Type 2 diabetes has emerged as one of the leading threats to global health. The rapid rise in diabetes prevalence in both industrialized and emerging economies bears testament to the failures of prevention, and high rates of complication in those with diabetes highlight the inadequacies of current therapeutic approaches. Major gaps in our understanding of the mechanisms responsible for the development of diabetes represent obstacles to innovation with respect to novel preventative and therapeutic strategies. Human genetics provides an increasingly-powerful approach for addressing these deficiencies and providing mechanistic insights into disease that can result in health-related benefits. This proposal seeks to use information from human genetic discovery efforts that have, in recent years, identified over 100 regions of the genome which harbor DNA sequence variants influencing T2D-risk. There has been limited progress in turning these discoveries into mechanistic insights but several recent technological and analytical advances have transformed the situation, and it is these that we plan to exploit.
Our first aim i s to home i on the specific DNA sequence changes driving the risk-associations in these regions. The aggregation of very large genetic datasets, particularly when derived from a range of ethnic groups, makes it possible to define the subset of these variants likely to be driving the T2D-risk effect. We will take extensive genetic data sets collected as part of large international consortia and apply existing and novel approaches to derive the most precise localization of these T2D-risk variants yet obtained. Having identified these variants, the second aim is to understand the cellular processes they perturb. Recently, it has become possible to generate detailed functional maps of the genome from key diabetes- relevant human tissues, including the pancreatic islet. These maps define elements crucial for regulating cellular activity. We will use these maps to highlight the specific elements that contain T2D-causal variants, and initiate experimental studies to test the functional hypotheses that emerge.
The third aim seeks to connect these T2D-associated functional elements to the specific genes, proteins, networks and pathways that mediate their effects. We will aggregate data from a variety of existing and novel public and proprietary sources, each of which provides complementary clues to the relevance of the regional genes to T2D development. Most medicines act on specific protein targets, and these efforts will result in novel protein targets that are directly implicated in human disease. An essential feature of this proposal is that it relies on extensive data sets that have already been collected, or, in some cases, are being generated with existing funding. The funding we request here will support the further integration of these data, and also enable its dissemination to the wider research community, most particularly via the AMP-T2DGENES consortium portal.
The research in this proposal aims to identify fundamental processes involved in the development of type 2 diabetes. Type 2 diabetes is a leading cause of illness and death across the world and currently-available strategies for prevention and treatment of this condition are manifestly inadequate. We will harness the power of human genetics, allied to molecular characterization of the pancreatic islet and other key tissues, to generate novel insights into disease biology: these will provide the basis for more effective preventative and therapeutic approaches that reduce the burden of disease.
|Zhang, Mingfeng; Lykke-Andersen, Soren; Zhu, Bin et al. (2018) Characterising cis-regulatory variation in the transcriptome of histologically normal and tumour-derived pancreatic tissues. Gut 67:521-533|
|Thurner, Matthias; van de Bunt, Martijn; Torres, Jason M et al. (2018) Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci. Elife 7:|
|Small, Kerrin S; Todor?evi?, Marijana; Civelek, Mete et al. (2018) Regulatory variants at KLF14 influence type 2 diabetes risk via a female-specific effect on adipocyte size and body composition. Nat Genet 50:572-580|
|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|
|Fitipaldi, Hugo; McCarthy, Mark I; Florez, Jose C et al. (2018) A Global Overview of Precision Medicine in Type 2 Diabetes. Diabetes 67:1911-1922|
|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|
|Gamazon, Eric R; Segrè, Ayellet V; van de Bunt, Martijn et al. (2018) Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation. Nat Genet 50:956-967|
|Corbin, Laura J; Tan, Vanessa Y; Hughes, David A et al. (2018) Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference. Nat Commun 9:711|
|Mägi, Reedik; Horikoshi, Momoko; Sofer, Tamar et al. (2017) Trans-ethnic meta-regression of genome-wide association studies accounting for ancestry increases power for discovery and improves fine-mapping resolution. Hum Mol Genet 26:3639-3650|
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