ABSTRACT
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, Aß42, 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, Aß42, 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 Aß42, 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 biomarkers 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 longitudinal trajectories can predict AD diagnosis. These findings motivate further development of nEV biomarkers toward a clinical blood test for AD.
ABSTRACT
Current hypotheses and theories regarding the pathogenesis of Alzheimer's disease (AD) heavily implicate brain insulin resistance (IR) as a key factor. Despite the many well-validated metrics for systemic IR, the absence of biomarkers for brain-specific IR represents a translational gap that has hindered its study in living humans. In our lab, we have been working to develop biomarkers that reflect the common mechanisms of brain IR and AD that may be used to follow their engagement by experimental treatments. We present two promising biomarkers for brain IR in AD: insulin cascade mediators probed in extracellular vesicles (EVs) enriched for neuronal origin, and two-dimensional magnetic resonance spectroscopy (MRS) measures of brain glucose. As further evidence for a fundamental link between brain IR and AD, we provide a novel analysis demonstrating the close spatial correlation between brain expression of genes implicated in IR (using Allen Human Brain Atlas data) and tau and beta-amyloid pathologies. We proceed to propose the bold hypotheses that baseline differences in the metabolic reliance on glycolysis, and the expression of glucose transporters (GLUT) and insulin signaling genes determine the vulnerability of different brain regions to Tau and/or Amyloid beta (Aß) pathology, and that IR is a critical link between these two pathologies that define AD. Lastly, we provide an overview of ongoing clinical trials that target IR as an angle to treat AD, and suggest how biomarkers may be used to evaluate treatment efficacy and target engagement.
