With the insufficient satisfaction rates and high cost of operative treatment for osteoarthritis (OA), alternatives have been sought. Furthermore, the inability of current medications to arrest disease progression has led to rapidly growing clinical research relating to mesenchymal stem cells (MSCs). The availability and function of MSCs vary according to tissue source. The three primary sources include the placenta, bone marrow, and adipose tissue, all of which offer excellent safety profiles. The primary mechanisms of action are trophic and immunomodulatory effects, which prevent the further degradation of joints. However, the function and degree to which benefits are observed vary significantly based on the exosomes secreted by MSCs. Paracrine and autocrine mechanisms prevent cell apoptosis and tissue fibrosis, initiate angiogenesis, and stimulate mitosis via growth factors. MSCs have even been shown to exhibit antimicrobial effects. Clinical results incorporating clinical scores and objective radiological imaging have been promising, but a lack of standardization in isolating MSCs prevents their incorporation in current guidelines.

AimTo assess the prevalence of actionable pharmacogenetic interventions in patients who underwent pharmacogenetic testing with a multi-gene panel. MethodsWe retrospectively reviewed single-center electronic health records. A total of 319 patients were enrolled who underwent pharmacogenomic testing with the RightMed test panel using TaqMan quantitative real-time PCR method and copy number variation analysis to determine the SNPs in the 27 target genes. ResultsActionable drug-gene pairs were found in 235 (73.7%) patients. Relevant guidelines on genotype-based prescribing were available for 133 (56.7%) patients at the time of testing. Based on the patients' genotype, 139 (43.6%) patients were using at least one drug with significant pharmacogenetic interactions. ConclusionTwo out of three patients had at least one drug-gene pair in their therapy. Further studies should assess the clinical effectiveness of integrating pharmacogenomic data into patients' electronic health records.