Evidence map›Paper›PMID 35562381›Full record

ArticleScientific reports2022

Non-volatile organic compounds in exhaled breath particles correspond to active tuberculosis.

Dapeng Chen, Noella A Bryden, Wayne A Bryden, Michael McLoughlin, Dexter Smith, Alese P Devin, Emily R Caton, Caroline R Haddaway, Michele Tameris, Thomas J Scriba and 4 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 29% 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

7 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Review
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

14 authors at 5 institutions in 2 countries.

Dapeng ChenZeteo Tech, Inc., Sykesville, MD, USA. dapeng.chen@zeteotech.com.
Noella A BrydenZeteo Tech, Inc., Sykesville, MD, USA.
Wayne A BrydenZeteo Tech, Inc., Sykesville, MD, USA.
Michael McLoughlinZeteo Tech, Inc., Sykesville, MD, USA.
Dexter SmithZeteo Tech, Inc., Sykesville, MD, USA.
Alese P DevinZeteo Tech, Inc., Sykesville, MD, USA.
Emily R CatonZeteo Tech, Inc., Sykesville, MD, USA.
Caroline R HaddawayZeteo Tech, Inc., Sykesville, MD, USA.
Michele TamerisSouth African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa.
Thomas J ScribaSouth African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa.
Mark HatherillSouth African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa.
Sophia GessnerSAMRC/NHLS/UCT Molecular Mycobacteriology Research Unit, Institute of Infectious Disease and Molecular Medicine and Division of Medical Microbiology, Department of Pathology, University of Cape Town, Cape Town, South Africa.
Digby F WarnerSAMRC/NHLS/UCT Molecular Mycobacteriology Research Unit, Institute of Infectious Disease and Molecular Medicine and Division of Medical Microbiology, Department of Pathology, University of Cape Town, Cape Town, South Africa.
Robin WoodDesmond Tutu HIV Centre, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
Zeteo Tech (United States) · USSouth African Medical Research Council · ZASouth African Tuberculosis Vaccine Initiative · ZADesmond Tutu HIV Foundation · ZAUniversity of Cape Town · ZA

Funding

Identifying TB transmitters in high TB/HIV burdened communitiesR01AI147347 · NIAID · DESMOND TUTU HIV FOUNDATION · PI WOOD, ROBIN · 2019 to 2023
$4.0M
NIAID NIH HHS R01A/147347NIAID NIH HHS R01 AI147347
6 · The paper itself

Abstract

Human breath contains trace amounts of non-volatile organic compounds (NOCs) which might provide non-invasive methods for evaluating individual health. In previous work, we demonstrated that lipids detected in exhaled breath aerosol (EBA) could be used as markers of active tuberculosis (TB). Here, we advanced our analytical platform for characterizing small metabolites and lipids in EBA samples collected from participants enrolled in clinical trials designed to identify molecular signatures of active TB. EBA samples from 26 participants with active TB and 73 healthy participants were processed using a dual-phase extraction method, and metabolites and lipids were identified via mass spectrometry database matching. In total, 13 metabolite and 9 lipid markers were identified with statistically different optimized relative standard deviation values between individuals diagnosed with active TB and the healthy controls. Importantly, EBA lipid profiles can be used to separate the two sample types, indicating the diagnostic potential of the identified molecules. A feature ranking algorithm reduced this number to 10 molecules, with the membrane glycerophospholipid, phosphatidylinositol 24:4, emerging as the top driver of segregation between the two groups. These results support the use of this approach to identify consistent NOC signatures from EBA samples in active TB cases. This suggests the potential to apply this method to other human diseases which alter respiratory NOC release.

Indexed as

Body FluidsTuberculosisVolatile Organic CompoundsAerosolsBiomarkersBreath TestsExhalationHumansLipidsAerosolsBiomarkersLipidsVolatile Organic Compounds

Identifiers

PMID35562381
PMCPMC9106714
OpenAlexW4280560850

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.