Tau-PET is superior to phospho-tau when predicting cognitive decline in symptomatic AD patients.

INTRODUCTION: Biomarkers for the prediction of cognitive decline in patients with amnestic mild cognitive impairment (MCI) and amnestic mild dementia are needed for both clinical practice and clinical trials. METHODS: We evaluated the ability of tau-PET (positron emission tomography), cortical atrophy on magnetic resonance imaging (MRI), baseline cognition, apolipoprotein E gene (APOE) status, plasma and cerebrospinal fluid (CSF) levels of phosphorylated tau-217, neurofilament light (NfL), and amyloid beta (Aß)42/40 ratio (individually and in combination) to predict cognitive decline over 2 years in BioFINDER-2 and Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS: Baseline tau-PET and a composite baseline cognitive score were the strongest independent predictors of cognitive decline. Cortical thickness and NfL provided some additional information. Using a predictive algorithm to enrich patient selection in a theoretical clinical trial led to a significantly lower required sample size. DISCUSSION: Models including baseline tau-PET and cognition consistently provided the best prediction of change in cognitive function over 2 years in patients with amnestic MCI or mild dementia.

Robustness of CSF Aß42/40 and Aß42/P-tau181 measured using fully automated immunoassays to detect AD-related outcomes.

INTRODUCTION: This study investigated the comparability of cerebrospinal fluid (CSF) cutoffs for Elecsys immunoassays for amyloid beta (Aß)42/Aß40 or Aß42/phosphorylated tau (p-tau)181 and the effects of measurement variability when predicting Alzheimer's disease (AD)-related outcomes (i.e., Aß-positron emission tomography [PET] visual read and AD neuropathology). METHODS: We studied 750 participants (BioFINDER study, Alzheimer's Disease Neuroimaging Initiative [ADNI], and University of California San Francisco [UCSF]). Youden's index was used to identify cutoffs and to calculate accuracy (Aß-PET visual read as outcome). Using longitudinal variability in Aß-negative controls, we identified a gray zone around cut-points where the risk of an inconsistent predicted outcome was >5%. RESULTS: For Aß42/Aß40, cutoffs across cohorts were <0.059 (BioFINDER), <0.057 (ADNI), and <0.058 (UCSF). For Aß42/p-tau181, cutoffs were <41.90 (BioFINDER), <39.20 (ADNI), and <46.02 (UCSF). Accuracy was ≈90% for both Aß42/Aß40 and Aß42/p-tau181 using these cutoffs. Using Aß-PET as an outcome, 8.7% of participants fell within a gray zone interval for Aß42/Aß40, compared to 4.5% for Aß42/p-tau181. Similar findings were observed using a measure of overall AD neuropathologic change (7.7% vs. 3.3%). In a subset with CSF and plasma Aß42/40, the number of individuals within the gray zone was ≈1.5 to 3 times greater when using plasma Aß42/40. DISCUSSION: CSF Aß42/p-tau181 was more robust to the effects of measurement variability, suggesting that it may be the preferred Elecsys-based measure in clinical practice and trials.

Optimal combinations of CSF biomarkers for predicting cognitive decline and clinical conversion in cognitively unimpaired participants and mild cognitive impairment patients: A multi-cohort study.

INTRODUCTION: Our objective was determining the optimal combinations of cerebrospinal fluid (CSF) biomarkers for predicting disease progression in Alzheimer's disease (AD) and other neurodegenerative diseases. METHODS: We included 1,983 participants from three different cohorts with longitudinal cognitive and clinical data, and baseline CSF levels of Aß42, Aß40, phosphorylated tau at threonine-181 (p-tau), neurofilament light (NfL), neurogranin, α-synuclein, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), glial fibrillary acidic protein (GFAP), YKL-40, S100b, and interleukin 6 (IL-6) (Elecsys NeuroToolKit). RESULTS: Change of modified Preclinical Alzheimer's Cognitive Composite (mPACC) in cognitively unimpaired (CU) was best predicted by p-tau/Aß42 alone (R2 ≥ 0.31) or together with NfL (R2  = 0.25), while p-tau/Aß42 (R2 ≥ 0.19) was sufficient to accurately predict change of the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) patients. P-tau/Aß42 (AUC ≥ 0.87) and p-tau/Aß42 together with NfL (AUC ≥ 0.75) were the best predictors of conversion to AD and all-cause dementia, respectively. DISCUSSION: P-tau/Aß42 is sufficient for predicting progression in AD, with very high accuracy. Adding NfL improves the prediction of all-cause dementia conversion and cognitive decline.

