Preclinical Alzheimer's disease biomarkers accurately predict cognitive and neuropathological outcomes

Abstract

Alzheimer's disease biomarkers are widely accepted as surrogate markers of underlying neuropathological changes. However, few studies have evaluated whether preclinical Alzheimer's disease biomarkers predict Alzheimer's neuropathology at autopsy. We sought to determine whether amyloid PET imaging or CSF biomarkers accurately predict cognitive outcomes and Alzheimer's disease neuropathological findings. This study included 720 participants, 42-91 years of age, who were enrolled in longitudinal studies of memory and aging in the Washington University Knight Alzheimer Disease Research Center and were cognitively normal at baseline, underwent amyloid PET imaging and/or CSF collection within 1 year of baseline clinical assessment, and had subsequent clinical follow-up. Cognitive status was assessed longitudinally by Clinical Dementia Rating®. Biomarker status was assessed using predefined cut-offs for amyloid PET imaging or CSF p-tau181/amyloid-β42. Subsequently, 57 participants died and underwent neuropathologic examination. Alzheimer's disease neuropathological changes were assessed using standard criteria. We assessed the predictive value of Alzheimer's disease biomarker status on progression to cognitive impairment and for presence of Alzheimer's disease neuropathological changes. Among cognitively normal participants with positive biomarkers, 34.4% developed cognitive impairment (Clinical Dementia Rating > 0) as compared to 8.4% of those with negative biomarkers. Cox proportional hazards modelling indicated that preclinical Alzheimer's disease biomarker status, APOE ɛ4 carrier status, polygenic risk score and centred age influenced risk of developing cognitive impairment. Among autopsied participants, 90.9% of biomarker-positive participants and 8.6% of biomarker-negative participants had Alzheimer's disease neuropathological changes. Sensitivity was 87.0%, specificity 94.1%, positive predictive value 90.9% and negative predictive value 91.4% for detection of Alzheimer's disease neuropathological changes by preclinical biomarkers. Single CSF and amyloid PET baseline biomarkers were also predictive of Alzheimer's disease neuropathological changes, as well as Thal phase and Braak stage of pathology at autopsy. Biomarker-negative participants who developed cognitive impairment were more likely to exhibit non-Alzheimer's disease pathology at autopsy. The detection of preclinical Alzheimer's disease biomarkers is strongly predictive of future cognitive impairment and accurately predicts presence of Alzheimer's disease neuropathology at autopsy.

Keywords: CSF; PET scan; biomarker; neuropathology; validation study.

Figure 1

Survival analysis and longitudinal biomarker trends in biomarker-negative and -positive groups. (A) Model-based cumulative incidence function curves for probability of progression to CDR > 0 in biomarker-negative (blue; lower curve) and biomarker-positive (red; upper curve) populations. (B) Spaghetti plots of longitudinal amyloid PET biomarker trends in CDR progressors (CDR > 0) and non-progressors (CDR = 0). Amyloid PET PIB and AV-45 SUVR measurements were converted to Centiloid units to combine tracer data. Data were plotted and subcategorized by biomarker-positive and -negative assignment. Biomarker category assignment was based on SUVR cut-offs. The comparable converted Centiloid cut-off value (16.4) is presented for visualization but was not used in determining biomarker status. Fitted lines obtained by simple linear regression with 95% CI are also shown. Only participants with at least one additional biomarker assessment of the same modality used to define original biomarker status were included.

Figure 2

Baseline biomarker levels in participants stratified by biomarker status and final Alzheimer's disease neuropathological diagnosis. (A) Boxplots of baseline amyloid PET biomarker levels stratified by biomarker positivity and low/absent or intermediate/high ADNC at autopsy. Amyloid PET PIB and AV-45 SUVR measurements were converted to Centiloid units to combine tracer data. Biomarker category assignment was based on SUVR cut-offs. The comparable converted Centiloid cut-off value (16.4) is presented for ease of visualization but was not used as a threshold for biomarker positivity. (B) Boxplots of baseline CSF p-tau181/Aβ₄₂ levels for biomarker-negative participants stratified by low/absent or intermediate/high ADNC at autopsy. Among the participants whose biomarker status was based on CSF, there were no biomarker-positive participants without ADNC in the autopsy cohort. So, biomarker-positive participants were excluded from this plot. In both A and B, the box size defines the interquartile range, the horizontal line indicates the median, the diamond indicates the mean, the whiskers indicate maximum and minimum range of data points and open circles indicate outliers.

Figure 3

Probability curves of ADNC pathology as a function of baseline single biomarker values. (A) Probability curves (with shaded 95% confidence intervals) of intermediate-high ADNC at autopsy as a function of baseline levels of Aβ₄₂, p-tau181, t-tau, p-tau181/Aβ₄₂ ratio and amyloid PET Centiloid units. Probability curves are generated from univariate logistic regression models with biomarker level as independent variable and probability of intermediate-high ADNC as dependent variable. (B) Cumulative probability curves of Thal phase pathology at autopsy as a function of baseline levels Aβ₄₂, p-tau181, t-tau, p-tau181/Aβ₄₂ ratio and amyloid PET Centiloid units. Thal phases are grouped in this model consistent with NIA-AA criteria: A0 = Thal phase 0, A1 = Thal phase 1 or 2, A2 = Thal phase 3, A3 = Thal phase 4 or 5. (C) Cumulative probability curves of Braak stage pathology at autopsy as a function of baseline levels Aβ₄₂, p-tau181, t-tau, p-tau181/Aβ₄₂ ratio and amyloid PET Centiloid units. Braak stages are grouped in this model consistent with NIA-AA criteria: B0 = Braak stage 0, B1 = Braak stage I or II, B2 = Braak stage III or IV, B3 = Braak stage V or VI. (B and C) Probability curves were generated from univariate ordinal logistic regression models with biomarker level as independent variable and cumulative probability of pathologic group as dependent variable. Modelled probabilities are cumulated over lower pathology groups, such that each curve delineates the probability of a given pathologic group or lower. Vertical dashed lines highlight p-tau181/Aβ₄₂ ratio and Centiloid cut-off thresholds for reference.