Evidence map›Paper›PMID 35317263›Full record

ArticleGene reports2022

Using bioinformatics and systems biology to discover common pathogenetic processes between sarcoidosis and COVID-19.

Lanyi Fu, Maolin Yao, Xuedong Liu, Dong Zheng

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Gene reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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.

Lanyi FuLaboratory of Genetics and Molecular Biology, College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China.
Maolin YaoLaboratory of Genetics and Molecular Biology, College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China.
Xuedong LiuLaboratory of Genetics and Molecular Biology, College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China.
Dong ZhengLaboratory of Genetics and Molecular Biology, College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China.
Northeast Forestry University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease (COVID-19) pandemic caused by SARS-CoV-2 is ongoing. Individuals with sarcoidosis tend to develop severe COVID-19; however, the underlying pathological mechanisms remain elusive. To determine common transcriptional signatures and pathways between sarcoidosis and COVID-19, we investigated the whole-genome transcriptome of peripheral blood mononuclear cells (PBMCs) from patients with COVID-19 and sarcoidosis and conducted bioinformatic analysis, including gene ontology and pathway enrichment, protein-protein interaction (PPI) network, and gene regulatory network (GRN) construction. We identified 33 abnormally expressed genes that were common between COVID-19 and sarcoidosis. Functional enrichment analysis showed that these differentially expressed genes were associated with cytokine production involved in the immune response and T cell cytokine production. We identified several hub genes from the PPI network encoded by the common genes. These hub genes have high diagnostic potential for COVID-19 and sarcoidosis and can be potential biomarkers. Moreover, GRN analysis identified important microRNAs and transcription factors that regulate the common genes. This study provides a novel characterization of the transcriptional signatures and biological processes commonly dysregulated in sarcoidosis and COVID-19 and identified several critical regulators and biomarkers. This study highlights a potential pathological association between COVID-19 and sarcoidosis, establishing a theoretical basis for future clinical trials.

Indexed as

AUC, area under the ROC curveCC, cellular componentCOVID-19DEG, differentially expressed geneGO, Gene OntologyGRN, gene regulatory networkKEGG, Kyoto Encyclopedia of Genes and GenomesMCC, maximal clique centralityMF, molecular functionMolecular pathwayPBMC, peripheral blood mononuclear cellROC, receiver operating characteristicSarcoidosisSARS-CoV-2TF, transcription factorTranscriptional signature

Identifiers

PMID35317263
PMCPMC8931993
OpenAlexW4220859317

What OpenQuestion holds

Textmetadata
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.