Evidence map›Paper›PMID 41510223›Full record

ArticleResearch square2025

Inhibition of N6-Methyladenosine Accumulation by Targeting METTL3 Mitigates Tau Pathology and Cognitive Decline in Alzheimer's Disease.

Lulu Jiang, Allison Tucker, Camron Sepehri, Dev Patel, Qingbo Wang, Shuo Yuan, Eliana Sherman, Yicheng Chen, Joey Beh, Addysen Downey and 3 more

Abstract readPreprint
In one paragraph

Article in Research square, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Lulu JiangUniversity of Virginia.ORCID 0000-0002-6918-6777
Allison TuckerUniversity of Virginia.ORCID 0009-0009-2540-3467
Camron SepehriUniversity of Virginia.
Dev PatelUniversity of Virginia.
Qingbo WangUniversity of Virginia.
Shuo YuanUniversity of Virginia.
Eliana ShermanUniversity of Virginia.
Yicheng ChenUniversity of Virginia.
Joey BehUniversity of Virginia.
Addysen DowneyUniversity of Virginia.
Daniel GoldbergUniversity of Virginia.
Weronika GniadzikUniversity of Virginia.
Xin MaUniversity of Virginia.ORCID 0000-0002-7058-0165

Funding

Epitranscriptomic Mechanism in pathogenesis of Alzheimer’s diseaseR01AG091577 · NIA · UNIVERSITY OF VIRGINIA · PI Lulu Jiang · 2025 to 2026
$1.5M
NIA NIH HHS R01 AG091577
6 · The paper itself

Abstract

Dysregulation of N6-methyladenosine (m6A) modification of RNA has emerged as a novel feature of Alzheimer's disease (AD). Here, we investigate the relationship between m6A modification and AD pathology, and the therapeutic potential of modulating excessive m6A via its "writer" methyltransferase METTL3 in a humanized P301S tau transgenic mouse model of AD (PS19). We observed significantly elevated m6A levels in human post-mortem AD frontal cortex tissue compared to healthy controls, which positively correlated with hyperphosphorylated tau and amyloid-β (Aβ) deposition. These effects were recapitulated in the PS19 tau mice model of AD. Importantly, treatment of PS19 mice with the METTL3 inhibitor STM2457 reduced excessive m6A, alleviated tau pathology, and attenuated neurodegeneration. Behavioral assessments further demonstrated that STM2457-treated PS19 mice exhibited significantly improved learning and memory relative to untreated PS19 mice. Our results identify m6A as a critical contributor to AD pathogenesis and demonstrate that pharmacological inhibition of METTL3 represents a promising therapeutic strategy to improve cognition in AD.

Indexed as

Alzheimer’s diseasecognitionMETTL3 inhibitorN6-methyladenosineRNA modificationSTM2457tauopathy

Identifiers

PMID41510223
PMCPMC12776473

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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.