Evidence map›Paper›PMID 39164226›Full record

ArticleNature communications2024

Rapid single-tier serodiagnosis of Lyme disease.

Rajesh Ghosh, Hyou-Arm Joung, Artem Goncharov, Barath Palanisamy, Kevin Ngo, Katarina Pejcinovic, Nicole Krockenberger, Elizabeth J Horn, Omai B Garner, Ezdehar Ghazal and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
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

16 citing papers in PubMed.

  1. Article
  2. Protective efficacy of mutant strains ofInfection and immunity · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Rajesh Ghosh *Bioengineering Department, University of California, Los Angeles, CA, 90095, USA.ORCID 0000-0002-7408-8944
Hyou-Arm Joung *Electrical & Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.ORCID 0000-0001-5106-4459
Artem GoncharovElectrical & Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.
Barath PalanisamyBioengineering Department, University of California, Los Angeles, CA, 90095, USA.
Kevin NgoBioengineering Department, University of California, Los Angeles, CA, 90095, USA.
Katarina PejcinovicBioengineering Department, University of California, Los Angeles, CA, 90095, USA.ORCID 0009-0002-7802-3993
Nicole KrockenbergerBioengineering Department, University of California, Los Angeles, CA, 90095, USA.ORCID 0009-0001-1693-1120
Elizabeth J HornLyme Disease Biobank, Portland, Oregon, OR, 97221, USA.
Omai B GarnerDepartment of Pathology and Laboratory Medicine, University of California, Los Angeles, CA, 90095, USA.
Ezdehar GhazalDepartment of Pathology, Microbiology, and Immunology, New York Medical College, Valhalla, NY, 10595, USA.
Andrew O'KulaDepartment of Pathology, Microbiology, and Immunology, New York Medical College, Valhalla, NY, 10595, USA.
Paul M ArnaboldiDepartment of Pathology, Microbiology, and Immunology, New York Medical College, Valhalla, NY, 10595, USA.
Raymond J DattwylerDepartment of Pathology, Microbiology, and Immunology, New York Medical College, Valhalla, NY, 10595, USA.ORCID 0000-0002-1983-1301
Aydogan OzcanBioengineering Department, University of California, Los Angeles, CA, 90095, USA. ozcan@ucla.edu.ORCID 0000-0002-0717-683X
Dino Di CarloBioengineering Department, University of California, Los Angeles, CA, 90095, USA. dicarlo@ucla.edu.ORCID 0000-0003-3942-4284

Funding

A peptide-based point-of-care vertical flow assay for the rapid diagnosis of Lyme diseaseR44AI150060 · NIAID · BIOPEPTIDES, INC. · PI ARNABOLDI, PAUL MICHAEL, DI CARLO, DINO · 2020 to 2023
$3.3M
National Science Foundation (NSF) 1648451NIAID NIH HHS R44 AI150060U.S. Department of Health & Human Services | National Institutes of Health (NIH) R44AI150060
6 · The paper itself

Abstract

Point-of-care serological and direct antigen testing offers actionable insights for diagnosing challenging illnesses, empowering distributed health systems. Here, we report a POC-compatible serologic test for Lyme disease (LD), leveraging synthetic peptides specific to LD antibodies and a paper-based platform for rapid, and cost-effective diagnosis. Antigenic epitopes conserved across Borrelia burgdorferi genospecies, targeted by IgG and IgM antibodies, are selected to develop a multiplexed panel for detection of LD antibodies from patient sera. Multiple peptide epitopes, when combined synergistically with a machine learning-based diagnostic model achieve high sensitivity without sacrificing specificity. Blinded validation with 15 LD-positive and 15 negative samples shows 95.5% sensitivity and 100% specificity. Blind testing with the CDC's LD repository samples confirms the test accuracy, matching lab-based two-tier results, correctly differentiating between LD and look-alike diseases. This LD diagnostic test could potentially replace the cumbersome two-tier testing, improving diagnosis and enabling earlier treatment while facilitating immune monitoring and surveillance.

Indexed as

Antibodies, BacterialBorrelia burgdorferiImmunoglobulin GImmunoglobulin MLyme DiseaseSensitivity and SpecificitySerologic TestsAntigens, BacterialEpitopesHumansMachine LearningPoint-of-Care SystemsPoint-of-Care TestingAntibodies, BacterialAntigens, BacterialEpitopesImmunoglobulin GImmunoglobulin M

Identifiers

PMID39164226
PMCPMC11336255

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.