ProRegeM-PhD Program in Mechanisms of Disease and Regenerative Medicine, Universidade do Algarve, 805-139 Faro, Portugal; Faculty of Medicine and Biomedical Sciences, Gambelas Campus, 805-139 Faro, Portugal.
Center for Research in Health Technologies and Information Systems (CINTESIS), Universidade do Algarve, Faro, Portugal.
Eur J Cancer. 2022 Sep;172:146-157. doi: 10.1016/j.ejca.2022.05.034. Epub 2022 Jun 27.
Translation of genome-wide association study (GWAS) findings into preventive approaches is challenged by the identification of the causal risk variants and the understanding of the biological mechanisms by which they act. We present using allelic expression (AE) ratios to perform quantitative case-control analysis as a novel approach to identify risk associations, causal regulatory variants, and target genes.
Using the breast cancer (BC) risk locus 17q22 to validate this approach, we measured AE ratios in normal breast tissue samples from controls and cases, as well as from unmatched blood samples. Then we used in-silico and in-vitro analysis to map and functionally characterised candidate causal variants.
We found a significant shift in the AE patterns of STXBP4 (rs2628315) and COX11 (rs17817901) in the normal breast tissue of cases and healthy controls. Preferential expression of the G-rs2628315 and A-rs17817901 alleles, more often observed in cases, was associated with an increased risk for BC. Analysis of blood samples from cases and controls found a similar association. Furthermore, we identified two putative cis-regulatory variants - rs17817901 and rs8066588 - that affect a miRNA and a transcription factor binding site, respectively.
We propose causal variants and target genes for the 17q22 BC risk locus and show that using AE ratios in case-control association studies is helpful in identifying risk and mapping causal variants.
将全基因组关联研究(GWAS)的发现转化为预防方法受到鉴定因果风险变异和理解其作用的生物学机制的挑战。我们提出使用等位基因表达(AE)比率进行定量病例对照分析,作为一种识别风险关联、因果调节变异和靶基因的新方法。
使用乳腺癌(BC)风险位点 17q22 来验证这种方法,我们测量了对照和病例以及不匹配的血液样本中正常乳腺组织样本中的 AE 比率。然后,我们使用计算机模拟和体外分析来映射和功能表征候选因果变异。
我们发现病例和健康对照者正常乳腺组织中 STXBP4(rs2628315)和 COX11(rs17817901)的 AE 模式发生了显著变化。在病例中更常观察到的 G-rs2628315 和 A-rs17817901 等位基因的优先表达与 BC 风险增加相关。对病例和对照者的血液样本进行分析发现了类似的关联。此外,我们鉴定了两个可能的顺式调节变异体 - rs17817901 和 rs8066588 - 分别影响 miRNA 和转录因子结合位点。
我们提出了 17q22 BC 风险位点的因果变异和靶基因,并表明在病例对照关联研究中使用 AE 比率有助于识别风险和映射因果变异。