Guidelines for in vivo models of developmental programming of cardiovascular disease risk

Abstract

Research using animals depends on the generation of offspring for use in experiments or for the maintenance of animal colonies. Although not considered by all, several different factors preceding and during pregnancy, as well as during lactation, can program various characteristics in the offspring. Here, we present the most common models of developmental programming of cardiovascular outcomes, important considerations for study design, and provide guidelines for producing and reporting rigorous and reproducible cardiovascular studies in offspring exposed to normal conditions or developmental insult. These guidelines provide considerations for the selection of the appropriate animal model and factors that should be reported to increase rigor and reproducibility while ensuring transparent reporting of methods and results.

Keywords: chronic disease; developmental insult; fetal growth restriction; offspring; pregnancy.

Figure 1.

Different preclinical models of developmental insult used in the literature. Models include adverse pregnancy conditions (hypertensive disorders of pregnancy and gestational diabetes), maternal under- or overnutrition, and environmental exposures. AVP, arginine vasopressin; BPH/5, blood pressure high 5; GC, glucocorticoids; RUPP, reduced uterine perfusion pressure; STZ, streptozotocin. Created using a licensed version of BioRender.com.

Figure 2.

Risk and complications of gestational diabetes (GD) in exposed mothers and offspring. Diabetes during pregnancy poses risks for both the mother and the exposed offspring. Risks can manifest during the index pregnancy, later life for mother, and all stages of development for the offspring. Created using a licensed version of BioRender.com.

Figure 3.

Preclinical models of diabetes during pregnancy. Experimental models of diabetes-induced programming of cardiovascular diseases range from in vitro to in vivo models. Both pregestational and gestational diabetes can be modeled in vivo based on the timing of interventions that produce diabetes-like conditions. GD, gestational diabetes. Created using a licensed version of BioRender.com.