In a recent study published in The Lancet EBioMedicine , a team of scientists used Mendelian Randomization analyses to explore whether antidiabetic medications could potentially be used as disease-modifying osteoarthritis drugs or DMOADs for the therapeutic management of osteoarthritis. Study: Exploring antidiabetic drug targets as potential disease-modifying agents in osteoarthritis . Image Credit: Peter Porrini/Shutterstock.
com Background Osteoarthritis is a disease that affects the joints. It is characterized by the progressive degradation of the cartilage in the joints, inflammation, and subchondral bone remodeling. Various biochemical processes and biomechanical forces contribute to the etiology of this prevalent form of arthritis.
Despite the pain and morbidity of osteoarthritis, which contribute substantially to limiting normal function and disability, there are no effective DMOADs to retard or reverse the progression of joint degeneration. However, recent research has shown that metabolic dysregulation could be a major contributor to the progression of the disease, indicating an interplay between osteoarthritis and metabolic syndromes. Evidence from local and systemic-level interactions shows that hyperglycemia could influence osteoarthritis, and the accumulation of the end products of glycation and oxidative stress is also believed to contribute to cartilage damage.
These findings have highlighted the potential use of antidiabetic medications to influence or modify the pathways involved in joint health. About the study In the present study, the researchers employed a Mendelian Randomization approach, which uses genetic variants in the form of single nucleotide polymorphisms (SNPs) to examine causal relationships to determine whether antidiabetic medications could play a potential role as DMOADs. Previous research has explored metformin's impact on osteoarthritis and found that the drug can modulate the homeostasis of the cartilage matrix and control inflammatory responses.
Related Stories Angiotensin receptor blockers found to lower epilepsy risk, new study reveals Intermittent fasting outperforms traditional drugs in managing early type 2 diabetes Exploring the comorbidities associated with osteoarthritis Other studies on another class of antidiabetic medications, glucagon-like peptide-1 receptor agonists (GLP1-RA), have also reported promising results for treating osteoarthritis. Here, the scientists applied Mendelian Randomization to examine whether the antidiabetic medication targets were also involved in osteoarthritis and explore the potential of antidiabetic medications to modify osteoarthritis progression. Pharmacological databases were used to identify the genetic targets of the types of antidiabetic medications in clinical use.
The results from genome-wide association studies conducted among the United Kingdom Biobank population were then used to obtain the instrumental variables or SNPs. This step helped in identifying the drug target instrumental variables for the seven major antidiabetic medications, namely, alpha-glucosidase inhibitors, GLP1-RA, insulin and insulin analogs, metformin, sodium-glucose cotransporter 2 inhibitors or SGLT2i, sulfonylureas, and thiazolidinediones. The summary statistics from some of the most recent and comprehensive genome-wide analysis studies were used to investigate osteoarthritis phenotypes such as hip and/or knee osteoarthritis, hand osteoarthritis, knee osteoarthritis, finger osteoarthritis, hip osteoarthritis, spine osteoarthritis, thumb osteoarthritis, early-onset forms of osteoarthritis, total joint replacements, total hip or total knee replacements, or osteoarthritis on any other sites.
A two-sample Mendelian Randomization was then conducted to determine the causal effect of each of the genetic proxies of antidiabetic drug targets on the osteoarthritis phenotypes. Focusing on the genetic proxies instead of blood glucose levels helped distinguish between regular changes in blood glucose levels and the impact of the antidiabetic drugs. The Mendelian Randomization analyses were adjusted for covariates such as smoking status, blood pressure, alcohol consumption levels, and body mass index.
Furthermore, gene expression and colocalization analyses were conducted to determine the link between the gene expression related to the antidiabetic medication and the risk of osteoarthritis. Results The study found that antidiabetic medications could potentially play a therapeutic role in slowing the progression of osteoarthritis. Many of the drug targets for antidiabetic medications showed significant associations with osteoarthritis outcomes, indicating that metabolic dysregulation could be one of the underlying factors of the pathogenesis of osteoarthritis.
However, the findings also indicated that sulfonylurea-based antidiabetic drugs could increase the risk of osteoarthritis. Sulfonylureas target the KCNJ11 gene, which codes for the four subunits of the adenosine triphosphate (ATP)-sensitive potassium channel in the membranes of the beta cells in the pancreas. This subunit plays a protective role in osteoarthritis, and sulfonylureas' inhibition of it increases the risk of osteoarthritis .
This was further supported by the finding that the expression of KCNJ11 was observed mainly in myocytes and skeletal muscles, and serum analyses of osteoarthritis patients indicated a down-regulation of KCNJ11 gene expression. The results confirmed the beneficial effects of GLP1-RAs and metformin in lowering the risk of finger and knee osteoarthritis, supporting the advantageous effects of metformin in chondroprotection, pain reduction, and modulation of immune responses. Conclusions Overall, the study found that while some antidiabetic medications such as sulfonylureas can increase the risk of osteoarthritis, GLP1-RAs and metformin exhibit beneficial effects in lowering the risk of various osteoarthritis phenotypes through their immunoregulatory, anti-inflammatory, and chondroprotective properties.
These findings support the potential use of antidiabetic medications as DMOADs. Fu, K., Si, S.
, Jin, X., Zhang, Y., Duong, V.
, Cai, Q., Li, G., Oo, W.
M., Zheng, X., Boer, C.
G., Zhang, Y., Wei, X.
, Zhang, C., Gao, Y., & Hunter, D.
J. (2024). Exploring antidiabetic drug targets as potential disease-modifying agents in osteoarthritis.
EBioMedicine , 107. doi: 10.1016/j.
ebiom.2024.105285 .
https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(24)00321-9/fulltext.
