Treatment with PPAR-? agonists such as fibrates has been proposed as a strategy to prevent major cardiovascular events (MACE) in patients with type 2 diabetes (T2D). However, clinical trials have shown inconsistent benefits of these drugs in this population. Pursuing a personalized approach to CVD prevention in diabetes, we have recently identified a common non-coding variant (rs6008845, C/T), flanking the PPARA gene, which can be used to distinguish individuals who are more likely to derive benefit from fenofibrate than other T2D patients. In the ACCORD Lipid trial, rs6008845 T/T homozygotes experienced a 50% MACE reduction in response to fenofibrate whereas no benefit was observed in C/T heterozygotes or C/C homozygotes (p for interaction=3.7x10-4). Preliminary evidence from our group suggests that rs6008845 acts by enhancing the anti-inflammatory effects of fenofibrate rather than its triglyceride-lowering properties. The goal of this R21 application, written in response to RFA-HL-17-22, is to explore this hypothesis further by leveraging the ACCORD samples and data banked in the NHLBI repository as well as the multiplexing capabilities of the OLINK proteomic platform. We intend to study a 1:3 case-control set nested in ACCORD Lipid, including all T/T participants who had a MACE (n=80) and serum aliquots stored in BioLINCC, and a sample of three times as many (n=240) T/T participants who did not have a MACE. Through this set, we will address the following Specific Aims: 1. To characterize the anti-inflammatory response to fenofibrate among rs6008845 T/T homozygotes with T2D. Serum samples collected at baseline and 12 months after randomization will be assayed for 93 inflammation-related serum proteins (92 included in the OLINK ?Inflammation? multiplex panel + the chemokine CTACK). The effect of fenofibrate, as compared to placebo, will be evaluated on individual biomarkers as well as by means of supervised and unsupervised data reduction techniques, such as hierarchical cluster analysis, allowing the identification of multi-marker inflammatory signatures influenced by this treatment. 2. To estimate the extent to which anti-inflammatory effects contribute to the cardiovascular benefit exerted by fenofibrate on T/T homozygotes. Using the biomarker data generated in Aim 1, we will use triangulation techniques to estimate the proportion of the fenofibrate benefit on MACE risk that can be ascribed to the effect of this drug on inflammatory biomarkers, given their association with MACE incidence. Understanding the mechanisms through which fenofibrate prevents MACE among T2D patients homozygous for the rs6008845 T allele would provide further support for the possible use of this genetic marker to personalize CVD prevention in T2D and would pave the way for pharmacogenetic clinical trials, in which randomization to fibrate or placebo is stratified by rs6008845 genotype. Importantly, it would also point to critical nodes in the path between T2D and CVD that can be targeted to develop new drugs to prevent MACE in this population.
By understanding the mechanisms through which fenofibrate prevents MACE among rs6008845 T allele homozygotes, this research will generate new knowledge about the molecular pathways underlying the etiology of cardiovascular disease in diabetes, which can be used to develop new interventions to prevent or treat this complication of diabetes. It will also provide further evidence for the use of this genetic marker to personalize CVD prevention in T2D.
