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Madhu SV. Prediction of gestational diabetes mellitus: are we ready for a biomarker lead screening strategy for GDM? Int J Diabetes Dev Ctries 2022. [DOI: 10.1007/s13410-022-01146-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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Alanen J, Appelblom H, Korpimaki T, Kouru H, Sairanen M, Gissler M, Ryynanen M, Nevalainen J. Glycosylated fibronectin as a first trimester marker for gestational diabetes. Arch Gynecol Obstet 2020; 302:853-860. [PMID: 32653948 PMCID: PMC7471182 DOI: 10.1007/s00404-020-05670-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Accepted: 06/25/2020] [Indexed: 12/17/2022]
Abstract
Purpose To evaluate the performance of first trimester maternal serum glycosylated (Sambucus nigra lectin-reactive) fibronectin in prediction of gestational diabetes mellitus (GDM).
Methods In this case–control study, first trimester maternal serum glycosylated fibronectin and fibronectin were measured in 19 women who consequently developed GDM and in 59 control women with normal pregnancy outcomes. Adiponectin was used as a reference protein to evaluate relation of glycoprotein to SNA-lectin-reactive assay format. Samples were taken during gestational weeks 9+6–11+6. Data concerning GDM was obtained from the National Institute for Health and Welfare, which records the pregnancy outcomes of all women in Finland. Results There was no difference in maternal serum glycosylated fibronectin concentrations between women with consequent GDM [447.5 μg/mL, interquartile range (IQR) 254.4–540.9 μg/mL] and control women (437.6 μg/mL, IQR 357.1–569.1 μg/mL). Maternal serum fibronectin levels were significantly lower in GDM group (224.2 μg/mL, IQR 156.8–270.6 μg/mL), compared to the control group (264.8 μg/mL, IQR 224.6–330.6 μg/mL, p < 0.01). There was no difference in assay formats for adiponectin. Conclusion There was no association between first trimester maternal serum glycosylated (SNA-reactive) fibronectin and GDM.
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Affiliation(s)
- Julia Alanen
- Department of Obstetrics and Gynecology, Medical Research Center, PEDEGO Research Unit, University of Oulu and Oulu University Hospital, PL 24, 90100 OYS, Oulu, Finland
| | | | | | | | | | - Mika Gissler
- National Institute for Health and Welfare, Helsinki, Finland
| | - Markku Ryynanen
- Department of Obstetrics and Gynecology, Medical Research Center, PEDEGO Research Unit, University of Oulu and Oulu University Hospital, PL 24, 90100 OYS, Oulu, Finland
| | - Jaana Nevalainen
- Department of Obstetrics and Gynecology, Medical Research Center, PEDEGO Research Unit, University of Oulu and Oulu University Hospital, PL 24, 90100 OYS, Oulu, Finland.
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Amirian A, Rahnemaei FA, Abdi F. Role of C-reactive Protein(CRP) or high-sensitivity CRP in predicting gestational diabetes Mellitus:Systematic review. Diabetes Metab Syndr 2020; 14:229-236. [PMID: 32247209 DOI: 10.1016/j.dsx.2020.02.004] [Citation(s) in RCA: 15] [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: 10/29/2019] [Revised: 02/06/2020] [Accepted: 02/07/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND AND AIMS Gestational Diabetes Mellitus (GDM) is the most common disorder during pregnancy in 8-18% of pregnancies. Due to maternal and neonatal morbidity and mortality, early diagnosis and appropriate treatment have always been of interest to researchers. One of the recent cases for early diagnosis of GDM is the size of the C-reactive protein (CRP). The purpose of this review study was to investigate the role of CRP or its high sensitivity type in predicting GDM. METHODS Systematic searching of MEDLINE, ISI Web of Science, PubMed, Scopus, Google Scholar, and ProQuest databases between 2009 and 2019 using keywords 'Gestational Diabetes Mellitus','Screening', 'C-reactive protein',' High sensitivity CRP'was performed. The quality of articles was also assessed using the STROBE checklist. RESULTS After a thorough search of the mentioned databases, 31 articles with the desired quality were finally selected. Most of studies showed significant relationship between CRP or high-sensitivity CRP(hs-CRP) level with GDMbutthe relationship was not significant in fewstudies. CONCLUSIONS Blood levels of CRP or hs-CRP could be used as a potential indicator for GDM, but more studies are needed.
