Evidence map›Paper›PMID 33381146›Full record

ArticleFrontiers in genetics2020

Aberrantly Methylated-Differentially Expressed Genes Identify Novel Atherosclerosis Risk Subtypes.

Yuzhou Xue, Yongzheng Guo, Suxin Luo, Wei Zhou, Jing Xiang, Yuansong Zhu, Zhenxian Xiang, Jian Shen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.6field-weighted citation impact, top 40% 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

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
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  5. Article
  6. Review
  7. Making sense of the ageing methylome.Nature reviews. Genetics · 2022
    Review
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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

8 authors at 2 institutions in 1 country.

Yuzhou XueDepartment of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yongzheng GuoDepartment of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Suxin LuoDepartment of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Wei ZhouDepartment of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Jing XiangDepartment of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yuansong ZhuDepartment of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Zhenxian XiangDepartment of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Jian ShenDepartment of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Chongqing Medical University · CNFirst Affiliated Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing evidence has indicated that modulation of epigenetic mechanisms, especially methylation and long-non-coding RNA (lncRNA) regulation, plays a pivotal role in the process of atherosclerosis; however, few studies focused on revealing the epigenetic-related subgroups during atherosclerotic progression using unsupervised clustering analysis. Hence, we aimed to identify the epigenetics-related differentially expressed genes associated with atherosclerosis subtypes and characterize their clinical utility in atherosclerosis. Eighty samples with expression data (GSE40231) and 49 samples with methylation data (GSE46394) from a large artery plaque were downloaded from the GEO database, and aberrantly methylated-differentially expressed (AMDE) genes were identified based on the relationship between methylation and expression. Furthermore, we conducted weighted correlation network analysis (WGCNA) and co-expression analysis to identify the core AMDE genes strongly involved in atherosclerosis. K-means clustering was used to characterize two subtypes of atherosclerosis in GSE40231, and then 29 samples were recognized as validation dataset (GSE28829). In a blood sample cohort (GSE90074), chi-square test and logistic analysis were performed to explore the clinical implication of the K-means clusters. Furthermore, significance analysis of microarrays and prediction analysis of microarrays (PAM) were applied to identify the signature AMDE genes. Moreover, the classification performance of signature AMDE gene-based classifier from PAM was validated in another blood sample cohort (GSE34822). A total of 1,569 AMDE mRNAs and eight AMDE long non-coding RNAs (lncRNAs) were identified by differential analysis. Through the WGCNA and co-expression analysis, 32 AMDE mRNAs and seven AMDE lncRNAs were identified as the core genes involved in atherosclerosis development. Functional analysis revealed that AMDE genes were strongly related to inflammation and axon guidance. In the clinical analysis, the atherosclerotic subtypes were associated with the severity of coronary artery disease and risk of adverse events. Eight genes, including

Indexed as

atherosclerosisdifferentially expressed geneK-means clusteringlncRNAmethylation

Identifiers

PMID33381146
PMCPMC7767999
OpenAlexW3112146410

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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.