Nearly seven million Americans live with Alzheimer’s disease, a progressive condition that destroys memory and other mental functions and is among the leading causes of death in the nation. While treatments to slow Alzheimer’s progression are available, no cure exists and the Alzheimer’s Association projects this figure will more than double by 2050.
Enter UMass Lowell Kennedy College of Sciences Dean Noureddine Melikechi, a researcher analyzing the basic metals in a patient’s plasma.
Hoping to better understand the disease, Melikechi and his research team, whose collective work was featured on the cover of the Journal of Analytical Atomic Spectrometry, have discovered potential biomarkers of Alzheimer’s disease using physics and machine learning.
Working with the dementia care unit at the Veterans Affairs hospital in Bedford, Melikechi and his team collected blood samples from Alzheimer’s patients and healthy individuals. They then examined the plasma, the liquid portion of the blood, using inductively coupled plasma mass spectrometry (ICP-MS), an analytical technique allowing them to measure the concentration of metals, such as iron and zinc, in the plasma.
Using machine learning algorithms, they found combinations of metals that differentiated the plasma samples of Alzheimer’s patients from those of healthy individuals. The researchers went back to their ICP-MS data and, through more testing, validated that most plasma samples could be identified as either Alzheimer’s or healthy based on the metal ratios of sodium and potassium; iron and sodium; and phosphorus and zinc.
“We have shown that ratios of elements present in blood may have the potential to be used as biomarkers of Alzheimer’s disease,” said Melikechi.
The research team is now looking at proteins associated with the disease.
Melikechi says using mass spectrometry with machine learning can lead to greater knowledge of diseases beyond Alzheimer’s.
“We are such a complex species, but we are made fundamentally from atoms, molecules and proteins,” he said. “If we understand more about humans at the fundamental level, that could lead to the development of new medicines and treatments for a broad spectrum of conditions.”