The normal action of insulin to promote glucose disposal varies over 600% in the population, with those individuals who are least sensitive to insulin having to mount sustained increased levels to maintain optimum serum glucose levels. Some of these individuals develop type 2 diabetes mellitus (DM2), but even those who do not develop DM2 are at increased risk for dyslipidemia, hypertension and atherosclerotic cardiovascular disease. While up to a third of the US population has this insulin resistance (IR) syndrome, our ability to identify individuals with (or at risk) for IR is extremely limited, and there are few treatment options for IR. Insulin sensitivity (IS) is largely determined at the genetic level, with heritability estimated at -50%. To aid in the search for genetic variation that underlies the extreme variance in IS, and the pathophysiology of IR, we are performing genome-wide association study of all individuals in the world phenotyped by insulin clamp measures of IS, through the Genetics of Insulin Sensitivity (GENESIS-2) consortium. Further insights into the cellular and molecular basis of IR could be gained through the study of metabolic and vascular cells from subjects with known insulin sensitivity and genetic architecture. Toward this end, we propose here to develop induced pluripotent cell (iPSC) lines from several hundred individuals of the GENESIS-2 cohort, as a sustainable resource for the production of metabolic and vascular cells in culture, the Genetics of Insulin Sensitivity iPSC (GENESiPS) study. We will develop methods for optimized differentiation of iPSC to the skeletal muscle (or adipose) and vascular endothelial cell lineages. The cellular phenotype of these cells will be investigated through whole genome transcriptome sequencing, as well as cell-based assays of insulin signaling and action. By combining the known human IS phenotype and whole genome variation with the differentiated cellular phenotypes at baseline and in response to insulin stimulation, we will undertake a systems biology approach to defining the cellular IR phenotype. These analyses will leverage novel network approaches that improve power, and provide added insights into the genes and pathways that may be targeted for the development of next generation insulin sensitizing therapies.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01HL107388-04
Application #
8689145
Study Section
Special Emphasis Panel (ZHL1)
Program Officer
Srinivas, Pothur R
Project Start
2011-07-05
Project End
2016-06-30
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
4
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Stanford University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
City
Stanford
State
CA
Country
United States
Zip Code
94304
Carcamo-Orive, Ivan; Huang, Ngan F; Quertermous, Thomas et al. (2017) Induced Pluripotent Stem Cell-Derived Endothelial Cells in Insulin Resistance and Metabolic Syndrome. Arterioscler Thromb Vasc Biol 37:2038-2042
Carcamo-Orive, Ivan; Hoffman, Gabriel E; Cundiff, Paige et al. (2017) Analysis of Transcriptional Variability in a Large Human iPSC Library Reveals Genetic and Non-genetic Determinants of Heterogeneity. Cell Stem Cell 20:518-532.e9
Evrard, Solene M; Lecce, Laura; Michelis, Katherine C et al. (2016) Endothelial to mesenchymal transition is common in atherosclerotic lesions and is associated with plaque instability. Nat Commun 7:11853
Margolies, Laurie R; Pandey, Gaurav; Horowitz, Eliot R et al. (2016) Breast Imaging in the Era of Big Data: Structured Reporting and Data Mining. AJR Am J Roentgenol 206:259-64
Quertermous, Thomas; Ingelsson, Erik (2016) Coronary Artery Disease and Its Risk Factors: Leveraging Shared Genetics to Discover Novel Biology. Circ Res 118:14-6
Pjanic, Milos; Miller, Clint L; Wirka, Robert et al. (2016) Genetics and Genomics of Coronary Artery Disease. Curr Cardiol Rep 18:102
Hoffman, Gabriel E; Schadt, Eric E (2016) variancePartition: interpreting drivers of variation in complex gene expression studies. BMC Bioinformatics 17:483
Chennamsetty, Indumathi; Coronado, Michael; Contrepois, Kévin et al. (2016) Nat1 Deficiency Is Associated with Mitochondrial Dysfunction and Exercise Intolerance in Mice. Cell Rep 17:527-540
Miller, Clint L; Pjanic, Milos; Quertermous, Thomas (2015) From Locus Association to Mechanism of Gene Causality: The Devil Is in the Details. Arterioscler Thromb Vasc Biol 35:2079-2080
Assimes, Themistocles L; Quertermous, Thomas (2014) Study of exonic variation identifies incremental information regarding lipid-related and coronary heart disease genes. Circ Res 115:478-80