New Blood Test Detects Alzheimer’s Biomarkers & Reveals Gender Differences
A new blood test capable of detecting structural changes in proteins associated with Alzheimer’s disease has been developed by researchers funded by the National Institutes of Health (NIH). The test, detailed in a study published Friday in Nature Aging, offers a potentially earlier and more informative method of diagnosis than existing blood-based biomarkers.
The research, led by scientists at Scripps Research Institute and utilizing data from Alzheimer’s Disease Research Centers in Kansas and California, focuses on identifying alterations in protein structure, a hallmark of Alzheimer’s pathology often missed by conventional tests that measure only the amount of specific proteins present. “This work introduces a fundamentally new, blood-based approach to detecting and staging Alzheimer’s disease,” said Dr. Richard Hodes, director of the National Institute on Aging (NIA), which funded the study.
Current Alzheimer’s blood tests typically quantify the levels of proteins linked to the disease. However, researchers have long understood that the disease process involves protein misfolding caused by a breakdown in cellular regulation. The study hypothesized that analyzing these structural changes could reveal more about the underlying mechanisms of the disease and potentially identify new biomarkers. Researchers analyzed plasma samples from 520 participants, including individuals with diagnosed Alzheimer’s, those with mild cognitive impairment, and healthy controls, all of whom were participating in ongoing research.
Using mass spectrometry and machine learning, the team was able to characterize protein structural changes associated with genetic risk factors for Alzheimer’s, particularly variations in the ApoE gene. They too found correlations between these changes and the severity of neuropsychiatric symptoms, observing distinct structural patterns between males and females. This finding builds on existing research highlighting potential sex-based differences in the manifestation of Alzheimer’s disease.
The researchers then employed machine learning to create a diagnostic panel based on three proteins – C1QA, CLUS, and ApoB – that reflect the structural alterations associated with Alzheimer’s. This panel demonstrated a high degree of accuracy in distinguishing between Alzheimer’s disease, mild cognitive impairment, and healthy controls, and in tracking the progression of the disease over time.
“With this work, we have created a potential new panel of biomarkers that reveals structural alterations in proteins linked to Alzheimer’s disease, invisible to traditional approaches,” said John Yates, the study’s lead author and a professor of Integrative Structural and Computational Biology at Scripps Research Institute. “This approach accurately distinguishes stages of the disease, which could contribute to earlier diagnosis.”
The NIH has identified Alzheimer’s and related dementias as a significant public health challenge, estimating that 7.1 million Americans currently live with the disease, a number projected to rise to over 13.9 million by 2060. The development of this new biomarker test aligns with a broader effort to incorporate biomarker-guided diagnostics into clinical care pathways, as outlined in recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines. Further research is needed to validate these findings in larger, more diverse populations and to determine the test’s clinical utility in routine diagnostic settings.