Alzheimer’s disease is a disorder characterized by abnormalities in several different biological areas.
A study carried out by HBHL-funded researcher Yasser Iturria-Medina and his research group, in the Department of Neurology and Neurosurgery at The Neuro, represents the first and largest multimodal data collection effort to date for Alzheimer’s disease. It includes two independent, large-scale, post-mortem and in vivo cohorts covering the entire disease spectrum.
By developing a new machine-learning method, the group was able to assemble different layers of molecular data into the first personalized multi-level index of Alzheimer’s dementia progression. It can predict the severity of the abnormalities affecting the nervous system and identify both disease-progression stages and distinct disease subtypes at the molecular level.
Read the full Research Spotlight on the HBHL website.