Biomarkers.

Background: With the emergence of anti-amyloid drugs, there is an increased need to determine the presence of brain amyloid in people using non-invasive, cost-effective biomarkers. The goal of this study was to determine the added and stand-alone value of plasma biomarkers for predicting positive amyloid PET in a mixed sample of Hispanic and non-Hispanic older adults.

Method: Participants (n=209) from the 1Florida ADRC at Mount Sinai Medical Center, Miami Beach had neurological and neuropsychological evaluations; MRI, rated positive (Hpc+) or negative (Hpc-) for hippocampal atrophy on visual read; amyloid PET brain scans, rated amyloid positive (A+) or negative (A-) on visual read; blood draws for APOE ε4 genotyping (e4+, e4-); and plasma biomarkers including Abeta 42/40 ratio (Quest Diagnostics), p-tau217 (ALZPath), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) (Quanterix). A base logistic regression model including age, sex, APOEε4 status, and hippocampal atrophy was a reference to assess the value of adding plasma markers in predicting A+/A-. Areas under the receiver operating characteristic (ROC) were computed and DeLong's approach was used to compare ROC curves. Youden's index was used to identify optimal sensitivities/specificities to discriminate A+ from A- participants.

Result: Demographics and clinical data are shown in Table 1. In the base model, the AUC was 0.78 with both APOEe4 and hippocampal atrophy as significant independent predictors of A+ (Table 2). Prediction of A+ was improved by adding all plasma biomarkers (AUC=0.96; 93%/87% sensitivity/specificity), with APOEe4, Abeta42/40, and p-tau217 as independent predictors. Adding either Abeta 42/40 (AUC=0.88) or p-tau217 (AUC=0.94) alone to the base model also improved model prediction. As stand-alone predictors of A+, the optimal specific/sensitivity was 85%/89% for p-tau217 and 77%/81% for Abeta42/40; p-tau217 outperformed Abeta42/40 (AUC=0.92 versus 0.82) (Figure 1). There was a trend for the combination of both biomarkers to outperform p-tau217 alone (AUC=0.94 versus 0.92).

Conclusion: Positive amyloid PET status can be predicted with high accuracy in an ethnically diverse population using combinations of biomarkers, APOE genotype, and a measure of hippocampal atrophy. As a stand-alone biomarker, p-tau217 performed better than other biomarkers in predicting amyloid status.