Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, 90095, CA, USA.
The Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, 90048, CA, USA.
Nat Commun. 2018 Oct 4;9(1):4079. doi: 10.1038/s41467-018-06302-1.
Although genome-wide association studies (GWAS) for prostate cancer (PrCa) have identified more than 100 risk regions, most of the risk genes at these regions remain largely unknown. Here we integrate the largest PrCa GWAS (N = 142,392) with gene expression measured in 45 tissues (N = 4458), including normal and tumor prostate, to perform a multi-tissue transcriptome-wide association study (TWAS) for PrCa. We identify 217 genes at 84 independent 1 Mb regions associated with PrCa risk, 9 of which are regions with no genome-wide significant SNP within 2 Mb. 23 genes are significant in TWAS only for alternative splicing models in prostate tumor thus supporting the hypothesis of splicing driving risk for continued oncogenesis. Finally, we use a Bayesian probabilistic approach to estimate credible sets of genes containing the causal gene at a pre-defined level; this reduced the list of 217 associations to 109 genes in the 90% credible set. Overall, our findings highlight the power of integrating expression with PrCa GWAS to identify novel risk loci and prioritize putative causal genes at known risk loci.
尽管全基因组关联研究（GWAS）已经确定了超过 100 个前列腺癌（PrCa）的风险区域，但这些区域的大多数风险基因仍很大程度上未知。在这里，我们整合了最大的前列腺癌 GWAS（N=142392）和 45 种组织（N=4458）中测量的基因表达数据，进行了前列腺癌的多组织转录组全基因组关联研究（TWAS）。我们在 84 个独立的 1Mb 区域中确定了 217 个与前列腺癌风险相关的基因，其中 9 个是在 2Mb 范围内没有全基因组显著 SNP 的区域。在 TWAS 中，只有 23 个基因在前列腺肿瘤的剪接模型中具有统计学意义，这支持了剪接驱动持续致癌风险的假说。最后，我们使用贝叶斯概率方法来估计包含预定水平因果基因的可信基因集；这将 217 个关联中的 90%可信集列表减少到 109 个基因。总的来说，我们的研究结果强调了将表达与前列腺癌 GWAS 相结合以识别新的风险区域和优先考虑已知风险区域中潜在因果基因的力量。
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