Article (Scientific journals)
A Machine-Learning Approach Identifies Rejuvenating Interventions in the Human Brain.
Santamaria, Guillem; Iglesias, Cristina; Jung, Sascha et al.
2025In Advanced Science, p. 03344
Peer reviewed
 

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Keywords :
cognitive decline; gene expression; senescence; therapies; transcriptional age
Abstract :
[en] The increase in life expectancy has caused a rise in age-related brain disorders. Although brain rejuvenation is a promising strategy to counteract brain functional decline, systematic discovery methods for efficient interventions are lacking. A computational platform based on a transcriptional brain aging clock capable of detecting age- and neurodegeneration-related changes is developed. Applied to neurodegeneration-positive samples, it reveals that neurodegenerative disease presence and severity significantly increase predicted age. By screening 43840 transcriptional profiles of chemical and genetic perturbations, it identifies 453 unique rejuvenating interventions, several of which are known to extend lifespan in animal models. Additionally, the identified interventions include drugs already used to treat neurological disorders, Alzheimer's disease among them. A combination of compounds predicted by the platform reduced anxiety, improved memory, and rejuvenated the brain cortex transcriptome in aged mice. These results demonstrate the platform's ability to identify brain-rejuvenating interventions, offering potential treatments for neurodegenerative diseases.
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
Santamaria, Guillem ;  Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du Swing, Esch-Belval Esch-sur-Alzette, 4367, Luxembourg
Iglesias, Cristina;  Centro de Investigación en Medicina Molecular y Enfermedades Crónicas (CIMUS), University of Santiago de Compostela (USC), Instituto de Investigación Sanitaria (IDIS), Campus Vida Avenida Barcelona, s/n, Santiago de Compostela, 15782, Spain
Jung, Sascha;  CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Bizkaia Technology Park, 801 Building, Derio, 48160, Spain
Arcos Hodar, Javier;  CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Bizkaia Technology Park, 801 Building, Derio, 48160, Spain
Nogueiras, Ruben;  Centro de Investigación en Medicina Molecular y Enfermedades Crónicas (CIMUS), University of Santiago de Compostela (USC), Instituto de Investigación Sanitaria (IDIS), Campus Vida Avenida Barcelona, s/n, Santiago de Compostela, 15782, Spain
DEL SOL MESA, Antonio  ;  University of Luxembourg ; CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Bizkaia Technology Park, 801 Building, Derio, 48160, Spain ; IKERBASQUE, Basque Foundation for Science, Bilbao, 48013, Spain
External co-authors :
yes
Language :
English
Title :
A Machine-Learning Approach Identifies Rejuvenating Interventions in the Human Brain.
Publication date :
14 July 2025
Journal title :
Advanced Science
ISSN :
2198-3844
eISSN :
2198-3844
Publisher :
Wiley, Germany
Pages :
e03344
Peer reviewed :
Peer reviewed
Funders :
Xunta de Galicia
Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas
Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición
H2020 European Research Council
Ministerio de Ciencia e Innovación
Government of Canada
Fonds National de la Recherche Luxembourg
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