Large animal models for Duchenne muscular dystrophy (DMD) are crucial for evaluation of diagnostic procedures and treatment strategies. Pigs cloned from male cells lacking DMD exon 52 (DMDΔ52) resemble molecular, clinical and pathological hallmarks of DMD, but die before sexual maturity and cannot be propagated by breeding. Therefore, we generated female DMD+/- carriers. A single founder animal had 11 litters with 29 DMDY/-, 34 DMD+/- as well as 36 male and 29 female wild-type offspring. Breeding with F1 and F2 DMD+/- carriers resulted in additional 114 DMDY/- piglets. With intensive neonatal management, the majority survived for 3-4 months, providing statistically relevant cohorts for experimental studies. Pathological investigations and proteome studies of skeletal muscles and myocardium confirmed the resemblance of human disease mechanisms. Importantly, DMDY/- pigs reveal progressive myocardial fibrosis and increased expression of connexin-43, associated with significantly reduced left ventricular ejection fraction already at age 3 months. Furthermore, behavioral tests provided evidence for impaired cognitive ability. Our breeding cohort of DMDΔ52 pigs and standardized tissue repositories provide important resources for studying DMD disease mechanisms and for testing novel treatment strategies.

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Worldwide, gestational diabetes affects 2–25% of pregnancies. Due to related disturbances of the maternal metabolism during the periconceptional period and pregnancy, children bear an increased risk for future diseases. It is well known that an aberrant intrauterine environment caused by elevated maternal glucose levels is related to elevated risks for increased birth weights and metabolic disorders in later life, such as obesity or type 2 diabetes. The complexity of disturbances induced by maternal diabetes, with multiple underlying mechanisms, makes early diagnosis or prevention a challenging task. Omics technologies allowing holistic quantification of several classes of molecules from biological fluids, cells, or tissues are powerful tools to systematically investigate the effects of maternal diabetes on the offspring in an unbiased manner. Differentially abundant molecules or distinct molecular profiles may serve as diagnostic biomarkers, which may also support the development of preventive and therapeutic strategies. In this review, we summarize key findings from state-of-the-art Omics studies addressing the impact of maternal diabetes on offspring health.

Adipose tissue (AT) is no longer considered to be responsible for energy storage only but is now recognized as a major endocrine organ that is distributed across different parts of the body and is actively involved in regulatory processes controlling energy homeostasis. Moreover, AT plays a crucial role in the development of metabolic disease such as diabetes. Recent evidence has shown that adipokines have the ability to regulate blood glucose levels and improve metabolic homeostasis. While AT has been studied extensively in the context of type 2 diabetes, less is known about how different AT types are affected by absolute insulin deficiency in type 1 or permanent neonatal diabetes mellitus. Here, we analyzed visceral and subcutaneous AT in a diabetic, insulin-deficient pig model (MIDY) and wild-type (WT) littermate controls by RNA sequencing and quantitative proteomics. Multi-omics analysis indicates a depot-specific dysregulation of crucial metabolic pathways in MIDY AT samples. We identified key proteins involved in glucose uptake and downstream signaling, lipogenesis, lipolysis and β-oxidation to be differentially regulated between visceral and subcutaneous AT in response to insulin deficiency. Proteins related to glycogenolysis, pyruvate metabolism, TCA cycle and lipogenesis were increased in subcutaneous AT, whereas β-oxidation-related proteins were increased in visceral AT from MIDY pigs, pointing at a regionally different metabolic adaptation to master energy stress arising from diminished glucose utilization in MIDY AT. Chronic, absolute insulin deficiency and hyperglycemia revealed fat depot-specific signatures using multi-omics analysis. The generated datasets are a valuable resource for further comparative and translational studies in clinical diabetes research.