Type 2 diabetes (T2D) is characterized by insulin resistance and a relative deficiency of insulin secretion. T2D affects ~300 million people worldwide, >25 million in the US alone. 27% of Americans aged e60y suffer from T2D. T2D incidence and prevalence are increasing rapidly. In the US alone, medical costs of diabetes in 2012 were estimated at $176 billion, ~10% of US health care costs. The increasing number of younger T2D cases amplifies the socioeconomic impact of T2D and increases the urgency with which we must act to identify causes and new treatments. The goal of the Finland-United States Investigation of NIDDM Genetics (FUSION) study is to identify genetic variants that predispose to T2D and that are responsible for variability in T2D-related QTs. Improved understanding of the genetic basis of T2D and related QTs has the potential to reduce the impact of the T2D epidemic by supporting identification of novel drugs and therapies, enabling better targeting of drugs and therapies, and providing more accurate T2D risk prediction. In this proposal, we propose to (1) discover genetic loci and variants that influence T2D risk and variability in T2D-related QTs using association studies based on GWAS and sequence data with increasing emphasis on low-frequency and rare variants; (2) identify muscle and adipose tissue regulatory elements that increase risk of T2D and contribute to variation in related QTs by molecularly characterizing muscle and adipose biopsy samples from 324 individuals from across the glucose tolerance spectrum; and (3) identify the likely causal genes (and other functional units) and disease mechanisms at known T2D and QT loci through genotype-based callback detailed phenotyping in appropriately consented individuals with likely high-impact variants and in non-carrier controls. These efforts will contribute to improved understanding of the etiology of T2D, and have the potential to point the way to novel methods of treatment and prevention. Methods developed and lessons learned in the FUSION study will be useful in the study of other complex genetic diseases.

Public Health Relevance

The rising prevalence of type 2 diabetes in the US and worldwide represents one of the major challenges to public health, and improved options for treatment and prevention are required. The present proposal builds on a longstanding and productive collaboration between researchers in the USA and Finland to understand the genetic basis of type 2 diabetes, and to use this information to reveal disease mechanisms. In this proposal, we will continue to identify genetic loci that influence risk to type 2 diabetes and variability in diabetes-related quantitative traits, and increasingly focus on identifying the causl variants, genes and other functional units, and the mechanisms by which they act.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01DK062370-13
Application #
9064139
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Blondel, Olivier
Project Start
2002-07-01
Project End
2018-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
13
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Type
Schools of Public Health
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Teslovich, Tanya M; Kim, Daniel Seung; Yin, Xianyong et al. (2018) Identification of seven novel loci associated with amino acid levels using single-variant and gene-based tests in 8545 Finnish men from the METSIM study. Hum Mol Genet 27:1664-1674
Kycia, Ina; Wolford, Brooke N; Huyghe, Jeroen R et al. (2018) A Common Type 2 Diabetes Risk Variant Potentiates Activity of an Evolutionarily Conserved Islet Stretch Enhancer and Increases C2CD4A and C2CD4B Expression. Am J Hum Genet 102:620-635
Pan, David Z; Garske, Kristina M; Alvarez, Marcus et al. (2018) Integration of human adipocyte chromosomal interactions with adipose gene expression prioritizes obesity-related genes from GWAS. Nat Commun 9:1512
Sung, Yun J (see original citation for additional authors) (2018) A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure. Am J Hum Genet 102:375-400
Dutta, Diptavo; Scott, Laura; Boehnke, Michael et al. (2018) Multi-SKAT: General framework to test for rare-variant association with multiple phenotypes. Genet Epidemiol :
Latva-Rasku, Aino; Honka, Miikka-Juhani; Stan?áková, Alena et al. (2018) A Partial Loss-of-Function Variant in AKT2 Is Associated With Reduced Insulin-Mediated Glucose Uptake in Multiple Insulin-Sensitive Tissues: A Genotype-Based Callback Positron Emission Tomography Study. Diabetes 67:334-342
Ray, Debashree; Boehnke, Michael (2018) Methods for meta-analysis of multiple traits using GWAS summary statistics. Genet Epidemiol 42:134-145
Mahajan, Anubha (see original citation for additional authors) (2018) Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. Nat Genet 50:559-571
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
Liu, Dajiang J (see original citation for additional authors) (2017) Exome-wide association study of plasma lipids in >300,000 individuals. Nat Genet 49:1758-1766

Showing the most recent 10 out of 121 publications