Evidence map›Paper›PMID 35048206›Full record

ArticleMolecular biomedicine2022

Autoantibodies against cytoskeletons and lysosomal trafficking discriminate sarcoidosis from healthy controls, tuberculosis and lung cancers.

Samer Najeeb Hanoudi, Harvinder Talwar, Sorin Draghici, Lobelia Samavati

Open access · diamondAbstract read
In one paragraph

Article in Molecular biomedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Discovery of Two Novel Immunoepitopes and Development of a Peptide-based Sarcoidosis Immunoassay.American journal of respiratory and critical care medicine · 2024
    Article
  4. Article
  5. 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

4 authors at 1 institution in 1 country.

Samer Najeeb Hanoudi *Department of Computer Science, Wayne State University, Detroit, MI, 48202, USA.
Harvinder Talwar *Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, Wayne State University School of Medicine, 3990 John R, 3 Hudson, Detroit, MI, 48201, USA.
Sorin DraghiciDepartment of Computer Science, Wayne State University, Detroit, MI, 48202, USA.
Lobelia SamavatiDepartment of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, Wayne State University School of Medicine, 3990 John R, 3 Hudson, Detroit, MI, 48201, USA. lsamavat@med.wayne.edu.ORCID http://orcid.org/0000-0002-3327-2585
Wayne State University · US

Funding

Role and Regulation of MKP-1 in SarcoidosisR01HL113508 · NHLBI · WAYNE STATE UNIVERSITY · PI SAMAVATI, LOBELIA · 2013 to 2017
$1.9M
A novel T7 phage display technology to detect sarcoidosis specific antigensR01HL150474 · NHLBI · WAYNE STATE UNIVERSITY · PI SAMAVATI, LOBELIA · 2020 to 2023
$1.8M
Development &validationof a panel of antibodies for the diagnosis of sarcoidosisR21HL104481 · NHLBI · WAYNE STATE UNIVERSITY · PI SAMAVATI, LOBELIA · 2012 to 2013
$399k
Diagnostic classifiers for sarcoidosis using a novel T7 phage display technologyR21HL148089 · NHLBI · WAYNE STATE UNIVERSITY · PI SAMAVATI, LOBELIA · 2019 to 2020
$231k
NHLBI NIH HHS HL113508NHLBI NIH HHS R01 HL113508NHLBI NIH HHS R01 HL150474NHLBI NIH HHS R21 HL104481NHLBI NIH HHS R21 HL148089
6 · The paper itself

Abstract

Sarcoidosis is a systemic granulomatous disease of unknown etiology. Hypergammaglobulinemia and the presence of autoantibodies in sarcoidosis suggest active humoral immunity to unknown antigen(s). We developed a complex cDNA library derived from tissues of sarcoidosis patients. Using a high throughput method, we constructed a microarray platform from this cDNA library containing large numbers of sarcoidosis clones. After selective biopanning, 1070 sarcoidosis-specifc clones were arrayed and immunoscreend with 152 sera from patients with sarcoidosis and other pulmonary diseases. To identify the sarcoidosis classifiers two statistical approaches were conducted: First, we identified significant biomarkers between sarcoidosis and healthy controls, and second identified markers comparing sarcoidosis to all other groups. At the threshold of an False Discovery Rate (FDR) < 0.01, we identified 14 clones in the first approach and 12 clones in the second approach discriminating sarcoidosis from other groups. We used the classifiers to build a naïve Bayes model on the training-set and validated it on an independent test-set. The first approach yielded an AUC of 0.947 using 14 significant clones with a sensitivity of 0.93 and specificity of 0.88, whereas the AUC of the second option was 0.92 with a sensitivity of 0.96 and specificity of 0.83. These results suggest robust classifier performance. Furthermore, we characterized the informative phage clones by sequencing and homology searches. Large numbers of classifier-clones were peptides involved in cellular trafficking and cytoskeletons. These results show that sarcoidosis is associated with a specific pattern of immunoreactivity that can discriminate it from other diseases.

Indexed as

ImmunoscreeningMicroarraySarcoidosisT7phage libraryTuberculosis

Identifiers

PMID35048206
PMCPMC8770712
OpenAlexW4206773003

What OpenQuestion holds

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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.