an Jiaotong University, Xi’an 710061, China
| | - Haonan Guo
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China
| | - Yingyu Jing
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China
| | - Lin Song
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China
| | - Huan Chen
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China
| | - Mengjun Wang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China
- Department of Endocrinology, 521 Hospital of Norinco Group, Xi’an 710065, China
| | - Lei Gao
- Department of Endocrinology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, China
| | - Lili Huang
- Department of Medical Ultrasound, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, China
| | - Yanan Song
- Department of Endocrinology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, China
| | - Bo Sun
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China
| | - Wei Cui
- International Center for Obesity and Metabolic Disease Research of Xi’an Jiaotong University, Xi’an 710061, China
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China
| | - Jing Xu
- Department of Endocrinology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, China
- International Center for Obesity and Metabolic Disease Research of Xi’an Jiaotong University, Xi’an 710061, China
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Beunen K, Vercauter L, Van Crombrugge P, Moyson C, Verhaeghe J, Vandeginste S, Verlaenen H, Vercammen C, Maes T, Dufraimont E, Roggen N, De Block C, Jacquemyn Y, Mekahli F, De Clippel K, Van Den Bruel A, Loccufier A, Laenen A, Devlieger R, Mathieu C, Benhalima K. Type 1 diabetes-related autoimmune antibodies in women with gestational diabetes mellitus and the long-term risk for glucose intolerance. Front Endocrinol (Lausanne) 2022; 13:973820. [PMID: 36093103 PMCID: PMC9449803 DOI: 10.3389/fendo.2022.973820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 08/04/2022] [Indexed: 11/13/2022] Open
Abstract
AIMS To characterize women with gestational diabetes mellitus (GDM) positive for type 1 diabetes-related autoimmune antibodies (T1D-related autoantibodies) in pregnancy and to evaluate their risk for long-term glucose intolerance. METHODS In a multi-centric prospective cohort study with 1843 women receiving universal screening for GDM with a 75 g oral glucose tolerance test (OGTT), autoantibodies were measured in women with GDM: insulin autoantibodies (IAA), islet cell antibodies (ICA), insulinoma-associated protein-2 antibodies (IA-2A) and glutamic acid decarboxylase antibodies (GADA). Long-term follow-up ( ± 4.6 years after delivery) with a 75 g OGTT and re-measurement of autoantibodies was done in women with a history of GDM and autoantibody positivity in pregnancy. RESULTS Of all women with GDM (231), 80.5% (186) received autoantibody measurement at a mean of 26.2 weeks in pregnancy, of which 8.1% (15) had one positive antibody (seven with IAA, two with ICA, four with IA-2A and two with GADA). Characteristics in pregnancy were similar but compared to women without autoantibodies, women with autoantibodies had more often gestational hypertension [33.3% (5) vs. 1.7% (3), p<0.001] and more often neonatal hypoglycemia [40.0% (6) vs. 12.5% (19), p=0.012]. Among 14 of the 15 autoantibody positive women with an early postpartum OGTT, two had impaired fasting glucose (IFG). Of the 12 women with long-term follow-up data, four tested again positive for T1D-related autoantibodies (three positive for IA-2A and one positive for ICA and IAA). Five women were glucose intolerant at the long-term follow-up of which two had IA-2A (one had IFG and one had T1D) and three without autoantibodies. There were no significant differences in long-term characteristics between women with and without autoantibodies postpartum. CONCLUSIONS Systematic screening for T1D-related autoantibodies in GDM does not seem warranted since the low positivity rate for autoantibodies in pregnancy and postpartum. At 4.6 years postpartum, five out of 12 women were glucose intolerant but only two still had autoantibodies. In women with clinically significant increased autoantibody levels during pregnancy, postpartum autoantibody re-measurement seems useful since the high risk for further increase of autoantibody levels.
