A new study shows artificial intelligence (AI) analysis of blood samples can predict and explain neurodegenerative disease progression. The AI analysis could one day help doctors choose more appropriate and effective treatments for individuals who see them.
Researchers at The Neuro (Montreal Neurological Institute-Hospital) of McGill University and the Ludmer Centre for Neuroinformatics and Mental Health used an AI algorithm to analyze the blood and post-mortem brain samples of 1,969 participants with Alzheimer disease (AD) and Huntington’s disease (HD). Their goal was to find molecular patterns specific to these diseases.
“This test could one day be used by doctors to evaluate patients and prescribe therapies tailored to their needs,” says Yasser Iturria-Medina, the study’s first author. “It could also be used in clinical trials to categorize patients and better determine how experimental drugs impact their predicted disease progression.”
The blood test detected 85% to 90% of the top predictive molecular pathways that the test of post-mortem brain data did, showing a similarity between molecular alterations in both the brain and peripheral body.
The algorithm was able to detect how these participants’ genes expressed themselves in unique ways over decades. This offers the first long-term view of molecular changes underlying neurodegeneration.
This study aimed to uncover the chronological information contained in large-scale data by covering decades of disease progression. This reveals how changes in gene expression over that time are related to changes in the participant’s condition.
Monideep Dutt, MD; Jamika Hallman-Cooper, MD; Ekta Bery, MD; Mohammed Shahnawaz, MD; and Grace Gombolay, MD
F. Stephen Benesh, MD, and Shruti P. Agnihotri, MD
Nidhiben Anadani, MD