Mar 13, 2026
3 min read
Researchers discover protein patterns that track the progression of Alzheimer's disease
New research findings show that changes in the shape of proteins — rather than the amount of proteins — offer a potential new way to detect and track Alzheimer's disease.
March 09, 2026
LA JOLLA, CA—Alzheimer's disease affects approximately 7.2 million Americans age 65 and older.According to the Alzheimer's Association, current tests usually measure the levels of two proteins, amyloid beta (Aβ) and phosphorylated tau (p-tau), in the blood or cerebrospinal fluid. But these markers may not fully capture the previous biological changes associated with the development of the disease.
Now, research scientists have developed a blood-based method that examines how proteins are folded instead of measuring their levels in the bloodstream.Their study, published in Nature Aging on February 27, 2026, shows that structural differences in three plasma proteins are associated with disease states and can distinguish mentally normal individuals from Alzheimer's disease and mild cognitive impairment (MCI) patients with high accuracy.New tests can help with early diagnosis and intervention for early stages.
"Many neurodegenerative diseases are driven by changes in protein structure," said senior author John Yates, a professor at Research."The question is, are there structural changes in certain proteins that could be useful as predictive markers?"
Alzheimer's has long been associated with amyloid plaques and tau knots in the brain.But growing evidence suggests that the disease reflects a widespread malfunction of proteostasis, the system that keeps proteins properly folded and removes damaged ones.
As this system declines with age, proteins become more vulnerable to degradation as they are produced and stored.The researchers hypothesized that if proteostasis in the brain is disrupted, proteins circulating in the blood may show similar structural changes.
To test whether structural changes in blood proteins can serve as markers of disease, the team analyzed plasma samples from 520 people in three groups: cognitively normal adults, individuals with mild cognitive impairment, and patients diagnosed with Alzheimer's disease.Using mass spectrometry, the researchers measured how exposed or hidden specific protein sites - an indicator of structural changes - were and used machine learning algorithms to identify patterns associated with the stage of the disease.
The results revealed a consistent trend in all patient groups: as Alzheimer's progressed, some blood proteins became less structurally "open".These structural changes provide a stronger signal to distinguish the stage of the disease than measuring protein levels alone.
Among hundreds of candidates, three proteins stood out: C1QA, involved in immune signaling;clusterin, involved in protein folding and amyloid clearance;and apolipoprotein B, which helps carry fat in the bloodstream and plays a role in blood vessel health.
"The relationship was significant," said co-author Casimir Bamberger, the study's senior researcher."Finding three lysine sites in three different proteins is highly correlated with disease state."
Structural differences in specific protein locations allowed the researchers to classify individuals as cognitively normal, MCI, or Alzheimer's disease with an overall accuracy of about 83%.In two-way comparisons, for example, discriminating between healthy individuals and those with MCI, accuracy exceeded 93%.
The three-marker model performed consistently in independent cohorts and remained accurate when tested on follow-up samples several months later.In blood samples collected over several months, the panel classified disease status with approximately 86% accuracy and reflected changes in diagnostic status over time.The structural score also correlated strongly with cognitive test scores and moderately with MRI measures of brain atrophy.
Together, the results suggest that measuring blood protein composition could provide complementary information to existing amyloid and tau tests.By targeting the structural changes associated with the biology of the underlying disease, it could help differentiate disease stages, monitor progression, and measure whether treatments are effective.
"Recognizing the early signs of Alzheimer's disease is critical for effective treatment," says Yates.
The new blood test will require extensive training and follow-up periods before it is ready for clinical use.Researchers are also investigating whether the same method can be used for other diseases, such as Parkinson's disease and cancer.
In addition to Yates and Bamberg, authors of the "Structural Signature of Plasma Proteins Classifies Alzheimer's Disease Status" study include Ahram Son, Hyunso Kim and researcher Jolin K. Diedrich;Heather M. Wilkins, Jeffrey M. Burns, Jill K. Morris, and Russell H. Swerdlow of the Medical University of Kansas;and Robert A. of the University of California, San Diego.
This research was supported by the National Institutes of Health (grants RF1AG061846-01, 5R01AG075862, P30AG072973, and P30-AG066530).
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