Evidence map›Paper›PMID 38932215›Full record

ArticleViruses2024

Identification and Analysis of Biomarkers Associated with Lipophagy and Therapeutic Agents for COVID-19.

Yujia Wu, Zhenlin Wu, Qiying Jin, Jinyuan Liu, Peiping Xu

Abstract read
In one paragraph

Article in Viruses, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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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

2 citing papers in PubMed.

  1. Trial
  2. 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

5 authors.

Yujia WuInstitute of Tropical Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.ORCID 0009-0007-7722-9793
Zhenlin WuInstitute of Tropical Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
Qiying JinInstitute of Tropical Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
Jinyuan LiuBasic Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
Peiping XuInstitute of Tropical Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.

Funding

National Natural Science Foundation of China 82141208
6 · The paper itself

Abstract

backgroundLipids, as a fundamental cell component, play an regulating role in controlling the different cellular biological processes involved in viral infections. A notable feature of coronavirus disease 2019 (COVID-19) is impaired lipid metabolism. The function of lipophagy-related genes in COVID-19 is unknown. The present study aimed to investigate biomarkers and drug targets associated with lipophagy and lipophagy-based therapeutic agents for COVID-19 through bioinformatics analysis.

methodsLipophagy-related biomarkers for COVID-19 were identified using machine learning algorithms such as random forest, Support Vector Machine-Recursive Feature Elimination, Generalized Linear Model, and Extreme Gradient Boosting in three COVID-19-associated GEO datasets: scRNA-seq (GSE145926) and bulk RNA-seq (GSE183533 and GSE190496). The cMAP database was searched for potential COVID-19 medications.

resultsThe lipophagy pathway was downregulated, and the lipid droplet formation pathway was upregulated, resulting in impaired lipid metabolism. Seven lipophagy-related genes, including

conclusionsThe lipophagy-related genes

Indexed as

Antiviral AgentsBiomarkersCOVID-19COVID-19 Drug TreatmentLipid MetabolismSARS-CoV-2BenzoquinonesComputational BiologyHumansHydroxamic AcidsLactams, MacrocyclicMachine LearningAntiviral AgentsBenzoquinonesBiomarkersgeldanamycinHydroxamic AcidsLactams, Macrocyclictrichostatin AbioinformaticsCOVID-19lipid metabolismlipophagy-related genestherapeutic agents

Identifiers

PMID38932215
PMCPMC11209609

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