Evidence map›Paper›PMID 33639924›Full record

ArticleMalaria journal2021

Measurement of gene amplifications related to drug resistance in Plasmodium falciparum using droplet digital PCR.

Suttipat Srisutham, Kanokon Suwannasin, Rungniran Sugaram, Arjen M Dondorp, Mallika Imwong

Open access · goldAbstract readComparative Study
In one paragraph

Article in Malaria journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

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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

5 authors at 3 institutions in 2 countries.

Suttipat SrisuthamDepartment of Clinical Microscopy, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, Thailand.
Kanokon SuwannasinMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
Rungniran SugaramDivision of Vector Borne Diseases, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand.
Arjen M DondorpMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
Mallika ImwongMahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand. noi@tropmedres.ac.ORCID http://orcid.org/0000-0003-0857-1855
Mahidol University · THChulalongkorn University · THMinistry of Public Health · TH

Funding

Wellcome Trust
6 · The paper itself

Abstract

backgroundCopy number variations (CNVs) of the Plasmodium falciparum multidrug resistance 1 (pfmdr1), P. falciparum plasmepsin2 (pfplasmepsin2) and P. falciparum GTP cyclohydrolase 1 (pfgch1) genes are associated with anti-malarial drug resistance in P. falciparum malaria. Droplet digital PCR (ddPCR) assays have been developed for accurate assessment of CNVs in several human genes. The aim of the present study was to develop and validate ddPCR assays for detection of the CNVs of P. falciparum genes associated with resistance to anti-malarial drugs.

methodsA multiplex ddPCR assay was developed to detect the CNVs in the pfmdr1 and pfplasmepsin2 genes, while a duplex ddPCR assay was developed to detect CNV in the pfgch1 gene. The gene copy number (GCN) quantification limit, as well as the accuracy and precision of the ddPCR assays were determined and compared to conventional quantitative PCR (qPCR). In order to reduce the cost of testing, a multiplex ddPCR assay of two target genes, pfmdr1 and pfplasmepsin2, was validated. In addition, the CNVs of genes of field samples collected from Thailand from 2015 to 2019 (n = 84) were assessed by ddPCR and results were compared to qPCR as the reference assay.

resultsThere were no significant differences between the GCN results obtained from uniplex and multiplex ddPCR assays for detection of CNVs in the pfmdr1 and pfplasmepsin2 genes (p = 0.363 and 0.330, respectively). Based on the obtained gene copy number quantification limit, the accuracy and percent relative standard deviation (%RSD) value of the multiplex ddPCR assay were 95% and 5%, respectively, for detection of the CNV of the pfmdr1 gene, and 91% and 5% for detection of the CNV of the pfplasmepsin2 gene. There was no significant difference in gene copy numbers assessed by uniplex or duplex ddPCR assays regarding CNV in the pfgch1 gene (p = 0.276). The accuracy and %RSD value of the duplex ddPCR assay were 95% and 4%, respectively, regarding pfgch1 GCN. In the P. falciparum field samples, pfmdr1 and pfplasmepsin2 GCNs were amplified in 15% and 27% of samples from Ubon Ratchathani, Thailand, while pfgch1 GCN was amplified in 50% of samples from Yala, Thailand. There was 100% agreement between the GCN results obtained from the ddPCR and qPCR assays (κ = 1.00). The results suggested that multiplex ddPCR assay is the optional assay for the accurate detection of gene copy number without requiring calibration standards, while the cost and required time are reduced. Based on the results of this study, criteria for GCN detection by ddPCR analysis were generated.

conclusionsThe developed ddPCR assays are simple, accurate, precise and cost-effective tools for detection of the CNVs in the pfmdr1, pfplasmepsin2 and pfgch1 genes of P. falciparum. The ddPCR assay is a useful additional tool for the surveillance of anti-malarial drug resistance.

Indexed as

Gene AmplificationAntimalarialsDrug ResistanceMultiplex Polymerase Chain ReactionPlasmodium falciparumPolymerase Chain ReactionThailandAntimalarialsddPCRpfgch1pfmdr1pfplasmepsin2Plasmodium falciparum

Identifiers

PMID33639924
PMCPMC7916280
OpenAlexW3128388919

What OpenQuestion holds

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LicenceCC BY
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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.