Presenter of 3 Presentations
Which Alzheimer’s Disease diagnostic biomarkers may be useful in clinical practice in the future including a clinical case focusing on possible future practice
AN ACCURATE FULLY AUTOMATED PANEL OF PLASMA BIOMARKER ASSAYS FOR ALZHEIMER’S DISEASE
Abstract
Aims
To examine the accuracy of key Alzheimer’s disease (AD) plasma biomarkers for identifying β-amyloid (Aβ) and prediction of AD dementia using fully-automated assays.
Methods
Two independent cohorts (ntotal=926): PanelA+ (32 cognitively unimpaired [CU], 106 mild cognitively impaired [MCI], 89 AD participants); BioFINDER (463 CU and 236 MCI). Using novel plasma prototype Elecsys© immunoassays, Aβ42/Aβ40, two different phospho-tau217 variants (P-tau217-1 and P-tau217-2), apolipoproteinE-ε4 (ApoE4), neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) were analyzed. Accuracy for Aβ positivity (CSF Aβ42/Aβ40) and progression to AD dementia within 6 years was analyzed using the area under the curve (AUC).
Results
Plasma Aβ42/Aβ40 identified Aβ positivity with higher accuracy than previous Elecsys prototype assays (PanelA+ AUC 0.87 vs 0.80, p=0.009; BioFINDER 0.83 vs 0.78; p=0.03). Combining Aβ42/Aβ40, P-tau217-1 and ApoE4 improved the AUCs (PanelA+ 0.92, BioFINDER 0.89; p<0.01). Also including GFAP improved the model fit, but resulted in similar AUCs (PanelA+ 0.93, p=0.10; BioFINDER 0.90, p<0.01). Results were similar in CU/MCI subgroups and when using CSF P-tau/Aβ42 for Aβ status. Dichotomized plasma ApoE4 concentrations had 100% concordance with APOE-ε4 carrier status. In BioFINDER, P-tau217-1, P-tau217-2 and ApoE4 predicted AD dementia among CU participants with an AUC of 0.85. Among MCI participants, P-tau217-1, P-tau217-2 and Aβ42/Aβ40 had an AUC of 0.87.
Conclusions
Using fully-automated assays, a combination of biomarkers accurately identified Aβ positivity in two independent cohorts and predicted AD dementia. Future work will focus on evaluating the feasibility and diagnostic utility of these biomarkers for use in clinical practice and AD trials.
MINIMAL CLINICALLY IMPORTANT DIFFERENCES FOR COGNITIVE OUTCOMES IN PRECLINICAL AND PRODROMAL STAGES – IMPLICATIONS FOR CLINICAL AD TRIALS
Abstract
Aims
This study has two purposes: 1) to explore different estimates for minimal clinically important differences (MCID) for commonly used cognitive tests, using anchor and distribution-based approaches and 2) to investigate an optimal composite cognitive measure that best predicts a minimal change in Clinical Dementia Rating Sum of Boxes (CDR-SB).
Methods
From the Swedish BioFINDER study, we included 1) 451 cognitively unimpaired individuals (CU) and 2) 292 people with mild cognitive impairment (MCI). We calculated MCID associated with a change of 0.5-1.0 on CDR-SB for MMSE, ADAS-cog delayed recall 10-word list, A Quick Test of Cognitive Speed (AQT) Color and Form, Stroop, Letter S Fluency, Animal Fluency, Symbol Digit Modalities Test and Trailmaking Test (TMT) A and B. For investigating cognitive measures that predict a change in CDR-SB we conducted ROC analyses.
Results
We identified potential MCIDs for individuals with and without cognitive impairment on a range of cognitive test outcomes. For amyloid positive CU we found the best predicting composite cognitive measure was test changes in ADAS-cog delayed recall 10-word list, MMSE, symbol digit modalities test and TMT B, including gender in the model. This produced an AUC of 0.87 (95% CI 0.79-0.94; sensitivity 75%, specificity 88%).
Conclusions
We established MCIDs for commonly used cognitive tests. These may be applied in clinical practice or to identify treatment benefit in clinical trials of therapies for early AD. We also identified brief cognitive test batteries that most accurately estimates clinical meaningful cognitive changes in CU individuals and specifically in preclinical AD.