Effect of Drugs Used in Pharmacotherapy of Type 2 Diabetes on Bone Density and Risk of Bone Fractures.
Agnieszka WikarekMałgorzata GrabarczykKatarzyna KlimekAgata Janoska-GawrońskaMagdalena SuchodolskaHolecki MichałPublished in: Medicina (Kaunas, Lithuania) (2024)
This review summarizes the complex relationship between medications used to treat type 2 diabetes and bone health. T2DM patients face an increased fracture risk despite higher bone mineral density; thus, we analyzed the impact of key drug classes, including Metformin, Sulphonylureas, SGLT-2 inhibitors, DPP-4 inhibitors, GLP-1 agonists, and Thiazolidinediones. Metformin, despite promising preclinical results, lacks a clear consensus on its role in reducing fracture risk. Sulphonylureas present conflicting data, with potential neutral effects on bone. SGLT-2 inhibitors seem to have a transient impact on serum calcium and phosphorus, but evidence on their fracture association is inconclusive. DPP-4 inhibitors emerge as promising contributors to bone health, and GLP-1 agonists exhibit positive effects on bone metabolism, reducing fracture risk. Thiazolidinediones, however, demonstrate adverse impacts on bone, inducing loss through mesenchymal stem cell effects. Insulin presents a complex relationship with bone health. While it has an anabolic effect on bone mineral density, its role in fracture risk remains inconsistent. In conclusion, a comprehensive understanding of diabetes medications' impact on bone health is crucial. Further research is needed to formulate clear guidelines for managing bone health in diabetic patients, considering individual profiles, glycemic control, and potential medication-related effects on bone.
Keyphrases
- bone mineral density
- postmenopausal women
- type diabetes
- glycemic control
- body composition
- healthcare
- public health
- soft tissue
- mental health
- bone loss
- bone regeneration
- cardiovascular disease
- chronic kidney disease
- insulin resistance
- end stage renal disease
- emergency department
- human health
- deep learning
- risk assessment
- health promotion
- ejection fraction
- big data
- weight loss
- clinical practice
- subarachnoid hemorrhage
- artificial intelligence