CRISPR-enabled point-of-care genotyping for APOL1 genetic risk assessment
Name
44321_2024_Article_126.pdf
Size
2.5 MB
Format
Adobe PDF
Checksum (MD5)
443c9065867892873d5c629f6fde85ae
Author(s)
Greensmith, Robert
Lape, Isadora T.
Riella, Cristian V.
Schubert, Alexander J.
Metzger, Jakob J.
Dighe, Anand S.
Tan, Xiao
Hemmer, Bernhard
Rau, Josefine
Wendlinger, Sarah
Date Issued
September 13, 2024
Journal
EMBO Molecular Medicine
Publisher
Nature Publishing Group UK
Citation
Greensmith, Robert, Lape, Isadora T., Riella, Cristian V., Schubert, Alexander J., Metzger, Jakob J. et al. 2024. "CRISPR-enabled point-of-care genotyping for APOL1 genetic risk assessment." EMBO Molecular Medicine.
Version
Final published version
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Massachusetts Institute of Technology. Department of Biological Engineering
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1038/s44321-024-00126-x
