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Additional file 1: Supplementary figure 1. Baseline CSF tau368 concentrations. Supplementary figure 2. Correlation between CSF tau, cognition and tau PET with age. Supplementary figure 3. ROC curves for identifying Braak stages. Supplementary figure 4. Correlation between CSF tau biomarkers and hippocampal volume. Supplementary table 1. Correlation between CSF tau biomarkers and tau PET SUVr. Supplementary table 2. Correlations with tau PET imaging and cognition using ratios with p-tau in the group with symptomatic AD. Supplementary table 3. The relationship between CSF p-tau217 and PET imaging. Supplementary table 4. The relationship between CSF p-tau181 and PET imaging. Supplementary table 5. The relationship between CSF t-tau and PET imaging. Supplementary table 6. Correlation between global cognition and CSF biomarkers in the whole group.

Additional file 1. Supplementary tables.

Additional file 3. Differentially expressed proteins (DEPs) in the cerebrospinal fluid (CSF) of cognitively unimpaired (CU) tau pathology positive (T+) compared to negative (T���) subjects. Table containing Protein ID, p-value, adjusted p-value, t-value and logFC for differentially expressed proteins in the cerebrospinal fluid of cognitively unimpaired tau pathology positive compared to negative subjects.

Additional file 4. Differentially expressed proteins (DEPs) in the cerebrospinal fluid (CSF) of cognitively unimpaired (CU) neurodegeneration positive (N+) compared to negative (N���) subjects. Table containing Protein ID, p-value, adjusted p-value, t-value and logFC for differentially expressed proteins in the cerebrospinal fluid of cognitively unimpaired neurodegeneration positive compared to negative subjects

Additional file 1 : Supplemental Figure 1. There was significant positive correlation between the semiquantitative value of [18F]BCPP-EF SUVR relative to the whole brain and [18F]BCPP-EF SUVR relative to the centrum semiovale in the average of the all ROIs (manually located bilaterally in the cerebellum, anterior cingulated cortex, caudate, putamen, thalamus, posterior cingulated cortex, precuneus, superior frontal cortex, middle frontal cortex, occipital cortex, lateral temporal cortex, medial temporal cortex including hippocampus, parahippocampus, amygdala, parietal cortex, pons, and midbrain).

Additional file 2. Machine learning results for predicting neurodegeneration positivity (N+). Table containing features, AUC and standard deviation results for all 1023 models for predicting neurodegeneration positivity.

Additional file 1.

Objective To assess the frequency of biologically defined Alzheimer disease (AD) in relation to age, sex, APOE ε4, and clinical diagnosis in a prospective cohort study evaluated with amyloid-PET and tau-PET. Methods We assessed cognitively unimpaired (CU) elderly (n = 166), patients with amnestic mild cognitive impairment (n = 77), and patients with probable AD dementia (n = 62) who underwent evaluation by dementia specialists and neuropsychologists in addition to amyloid-PET with [18F]AZD4694 and tau-PET with [18F]MK6240. Individuals were grouped according to their AD biomarker profile. Positive predictive value for biologically defined AD was assessed in relation to clinical diagnosis. Frequency of AD biomarker profiles was assessed using logistic regressions with odds ratios (ORs) and 95% confidence intervals (CIs). Results The clinical diagnosis of probable AD dementia demonstrated good agreement with biologically defined AD (positive predictive value 85.2%). A total of 7.88% of CU were positive for both amyloid-PET and tau-PET. Frequency of biologically defined AD increased with age (OR 1.14; p < 0.0001) and frequency of APOE ε4 allele carriers (single ε4: OR 3.82; p < 0.0001; double ε4: OR 17.55, p < 0.0001). Conclusion Whereas we observed strong, but not complete, agreement between clinically defined probable AD dementia and biomarker positivity for both β-amyloid and tau, we also observed that biologically defined AD was not rare in CU elderly. Abnormal tau-PET was almost exclusively observed in individuals with abnormal amyloid-PET. Our results highlight that even in tertiary care memory clinics, detailed evaluation by dementia specialists systematically underestimates the frequency of biologically defined AD and related entities. Classification of Evidence This study provides Class I evidence that biologically defined AD (abnormal amyloid PET and tau PET) was observed in 85.2% of people with clinically defined AD and 7.88% of CU elderly.

ObjectiveTo identify the pathophysiologic mechanisms and clinical significance of anosognosia for cognitive decline in mild cognitive impairment.MethodsWe stratified 468 patients with amnestic mild cognitive impairment into intact and impaired awareness groups, determined by the discrepancy between the patient and the informant score on the Everyday Cognition questionnaire. Voxel-based linear regression models evaluated the associations between self-awareness status and baseline β-amyloid load, measured by [18F]florbetapir, and the relationships between awareness status and regional brain glucose metabolism measured by [18F]fluorodeoxyglucose at baseline and at 24-month follow-up. Multivariate logistic regression tested the association of awareness status with conversion from amnestic mild cognitive impairment to dementia.ResultsWe found that participants with impaired awareness had lower [18F]fluorodeoxyglucose uptake and increased [18F]florbetapir uptake in the posterior cingulate cortex at baseline. In addition, impaired awareness in mild cognitive impairment predicted [18F]fluorodeoxyglucose hypometabolism in the posterior cingulate cortex, left basal forebrain, bilateral medial temporal lobes, and right lateral temporal lobe over 24 months. Furthermore, participants with impaired awareness had a nearly 3-fold increase in likelihood of conversion to dementia within a 2-year time frame.ConclusionsOur results suggest that anosognosia is linked to Alzheimer disease pathophysiology in vulnerable structures, and predicts subsequent hypometabolism in the default mode network, accompanied by an increased risk of progression to dementia. This highlights the importance of assessing awareness of cognitive decline in the clinical evaluation and management of individuals with amnestic mild cognitive impairment.