This application represents a response to RFA-DK-09-004 (Multiethnic Study of type 2 diabetes genes) from investigators experienced in the genetics of T2D and related complex traits, and in broader aspects of T2D pathophysiology. The applicants (collectively, the Global Diabetes Consortium [GDC]) will work with other members of the U01 Steering Committee to realize the objectives of the study through: contributing well-characterized, appropriately-consented samples for re-sequencing and genotyping. The samples within this proposal are of South Asian, East Asian, European, African and Arab origin (>100,000 samples in total), and representative of populations accounting for -70% of global T2D. Many of the samples have undergone high-density GWA scanning and/or have additional features which deliver added-value; contributing expertise in T2D genetics, large-scale genomics and T2D pathophysiology. The applicants have completed some of the first large-scale, high-density T2D GWA scans in European, S Asian, E Asian and Arab populations and bring links to relevant community and collaborative efforts including the 1000 Genomes Project and the recent T2D re-sequencing and fine-mapping experience of the WTCCC; working with the Steering Committee to develop plans for coordinated analysis. Our proposal describes plans to combine information from the 1000 Genomes project with de novo re-sequencing of contiguous regions and deep-re-sequencing of well-annotated sequence within GWA-proven T2D-association signals across a range of ethnic groups. Large-scale genotyping studies will be used to fine-map variants causal for the index association and those that represent independent causal events (particularly low-frequency, penetrate alleles). The plan anticipates a shift towards genome-wide discovery re-sequencing; building a strong global consortium of investigators. Oxford will contribute substantially to all four of these aims, contributing samples of European and S Asian origin;providing expertise in T2D genetics, large-scale genomics and statistical analysis;participating in the U0l steering committee;and taking responsibility for building a global T2D genetics consortium.

Public Health Relevance

The rising prevalence of T2D in societies worldwide constitutes a major challenge to global health, and improved therapeutic and preventative options are required. Recent genetic discoveries have provided important clues about the development of T2D, but further work is needed to define the causal mechanisms. The present proposal brings together a group of investigators with unequalled expertise and a wide range of clinical samples who will work with others in the U01 consortium to realize these important objectives.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01DK085545-04
Application #
8319234
Study Section
Special Emphasis Panel (ZDK1-GRB-G (O2))
Program Officer
Akolkar, Beena
Project Start
2009-09-20
Project End
2013-07-31
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
4
Fiscal Year
2012
Total Cost
$542,883
Indirect Cost
$33,309
Name
University of Oxford
Department
Type
DUNS #
226694883
City
Oxford
State
Country
United Kingdom
Zip Code
OX1 2-JD
Konigorski, Stefan; Wang, Yuan; Cigsar, Candemir et al. (2018) Estimating and testing direct genetic effects in directed acyclic graphs using estimating equations. Genet Epidemiol 42:174-186
Jun, Goo; Manning, Alisa; Almeida, Marcio et al. (2018) Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees. Proc Natl Acad Sci U S A 115:379-384
Kwon, Minseok; Leem, Sangseob; Yoon, Joon et al. (2018) GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data. BMC Syst Biol 12:19
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
Hwang, Jessica L; Park, Soo-Young; Ye, Honggang et al. (2018) FOXP3 mutations causing early-onset insulin-requiring diabetes but without other features of immune dysregulation, polyendocrinopathy, enteropathy, X-linked syndrome. Pediatr Diabetes 19:388-392
Chien, Li-Chu; Chiu, Yen-Feng (2018) General retrospective mega-analysis framework for rare variant association tests. Genet Epidemiol 42:621-635
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
Thomsen, Soren K; Raimondo, Anne; Hastoy, Benoit et al. (2018) Type 2 diabetes risk alleles in PAM impact insulin release from human pancreatic ?-cells. Nat Genet 50:1122-1131
Ahn, Eunyong; Park, Taesung (2017) Analysis of population-specific pharmacogenomic variants using next-generation sequencing data. Sci Rep 7:8416
Cao, Hongyan; Li, Zhi; Yang, Haitao et al. (2017) Longitudinal data analysis for rare variants detection with penalized quadratic inference function. Sci Rep 7:650

Showing the most recent 10 out of 78 publications