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The genetic architecture of type 2 diabetes

Christian Fuchsberger, +300 more
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TLDR
Large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes, but most fell within regions previously identified by genome-wide association studies.
Abstract
The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.

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Citations
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Journal ArticleDOI

Global aetiology and epidemiology of type 2 diabetes mellitus and its complications.

TL;DR: An updated view of the global epidemiology of type 2 diabetes mellitus, as well as dietary, lifestyle and other risk factors for T2DM and its complications are provided.
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10 Years of GWAS Discovery: Biology, Function, and Translation

TL;DR: The remarkable range of discoveriesGWASs has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics are reviewed.
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Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations

TL;DR: Genome-wide polygenic risk scores derived from GWAS data for five common diseases can identify subgroups of the population with risk approaching or exceeding that of a monogenic mutation.
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Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.

Anubha Mahajan, +131 more
- 08 Oct 2018 - 
TL;DR: Combining 32 genome-wide association studies with high-density imputation provides a comprehensive view of the genetic contribution to type 2 diabetes in individuals of European ancestry with respect to locus discovery, causal-variant resolution, and mechanistic insight.
References
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A Global Overview of Precision Medicine in Type 2 Diabetes

TL;DR: An overview of the evidence and barriers to the development and implementation of precision medicine in type 2 diabetes is given and recently presented paradigms through which complex data might enhance the understanding of diabetes and ultimately the ability to tackle the disease more effectively than ever before are discussed.
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Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution

TL;DR: In this paper, the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries and 132,177 European-ancestry individuals was analyzed.
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Genetic variant effects on gene expression in human pancreatic islets and their implications for T2D.

TL;DR: The relationship between genetic variants influencing predisposition to type 2 diabetes and related glycemic traits, and human pancreatic islet transcription is explored using data from 420 donors to illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.
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Biomarkers for type 2 diabetes

TL;DR: Combination of genetic variants and physiologically characterized pathways improves the classification of individuals with type 2 diabetes into subgroups, and is also paving the way to a precision medicine approach, in T2D.