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Affiliation(s)
- Azam Amirian
- Department of Midwifery, School of Nursing and Midwifery, Jiroft University of Medical Sciences, Jiroft, Iran
| | - Fatemeh Alsadat Rahnemaei
- Student Research Committee, Nursing and Midwifery Faculty, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fatemeh Abdi
- Social Determinants of Health Research Center, Alborz University of Medical Sciences, Karaj, Iran.
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Punnose J, Malhotra RK, Sukhija K, Mathew A, Sharma A, Choudhary N. Glycated haemoglobin in the first trimester: A predictor of gestational diabetes mellitus in pregnant Asian Indian women. Diabetes Res Clin Pract 2020; 159:107953. [PMID: 31794807 DOI: 10.1016/j.diabres.2019.107953] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 11/19/2019] [Accepted: 11/27/2019] [Indexed: 02/07/2023]
Abstract
AIM To assess the efficacy of first trimester glycated hemoglobin (HbA1c-FT) in diagnosing or predicting gestational diabetes mellitus (GDM) in Asian Indian women. METHODS This retrospective cohort study involved 2275 women who underwent both HbA1c-FT estimation and GDM screening with a one-step 75 g oral glucose tolerance test. Receiver Operating Characteristic (ROC) curve statistics were applied to assess the discriminative ability of HbA1c-FT in GDM diagnosis. A multivariable logistic regression analysis after adjusting for plausible confounders was used to evaluate the independent effect of HbA1c-FT on GDM diagnosis. RESULTS The mean HbA1c-FT of GDM (n = 578) and non-GDM women (n = 1697) were 5.04 + 0.04% and 4.9 + 0.37%, respectively (p < 0.001). Compared to women with a HbA1c-FT < 5.2%, the adjusted odds ratio to develop GDM of women with an HbA1c-FT range of 5.2-5.5% and those >5.6% to develop GDM were 1.627 (p < 0.004) and 2.6 (p < 0.001), respectively. The area under the ROC curve to detect GDM was 0.606 (95% CI: 0.519-0.633 p < 0.001), but the sensitivity and specificity of the HbA1c-FT were not sufficient to diagnose, rule in or rule out GDM. CONCLUSIONS HbA1c-FT is an independent GDM predictor in Asian Indian women but lacks sufficient sensitivity or specificity for use as a diagnostic test.
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Affiliation(s)
- John Punnose
- Department of Endocrinology, St. Stephen's Hospital, Delhi, India.
| | | | - Komal Sukhija
- Department of Endocrinology, St. Stephen's Hospital, Delhi, India
| | - Anu Mathew
- Department of Endocrinology, St. Stephen's Hospital, Delhi, India
| | - Asha Sharma
- Department of Obstetrics and Gynaecology, St. Stephen's Hospital, Delhi, India
| | - Naimaa Choudhary
- Department of Obstetrics and Gynaecology, St. Stephen's Hospital, Delhi, India
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Zhou T, Huang L, Wang M, Chen D, Chen Z, Jiang SW. A Critical Review of Proteomic Studies in Gestational Diabetes Mellitus. J Diabetes Res 2020; 2020:6450352. [PMID: 32724825 PMCID: PMC7381988 DOI: 10.1155/2020/6450352] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 06/18/2020] [Accepted: 06/30/2020] [Indexed: 12/16/2022] Open
Abstract
Gestational diabetes mellitus is a progressive and complex pregnancy complication, which threatens both maternal and fetal health. It is urgent to screen for specific biomarkers for early diagnosis and precise treatment, as well as to identify key moleculars to better understand the pathogenic mechanisms. In the present review, we comprehensively summarized recent studies of gestational diabetes using mass spectrometry-based proteomic technologies. Focused on the entire experimental design and proteomic results, we showed that these studies have covered a broad range of research contents in terms of sampling time, sample types, and outcome associations. Although most of the studies only stayed in the stage of initial discovery, several proteins were further verified to be efficient for disease diagnosis. Functional analysis of all the combined significant proteins also showed that a small number of proteins are known to be involved in the regulation of insulin or indirect signaling pathways. However, many factors such as diagnostic criteria, sample processing, proteomic method, and statistical method can greatly affect the identification of reproducible and reliable protein candidates. Thus, we further provided constructive suggestions and recommendations for carrying out proteomic or follow-up studies of gestational diabetes or other pregnancy complications in the future.
