Core Viewpoint - Metformin, originally developed for type 2 diabetes, shows potential as a neuroprotective agent, particularly in the context of neurodegenerative diseases like multiple sclerosis, Parkinson's, and Alzheimer's [2][4][8]. Group 1: Research Findings - A recent study published in Nature Communications indicates that Metformin alters mitochondria-related metabolism and enhances the function of human oligodendrocytes, suggesting its neuroprotective effects [3][4]. - The study demonstrates that Metformin can penetrate the blood-brain barrier and promote functional regeneration of oligodendrocyte precursor cells (OPCs) in aged rats, enhancing myelin regeneration capabilities [8][9]. - In human stem cell-derived OPCs, Metformin increased the generation of myelin-related proteins, indicating its potential to stimulate myelin production in various cellular models [9]. Group 2: Clinical Implications - Clinical trials are currently underway to evaluate Metformin's efficacy as a treatment for multiple sclerosis, either as a monotherapy or in combination with other drugs, as well as its application as a direct neuroprotective agent for neurodegenerative diseases [8]. - Despite ongoing clinical trials, results have not yet been disclosed, and the specific effects of Metformin on human oligodendrocytes remain unclear, highlighting the need for further research [8][9].

Core Viewpoint - The article discusses a significant study identifying 64 genes that influence brain aging speed and suggests 13 potential anti-aging drugs, utilizing AI models to analyze brain scans and genetic data [1][3]. Research Overview - The study is noted as the largest attempt to determine genetic factors affecting organ aging, with implications for developing new brain anti-aging drugs [3]. - The research aims to identify factors leading to brain aging and explore potential solutions [5]. Methodology - The study uses Brain Age Gap (BAG) as a marker for brain aging, defined as the difference between predicted brain age and actual age [6]. - Data from 29,097 healthy participants in the UK Biobank was used to train seven AI models for brain age estimation [8]. - Validation was conducted using data from 3,227 healthy and 6,637 brain disease subjects, employing various assessment metrics [9][10]. Genetic Analysis - A Genome-Wide Association Study (GWAS) was performed on 31,520 healthy participants to identify genetic variations associated with BAG [11][12]. - The study explored the causal relationship between BAG and 18 brain diseases, finding a significant impact on intelligence [13][14]. Drug Discovery - The research identified 64 druggable genes linked to biological pathways related to brain aging, suggesting that targeting these genes could help combat aging or related diseases [14][15]. - A drug repurposing analysis revealed 466 potential anti-aging drugs, with 29 showing promise in delaying brain aging [17][18]. - Among these, 20 drugs, including Dasatinib and Diclofenac, have been previously noted for their anti-aging potential, with 13 currently undergoing clinical trials [19][20].