CRISPR-Based Assay for Point-of-Care Pharmacogenetic CYP2C19 Genotyping

Pharmacogenetic testing enables personalized drug dosing by accounting for genetic variation in drug metabolism. Although there is increasing evidence that genetically guided dosing improves therapeutic efficacy and reduces adverse effects, clinical implementation remains limited as genotyping methods suffer from slow turnaround times and are not optimized for point-of-care use. Here, we present a rapid, multiplexed CRISPR-based assay for genotyping the key CYP2C19 polymorphisms *2, *3, and *17. These variants can alter enzyme activity, impacting the metabolism of drugs such as clopidogrel and mavacamten. Our assay combines isothermal amplification with a dual guide RNA detection strategy, where LwaCas13a selectively detects mutant alleles and LbaCas12a identifies wild-type alleles. In a validation study of 110 participants, the assay showed high concordance with Sanger sequencing, the current gold standard, with variant-specific accuracies of 97.3% (*2), 100% (*3), and 99.1% (*17), demonstrating robust performance across a diverse clinical cohort. The workflow supports both column-based DNA extraction and a simplified, crude extraction protocol. Genotyping results are obtained through either fluorescence detection or multi-analyte lateral-flow readouts, allowing visual interpretation of genotypes with minimal equipment. In conclusion, our findings show that CRISPR-based genotyping can deliver accurate CYP2C19 pharmacogenetic testing, facilitating broader adoption of genotype-guided drug dosing. Furthermore, the programmability of CRISPR-Cas systems enables adaptation to other pharmacogenetic targets relevant to drug metabolism.

Authors

Institutions

Publication Details

Journal
ACS Sensors
Published
2026-06-25
DOI
https://doi.org/10.1021/acssensors.6c00841
Primary Topic
Pharmacogenetics and Drug Metabolism
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CRISPR-Based Assay for Point-of-Care Pharmacogenetic CYP2C19 Genotyping

Tobias Petzold, Robert Greensmith, Anand S. Dighe, Antonia Ibel et al.
ACS Sensors
Pharmacogenetics and Drug Metabolism
article

CRISPR-Based Assay for Point-of-Care Pharmacogenetic CYP2C19 Genotyping

Tobias Petzold, Robert Greensmith, Anand S. Dighe, Antonia Ibel, Qiao Meng, Alexander J. Schubert, Michael M. Kaminski, Daw‐Yang Hwang, Jan Halbritter, Josefine Rau, JC Hoffmann, Julia M. Mandler, Fabian Abele, Xiao Tan, Philipp Enghard, Carlos Cordero, Kai-Uwe Eckardt
article en

Abstract

Pharmacogenetic testing enables personalized drug dosing by accounting for genetic variation in drug metabolism. Although there is increasing evidence that genetically guided dosing improves therapeutic efficacy and reduces adverse effects, clinical implementation remains limited as genotyping methods suffer from slow turnaround times and are not optimized for point-of-care use. Here, we present a rapid, multiplexed CRISPR-based assay for genotyping the key CYP2C19 polymorphisms *2, *3, and *17. These variants can alter enzyme activity, impacting the metabolism of drugs such as clopidogrel and mavacamten. Our assay combines isothermal amplification with a dual guide RNA detection strategy, where LwaCas13a selectively detects mutant alleles and LbaCas12a identifies wild-type alleles. In a validation study of 110 participants, the assay showed high concordance with Sanger sequencing, the current gold standard, with variant-specific accuracies of 97.3% (*2), 100% (*3), and 99.1% (*17), demonstrating robust performance across a diverse clinical cohort. The workflow supports both column-based DNA extraction and a simplified, crude extraction protocol. Genotyping results are obtained through either fluorescence detection or multi-analyte lateral-flow readouts, allowing visual interpretation of genotypes with minimal equipment. In conclusion, our findings show that CRISPR-based genotyping can deliver accurate CYP2C19 pharmacogenetic testing, facilitating broader adoption of genotype-guided drug dosing. Furthermore, the programmability of CRISPR-Cas systems enables adaptation to other pharmacogenetic targets relevant to drug metabolism.

ACS Sensors
Harvard University (US), Kaohsiung Medical University (TW), University of Freiburg (DE), National Health Research Institutes (TW), Max Delbrück Center (DE), University Medical Center Freiburg (DE), Kaohsiung Medical University Chung-Ho Memorial Hospital (TW), TUM Klinikum (DE), Massachusetts General Hospital (US), Institute of Cancer Research (CA), German Rheumatism Research Centre (DE), Friede Springer Stiftung (DE), InSysBio (Russia) (RU), Deutsches Herzzentrum der Charité (DE), Inspire (CH), German Centre for Cardiovascular Research (DE), Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE), Institute for Medical Research (US), Franklin University (US), Technical University of Munich (DE), Massachusetts Institute of Technology (US), Charité - Universitätsmedizin Berlin (DE)
Massachusetts General Hospital, Massachusetts Institute of Technology, Harvard University, Deutsches Zentrum für Herz-Kreislaufforschung, Deutsche Forschungsgemeinschaft, Albert-Ludwigs-Universität Freiburg, Charité – Universitätsmedizin Berlin, Kaohsiung Medical University, National Health Research Institutes, Technische Universität München, Kaohsiung Medical University Chung-Ho Memorial Hospital, Berlin Institute of Health, Hansjörg Wyss Institute for Biologically Inspired Engineering, Harvard University, Leibniz-Gemeinschaft, National Institute of Diabetes and Digestive and Kidney Diseases
Openalex Percentile: Top 7%
Pharmacogenetics and Drug Metabolism
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.