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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

The era of GWAS is over - Commentary.

TL;DR: That genome-wide association studies are an effective strategy to identify underlying genetic susceptibility for complex diseases is undisputable, but as a consequence of this, increasingly smaller effects are being detected.
Journal ArticleDOI

Integration of a Large-Scale Genetic Analysis Workbench Increases the Accessibility of a High-Performance Pathway-Based Analysis Method

TL;DR: The proposed new PHARAOH program not only supports various de facto standard genetic data formats but also provides many quality control measures and filters based on those measures.
Dissertation

Computational discovery of Genetic Markers for Type 2 diabetes

TL;DR: New ways to approach Multi-Locus Genome Wide Association Studies in complex diseases are developed, that are not only computationally feasible, but can also study the non-linearity in a dataset.
Dissertation

An Analytical Method for Inferring Library Identity From Illumina NGS Read Groups

TL;DR: Bioinformatics; quality control; sequencing; genomics; software; illumina; sequencing library; binary classifier; machine learning
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