Study Finds 34 Blood RNAs Predict Alzheimer’s With 0.945 Accuracy, Beating pTau217
Updated
Updated · Nature.com · Jul 1
Study Finds 34 Blood RNAs Predict Alzheimer’s With 0.945 Accuracy, Beating pTau217
3 articles · Updated · Nature.com · Jul 1
Summary
Blood data from 1,221 people identified 34 circular RNAs linked to Alzheimer’s, and a model using them classified biomarker-confirmed disease with an AUC of 0.945 versus 0.877 for plasma pTau217.
Combining the circRNA panel with pTau217 pushed diagnostic accuracy to an AUC of 0.977, while the signal showed low predictive power for Parkinson’s, frontotemporal dementia and other neurodegenerative diseases.
In progression tracking, the circRNA model predicted conversion to symptomatic Alzheimer’s better than pTau217 alone, with a hazard ratio of 2.92 versus 1.81 and a 5-year progression AUC of 0.870 versus 0.676.
Independent replication supported the findings in a 551-person Knight-ADRC cohort and a 1,767-person A4 cohort, with circRNA changes appearing about 2 to 4 years before symptom onset.
The study suggests a noninvasive blood test could help detect Alzheimer’s earlier and monitor disease beyond amyloid-focused markers, though researchers said larger prospective validation is still needed.
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New Blood Test Using circRNAs Offers 0.945 AUC for Early, Accurate Alzheimer’s Detection
Overview
A groundbreaking study published in Nature Medicine on July 1, 2026, introduces a new way to predict Alzheimer’s disease using blood-based circular RNAs (circRNAs). Led by Phillips, Sanford, Janve, and colleagues, the research identifies specific circRNAs as reliable biomarkers for early detection of Alzheimer’s. This discovery marks a major shift toward less invasive and more accessible diagnosis compared to current brain imaging or spinal fluid tests. The new approach promises to transform how Alzheimer’s is identified and managed, opening the door to earlier intervention and improved patient outcomes.