Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Abstract

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

Fig. 1

Overview of the fine-mapping workflow. Flowchart describing the procedure followed during fine-mapping, providing an overview of the outcomes at each stage and suggesting possible applications for the final catalogue of variants

Fig. 2

Polar bar plot depicting the proportion of tag variants assigned each functional annotation within the 95% credible set selected by JAM (red bars), relative to tags that were not selected as candidates during fine-mapping (blue bars). Binary annotations for all respective proxy variants were inherited by their tag. Annotations are grouped by category and ordered according to the proportion of variants in the credible set that receive each specific annotation. For greater clarity at lower values the plot axis is capped at 50%, therefore for annotation classes that exceed this limit (Heterochromatin and Coding) the total percentage of tags receiving the annotation is specified in brackets

Fig. 3

Locus Explorer plots of results and annotations at three regions. a Chr2q37-ANO7; b Chr6q22-RFX6; c Chr21q22-TMPRSS2. Upper section shows regional association plots for the initial EUR meta-analysis data depicting variant P-values (−log₁₀(P) panel) and fine-mapping results indicating the posterior probability of association for priority pruner tags (PostProb panel). Triangles and circles on the meta-analysis plot denote variants directly genotyped in the OncoArray study and imputed variants respectively, with colours used to indicate all variants in linkage disequilibrium (LD) at r² > 0.5 with those selected in the credible set. Names of the representative variants for each independent signal used in the familial relative risk calculation are shown in black and the original GWAS tag SNP marked in red. Only variants selected in the credible set are shown on the fine-mapping results plot, with positions of tags included in the 95% credible set marked as dashed lines and positions of all their respective proxy SNPs indicated as coloured circles. Middle section shows additional information regarding the density of directly genotyped variants within the OncoArray cohort and total imputed markers analysed (SNP panel) and the extent of variation correlated with tags in the credible set at LD r² > 0.5 (R² panel). Lower section indicates the relative positions of genes and biological annotations. Genes on the positive and negative strand are denoted by green and purple colours, respectively. Annotations displayed are as follows: histone modifications in ENCODE tier 1 cell lines (Histone track); the positions of variants that are eQTLs with prostate tumour expression in TCGA prostate adenocarcinoma samples and the respective genes for which expression is altered (eQTL track); chromatin state categorisations in the PrEC cell line by ChromHMM (ChromHMM track); the position of conserved element peaks (Conserved track); and the position of DNaseI hypersensitivity site peaks in ENCODE prostate cell lines (DNaseI track)