Evidence map›Paper›PMID 34668408›Full record

ArticleAmerican journal of physiology. Lung cellular and molecular physiology2021

Lung proteomic biomarkers associated with chronic obstructive pulmonary disease.

Yu-Hang Zhang, Michael R Hoopmann, Peter J Castaldi, Kirsten A Simonsen, Mukul K Midha, Michael H Cho, Gerard J Criner, Raphael Bueno, Jiangyuan Liu, Robert L Moritz and 1 more

Open access · greenAbstract read
In one paragraph

Article in American journal of physiology. Lung cellular and molecular physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 35 citations in OpenAlex.

  1. Review
  2. Article
  3. Circulating proteomic landscape of lung function.The European respiratory journal · 2026
    Article
  4. Observational
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  6. Review
  7. Lung NR3C1Communications biology · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Blood-based Transcriptomic and Proteomic Biomarkers of Emphysema.American journal of respiratory and critical care medicine · 2024
    Article
  17. Blood Biomarkers of Emphysema: What Can They Really Tell Us?American journal of respiratory and critical care medicine · 2024
    Article
  18. Article
  19. Article
  20. 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

11 authors at 3 institutions in 1 country.

Yu-Hang ZhangChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.ORCID 0000-0003-3825-0796
Michael R HoopmannInstitute for Systems Biology, Seattle, Washington.
Peter J CastaldiChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Kirsten A SimonsenInstitute for Systems Biology, Seattle, Washington.
Mukul K MidhaInstitute for Systems Biology, Seattle, Washington.
Michael H ChoChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Gerard J CrinerTemple University School of Medicine, Philadelphia, Pennsylvania.
Raphael BuenoDivision of Thoracic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Jiangyuan LiuChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Robert L MoritzInstitute for Systems Biology, Seattle, Washington.
Edwin K SilvermanChanning Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Brigham and Women's Hospital · USInstitute for Systems Biology · USTemple University · US

Funding

Respiratory Computational Discovery CoreP01HL114501 · NHLBI · WEILL MEDICAL COLL OF CORNELL UNIV · PI CHOI, MARY E · 2013 to 2025
$24.9M
COPD Susceptibility, Heterogeneity, and Progression: Proteomics and GeneticsR01HL133135 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI MORITZ, ROBERT L, SILVERMAN, EDWIN K · 2017 to 2025
$7.2M
Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTLR01HL124233 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI CASTALDI, PETER · 2014 to 2024
$7.1M
Shortening the development cycle time of Trans Proteomic Pipeline tools with high performance computingR01GM087221 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC, MORITZ, ROBERT L · 2010 to 2021
$6.0M
Genetic and Functional Dissection of a Cluster of COPD GWAS Signals on Chromosome 4qR01HL147148 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI CHO, MICHAEL H., SILVERMAN, EDWIN K · 2019 to 2022
$3.5M
Identifying functional variants in COPD GWAS lociR01HL137927 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI CHO, MICHAEL H., SILVERMAN, EDWIN K · 2017 to 2020
$3.5M
Prospective Health Outcomes and Inflammatory Biomarkers Associated with e-Cigarette UseR01HL147326 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI CASTALDI, PETER · 2019 to 2021
$1.5M
FAIMS-Selected Reaction Monitoring to Quantitative Protein Networks in DiseaseS10RR027584 · NCRR · INSTITUTE FOR SYSTEMS BIOLOGY · PI MORITZ, ROBERT L · 2011 to 2011
$576k
NCRR NIH HHS S10 RR027584NHLBI NIH HHS P01 HL114501NHLBI NIH HHS R01 HL124233NHLBI NIH HHS R01 HL133135NHLBI NIH HHS R01 HL137927NHLBI NIH HHS R01 HL147148NHLBI NIH HHS R01 HL147326NIGMS NIH HHS R01 GM087221
6 · The paper itself

Abstract

Identifying protein biomarkers for chronic obstructive pulmonary disease (COPD) has been challenging. Most previous studies have used individual proteins or preselected protein panels measured in blood samples. Mass spectrometry proteomic studies of lung tissue have been based on small sample sizes. We used mass spectrometry proteomic approaches to discover protein biomarkers from 150 lung tissue samples representing COPD cases and controls. Top COPD-associated proteins were identified based on multiple linear regression analysis with false discovery rate (FDR) < 0.05. Correlations between pairs of COPD-associated proteins were examined. Machine learning models were also evaluated to identify potential combinations of protein biomarkers related to COPD. We identified 4,407 proteins passing quality controls. Twenty-five proteins were significantly associated with COPD at FDR < 0.05, including interleukin 33, ferritin (light chain and heavy chain), and two proteins related to caveolae (CAV1 and CAVIN1). Multiple previously reported plasma protein biomarkers for COPD were not significantly associated with proteomic analysis of COPD in lung tissue, although RAGE was borderline significant. Eleven pairs of top significant proteins were highly correlated (

Indexed as

AgedBiomarkersCase-Control StudiesFemaleHumansLungMaleMass SpectrometryMiddle AgedProteomePulmonary Disease, Chronic ObstructiveBiomarkersProteomebiomarkerschronic obstructive pulmonary diseasemachine learningmass spectrometryproteomics

Identifiers

PMID34668408
PMCPMC8715017
OpenAlexW3206649365

What OpenQuestion holds

Textmetadata
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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.