Evidence map›Paper›PMID 39700090›Full record

ArticlePloS one2024

Exploring the mechanism of berberine treatment for atherosclerosis combined with non-alcoholic fatty liver disease based on bioinformatic and experimental study.

Shushu Wang, Kachun Lu, Liwen Lin, Gaijie Li, Yuxin Han, Zhichao Lin, Qingmin Chu, Kunsheng Wu, Peijian Liu, Guiting Zhou and 2 more

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

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, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  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

12 authors.

Shushu WangThe First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
Kachun LuThe First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
Liwen LinThe First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
Gaijie LiThe First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
Yuxin HanThe First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
Zhichao LinThe First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
Qingmin ChuThe First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
Kunsheng WuShunde Hospital of Guangzhou University of Chinese Medicine, Foshan, China.
Peijian LiuShunde Hospital of Guangzhou University of Chinese Medicine, Foshan, China.
Guiting ZhouShunde Hospital of Guangzhou University of Chinese Medicine, Foshan, China.
Rui PengShunde Hospital of Guangzhou University of Chinese Medicine, Foshan, China.
Chuanjin LuoCardiology Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.ORCID 0000-0002-1691-104X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atherosclerosis (AS) and Non-alcoholic fatty liver disease (NAFLD) are chronic metabolic disorders with high prevalence and significant health impacts. Both conditions share common pathophysiological pathways including abnormal lipid metabolism and inflammation. Berberine (BBR), an isoquinoline alkaloid, is known for its beneficial effects on various metabolic and cardiovascular disorders. This study investigates BBR's impact on AS and NAFLD through bioinformatics analysis and experimental models. This study utilized various bioinformatics methods, including transcriptome analysis, weighted gene co-expression network analysis (WGCNA), machine learning, and molecular docking, to identify key genes and pathways involved in AS and NAFLD. Subsequently an animal model of AS combined with NAFLD was established using ApoE-/- mice fed a high-fat diet. The efficacy and mechanism of action of BBR were verified using methods such as hematoxylin and eosin (HE) staining, Oil Red O staining, and real-time quantitative PCR (RTqPCR). Through transcriptome analysis, WGCNA, and machine learning, this study identified 48 key genes involved in both AS and NAFLD. Function analysis revealed that the implicated genes were significantly involved in pathways like cytokine-cytokine receptor interaction, chemokine signaling, and IL-17 signaling pathway, suggesting their role in inflammation and immune responses. Single cell validation identified six key genes: dual specificity phosphatase 6 (DUSP6), chemokine ligand 3 (CCL3), complement component 5a receptor 1 (C5AR1), formyl peptide receptor 1 (FPR1), myeloid nuclear differentiation antigen (MNDA), and proviral integration site of murine 2(PIM2). Finally, molecular docking and animal experiments showed that BBR significantly reduced lipid deposits and inflammatory markers in liver and aortic tissues. In conclusion, BBR can improve AS combined with NAFLD by regulating genes like MNDA, PIM2, DUSP6, CCL3, C5AR1, and FPR1, with the mechanism related to inflammation control. The findings suggest potential clinical benefits of BBR in reducing the progression of both AS and NAFLD, warranting further investigation.

Indexed as

AtherosclerosisBerberineComputational BiologyNon-alcoholic Fatty Liver DiseaseAnimalsDiet, High-FatDisease Models, AnimalGene Expression ProfilingMachine LearningMaleMiceMice, Inbred C57BLMolecular Docking SimulationBerberine

Identifiers

PMID39700090
PMCPMC11658604

What OpenQuestion holds

Textmetadata
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.