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Affiliation(s)
- Tao Zhou
- Research Institute for Reproductive Medicine and Genetic Diseases, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi 214002, China
| | - Lu Huang
- Department of Obstetrics, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi 214002, China
| | - Min Wang
- Centre for Reproductive Medicine, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi 214002, China
| | - Daozhen Chen
- Research Institute for Reproductive Medicine and Genetic Diseases, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi 214002, China
| | - Zhong Chen
- Department of Obstetrics, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi 214002, China
| | - Shi-Wen Jiang
- Research Institute for Reproductive Medicine and Genetic Diseases, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi 214002, China
- Centre for Reproductive Medicine, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi 214002, China
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Adam S, Pheiffer C, Dias S, Rheeder P. Association between gestational diabetes and biomarkers: a role in diagnosis. Biomarkers 2018; 23:386-391. [DOI: 10.1080/1354750x.2018.1432690] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Sumaiya Adam
- Department of Obstetrics and Gynaecology, University of Pretoria, Arcadia, South Africa
| | - Carmen Pheiffer
- Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg, South Africa
- Division of Medical Physiology, Faculty of Medicine and Health Sciences, University of Stellenbosch, Stellenbosch, South Africa
| | - Stephanie Dias
- Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg, South Africa
| | - Paul Rheeder
- Department of Internal Medicine, University of Pretoria, Arcadia, South Africa
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Zhu J, Chen Y, Li C, Tao M, Teng Y. The diagnostic value of glycated albumin in gestational diabetes mellitus. J Endocrinol Invest 2018; 41:121-128. [PMID: 28589381 PMCID: PMC5754373 DOI: 10.1007/s40618-016-0605-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2016] [Accepted: 12/27/2016] [Indexed: 01/10/2023]
Abstract
PURPOSE Our objective was to compare the diagnostic performance of glycated hemoglobin (HbA1c), GA, and fasting plasma glucose (FPG) for the diagnosis of GDM. METHODS Women at their late second or early third trimesters seen from October 2011 to April 2012 were studied. GDM was diagnosed based on oral glucose tolerance test results, and GA and HbA1c were measured at the same time. Patients were divided into two groups (with and without GDM), and areas under the receiver-operating characteristic curves (AUCs) were calculated to determine the diagnostic value of FPG, GA, and HbA1c. RESULTS A total of 698 women were included, of which 232 (33.2%) had GDM. Overall, FPG had the highest AUC for the detection of GDM, and was significantly higher than that of GA (0.692 vs. 0.568, p < 0.001) and HbA1c (0.692 vs. 0.619, p = 0.014). The AUC of FPG was significantly greater than that of GA and HbA1c. At 24-28 weeks' gestation, the AUCs of FPG were significantly greater than those of GA and HbA1c. CONCLUSIONS These results do not support the use of GA as a screening tool for GDM.
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Affiliation(s)
- Jieping Zhu
- Department of Obstetrics and Gynecology, Shanghai 6th People's Hospital, No 600 Yishan Road, Shanghai, 200233, China
| | - Yu Chen
- Department of Obstetrics and Gynecology, Shanghai 6th People's Hospital, No 600 Yishan Road, Shanghai, 200233, China
| | - Changbin Li
- Department of Obstetrics and Gynecology, Shanghai 6th People's Hospital, No 600 Yishan Road, Shanghai, 200233, China
| | - Minfang Tao
- Department of Obstetrics and Gynecology, Shanghai 6th People's Hospital, No 600 Yishan Road, Shanghai, 200233, China.
| | - Yincheng Teng
- Department of Obstetrics and Gynecology, Shanghai 6th People's Hospital, No 600 Yishan Road, Shanghai, 200233, China
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Mirghani Dirar A, Doupis J. Gestational diabetes from A to Z. World J Diabetes 2017; 8:489-511. [PMID: 29290922 PMCID: PMC5740094 DOI: 10.4239/wjd.v8.i12.489] [Citation(s) in RCA: 101] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2017] [Revised: 10/24/2017] [Accepted: 10/30/2017] [Indexed: 02/05/2023] Open
Abstract
Gestational diabetes mellitus (GDM) is defined as any degree of hyperglycaemia that is recognized for the first time during pregnancy. This definition includes cases of undiagnosed type 2 diabetes mellitus (T2DM) identified early in pregnancy and true GDM which develops later. GDM constitutes a greater impact on diabetes epidemic as it carries a major risk of developing T2DM to the mother and foetus later in life. In addition, GDM has also been linked with cardiometabolic risk factors such as lipid abnormalities, hypertensive disorders and hyperinsulinemia. These might result in later development of cardiovascular disease and metabolic syndrome. The understanding of the different risk factors, the pathophysiological mechanisms and the genetic factors of GDM, will help us to identify the women at risk, to develop effective preventive measures and to provide adequate management of the disease. Clinical trials have shown that T2DM can be prevented in women with prior GDM, by intensive lifestyle modification and by using pioglitazone and metformin. However, a matter of controversy surrounding both screening and management of GDM continues to emerge, despite several recent well-designed clinical trials tackling these issues. The aim of this manuscript is to critically review GDM in a detailed and comprehensive manner, in order to provide a scientific analysis and updated write-up of different related aspects.
