Scientists employed Mendelian Randomization analysis in a recent study that was published in The Lancet EBioMedicine to investigate the possibility of using antidiabetic medicines as disease-modifying osteoarthritis drugs, or DMOADs, for the therapeutic management of osteoarthritis risk.
Context
One condition that affects the joints is osteoarthritis. It is distinguished by subchondral bone remodeling, inflammation, and a gradual deterioration of joint cartilage. Numerous biochemical mechanisms and biomechanical forces are involved in the genesis of this common type of arthritis.
Although osteoarthritis pain and morbidity significantly impair normal function and cause disability, there are no effective DMOADs that can stop or reverse the deterioration of the joint.
Nonetheless, current studies have demonstrated that metabolic dysregulation may play a significant role in the disease’s advancement, suggesting a relationship between osteoarthritis risk and metabolic disorders.
Hyperglycemia may have an impact on osteoarthritis, according to data from interactions at the local and systemic levels. Oxidative stress and glycation end products are thought to compound cartilage degradation.
The possible application of antidiabetic drugs to affect or change the pathways related to joint health has been brought to light by these findings.
About the Study
To ascertain if antidiabetic drugs may have a role as DMOADs, the researchers in this study used a Mendelian Randomization technique, which looks at causal correlations using genetic variants in the form of single nucleotide polymorphisms (SNPs).
Metformin has been studied for its effect on osteoarthritis and has been shown to regulate inflammatory responses and the cartilage matrix’s homeostasis.
Promising outcomes for treating osteoarthritis have also been reported by other trials using glucagon-like peptide-1 receptor agonists (GLP1-RA), a different family of antidiabetic drugs.
Here, the researchers used Mendelian Randomization to investigate the possibility that the targets of antidiabetic drugs were also implicated in osteoarthritis and to see if they may slow the evolution of the condition.
The genetic targets of the various antidiabetic drug types prescribed in clinical practice were found using pharmacological databases. The instrumental variables, or SNPs, were then derived from genome-wide association studies carried out among the United Kingdom Biobank population.
The seven main antidiabetic drugs—alpha-glucosidase inhibitors, GLP1-RA, insulin and insulin analogs, metformin, sodium-glucose cotransporter 2 inhibitors, or SGLT2i, sulfonylureas, and thiazolidinediones—were identified with the use of this phase.
The 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 site, were investigated using the summary statistics from some of the most recent and extensive genome-wide analysis studies.
The causal relationship between the osteoarthritis phenotypes and each genetic proxy of an antidiabetic pharmacological target was then ascertained using a two-sample Mendelian Randomization.
It was possible to discern between the effects of the antidiabetic medications and normal variations in blood glucose levels by concentrating on the genetic proxies rather than blood glucose levels.
Covariates like blood pressure, body mass index, alcohol use, and smoking status were taken into account while adjusting the Mendelian Randomization studies. Moreover, gene expression and colocalization studies were carried out to ascertain the relationship between the risk of osteoarthritis and the gene expression associated with the antidiabetic drug.
In conclusion
Overall, the study discovered that while some antidiabetic drugs, like sulfonylureas, can raise the risk of osteoarthritis, metformin and GLP1-RAs, with their immunoregulatory, anti-inflammatory, and chondroprotective qualities, help reduce the risk of different osteoarthritis phenotypes. These results lend support to the idea of using antidiabetic drugs as DMOADs.
For more information: Exploring antidiabetic drug targets as potential disease-modifying agents in osteoarthritis, eBioMedicine https://doi.org/10.1016/j.ebiom.2024.105285
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