Autism spectrum disorder (ASD) has phenotypically and genetically heterogeneous characteristics. A simulation study demonstrated that attempts to categorize patients with a complex disease into more homogeneous subgroups could have more power to elucidate hidden heritability. We conducted cluster analyses using the k-means algorithm with a cluster number of 15 based on phenotypic variables from the Simons Simplex Collection (SSC). As a preliminary study, we conducted a conventional genome-wide association study (GWAS) with a data set of 597 ASD cases and 370 controls. In the second step, we divided cases based on the clustering results and conducted GWAS in each of the subgroups vs controls (cluster-based GWAS). We also conducted cluster-based GWAS on another SSC data set of 712 probands and 354 controls in the replication stage. In the preliminary study, which was conducted in conventional GWAS design, we observed no significant associations. In the second step of cluster-based GWASs, we identified 65 chromosomal loci, which included 30 intragenic loci located in 21 genes and 35 intergenic loci that satisfied the threshold of P < 5.0 × 10⁻⁸. Some of these loci were located within or near previously reported candidate genes for ASD: CDH5, CNTN5, CNTNAP5, DNAH17, DPP10, DSCAM, FOXK1, GABBR2, GRIN2A5, ITPR1, NTM, SDK1, SNCA, and SRRM4. Of these 65 significant chromosomal loci, rs11064685 located within the SRRM4 gene had a significantly different distribution in the cases vs controls in the replication cohort. These findings suggest that clustering may successfully identify subgroups with relatively homogeneous disease etiologies. Further cluster validation and replication studies are warranted in larger cohorts.

自闭症谱系障碍（ASD）具有表型和遗传异质性特征。一项模拟研究表明，将复杂疾病患者分为更均一的亚组的尝试可能具有更大的能力来阐明隐藏的遗传力。我们基于来自Simons Simplex Collection（SSC）的表型变量，使用k-means算法进行了聚类分析，聚类数为15。作为初步研究，我们进行了常规的全基因组关联研究（GWAS），其数据集包括597个ASD病例和370个对照。在第二步中，我们基于聚类结果对案例进行划分，并在每个子组与控件（基于集群的GWAS）中进行了GWAS。在复制阶段，我们还对712个先证者和354个对照的另一个SSC数据集进行了基于群集的GWAS。在常规GWAS设计中进行的初步研究中，我们没有发现明显的关联。在基于集群的GWAS的第二步中，我们确定了65个染色体基因座，其中包括位于21个基因中的30个基因内基因座和35个满足基因组阈值的基因间基因座。P  ＜5.0×10 ^-8。这些基因座中的一些位于先前报道的ASD候选基因内或附近：CDH5，CNTN5，CNTNAP5，DNAH17，DPP10，DSCAM，FOXK1，GABBR2，GRIN2A 5，ITPR1，NTM，SDK1，SNCA和SRRM4。在这65个重要的染色体位点中，位于SRRM4基因内的rs11064685在病例中与在复制队列中的对照组相比具有明显不同的分布。这些发现表明，聚类可以成功地确定具有相对均一的病因的亚组。在更大的队列中，需要进一步的集群验证和复制研究。