Evidence map›Paper›PMID 31026601›Full record

ArticleThe Journal of molecular diagnostics : JMD2019

Multiplex Solid-Phase Melt Curve Analysis for the Point-of-Care Detection of HIV-1 Drug Resistance.

Dana S Clutter, Gelareh Mazarei, Ruma Sinha, Justen Manasa, Janin Nouhin, Ellen LaPrade, Sara Bolouki, Philip L Tzou, Jessica Hannita-Hui, Malaya K Sahoo and 6 more

Open access · greenAbstract read
In one paragraph

Article in The Journal of molecular diagnostics : JMD, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

6 citing papers in PubMed, 10 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

16 authors at 4 institutions in 2 countries.

Dana S ClutterDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California.
Gelareh MazareiInSilixa Inc., Sunnyvale, California.
Ruma SinhaInSilixa Inc., Sunnyvale, California.
Justen ManasaAfrican Institute of Biomedical Science and Technology, Harare, Zimbabwe.
Janin NouhinDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California.
Ellen LaPradeDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California.
Sara BoloukiInSilixa Inc., Sunnyvale, California.
Philip L TzouDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California.
Jessica Hannita-HuiDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California.
Malaya K SahooDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California.
Peter KuimelisInSilixa Inc., Sunnyvale, California.
Robert G KuimelisInSilixa Inc., Sunnyvale, California.
Benjamin A PinskyDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California; Department of Pathology, Stanford University School of Medicine, Stanford, California.
Gary K SchoolnikInSilixa Inc., Sunnyvale, California.
Arjang HassibiInSilixa Inc., Sunnyvale, California.
Robert W ShaferDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California. Electronic address: rshafer@stanford.edu.
Insilixa (United States) · USStanford University · USStanford Medicine · USAfrican Institute of Biomedical Science and Technology · ZW

Funding

Research Mentoring and Building Capacity of underrepresented Minority Research Scientists in India.D43TW010540 · FIC · YALE UNIVERSITY · PI MICHELE BARRY, Eva Harris · 2017 to 2026
$15.5M
HIV Resistance Testing Using Point-of-Care Dynamic Solid-Phase Melt AnalysisR21AI131918 · NIAID · STANFORD UNIVERSITY · PI SHAFER, ROBERT WILLIAM · 2018 to 2019
$432k
FIC NIH HHS D43 TW010540NIAID NIH HHS R21 AI131918
6 · The paper itself

Abstract

A point-of-care HIV-1 genotypic resistance assay that could be performed during a clinic visit would enable care providers to make informed treatment decisions for patients starting therapy or experiencing virologic failure on therapy. The main challenge for such an assay is the genetic variability at and surrounding each drug-resistance mutation (DRM). We analyzed a database of diverse global HIV sequences and used thermodynamic simulations to design an array of surface-bound oligonucleotide probe sets with each set sharing distinct 5' and 3' flanking sequences but having different centrally located nucleotides complementary to six codons at HIV-1 DRM reverse transcriptase position 103: AAA, AAC, AAG, AAT, AGA, and AGC. We then performed in vitro experiments using 80-mer oligonucleotides and PCR-amplified DNA from clinical plasma HIV-1 samples and culture supernatants that contained subtype A, B, C, D, CRF01_AE, and CRF02_AG viruses. Multiplexed solid-phase melt curve analysis discriminated perfectly among each of the six reported reverse transcriptase position 103 codons in both 80-mers and clinical samples. The sensitivity and specificity for detecting targets that contained AAC mixed with targets that contained AAA were >98% when AAC was present at a proportion of ≥10%. Multiplexed solid-phase melt curve analysis is a promising approach for developing point-of-care assays to distinguish between different codons in genetically variable regions such as those surrounding HIV-1 DRMs.

Indexed as

Drug Resistance, ViralPoint-of-Care TestingDatabases, GeneticGenotypeHIV-1HIV InfectionsHumansMutationRNA, ViralRNA, Viral

Identifiers

PMID31026601
PMCPMC6643098
OpenAlexW2940669280

What OpenQuestion holds

Textmetadata
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.