Evidence map›Paper›PMID 39452046›Full record

ArticleBrain sciences2024

From Diabetes to Dementia: Identifying Key Genes in the Progression of Cognitive Impairment.

Zhaoming Cao, Yage Du, Guangyi Xu, He Zhu, Yinchao Ma, Ziyuan Wang, Shaoying Wang, Yanhui Lu

Abstract read
In one paragraph

Article in Brain sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Allele specific expression in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  3. Article
  4. 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.

Zhaoming CaoSchool of Nursing, Peking University, Beijing 100191, China.ORCID 0000-0001-7800-7366
Yage DuSchool of Nursing, Peking University, Beijing 100191, China.
Guangyi XuSchool of Nursing, Peking University, Beijing 100191, China.
He ZhuSchool of Stomatology, Peking University, Beijing 100191, China.
Yinchao MaThe Key Laboratory of Medical Immunology of the National Health Commission, School of Basic Medical Sciences, Peking University, Beijing 100191, China.
Ziyuan WangThe Key Laboratory of Medical Immunology of the National Health Commission, School of Basic Medical Sciences, Peking University, Beijing 100191, China.
Shaoying WangSchool of Stomatology, Peking University, Beijing 100191, China.
Yanhui LuSchool of Nursing, Peking University, Beijing 100191, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo provide a basis for further research on the molecular mechanisms underlying type 2 diabetes-associated mild cognitive impairment (DCI) using two bioinformatics methods to screen key genes involved in the progression of mild cognitive impairment (MCI) and type 2 diabetes.

methodsRNA sequencing data of MCI and normal cognition groups, as well as expression profile and sample information data of clinical characteristic data of GSE63060, which contains 160 MCI samples and 104 normal samples, were downloaded from the GEO database. Hub genes were identified using weighted gene co-expression network analysis (WGCNA). Protein-protein interaction (PPI) analysis, combined with least absolute shrinkage and selection operator (LASSO) and receiver operating characteristic (ROC) curve analyses, was used to verify the genes. Moreover, RNA sequencing and clinical characteristic data for GSE166502 of 13 type 2 diabetes samples and 13 normal controls were downloaded from the GEO database, and the correlation between the screened genes and type 2 diabetes was verified by difference and ROC curve analyses. In addition, we collected clinical biopsies to validate the results.

resultsBased on WGCNA, 10 modules were integrated, and six were correlated with MCI. Six hub genes associated with MCI (TOMM7, SNRPG, COX7C, UQCRQ, RPL31, and RPS24) were identified using the LASSO algorithm. The ROC curve was screened by integrating the GEO database, and revealed COX7C, SNRPG, TOMM7, and RPS24 as key genes in the progression of type 2 diabetes.

conclusionsCOX7C, SNRPG, TOMM7, and RPS24 are involved in MCI and type 2 diabetes progression. Therefore, the molecular mechanisms of these four genes in the development of type 2 diabetes-associated MCI should be studied.

Indexed as

chronic illnessclinical decision-makingdementiadiabetesgeneticsgenomicskey genesLASSOneurologynursing assessmentweighted gene co-expression network analysis

Identifiers

PMID39452046
PMCPMC11506463

What Socratic holds

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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.