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

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

  • Nat Biomed Eng. 2022 Jan;6(1):76-93. doi: 10.1038/s41551-021-00819-5.
Chenglong Xie  # 1 2 3 4 5,  Xu-Xu Zhuang  # 6,  Zhangming Niu  # 7 8,  Ruixue Ai  # 2,  Sofie Lautrup 2,  Shuangjia Zheng 9,  Yinghui Jiang 8,  Ruiyu Han 2,  Tanima Sen Gupta 2,  Shuqin Cao 2,  Maria Jose Lagartos-Donate 2,  Cui-Zan Cai 6,  Li-Ming Xie 6,  Domenica Caponio 2,  Wen-Wen Wang 10,  Tomas Schmauck-Medina 2,  Jianying Zhang 2,  He-Ling Wang 2,  Guofeng Lou 2,  Xianglu Xiao 8,  Wenhua Zheng 11,  Konstantinos Palikaras 12,  Guang Yang 13 14,  Kim A Caldwell 15 16,  Guy A Caldwell 15 16,  Han-Ming Shen 17 18,  Hilde Nilsen 2 19,  Jia-Hong Lu 20,  Evandro F Fang 21 22 23
Affiliations

Affiliations

  • 1 Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
  • 2 Department of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.
  • 3 Institute of Aging, Wenzhou Medical University, Wenzhou, China.
  • 4 Oujiang Laboratory, Wenzhou, Zhejiang, China.
  • 5 Key Laboratory of Alzheimer's Disease of Zhejiang Province, Wenzhou, China.
  • 6 State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China.
  • 7 Aladdin Healthcare Technologies Ltd., London, UK.
  • 8 MindRank AI Ltd., Hangzhou, Zhejiang, China.
  • 9 School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China.
  • 10 Center of Traditional Chinese Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
  • 11 Faculty of Health Sciences, University of Macau, Taipa, Macau, China.
  • 12 Department of Physiology, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.
  • 13 Cardiovascular Research Centre, Royal Brompton Hospital, London, UK.
  • 14 National Heart and Lung Institute, Imperial College London, London, UK.
  • 15 Department of Biological Sciences, The University of Alabama, Tuscaloosa, AL, USA.
  • 16 Departments of Neurology and Neurobiology, Center for Neurodegeneration and Experimental Therapeutics, Nathan Shock Center for Research on the Basic Biology of Aging, University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA.
  • 17 Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
  • 18 Faculty of Health Sciences, University of Macau, Macau, China.
  • 19 The Norwegian Centre on Healthy Ageing (NO-Age), Oslo, Norway.
  • 20 State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China. jiahonglu@um.edu.mo.
  • 21 Department of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway. e.f.fang@medisin.uio.no.
  • 22 The Norwegian Centre on Healthy Ageing (NO-Age), Oslo, Norway. e.f.fang@medisin.uio.no.
  • 23 Department of Geriatrics, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, China. e.f.fang@medisin.uio.no.
  • # Contributed equally.
PMID: 34992270 DOI: 10.1038/s41551-021-00819-5
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.

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