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Affiliation(s)
- AbdelHameed Mirghani Dirar
- Prince Abdel Aziz Bin Musaad Hospital, Diabetes and Endocrinology Center, Arar 91421, North Zone Province, Saudi Arabia
| | - John Doupis
- Iatriko Paleou Falirou Medical Center, Division of Diabetes and Clinical Research Center, Athens 17562, Greece
- Postgraduate Diabetes Education, Institute of Molecular and Experimental Medicine, Cardiff University School of Medicine, Cardiff CF14 4XN, United Kingdom
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Zhao D, Shen L, Wei Y, Xie J, Chen S, Liang Y, Chen Y, Wu H. Identification of candidate biomarkers for the prediction of gestational diabetes mellitus in the early stages of pregnancy using iTRAQ quantitative proteomics. Proteomics Clin Appl 2017; 11. [PMID: 28220636 DOI: 10.1002/prca.201600152] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Revised: 02/08/2017] [Accepted: 02/17/2017] [Indexed: 12/16/2022]
Affiliation(s)
- Danqing Zhao
- Department of General Surgery; the Second Affiliated Hospital of Soochow University; Suzhou P. R. China
- Department of Obstetrics and Gynecology; Affiliated Hospital of Guizhou Medical University; Guiyang P. R. China
| | - Liming Shen
- College of Life Science and Oceanography; Shenzhen University; Shenzhen P. R. China
| | - Yan Wei
- School of Public Health; Guizhou Medical University; Guiyang P. R. China
| | - Jiaming Xie
- Department of General Surgery; the Second Affiliated Hospital of Soochow University; Suzhou P. R. China
| | - Shuqiang Chen
- Department of Obstetrics and Gynecology; Affiliated Hospital of Guizhou Medical University; Guiyang P. R. China
| | - Yi Liang
- Department of Obstetrics and Gynecology; Affiliated Hospital of Guizhou Medical University; Guiyang P. R. China
| | - Youjiao Chen
- College of Life Science and Oceanography; Shenzhen University; Shenzhen P. R. China
| | - Haorong Wu
- Department of General Surgery; the Second Affiliated Hospital of Soochow University; Suzhou P. R. China
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Gómez-Cardona EE, Hernández-Domínguez EE, Velarde-Salcedo AJ, Pacheco AB, Diaz-Gois A, De León-Rodríguez A, Barba de la Rosa AP. 2D-DIGE as a strategy to identify serum biomarkers in Mexican patients with Type-2 diabetes with different body mass index. Sci Rep 2017; 7:46536. [PMID: 28425473 PMCID: PMC5397846 DOI: 10.1038/srep46536] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Accepted: 03/22/2017] [Indexed: 12/11/2022] Open
Abstract
Obesity and type 2 diabetes(T2D) are the most prevalent and serious metabolic diseases affecting people worldwide. However racial and ethnic disparities seems to be a risk factor for their development. Mexico has been named as one of the largest populations with the highest prevalence of diabetes and obesity. The aim of this study was to identify novel T2D-associated proteins in Mexican patients. Blood samples were collected from 62 Mexican patients with T2D and they were grouped according to their body mass index(BMI). A panel of 10 diabetes and obesity serum markers was determined using MAGPIX. A comparative proteomics study was performed using two-dimensional difference in-gel electrophoresis(2D-DIGE) followed by mass spectrometry(LC-MS/MS). We detected 113 spots differentially accumulated, in which 64 unique proteins were identified, proteins that were involved in metabolism pathways, molecular transport, and cellular signalling. Four proteins(14-3-3, ApoH, ZAG, and OTO3) showing diabetes-related variation and also changes in relation to obesity were selected for further validation by western blotting. Our results reveal new diabetes related proteins present in the Mexican population. These could provide additional insight into the understanding of diabetes development in Mexican population and may also be useful candidate biomarkers.
