Evidence map›Paper›PMID 29977241›Full record

ArticleFrontiers in immunology2018

Nonallergic Asthma and Its Severity: Biomarkers for Its Discrimination in Peripheral Samples.

Selene Baos, David Calzada, Lucía Cremades-Jimeno, Joaquín Sastre, César Picado, Joaquín Quiralte, Fernando Florido, Carlos Lahoz, Blanca Cárdaba

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.

  1. Pooled it
  2. Review
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  15. Relationship between CCR5Postepy dermatologii i alergologii · 2021
    Article
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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

9 authors at 6 institutions in 1 country.

Selene BaosImmunology Department, Instituto de Investigación Sanitaria Fundación Jiménez Díaz, Universidad Autónoma de Madrid, Madrid, Spain.
David CalzadaImmunology Department, Instituto de Investigación Sanitaria Fundación Jiménez Díaz, Universidad Autónoma de Madrid, Madrid, Spain.
Lucía Cremades-JimenoImmunology Department, Instituto de Investigación Sanitaria Fundación Jiménez Díaz, Universidad Autónoma de Madrid, Madrid, Spain.
Joaquín SastreCentro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain.
César PicadoCentro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain.
Joaquín QuiralteAllergy Department, Hospital Universitario Virgen del Rocío, Seville, Spain.
Fernando FloridoAllergy Department, Hospital Universitario San Cecilio, Granada, Spain.
Carlos LahozImmunology Department, Instituto de Investigación Sanitaria Fundación Jiménez Díaz, Universidad Autónoma de Madrid, Madrid, Spain.
Blanca CárdabaImmunology Department, Instituto de Investigación Sanitaria Fundación Jiménez Díaz, Universidad Autónoma de Madrid, Madrid, Spain.
Hospital Universitario Fundación Jiménez Díaz · ESCentro de Investigación Biomédica en Red de Enfermedades Respiratorias · ESHospital Universitario Virgen del Rocío · ESInstituto de Investigación Biosanitaria de Granada · ESUniversidad Autónoma de Madrid · ESUniversitat de Barcelona · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Asthma is a complex and heterogeneous respiratory disorder characterized by chronic airway inflammation. It has generally been associated with allergic mechanisms related to type 2 airway inflammation. Nevertheless, between 10 and 33% of asthmatic individuals have nonallergic asthma (NA). Several targeted treatments are in clinical development for patients with Th2 immune response, but few biomarkers are been defined for low or non-Th2-mediated inflammation asthma. We have recently defined by gene expression a set of genes as potential biomarkers of NA, mainly associated with disease severity: IL10, MSR1, PHLDA1, SERPINB2, CHI3L1, IL8, and PI3. Here, we analyzed their protein expression and specificity using sera and isolated peripheral blood mononuclear cells (PBMCs). First, protein quantification was carried out using ELISA (in sera) or Western blot (proteins extracted from PBMCs by Trizol procedure), depending on the biomarker in 30 healthy controls (C) subjects and 30 NA patients. A receiver operating characteristic curve analysis was performed by using the R program to study the specificity and sensitivity of the candidate biomarkers at a gene- and protein expression level. Four kinds of comparisons were performed: total NA group vs C group, severe NA patients vs C, moderate-mild NA patients vs C, and severe NA patients vs moderate-mild NA patients. We found that all the single genes showed good sensitivity vs specificity for some phenotypic discrimination, with CHI3L1 and PI3 exhibiting the best results for C vs NA: CHI3L1 area under the curve (AUC) (CI 95%): 0.95 (0.84-1.00) and PI3 AUC: 0.99 (0.98-1.00); C vs severe NA: PI3 AUC: 1 (0.99-1.00); and C vs moderate-mild NA: CHI3L1 AUC: 1 (0.99-1.00) and PI3 AUC: 0.99 (0.96-1.00). However, the results for discriminating asthma disease and severity with protein expression were better when two or three biomarkers were combined. In conclusion, individual genes and combinations of proteins have been evaluated as reliable biomarkers for classifying NA subjects and their severity. These new panels could be good diagnostic tests.

Indexed as

biomarkersgene expressionnonallergic asthmaprotein expressionreceiver operating characteristicseverity

Identifiers

PMID29977241
PMCPMC6021512
OpenAlexW2808823161

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.