In genome‐wide association studies, signals associated with rare variants and interactions between genes are hard to detect even when the sample size is in tens of thousands. To overcome these problems, we examine the concept of supervariant. Like the classic concept of the gene, a supervariant is a combination of alleles in multiple loci, but the contributing loci can be anywhere in the genome. We hypothesize that supervariants are easy to detect and the aggregated signals are more stable in their associations with the disease than that from a single nucleoid polymorphism. Using the UK Biobank databases, we develop a ranking and aggregation method for identifying supervariants. Specifically, we examine 9,377 breast cancer cases with 46,861 controls matched by sex and age. In our simulations, the use of supervariants outperforms single‐nucleotide polymorphism‐based association method in detecting rare variants and signals with interactive structure. In real data analysis, we identify supervariants on Chromosomes 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 16, and 22 which cover previously reported loci that have associations with breast or other cancers, and several novel loci on Chromosomes 2, 5, 9, and 12. These findings demonstrate the validity of supervariants and its potential of discovering replicable and novel results for complex disease.

中文翻译：

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乳腺癌的超变体鉴定。

在全基因组关联研究中，即使样本量达到数万，与罕见变异和基因之间相互作用相关的信号也很难检测到。为了克服这些问题，我们研究了超变的概念。与基因的经典概念一样，超变体是多个基因座中等位基因的组合，但贡献基因座可以位于基因组中的任何位置。我们假设超变体很容易检测，并且聚集的信号与疾病的关联比来自单个核多态性的信号更稳定。使用英国生物银行数据库，我们开发了一种用于识别超变体的排名和聚合方法。具体来说，我们检查了 9,377 例乳腺癌病例和 46,861 名性别和年龄匹配的对照者。在我们的模拟中，在检测具有交互结构的罕见变异和信号方面，超变体的使用优于基于单核苷酸多态性的关联方法。在实际数据分析中，我们识别了 1、2、3、5、6、7、8、9、10、11、16 和 22 号染色体上的超变体，这些超变体涵盖了先前报道的与乳腺癌或其他癌症相关的位点，以及一些2、5、9 和 12 号染色体上的新位点。这些发现证明了超变体的有效性及其为复杂疾病发现可复制和新颖结果的潜力。