Evidence map›Paper›PMID 33144648›Full record

ArticleScientific reports2020

Phenotype prediction and characterization of 25 pharmacogenes in Thais from whole genome sequencing for clinical implementation.

John Mauleekoonphairoj, Monpat Chamnanphon, Apichai Khongphatthanayothin, Boosamas Sutjaporn, Pharawee Wandee, Yong Poovorawan, Koonlawee Nademanee, Monnat Pongpanich, Pajaree Chariyavilaskul

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Frontiers in pharmacology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

John MauleekoonphairojDepartment of Medicine, Faculty of Medicine, Center of Excellence in Arrhythmia Research Chulalongkorn University, Chulalongkorn University, Bangkok, Thailand.
Monpat ChamnanphonClinical Pharmacokinetics and Pharmacogenomics Research Unit, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Apichai KhongphatthanayothinDepartment of Medicine, Faculty of Medicine, Center of Excellence in Arrhythmia Research Chulalongkorn University, Chulalongkorn University, Bangkok, Thailand.
Boosamas SutjapornDepartment of Medicine, Faculty of Medicine, Center of Excellence in Arrhythmia Research Chulalongkorn University, Chulalongkorn University, Bangkok, Thailand.
Pharawee WandeeDepartment of Medicine, Faculty of Medicine, Center of Excellence in Arrhythmia Research Chulalongkorn University, Chulalongkorn University, Bangkok, Thailand.
Yong PoovorawanDepartment of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Koonlawee NademaneeDepartment of Medicine, Faculty of Medicine, Center of Excellence in Arrhythmia Research Chulalongkorn University, Chulalongkorn University, Bangkok, Thailand.
Monnat PongpanichDepartment of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok, Thailand.
Pajaree ChariyavilaskulClinical Pharmacokinetics and Pharmacogenomics Research Unit, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. pajaree.l@chula.ac.th.
Chulalongkorn University · THBangkok Hospital · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Publicly available pharmacogenomics (PGx) databases enable translation of genotype data into clinically actionable information. As variation within pharmacogenes is population-specific, this study investigated the spectrum of 25 clinically relevant pharmacogenes in the Thai population (n = 291) from whole genome sequencing. The bioinformatics tool Stargazer was used for phenotype prediction, through assignment of alleles and detection of structural variation. Known and unreported potentially deleterious PGx variants were identified. Over 25% of Thais carried a high-risk diplotype in CYP3A5, CYP2C19, CYP2D6, NAT2, SLCO1B1, and UGT1A1. CYP2D6 structural variants accounted for 83.8% of all high-risk diplotypes. Of 39 known PGx variants identified, six variants associated with adverse drug reactions were common. Allele frequencies of CYP3A5*3 (rs776746), CYP2B6*6 (rs2279343), and NAT2 (rs1041983) were significantly higher in Thais than East-Asian and global populations. 121 unreported variants had potential to exert clinical impact, majority were rare and population-specific, with 60.3% of variants absent from gnomAD database. This study demonstrates the population-specific variation in clinically relevant pharmacogenes, the importance of CYP2D6 structural variation detection in the Thai population, and potential of unreported variants in explaining drug response. These findings are essential in development of dosing guidelines, PGx testing, clinical trials, and drugs.

Indexed as

AllelesArylamine N-AcetyltransferaseComputational BiologyCytochrome P-450 CYP2C19Cytochrome P-450 CYP2D6Cytochrome P-450 CYP3AGenomicsGenotypeGlucuronosyltransferaseHaplotypesHumansLiver-Specific Organic Anion Transporter 1MutationPhenotypeThailandUGT1A1 EnzymeArylamine N-AcetyltransferaseCytochrome P-450 CYP2C19Cytochrome P-450 CYP2D6Cytochrome P-450 CYP3AGlucuronosyltransferaseLiver-Specific Organic Anion Transporter 1NAT2 protein, humanSLCO1B1 protein, humanUGT1A1 Enzyme

Identifiers

PMID33144648
PMCPMC7641128
OpenAlexW3094911871

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.