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Affiliation(s)
- Kaat Beunen
- Department of Endocrinology, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium
- *Correspondence: Kaat Beunen,
| | | | - Paul Van Crombrugge
- Department of Endocrinology, Onze Lieve Vrouw (OLV) Hospital Aalst-Asse-Ninove, Aalst, Belgium
| | - Carolien Moyson
- Department of Endocrinology, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium
| | - Johan Verhaeghe
- Department of Obstetrics and Gynecology, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium
| | - Sofie Vandeginste
- Department of Obstetrics and Gynecology, OLV Hospital Aalst-Asse-Ninove, Aalst, Belgium
| | - Hilde Verlaenen
- Department of Obstetrics and Gynecology, OLV Hospital Aalst-Asse-Ninove, Aalst, Belgium
| | - Chris Vercammen
- Department of Endocrinology, Imelda Hospital, Bonheiden, Belgium
| | - Toon Maes
- Department of Endocrinology, Imelda Hospital, Bonheiden, Belgium
| | - Els Dufraimont
- Department of Obstetrics and Gynecology, Imelda Hospital, Bonheiden, Belgium
| | - Nele Roggen
- Department of Obstetrics and Gynecology, Imelda Hospital, Bonheiden, Belgium
| | - Christophe De Block
- Department of Endocrinology-Diabetology-Metabolism, Antwerp University Hospital, Edegem, Belgium
| | - Yves Jacquemyn
- Department of Obstetrics and Gynecology, Antwerp University Hospital, Edegem, Belgium
| | - Farah Mekahli
- Department of Endocrinology, Hospital St Jan Brussel, Brussel, Belgium
| | - Katrien De Clippel
- Department of Obstetrics and Gynecology, Hospital St Jan Brussel, Brussel, Belgium
| | | | - Anne Loccufier
- Department of Obstetrics and Gynecology, General Hospital St Jan Brugge, Brugge, Belgium
| | - Annouschka Laenen
- Center of Biostatics and Statistical Bioinformatics, KU Leuven, Leuven, Belgium
| | - Roland Devlieger
- Department of Obstetrics and Gynecology, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium
| | - Chantal Mathieu
- Department of Endocrinology, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium
| | - Katrien Benhalima
- Department of Endocrinology, University Hospitals Gasthuisberg, KU Leuven, Leuven, Belgium
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Tian Y, Li P. Genetic risk score to improve prediction and treatment in gestational diabetes mellitus. Front Endocrinol (Lausanne) 2022; 13:955821. [PMID: 36339414 PMCID: PMC9627198 DOI: 10.3389/fendo.2022.955821] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Accepted: 09/29/2022] [Indexed: 11/25/2022] Open
Abstract
Diabetes mellitus is a chronic disease caused by the interaction of genetics and the environment that can lead to chronic damage to many organ systems. Genome-wide association studies have identified accumulating single-nucleotide polymorphisms related to type 2 diabetes mellitus and gestational diabetes mellitus. Genetic risk score (GRS) has been utilized to evaluate the incidence risk to improve prediction and optimize treatments. This article reviews the research progress in the use of the GRS in diabetes mellitus in recent years and discusses future prospects.
