Type 2 diabetes mellitus affects almost 25 million Americans, and is a leading cause of death and disability. Metformin, a member of the biguanide class of drugs, is a first-line medication used to treat type 2 diabetes mellitus, as it s highly effective, safe, and reduces the risk of diabetic complications such as kidney disease, blindness, and heart attack. Metformin lowers blood sugar in diabetes predominantly by lowering hepatic glucose output, and may also increase insulin sensitivity in muscle. Despite its widespread use for more than 50 years, the full mechanism of action of metformin is not understood, and the direct target of metformin is unknown. Better understanding of the mechanism of metformin action may lead to more intelligent therapies for type 2 diabetes mellitus. To determine the molecular targets of metformin, we propose the use of classical genetics and genomics in C. elegans. We have found that metformin affects both growth and metabolism of C. elegans in a dose dependent manner, and metformin's action in C. elegans, as it is in mammals, is partially genetically dependent upon AMP-activated protein kinase (AMPK) signaling. This indicates that C. elegans is a facile and genetically tractable model organism to study metformin's action. In C. elegans, forward genetic screening enables identification of the most important genes in any given biological response. Using an optimal dose to slow the growth of wild-type worms for screening purposes, we conducted a large-scale, 300,000 haploid-genome forward genetic screen, yielding 30 independent mutants resistant to the effects of metformin. In parallel, we conducted reverse genetic RNAi screening, identifying 16 genes, which when knocked down, lead to resistance to metformin's effects. Fourteen of these 16 have human orthologs which lie in loci associated with human diabetes, obesity or cardiometabolic disease in GWAS, a compelling argument for the relevance of this data set to human disease.
In Aim 1 we will define the metabolic state produced by metformin in C. elegans by studying the physiology of metformin-treated C. elegans.
In Aim 2, we will genetically identify major pathways through which metformin exacts these metabolic effects. Causal mutations in the most metformin resistant genetic mutants will be identified by next-generation whole genome sequencing. The mechanism of action of identified metformin response genes will be established using C. elegans transgenics, tissue specific RNAi, and through detailed physiologic characterization. The most important pathways will be identified by analysis of additional members of each pathway in the response to metformin. Finally, we will correlate each metformin response pathway with emerging human diabetes, obesity and metformin response genes identified in GWAS. Through fundamental study of metformin's action, we hope both to illuminate possible mechanisms of the development of diabetes and to identify new targets for diabetes treatment.
Type 2 diabetes affects almost 25 million Americans and another 79 million are prediabetic. The most commonly prescribed medicine for type 2 diabetes is metformin and yet the genetic mechanism by which metformin lowers blood sugar in diabetes remains unknown. This application aims to identify the means by which metformin acts using a genetic approach in a facile gene discovery system. Identification of metformin's mechanism of action is of central importance to future design of more intelligent therapies for type 2 diabetes.