Prevalence of gestational diabetes mellitus in women with a family history of type 2 diabetes in first- and second-degree relatives

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Abstract

Aims

A family history of type 2 diabetes mellitus (T2DM) markedly increases an individual's lifetime risk of developing the disease. For gestational diabetes (GDM), this risk factor is less well characterized. This study aimed to investigate the relationship between family history of T2DM in first- and second-degree relatives in women with GDM and the differences in metabolic characteristics at early gestation.

Methods

This prospective cohort study included 1129 pregnant women. A broad risk evaluation was performed before 16 + 0 weeks of gestation, including a detailed family history of the different types of diabetes and a laboratory examination of glucometabolic parameters. Participants were followed up until delivery and GDM assessed according to the latest diagnosis criteria.

Results

We showed that pregnant women with first- (FHD1, 26.6%, OR 1.91, 95%CI 1.16 to 3.16, p = 0.005), second- (FHD2, 26.3%, OR 1.88, 95%CI 1.16 to 3.05, p = 0.005) or both first- and second-degree relatives with T2DM (FHD1 + D2, 33.3%, OR 2.64, 95%CI 1.41 to 4.94, p < 0.001) had a markedly increased risk of GDM compared to those with negative family history (FHN) ( n = 100, 15.9%). The association was strongest if both parents were affected (OR 4.69, 95%CI 1.33 to 16.55, p = 0.009). Women with FHD1 and FHD1 + D2 had adverse glucometabolic profiles already in early pregnancy.

Conclusions

Family history of T2DM is an important risk factor for GDM, also by applying the current diagnostic criteria. Furthermore, we showed that the degree of kinship plays an essential role in quantifying the risk already at early pregnancy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00592-022-02011-w.

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Most cited references 28

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Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

D. Matthews, J Hosker, A Rudenski … (1985)

The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.

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Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.

S Nambi, K Mather, A. Katz … (2000)

Insulin resistance plays an important role in the pathophysiology of diabetes and is associated with obesity and other cardiovascular risk factors. The "gold standard" glucose clamp and minimal model analysis are two established methods for determining insulin sensitivity in vivo, but neither is easily implemented in large studies. Thus, it is of interest to develop a simple, accurate method for assessing insulin sensitivity that is useful for clinical investigations. We performed both hyperinsulinemic isoglycemic glucose clamp and insulin-modified frequently sampled iv glucose tolerance tests on 28 nonobese, 13 obese, and 15 type 2 diabetic subjects. We obtained correlations between indexes of insulin sensitivity from glucose clamp studies (SI(Clamp)) and minimal model analysis (SI(MM)) that were comparable to previous reports (r = 0.57). We performed a sensitivity analysis on our data and discovered that physiological steady state values [i.e. fasting insulin (I(0)) and glucose (G(0))] contain critical information about insulin sensitivity. We defined a quantitative insulin sensitivity check index (QUICKI = 1/[log(I(0)) + log(G(0))]) that has substantially better correlation with SI(Clamp) (r = 0.78) than the correlation we observed between SI(MM) and SI(Clamp). Moreover, we observed a comparable overall correlation between QUICKI and SI(Clamp) in a totally independent group of 21 obese and 14 nonobese subjects from another institution. We conclude that QUICKI is an index of insulin sensitivity obtained from a fasting blood sample that may be useful for clinical research.

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The Pathophysiology of Gestational Diabetes Mellitus

Jasmine Plows, Joanna L. Stanley, Philip N. Baker … (2018)

Gestational diabetes mellitus (GDM) is a serious pregnancy complication, in which women without previously diagnosed diabetes develop chronic hyperglycemia during gestation. In most cases, this hyperglycemia is the result of impaired glucose tolerance due to pancreatic β-cell dysfunction on a background of chronic insulin resistance. Risk factors for GDM include overweight and obesity, advanced maternal age, and a family history or any form of diabetes. Consequences of GDM include increased risk of maternal cardiovascular disease and type 2 diabetes and macrosomia and birth complications in the infant. There is also a longer-term risk of obesity, type 2 diabetes, and cardiovascular disease in the child. GDM affects approximately 16.5% of pregnancies worldwide, and this number is set to increase with the escalating obesity epidemic. While several management strategies exist—including insulin and lifestyle interventions—there is not yet a cure or an efficacious prevention strategy. One reason for this is that the molecular mechanisms underlying GDM are poorly defined. This review discusses what is known about the pathophysiology of GDM, and where there are gaps in the literature that warrant further exploration.

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Author and article information

Contributors

Christian S. Göbl:

ORCID: http://orcid.org/0000-0002-3922-7443

christian.goebl@meduniwien.ac.at

Journal

Journal ID (nlm-ta): Acta Diabetol

Journal ID (iso-abbrev): Acta Diabetol

Title: Acta Diabetologica

Publisher: Springer Milan (Milan )

ISSN (Print): 0940-5429

ISSN (Electronic): 1432-5233

Publication date (Electronic): 12 December 2022

Publication date PMC-release: 12 December 2022

Publication date (Print): 2023

Volume: 60

Issue: 3

Pages: 345-351

Affiliations

[1 ]GRID grid.410567.1, Department of Obstetrics and Gynaecology, , University Hospital Basel, ; Basel, Switzerland

[2 ]GRID grid.22937.3d, ISNI 0000 0000 9259 8492, Department of Obstetrics and Gynaecology, , Medical University of Vienna, ; Waehringer Guertel 18-20, 1090 Vienna, Austria

[3 ]GRID grid.418879.b, ISNI 0000 0004 1758 9800, Metabolic Unit, , CNR Institute of Neuroscience, ; Padua, Italy

Author notes

This paper belongs in the Topical Collection “Pregnancy and Diabetes”, Managed by Marina Scavini and Antonio Secchi.

Author information

Cécile Monod http://orcid.org/0000-0001-5914-4517

Grammata Kotzaeridi http://orcid.org/0000-0002-1286-2607

Tina Linder http://orcid.org/0000-0001-5929-1285

Ingo Rosicky http://orcid.org/0000-0002-4443-2505

Valeria Filippi http://orcid.org/0000-0002-4281-0517

Andrea Tura http://orcid.org/0000-0003-3466-5900

Irene Hösli http://orcid.org/0000-0002-6209-8344

Christian S. Göbl http://orcid.org/0000-0002-3922-7443

Article

Publisher ID: 2011

DOI: 10.1007/s00592-022-02011-w

PMC ID: 9931850

PubMed ID: 36508047

SO-VID: 9d56c5a2-c773-49d5-b9f0-0b2dd31942e1

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 2 September 2022

Date accepted : 29 November 2022

Funding

Funded by: Medical University of Vienna

Open Access :

Open access funding provided by Medical University of Vienna.

Custom metadata

ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: gestational diabetes,type 2 diabetes mellitus,family history,degree of kinship

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ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: gestational diabetes, type 2 diabetes mellitus, family history, degree of kinship

Prevalence of gestational diabetes mellitus in women with a family history of type 2 diabetes in first- and second-degree relatives

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Supplementary Information

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Journal of the ASEAN Federation of Endocrine Societies

Most cited references 28

Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.

The Pathophysiology of Gestational Diabetes Mellitus

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