Novel diagnostic and prognostic approach for rapidly progressive dementias: Indicators based on amyloid/tau/neurodegeneration (ATN) framework.

AIMS: Apply established cerebrospinal fluid (CSF) and serum biomarkers and novel combined indicators based on the amyloid/tau/neurodegeneration (ATN) framework to improve diagnostic and prognostic power in patients with rapidly progressive dementias (RPDs). METHODS: CSF and serum biomarkers of Alzheimer's disease (AD) common neuropathology including Aß42, Aß40, p-Tau, and t-Tau were measured in cognitively normal (CN) controls (n = 33) and three RPD groups with rapidly progressive AD (rpAD, n = 23), autoimmune encephalitis (AE, n = 25), and Creutzfeldt-Jakob disease (CJD, n = 28). Logistic regression and multiple linear regression were used for producing combined indicators and prognostic assessment, respectively, including A&T, A&N, T&N, A&T&N, etc. RESULTS: Combined diagnostic indicator with A&T&N had the potential for differentiating AE from other types of RPDs, identifying 62.51% and 75% of AE subjects based on CSF and serum samples, respectively, compared to 39.13% and 37.5% when using autoantibodies. CSF t-Tau was associated with survival in the CJD group (adjusted R-Square = 0.16, p = 0.02), and its prognosis value improved when using combined predictors based on the ATN framework (adjusted R-Square = 0.273, p = 0.014). CONCLUSION: Combined indicators based on the ATN framework provide a novel perspective for establishing biomarkers for early recognition of RPDs due to treatment-responsive causes.

Data-Driven Thresholding Statistically Biases ATN Profiling across Cohort Datasets.

BACKGROUND: While the amyloid/tau/neurodegeneration (ATN) framework has found wide application in Alzheimer's disease research, it is unclear if thresholds obtained using distinct thresholding methods are concordant within the same dataset and interchangeable across cohorts. OBJECTIVES: To investigate the robustness of data-driven thresholding methods and ATN profiling across cohort datasets. DESIGN AND SETTING: We evaluated the impact of thresholding methods on ATN profiles by applying five commonly-used methodologies across cohort datasets. We assessed the generalizability of disease patterns discovered within ATN profiles by clustering individuals from different cohorts who were assigned to the same ATN profile. PARTICIPANTS AND MEASUREMENTS: Participants with available CSF amyloid-ß 1-42, phosphorylated tau, and total tau measurements were included from eleven AD cohort studies. RESULTS: We observed high variability among obtained ATN thresholds, both across methods and datasets that impacted the resulting profile assignments of participants significantly. Clustering participants from different cohorts within the same ATN category indicated that identified disease patterns were comparable across most cohorts and biases introduced through distinct thresholding and data representations remained insignificant in most ATN profiles. CONLUSION: Thresholding method selection is a decision of statistical relevance that will inevitably bias the resulting profiling and affect its sensitivity and specificity. Thresholds are likely not directly interchangeable between independent cohorts. To apply the ATN framework as an actionable and robust profiling scheme, a comprehensive understanding of the impact of used thresholding methods, their statistical implications, and a validation of results is crucial.

Clinical and biological relevance of glial fibrillary acidic protein in Alzheimer's disease.