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Du R, Li L, Wang Y. N6-Methyladenosine-Related Gene Signature Associated With Monocyte Infiltration Is Clinically Significant in Gestational Diabetes Mellitus. Front Endocrinol (Lausanne) 2022; 13:853857. [PMID: 35370940 PMCID: PMC8971567 DOI: 10.3389/fendo.2022.853857] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 02/18/2022] [Indexed: 12/20/2022] Open
Abstract
OBJECTIVE The objective of this study was to reveal the potential crosstalk between immune infiltration and N6- methyladenosine (m6A) modification in the placentas of patients with gestational diabetes mellitus (GDM), and to construct a model for the diagnosis of GDM. METHODS We analyzed imbalanced immune infiltration and differentially expressed m6A-related genes (DMRGs) in the placentas of patients with GDM, based on the GSE70493 dataset. An immune-related DMRG signature, with significant classifying power and diagnostic value, was identified using a least absolute shrinkage and selection operator (LASSO) regression. Based on the selected DMRGs, we developed and validated a nomogram model using GSE70493 and GSE92772 as the training and validation sets, respectively. RESULTS Infiltration of monocytes was higher in GDM placentas than in control samples, while the infiltration of macrophages (M1 and M2) in GDM placentas was lower than in controls. A total of 14 DMRGs were strongly associated with monocyte infiltration, seven of which were significant in distinguishing patients with GDM from normal controls. These genes were CD81, CFH, FABP5, GBP1, GNG11, IL1RL1, and SLAMF6. The calibration curve, decision curve, clinical impact curve, and receiver operating characteristic curve showed that the nomogram recognized GDM with high accuracy in both the training and validation sets. CONCLUSIONS Our results provide clues that crosstalk between m6A modification and immune infiltration may have implications in terms of novel biomarkers and therapeutic targets for GDM.
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Fan J, Zhang T, Yu Y, Zhang B. Is serum zinc status related to gestational diabetes mellitus? A meta-analysis. MATERNAL AND CHILD NUTRITION 2021; 17:e13239. [PMID: 34350703 PMCID: PMC8476424 DOI: 10.1111/mcn.13239] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 06/09/2021] [Accepted: 06/17/2021] [Indexed: 12/15/2022]
Abstract
Gestational diabetes mellitus (GDM) is a common medical disorder that begins during pregnancy. The present work aimed to investigate the relationship of maternal or foetal circulatory zinc levels with GDM. Related studies were retrieved against the PubMed/Medline, Web of Science, Scopus databases till July 2020. The overall effects were expressed as standard mean difference (SMD). Furthermore, the random effects model was used to assess the summarised risk ratios (SRRs) to determine the relationship between zinc and the risk of GDM. A total of 15 articles involving were retrieved for meta‐analysis; in the meantime, 4955 subjects including 1549 GDM cases were enrolled for quantitative analysis. Compared with normal control, GDM cases had decreased circulating zinc level on the whole, but the difference was not statistically significant (SMD = −0.40, 95%CI: −0.80 to −0.00, P = 0.05). Interestingly, upon subgroup analysis stratified by serum zinc content but not plasma zinc concentration, there was significant difference in zinc content between GDM cases and normal controls (SMD = −0.56; 95%CI: −1.07 to −0.04, P = 0.03). Meanwhile, subgroup analysis also revealed similar tendency among the Asians and during the 2nd trimester, but not among the Caucasians or during the 1st or 3rd trimester. Data extracted from four studies that compared pregnant women with GDM in the high level of zinc and GDM in the low level of zinc yielded an SRR of 0.929 (95%CI: 0.905–0.954). According to existing evidence, the serum zinc content decreases among GDM cases compared with subjects with no abnormality in glucose tolerance, in particular among the Asians and during the second trimester. Nonetheless, more well designed prospective study should be carried out for understanding the dynamic relationship of zinc level with the incidence of GDM.
