Advancements and challenges in generating accurate animal models of gestational diabetes mellitus.

Abstract

The maintenance of glucose homeostasis during pregnancy is critical to the health and well-being of both the mother and the developing fetus. Strikingly, approximately 7% of human pregnancies are characterized by insufficient insulin production or signaling, resulting in gestational diabetes mellitus (GDM). In addition to the acute health concerns of hyperglycemia, women diagnosed with GDM during pregnancy have an increased incidence of complications during pregnancy as well as an increased risk of developing type 2 diabetes (T2D) later in life. Furthermore, children born to mothers diagnosed with GDM have increased incidence of perinatal complications, including hypoglycemia, respiratory distress syndrome, and macrosomia, as well as an increased risk of being obese or developing T2D as adults. No single environmental or genetic factor is solely responsible for the disease; instead, a variety of risk factors, including weight, ethnicity, genetics, and family history, contribute to the likelihood of developing GDM, making the generation of animal models that fully recapitulate the disease difficult. Here, we discuss and critique the various animal models that have been generated to better understand the etiology of diabetes during pregnancy and its physiological impacts on both the mother and the fetus. Strategies utilized are diverse in nature and include the use of surgical manipulation, pharmacological treatment, nutritional manipulation, and genetic approaches in a variety of animal models. Continued development of animal models of GDM is essential for understanding the consequences of this disease as well as providing insights into potential treatments and preventative measures.

DOI: 10.1152/ajpendo.00425.2013

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Cite this paper

@article{Pasek2013AdvancementsAC, title={Advancements and challenges in generating accurate animal models of gestational diabetes mellitus.}, author={Raymond C. Pasek and Maureen A. Gannon}, journal={American journal of physiology. Endocrinology and metabolism}, year={2013}, volume={305 11}, pages={E1327-38} }