Test-retest variability of plasma biomarkers in Alzheimer's disease and its effects on clinical prediction models.

INTRODUCTION: The effect of random error on the performance of blood-based biomarkers for Alzheimer's disease (AD) must be determined before clinical implementation. METHODS: We measured test-retest variability of plasma amyloid beta (Aß)42/Aß40, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and phosphorylated tau (p-tau)217 and simulated effects of this variability on biomarker performance when predicting either cerebrospinal fluid (CSF) Aß status or conversion to AD dementia in 399 non-demented participants with cognitive symptoms. RESULTS: Clinical performance was highest when combining all biomarkers. Among single-biomarkers, p-tau217 performed best. Test-retest variability ranged from 4.1% (Aß42/Aß40) to 25% (GFAP). This variability reduced the performance of the biomarkers (≈ΔAUC [area under the curve] -1% to -4%) with the least effects on models with p-tau217. The percent of individuals with unstable predicted outcomes was lowest for the multi-biomarker combination (14%). DISCUSSION: Clinical prediction models combining plasma biomarkers-particularly p-tau217-exhibit high performance and are less effected by random error. Individuals with unstable predicted outcomes ("gray zone") should be recommended for further tests.

Current advances in plasma and cerebrospinal fluid biomarkers in Alzheimer's disease.

PURPOSE OF REVIEW: This review provides a concise overview of recent advances in cerebrospinal fluid (CSF) and blood-based biomarkers of Alzheimer's disease lesions. RECENT FINDINGS: Important recent advances for CSF Alzheimer's disease biomarkers include the introduction of fully automated assays, the development and implementation of certified reference materials for CSF Aß42 and a unified protocol for handling of samples, which all support reliability and availability of CSF Alzheimer's disease biomarkers. Aß deposition can be detected using Aß42/Aß40 ratio in both CSF and plasma, though a much more modest change is seen in plasma. Tau aggregation can be detected using phosphorylated tau (P-tau) at threonine 181 and 217 in CSF, with similar accuracy in plasma. Neurofilament light (NfL) be measured in CSF and shows similar diagnostic accuracy in plasma. Though total tau (T-tau) can also be measured in plasma, this measure is of limited clinical relevance for Alzheimer's disease in its current immunoassay format. SUMMARY: Alzheimer's disease biomarkers, including Aß, P-tau and NfL can now be reliably measured in both CSF and blood. Plasma-based measures of P-tau show particular promise, with potential applications in both clinical practice and in clinical trials.

The intact postsynaptic protein neurogranin is reduced in brain tissue from patients with familial and sporadic Alzheimer's disease.

Synaptic degeneration and neuronal loss are early events in Alzheimer's disease (AD), occurring long before symptom onset, thus making synaptic biomarkers relevant for enabling early diagnosis. The postsynaptic protein neurogranin (Ng) is a cerebrospinal fluid (CSF) biomarker for AD, also in the prodromal phase. Here we tested the hypothesis that during AD neurodegeneration, processing of full-length Ng into endogenous peptides in the brain is increased. We characterized Ng in post-mortem brain tissue and investigated the levels of endogenous Ng peptides in relation to full-length protein in brain tissue of patients with sporadic (sAD) and familial Alzheimer's disease (fAD), healthy controls and individuals who were cognitively unaffected but amyloid-positive (CU-AP) in two different brain regions. Brain tissue from parietal cortex [sAD (n = 10) and age-matched controls (n = 10)] and temporal cortex [sAD (n = 9), fAD (n = 10), CU-AP (n = 13) and controls (n = 9)] were included and all the samples were analyzed by three different methods. Using high-resolution mass spectrometry, 39 endogenous Ng peptides were identified while full-length Ng was found to be modified including disulfide bridges or glutathione. In sAD parietal cortex, the ratio of peptide-to-total full-length Ng was significantly increased for eight endogenous Ng peptides compared to controls. In the temporal cortex, several of the peptide-to-total full-length Ng ratios were increased in both sAD and fAD cases compared to controls and CU-AP. This finding was confirmed by western blot, which mainly detects full-length Ng, and enzyme-linked immunosorbent assay, most likely detecting a mix of peptides and full-length Ng. In addition, Ng was significantly associated with the degree of amyloid and tau pathology. These results suggest that processing of Ng into peptides is increased in AD brain tissue, which may reflect the ongoing synaptic degeneration, and which is also mirrored as increased levels of Ng peptides in CSF.