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Affiliation(s)
- Jiehui Fan
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Tingting Zhang
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yanchao Yu
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Bao Zhang
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
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Wang N, Peng Y, Wang L, Song L, Sun B, Wei J, Wang T, Mi Y, Cui W. Risk Factors Screening for Gestational Diabetes Mellitus Heterogeneity in Chinese Pregnant Women: A Case-Control Study. Diabetes Metab Syndr Obes 2021; 14:951-961. [PMID: 33688229 PMCID: PMC7936674 DOI: 10.2147/dmso.s295071] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 02/04/2021] [Indexed: 04/20/2023] Open
Abstract
PURPOSE To study the risk factors of gestational diabetes mellitus (GDM) heterogeneity, and to evaluate the correlation between the risk factors and obesity. METHODS We performed a case-control study of 452 women with GDM and 516 women with normal glucose tolerance (NGT) at the first and second trimester. We defined GDM women as GDM-resistance subtype, GDM-dysfunction subtype, and GDM-mixed subtype, according to their simultaneous insulin-release test with predominant insulin-sensitivity defect, insulin-secretion defect, or both defects. RESULTS We found that higher maternal age, family history of diabetes, the elevated level of fasting blood glucose in the first trimester (≥5.1 mmol/L) were risk factors of all GDM subtypes. Pre-pregnancy overweight/obesity and the increased gestational weight gain (GWG) in the first-trimester are risk factors of the GDM-resistance subtype. Indicators including younger age at first menstruation, the elevated levels of alanine aminotransferase (ALT), total bile acid (TBA), triglyceride (TG), and the decreased level of high-density lipoprotein cholesterol (HDL-C) are risk factors of the GDM-resistance subtype. However, the associations between those risk factors and GDM-resistance subtype attenuated after adjusted by pre-pregnancy body mass index (pre-BMI) and gestational weight gain (GWG) in the first trimester. Nonalcoholic fatty liver disease (NAFLD) and the improved level of TG are independent risk factors for the GDM-resistance subtype and the GDM-mixed subtype, respectively. CONCLUSION Women with GDM exhibited heterogeneity based on glycemic physiology and their risk factors are not all the same. Some obesity-related risk factors are specific to the GDM-resistance subtype, which are mediated by pre-pregnancy overweight/obesity and the elevated GWG the first-trimester.
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Affiliation(s)
- Ning Wang
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi'an, People’s Republic of China
| | - Yanqi Peng
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi'an, People’s Republic of China
| | - Lu Wang
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi'an, People’s Republic of China
| | - Lin Song
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi'an, People’s Republic of China
| | - Bo Sun
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi'an, People’s Republic of China
| | - Junxiang Wei
- The Second Department of Obstetrics, Northwest Women and Children’s Hospital, Xi'an, People’s Republic of China
| | - Ting Wang
- Department of Respiratory Medicine, Xi’an No.4 Hospital, Xi'an, People’s Republic of China
| | - Yang Mi
- The Second Department of Obstetrics, Northwest Women and Children’s Hospital, Xi'an, People’s Republic of China
- Correspondence: Yang Mi The Second Department of Obstetrics, Northwest Women and Children’s Hospital, 1616 Yanxiang Road, Xi'an, Shaanxi, 710065, People’s Republic of ChinaTel +86-13700222172 Email
| | - Wei Cui
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi'an, People’s Republic of China
- Wei Cui Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi’an Jiaotong University, 277 West Yanta Road, Xi'an, Shaanxi, 710061, People’s Republic of ChinaTel +86-13609281695 Email
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Incani M, Baroni MG, Cossu E. Testing for type 1 diabetes autoantibodies in gestational diabetes mellitus (GDM): is it clinically useful? BMC Endocr Disord 2019; 19:44. [PMID: 31053128 PMCID: PMC6500053 DOI: 10.1186/s12902-019-0373-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 04/22/2019] [Indexed: 12/13/2022] Open
Abstract
Gestational Diabetes Mellitus (GDM) is the most common metabolic disorder in pregnancy, and it is associated with increased risk of morbidity in maternal-fetal outcomes. GDM is also associated with a higher risk to develop diabetes in the future. Diabetes-related autoantibodies (AABs) have been detected in a small percentage (usually less than 10%) of women with gestational diabetes. The prevalence in gestational diabetes of these autoimmune markers of type 1 diabetes (T1D) has been assessed in many studies, together with the risk of progression of AABs-positive GDM towards impaired glucose regulation (IFG or IGT) and overt diabetes after pregancy. The question whether it is necessary to test for T1D autoantibodies in all pregnancies with GDM is still debated. Here we examine the epidemiology of T1D autoantibodies in GDM, their clinical relevance in term of future risk of diabetes or impaired glucose regulation and in term of maternal-fetal outcomes, and discuss when it may be the most appropriate time to search for T1D autoantibodies in women with gestational diabetes.
