Evidence map›Paper›PMID 34992270›Full record

ArticleNature biomedical engineering2022

Amelioration of Alzheimer's disease pathology by mitophagy inducers identified via machine learning and a cross-species workflow.

Chenglong Xie, Xu-Xu Zhuang, Zhangming Niu, Ruixue Ai, Sofie Lautrup, Shuangjia Zheng, Yinghui Jiang, Ruiyu Han, Tanima Sen Gupta, Shuqin Cao and 19 more

Open access · hybridAbstract read
In one paragraph

Article in Nature biomedical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 187 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
187citing papers in PubMed, 2 pooled it
36.8field-weighted citation impact, top 1% of its field
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

187 citing papers in PubMed, 2 syntheses or guidelines pooled it, 325 citations in OpenAlex.

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  10. A combined artificial intelligence-wet lab approach identifies a pivotal role of the NADAlzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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127 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

29 authors at 9 institutions in 7 countries.

Chenglong Xie *Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Xu-Xu Zhuang *State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China.ORCID http://orcid.org/0000-0002-2938-5923
Zhangming Niu *Aladdin Healthcare Technologies Ltd., London, UK.
Ruixue Ai *Department of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.ORCID http://orcid.org/0000-0001-9870-3692
Sofie LautrupDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.
Shuangjia ZhengSchool of Data and Computer Science, Sun Yat-sen University, Guangzhou, China.
Yinghui JiangMindRank AI Ltd., Hangzhou, Zhejiang, China.
Ruiyu HanDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.
Tanima Sen GuptaDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.
Shuqin CaoDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.
Maria Jose Lagartos-DonateDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.
Cui-Zan CaiState Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China.
Li-Ming XieState Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China.
Domenica CaponioDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.ORCID http://orcid.org/0000-0002-3827-8943
Wen-Wen WangCenter of Traditional Chinese Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
Tomas Schmauck-MedinaDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.ORCID http://orcid.org/0000-0003-4618-0628
Jianying ZhangDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.
He-Ling WangDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.ORCID http://orcid.org/0000-0002-8920-1487
Guofeng LouDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.
Xianglu XiaoMindRank AI Ltd., Hangzhou, Zhejiang, China.
Wenhua ZhengFaculty of Health Sciences, University of Macau, Taipa, Macau, China.
Konstantinos PalikarasDepartment of Physiology, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.ORCID http://orcid.org/0000-0001-6992-5560
Guang YangCardiovascular Research Centre, Royal Brompton Hospital, London, UK.ORCID http://orcid.org/0000-0001-7344-7733
Kim A CaldwellDepartment of Biological Sciences, The University of Alabama, Tuscaloosa, AL, USA.ORCID http://orcid.org/0000-0003-1580-6122
Guy A CaldwellDepartment of Biological Sciences, The University of Alabama, Tuscaloosa, AL, USA.ORCID http://orcid.org/0000-0002-8283-9090
Han-Ming ShenDepartment of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Hilde NilsenDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.
Jia-Hong LuState Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China. jiahonglu@um.edu.mo.ORCID http://orcid.org/0000-0002-1147-125X
Evandro F FangDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway. e.f.fang@medisin.uio.no.ORCID http://orcid.org/0000-0003-0355-7202
University of Oslo · NOUniversity of Macau · MOUniversity of Alabama · USNational and Kapodistrian University of Athens · GRNational University of Singapore · SGNorwegian Institute of Public Health · NORoyal Brompton Hospital · GBSun Yat-sen University · CNWenzhou Medical University · CN

Funding

British Heart Foundation PG/16/78/32402Howard Hughes Medical Institute
6 · The paper itself

Abstract

A reduced removal of dysfunctional mitochondria is common to aging and age-related neurodegenerative pathologies such as Alzheimer's disease (AD). Strategies for treating such impaired mitophagy would benefit from the identification of mitophagy modulators. Here we report the combined use of unsupervised machine learning (involving vector representations of molecular structures, pharmacophore fingerprinting and conformer fingerprinting) and a cross-species approach for the screening and experimental validation of new mitophagy-inducing compounds. From a library of naturally occurring compounds, the workflow allowed us to identify 18 small molecules, and among them two potent mitophagy inducers (Kaempferol and Rhapontigenin). In nematode and rodent models of AD, we show that both mitophagy inducers increased the survival and functionality of glutamatergic and cholinergic neurons, abrogated amyloid-β and tau pathologies, and improved the animals' memory. Our findings suggest the existence of a conserved mechanism of memory loss across the AD models, this mechanism being mediated by defective mitophagy. The computational-experimental screening and validation workflow might help uncover potent mitophagy modulators that stimulate neuronal health and brain homeostasis.

Indexed as

Alzheimer DiseaseMitophagyAmyloid beta-PeptidesAnimalsMachine LearningWorkflowAmyloid beta-Peptides

Identifiers

PMID34992270
PMCPMC8782726
OpenAlexW4205241347

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.