Results from a large international study of patients taking metformin, the world’s most commonly used drug to treat type 2 diabetes, reveal genetic differences among patients that may explain why some respond better to the drug than others. The insight could help physicians predict which patients will need higher doses than others to produce the same health effects and which ones will need to be prescribed different drugs altogether.
The new study is the first result from the Metformin Genetics Consortium, an international collaboration led by Kathy Giacomini, PhD, and Ewan Pearson, PhD.
“Right now we treat most people with type 2 diabetes the same,” Giacomini said, “but we wanted to discover whether there might be a specific genetic marker that could let us take a precision medicine approach to prescribing and dosing this common diabetes medication.”
The researchers found a common variant of the gene SLC2A2 that was correlated with a strong response to the drug.
This finding makes sense, Giacomini said, because the gene encodes GLUT2, a glucose transporter protein responsible for regulating the movement of glucose between the liver, the blood, and the kidneys. Gene expression data confirmed that people with this variant had less GLUT2 in the liver and other metabolic tissues, which led to a reduced ability to manage blood glucose. Metformin, which slows the liver’s production of glucose, appears to be able to reverse this deficit, which could explain its blockbuster efficacy in these patients.
The researchers also identified a compelling link between the new genetic variant and higher body weight, in line with previous clinical observations that metformin is particularly effective in overweight patients.
These findings suggest that the biological causes of high blood sugar could be different in different people, the researchers said. Moreover, the study revealed a much higher prevalence of the metformin-enhancing gene variant in African Americans than in other ethnic groups, highlighting the importance of including diverse cohorts in precision medicine studies.
This article was adapted from information provided by the University of California, San Francisco.