Novel tau fragments in cerebrospinal fluid: relation to tangle pathology and cognitive decline in Alzheimer's disease.

Tau is an axonal microtubule-binding protein. Tau pathology in brain and increased tau concentration in the cerebrospinal fluid (CSF) are hallmarks of Alzheimer's disease (AD). Most of tau in CSF is present as fragments. We immunoprecipitated tau from CSF and identified several endogenous peptides ending at amino acid (aa) 123 or 224 using high-resolution mass spectrometry. We raised neo-epitope-specific antibodies against tau fragments specifically ending at aa 123 and 224, respectively. With these antibodies, we performed immunohistochemistry on brain tissue and designed immunoassays measuring N-123, N-224, and x-224 tau. Immunoassays were applied to soluble brain fractions from pathologically confirmed subjects (81 AD patients, 33 controls), CSF from three cross-sectional and two longitudinal cohorts (a total of 133 AD, 38 MCI, 20 MCI-AD, 31 PSP, 15 CBS patients, and 91 controls), and neuronally- and peripherally-derived extracellular vesicles (NDEVs and PDEVs, respectively) in serum from four AD patients and four controls. Anti-tau 224 antibody stained neurofibrillary tangles and neuropil threads, while anti-tau 123 only showed weak cytoplasmic staining in AD. N-224 tau was lower in the AD soluble brain fraction compared to controls, while N-123 tau showed similar levels. N-224 tau was higher in AD compared to controls in all CSF cohorts (p < 0.001), but not N-123 tau. Decrease in cognitive performance and conversion from MCI to AD were associated with increased baseline CSF levels of N-224 tau (p < 0.0001). N-224 tau concentrations in PSP and CBS were significantly lower than in AD (p < 0.0001) and did not correlate to t-tau and p-tau. In a longitudinal cohort, CSF N-224 tau levels were stable over 6 months, with no significant effect of treatment with AChE inhibitors. N-224 tau was present in NDEVs, while N-123 tau showed comparable concentrations in both vesicle types. We suggest that N-123 tau is produced both in CNS and PNS and represents a general marker of tau metabolism, while N-224 tau is neuron-specific, present in the tangles, secreted in CSF, and upregulated in AD, suggesting a link between tau cleavage and propagation, tangle pathology, and cognitive decline.

Dynamics of extracellular matrix proteins in cerebrospinal fluid and serum and their relation to clinical outcome in human traumatic brain injury.

Background Brevican, neurocan, tenascin-C and tenascin-R are extracellular matrix proteins present in brain that show increased expression in experimental animal models of brain injury. However, little is known about the dynamics of these proteins in human body fluids, such as cerebrospinal fluid (CSF) and serum, after traumatic brain injury (TBI). The aims of this study were to investigate if matrix proteins in CSF and serum are associated with functional outcome following traumatic brain injury, if their concentrations change over time and to compare their levels between brain injured patients to controls. Methods In total, 42 traumatic brain injury patients, nine healthy controls and a contrast group consisting of 38 idiopathic normal pressure hydrocephalus patients were included. Enzyme-linked immunosorbent assays (ELISAs) were used to measure the concentrations of proteins. Results Increased concentrations of brevican, tenascin-C and tenascin-R in CSF correlated with unfavourable outcome, with stronger outcome prediction ability compared to other biomarkers of brain tissue injury. CSF brevican, tenascin-R and serum neurocan gradually decreased with time (p = 0.04, p = 0.008, p = 0.005, respectively), while serum tenascin-C (p = 0.01) increased. CSF concentrations of brevican, neurocan and tenascin-R (only in time point 3) after TBI were lower than in the idiopathic normal pressure hydrocephalus group (p < 0.0001, p < 0.0001, and p = 0.0008, respectively). In serum, tenascin-C concentration was higher and neurocan lower compared to healthy controls (p = 0.02 and p = 0.0009). Conclusions These findings indicate that levels of extracellular matrix proteins are associated with clinical outcome following TBI and may act as markers for different pathophysiology than currently used protein biomarkers.

