Researchers at Scripps Research have developed a blood test that detects Alzheimer's disease by analyzing structural changes in blood proteins. The method identifies differences in three specific proteins, allowing accurate distinction between healthy individuals, those with mild cognitive impairment, and Alzheimer's patients. Published in Nature Aging on February 27, 2026, the findings could enable earlier diagnosis and treatment.
Alzheimer's disease affects an estimated 7.2 million Americans aged 65 and older, according to the Alzheimer's Association. Traditional diagnostic tests measure levels of amyloid beta (Aβ) and phosphorylated tau (p-tau) in blood or spinal fluid, but these may miss the earliest changes in the disease.
A team at Scripps Research has proposed a novel approach focusing on protein folding in the bloodstream. Their study, published in Nature Aging on February 27, 2026, examined plasma samples from 520 participants divided into three groups: cognitively normal adults, individuals with mild cognitive impairment (MCI), and patients with Alzheimer's.
Using mass spectrometry, the researchers assessed how exposed or buried certain protein locations were, indicating structural changes. Machine learning helped identify patterns linked to disease stages. The analysis revealed that as Alzheimer's progressed, some blood proteins became less structurally "open," providing more insight than protein concentration levels alone.
Three proteins showed the strongest links to disease status: C1QA, involved in immune signaling; clusterin, which aids protein folding and amyloid removal; and apolipoprotein B, which transports fats and supports blood vessel health.
"The correlation was amazing," said co-author Casimir Bamberger, a senior scientist at Scripps Research. "It was very surprising to find three lysine sites on three different proteins that correlate so highly with disease state."
This three-protein model classified participants with 83% overall accuracy, rising above 93% when comparing two groups, such as healthy versus MCI. It remained reliable in independent groups and repeat tests months apart, achieving 86% accuracy and tracking diagnostic changes over time. The structural score also correlated with cognitive test results and moderately with MRI brain shrinkage measures.
"Many neurodegenerative diseases are driven by changes in protein structure," noted senior author John Yates, a professor at Scripps Research.
The method could complement existing amyloid and tau tests by focusing on proteostasis disruptions, the system's role in maintaining proper protein folding. It may help identify disease stages, monitor progression, and assess treatments.
"Detecting markers of Alzheimer’s early is absolutely critical to developing effective therapeutics," Yates added. Larger studies are needed for clinical use, and the approach might apply to other conditions like Parkinson's and cancer.
Authors include Ahrum Son, Hyunsoo Kim, Jolene K. Diedrich, Heather M. Wilkins, Jeffrey M. Burns, Jill K. Morris, Robert A. Rissman, and Russell H. Swerdlow. The work was supported by National Institutes of Health grants.
