Can a Tube of Blood Read Dementia Risk Earlier? Circular RNA Offers Another Clue for Alzheimer’s Diagnosis

The hardest part of Alzheimer’s disease is often not the name of the disease itself, but the fact that diagnosis comes too late. By the time changes in memory, language, and daily function become obvious, pathology in the brain has usually been accumulating for years. As anti-amyloid drugs gradually enter clinical use, who can be identified earlier and more accurately is no longer just a research question, but a real pressure that health systems are about to face.

A study published in *Nature Medicine* focuses on circular RNA in blood. The research team identified 34 blood circular RNAs associated with Alzheimer’s disease and used them to build a predictive model, attempting to distinguish biomarker-supported Alzheimer’s disease cases from control groups, while also evaluating their potential to predict disease progression.

Circular RNAs are a class of RNA molecules that form closed-loop structures. They were once regarded as peripheral signals in biology, but recent studies suggest they may participate in gene regulation, cellular stress responses, and neurodegenerative processes. If these molecules can reflect pathological changes in the brain through blood, they could become a less invasive testing material that is easier to monitor repeatedly.

According to the study abstract, this circular RNA model has been tested in a large discovery cohort and replication cohorts, with good classification performance for biomarker-confirmed Alzheimer’s disease. More importantly, when the model was combined with plasma pTau217, which is currently receiving considerable attention, the overall AUC was higher than that of pTau217 alone, suggesting the two may capture partly complementary disease signals.

This does not mean that a blood test can already replace clinical diagnosis, brain imaging, or cerebrospinal fluid testing. AUC is a statistical measure of a model’s discriminatory ability and does not directly equate to usability in real outpatient settings. Differences in age, comorbidities, population background, blood collection, and testing workflows may all affect results. Especially when symptoms are still mild or have not yet appeared, false positives and false negatives can trigger cascading consequences across psychological, medical, and insurance dimensions.

The study itself also notes that prospective validation remains a necessary step. The key in the next stage is to follow populations that more closely resemble clinical practice: whether these circular RNA signals can predict who will move from subjective cognitive decline to mild cognitive impairment, or from mild cognitive impairment to dementia; and whether the model remains stable across different laboratories and different testing platforms.

If subsequent evidence holds up, circular RNA may not become a single answer, but is more likely to join a layered toolbox: using blood markers first to lower the screening threshold, then arranging more detailed examinations and treatment assessments according to risk level. Alzheimer’s diagnosis is moving from “naming the disease after symptoms appear” toward “positioning risk along a pathological trajectory.” The significance of this study lies in being a new signal within that transition.