Insulin resistance is a physiological state in which normal levels of insulin fail to regulate blood glucose levels, and even in the absence of type 2 diabetes, there is strong evidence that insulin resistance dramatically increases risk for atherosclerosis and overt cardiovascular disease. In the past few years, we have identified 13 susceptibility loci for insulin resistance, but the causal gene and mechanisms are unknown for all but three of these loci, and the role of the ten remaining loci for development of insulin resistance has not been studied systematically. This represents a gold mine for in-depth physiological and mechanistic studies as increased understanding of the links between obesity, insulin resistance and cardiovascular disease may lead to new approaches to prevention and treatment that could have a huge public health impact. To establish and characterize genes associated with insulin resistance, we plan experiments in large human cohorts with functional follow-up using zebrafish and cell-based models. We will characterize suggested insulin resistance loci using detailed phenotypic information from large population-based samples (total N=13,811) assessed with dynamic measures of glucose and insulin metabolism, metabolomic, transcriptomic, epigenomic and proteomic profiling together with in silico data on gene regulation and transcription from public resources. Next, we will take 55 candidate genes forward to our pipeline for efficient characterization in zebrafish using high-throughput visualization techniques and biochemical measurements. We use CRISPR-Cas9 techniques to knockout the orthologous 55 genes from the 10 loci that are uncharacterized to date, and study the effect of perturbing these genes on insulin resistance. Finally, we will prioritize five candidate genes for mechanistic studies using gene knockdown in adipocytes and hepatocytes to study glucose, insulin and lipid metabolism, gene expression and metabolic pathways. By performing detailed follow-up analyses of loci hypothesized to be involved in insulin resistance, we expect to establish causal genes and mechanisms of action for several of these loci. The in-depth characterization using in vivo and in vitro models will provide further evidence towards causality and the mechanisms of action, as well as a first evaluation of which could be viable drug targets. Our approach of integrating comprehensive characterization in humans with experiments in functional model systems provides a translational framework, which by design is more likely to yield findings relevant for human biology and medicine. Importantly, we have access to unique study materials, state-of-the art methodology, and have a strong track record of successful collaborations in this field. Our work is anticipated to benefit the scientific community, to lead to new important insights into insulin resistance, cardiovascular disease and type 2 diabetes.

Public Health Relevance

Insulin resistance is a common and increasing public health problem that precedes development of type 2 diabetes and cardiovascular disease, but its genetic determinants are largely unknown. We will perform a series of studies in unique samples of up to 13,811 individuals from the general population, genetically modified zebrafish and cell-based model systems. Our work is anticipated to lead to new important insights to the development of insulin resistance, which in turn can lead to better treatment of this and related conditions.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK106236-02
Application #
9340169
Study Section
Kidney, Nutrition, Obesity and Diabetes Study Section (KNOD)
Program Officer
Akolkar, Beena
Project Start
2016-09-01
Project End
2021-06-30
Budget Start
2017-07-01
Budget End
2018-06-30
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Stanford University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Nowak, Christoph; Hetty, Susanne; Salihovic, Samira et al. (2018) Glucose challenge metabolomics implicates medium-chain acylcarnitines in insulin resistance. Sci Rep 8:8691
Figarska, Sylwia M; Gustafsson, Stefan; Sundström, Johan et al. (2018) Associations of Circulating Protein Levels With Lipid Fractions in the General Population. Arterioscler Thromb Vasc Biol 38:2505-2518
Tikkanen, Emmi; Gustafsson, Stefan; Amar, David et al. (2018) Biological Insights Into Muscular Strength: Genetic Findings in the UK Biobank. Sci Rep 8:6451
Tikkanen, Emmi; Gustafsson, Stefan; Ingelsson, Erik (2018) Associations of Fitness, Physical Activity, Strength, and Genetic Risk With Cardiovascular Disease: Longitudinal Analyses in the UK Biobank Study. Circulation 137:2583-2591
Nielsen, Jonas B; Fritsche, Lars G; Zhou, Wei et al. (2018) Genome-wide Study of Atrial Fibrillation Identifies Seven Risk Loci and Highlights Biological Pathways and Regulatory Elements Involved in Cardiac Development. Am J Hum Genet 102:103-115
Turcot, Valérie (see original citation for additional authors) (2018) Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet 50:26-41
Scott, Robert A; Scott, Laura J; Mägi, Reedik et al. (2017) An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans. Diabetes 66:2888-2902
Flannick, Jason (see original citation for additional authors) (2017) Sequence data and association statistics from 12,940 type 2 diabetes cases and controls. Sci Data 4:170179
Ingelsson, Erik; Knowles, Joshua W (2017) Leveraging Human Genetics to Understand the Relation of LDL Cholesterol with Type 2 Diabetes. Clin Chem 63:1187-1189
Shungin, Dmitry; Deng, Wei Q; Varga, Tibor V et al. (2017) Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions. PLoS Genet 13:e1006812

Showing the most recent 10 out of 24 publications