INTRODUCTION: There is a tremendous need for identifying reliable blood-based biomarkers for Alzheimer's disease (AD) that are tied to the biological ATN (amyloid, tau and neurodegeneration) framework as well as clinical assessment and progression. METHODS: One hundred forty-four elderly participants underwent 18F-AV45 positron emission tomography (PET) scan, structural magnetic resonance imaging (MRI) scan, and blood sample collection. The composite standardized uptake value ratio (SUVR) was derived from 18F-AV45 PET to assess brain amyloid burden, and the hippocampal volume was determined from structural MRI scans. Plasma glial fibrillary acidic protein (GFAP), phosphorylated tau-181 (ptau-181), and neurofilament light (NfL) measured by single molecular array (SIMOA) technology were assessed with respect to ATN framework, genetic risk factor, age, clinical assessment, and future functional decline among the participants. RESULTS: Among the three plasma markers, GFAP best discriminated participants stratified by clinical diagnosis and brain amyloid status. Age was strongly associated with NfL, followed by GFAP and ptau-181 at much weaker extent. Brain amyloid was strongly associated with plasma GFAP and ptau-181 and to a lesser extent with plasma NfL. Moderate association was observed between plasma markers. Hippocampal volume was weakly associated with all three markers. Elevated GFAP and ptau-181 were associated with worse cognition, and plasma GFAP was the most predictive of future functional decline. Combining GFAP and ptau-181 together was the best model to predict brain amyloid status across all participants (AUC = 0.86) or within cognitively impaired participants (AUC = 0.93); adding NfL as an additional predictor only had a marginal improvement. CONCLUSION: Our findings indicate that GFAP is of potential clinical utility in screening amyloid pathology and predicting future cognitive decline. GFAP, NfL, and ptau-181 were moderately associated with each other, with discrepant relevance to age, sex, and AD genetic risk, suggesting their relevant but differential roles for AD assessment. The combination of GFAP with ptau-181 provides an accurate model to predict brain amyloid status, with the superior performance of GFAP over ptau-181 when the prediction is limited to cognitively impaired participants.

Sex differences in risk factors that predict progression from mild cognitive impairment to Alzheimer's dementia.

OBJECTIVES: To evaluate whether cerebrospinal fluid biomarkers, apolipoprotein e4, neuroimaging abnormalities, and neuropsychological data differentially predict progression from mild cognitive impairment (MCI) to dementia for men and women. METHODS: Participants who were diagnosed with MCI at baseline (n = 449) were classified as either progressing to Alzheimer's dementia at follow-up or as not progressing. Men and women were first compared using bivariate analyses. Sex-stratified Cox proportional hazard regressions were performed examining the relationship between baseline data and the likelihood of progressing to dementia. Sex interactions were subsequently examined. RESULTS: Cox proportional hazard regression controlling for age and education indicated that all variables significantly predicted subsequent progression to dementia for men and women. Sex interactions indicated that only Rey Auditory Verbal Learning Test (RAVLT) delayed recall and Functional Activities Questionnaire (FAQ) were significantly stronger risk factors for women. When all variables were entered into a fully adjusted model, significant risk factors for women were Aß42, hippocampal volume, RAVLT delayed recall, Boston Naming Test, and FAQ. In contrast, for men, Aß42, p-tau181, p-tau181/Aß42, hippocampal volume, category fluency and FAQ were significant risk factors. Interactions with sex were only significant for p-tau181/Aß42 and RAVLT delayed recall for the fully adjusted model. CONCLUSIONS: Men and women with MCI may to differ for which factors predict subsequent dementia although future analyses with greater power are needed to evaluate sex differences. We hypothesize that brain and cognitive reserve theories may partially explain these findings.

Platelet-Derived Amyloid-ß Protein Precursor as a Biomarker of Alzheimer's Disease.

BACKGROUND: Platelet proteins may be associated with Alzheimer's disease (AD) pathology. OBJECTIVE: To investigate the relationship between platelet proteins and cerebrospinal fluid (CSF) biomarkers of AD and cognition in individuals with memory decline to identify effective screening methods for detecting the early stages of the disease. METHODS: We classified 68 participants with subjective memory decline according to the ATN framework determined by CSF amyloid-ß (A), CSF p-tau (T), and t-tau (N). All participants underwent Mini-Mental State Examination (MMSE) and platelet-related protein content testing. RESULTS: Eighteen participants had normal AD biomarkers (NCs), 24 subjects had non-AD pathologic changes (non-AD), and 26 subjects fell within the Alzheimer's continuum (AD). The platelet amyloid-ß protein precursor (AßPP) ratio in the AD group was significantly lower than in the non-AD and NCs groups, and positively correlated with MMSE scores and CSF amyloid-ß42 level, which could affect MMSE scores through CSF amyloid-ß42. Levels of platelet phosphorylated-tau 231 and ser396/404 phosphorylated tau were elevated in both AD and non-AD compared to NCs. Additionally, the receiver operating characteristic analysis demonstrated that the platelet AßPP ratio was a sensitive identifier for differentiating the AD from NCs (AUC = 0.846) and non-AD (AUC = 0.768). And ser396/404 phosphorylated tau could distinguish AD from NCs. CONCLUSION: Our study was the first to find an association between platelet AßPP ratio and CSF biomarkers of AD, which contribute to the understanding of the peripheral changes in AD. These findings may help to discover potential feasible and effective screening tools for AD.

