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Metabolic mechanisms of increased cardiovascular risk in type 2 diabetes associated with genetic variants

Grant number: 18/00164-7
Support type:Scholarships abroad - Research
Effective date (Start): September 01, 2018
Effective date (End): August 31, 2019
Field of knowledge:Biological Sciences - Physiology
Principal researcher:Carlos Roberto Bueno Júnior
Grantee:Carlos Roberto Bueno Júnior
Host: Alessandro Doria
Home Institution: Escola de Educação Física e Esporte de Ribeirão Preto (EEFERP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
Research place: Harvard University, Boston, United States  


Diabetic subjects to experience a 2-to 4-fold higher cardiovascular risk than non-diabetic subjects. One approach to gain novel insights into the links between diabetes and cardiovascular disease has been to look for genetic loci that are associated with coronary artery disease (CAD) among diabetic subjects and use this information to infer about the mechanisms linking diabetes to cardiovascular disease. Through a systematic genome-wide study, Dr. Doria has recently identified a previously unknown CAD locus that interacts so strongly with diabetes that its effect can only be detected among diabetic subjects. This locus is adjacent to the GLUL (glutamine synthase) gene. The goal of my proposal, totally innovative, is to gain insights into the metabolic mechanisms linking GLUL and other genes in the glutamic and ³-glutamyl pathways to CAD risk in type 2 diabetes. Based on Dr. Doria's preliminary findings, I will specifically investigate the hypothesis that the GLUL gene effect is due to increased susceptibility to oxidative stress resulting from an impairment of the ³-glutamyl cycle and glutathione production. To this end, I will conduct targeted metabolomic studies of ³-glutamyl cycle intermediates, glutathione, and oxidative stress markers (8-isoprostane, oxidized tyrosines) in red blood cells and plasma samples freshly collected from 400 type 2 diabetes patients and will relate these traits to the GLUL risk variant. Triangulation techniques will be employed to establish the causal path between genetic variants and oxidative stress.

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