Abstract
AbstractBackgroundNon‐invasive methods for detecting neurofibrillary tangles that spread throughout the brain are needed for efficiently screening patients in Alzheimer’s disease (AD) clinical trials. This can be accomplished via machine‐learning models using baseline clinical characteristics. Adding plasma pTau181 and brain region volumes may improve detection accuracy.MethodRegional MK6240 Tau‐PET SUVR data were available for 312 Amyloid‐positive patients from a clinical trial (182 MCI, 130 mild AD, 131 Tau‐negative, 181 Tau‐positive). Over 90% of the Tau‐positive subjects were in Braak 3‐6. Plasma pTau181 was measured using Simoa assay. Data were split randomly into 70%‐30% for training and testing purposes. Tau positivity for each Braak stage was defined via the one‐sided upper 99% confidence limit of a subset of 70 subjects with background SUVR.Signatures for detecting Tau positivity in Braak 3‐6 and for further discriminating Braak 3‐4 and 5‐6 were derived via the stochastic gradient boosting algorithm and Bayesian ordinal logistic regression respectively. Demographics (age, gender, BMI), ApoE4 status, and cognitive assessments were included, and the added value of plasma pTau181 and volumetric MRI measures were assessed. Prediction performance was assessed via 10‐fold cross‐validation in the training set followed by evaluation in the test set.ResultSignatures comprising psychometric data, ApoE4 status, and demographics achieved 76% accuracy (ROC AUC = 80.4%) for detecting Tau positivity in Braak 3‐6, and 60.8% accuracy for discriminating Braak 3‐4 versus 5‐6. Adding plasma pTau181 significantly improved the accuracy to 82.2% (ROC AUC = 86.6%, p<0.05) in Braak 3‐6, and to 67.6% accuracy (p<0.05) for Braak 3‐4 versus 5‐6. Besides plasma pTau181, key predictors were delayed word recall, ADAS‐cog‐14, BMI, CDR‐SB, and ApoE4 genotype.Detection accuracy of Tau positivity in Braak 3‐4 versus the spread to Braak 5‐6 improved significantly from 67.6% to 74.6% (p<0.05) when combining MRI data with plasma pTau181, ApoE4, and demographics. Key MRI predictors were the thickness and volume of the inferior parietal cortex. Adding cognitive assessments did not improve the detection accuracy.ConclusionThese results demonstrate the potential of non‐invasive investigations such as plasma pTau181, cognitive performance, and MRI data for detecting Tau deposition throughout the brain along the Braak stages.
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