The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Abnormality of m6A mRNA Methylation Is Involved in Alzheimer’s Disease
Open accessAbstract
Alzheimer's disease (AD), the most common form of dementia, is highly prevalent in older adults. The main clinical feature is the progressive decline of memory function, which eventually leads to the decline of cognitive function. At present, the pathogenesis of AD is unclear. In the disease process, synaptic changes are the key. Recent studies have shown that the dysregulation of RNA methylation is related to many biological processes, including neurodevelopment and neurodegenerative diseases. N6-methyladenosine (m6A) is the most abundant modification in eukaryotic RNA. In this study, RNA m6A methylation was quantified in APP/PS1 transgenic mice, which is an AD mouse model, and C57BL/6 control mice, and data showed that m6A methylation was elevated in the cortex and the hippocampus of APP/PS1 transgenic mice. Next, the alterations of m6A RNA methylation in AD and in C57BL/6 mice were investigated using high-throughput sequencing. Genome-wide maps of m6A mRNA showed that the degrees of m6A methylation were higher in many genes and lower in others in AD mice. Interestingly, the expression of the m6A methyltransferase METTL3 was elevated and that of the m6A demethylase FTO was decreased in AD mice. The data were analyzed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, and pathways that might be related to synaptic or neuron development and growth were constructed. The related pathways and genes predicted the potential roles of the differentially expressed m6A methylation RNA in AD. Collectively, our findings demonstrate that the m6A methylation of RNA promotes the development of AD.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures








Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source doesn’t support the claim as written.
In the citing paper
“Interestingly, m6A does not appear to accumulate in models of Aβ amyloidosis, which accumulate aggregates extracellularly (Han et al., 2020).”
From β-amyloid accumulation enhances microtubule associated protein tau pathology in an APPNL-G-F/MAPTP301S mouse model of Alzheimer’s disease (2024) · cites this paper as Han et al., 2020
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Total m6A levels were also reported in a previous manuscript examining m6A in an AD model utilizing over-expression of only APP, which is a model that exhibits Aβ accumulation without corresponding MAPT pathology (Han et al., 2020).”
From β-amyloid accumulation enhances microtubule associated protein tau pathology in an APPNL-G-F/MAPTP301S mouse model of Alzheimer’s disease (2024) · cites this paper as Han et al., 2020
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Data from this manuscript suggest that the absence of MAPT pathology in this model produced a corresponding absence of m6A accumulation (Han et al., 2020).”
From β-amyloid accumulation enhances microtubule associated protein tau pathology in an APPNL-G-F/MAPTP301S mouse model of Alzheimer’s disease (2024) · cites this paper as Han et al., 2020
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method
Livak, K. J., & Schmittgen, T. D. (2001) · Methods · doi:10.1006/meth.2001.1262 · Cited by 180,860
Comprehensive Analysis of mRNA Methylation Reveals Enrichment in 3′ UTRs and near Stop Codons
Meyer, K. D., Saletore, Y., Zumbo, P., Elemento, O., Mason, C. E., & Jaffrey, S. R. (2012) · Cell · doi:10.1016/j.cell.2012.05.003 · Cited by 4,223
N6-Methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO
Jia, G., Fu, Y., Zhao, X., Dai, Q., Zheng, G., Yang, Y., Yi, C., Lindahl, T., Pan, T., Yang, Y.-G., et al. (2011) · Nature Chemical Biology · doi:10.1038/nchembio.687 · Cited by 4,106
Mutation of the mouse klotho gene leads to a syndrome resembling ageing
Kuro-o, M., Matsumura, Y., Aizawa, H., Kawaguchi, H., Suga, T., Utsugi, T., Ohyama, Y., Kurabayashi, M., Kaname, T., Kume, E., et al. (1997) · Nature · doi:10.1038/36285 · Cited by 3,837
Clinical and biomarker changes in dominantly inherited Alzheimer's disease
Bateman, R. J., Xiong, C., Benzinger, T. L. S., Fagan, A. M., Goate, A., Fox, N. C., Marcus, D. S., Cairns, N. J., Xie, X., Blazey, T. M., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1202753 · Cited by 3,814
A METTL3–METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation
Liu, J., Yue, Y., Han, D., Wang, X., Fu, Y., Zhang, L., Jia, G., Yu, M., Lu, Z., Deng, X., et al. (2014) · Nature Chemical Biology · doi:10.1038/nchembio.1432 · Cited by 3,433
Vu, L., Pickering, B. F., Cheng, Y., Zaccara, S., Nguyen, D. T. T., Minuesa, G., Chou, T., Chow, A., Saletore, Y., MacKay, M. J., et al. (2017) · Nature Medicine · doi:10.1038/nm.4416 · Cited by 1,249
Dynamic m6A mRNA methylation directs translational control of heat shock response
Zhou, J. L., Wan, J., Gao, X., Zhang, X., Jaffrey, S. R., & Qian, S. (2015) · Nature · doi:10.1038/nature15377 · Cited by 1,228
Zhao, X., Yang, Y., Sun, B.-F., Shi, Y. X., Yang, X., Xiao, W., Hao, Y.-J., Ping, X., Chen, Y., Wang, W., et al. (2014) · Cell Research · doi:10.1038/cr.2014.151 · Cited by 1,201
Neurotoxicity of Amyloid -Protein: Synaptic and Network Dysfunction
Mucke, L., & Selkoe, D. J. (2012) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a006338 · Cited by 1,000
Cited by
Sorted by citations
Items 301–301 of 301
Kang, Z., Zhang, F., Ming, G., Song, H., & Liu, J. (2026) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-026-01039-y
Metadata
- Authors
- Han, M., Liu, Z., Xu, Y., Liu, X., Wang, D., Li, F., Wang, Y., & Bi, J.
- Affiliations
- Second Hospital of Shandong University (CN)
- Shandong University (CN)
- Corresponding author
- Wang, Yun
- Venue
- Frontiers in Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2020-02-28
- Volume
- 14
- Pages
- 98-98
- ISSN
- 1662-453X (ISSN-L)
- PMC
- PMC7058666
- OpenAlex
- W3008232393
- Cited by
- 286
- References
- 29
- Citations by year
- 2026: 26 · 2025: 25 · 2024: 43 · 2023: 64 · 2022: 52 · 2021: 62 · 2020: 14
- FWCI
- 16.79
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Neuroscience (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA modifications and cancer
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
- Keywords
- Alzheimer's disease, N6-methyladenosine, RNA methylation, APP/PS1 mice, synaptic dysfunction, hippocampus, cortex, neurodegeneration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review