An RNA biomarker panel for the diagnosis of alzheimer’s disease from whole blood

Alzheimer’s Disease (AD) diagnosis remains primarily clinical, relying on patient history, cognitive tests, and sometimes brain imaging. Emerging approaches include advanced neuroimaging techniques and the use of protein biomarkers in cerebrospinal fluid and plasma. However, these methods have limitations such as high costs and the need for specialized infrastructures. In contrast, analysis of RNA expression in blood samples could be achieved with a high degree of sensitivity and accuracy in point of care settings, providing an ideal platform for a timely and accurate AD diagnosis. Peripheral blood samples from 50 AD patients and 50 healthy subjects were analyzed utilizing a whole transcriptome RNA sequencing approach to determine differences in the expression of (i) mRNAs, (ii) lncRNAs, (iii) miRNAs, (iv) circRNAs and (v) alternatively spliced mRNA isoforms. Multiple parallel analysis pipelines were utilized to identify a set of putative RNA biomarkers. A two-step validation assay was utilized to identify differentially expressed transcripts and form an AD RNA biomarker panel. The final Alzheimer’s disease (AD) panel includes only mRNAs, as non-coding RNAs lacked sufficient robustness in whole blood for clinical translation under our criteria. Expression levels of the four selected RNA biomarkers in each AD patient were compared with those in healthy controls to calculate an AD predictive score (ADps), achieving a positive predictive value above 90% and specificity exceeding 95%. The four RNA biomarkers can reliably identify Alzheimer’s disease (AD) patients using a small amount of peripheral blood and show strong potential as a minimally invasive, cost-effective tool for early diagnosis. However, their predictive accuracy and discriminative power may be more precisely established through analysis of a larger, well-defined AD cohort.