Singh Gurinderdeep, Darwin Ronald, Panda Krishna Chandra, Afzal Shaikh Amir, Katiyar Shashwat, Dhakar Ram C, Mani Sangeetha
Department of Pharmaceutical Sciences and Drug Research, Punjabi University Patiala, Patiala, India.
School of Pharmaceutical Sciences, Vels Institute of Science Technology & Advanced Studies, Chennai, India.
J Biomater Sci Polym Ed. 2025 Jul;36(10):1466-1501. doi: 10.1080/09205063.2024.2445376. Epub 2024 Dec 27.
Osteoporosis is well noted to be a universal ailment that realization impaired bone mass and micro architectural deterioration thus enhancing the probability of fracture. Despite its high incidence, its management remains highly demanding because of the multifactorial pathophysiology of the disease. This review highlights recent findings in the management of osteoporosis particularly, gene expression and hormonal control. Some of the newest approaches regarding the subject are described, including single-cell RNA sequencing and long non-coding RNAs. Also, the review reflects new findings on hormonal signaling and estrogen and parathyroid hormone; patient-specific approaches due to genetic and hormonal variation. Potential new biomarkers and AI comprised as factors for improving the ability to anticipate and manage fractures. These hold great potential of new drugs, combination therapies and gene based therapies for osteoporosis in the future. Further studies and cooperation of scientists and clinicians will help to apply such novelties into practical uses in the sphere of medicine in order to enhance the treatment of patients with osteoporosis.
骨质疏松症是一种广为人知的全身性疾病,其特征是骨量减少和微结构恶化,从而增加了骨折的可能性。尽管其发病率很高,但由于该疾病的多因素病理生理学,其治疗仍然极具挑战性。本综述重点介绍了骨质疏松症治疗方面的最新研究成果,特别是基因表达和激素调控。文中描述了一些关于该主题的最新方法,包括单细胞RNA测序和长链非编码RNA。此外,该综述还反映了激素信号传导以及雌激素和甲状旁腺激素方面的新发现;由于遗传和激素变异而采用的针对患者个体的方法。潜在的新生物标志物和人工智能作为改善骨折预测和管理能力的因素。这些在未来的骨质疏松症新药、联合疗法和基因疗法方面具有巨大潜力。科学家和临床医生的进一步研究与合作将有助于将这些新成果应用于医学领域的实际应用中,以加强对骨质疏松症患者的治疗。