Evidence mapPaperPMID 39165965Full record

ArticleHeliyon2024

Comprehensive analysis of shared risk genes and immunity-metabolisms between non-alcoholic fatty liver disease and atherosclerosis via bulk and single-cell transcriptome analyses.

Qian Hu, Yunfang Luo, Hao He, Hua Chen, Di Liao

Abstract read
In one paragraph

Article in Heliyon, 2024. 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
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. [Dual role and therapeutic potential of TREM2 in atherosclerosis].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
    Review
  2. Article
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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.

Qian HuCenter for Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China.
Yunfang LuoDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Hao HeXiangya School of Medicine, Central South University, Changsha, Hunan, China.
Hua ChenDepartment of Neurosurgery, the First people's Hospital of Changde City, Changde, Hunan, China.
Di LiaoDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: and design: Considering the clinical link between non-alcoholic fatty liver disease (NAFLD) and atherosclerosis (AS), we performed bioinformatics analysis to uncover their pathogenic interrelationship. Methods and results: Data from the U.S. National Health and Nutritional Examination Survey (NHANES) 1999-2018 were included. Among 4851 participants in NHANES, NAFLD was significantly associated with atherosclerotic cardiovascular disease risk (ASCVD risk) (OR = 2.32, 95%CI: 2.04-2.65, P < 0.0001). We conducted WGCNA analysis for NAFLD (GSE130970) and AS (GSE28829) and identified three modules positively related to NAFLD severity and two modules accelerating atherosclerosis plaque progression. 198 key-modules genes were obtained via overlapping these modules. Next, we mined the disease-controlled differentially expressed genes (DEGs) from NAFLD (GSE89632) and AS (GSE100927), respectively. The final common risk genes ( Conclusion: We found 7 shared hub genes with good diagnostic ability and depicted the landscapes of immune and metabolism involved in NAFLD and AS. Our results provided a comprehensive association between them and may contribute to developing potential intervention strategies for targeting both disorders based on these risk factors.

Indexed as

AtherosclerosisBioinformaticsImmune and metabolism dysregulationLandscapeNon-alcoholic fatty liver diseaseShared risk genes

Identifiers

PMID39165965
PMCPMC11334902

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.