Implications of human genetic variation in CRISPR-based therapeutic genome editing.
Implications of human genetic variation in CRISPR-based therapeutic genome editing.
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DOI：
10.1038/nm.4377
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发表时间：
2017-09
期刊：
影响因子：
82.9
通讯作者：
Zhang F
中科院分区：
文献类型：
--
作者：
Scott DA;Zhang F
CRISPR-Cas基因组编辑方法具有巨大的潜力，可以作为治疗工具在DNA水平上修复致病突变。与针对个体患者中高度保守的靶点的典型药物开发策略相反，在基因组水平上治疗疾病必须与显著的个体间天然遗传变异相抗衡。在这里，我们分析了最近发布的ExAC（http：exac.broadinstitute.org）和1000个基因组数据集（http：www.internationalgenome.org），以确定人类遗传变异如何影响治疗性基因组编辑背景下的Cas内切核酸酶靶标选择。我们发现，这种变异比其他变异更容易混淆某些Cas内切核酸酶的靶位点，我们提供了一个指导RNA的纲要，预测在不同的患者群体中具有高疗效。为了进一步分析，我们专注于12个治疗相关的基因，并考虑遗传变异如何影响这些位点的脱靶候选人。我们的分析表明，在大量的个体中，大多数候选脱靶位点将是罕见的，这强调了通过全基因组测序对患者进行预筛选以确保安全性的必要性。这些信息可以与指导RNA选择的经验方法整合到一个框架中，用于设计基于CRISPR的治疗方法，以最大限度地提高患者群体的疗效和安全性。
CRISPR-Cas genome editing methods hold immense potential as therapeutic tools to fix disease-causing mutations at the level of DNA. In contrast to typical drug development strategies aimed at targets that are highly conserved among individual patients, treatment of disease at the genomic level must contend with significant inter-individual natural genetic variation. Here we analyze the recently released ExAC (http://exac.broadinstitute.org) and 1000 Genomes datasets (http://www.internationalgenome.org) to determine how human genetic variation impacts Cas endonuclease target choice in the context of therapeutic genome editing. We find that this variation confounds the target sites of certain Cas endonucleases more than others and we provide a compendium of guide RNAs predicted to have high efficacy in diverse patient populations. For further analysis, we focus on 12 therapeutically relevant genes and consider how genetic variation affects off-target candidates for these loci. Our analysis suggests that in large populations of individuals, most candidate off-target sites will be rare, underscoring the need for pre-screening of patients through whole genome sequencing to ensure safety. This information can be integrated with empirical methods for guide RNA selection into a framework for designing CRISPR-based therapeutics that maximize efficacy and safety across patient populations.
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