Application of Induced Pluripotent Stem Cells for Disease Modeling and 3D Model Construction: Focus on Osteoarthritis

• Published in: Cells (Basel, Switzerland) Vol. 10; no. 11; p. 3032
• Main Authors: Hwang, Joel Jihwan, Choi, Jinhyeok, Rim, Yeri Alice, Nam, Yoojun, Ju, Ji Hyeon
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 05.11.2021; MDPI
• Subjects: Age; Alzheimer's disease; Arthritis; Cartilage; Cell Differentiation; Clinical trials; disease modeling; Drug screening; Ethics; Etiology; Fibroblasts; Gene expression; Genomes; Heart rate; Humans; induced pluripotent stem cell; Induced Pluripotent Stem Cells - pathology; Joint diseases; Models, Biological; Obesity; Osteoarthritis; Osteoarthritis - pathology; Pathogenesis; Phenotypes; Pluripotency; Review; Risk assessment; Stem cells; Transcription factors; induced pluripotent stem cell; osteoarthritis; disease modeling
• ISSN: 2073-4409; 2073-4409
• DOI: 10.3390/cells10113032

Since their discovery in 2006, induced pluripotent stem cells (iPSCs) have shown promising potential, specifically because of their accessibility and plasticity. Hence, the clinical applicability of iPSCs was investigated in various fields of research. However, only a few iPSC studies pertaining to osteoarthritis (OA) have been performed so far, despite the high prevalence rate of degenerative joint disease. In this review, we discuss some of the most recent applications of iPSCs in disease modeling and the construction of 3D models in various fields, specifically focusing on osteoarthritis and OA-related conditions. Notably, we comprehensively reviewed the successful results of iPSC-derived disease models in recapitulating OA phenotypes for both OA and early-onset OA to encompass their broad etiology. Moreover, the latest publications with protocols that have used iPSCs to construct 3D models in recapitulating various conditions, particularly the OA environment, were further discussed. With the overall optimistic results seen in both fields, iPSCs are expected to be more widely used for OA disease modeling and 3D model construction, which could further expand OA drug screening, risk assessment, and therapeutic capabilities.