Replication study of plasma proteins relating to Alzheimer's pathology.

INTRODUCTION: This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis. METHODS: Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively. RESULTS: Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis. DISCUSSION: Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis.

Blood-Based ATN Biomarkers of Alzheimer's Disease: A Meta-Analysis.

BACKGROUND: The Amyloid Tau Neurodegeneration (ATN) framework was proposed to define the biological state underpinning Alzheimer's disease (AD). Blood-based biomarkers offer a scalable alternative to the costly and invasive currently available biomarkers. OBJECTIVE: In this meta-analysis we sought to assess the diagnostic performance of plasma amyloid (Aß40, Aß42, Aß42/40 ratio), tangle (p-tau181), and neurodegeneration (total tau [t-tau], neurofilament light [NfL]) biomarkers. METHODS: Electronic databases were screened for studies reporting biomarker concentrations for AD and control cohorts. Biomarker performance was examined by random-effect meta-analyses based on the ratio between biomarker concentrations in patients and controls. RESULTS: 83 studies published between 1996 and 2020 were included in the analyses. Aß42/40 ratio as well as Aß42 discriminated AD patients from controls when using novel platforms such as immunomagnetic reduction (IMR). We found significant differences in ptau-181 concentration for studies based on single molecule array (Simoa), but not for studies based on IMR or ELISA. T-tau was significantly different between AD patients and control in IMR and Simoa but not in ELISA-based studies. In contrast, NfL differentiated between groups across platforms. Exosome studies showed strong separation between patients and controls for Aß42, t-tau, and p-tau181. CONCLUSION: Currently available assays for sampling plasma ATN biomarkers appear to differentiate between AD patients and controls. Novel assay methodologies have given the field a significant boost for testing these biomarkers, such as IMR for Aß, Simoa for p-tau181. Enriching samples through extracellular vesicles shows promise but requires further validation.

Prediction of Alzheimer's disease biomarker status defined by the 'ATN framework' among cognitively healthy individuals: results from the EPAD longitudinal cohort study.

BACKGROUND: The Amyloid/Tau/Neurodegeneration (ATN) framework has been proposed as a means of evidencing the biological state of Alzheimer's disease (AD). Predicting ATN status in pre-dementia individuals therefore provides an important opportunity for targeted recruitment into AD interventional studies. We investigated the extent to which ATN-defined biomarker status can be predicted by known AD risk factors as well as vascular-related composite risk scores. METHODS: One thousand ten cognitively healthy older adults were allocated to one of five ATN-defined biomarker categories. Multinomial logistic regression tested risk factors including age, sex, education, APOE4, family history of dementia, cognitive function, vascular risk indices (high systolic blood pressure, body mass index (BMI), high cholesterol, physical inactivity, ever smoked, blood pressure medication, diabetes, prior cardiovascular disease, atrial fibrillation and white matter lesion (WML) volume), and three vascular-related composite scores, to predict five ATN subgroups; ROC curve models estimated their added value in predicting pathology. RESULTS: Age, APOE4, family history, BMI, MMSE and white matter lesions (WML) volume differed between ATN biomarker groups. Prediction of Alzheimer's disease pathology (versus normal AD biomarkers) improved by 7% after adding family history, BMI, MMSE and WML to a ROC curve that included age, sex and APOE4. Risk composite scores did not add value. CONCLUSIONS: ATN-defined Alzheimer's disease biomarker status prediction among cognitively healthy individuals is possible through a combination of constitutional and cardiovascular risk factors but established dementia composite risk scores do not appear to add value in this context.

Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer's Disease Pathology.

BACKGROUND: Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown. OBJECTIVE: We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes. METHODS: We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677). RESULTS: We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts. CONCLUSIONS: Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo.