Role of plasma ptau181, neurofilament light, and subjective cognitive decline in predicting progression to MCI in older adults from the Alzheimer’s Disease Neuroimaging Initiative

Abstract

AbstractBackgroundAccurate identification of AD risk using non‐invasive biomarkers is a critical need. Recently plasma biomarkers of amyloid, phosphorylated tau, and neurodegeneration have been shown to accurately identify mild cognitive impairment (MCI), and brain amyloid levels. However, little is known about whether baseline plasma biomarker predict future progression from cognitively unimpaired (CN) to MCI. The overall goal of this study was to examine the predictive utility of markers that can easily be collected remotely.MethodWe identified a set of non‐invasive markers in ADNI: plasma p‐tau181 and neurofilament light (NfL), Neuropsychiatric Inventory Questionnaire (NPIQ), self‐ and study partner versions of a subjective cognitive decline instrument (Everyday Cognition Scale; Ecog), and APOE. In 300 ADNI participants who were CN at baseline, we determined the associations between these markers and progression to MCI using logistic regression. Models covaried for age, gender, and education level. Area under the receiver operator curve (AUC) evaluated discrimination accuracy. Likelihood ratio tests (LRT) determined the best fitting model.Result42 (14%) of participants progressed to MCI (Table 1). In the full model including all predictors (AUC = .879; Table 2 and Figure 1), study partner Ecog score was the only significant predictor associated with progression to MCI. Excluding study partner Ecog decreased model accuracy (AUC = .779; Figure 1). The LRT between this model and the full model was significant (c2(1) = 5.04, p < .05).ConclusionEven when accounting for the contributions of ptau181 and Nfl, study partner‐reported subjective cognitive decline independently predicts future progression to MCI. This approach can be used in the future to efficiently predict MCI risk without the need for in‐clinic assessment.