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Affiliation(s)
- Erik E Gómez-Cardona
- IPICyT, Instituto Potosino de Investigación Científica y Tecnológica A.C. Camino a la Presa San Jose No. 2055, Lomas 4a sección, San Luis Potosí, San Luis Potosí, 78216, Mexico
| | - Eric E Hernández-Domínguez
- IPICyT, Instituto Potosino de Investigación Científica y Tecnológica A.C. Camino a la Presa San Jose No. 2055, Lomas 4a sección, San Luis Potosí, San Luis Potosí, 78216, Mexico
| | - Aída J Velarde-Salcedo
- IPICyT, Instituto Potosino de Investigación Científica y Tecnológica A.C. Camino a la Presa San Jose No. 2055, Lomas 4a sección, San Luis Potosí, San Luis Potosí, 78216, Mexico
| | - Alberto-Barrera- Pacheco
- IPICyT, Instituto Potosino de Investigación Científica y Tecnológica A.C. Camino a la Presa San Jose No. 2055, Lomas 4a sección, San Luis Potosí, San Luis Potosí, 78216, Mexico
| | - Agustín Diaz-Gois
- Juridiscción Sanitaria No. 1, Centros de Salud San Luis Potosi, San Luis Potosi, Mexico
| | - Antonio De León-Rodríguez
- IPICyT, Instituto Potosino de Investigación Científica y Tecnológica A.C. Camino a la Presa San Jose No. 2055, Lomas 4a sección, San Luis Potosí, San Luis Potosí, 78216, Mexico.,Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EH, UK
| | - Ana P Barba de la Rosa
- IPICyT, Instituto Potosino de Investigación Científica y Tecnológica A.C. Camino a la Presa San Jose No. 2055, Lomas 4a sección, San Luis Potosí, San Luis Potosí, 78216, Mexico
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Farrar D, Simmonds M, Bryant M, Lawlor DA, Dunne F, Tuffnell D, Sheldon TA. Risk factor screening to identify women requiring oral glucose tolerance testing to diagnose gestational diabetes: A systematic review and meta-analysis and analysis of two pregnancy cohorts. PLoS One 2017; 12:e0175288. [PMID: 28384264 PMCID: PMC5383279 DOI: 10.1371/journal.pone.0175288] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Accepted: 03/23/2017] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Easily identifiable risk factors including: obesity and ethnicity at high risk of diabetes are commonly used to indicate which women should be offered the oral glucose tolerance test (OGTT) to diagnose gestational diabetes (GDM). Evidence regarding these risk factors is limited however. We conducted a systematic review (SR) and meta-analysis and individual participant data (IPD) analysis to evaluate the performance of risk factors in identifying women with GDM. METHODS We searched MEDLINE, Medline in Process, Embase, Maternity and Infant Care and the Cochrane Central Register of Controlled Trials (CENTRAL) up to August 2016 and conducted additional reference checking. We included observational, cohort, case-control and cross-sectional studies reporting the performance characteristics of risk factors used to identify women at high risk of GDM. We had access to IPD from the Born in Bradford and Atlantic Diabetes in Pregnancy cohorts, all pregnant women in the two cohorts with data on risk factors and OGTT results were included. RESULTS Twenty nine published studies with 211,698 women for the SR and a further 14,103 women from two birth cohorts (Born in Bradford and the Atlantic Diabetes in Pregnancy study) for the IPD analysis were included. Six studies assessed the screening performance of guidelines; six examined combinations of risk factors; eight evaluated the number of risk factors and nine examined prediction models or scores. Meta-analysis using data from published studies suggests that irrespective of the method used, risk factors do not identify women with GDM well. Using IPD and combining risk factors to produce the highest sensitivities, results in low specificities (and so higher false positives). Strategies that use the risk factors of age (>25 or >30) and BMI (>25 or 30) perform as well as other strategies with additional risk factors included. CONCLUSIONS Risk factor screening methods are poor predictors of which pregnant women will be diagnosed with GDM. A simple approach of offering an OGTT to women 25 years or older and/or with a BMI of 25kg/m2 or more is as good as more complex risk prediction models. Research to identify more accurate (bio)markers is needed. Systematic Review Registration: PROSPERO CRD42013004608.
