Authors in Frontiers in Science propose targeting the GPCR network to identify interventions in aging
Authors in Frontiers in Science propose targeting the GPCR network to identify interventions in aging
GPCRs are cell receptors that receive hormonal, neural, and immune signals. The article brings together age-related changes in these receptors to propose an approach: measure how receptor function changes across tissues and test combinations of interventions.
On October 22, Frontiers in Science published an article on GPCRs. Some receptors in this family are already targets of drugs for diabetes and hypertension. The authors propose studying them as a network: measuring how receptor signaling changes with age in a specific tissue, then testing combinations of compounds that activate or block different receptors.
The authors describe several recurring changes: some receptors become less abundant on the cell surface, while others are transported to the surface less efficiently and couple less effectively to G proteins, which transmit signals inside the cell. Their model suggests that signals involved in metabolism, tissue repair, and nervous system function may weaken, while signals that trigger inflammation and scar tissue formation may strengthen. They propose studying these processes together by identifying which receptor signals have changed in a specific tissue and how they influence one another.
The authors propose first identifying which receptor signals have changed in a tissue. The next step would be to test combinations of compounds that activate some receptors, block others, and alter the sensitivity of others. Each combination requires data on the tissue response, appropriate doses, and checks for drug interactions.
A table in the article shows the stages of development for different receptor targets. Drugs that act on the receptor for the hormone GLP-1 are already used for metabolic diseases, and angiotensin AT1 receptor blockers are used for hypertension. Many other targets associated with inflammation and senescent cells remain at the preclinical or early clinical stage.
To select these combinations, the authors propose comparing data on gene activity, proteins, and metabolism with tissue responses to drugs. They suggest using AI and digital twins, computer models of tissues and the body, to select the next experiments and clinical trials. Testing requires attention to the specific combination of interventions, the tissue, the doses, and the biomarkers, which are measurable indicators of the tissue response.