Metformin is the first-line agent in the treatment of type 2 diabetes, yet little is known about the molecular mechanisms of metformin action. The genetic parsing of metformin responders versus non-responders remains similarly underexplored. The Diabetes Prevention Program (DPP) includes 988 participants randomized to metformin. We propose to complete a genome-wide association study (including exome content) for metformin response in the DPP. In parallel, we will explore genetic determinants of metformin response for diabetes prevention and for lowering glycated hemoglobin: the latter will be meta-analyzed with data from 3,500 participants in the GoDARTS cohort. To prioritize human findings we will leverage information from an siRNA genomic screen for metformin response in the roundworm nematode C. elegans, integrating genes and pathways identified in the course of this screen with the human findings. Results that emerge from this integration will undergo further replication in three independent human cohorts. Top signals will be carried forward for functional validation in an established human hepatocyte model, where knockout and point mutation approaches using CRISPR technology will be used to confirm the causal gene and variant. If successful, this project will accomplish the twin goals of elucidating the mechanism of action of metformin and identifying genetic predictors of clinical response, while illustrating the arc of progress from genetic association to identifying the causal gene/variant in order to illuminate function.
Metformin is the first-line agent in the treatment for type 2 diabetes, yet its mechanism of action is not well understood, and the reason why a substantial number of patients eventually fail metformin is not known. We propose to conduct a genome-wide association study (including coding variants) in the Diabetes Prevention Program and the GoDARTS cohort to discover genetic determinants of metformin response, using a parallel genomic screen in the roundworm C. elegans to prioritize genes and pathways of interest in the human data. We will then use a human hepatocyte cell model to confirm the functional impact of these genes on metformin action in the relevant tissue type.
|Florez, Jose C (2017) Mining the Genome for Therapeutic Targets. Diabetes 66:1770-1778|
|Mercader, Josep M; Liao, Rachel G; Bell, Avery D et al. (2017) A Loss-of-Function Splice Acceptor Variant in IGF2 Is Protective for Type 2 Diabetes. Diabetes 66:2903-2914|
|Florez, Jose C (2017) The pharmacogenetics of metformin. Diabetologia 60:1648-1655|
|Kim, Catherine; Dabelea, Dana; Kalyani, Rita R et al. (2017) Changes in Visceral Adiposity, Subcutaneous Adiposity, and Sex Hormones in the Diabetes Prevention Program. J Clin Endocrinol Metab 102:3381-3389|
|McCaffery, Jeanne M; Jablonski, Kathleen A; Franks, Paul W et al. (2017) Replication of the Association of BDNF and MC4R Variants With Dietary Intake in the Diabetes Prevention Program. Psychosom Med 79:224-233|
|Zhou, Kaixin; Yee, Sook Wah; Seiser, Eric L et al. (2016) Variation in the glucose transporter gene SLC2A2 is associated with glycemic response to metformin. Nat Genet 48:1055-1059|
|Varga, Tibor V; Winters, Alexandra H; Jablonski, Kathleen A et al. (2016) Comprehensive Analysis of Established Dyslipidemia-Associated Loci in the Diabetes Prevention Program. Circ Cardiovasc Genet 9:495-503|
|Hall, Kathryn T; Jablonski, Kathleen A; Chen, Ling et al. (2016) Catechol-O-methyltransferase association with hemoglobin A1c. Metabolism 65:961-967|
|Wu, Lianfeng; Zhou, Ben; Oshiro-Rapley, Noriko et al. (2016) An Ancient, Unified Mechanism for Metformin Growth Inhibition in C. elegans and Cancer. Cell 167:1705-1718.e13|
|Livingstone, Katherine M; Celis-Morales, Carlos; Papandonatos, George D et al. (2016) FTO genotype and weight loss: systematic review and meta-analysis of 9563 individual participant data from eight randomised controlled trials. BMJ 354:i4707|
Showing the most recent 10 out of 46 publications