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Affiliation(s)
- Diane Farrar
- Bradford Institute for Health Research, Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, United Kingdom
- Department of Health Sciences, University of York, York, United Kingdom
| | - Mark Simmonds
- Centre for Reviews and Dissemination, University of York, York, United Kingdom
| | - Maria Bryant
- Bradford Institute for Health Research, Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, United Kingdom
- Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, United Kingdom
| | - Debbie A. Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Fidelma Dunne
- Galway Diabetes Research Centre (GDRC) and School of Medicine, National University of Ireland, Galway, Republic of Ireland
| | - Derek Tuffnell
- Bradford Women’s and Newborn Unit, Bradford, United Kingdom
| | - Trevor A. Sheldon
- Department of Health Sciences, University of York, York, United Kingdom
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12
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Cuffe JS, Xu ZC, Perkins AV. Biomarkers of oxidative stress in pregnancy complications. Biomark Med 2017; 11:295-306. [PMID: 28157383 DOI: 10.2217/bmm-2016-0250] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Pregnancy complications including pre-eclampsia, gestational-diabetes mellitus, preterm birth and intrauterine growth restriction can cause acute and chronic health problems for the mother and lead to fetal loss or dysregulation of infant physiology. The human placenta is susceptible to oxidative stress and oxidative damage in early gestation contributes to the onset of these conditions later in pregnancy. Current methods of predicting pregnancy complications are limited and although a large number of factors are associated with disease progression, few biomarkers have been used to aid in disease diagnosis early in gestation. This review discusses the detection of oxidative stress markers in biological fluids and highlights the need for further studies to validate their use in the prediction or diagnosis of pregnancy disorders.
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Affiliation(s)
- James Sm Cuffe
- School of Medical Science & Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Southport, Queensland 4222, Australia
| | - Ziheng Calvin Xu
- School of Medical Science & Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Southport, Queensland 4222, Australia
| | - Anthony V Perkins
- School of Medical Science & Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Southport, Queensland 4222, Australia
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13
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Cuffe JSM, Holland O, Salomon C, Rice GE, Perkins AV. Review: Placental derived biomarkers of pregnancy disorders. Placenta 2017; 54:104-110. [PMID: 28117143 DOI: 10.1016/j.placenta.2017.01.119] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2016] [Revised: 01/09/2017] [Accepted: 01/13/2017] [Indexed: 12/25/2022]
Abstract
Pregnancy is one of the greatest physiological challenges that a women can experience. The physiological adaptations that accompany pregnancy may increase the risk of developing a number of disorders that can lead to both acute and chronic physiological outcomes. In addition, fetal development may be impaired and, if the fetus survives, the child may be at an increased risk of disease throughout life. Pregnancy disorders are poorly predicted by traditional risk factors and maternal history alone. The identification of biomarkers that can predict incidence and severity of disease would allow for improved and targeted prophylactic therapies to prevent adverse maternal and fetal outcomes. Many of these pregnancy disorders, including preeclampsia, intrauterine growth restriction, gestational diabetes mellitus and preterm birth are known to be regulated at least in part by poor trophoblast invasion and/or dysregulated placental function. Cellular stress within the placenta increases the release of a number of factors into the maternal circulation. While many of these factors minimally impact maternal biology, others affect key physiological systems and contribute to disease. Importantly, these factors may be detected in physiological fluids and have predictive capacity making them ideal candidates as biomarkers of pregnancy disorders. This review will discuss what is known about these placental derived biomarkers of pregnancy disorders and highlight potential clinical opportunities for disease prediction and diagnosis.
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Affiliation(s)
- James S M Cuffe
- School of Medical Science, Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Southport, Queensland, Australia.
| | - Olivia Holland
- School of Medical Science, Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Southport, Queensland, Australia
| | - Carlos Salomon
- Exosome Biology Laboratory, Centre for Clinical Diagnostics, University of Queensland Centre for Clinical Research, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia; Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Ochsner Clinic Foundation, New Orleans, USA
| | - Gregory E Rice
- Exosome Biology Laboratory, Centre for Clinical Diagnostics, University of Queensland Centre for Clinical Research, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia; Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Ochsner Clinic Foundation, New Orleans, USA
| | - Anthony V Perkins
- School of Medical Science, Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Southport, Queensland, Australia
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Huhn EA, Fischer T, Göbl CS, Todesco Bernasconi M, Kreft M, Kunze M, Schoetzau A, Dölzlmüller E, Eppel W, Husslein P, Ochsenbein-Koelble N, Zimmermann R, Bäz E, Prömpeler H, Bruder E, Hahn S, Hoesli I. Screening of gestational diabetes mellitus in early pregnancy by oral glucose tolerance test and glycosylated fibronectin: study protocol for an international, prospective, multicentre cohort trial. BMJ Open 2016; 6:e012115. [PMID: 27733413 PMCID: PMC5073542 DOI: 10.1136/bmjopen-2016-012115] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
INTRODUCTION As the accurate diagnosis and treatment of gestational diabetes mellitus (GDM) is of increasing importance; new diagnostic approaches for the assessment of GDM in early pregnancy were recently suggested. We evaluate the diagnostic power of an 'early' oral glucose tolerance test (OGTT) 75 g and glycosylated fibronectin (glyFn) for GDM screening in a normal cohort. METHODS AND ANALYSIS In a prospective cohort study, 748 singleton pregnancies are recruited in 6 centres in Switzerland, Austria and Germany. Women are screened for pre-existing diabetes mellitus and GDM by an 'early' OGTT 75 g and/or the new biomarker, glyFn, at 12-15 weeks of gestation. Different screening strategies are compared to evaluate the impact on detection of GDM by an OGTT 75 g at 24-28 weeks of gestation as recommended by the International Association of Diabetes and Pregnancy Study Groups (IADPSG). A new screening algorithm is created by using multivariable risk estimation based on 'early' OGTT 75 g and/or glyFn results, incorporating maternal risk factors. Recruitment began in May 2014. ETHICS AND DISSEMINATION This study received ethical approval from the ethics committees in Basel, Zurich, Vienna, Salzburg and Freiburg. It was registered under http://www.ClinicalTrials.gov (NCT02035059) on 12 January 2014. Data will be presented at international conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER NCT02035059.
