Evidence map›Paper›PMID 39424325›Full record

ArticleGenome research2024

Dynamic dysregulation of retrotransposons in neurodegenerative diseases at the single-cell level.

Wankun Deng, Citu Citu, Andi Liu, Zhongming Zhao

Abstract read
In one paragraph

Article in Genome research, 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. Review
  2. 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

4 authors.

Wankun Deng *Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas 77030, USA.
Citu Citu *Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas 77030, USA.
Andi LiuCenter for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas 77030, USA.
Zhongming ZhaoCenter for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas 77030, USA; zhongming.zhao@uth.tmc.edu.ORCID 0000-0002-3477-0914

Funding

AIM-AI: an Actionable, Integrated and Multiscale genetic map of Alzheimer's disease via deep learningU01AG079847 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Christopher A. Gaiteri, Xiaoqian Jiang · 2023 to 2026
$5.1M
Transforming dbGaP genetic and genomic data to FAIR-ready by artificial intelligence and machine learning algorithmsR01LM012806 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Zhongming Zhao · 2017 to 2026
$3.7M
Constructing A Transcriptomic Atlas of Retrotransposon in Alzheimer's DiseaseR03AG077191 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHAO, ZHONGMING · 2022 to 2022
$312k
NIA NIH HHS R03 AG077191NIA NIH HHS U01 AG079847NLM NIH HHS R01 LM012806
6 · The paper itself

Abstract

Retrotransposable elements (RTEs) are common mobile genetic elements comprising ∼42% of the human genome. RTEs play critical roles in gene regulation and function, but how they are specifically involved in complex diseases is largely unknown. Here, we investigate the cellular heterogeneity of RTEs using 12 single-cell transcriptome profiles covering three neurodegenerative diseases, Alzheimer's disease (AD), Parkinson's disease, and multiple sclerosis. We identify cell type marker RTEs in neurons, astrocytes, oligodendrocytes, and oligodendrocyte precursor cells that are related to these diseases. The differential expression analysis reveals the landscape of dysregulated RTE expression, especially L1s, in excitatory neurons of multiple neurodegenerative diseases. Machine learning algorithms for predicting cell disease stage using a combination of RTE and gene expression features suggests dynamic regulation of RTEs in AD. Furthermore, we construct a single-cell atlas of retrotransposable elements in neurodegenerative disease (scARE) using these data sets and features. scARE has six feature analysis modules to explore RTE dynamics in a user-defined condition. To our knowledge, scARE represents the first systematic investigation of RTE dynamics at the single-cell level within the context of neurodegenerative diseases.

Indexed as

Neurodegenerative DiseasesRetroelementsSingle-Cell AnalysisAlzheimer DiseaseAstrocytesGene Expression RegulationHumansMultiple SclerosisNeuronsOligodendrogliaParkinson DiseaseTranscriptomeRetroelements

Identifiers

PMID39424325
PMCPMC11529867

What OpenQuestion 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 OpenQuestion graph.