Evidence map›Paper›PMID 37047411›Full record

ArticleInternational journal of molecular sciences2023

Transcriptome Sequencing Reveals Autophagy Networks in Rat Livers during the Development of NAFLD and Identifies Autophagy Hub Genes.

Jian Xie, Qiuyi Chen, Yongxia Zhao, Mingxia Luo, Xin Zeng, Lin Qin, Daopeng Tan, Yuqi He

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

8 authors at 1 institution in 1 country.

Jian XieGuizhou Engineering Research Center of Industrial Key-Technology for Dendrobium Nobile, Zunyi Medical University, Zunyi 563000, China.ORCID 0000-0001-8118-059X
Qiuyi ChenGuizhou Engineering Research Center of Industrial Key-Technology for Dendrobium Nobile, Zunyi Medical University, Zunyi 563000, China.
Yongxia ZhaoGuizhou Engineering Research Center of Industrial Key-Technology for Dendrobium Nobile, Zunyi Medical University, Zunyi 563000, China.
Mingxia LuoGuizhou Engineering Research Center of Industrial Key-Technology for Dendrobium Nobile, Zunyi Medical University, Zunyi 563000, China.
Xin ZengDepartment of Medical Genetics, Zunyi Medical University, Zunyi 563000, China.
Lin QinGuizhou Engineering Research Center of Industrial Key-Technology for Dendrobium Nobile, Zunyi Medical University, Zunyi 563000, China.
Daopeng TanGuizhou Engineering Research Center of Industrial Key-Technology for Dendrobium Nobile, Zunyi Medical University, Zunyi 563000, China.ORCID 0000-0003-4385-2759
Yuqi HeGuizhou Engineering Research Center of Industrial Key-Technology for Dendrobium Nobile, Zunyi Medical University, Zunyi 563000, China.
Zunyi Medical University · CN

Funding

Doctor science foundation of Zunyi Medical University F-941Guizhou Engineering Research Center of Industrial Key-technology for Dendrobium Nobile QJJ[2022]048Guizhou Province Science and Technology Support Program QKHZC[2019]2953Innovative projects of college students in Guizhou Province ZYDC2020022National Natural Science Foundation of China 82260843, 82060649Science and Technology Fund of Guizhou Provincial Health Commission gzwkj2021-539Science and Technology Program of Guizhou Province QKHRCPT[2019]1332Science and Technology Program of Zunyi ZSKHHZ[2022]380
6 · The paper itself

Abstract

(1) Autophagy is an important biological process in cells and is closely associated with the development and progression of non-alcoholic fatty liver disease (NAFLD). Therefore, this study aims to investigate the biological function of the autophagy hub genes, which could be used as a potential therapeutic target and diagnostic markers for NAFLD. (2) Male C57BL/6J mice were sacrificed after 16 and 38 weeks of a high-fat diet, serum biochemical indexes were detected, and liver lobules were collected for pathological observation and transcriptome sequencing. The R software was used to identify differentially expressed autophagy genes (DEGs) from the transcriptome sequencing data of mice fed with a normal diet for 38 weeks (ND38) and a high-fat diet for 38 weeks (HFD38). Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed on the DEGs, a protein-protein interaction (PPI) network of the DEGs was established using the STRING data website, and the results were visualized through Cytoscape. (3) After 16 weeks and 38 weeks of a high-fat diet, there was a significant increase in body weight, serum total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-C) and triglycerides (TG) in mice, along with lipid accumulation in the liver, which was more severe at 38 weeks than at 16 weeks. The transcriptome data showed significant changes in the expression profile of autophagy genes in the livers of NAFLD mice following a long-term high-fat diet. Among the 31 differentially expressed autophagy-related genes, 13 were upregulated and 18 were downregulated. GO and KEGG pathway analysis revealed that these DEGs were primarily involved in autophagy, cholesterol transport, triglyceride metabolism, apoptosis, the FoxO signaling pathway, the p53 signaling pathway and the IL-17 signaling pathway. Four hub genes were identified by the PPI network analysis, of which

Indexed as

Non-alcoholic Fatty Liver DiseaseAnimalsAutophagyCholesterolGene Expression ProfilingMaleMiceMice, Inbred C57BLRatsTranscriptomeCholesterolautophagybiomarkershigh-fat dietNAFLDtranscriptome

Identifiers

PMID37047411
PMCPMC10094595
OpenAlexW4361275776

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.