The Annals of Applied Statistics

Joint analysis of SNP and gene expression data in genetic association studies of complex diseases

Yen-Tsung Huang, Tyler J. VanderWeele, and Xihong Lin

Full-text: Open access

Abstract

Genetic association studies have been a popular approach for assessing the association between common Single Nucleotide Polymorphisms (SNPs) and complex diseases. However, other genomic data involved in the mechanism from SNPs to disease, for example, gene expressions, are usually neglected in these association studies. In this paper, we propose to exploit gene expression information to more powerfully test the association between SNPs and diseases by jointly modeling the relations among SNPs, gene expressions and diseases. We propose a variance component test for the total effect of SNPs and a gene expression on disease risk. We cast the test within the causal mediation analysis framework with the gene expression as a potential mediator. For eQTL SNPs, the use of gene expression information can enhance power to test for the total effect of a SNP-set, which is the combined direct and indirect effects of the SNPs mediated through the gene expression, on disease risk. We show that the test statistic under the null hypothesis follows a mixture of $\chi^{2}$ distributions, which can be evaluated analytically or empirically using the resampling-based perturbation method. We construct tests for each of three disease models that are determined by SNPs only, SNPs and gene expression, or include also their interactions. As the true disease model is unknown in practice, we further propose an omnibus test to accommodate different underlying disease models. We evaluate the finite sample performance of the proposed methods using simulation studies, and show that our proposed test performs well and the omnibus test can almost reach the optimal power where the disease model is known and correctly specified. We apply our method to reanalyze the overall effect of the SNP-set and expression of the ORMDL3 gene on the risk of asthma.

Article information

Source
Ann. Appl. Stat., Volume 8, Number 1 (2014), 352-376.

Dates
First available in Project Euclid: 8 April 2014

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1396966290

Digital Object Identifier
doi:10.1214/13-AOAS690

Mathematical Reviews number (MathSciNet)
MR3191994

Zentralblatt MATH identifier
06302239

Keywords
Causal inference data integration mediation analysis mixed models score test SNP set analysis variance component test

Citation

Huang, Yen-Tsung; VanderWeele, Tyler J.; Lin, Xihong. Joint analysis of SNP and gene expression data in genetic association studies of complex diseases. Ann. Appl. Stat. 8 (2014), no. 1, 352--376. doi:10.1214/13-AOAS690. https://projecteuclid.org/euclid.aoas/1396966290


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Supplemental materials

  • Supplementary material: Detailed causal and statistical development and supplementary table and figures. Section 1: detailed development of causal mediation model and derivations referenced in Sections 4.1 and 4.2; Section 2: derivation of model (4.7) in Sections 4.4; Section 3: asymptotic distribution of $Q$ referenced in Section 3.1; table and figures referenced in Sections 5.2 and 5.4.