Evidence map›Paper›PMID 38738952›Full record

SynthesisCNS neuroscience & therapeutics2024

Meta-analysis and transcriptomic analysis reveal that NKRF and ZBTB17 regulate the NF-κB signaling pathway, contributing to the shared molecular mechanisms of Alzheimer's disease and atherosclerosis.

Di Zhang, Keyan Chen, Li Shen Shan

Abstract readMeta-Analysis
In one paragraph

Synthesis in CNS neuroscience & therapeutics, 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. Review
  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

3 authors.

Di ZhangDepartment of Cardiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Keyan ChenLaboratory Animal Science of China Medical University, Shenyang, Liaoning, China.ORCID 0000-0002-8041-4312
Li Shen ShanDepartment of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.

Funding

Basic Scientific Research Project of Colleges and Universities of Liaoning Province General Program, No. LJKZ0746Basic Scientific Research Project of Colleges and Universities of Liaoning Province Key Program, No. LJKZ0746Liaoning Provincial Natural Fund 2022-MS-180
6 · The paper itself

Abstract

introductionAlzheimer's disease (AD) and atherosclerosis (AS) are widespread diseases predominantly observed in the elderly population. Despite their prevalence, the underlying molecular interconnections between these two conditions are not well understood.

methodsUtilizing meta-analysis, bioinformatics methodologies, and the GEO database, we systematically analyzed transcriptome data to pinpoint key genes concurrently differentially expressed in AD and AS. Our experimental validations in mouse models highlighted the prominence of two genes, NKRF (NF-κB-repressing factor) and ZBTB17 (MYC-interacting zinc-finger protein 1).

resultsThese genes appear to influence the progression of both AD and AS by modulating the NF-κB signaling pathway, as confirmed through subsequent in vitro and in vivo studies.

conclusionsThis research uncovers a novel shared molecular pathway between AD and AS, underscoring the significant roles of NKRF and ZBTB17 in the pathogenesis of these disorders.

Indexed as

Alzheimer DiseaseAtherosclerosisNF-kappa BSignal TransductionAnimalsGene Expression ProfilingHumansMiceMice, TransgenicRepressor ProteinsTranscriptomeNF-kappa BRepressor ProteinsAlzheimer's diseaseatherosclerosismeta‐analysisNKRFZBTB17

Identifiers

PMID38738952
PMCPMC11090078

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.