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. 2010 Dec 10;87(6):779-89.
doi: 10.1016/j.ajhg.2010.10.024.

Gene expression in skin and lymphoblastoid cells: Refined statistical method reveals extensive overlap in cis-eQTL signals

Jun Ding  1 , Johann E Gudjonsson, Liming Liang, Philip E Stuart, Yun Li, Wei Chen, Michael Weichenthal, Eva Ellinghaus, Andre Franke, William Cookson, Rajan P Nair, James T Elder, Gonçalo R Abecasis
Affiliations

Gene expression in skin and lymphoblastoid cells: Refined statistical method reveals extensive overlap in cis-eQTL signals

Jun Ding et al. Am J Hum Genet. .

Abstract

Psoriasis, an immune-mediated, inflammatory disease of the skin and joints, provides an ideal system for expression quantitative trait locus (eQTL) analysis, because it has a strong genetic basis and disease-relevant tissue (skin) is readily accessible. To better understand the role of genetic variants regulating cutaneous gene expression, we identified 841 cis-acting eQTLs using RNA extracted from skin biopsies of 53 psoriatic individuals and 57 healthy controls. We found substantial overlap between cis-eQTLs of normal control, uninvolved psoriatic, and lesional psoriatic skin. Consistent with recent studies and with the idea that control of gene expression can mediate relationships between genetic variants and disease risk, we found that eQTL SNPs are more likely to be associated with psoriasis than are randomly selected SNPs. To explore the tissue specificity of these eQTLs and hence to quantify the benefits of studying eQTLs in different tissues, we developed a refined statistical method for estimating eQTL overlap and used it to compare skin eQTLs to a published panel of lymphoblastoid cell line (LCL) eQTLs. Our method accounts for the fact that most eQTL studies are likely to miss some true eQTLs as a result of power limitations and shows that ∼70% of cis-eQTLs in LCLs are shared with skin, as compared with the naive estimate of < 50% sharing. Our results provide a useful method for estimating the overlap between various eQTL studies and provide a catalog of cis-eQTLs in skin that can facilitate efforts to understand the functional impact of identified susceptibility variants on psoriasis and other skin traits.

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Figures

Figure 1
Figure 1
Simplified Diagram for Categorization of Significant eQTLs from Study1 into Groups for the Estimation of the Overlap Percentage
Figure 2
Figure 2
Regional Plots for Evidence of cis-Association between SNPs and ERAP2 or RPS26 The most significant SNPs (the most significant SNP associated with ERAP2 in normal skin on the left panel; the most significant SNP associated with RPS26 in uninvolved skin on the right panel) are highlighted with a square. The other SNPs are drawn as circles and color coded according to the degree of linkage disequilibrium with the most significant SNP.
Figure 3
Figure 3
The Sharing of cis-eQTLs in Normal, Uninvolved, and Lesional Skin with the Other Two Types of Skin The p value threshold for discovery is 9 × 10−7, and the p value threshold for replication is 0.05.
Figure 4
Figure 4
Quantile-Quantile Plot of Psoriasis GWAS p Values for 389 Independent eQTL SNPs in Skin, with Confidence Intervals Defined by Non-eQTL SNPs
See this image and copyright information in PMC

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