Alzheimer’s disease (AD), due to its multifactorial nature and complex etiology, poses challenges for research, diagnosis, and treatment, and impacts millions worldwide. To address the need for minimally invasive, repeatable measures that aid in AD diagnosis and progression monitoring, studies leveraging RNAs associated with extracellular vesicles (EVs) in human biofluids have revealed AD-associated changes. However, the validation of AD biomarkers has suffered from the collection of samples from differing points in the disease time course or a lack of confirmed AD diagnoses. Here, we integrate clinical diagnosis and postmortem pathology data to form more accurate experimental groups and use small RNA sequencing to show that EVs from plasma can serve as a potential source of RNAs that reflect disease-related changes. Importantly, we demonstrated that these changes are identifiable in the EVs of preclinical patients, years before symptom manifestation, and that machine learning models based on differentially expressed RNAs can help predict disease conversion or progression. This research offers critical insight into early disease biomarkers and underscores the significance of accounting for disease progression and pathology in human AD studies.

Epstein–Barr virus (EBV) infection is nearly ubiquitous and strongly linked to multiple sclerosis (MS), but how EBV-infected B cells communicate with distal tissues remains unclear. We performed an integrated multiomic characterization of small extracellular vesicles (sEVs) released from spontaneous lymphoblastoid cell lines (SLCLs) derived from healthy donors and patients with MS, transformed ex vivo by endogenous wild-type EBV. Proteomics identified over 6,000 shared proteins enriched in nucleic acid–binding and chromatin-associated factors. EV-associated DNA resolved into two structurally distinct compartments: DNase-sensitive, high–molecular weight DNA associated with the vesicle corona and DNase-resistant, nucleosome-sized (∼130–150 bp) DNA. Both compartments were overwhelmingly host-derived and broadly genomically distributed, whereas EBV DNA was minimal. In contrast, viral RNA cargo was dominated by the EBV noncoding RNA EBER1, which was strikingly enriched across all lines and confirmed within individual vesicles by ddPCR and super-resolution microscopy. EBER1 has previously been detected in MS brain tissue, yet its route to the CNS has remained unexplained. Our findings identify sEVs as a plausible vehicle for disseminating this immunostimulatory viral ncRNA beyond sites of latency, pointing to EV-mediated export of EBER1 as a candidate mechanism linking peripheral EBV infection to distal tissue signaling in MS and beyond.