ArticlePloS one2026
Pharmacogenomic landscape in Thailand: Array-based profiling and EMR-linked medication exposure.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Pharmacogenomic (PGx) data in Thailand remain limited, and genetics-only surveys rarely quantify "realized actionability"-the overlap between actionable PGx phenotypes and real-world medication exposure. We profiled 4,662 Thai adults using SNP-array data and a pre-specified PGx panel (11 genes; 26 markers) with a hybrid required/optional calling policy for diplotype/phenotype assignment. CPIC level A/B gene-drug relationships were linked to hospital electronic medical record (EMR) prescription/dispensation data to quantify drug-specific realized actionability. Overall callability across gene-results was 98.62%, exceeding 99% for most genes and lower for CYP2C19 (95.99%) and NUDT15 (90.28%). Across nine phenotype-coded genes, 95.99% carried ≥1 CPIC-actionable result (median 2; IQR 2-3). Actionable prevalence among callable individuals was highest for CYP3A5 (58.54%) and CYP2C19 (56.67%), followed by ABCG2 (45.10%) and UGT1A1 (27.37%). EMR linkage identified 1,529 (32.58%) participants exposed to ≥1 study medication; omeprazole (n = 658) and statins were most common (atorvastatin n = 606; simvastatin n = 603). Among users, actionable phenotypes were frequent for CYP2C19-omeprazole (55.02%) and SLCO1B1-statins (21.95-23.05%). In conclusion, an Asian-optimized SNP array supports scalable PGx phenotyping in Thai adults. EMR linkage quantifies realized actionability and highlights high-yield targets (CYP2C19-proton pump inhibitors; SLCO1B1-statins) for pre-emptive implementation.
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