Evidence map›Paper›PMID 30205969›Full record

Trial reportTuberculosis (Edinburgh, Scotland)2018

Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis.

Komal Kedia, Jason P Wendler, Erin S Baker, Kristin E Burnum-Johnson, Leah G Jarsberg, Kelly G Stratton, Aaron T Wright, Paul D Piehowski, Marina A Gritsenko, David M Lewinsohn and 5 more

Open access · hybridAbstract readClinical Trial, Phase IIMulticenter Study
In one paragraph

Trial report in Tuberculosis (Edinburgh, Scotland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

14 citing papers in PubMed, 20 citations in OpenAlex.

  1. Trial
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
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

15 authors at 5 institutions in 1 country.

Komal KediaBiological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
Jason P WendlerBiological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
Erin S BakerBiological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
Kristin E Burnum-JohnsonBiological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
Leah G JarsbergDivision of Pulmonary and Critical Care Medicine, University of California San Francisco, San Francisco, CA, USA.
Kelly G StrattonComputational and Statistical Analysis Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Aaron T WrightBiological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
Paul D PiehowskiBiological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
Marina A GritsenkoBiological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
David M LewinsohnPulmonary and Critical Care Medicine, Oregon Health & Science University, Portland, OR, USA.
George B SigalMeso Scale Diagnostics, Rockville, MD, USA.
Marc H WeinerUniversity of Texas Health Science Center at San Antonio and the South Texas VAMC, San Antonio, TX, USA.
Richard D SmithBiological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
Jon M JacobsBiological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA. Electronic address: Jon.Jacobs@pnnl.gov.
Payam NahidDivision of Pulmonary and Critical Care Medicine, University of California San Francisco, San Francisco, CA, USA.
Pacific Northwest National Laboratory · USUniversity of California, San Francisco · USMeso Scale Discovery (United States) · USOregon Health & Science University · USThe University of Texas Health Science Center at San Antonio · US

Funding

Equipment Supplement Request for a Research Resource for Ultra-sensitive High Throughput ProteomicsP41GM103493 · NIGMS · BATTELLE PACIFIC NORTHWEST LABORATORIES · PI SMITH, RICHARD D · 2012 to 2022
$22.6M
TB Surrogate Markers for Assessing Reponse to Treatment (TB SMART Study)R01AI104589 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI NAHID, PAYAM, SIGAL, GEORGE B · 2013 to 2017
$6.2M
NIAID NIH HHS R01 AI104589NIGMS NIH HHS P41 GM103493
6 · The paper itself

Abstract

rationaleThe monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment.

objectiveWe utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy.

methodsSerum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points.

resultsA total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status.

conclusionA comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.

Indexed as

Ion Mobility SpectrometryMass SpectrometryAdolescentAdultAntitubercular AgentsBiomarkersBlood ProteinsChildChild, PreschoolChromatography, LiquidDrug Therapy, CombinationFemaleHigh-Throughput Screening AssaysHost-Pathogen InteractionsHumansInfantAntitubercular AgentsBiomarkersBlood ProteinsAntibiotic treatmentIon mobility spectrometryProteomicsTuberculosis

Identifiers

PMID30205969
PMCPMC6181582
OpenAlexW2883461060

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.