Genetic association analysis of complex diseases incorporating intermediate phenotype information

PLoS One. 2012;7(10):e46612. doi: 10.1371/journal.pone.0046612. Epub 2012 Oct 19.

Abstract

Genetic researchers often collect disease related quantitative traits in addition to disease status because they are interested in understanding the pathophysiology of disease processes. In genome-wide association (GWA) studies, these quantitative phenotypes may be relevant to disease development and serve as intermediate phenotypes or they could be behavioral or other risk factors that predict disease risk. Statistical tests combining both disease status and quantitative risk factors should be more powerful than case-control studies, as the former incorporates more information about the disease. In this paper, we proposed a modified inverse-variance weighted meta-analysis method to combine disease status and quantitative intermediate phenotype information. The simulation results showed that when an intermediate phenotype was available, the inverse-variance weighted method had more power than did a case-control study of complex diseases, especially in identifying susceptibility loci having minor effects. We further applied this modified meta-analysis to a study of imputed lung cancer genotypes with smoking data in 1154 cases and 1137 matched controls. The most significant SNPs came from the CHRNA3-CHRNA5-CHRNB4 region on chromosome 15q24-25.1, which has been replicated in many other studies. Our results confirm that this CHRNA region is associated with both lung cancer development and smoking behavior. We also detected three significant SNPs--rs1800469, rs1982072, and rs2241714--in the promoter region of the TGFB1 gene on chromosome 19 (p = 1.46×10(-5), 1.18×10(-5), and 6.57×10(-6), respectively). The SNP rs1800469 is reported to be associated with chronic obstructive pulmonary disease and lung cancer in cigarette smokers. The present study is the first GWA study to replicate this result. Signals in the 3q26 region were also identified in the meta-analysis. We demonstrate the intermediate phenotype can potentially enhance the power of complex disease association analysis and the modified meta-analysis method is robust to incorporate intermediate phenotype or other quantitative risk factor in the analysis.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Analysis of Variance
  • Case-Control Studies
  • Chromosome Mapping
  • Chromosomes, Human, Pair 15
  • Chromosomes, Human, Pair 19
  • Genome-Wide Association Study / methods
  • Genome-Wide Association Study / statistics & numerical data*
  • Genotype*
  • Humans
  • Lung Neoplasms / etiology
  • Lung Neoplasms / genetics*
  • Meta-Analysis as Topic
  • Nerve Tissue Proteins / genetics
  • Phenotype*
  • Polymorphism, Single Nucleotide*
  • Promoter Regions, Genetic
  • Receptors, Nicotinic / genetics
  • Risk Factors
  • Smoking / adverse effects
  • Smoking / genetics*
  • Transforming Growth Factor beta1 / genetics

Substances

  • CHRNA5 protein, human
  • Nerve Tissue Proteins
  • Receptors, Nicotinic
  • TGFB1 protein, human
  • Transforming Growth Factor beta1
  • nicotinic acetylcholine receptor alpha4 subunit
  • nicotinic receptor subunit alpha3