A new blood test capable of detecting biomarkers for Alzheimer’s disease has been identified through research funded by the National Institutes of Health (NIH). The test measures structural changes in proteins, offering more detailed information than standard examinations.
The findings, published in Nature Aging on February 28, 2026, also shed light on how the biology of Alzheimer’s may differ between men and women. Early and accurate diagnosis is crucial for managing the progression of Alzheimer’s and improving patient care.
“This work introduces a fundamentally new, blood-based approach to the diagnosis and staging of Alzheimer’s,” explained Richard Hodes, director of the National Institute on Aging (NIA), an institute within the NIH, which funded the study. “By revealing structural changes in proteins associated with genetic risk, symptom severity and sex differences – characteristics not detected by existing biomarkers – this research could enable earlier diagnosis and more effective clinical trials.”
Most current blood tests for Alzheimer’s measure the amount of a protein associated with the disease. However, researchers know that dysfunction in cellular regulation during Alzheimer’s causes abnormal protein folding. The study’s researchers aimed to determine if these structural changes could be identified in blood tests to aid in diagnosis.
They hypothesized that a comprehensive investigation of structural changes in Alzheimer’s-associated proteins could reveal more information about the mechanisms underlying risk factors and symptoms than current blood tests, and potentially identify additional blood-based biomarkers.
Nearly all Alzheimer’s patients develop neuropsychiatric symptoms, but research suggests differences between men and women in the frequency and severity of some symptoms. The researchers wondered if structural changes in proteins could help understand the biological processes behind these gender differences.
To investigate, the team analyzed plasma samples from 520 individuals, including those with diagnosed Alzheimer’s, individuals with mild cognitive impairment, and healthy controls. Participants were volunteers involved in research at Alzheimer’s Disease Research Centers in Kansas and California, where they received annual check-ups.
Using mass spectrometry and machine learning, researchers were able to characterize changes in protein structure associated with the genetic risk of Alzheimer’s, particularly variants of the ApoE gene. They also linked disease-related changes to the severity of neuropsychiatric symptoms in men and women, observing distinct structural patterns based on sex.
The research team then used machine learning to develop a diagnostic panel of three proteins – C1QA, CLUS, and ApoB – representing structural changes associated with Alzheimer’s. They found the panel accurately distinguished between Alzheimer’s, mild cognitive impairment, and healthy controls, and could differentiate stages of the disease and monitor its progression over time.
“With this work, we have created a potential new biomarker panel that reveals structural alterations in proteins linked to Alzheimer’s disease, invisible to traditional approaches,” concluded John Yates, lead author of the study and a professor of Integrative Structural and Computational Biology at the Scripps Research Institute in La Jolla, California. “This approach accurately distinguishes disease stages, which could contribute to earlier diagnosis.”
