Abstract
Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.
Highlights
Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci
To translate GWAS findings into an improved understanding of the biology underlying disease risk, it is essential to first identify the target genes of risk-associated variants. This is not straightforward because most risk variants lie in non-coding regions, enhancers, many of which do not target the nearest gene[4]. To help with this task, we recently developed a pipeline that identifies likely target genes of breast cancer risk variants based on breast tissue-specific genomic data, such as promoter–enhancer chromatin interactions and expression quantitative trait loci[2]
For each gene and for a given expression quantitative trait loci (eQTL) dataset, we identified cis eQTL in low linkage disequilibrium (LD; r2 < 0.05) with each other, and with an association with gene expression significant at a conservative significance threshold of 8.9 × 10−10
Summary
Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. This is not straightforward because most risk variants lie in non-coding regions, enhancers, many of which do not target the nearest gene[4] To help with this task, we recently developed a pipeline that identifies likely target genes of breast cancer risk variants based on breast tissue-specific genomic data, such as promoter–enhancer chromatin interactions and expression quantitative trait loci (eQTL)[2]. Using this approach, called INQUISIT, we identified 689 genes as potential targets of the breast cancer risk variants. Gene-based analyses would be expected to identify previously unreported risk loci if, for example, multiple independent eQTL for a given gene are individually associated with disease risk, but not at the genome-wide significance level used for single-variant analyses
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