A combined in vivo and in silico model shows specific predictors of individual trans-generational diabetic programming. (18th June 2021)

• Record Type: Journal Article
• Authors: Eberle, Claudia; Ament, Christoph
• Is Part Of: Journal of developmental origins of health and disease. Volume 12:Number 3(2021)
• Page Start: 396
• Page End: 403
• Publication Date: 2021-06-18
• Subjects: gestational diabetes, -- hyperglycemia, -- trans-generational programming, -- Ins2Akita mouse model, -- in silico model, -- model-based predictors; Developmental biology -- Periodicals; Embryology, Human -- Periodicals; Disease susceptibility -- Periodicals; Prenatal influences -- Periodicals; Diseases -- Causes and theories of causation -- Periodicals; 612.64
• DOI: 10.1017/S2040174420000471
• Languages: English
• ISSNs: 2040-1744

Abstract

Abstract: Diabetic pregnancies are cleary associated with maternal type 2 diabetes and metabolic syndrome as well as atherosclerotic diseases in the offspring. The global prevalence of hyperglycemia in pregnancy was estimated as 15.8% of live births to women in 2019, with an upward trend. Numerous parental risk factors as well as trans-generational mechanisms targeting the utero-placental system, leading to diabetes, dysmetabolic and atherosclerotic conditions in the next generation, seem to be involved within this pathophysiological context. To focus on the predictable impact of trans-generational diabetic programming, we studied age- and gender-matched offspring of diabetic and nondiabetic mothers. The offspring generation consists of three groups: C57BL/6-J- Ins2 Akita (positive control group), wild-type C57BL/6-J- Ins2 Akita (experimental group), and C57BL/6-J mice (negative control group). We undertook intraperitoneal glucose tolerance tests at 3 and 11 weeks of age. Moreover, this in vivo model was complemented by a corresponding in silico model. Although at 3 weeks of age, no significant effects could be observed, we could demonstrate at 11 weeks of age characteristic and significant differences in relation to maternal diabetic imprinting based on the in silico model-based predictors. These predictors allow the generation of a concise classification tree assigning maternal diabetic imprinting correctly in 91% of study cases. Our data show that hyperglycemic in utero milieu contributes to trans-generational diabetic programming leading to impaired glucose tolerance in the offspring of diabetic mothers early on. These observations can be clearly and early distinguished from genetically determined diabetes, for example, type 1 diabetes, in which basal glucose values are significantly raised.