Cerebrospinal fluid neurogranin concentration in neurodegeneration: relation to clinical phenotypes and neuropathology.

Neurogranin (Ng) is a post-synaptic protein that previously has been shown to be a biomarker for synaptic function when measured in cerebrospinal fluid (CSF). The CSF concentration of Ng is increased in Alzheimer's disease dementia (ADD), and even in the pre-dementia stage. In this prospective study, we used an enzyme-linked immunosorbent assay that quantifies Ng in CSF to test the performance of Ng as a marker of synaptic function. In 915 patients, CSF Ng was evaluated across several different neurodegenerative diseases. Of these 915 patients, 116 had a neuropathologically confirmed definitive diagnosis and the relation between CSF Ng and topographical distribution of different pathologies in the brain was evaluated. CSF Ng was specifically increased in ADD compared to eight other neurodegenerative diseases, including Parkinson's disease (p < 0.0001), frontotemporal dementia (p < 0.0001), and amyotrophic lateral sclerosis (p = 0.0002). Similar results were obtained in neuropathologically confirmed cases. Using a biomarker index to evaluate whether CSF Ng contributed diagnostic information to the core AD CSF biomarkers (amyloid ß (Aß), t-tau, and p-tau), we show that Ng significantly increased the discrimination between AD and several other disorders. Higher CSF Ng levels were positively associated with greater Aß neuritic plaque (Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuritic plaque score, p = 0.0002) and tau tangle pathology (Braak neurofibrillary tangles staging, p = 0.0007) scores. In the hippocampus and amygdala, two brain regions heavily affected in ADD with high expression of Ng, CSF Ng was associated with plaque (p = 0.0006 and p < 0.0001), but not with tangle, α-synuclein, or TAR DNA-binding protein 43 loads. These data support that CSF Ng is increased specifically in ADD, that high CSF Ng concentrations likely reflect synaptic dysfunction and that CSF Ng is associated with ß-amyloid plaque pathology.

Transient increase in CSF GAP-43 concentration after ischemic stroke.

BACKGROUND: Cerebrospinal fluid (CSF) biomarkers reflect ongoing processes in the brain. Growth-associated protein 43 (GAP-43) is highly upregulated in brain tissue shortly after experimental ischemia suggesting the CSF GAP-43 concentration may be altered in ischemic brain disorders. CSF GAP-43 concentration is elevated in Alzheimer's disease patients; however, patients suffering from stroke have not been studied previously. METHODS: The concentration of GAP-43 was measured in longitudinal CSF samples from 28 stroke patients prospectively collected on days 0-1, 2-4, 7-9, 3 weeks, and 3-5 months after ischemia and cross-sectionally in 19 controls. The stroke patients were clinically evaluated using a stroke severity score system. The extent of the brain lesion, including injury size and degrees of white matter lesions and atrophy were evaluated by CT and magnetic resonance imaging. RESULTS: Increased GAP-43 concentration was detected from day 7-9 to 3 weeks after stroke, compared to day 1-4 and to levels in the control group (P = 0.02 and P = 0.007). At 3-5 months after stroke GAP-43 returned to admission levels. The initial increase in GAP-43 during the nine first days was associated to stroke severity, the degree of white matter lesions and atrophy and correlated positively with infarct size (rs = 0.65, P = 0.001). CONCLUSIONS: The transient increase of CSF GAP-43 is important to take into account when used as a biomarker for other neurodegenerative diseases such as Alzheimer's disease. Furthermore, GAP-43 may be a marker of neuronal responses after stroke and additional studies confirming the potential of CSF GAP-43 to reflect severity and outcome of stroke in larger cohorts are warranted.

Efficacy assessment of an active tau immunotherapy in Alzheimer's disease patients with amyloid and tau pathology: a post hoc analysis of the "ADAMANT" randomised, placebo-controlled, double-blind, multi-centre, phase 2 clinical trial.

