Genome-wide association studies (GWASs) are highly effective at identifying common risk variants for schizophrenia. Rare risk variants are also important contributors to schizophrenia etiology but, with the exception of large copy number variants, are difficult to detect with GWAS. Exome and genome sequencing, which have accelerated the study of rare variants, are expensive so alternative methods are needed to aid detection of rare variants. Here we re-analyze an Irish schizophrenia GWAS dataset (n = 3,473) by performing identity-by-descent (IBD) mapping followed by exome sequencing of individuals identified as sharing risk haplotypes to search for rare risk variants in coding regions. We identified 45 rare haplotypes (>1 cM) that were significantly more common in cases than controls. By exome sequencing 105 haplotype carriers, we investigated these haplotypes for functional coding variants that could be tested for association in independent GWAS samples. We identified one rare missense variant in PCNT but did not find statistical support for an association with schizophrenia in a replication analysis. However, IBD mapping can prioritize both individual samples and genomic regions for follow-up analysis but genome rather than exome sequencing may be more effective at detecting risk variants on rare haplotypes.

中文翻译：

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基于人群的血统身份图谱与外显子组测序相结合，可检测精神分裂症的罕见风险变异。

全基因组关联研究 (GWAS) 在识别精神分裂症的常见风险变异方面非常有效。罕见的风险变异也是精神分裂症病因的重要贡献者，但除了大拷贝数变异外，很难用 GWAS 检测到。外显子组和基因组测序加速了罕见变异的研究，但价格昂贵，因此需要替代方法来帮助检测罕见变异。在这里，我们重新分析了爱尔兰精神分裂症 GWAS 数据集（n = 3,473），方法是执行血统身份（IBD）作图，然后对被确定为共享风险单倍型的个体进行外显子组测序，以搜索编码区域中的罕见风险变异。我们鉴定了 45 种罕见的单倍型（> 1 cM），它们在病例中比对照组更常见。通过对 105 个单倍型携带者进行外显子组测序，我们研究了这些单倍型的功能编码变体，这些变体可以在独立 GWAS 样本中进行关联测试。我们在 PCNT 中发现了一种罕见的错义变异，但在复制分析中没有找到与精神分裂症相关的统计支持。然而，IBD 作图可以优先考虑单个样本和基因组区域以进行后续分析，但基因组测序（而不是外显子组测序）在检测罕见单倍型的风险变异方面可能更有效。