Exploring the multifaceted role of TGF-β signaling in diabetic complications.
Tarapati RanaAmit GuptaAayush SehgalSukhbir SinghNeelam SharmaMadhukar GargSaurabh BhatiaAhmed Al-HarrasiLotfi AleyaSimona BungauPublished in: Environmental science and pollution research international (2022)
Diabetes is one of the most comprehensive metabolic disorders and is spread across the globe. The data from IDF Diabetes Atlas and National Diabetes Statistics mentions that the number of patients with diabetes is increasing at an exponential rate which is challenging the current therapeutics used for the management of diabetes. However, current therapies used for the treatment may provide symptomatic relief but lack in preventing the progression of the disease and thereby limiting the treatment of diabetes-associated complications. A thorough review and analysis were conducted using various databases including EMBASE, MEDLINE, and Google Scholar to extract the available information on challenges faced by current therapies which have triggered the development of novel molecules or drugs. From the analysis, it was analyzed that transforming growth factor βs (TGF-βs) have been shown to exhibit pleiotropic activity and are responsible for maintaining homeostasis and its overexpression is convoluted in the pathogenesis of various disorders. Therefore, developing drugs that block TGF-β signaling may provide therapeutic benefits. This extensive review concluded that drugs targeting TGF-β signaling pathway and its subsequent blockade have shown promising results and hold the potential to become drugs of choice in the management of diabetes and associated complications.
Keyphrases
- transforming growth factor
- type diabetes
- cardiovascular disease
- glycemic control
- epithelial mesenchymal transition
- signaling pathway
- oxidative stress
- cell proliferation
- skeletal muscle
- healthcare
- metabolic syndrome
- risk assessment
- machine learning
- adipose tissue
- insulin resistance
- climate change
- quality improvement
- weight loss
- cancer therapy
- anti inflammatory
- drug delivery
- single cell
- human health
- data analysis
- deep learning