BACKGROUND: Tau pathology correlates with and predicts clinical decline in Alzheimer's disease. Approved tau-targeted therapies are not available. METHODS: ADAMANT, a 24-month randomised, placebo-controlled, parallel-group, double-blinded, multicenter, Phase 2 clinical trial (EudraCT2015-000630-30, NCT02579252) enrolled 196 participants with Alzheimer's disease; 119 are included in this post-hoc subgroup analysis. AADvac1, active immunotherapy against pathological tau protein. A machine learning model predicted likely Amyloid+Tau+ participants from baseline MRI. STATISTICAL METHODS: MMRM for change from baseline in cognition, function, and neurodegeneration; linear regression for associations between antibody response and endpoints. RESULTS: The prediction model achieved PPV of 97.7% for amyloid, 96.2% for tau. 119 participants in the full analysis set (70 treatment and 49 placebo) were classified as A+T+. A trend for CDR-SB 104-week change (estimated marginal means [emm] = -0.99 points, 95% CI [-2.13, 0.13], p = 0.0825]) and ADCS-MCI-ADL (emm = 3.82 points, CI [-0.29, 7.92], p = 0.0679) in favour of the treatment group was seen. Reduction was seen in plasma NF-L (emm = -0.15 log pg/mL, CI [-0.27, -0.03], p = 0.0139). Higher antibody response to AADvac1 was related to slowing of decline on CDR-SB (rho = -0.10, CI [-0.21, 0.01], p = 0.0376) and ADL (rho = 0.15, CI [0.03, 0.27], p = 0.0201), and related to slower brain atrophy (rho = 0.18-0.35, p < 0.05 for temporal volume, whole cortex, and right and left hippocampus). CONCLUSIONS: In the subgroup of ML imputed or CSF identified A+T+, AADvac1 slowed AD-related decline in an antibody-dependent manner. Larger anti-tau trials are warranted. FUNDING: AXON Neuroscience SE.

A blood-based biomarker workflow for optimal tau-PET referral in memory clinic settings.

Blood-based biomarkers for screening may guide tau positrion emissition tomography (PET) scan referrals to optimize prognostic evaluation in Alzheimer's disease. Plasma Aß42/Aß40, pTau181, pTau217, pTau231, NfL, and GFAP were measured along with tau-PET in memory clinic patients with subjective cognitive decline, mild cognitive impairment or dementia, in the Swedish BioFINDER-2 study (n = 548) and in the TRIAD study (n = 179). For each plasma biomarker, cutoffs were determined for 90%, 95%, or 97.5% sensitivity to detect tau-PET-positivity. We calculated the percentage of patients below the cutoffs (who would not undergo tau-PET; "saved scans") and the tau-PET-positivity rate among participants above the cutoffs (who would undergo tau-PET; "positive predictive value"). Generally, plasma pTau217 performed best. At the 95% sensitivity cutoff in both cohorts, pTau217 resulted in avoiding nearly half tau-PET scans, with a tau-PET-positivity rate among those who would be referred for a scan around 70%. And although tau-PET was strongly associated with subsequent cognitive decline, in BioFINDER-2 it predicted cognitive decline only among individuals above the referral cutoff on plasma pTau217, supporting that this workflow could reduce prognostically uninformative tau-PET scans. In conclusion, plasma pTau217 may guide selection of patients for tau-PET, when accurate prognostic information is of clinical value.

Plasma amyloid-ß42/40 and apolipoprotein E for amyloid PET pre-screening in secondary prevention trials of Alzheimer's disease.