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Affiliation(s)
- Michela Incani
- Endocrinology and Diabetes, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Marco Giorgio Baroni
- Endocrinology and Diabetes, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.
- Endocrinology, Department of Experimental Medicine, Sapienza University of Rome, Policlinico Umberto I, 00161, Rome, Italy.
| | - Efisio Cossu
- Endocrinology and Diabetes, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
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Liu S, Liu Y, Liao S. Heterogeneous impact of type 2 diabetes mellitus-related genetic variants on gestational glycemic traits: review and future research needs. Mol Genet Genomics 2019; 294:811-847. [PMID: 30945019 DOI: 10.1007/s00438-019-01552-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 03/25/2019] [Indexed: 02/07/2023]
Abstract
Gestational glucose homeostasis influences mother's metabolic health, pregnancy outcomes, fetal development and offspring growth. To understand the genetic roles in pregnant glucose metabolism and genetic predisposition for gestational diabetes (GDM), we reviewed the recent literature up to Jan, 2018 and evaluated the influence of T2DM-related genetic variants on gestational glycemic traits and glucose tolerance. A total of 140 variants of 89 genes were integrated. Their associations with glycemic traits in and outside pregnancy were compared. The genetic circumstances underlying glucose metabolism exhibit a similarity between pregnant and non-pregnant populations. While, not all of the T2DM-associated genetic variants are related to pregnant glucose tolerance, such as genes involved in fasting insulin/C-peptide regulation. Some genetic variants may have distinct effects on gestational glucose homeostasis. And certain genes may be particularly involved in this process via specific mechanisms, such as HKDC1, MTNR1B, BACE2, genes encoding cell cycle regulators, adipocyte regulators, inflammatory factors and hepatic factors related to gestational glucose sensing and insulin signaling. However, it is currently difficult to evaluate these associations with quantitative synthesis due to inadequate data, different analytical methods, varied measurements for glycemic traits, controversies in diagnosis of GDM, and unknown ethnicity- and/or sex-related influences on pregnant maternal metabolism. In conclusion, different genetic associations with glycemic traits may exist between pregnant and non-pregnant conditions. Comprehensive research on specific genetic regulation in gestation is necessary.
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Affiliation(s)
- Shasha Liu
- Diabetes Center and Transplantation Translational Medicine, Key Laboratory of Sichuan Province, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Yihuanlu Xierduan 32#, Chengdu, 610072, China
| | - Yunqiang Liu
- Department of Medical Genetics and Division of Morbid Genomics, State Key Laboratory of Biotherapy, West China Hospital, West China Medical School, Sichuan University, Chengdu, 610041, China
| | - Shunyao Liao
- Diabetes Center and Transplantation Translational Medicine, Key Laboratory of Sichuan Province, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Yihuanlu Xierduan 32#, Chengdu, 610072, China.
