Our team has been a pioneer in harvesting extracellular vesicles (EVs) enriched for neuronal origin from peripheral blood and using them as a biomarker discovery platform for neurological disorders. This methodology has demonstrated excellent diagnostic and predictive performance for Alzheimer's and other neurodegenerative diseases in multiple studies, providing a strong proof of concept for this approach. Here, we describe our methodology in detail and offer further evidence that isolated EVs are enriched for neuronal origin. In addition, we present evidence that EVs enriched for neuronal origin represent a more sensitive and accurate base for biomarkers than plasma, serum, or non-enriched total plasma EVs. Finally, we proceed to investigate the protein content of EVs enriched for neuronal origin and compare it with other relevant enriched and non-enriched populations of plasma EVs. Neuronal-origin enriched plasma EVs contain higher levels of signaling molecules of great interest for cellular metabolism, survival, and repair, which may be useful as biomarkers and to follow response to therapeutic interventions in a mechanism-specific manner.

IMPORTANCE Blood biomarkers able to diagnose Alzheimer disease (AD) at the preclinical stage would enable trial enrollment when the disease is potentially reversible. Plasma neuronal-enriched extracellular vesicles (nEVs) of patients with AD were reported to exhibit elevated levels of phosphorylated (p) tau, Aβ42, and phosphorylated insulin receptor substrate 1 (IRS-1). OBJECTIVE To validate nEV biomarkers as AD predictors. DESIGN, SETTING, PARTICIPANTS This case-control study included longitudinal plasma samples from cognitively normal participants in the Baltimore Longitudinal Study of Aging (BLSA) cohort who developed AD up to January 2015 and age-and sex-matched controls who remained cognitively normal over a similar length of follow-up. Repeated samples were blindly analyzed over 1 year from participants with clinical AD and controls from the Johns Hopkins Alzheimer Disease Research Center (JHADRC). Data were collected from September 2016 to January 2018. Analyses were conducted in March 2019. MAIN OUTCOMES AND MEASURES Neuronal-enriched extracellular vesicles were immunoprecipitated; tau, Aβ42, and IRS-1 biomarkers were quantified by immunoassays; and nEV concentration and diameter were determined by nanoparticle tracking analysis. Levels and longitudinal trajectories of nEV biomarkers between participants with future AD and control participants were compared. RESULTS Overall, 887 longitudinal plasma samples from 128 BLSA participants who eventually developed AD and 222 age and sex-matched controls who remained cognitively normal were analyzed. Participants were followed up (from earliest sample to AD symptom onset) for a mean (SD) of 3.5 (2.31) years (range, 0-9.73 years). Overall, 161 participants were included in the training set, and 80 were in the test set. Participants in the BLSA cohort with future AD (mean [SD] age, 79.09 [7.02] years; 68 women [53.13%]) had longitudinally higher p-tau181, p-tau231, pSer312-IRS-1, pY-IRS-1, and nEV diameter than controls (mean [SD] age, 76.2 [7.36] years; 110 women [50.45%]) but had similar Aβ42, total tau, TSG101, and nEV concentration. In the training BLSA set, a model combining preclinical longitudinal data achieved 89.6% area under curve (AUC), 81.8% sensitivity, and 85.8% specificity for predicting AD. The model was validated in the test BLSA set (80% AUC, 55.6% sensitivity, 88.7% specificity). Preclinical levels of nEV xbiomarkers were associated with cognitive performance. In addition, 128 repeated samples over 1 year from 64 JHADRC participants with clinical AD and controls were analyzed. In the JHADRC cohort (35 participants with AD: mean [SD] age, 74.03 [8.73] years; 18 women [51.43%] and 29 controls: mean [SD] age, 72.14 [7.86] years; 23 women [79.31%]), nEV biomarkers achieved discrimination with 98.9% AUC, 100% sensitivity, and 94.7% specificity in the training set and 76.7% AUC, 91.7% sensitivity, and 60% specificity in the test set. CONCLUSIONS AND RELEVANCE We validated nEV biomarker candidates and further demonstrated that their preclinical longitud...