Blood-Based Circular RNAs Enable Early and Accurate Alzheimer’s Disease Diagnosis

Detection of Alzheimer’s disease (AD) prior to the development of clinical symptoms is critical due to new treatments for symptomatic AD. Circular RNAs (circRNAs) are highly stable non-coding RNAs enriched in brain that can cross the blood-brain-barrier and are associated with AD. Using two large and independent whole-blood transcriptomic datasets, we identified 34 circRNAs associated with clinical AD status. A single-cutoff predictive model including these 34 circRNAs was comparable to plasma pTau217 in classifying AD based on clinical or AT status, that replicated in the independent dataset. The circRNAs (Hazard Ratio (HR): 2.92) outperformed pTau217 (HR: 1.81) and amyloid-PET when predicting progression to symptomatic AD. CircRNA levels began diverging 4–8 years before symptom onset, enabling preclinical risk stratification. The circRNA model was specific for AD showing low predictive power for PD, DLB, and FTD. These results establish blood circRNAs as robust biomarkers in AD diagnosis and disease progression.