Evidence map›Paper›PMID 39610716›Full record

ArticleFrontiers in aging neuroscience2024

Identification of altered immune cell types and molecular mechanisms in Alzheimer's disease progression by single-cell RNA sequencing.

Hua Lin, Li Su, Daniel Mao, Grace Yang, Qi Huang, Yating Lan, Jingyi Zeng, Wenyi Song, Guining Liang, Qingyan Wei and 3 more

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Giant cell tumor of bone inhibits osteoblastogenesis via WNT5B.Journal of bone and mineral metabolism · 2026
    Article
  2. Review
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

13 authors.

Hua Lin *Department of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Li Su *Department of Neurology, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China.
Daniel Mao *Department of Biology, Pennsylvania State University, University Park, PA, United States.
Grace Yang *State College Area High School, State College, PA, United States.
Qi HuangDepartment of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Yating LanDepartment of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Jingyi ZengDepartment of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Wenyi SongDepartment of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Guining LiangDepartment of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Qingyan WeiDepartment of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Donghua ZouDepartment of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Rongjie LiDepartment of Geriatrics, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, China.
Chanhua ZouDepartment of Comprehensive Internal Medicine, Guangxi Medical University Caner Hospital, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by gradual loss of cognitive function. Understanding the molecular mechanisms is crucial for developing effective therapies. Methods: Data from single-cell RNA sequencing (scRNA-seq) in the GSE181279 dataset and gene chips in the GSE63060 and GSE63061 datasets were collected and analyzed to identify immune cell types and differentially expressed genes. Cell communication, pseudotime trajectory, enrichment analysis, co- expression network, and short time-series expression miner were analyzed to identify disease-specific molecular and cellular mechanisms. Results: We identified eight cell types (B cells, monocytes, natural killer cells, gamma-delta T cells, CD8+ T cells, Tem/Temra cytotoxic T cells, Tem/Trm cytotoxic T cells, and mucosal-associated invariant T cells) using scRNA-seq. AD samples were enriched in monocytes, CD8+ T cells, Tem/Temra cytotoxic T cells, and Tem/Trm cytotoxic T cells, whereas samples from healthy controls were enriched in natural killer and mucosal-associated invariant T cells. Five co-expression modules that were identified through weighted gene correlation network analysis were enriched in immune- inflammatory pathways. Candidate genes with higher area under the receiver operating characteristic curve values were screened, and the expression trend of Ubiquitin-Fold Modifier Conjugating Enzyme 1 (UFC1) gradually decreased from healthy controls to mild cognitive impairment and then to AD. Conclusion: Our study suggests that peripheral immune cells may be a potential therapeutic target for AD. Candidate genes, particularly UFC1, may serve as potential biomarkers for progression of AD.

Indexed as

Alzheimer’s diseaseimmune cellsmonocytessingle-cell RNA sequencingtlymphocytesUFC1

Identifiers

PMID39610716
PMCPMC11602448

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