Evidence map›Paper›PMID 33733639›Full record

ArticleAllergy, asthma & immunology research2021

Hemopexin: A Novel Anti-inflammatory Marker for Distinguishing COPD From Asthma.

Natasha A Winter, Peter G Gibson, Michael Fricker, Jodie L Simpson, Peter A Wark, Vanessa M McDonald

Open access · diamondAbstract read
In one paragraph

Article in Allergy, asthma & immunology research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

13 citing papers in PubMed, 19 citations in OpenAlex.

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  10. Current Insights on the Impact of Proteomics in Respiratory Allergies.International journal of molecular sciences · 2022
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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

6 authors at 2 institutions in 1 country.

Natasha A WinterNational Health and Medical Research Council Centre for Research Excellence in Severe Asthma and The Priority Research Centre for Health Lungs, The University of Newcastle, Newcastle, NSW, Australia.ORCID https://orcid.org/0000-0001-5797-0073
Peter G GibsonNational Health and Medical Research Council Centre for Research Excellence in Severe Asthma and The Priority Research Centre for Health Lungs, The University of Newcastle, Newcastle, NSW, Australia.ORCID https://orcid.org/0000-0001-5865-489X
Michael FrickerNational Health and Medical Research Council Centre for Research Excellence in Severe Asthma and The Priority Research Centre for Health Lungs, The University of Newcastle, Newcastle, NSW, Australia.ORCID https://orcid.org/0000-0002-8587-1774
Jodie L SimpsonSchool of Medicine and Public Health, The University of Newcastle, Newcastle, NSW, Australia.ORCID https://orcid.org/0000-0002-3626-680X
Peter A WarkNational Health and Medical Research Council Centre for Research Excellence in Severe Asthma and The Priority Research Centre for Health Lungs, The University of Newcastle, Newcastle, NSW, Australia.ORCID https://orcid.org/0000-0001-5676-6126
Vanessa M McDonaldNational Health and Medical Research Council Centre for Research Excellence in Severe Asthma and The Priority Research Centre for Health Lungs, The University of Newcastle, Newcastle, NSW, Australia.ORCID https://orcid.org/0000-0001-9890-3408
John Hunter Hospital · AUNational Health and Medical Research Council · AU

Funding

Hunter Medical Research InstituteJohn Hunter Hospital Charitable TrustLung Foundation of AustraliaNational Health and Medical Research CouncilRamaciotti FoundationsUniversity of Newcastle Australia
6 · The paper itself

Abstract

purposeSystemic inflammatory biomarkers can improve diagnosis and assessment of chronic obstructive pulmonary disease (COPD) and asthma. We aimed to validate an airway disease biomarker panel of 4 systemic inflammatory biomarkers, α2-macroglobulin, ceruloplasmin, haptoglobin and hemopexin, to establish their relationship to airway disease diagnosis and inflammatory phenotypes and to identify an optimized biomarker panel for disease differentiation.

methodsParticipants with COPD or asthma were classified by inflammatory phenotypes. Immunoassay methods were used to measure levels of validation biomarkers in the sera of participants with disease and non-respiratory disease controls. Markers were analyzed individually and in combination for disease differentiation and compared to established biomarkers (C-reactive protein, interleukin-6, and white blood cell/blood eosinophil count).

resultsThe study population comprised of 141 COPD, 127 severe asthma, 54 mild-moderate asthma and 71 control participants. Significant differences in ceruloplasmin, haptoglobin and hemopexin levels between disease groups and between systemic inflammatory phenotypes were observed. However, no differences were found between airway inflammatory phenotypes. Hemopexin was the best performing individual biomarker and could diagnose COPD versus control participants (area under the curve [AUC], 98.3%; 95% confidence interval [CI], 96.7%-99.9%) and differentiate COPD from asthmatic participants (AUC, 97.0%; 95% CI, 95.4%-98.6%), outperforming established biomarkers. A biomarker panel, including hemopexin, haptoglobin and other established biomarkers, could diagnose asthma versus control participants (AUC, 87.5%; 95% CI, 82.8%-92.2%).

conclusionsHemopexin can be a novel biomarker with superior diagnostic ability in differentiating COPD and asthma. We propose an anti-inflammatory axis between the airways and systemic circulation, in which hemopexin is a protective component in airway disease.

Indexed as

airway inflammationanti-inflammationAsthmabiomarkerCOPDdiagnosishaptoglobinhemopexin

Identifiers

PMID33733639
PMCPMC7984952
OpenAlexW3126445329

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.