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Affiliation(s)
- E A Huhn
- Department of Obstetrics and Gynaecology, University Hospital Basel, Basel, Switzerland
| | - T Fischer
- Department of Obstetrics and Gynaecology, Salzburger Landeskrankenhaus, Paracelsus Medical University, Salzburg, Austria
| | - C S Göbl
- Division of Obstetrics and Feto-maternal Medicine, Department of Obstetrics and Gynaecology, Medical University of Vienna, Vienna, Austria
| | - M Todesco Bernasconi
- Department of Obstetrics and Gynaecology, Cantonal Hospital Aarau, Aarau, Switzerland
| | - M Kreft
- Department of Obstetrics and Gynaecology, University Hospital Zurich, Zurich, Switzerland
| | - M Kunze
- Department of Obstetrics and Gynaecology, University Hospital Freiburg, Freiburg, Germany
| | - A Schoetzau
- Department of Obstetrics and Gynaecology, University Hospital Basel, Basel, Switzerland
| | - E Dölzlmüller
- Department of Obstetrics and Gynaecology, Salzburger Landeskrankenhaus, Paracelsus Medical University, Salzburg, Austria
| | - W Eppel
- Division of Obstetrics and Feto-maternal Medicine, Department of Obstetrics and Gynaecology, Medical University of Vienna, Vienna, Austria
| | - P Husslein
- Division of Obstetrics and Feto-maternal Medicine, Department of Obstetrics and Gynaecology, Medical University of Vienna, Vienna, Austria
| | - N Ochsenbein-Koelble
- Department of Obstetrics and Gynaecology, University Hospital Zurich, Zurich, Switzerland
| | - R Zimmermann
- Department of Obstetrics and Gynaecology, University Hospital Zurich, Zurich, Switzerland
| | - E Bäz
- Department of Obstetrics and Gynaecology, University Hospital Freiburg, Freiburg, Germany
| | - H Prömpeler
- Department of Obstetrics and Gynaecology, University Hospital Freiburg, Freiburg, Germany
| | - E Bruder
- Department of Pathology, University Hospital Basel, Basel, Switzerland
| | - S Hahn
- Department of Biomedicine, Laboratory of Perinatology, University Basel, Basel, Switzerland
| | - I Hoesli
- Department of Obstetrics and Gynaecology, University Hospital Basel, Basel, Switzerland
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Zhao W, Pan J, Li H, Huang Y, Liu F, Tao M, Jia W. Relationship between High Serum Cystatin C Levels and the Risk of Gestational Diabetes Mellitus. PLoS One 2016; 11:e0147277. [PMID: 26849560 PMCID: PMC4743926 DOI: 10.1371/journal.pone.0147277] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2015] [Accepted: 01/02/2016] [Indexed: 11/21/2022] Open
Abstract
Aims Serum cystatin C (CysC) has recently been shown to be associated with the incidence of type 2 diabetes mellitus (T2DM) and progression to the pre-diabetic state. The aim of this study was to explore the relationship between serum CysC and the risk of gestational diabetes mellitus (GDM) in Chinese pregnant women. Methods This cross-sectional study consisted of 400 pregnant women including111 with GDM and 289 with normal glucose tolerance at 24–28 weeks of gestation. The subjects were further divided into four groups according to the CysC quartiles, and their clinical characteristics were compared. The serum CysC concentration was measured using immunoturbidimetry and the degree of insulin resistance was assessed by the homeostasis model assessment of insulin resistance (HOMA-IR). Results Serum CysC levels were significantly higher in pregnant women with GDM than in the healthy pregnant women[1.0(0.8–1.8) vs 0.7(0.6–1.0), P<0.01). The Spearman’s correlation analysis showed that serum CysC was positively associated with HOMA-IR(r = 0.118, P<0.05) and the occurrence of GDM(r = 0.348, P<0.01). The pregnant women were divided into quartiles according to their serum CysC concentrations. Compared to the first quartile, pregnant women in Q2 (OR, 2.441; P = 0.025), Q3 (OR, 3.383; P = 0.001) and Q4 (OR, 5.516; P<0.001) had higher risk of GDM after adjusted for age, BMI, HbA1c and HOMA-IR. Further, with a rise in the serum CysC, there was an increasing trend in the HOMA-IR levels (P<0.05). A binary logistic regression analysis after adjusting for other confounding variables revealed a significant and independent association between serum CysC and GDM [OR = 14.269; 95% confidence interval, 4.977–40.908, P<0.01].The receiver operating characteristic curve analysis revealed that the optimal cutoff point for serum CysC to indicate GDM was 0.95mg/L. Conclusions Serum CysC is significantly and independently associated with insulin resistance and GDM. It may be a helpful biomarker to identify the risk of GDM in Chinese pregnant women.
