Detecting genetic variants enables risk factor identification, disease screening, and initiation of preventative therapeutics. However, current methods, relying on hybridization or sequencing, are unsuitable for point-of-care settings. In contrast, CRISPR-based-diagnostics offer high sensitivity and specificity for point-of-care applications. While these methods have predominantly been used for pathogen sensing, their utilization for genotyping is limited. Here, we report a multiplexed CRISPR-based genotyping assay using LwaCas13a, PsmCas13b, and LbaCas12a, enabling the simultaneous detection of six genotypes. We applied this assay to identify genetic variants in the APOL1 gene prevalent among African Americans, which are associated with an 8-30-fold increase in the risk of developing kidney disease. Machine learning facilitated robust analysis across a multicenter clinical cohort of more than 100 patients, accurately identifying their genotypes. In addition, we optimized the readout using a multi-analyte lateral-flow assay demonstrating the ability for simplified genotype determination of clinical samples. Our CRISPR-based genotyping assay enables cost-effective point-of-care genetic variant detection due to its simplicity, versatility, and fast readout.

中文翻译：

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用于 APOL1 遗传风险评估的 CRISPR 支持的即时基因分型。


检测遗传变异有助于识别风险因素、筛查疾病和开始预防性治疗。然而，目前依赖于杂交或测序的方法不适用于床旁环境。相比之下，基于 CRISPR 的诊断为即时应用提供了高灵敏度和特异性。虽然这些方法主要用于病原体传感，但它们在基因分型中的应用是有限的。在这里，我们报道了一种使用 LwaCas13a、PsmCas13b 和 LbaCas12a 的基于 CRISPR 的多重基因分型测定，能够同时检测六种基因型。我们应用该测定法来识别非裔美国人中普遍存在的 APOL1 基因的遗传变异，这与患肾病风险增加 8-30 倍有关。机器学习促进了对 100 多名患者的多中心临床队列的稳健分析，准确识别了他们的基因型。此外，我们使用多分析物侧流测定优化了读数，证明了简化临床样本基因型测定的能力。我们基于 CRISPR 的基因分型检测试剂盒具有简单性、多功能性和快速读数性，可实现经济高效的即时遗传变异检测。