Evidence map›Paper›PMID 34427843›Full record

ArticleMetabolic brain disease2022

Identification of methylation markers for diagnosis of autism spectrum disorder.

Bei Zhang, Xiaoyuan Hu, Yuefei Li, Yongkang Ni, Lin Xue

Abstract read
PubMed Publisher
In one paragraph

Article in Metabolic brain disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.1field-weighted citation impact, top 26% 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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Efficacy and safety ofFrontiers in nutrition · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. DNA Methylation Profiles ofInternational journal of molecular sciences · 2022
    Article
  7. Article
  8. 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

5 authors at 3 institutions in 1 country.

Bei ZhangDepartment of quality management, The Fourth People's Hospital of Urumqi, Jianquan street, Urumqi, Xinjiang, 830002, China.
Xiaoyuan HuXinjiang Uighur Autonomous Region Center for Disease Control and Prevention, Jianquan street, Tianshan District, Urumqi, Xinjiang, 830001, China.
Yuefei LiSchool of Public Health, Xinjiang Medical University, Liyushan Road, Xinshi District, Urumqi, Xinjiang, 830000, China.
Yongkang NiSchool of Public Health, Xinjiang Medical University, Liyushan Road, Xinshi District, Urumqi, Xinjiang, 830000, China.
Lin XueDepartment of quality management, The Fourth People's Hospital of Urumqi, Jianquan street, Urumqi, Xinjiang, 830002, China. xuelin126@yeah.net.
Urumqi 4th People's Hospital · CNXinjiang Medical University · CNXinjiang Uygur Autonomous Region Disease Prevention and Control Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autism spectrum disorder (ASD) is a hereditary heterogeneous neurodevelopmental disorder characterized by social and speech dysplasia. We collected the expression profiles of ASD in GSE26415, GSE42133 and GSE123302 from the gene expression omnibus (GEO) database, as well as methylation data of GSE109905. Differentially expressed genes (DEGs) between ASD and controls were obtained by differential expression analysis. Enrichment analysis identified the biological functions and signaling pathways involved by common genes in three groups of DEGs. Protein-protein interaction (PPI) networks were used to identify genes with the highest connectivity as key genes. In addition, we identified methylation markers by associating differentially methylated positions. Key methylation markers were identified using the least absolute shrink and selection operator (LASSO) model. Receiver operating characteristic curves and nomograms were used to identify the diagnostic role of key methylation markers for ASD. A total of 57 common genes were identified in the three groups of DEGs. These genes were mainly enriched in Sphingolipid metabolism and PPAR signaling pathway. In the PPI network, we identified seven key genes with higher connectivity, and used qRT-PCR experiments to verify the expressions. In addition, we identified 31 methylation markers and screened 3 key methylation markers (RUNX2, IMMP2L and MDM2) by LASSO model. Their methylation levels were closely related to the diagnostic effects of ASD. Our analysis identified RUNX2, IMMP2L and MDM2 as possible diagnostic markers for ASD. Identifying different biomarkers and risk genes will contribute to the diagnosis of ASD and the development of new clinical and drug treatments.

Indexed as

Autism Spectrum DisorderBiomarkersDNA MethylationHumansSignal TransductionBiomarkersAutism spectrum disorderDiagnostic markersDNA methylationLASSO modelMDM2

Identifiers

PMID34427843
OpenAlexW3135280042

What OpenQuestion holds

Textmetadata
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.