Added value of inflammatory plasma biomarkers to pathologic biomarkers in predicting preclinical Alzheimer's disease

Background: Plasma biomarkers have recently emerged for the diagnosis, assessment, and disease monitoring of Alzheimer's disease (AD), but have yet to be fully validated in preclinical AD. In addition to AD pathologic plasma biomarkers (amyloid-beta (A beta) and phosphorylated tau (p-tau) species), a proteomic panel can discriminate between symptomatic AD and cognitively unimpaired older adults in a dementia clinic population. Objective: Examine the added value of a plasma proteomic panel, validated in symptomatic AD, over standard AD pathologic plasma biomarkers and demographic and genetic (apolipoprotein (APOE) epsilon 4 status) risk factors in detecting preclinical AD. Methods: 125 cognitively unimpaired older adults (mean age = 66 years) who completed A beta PET and plasma draw were analyzed using multiple regression with A beta PET status (positive versus negative) as the outcome to determine the best fit for predicting preclinical AD. Model 1 included age, education, and gender. Model 2 and 3 added predictors APOE epsilon 4 status (carrier versus non-carrier) and AD pathologic blood biomarkers (A beta 42/40 ratio, p-tau181), respectively. Random forest modeling established the 5 proteomic markers from the proteomic panel that best predicted A beta PET status, and these markers were added in Model 4. Results: The best model for predicting A beta PET status included age, years of education, APOE epsilon 4 status, A beta 42/40 ratio, and p-tau181. Adding the top 5 proteomic markers did not significantly improve the model. Conclusions: Proteomic markers in plasma did not add predictive value to standard AD pathologic plasma biomarkers in predicting preclinical AD in this sample.