Evidence map›Paper›PMID 41387780›Full record

ArticleMolecular medicine (Cambridge, Mass.)2025

The SARS-CoV-2 nucleocapsid protein induces microglia senescence-mediated cognitive impairment via Glycolysis.

Nan-Shi-Yu Yang, Han-Xi Sha, Chen-Yu Zhang, Hui Chen, Yu-Biao Liu, Jian-Bing Xiong, Jia-Xi Duan, Jun Zhang, Cha-Xiang Guan, Yong Zhou and 2 more

Abstract read
In one paragraph

Article in Molecular medicine (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Nan-Shi-Yu Yang *Department of Emergency, Xiangya Hospital, Central South University, Changsha, Hunan, 410078, China.
Han-Xi Sha *Department of Physiology, Xiangya School of Basic Medical Science, Central South University, Changsha, Hunan, 410078, China.
Chen-Yu ZhangDepartment of Physiology, Xiangya School of Basic Medical Science, Central South University, Changsha, Hunan, 410078, China.
Hui ChenDepartment of Physiology, Xiangya School of Basic Medical Science, Central South University, Changsha, Hunan, 410078, China.
Yu-Biao LiuDepartment of Physiology, Xiangya School of Basic Medical Science, Central South University, Changsha, Hunan, 410078, China.
Jian-Bing XiongDepartment of Emergency, Xiangya Hospital, Central South University, Changsha, Hunan, 410078, China.
Jia-Xi DuanDepartment of Geriatrics, Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, 410078, China.
Jun ZhangDepartment of Physiology, Hunan University of Medicine, Huaihua, 418000, China.
Cha-Xiang GuanDepartment of Physiology, Xiangya School of Basic Medical Science, Central South University, Changsha, Hunan, 410078, China.
Yong ZhouDepartment of Physiology, Xiangya School of Basic Medical Science, Central South University, Changsha, Hunan, 410078, China.
Feng SuDepartment of Emergency, Xiangya Hospital, Central South University, Changsha, Hunan, 410078, China. sufeng@csu.edu.cn.
Wen-Jing ZhongDepartment of Physiology, Xiangya School of Basic Medical Science, Central South University, Changsha, Hunan, 410078, China. zhongwenjing@csu.edu.cn.

Funding

the Hunan Province Special Project for the Construction of Innovative Provinces 2023JJ50075the Hunan Provincial Key Area R&D Programs 2022SK2127the Open competition mechanism to select the best candidates for key research projects of Ningxia Medical University XJKF230104the Postdoctoral Fellowship Program of CPSF GZC20233159
6 · The paper itself

Abstract

The COVID-19 pandemic has precipitated a surge in neurocognitive dysfunction, with long-term implications for global health systems and socioeconomic stability. Despite growing clinical recognition of post-COVID cognitive deficits ("brain fog"), the molecular mechanisms driving these impairments remain poorly understood. Our study addresses this critical gap by identifying SARS-CoV-2 nucleocapsid protein (SARS-CoV-2 N protein), a core structural component of the virus, as a novel etiological factor in senescence-mediated cognitive decline. We observed that SARS-CoV-2 N protein caused microglial senescence both in vivo and in vitro. Mechanistically, SARS-CoV-2 N protein-induced metabolic shifting toward glycolysis initiated a cascade of microglial senescence, which propagated cognitive impairment. We found that glycolysis inhibition reduced SARS-CoV-2 N protein-triggered microglial senescence and attenuated cognitive impairment in mice. Disrupted mitochondrial dynamics impaired oxidative phosphorylation capacity, forcing glycolytic reprogramming that ultimately triggered cellular senescence activation. We found that the SARS-CoV-2 N protein promoted excessive mitochondrial dysfunction in microglia, resulting in mitochondrial fragmentation. Inhibition of mitochondrial fission effectively rescued SARS-CoV-2 N protein-induced microglial senescence. In conclusion, our study suggests that the SARS-CoV-2 N protein induces senescence-mediated cognitive impairment by promoting glycolysis in microglia. Therapeutic targeting of glycolysis in SARS-CoV-2 N protein-triggered microglial senescence could be beneficial for treating or preventing cognitive impairment.

Indexed as

Cellular SenescenceCognitive DysfunctionCoronavirus Nucleocapsid ProteinsCOVID-19GlycolysisMicrogliaPhosphoproteinsSARS-CoV-2AnimalsHumansMaleMiceMice, Inbred C57BLMitochondriaMitochondrial DynamicsCoronavirus Nucleocapsid Proteinsnucleocapsid phosphoprotein, SARS-CoV-2PhosphoproteinsCognitive impairmentGlycolysisMicrogliaSARS-CoV-2 N proteinSenescence

Identifiers

PMID41387780
PMCPMC12817434

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.