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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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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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Chromatin interactions and expression quantitative trait loci reveal genetic drivers of multimorbidities

TL;DR: This work created a “multimorbidity atlas” of traits based on pleiotropy of spatially regulated genes using convex biclustering of eGenes that are shared between phenotypes and identified complex inter-relationships between nominally different phenotype associated SNPs.
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TL;DR: A comprehensive bioinformatics analysis of microarray data in the context of protein-protein interaction (PPI) networks was employed, combined with subcellular location information to mine the potential candidate genes for T2DM and provide further insight on the possible mechanisms involved.
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Identification of novel variants associated with osteoporosis, type 2 diabetes and potentially pleiotropic loci using pleiotropic cFDR method.

TL;DR: This study highlights PLEKHA1 as an important potentially pleiotropic gene to help gain a better understanding of the shared genetic determination of osteoporosis and T2D.
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Recent advances and perspectives in next generation sequencing application to the genetic research of type 2 diabetes.

TL;DR: These advances in application of next-generation sequencing methods for elucidation of T2D pathogenesis are reviewed, as well as progress and challenges in implementation of this new knowledge about T1D genetics in diagnosis, prevention, and treatment of the disease.
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"Omics" and "epi-omics" underlying the β-cell adaptation to insulin resistance.

TL;DR: The current review focuses on summarizing the “omics” and “epi-omics’ approaches that particularly focus on addressing the β-cell adaptation to insulin resistance and T2D.