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Journal ArticleDOI

Genome-wide association: which do you want first: the good news, the bad news, or the good news?

Kent D. Taylor, +2 more
- 01 Dec 2007 - 
- Vol. 56, Iss: 12, pp 2844-2848
TLDR
The strength of the GWA is that it has the potential to identify genes of high genetic effect that were previously unsuspected as candidates, and is not biased by a priori assumptions based on prior observations of the phenotype.
Abstract
It has long been appreciated that there is a genetic component to type 2 diabetes, but progress in gene finding has been slow because the genetic component is complex. Accumulating data on various diabetes-related phenotypes suggest that so-called “type 2 diabetes” is likely a collection of many diseases due to varying but often overlapping underlying mechanisms. As such, the search for the once hoped-for simple genetic basis of type 2 diabetes has proved elusive. This year marks the application of the next gene-finding tool to the study of type 2 diabetes, the genome-wide association study (GWA). This type of study is the logical extension of the candidate gene association study, an approach in which a few (1–20 or so) single nucleotide polymorphisms (SNPs) within a single gene are tested for association with the phenotype of interest. By that approach, the candidate gene is chosen based on biochemistry or physiology related to that phenotype. The candidate gene approach has identified some genes but has not yielded the definitive picture of the genetic contribution to type 2 diabetes (Table 1; reviewed in [1]). In contrast, the GWA approach tests every gene by testing the association of SNPs in every known gene (∼100,000 SNPs) or in both known genes and in regions outside of genes throughout the genome (∼300,000 to 1 million). The GWA is therefore not biased by a priori assumptions based on prior observations of the phenotype (e.g., kinetics of insulin signaling, glucose-mediated insulin secretion, etc). Therefore, the strength of the GWA is that it has the potential to identify genes of high genetic effect that were previously unsuspected as candidates. The latter might be because little was known about the genes previously or because investigators simply had not addressed the action of the products of these genes …

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Citations
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Journal ArticleDOI

Inflammatory bowel disease: cause and immunobiology

TL;DR: How environmental factors, infectious microbes, ethnic origin, genetic susceptibility, and a dysregulated immune system can result in mucosal inflammation are discussed.
Journal ArticleDOI

Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array

TL;DR: The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.
Journal ArticleDOI

Signals of recent positive selection in a worldwide sample of human populations

TL;DR: Analysis of recent selection in a global sample of 53 populations, using genotype data from the Human Genome Diversity-CEPH Panel, suggests that there has been selection on loci involved in susceptibility to type II diabetes.
Journal ArticleDOI

Human autoimmune diseases: a comprehensive update.

TL;DR: The identification of cytokines and chemokines, and their cognate receptors, has led to novel therapies that block pathological inflammatory responses within the target organ and have greatly improved the therapeutic effect in patients with autoimmune disease, particularly rheumatoid arthritis.
References
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Book

Econometric Analysis of Cross Section and Panel Data

TL;DR: This is the essential companion to Jeffrey Wooldridge's widely-used graduate text Econometric Analysis of Cross Section and Panel Data (MIT Press, 2001).
Journal ArticleDOI

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

TL;DR: This work introduces PLINK, an open-source C/C++ WGAS tool set, and describes the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation, which focuses on the estimation and use of identity- by-state and identity/descent information in the context of population-based whole-genome studies.
Journal ArticleDOI

The sequence of the human genome.

J. Craig Venter, +272 more
- 16 Feb 2001 - 
TL;DR: Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems are indicated.
Journal ArticleDOI

Database resources of the National Center for Biotechnology Information

TL;DR: In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s website.
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