Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892-4608, USA.
Carcinogenesis. 2010 Jan;31(1):111-20. doi: 10.1093/carcin/bgp273. Epub 2009 Nov 11.
Genome-wide association studies (GWAS) have emerged as an important tool for discovering regions of the genome that harbor genetic variants that confer risk for different types of cancers. The success of GWAS in the last 3 years is due to the convergence of new technologies that can genotype hundreds of thousands of single-nucleotide polymorphism markers together with comprehensive annotation of genetic variation. This approach has provided the opportunity to scan across the genome in a sufficiently large set of cases and controls without a set of prior hypotheses in search of susceptibility alleles with low effect sizes. Generally, the susceptibility alleles discovered thus far are common, namely, with a frequency in one or more population of >10% and each allele confers a small contribution to the overall risk for the disease. For nearly all regions conclusively identified by GWAS, the per allele effect sizes estimated are <1.3. Consequently, the findings of GWAS underscore the complex nature of cancer and have focused attention on a subset of the genetic variants that comprise the genomic architecture of each type of cancer, which already can differ substantially by the number of regions associated with specific types of cancer. For instance, in prostate cancer, there could be >30 distinct regions harboring common susceptibility alleles identified by GWAS, whereas in lung cancer, a disease strongly driven by exposure to tobacco products, so far, only three regions have been conclusively established. To date, >85 regions have been conclusively associated in over a dozen different cancers, yet no more than five regions have been associated with more than one distinct cancer type. GWAS are an important discovery tool that require extensive follow-up to map each region, investigate the biological mechanism underpinning the association and eventually test the optimal markers for assessing risk for a disease or its outcome, such as in pharmacogenomics, the study of the effect of genetic variation on pharmacological interventions. The success of GWAS has opened new horizons for exploration and highlighted the complex genomic architecture of disease susceptibility.
全基因组关联研究（GWAS）已成为发现基因组中携带遗传变异的区域的重要工具，这些遗传变异赋予了不同类型癌症的风险。在过去的 3 年中，GWAS 的成功归因于新技术的融合，这些技术可以同时对数十万种单核苷酸多态性标记进行基因分型，并对遗传变异进行全面注释。这种方法提供了在足够大的病例和对照集中扫描基因组的机会，而无需一组先验假设来寻找具有低效应大小的易感性等位基因。通常，迄今为止发现的易感性等位基因是常见的，即在一个或多个人群中的频率>10%，每个等位基因对疾病的总体风险贡献很小。对于 GWAS 几乎所有明确确定的区域，估计的每个等位基因的效应大小都<1.3。因此，GWAS 的发现强调了癌症的复杂性，并将注意力集中在构成每种癌症基因组结构的遗传变异子集上，这些遗传变异已经可以因与特定类型癌症相关的区域数量而有很大差异。例如，在前列腺癌中，可能有>30 个不同的区域携带有 GWAS 确定的常见易感性等位基因，而在肺癌中，这种疾病强烈受到烟草产品暴露的驱动，到目前为止，只有三个区域得到了明确的确定。迄今为止，在十多种不同的癌症中已经有>85 个区域得到了明确的关联，但没有超过五个区域与一种以上的不同癌症类型有关。GWAS 是一种重要的发现工具，需要进行广泛的后续研究来绘制每个区域的图谱，研究关联背后的生物学机制，并最终测试评估疾病或其结果风险的最佳标记，如在药物遗传学中，研究遗传变异对药物干预的影响。GWAS 的成功为探索开辟了新的视野，并强调了疾病易感性的复杂基因组结构。
