CRISPR-enabled point-of-care genotyping for APOL1 genetic risk assessment
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...
| Main Authors: | , , , , , , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group UK
2024
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| Online Access: | https://hdl.handle.net/1721.1/156882 |
| _version_ | 1811075710036475904 |
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| author | 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 Diederich, Nora Schütz, Anja Riella, Leonardo V. |
| author2 | Massachusetts Institute of Technology. Institute for Medical Engineering & Science |
| author_facet | Massachusetts Institute of Technology. Institute for Medical Engineering & Science 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 Diederich, Nora Schütz, Anja Riella, Leonardo V. |
| author_sort | Greensmith, Robert |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T10:10:22Z |
| format | Article |
| id | mit-1721.1/156882 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T10:10:22Z |
| publishDate | 2024 |
| publisher | Nature Publishing Group UK |
| record_format | dspace |
| spelling | mit-1721.1/1568822024-09-18T03:51:00Z CRISPR-enabled point-of-care genotyping for APOL1 genetic risk assessment 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 Diederich, Nora Schütz, Anja Riella, Leonardo V. Massachusetts Institute of Technology. Institute for Medical Engineering & Science Massachusetts Institute of Technology. Department of Biological Engineering 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. 2024-09-17T14:25:24Z 2024-09-17T14:25:24Z 2024-09-13 2024-09-15T03:15:59Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/156882 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. en https://doi.org/10.1038/s44321-024-00126-x EMBO Molecular Medicine Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Nature Publishing Group UK EMBO Press |
| spellingShingle | 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 Diederich, Nora Schütz, Anja Riella, Leonardo V. CRISPR-enabled point-of-care genotyping for APOL1 genetic risk assessment |
| title | CRISPR-enabled point-of-care genotyping for APOL1 genetic risk assessment |
| title_full | CRISPR-enabled point-of-care genotyping for APOL1 genetic risk assessment |
| title_fullStr | CRISPR-enabled point-of-care genotyping for APOL1 genetic risk assessment |
| title_full_unstemmed | CRISPR-enabled point-of-care genotyping for APOL1 genetic risk assessment |
| title_short | CRISPR-enabled point-of-care genotyping for APOL1 genetic risk assessment |
| title_sort | crispr enabled point of care genotyping for apol1 genetic risk assessment |
| url | https://hdl.handle.net/1721.1/156882 |
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