NEW YORK – By digging into genetic features linked to the difference between individuals' chronological age and brain age, known as the brain age gap (BAG), a research team from China and Israel has narrowed in on several potential drug targets that may aid in slowing down brain aging in the future.
"We anticipate that our findings will serve as a valuable resource for prioritizing drug development efforts for BAG, shedding light on the understanding of human brain aging and potentially extending the health span in humans," co-senior and co-corresponding author Zhengxing Huang, a computer science and technology researcher at Zhejiang University in China, and his colleagues wrote in a paper published in Science Advances on Wednesday.
For their study, the investigators analyzed magnetic resonance imaging data for 38,961 UK Biobank (UKB) participants, using deep learning models to make biological brain estimates that were validated using data for three more cohorts.
From there, they used array-based genotyping data for 31,520 UKB individuals to perform a genome-wide association study focused on the BAG between chronological and biological brain age, identifying two new and seven previously known BAG-associated loci.
"To efficiently identify potential drug targets for individuals without brain disorders but at high risk for rapid brain aging, we conducted a GWAS using participants from UKB who did not have any brain disorders," the authors explained. "This allowed us to eliminate confounding factors such as changes in the brain caused by brain disorders, which could potentially contribute to abnormal aging."
With the help of blood and brain expression quantitative trait locus (eQTL) results and published blood plasma protein QTL data, the team performed Mendelian randomization and colocalization analyses that led to 64 potentially targetable genes regulated by variants implicated in the brain aging GWAS.
"Our integrated pipeline — combining multimodal (MRI and omics) data, deep learning, [Mendelian randomization], and colocalization analyses — provides a comprehensive framework for identifying druggable targets for brain aging and could aid in the translation of these findings into drug development for brain aging," the authors suggested.
Along with genes implicated in aging in prior studies or clinical trials, the investigators whittled their set of "druggable genes" down to seven with the strongest ties to brain aging: MAPT, TNFSF12, GZMB, SIRPB1, GNLY, NMB, and C1RL.
With insights from a drug-gene interaction database called DGIdb, meanwhile, they tracked down 466 approved or investigational drugs expected to impact the activity of at least 29 genes in the druggable gene list.
The team also performed a phenome-wide association study aimed at finding relationships between the brain aging-linked druggable gene set and dozens of human traits, highlighting apparent ties between specific genes and everything from blood pressure, body mass index, blood glucose, and lipid levels to the risk of stroke, asthma, type 2 diabetes, and other conditions.
"Our results offer the potential to mitigate the risk associated with drug discovery by identifying genetically supported targets and repurposing approved drugs to attenuate brain aging," the authors concluded. "We anticipate that our findings will serve as a valuable resource for prioritizing drug development efforts for BAG, shedding light on the understanding of human brain aging and potentially extending the health span in humans."