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Affiliation(s)
- Weijing Zhao
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Jiao-Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Medical Center of Diabetes, Shanghai Key Clinical Center of Metabolic Diseases, Shanghai Institute for Diabetes, Shanghai, China
| | - Jiemin Pan
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Jiao-Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Medical Center of Diabetes, Shanghai Key Clinical Center of Metabolic Diseases, Shanghai Institute for Diabetes, Shanghai, China
| | - Huaping Li
- Department of Obstetrics and Gynecology, Shanghai Jiao-Tong University Affiliated Sixth People’s Hospital, Shanghai, China
| | - Yajuan Huang
- Department of Obstetrics and Gynecology, Shanghai Jiao-Tong University Affiliated Sixth People’s Hospital, Shanghai, China
- * E-mail: (FL); (YH)
| | - Fang Liu
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Jiao-Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Medical Center of Diabetes, Shanghai Key Clinical Center of Metabolic Diseases, Shanghai Institute for Diabetes, Shanghai, China
- * E-mail: (FL); (YH)
| | - Minfang Tao
- Department of Obstetrics and Gynecology, Shanghai Jiao-Tong University Affiliated Sixth People’s Hospital, Shanghai, China
| | - Weiping Jia
- Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Jiao-Tong University Affiliated Sixth People’s Hospital, Shanghai Clinical Medical Center of Diabetes, Shanghai Key Clinical Center of Metabolic Diseases, Shanghai Institute for Diabetes, Shanghai, China
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Singh A, Subramani E, Datta Ray C, Rapole S, Chaudhury K. Proteomic-driven biomarker discovery in gestational diabetes mellitus: a review. J Proteomics 2015. [PMID: 26216595 DOI: 10.1016/j.jprot.2015.07.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance with onset or first recognition during pregnancy and it affects 18% of pregnant women worldwide. GDM is considered a high-risk state which may lead to type II diabetes which is associated with an increase in a number of interrelated adverse perinatal outcomes. Given the fact that the progress of a successful pregnancy is dependent on the intricate communication between several biological molecules, identification of the proteomic profile perturbations in women with GDM is expected to help in understanding the disease pathogenesis and also discovery of clinical biomarker(s). In recent years, both gel-free and gel-based proteomics have been extensively investigated for improving maternal and child health. Although there are several reports integrating various aspects of proteomics in pregnancy related diseases such as preeclampsia, extensive Pubmed search shows no review so far on the application of proteomics in gestational diabetes. In this review, we focus on various high-throughput proteomic technologies for the identification of unique biosignatures and biomarkers responsible for the early prediction of GDM. Further, different analytical strategies and biological samples involved in proteomic analysis of this pregnancy-related disease are discussed.This article is part of a Special Issue entitled: Proteomics in India.
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Affiliation(s)
- Apoorva Singh
- School of Medical Science and Technology, Indian Institute of Technology, Kharagpur, West Bengal, India
| | - Elavarasan Subramani
- School of Medical Science and Technology, Indian Institute of Technology, Kharagpur, West Bengal, India
| | - Chaitali Datta Ray
- Department of Obstetrics & Gynecology, Institute of Post Graduate Medical Education & Research, Kolkata, West Bengal, India
| | - Srikanth Rapole
- Proteomics Lab, National Centre for Cell Science, Ganesh khind, Pune, Maharashtra, India
| | - Koel Chaudhury
- School of Medical Science and Technology, Indian Institute of Technology, Kharagpur, West Bengal, India.
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