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Heneberg P, Šimčíková D, Čecháková M, Rypáčková B, Kučera P, Anděl M. Autoantibodies against ZnT8 are rare in Central-European LADA patients and absent in MODY patients, including those positive for other autoantibodies. J Diabetes Complications 2019; 33:46-52. [PMID: 30377089 DOI: 10.1016/j.jdiacomp.2018.10.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 08/10/2018] [Accepted: 10/07/2018] [Indexed: 12/14/2022]
Abstract
BACKGROUND Testing for autoantibodies against the zinc transporter ZnT8 (ZnTA) is becoming routine in pediatric diabetes. However, available data are inconclusive when focusing on adult-onset diabetes, including autoimmune diabetes, which does not require insulin at diagnosis (LADA). BASIC PROCEDURES We examined the ZnTA prevalence and titers and matched them with the clinical phenotype and PTPN22 genotypes of Czech LADA patients who were positive for GADA and/or IA2A and had a fasting C-peptide level >200 pmol/L at diagnosis as well as HNF4A-, GCK- or HNF1A-MODY patients and healthy controls. MAIN FINDINGS Most LADA patients were negative for ZnTA, and the sensitivity of the assay was only 18-20% for patients with LADA-like progression to insulinotherapy compared to healthy controls. In LADA patients, there was no association between the ZnTA and PTPN22 risk genotypes. LADA patients positive for ZnTA had a lower BMI than those positive for other autoantibodies alone. Importantly, MODY patients were completely negative for ZnTA, and the levels of ZnTA in MODY patients were similar to those in healthy controls. CONCLUSIONS ZnTA quantification did not improve LADA diagnosis. However, positivity for ZnTA can be used as a negative MODY pre-diagnostic criterion even in the region of Central and East Europe, where other islet cell autoantibodies are common in MODY patients.
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Affiliation(s)
- Petr Heneberg
- Charles University, Third Faculty of Medicine, Prague, Czech Republic.
| | - Daniela Šimčíková
- Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Marie Čecháková
- Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Blanka Rypáčková
- Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Petr Kučera
- Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Michal Anděl
- Charles University, Third Faculty of Medicine, Prague, Czech Republic
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Lin Z, Wang Y, Zhang B, Jin Z. Association of type 2 diabetes susceptible genes GCKR, SLC30A8, and FTO polymorphisms with gestational diabetes mellitus risk: a meta-analysis. Endocrine 2018; 62:34-45. [PMID: 30091126 DOI: 10.1007/s12020-018-1651-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Accepted: 06/08/2018] [Indexed: 12/23/2022]
Abstract
PURPOSE Current studies have detected the correlation of polymorphisms in type 2 diabetes susceptible genes GCKR, SLC30A8 and FTO with gestational diabetes mellitus (GDM) risk. However, findings of these studies were incongruous. Hence, we performed an integrated review and meta-analysis for the researches regarding the association of single nucleotide polymorphisms (SNPs) in GCKR, SLC30A8 and FTO genes and GDM risk. METHODS Eligible publications were selected on the basis of several inclusion and exclusion criteria. Correlation between each SNP and GDM risk was estimated by computing odds ratios (ORs) with 95% confidence intervals (95%CIs). RESULTS Consequently, 19 case-control studies (from 16 citations) including 3636 GDM cases and 7229 GDM-free controls were participated in a meta-analysis of seven prevalent SNPs (GCKR rs1260326 and rs780094; SLC30A8 rs13266634 and rs11558471; FTO rs8050136, rs1421085 and rs9939609). Our results demonstrated that the rs780094, rs13266634 and rs9939609 SNPs were significantly associated with GDM risk. In stratified analysis, correlations of rs780094 and rs13266634 SNPs could be observed in Asian and Caucasian subgroups. Moreover, association between rs9939609 SNP and GDM risk was detected in Caucasian subgroup. CONCLUSIONS The GCKR rs780094, SLC30A8 rs13266634 and FTO rs9939609 SNPs were demonstrated to be the potential biomarkers for GDM risk prediction.
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Affiliation(s)
- Ziqi Lin
- Department of Obstetrics and Gynecology, Shengjing Hospital Affiliated to China Medical University, Shenyang, 110004, Liaoning, China
| | - Yue Wang
- Department of Obstetrics and Gynecology, Shengjing Hospital Affiliated to China Medical University, Shenyang, 110004, Liaoning, China
| | - Bao Zhang
- Department of Obstetrics and Gynecology, Shengjing Hospital Affiliated to China Medical University, Shenyang, 110004, Liaoning, China
| | - Zhen Jin
- Department of Obstetrics and Gynecology, Shengjing Hospital Affiliated to China Medical University, Shenyang, 110004, Liaoning, China.
