Summary: Current tests for Alzheimer’s disease focus on the amount of amyloid and tau proteins in the blood. However, a breakthrough study suggests we should be looking at their shape instead. Researchers discovered that as Alzheimer’s progresses, certain blood proteins “fold” differently, becoming less structurally “open.”
By tracking the structural signatures of three specific proteins (C1QA, Clusterin, and Apolipoprotein B), the team was able to distinguish between healthy individuals, those with mild cognitive impairment (MCI), and Alzheimer’s patients with up to 93% accuracy. This “proteostasis” approach offers a potential way to detect the disease earlier and track how well treatments are working in real-time.
Key Facts
- Shape Over Substance: The test measures structural changes (folding) in proteins rather than their concentration, providing a more precise look at early biological shifts.
- The “Closed” Trend: As the disease advances, proteins in the plasma become less structurally open, a signal that outperformed traditional protein-level measurements.
- Triple Threat Panel: Three specific proteins were identified as the most accurate markers: C1QA (immune signaling), Clusterin (amyloid clearance), and Apolipoprotein B (vessel health).
- High Accuracy: The structural model showed 93% accuracy in distinguishing healthy adults from those with Mild Cognitive Impairment (MCI).
- Tracking Progression: The structural score correlated strongly with cognitive test scores and brain atrophy measured by MRI, making it a reliable tool for longitudinal tracking.
Source: Scripps Research Institute
Alzheimer’s disease affects an estimated 7.2 million Americans age 65 and older, according to the Alzheimer’s Association. Current tests often measure the levels of two proteins—amyloid beta (Aβ) and phosphorylated tau (p-tau)—in the blood or spinal fluid, but these markers may not fully capture earlier biological changes linked to disease progression.
Now, scientists at Scripps Research have developed a blood-based approach that examines how proteins are folded in the bloodstream rather than simply measuring their concentrations.
Their study, published in Nature Aging on February 27, 2026, reports that structural differences in three plasma proteins are associated with disease status and can distinguish cognitively normal individuals from those with Alzheimer’s and mild cognitive impairment (MCI) with high accuracy. The new test could help move diagnosis and intervention to an earlier stage.
“Many neurodegenerative diseases are driven by changes in protein structure,” says senior author John Yates, a professor at Scripps Research. “The question was, are there structural changes in specific proteins that might be useful as predictive markers?”
Alzheimer’s has long been associated with amyloid plaques and tau tangles in the brain. But growing evidence suggests the disease reflects a broader breakdown in proteostasis, the system that keeps proteins properly folded and removes damaged ones.
As this system declines with age, proteins become more prone to misfolding as they are produced and maintained. The researchers hypothesized that if proteostasis is disrupted in the brain, similar structural alterations might also appear in proteins circulating in the blood.
To test whether structural changes in blood proteins could serve as disease markers, the team analyzed plasma samples from 520 people across three groups: cognitively normal adults, individuals with mild cognitive impairment and patients diagnosed with Alzheimer’s.
Using mass spectrometry, the researchers measured how exposed or buried specific protein sites were—an indicator of structural change—and used machine-learning algorithms to identify patterns associated with disease stage.
The results revealed a consistent trend across all patient groups: as Alzheimer’s progressed, certain blood proteins became less structurally “open.” These structural changes provided a stronger signal for distinguishing disease stage than measuring protein levels alone.
Among hundreds of candidates, three proteins stood out: C1QA, involved in immune signaling; clusterin, associated with protein folding and amyloid clearance; and apolipoprotein B, which helps transport fats in the bloodstream and plays a role in blood vessel health.
“The correlation was amazing,” says 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.”
Structural differences at specific sites within these proteins enabled the researchers to classify individuals as cognitively normal, MCI or Alzheimer’s with approximately 83% overall accuracy. In two-way comparisons, such as distinguishing healthy individuals from those with MCI, accuracy exceeded 93%.
The three-marker model performed consistently across independent cohorts and remained accurate when tested on follow-up samples months later. In repeat blood samples collected months apart, the panel classified disease status with about 86% accuracy and reflected changes in diagnostic status over time. The structural score also correlated strongly with cognitive test scores and more moderately with MRI measures of brain atrophy.
Together, the findings suggest that measuring protein structure in blood could provide complementary information to existing amyloid and tau tests. By targeting structural changes linked to underlying disease biology, this could help distinguish disease stages, track progression and measure whether treatments are effective.
“Detecting markers of Alzheimer’s early is absolutely critical to developing effective therapeutics,” says Yates. “If treatment can start before significant damage has been done, it may be possible to better preserve long-term memory.”
The new blood test will require larger validation studies with longer follow-up periods before it’s ready for clinical use. The researchers are also exploring whether the same structural profiling approach could be applied to other diseases, such as Parkinson’s and cancer.
Funding: Support for this study was provided by the National Institutes of Health (grants RF1AG061846-01, 5R01AG075862, P30AG072973 and P30-AG066530).
Key Questions Answered:
A: Think of proteins like origami. To do their job, they have to be folded into a very specific shape. In Alzheimer’s, the body’s “folding system” starts to break down. Even if you have the right amount of protein, if it’s folded into the wrong shape, it can’t function—and it might even become toxic.
A: Potentially. Because the test picks up on the breakdown of “proteostasis” (the folding system), it may detect the very first warning signs before amyloid plaques even start to build up. In the study, it was incredibly accurate at identifying people with “Mild Cognitive Impairment,” which is often the precursor to Alzheimer’s.
A: While GLP-1 drugs are showing promise in treating neurodegeneration, this Scripps research is about detecting it. This blood test could eventually be used to see if drugs like GLP-1 analogs are actually working by checking if they help your proteins return to their healthy, “open” shapes.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- Journal paper reviewed in full.
- Additional context added by our staff.
About this Alzheimer’s disease research news
Author: Press Office
Source: Scripps Research Institute
Contact: Press Office – Scripps Research Institute
Image: The image is credited to Neuroscience News
Original Research: Open access.
“Structural signature of plasma proteins classifies the status of Alzheimer’s disease” by Ahrum Son, Hyunsoo Kim, Jolene K. Diedrich, Casimir Bamberger, Heather M. Wilkins, Jeffrey M. Burns, Jill K. Morris, Robert A. Rissman, Russell H. Swerdlow & John R. Yates III. Nature Aging
DOI:10.1038/s43587-026-01078-2
Abstract
Structural signature of plasma proteins classifies the status of Alzheimer’s disease
Alzheimer’s disease (AD) involves proteostasis dysregulation causing protein misfolding, but whether these structural changes manifest as plasma conformational biomarkers remains unclear.
We profiled plasma protein structures from 520 participants including individuals with AD, individuals with mild cognitive impairment (MCI) and healthy controls. Using mass spectrometry and machine learning, we systematically characterized the structural proteome changes associated with ApoE variations and neuropsychiatric symptoms to identify AD-specific signatures.
We developed a diagnostic panel using peptides from C1QA, CLUS and ApoB representing AD-associated structural changes. This three-marker panel achieved 83.44% accuracy in three-way classification (healthy versus MCI versus AD). Binary classification yielded area under the receiver operating characteristic curves of 0.9343 for healthy versus MCI and 0.9325 for MCI versus AD.
Longitudinal samples were classified with 86.0% accuracy. This multi-marker panel based on plasma protein structural alterations represents a promising diagnostic approach that may enhance early AD detection and provide insights for clinical trials, improving therapeutic outcomes.
