The state of genome-wide association studies in pulmonary disease: a new perspective.

Published

Journal Article (Review)

With rapid advances in our knowledge of the human genome and increasing availability of high-throughput investigative technology, genome-wide association (GWA) studies have recently gained marked popularity. As an unbiased approach to identifying genomic regions of importance in complex human disease, the results of such studies have the potential to illuminate novel causal pathways, guide mechanistic research, and aid in prediction of disease risk. The use of a genome-wide approach presents considerable methodological and statistical challenges, and properly conducted studies are essential to avoid false-positive results. A total of 22 GWA studies have been published in pulmonary medicine thus far, implicating several intriguing genomic regions in the determination of pulmonary function measures, onset of asthma, and susceptibility to chronic obstructive pulmonary disease. Many questions remain, however, as most identified genetic variants contribute only nominally to overall disease risk, genetic disease mechanisms remain uncertain, and disease-associated variants are not consistent across studies. Perhaps most fundamentally, the association signals identified have not yet been traced to causal variants. This perspective will review the current state of GWA studies in pulmonary disease. We begin with an introduction to the hypothesis, principles, and limitations of this type of genome-wide approach, highlight key points from available studies, and conclude by addressing future approaches to better understand the genetics of complex pulmonary disease.

Full Text

Duke Authors

Cited Authors

  • Todd, JL; Goldstein, DB; Ge, D; Christie, J; Palmer, SM

Published Date

  • October 2011

Published In

Volume / Issue

  • 184 / 8

Start / End Page

  • 873 - 880

PubMed ID

  • 21799071

Pubmed Central ID

  • 21799071

Electronic International Standard Serial Number (EISSN)

  • 1535-4970

International Standard Serial Number (ISSN)

  • 1073-449X

Digital Object Identifier (DOI)

  • 10.1164/rccm.201106-0971PP

Language

  • eng