Combining Select Neuropsychological Assessment with Blood-Based Biomarkers to Detect Mild Alzheimer's Disease: A Molecular Neuropsychology Approach

Background: Current work has sought to establish a rapid and cost effective means of screening for Alzheimer's disease (AD) with the most recent findings showing utility of integrating blood-based biomarkers with cognitive measures. Objective: The current project sought to create a combined biomarker-cognitive profile to detect mild AD. Methods: Data was analyzed from 266 participants (129 AD cases [Early AD n = 93; Very Early AD n = 36]; 137 controls) enrolled in the Texas Alzheimer's Research and Care Consortium (TARCC). Non-fasting serum samples were collected from each participant and assayed via a multi-plex biomarker assay platform using electrochemiluminescence. Logistic Regression was utilized to detect early AD using two serum biomarkers (TNF alpha and IL7), demographic information (age), and one neuropsychological measure (Clock 4-point) as predictor variable. Disease severity was determined via Clinical Dementia Rating (CDR) scale global scores. Results: In the total sample (all levels of CDR scores), the combination of biomarkers, cognitive test score, and demographics yielded the obtained sensitivity (SN) of 0.94, specificity (SP) of 0.90, and an overall accuracy of 0.92. When examining early AD cases (i.e.m CDR = 0.5-1), the biomarker-cognitive profile yielded SN of 0.94, SP of 0.85, and an overall accuracy of 0.91. When restricted to very early AD cases (i.e., CDR = 0.5), the biomarker-cognitive profile yielded SN of 0.97 and SP of 0.72, with an overall accuracy of 0.91. Conclusions: The combination of demographics, two biomarkers, and one cognitive test created a biomarker-cognitive profile that was highly accurate in detecting the presence of AD, even in the very early stages.