Innovative Research Paves the Path to Enhanced Brain Study Reliability

A new study identifies research strategies for tying brain function and structure to behavior and health. Brain-wide association studies, which use magnetic resonance imaging to identify relationships between brain structure or function and human behavior or health, have faced criticism for producing results that often cannot be replicated by other researchers. A new study published
HomeHealth"Revolutionizing Drug Discovery: The Potential of Alzheimer's in a Petri Dish"

“Revolutionizing Drug Discovery: The Potential of Alzheimer’s in a Petri Dish”

Ten years ago, scientists developed a novel approach to study Alzheimer’s disease, termed “Alzheimer’s in a dish.” This method involves maintaining cultures of mature brain cells in a gel, allowing researchers to replicate changes that occur in the human brain over a span of 10 to 13 years within just six weeks. However, the crucial question arises: does this model truly reflect the changes that occur in actual patients? A recent study conducted by researchers from Mass General Brigham, in collaboration with their peers at Beth Israel Deaconess Medical Center (BIDMC), introduced an algorithm to objectively evaluate how well Alzheimer’s models represent the functions and gene expression patterns observed in patient brains. Their findings, published in Neuron, highlight important shared pathways, affirming that the Alzheimer’s in a dish model can effectively and swiftly evaluate new drugs and guide drug discovery.

Co-senior author Doo Yeon Kim, PhD, from the Department of Neurology at Massachusetts General Hospital (MGH), a key member of the Mass General Brigham healthcare system, stated, “Our objective is to identify the best model that closely resembles the behavior of Alzheimer’s disease in patients’ brains. We created this 3D cell culture model for Alzheimer’s a decade ago, and our current data demonstrates that it can expedite drug discovery.”

This innovative study arose from a collaboration among researchers specializing in neurology and data-driven methodologies, united in their quest to find improved treatments for Alzheimer’s disease (AD). Over the years, AD research has encountered obstacles primarily due to limitations of mouse models, which lack the development of amyloid plaques and other AD characteristics found in humans. While various models were created by Kim and the team, it wasn’t until now that it was possible to assess how accurately these models represent the molecular and functional transformations present in the brain.

Co-senior author Winston Hide, PhD, from the Department of Pathology at BIDMC, expressed, “We confronted a core challenge: discerning which models truly capture the complexity of Alzheimer’s in the human brain. By shifting our focus from individual genes to the comprehensive biological pathways, we have developed a system that revolutionizes our approach to drug discovery and testing.”

To tackle this challenge, the research team, led by Pourya Naderi Yeganeah, PhD, and Sang Su Kwak, PhD, co-lead authors, designed an innovative integrative pathway activity analysis (IPAA) platform. This platform is capable of identifying which models closely reproduce the functional alterations typical of AD and pinpointing the most relevant pathways for drug development. Their study revealed 83 dysregulated pathways that were shared between brain samples from deceased Alzheimer’s patients and 3D cellular models. The researchers focused on one pathway—p38 mitogen-activated protein kinase (MAPK)—as a proof of concept, exploring drugs that target this pathway. Remarkably, they found that a clinical p38 MAPK inhibitor, not yet tested in AD patients, effectively reduced AD pathology in vitro, indicating its potential for future clinical trials. Their findings are not limited to a single pathway; the platform’s ability to identify promising drug targets, coupled with the rapid and scalable nature of the Alzheimer’s in a dish model, fosters the simultaneous testing of multiple drugs to uncover potential therapies. The researchers have already evaluated hundreds of approved drugs and natural substances using this model, positioning them well for clinical trials.

Co-senior author Rudolph Tanzi, PhD, Director of the McCance Center for Brain Health and Genetics and Aging Research Unit at MGH, remarked, “We now possess a system that enables us to evaluate new drugs quickly, along with an algorithmic platform that predicts which drugs will be most effective. Together, these advancements are bringing us closer to discovering better drugs and delivering them to patients.”