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Molecular Biomarkers for Gestational Diabetes Mellitus. Int J Mol Sci 2018; 19:ijms19102926. [PMID: 30261627 PMCID: PMC6213110 DOI: 10.3390/ijms19102926] [Citation(s) in RCA: 64] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 09/21/2018] [Accepted: 09/22/2018] [Indexed: 12/20/2022] Open
Abstract
Gestational diabetes mellitus (GDM) is a growing public health problem worldwide. The condition is associated with perinatal complications and an increased risk for future metabolic disease in both mothers and their offspring. In recent years, molecular biomarkers received considerable interest as screening tools for GDM. The purpose of this review is to provide an overview of the current status of single-nucleotide polymorphisms (SNPs), DNA methylation, and microRNAs as biomarkers for GDM. PubMed, Scopus, and Web of Science were searched for articles published between January 1990 and August 2018. The search terms included “gestational diabetes mellitus”, “blood”, “single-nucleotide polymorphism (SNP)”, “DNA methylation”, and “microRNAs”, including corresponding synonyms and associated terms for each word. This review updates current knowledge of the candidacy of these molecular biomarkers for GDM with recommendations for future research avenues.
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Lindell N, Carlsson A, Josefsson A, Samuelsson U. Maternal obesity as a risk factor for early childhood type 1 diabetes: a nationwide, prospective, population-based case-control study. Diabetologia 2018; 61:130-137. [PMID: 29098322 PMCID: PMC6448943 DOI: 10.1007/s00125-017-4481-2] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Accepted: 09/25/2017] [Indexed: 12/15/2022]
Abstract
AIMS/HYPOTHESIS Genetic and environmental factors are believed to cause type 1 diabetes. The aim of this study was to investigate the influence of maternal BMI and gestational weight gain on the subsequent risk of childhood type 1 diabetes. METHODS Children in the Swedish National Quality Register for Diabetes in Children were matched with control children from the Swedish Medical Birth Register. Children were included whose mothers had data available on BMI in early pregnancy and gestational weight gain, giving a total of 16,179 individuals: 3231 children with type 1 diabetes and 12,948 control children. RESULTS Mothers of children with type 1 diabetes were more likely to be obese (9% [n = 292/3231] vs 7.7% [n = 991/12,948]; p = 0.02) and/or have diabetes themselves (2.8% [n = 90/3231] vs 0.8% [n = 108/12,948]; p < 0.001) compared with mothers of control children. Gestational weight gain did not differ significantly between the two groups of mothers. In mothers without diabetes, maternal obesity was a significant risk factor for type 1 diabetes in the offspring (p = 0.04). A child had an increased risk of developing type 1 diabetes if the mother had been obese in early pregnancy (crude OR 1.20; 95% CI 1.05, 1.38; adjusted OR 1.18; 95% CI 1.02, 1.36). Among children with type 1 diabetes (n = 3231) there was a difference (p < 0.001) in age at onset in relation to the mother's BMI. Among children in the oldest age group (15-19 years), there were more mothers who had been underweight during pregnancy, while in the youngest age group (0-4 years) the pattern was reversed. CONCLUSIONS/INTERPRETATION Maternal obesity, in the absence of maternal diabetes, is a risk factor for type 1 diabetes in the offspring, and influences the age of onset of type 1 diabetes. This emphasises the importance of a normal maternal BMI to potentially decrease the incidence of type 1 diabetes.
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Affiliation(s)
- Nina Lindell
- Department of Obstetrics and Gynaecology, Linköping University, S-581 85, Linköping, Sweden.
- Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
| | - Annelie Carlsson
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Lund, Sweden
| | - Ann Josefsson
- Department of Obstetrics and Gynaecology, Linköping University, S-581 85, Linköping, Sweden
- Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
| | - Ulf Samuelsson
- Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
- Division of Paediatrics, Linköping University, Linköping, Sweden
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