The extent to which newly developed blood-based biomarkers could reduce screening costs in secondary prevention trials of Alzheimer's disease is mostly unexplored. We collected plasma amyloid-ß42/40, apolipoprotein E ε4 status and amyloid PET at baseline in 181 cognitively unimpaired participants [the age of 72.9 (5.3) years; 61.9% female; education of 11.9 (3.4) years] from the Swedish BioFINDER-1 study. We tested whether a model predicting amyloid PET status from plasma amyloid-ß42/40, apolipoprotein E status and age (combined) reduced cost of recruiting amyloid PET + cognitively unimpaired participants into a theoretical trial. We found that the percentage of cognitively unimpaired participants with an amyloid PET + scan rose from 29% in an unscreened population to 64% [(49, 79); P < 0.0001] when using the biomarker model to screen for high risk for amyloid PET + status. In simulations, plasma screening also resulted in a 54% reduction of the total number of amyloid PET scans required and reduced total recruitment costs by 43% [(31, 56), P < 0.001] compared to no pre-screening when assuming a 16× PET-to-plasma cost ratio. Total savings remained significant when the PET-to-plasma cost ratio was assumed to be 8× or 4×. This suggests that a simple plasma biomarker model could lower recruitment costs in Alzheimer's trials requiring amyloid PET positivity for inclusion.

A two-step workflow based on plasma p-tau217 to screen for amyloid ß positivity with further confirmatory testing only in uncertain cases.

Cost-effective strategies for identifying amyloid-ß (Aß) positivity in patients with cognitive impairment are urgently needed with recent approvals of anti-Aß immunotherapies for Alzheimer's disease (AD). Blood biomarkers can accurately detect AD pathology, but it is unclear whether their incorporation into a full diagnostic workflow can reduce the number of confirmatory cerebrospinal fluid (CSF) or positron emission tomography (PET) tests needed while accurately classifying patients. We evaluated a two-step workflow for determining Aß-PET status in patients with mild cognitive impairment (MCI) from two independent memory clinic-based cohorts (n = 348). A blood-based model including plasma tau protein 217 (p-tau217), age and APOE ε4 status was developed in BioFINDER-1 (area under the curve (AUC) = 89.3%) and validated in BioFINDER-2 (AUC = 94.3%). In step 1, the blood-based model was used to stratify the patients into low, intermediate or high risk of Aß-PET positivity. In step 2, we assumed referral only of intermediate-risk patients to CSF Aß42/Aß40 testing, whereas step 1 alone determined Aß-status for low- and high-risk groups. Depending on whether lenient, moderate or stringent thresholds were used in step 1, the two-step workflow overall accuracy for detecting Aß-PET status was 88.2%, 90.5% and 92.0%, respectively, while reducing the number of necessary CSF tests by 85.9%, 72.7% and 61.2%, respectively. In secondary analyses, an adapted version of the BioFINDER-1 model led to successful validation of the two-step workflow with a different plasma p-tau217 immunoassay in patients with cognitive impairment from the TRIAD cohort (n = 84). In conclusion, using a plasma p-tau217-based model for risk stratification of patients with MCI can substantially reduce the need for confirmatory testing while accurately classifying patients, offering a cost-effective strategy to detect AD in memory clinic settings.

Biomarker-Based Prediction of Longitudinal Tau Positron Emission Tomography in Alzheimer Disease.

