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Association Mapping and Disease: Evolutionary Perspectives.

Søren Besenbacher1, Thomas Mailund2, Bjarni J Vilhjálmsson2

  • 1Department of Clinical Medicine (MOMA), Aarhus University, Aarhus N, Denmark. besenbacher@clin.au.dk.

Methods in Molecular Biology (Clifton, N.J.)
|July 7, 2019
PubMed
Summary
This summary is machine-generated.

This chapter introduces the genetics of complex diseases, focusing on evolutionary models for disease genes and their impact on genetic architecture. It also surveys the current landscape of genome-wide association studies (GWASs).

Keywords:
Association mappingCommon disease/common variantComplex diseasesGenome-wide association studies

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Area of Science:

  • Genetics
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Complex diseases result from interactions between multiple genes and environmental factors.
  • Understanding the genetic basis of complex diseases is crucial for developing effective treatments.
  • Evolutionary models offer insights into the origins and maintenance of genetic variation underlying disease susceptibility.

Purpose of the Study:

  • To provide an introduction to the genetics of complex diseases.
  • To emphasize the role of evolutionary models in understanding disease genes.
  • To survey the current state of genome-wide association studies (GWASs).

Main Methods:

  • Review of evolutionary models for disease gene identification.
  • Discussion of the impact of different evolutionary models on genetic architecture.
  • Survey of current genome-wide association studies (GWASs) methodologies and findings.

Main Results:

  • Evolutionary models provide a framework for interpreting the genetic architecture of complex diseases.
  • Genome-wide association studies (GWASs) have identified numerous genetic variants associated with complex diseases.
  • The interplay between evolutionary pressures and genetic variation influences disease prevalence.

Conclusions:

  • A comprehensive understanding of complex disease genetics requires integrating evolutionary perspectives with large-scale genomic data.
  • Genome-wide association studies (GWASs) are powerful tools for dissecting the genetic underpinnings of complex diseases.
  • Future research should focus on refining evolutionary models and applying them to GWAS data for deeper insights into disease etiology.