Importance: There is currently no consensus as to which biomarkers best predict longitudinal tau accumulation at different clinical stages of Alzheimer disease (AD). Objective: To describe longitudinal [18F]RO948 tau positron emission tomography (PET) findings across the clinical continuum of AD and determine which biomarker combinations showed the strongest associations with longitudinal tau PET and best optimized clinical trial enrichment. Design, Setting, and Participants: This longitudinal cohort study consecutively enrolled amyloid-ß (Aß)-negative cognitively unimpaired (CU) participants, Aß-positive CU individuals, Aß-positive individuals with mild cognitive impairment (MCI), and individuals with AD dementia between September 2017 and November 2020 from the Swedish BioFINDER-2 (discovery cohort) and BioFINDER-1 (validation cohort) studies. Exposures: Baseline plasma and cerebrospinal fluid Aß42/Aß40, tau phosphorylated at threonine-217 (p-tau217), p-tau181 and neurofilament light, magnetic resonance imaging, amyloid PET ([18F]flutemetamol), and tau PET ([18F]RO948 in the BioFINDER-2 study; [18F]flortaucipir in the BioFINDER-1 study). Main Outcomes and Measures: Baseline tau PET standardized uptake value ratio (SUVR) and annual percent change in tau PET SUVR across regions of interest derived using a data-driven approach combining clustering and event-based modeling. Regression models were used to examine associations between individual biomarkers and longitudinal tau PET and to identify which combinations best predicted longitudinal tau PET. These combinations were then entered in a power analysis to examine how their use as an enrichment strategy would affect sample size in a simulated clinical trial. Results: Of 343 participants, the mean (SD) age was 72.56 (7.24) years, and 157 (51.1%) were female. The clustering/event-based modeling-based approach identified 5 regions of interest (stages). In Aß-positive CU individuals, the largest annual increase in tau PET SUVR was seen in stage I (entorhinal cortex, hippocampus, and amygdala; 4.04% [95% CI, 2.67%-5.32%]). In Aß-positive individuals with MCI and with AD dementia, the greatest increases were seen in stages II (temporal cortical regions; 4.45% [95% CI, 3.41%-5.49%]) and IV (certain frontal regions; 5.22% [95% CI, 3.95%-6.49%]), respectively. In Aß-negative CU individuals and those with MCI, modest change was seen in stage I (1.38% [95% CI, 0.78%-1.99%] and 1.80% [95% CI, 0.76%-2.84%], respectively). When looking at individual predictors and longitudinal tau PET in the stages that showed most change, plasma p-tau217 (R2 = 0.27, P < .005), tau PET (stage I baseline SUVR; R2 = 0.13, P < .05) and amyloid PET (R2 = 0.10, P < .05) were significantly associated with longitudinal tau PET in stage I in Aß-positive CU individuals. In Aß-positive individuals with MCI, plasma p-tau217 (R2 = 0.24, P < .005) and tau PET (stage II baseline SUVR; R2 = 0.44, P < .001) were significantly associated with longitudinal tau PET in stage II. Findings were replicated in BioFINDER-1 using longitudinal [18F]flortaucipir. For the power analysis component, plasma p-tau217 with tau PET resulted in sample size reductions of 43% (95% CI, 34%-46%; P < .005) in Aß-positive CU individuals and of 68% (95% CI, 61%-73%; P < .001) in Aß-positive individuals with MCI. Conclusions and Relevance: In trials using tau PET as the outcome, plasma p-tau217 with tau PET may prove optimal for enrichment in preclinical and prodromal AD. However, plasma p-tau217 was most important in preclinical AD, while tau PET was more important in prodromal AD.

Accelerated inflammatory aging in Alzheimer's disease and its relation to amyloid, tau, and cognition.

It is unclear how pathological aging of the inflammatory system relates to Alzheimer's disease (AD). We tested whether age-related inflammatory changes in cerebrospinal fluid (CSF) and plasma exist across different stages of AD, and whether such changes related to AD pathology. Linear regression was first used model chronological age in amyloid-ß negative, cognitively unimpaired individuals (Aß- CU; n = 312) based on a collection of 73 inflammatory proteins measured in both CSF and plasma. Fitted models were then applied on protein levels from Aß+ individuals with mild cognitive impairment (Aß+ MCI; n = 150) or Alzheimer's disease dementia (Aß+ AD; n = 139) to test whether the age predicted from proteins alone ("inflammatory age") differed significantly from true chronological age. Aß- individuals with subjective cognitive decline (Aß- SCD; n = 125) or MCI (Aß- MCI; n = 104) were used as an independent contrast group. The difference between inflammatory age and chronological age (InflammAGE score) was then assessed in relation to core AD biomarkers of amyloid, tau, and cognition. Both CSF and plasma inflammatory proteins were significantly associated with age in Aß- CU individuals, with CSF-based proteins predicting chronological age better than plasma-based counterparts. Meanwhile, the Aß- SCD and validation Aß- CU groups were not characterized by significant inflammatory aging, while there was increased inflammatory aging in Aß- MCI patients for CSF but not plasma inflammatory markers. Both CSF and plasma inflammatory changes were seen in the Aß+ MCI and Aß+ AD groups, with varying degrees of change compared to Aß- CU and Aß- SCD groups. Finally, CSF inflammatory changes were highly correlated with amyloid, tau, general neurodegeneration, and cognition, while plasma changes were mostly associated with amyloid and cognition. Inflammatory pathways change during aging and are specifically altered in AD, tracking closely with pathological hallmarks. These results have implications for tracking AD progression and for suggesting possible pathways for drug targeting.

Plasma biomarkers of Alzheimer's disease improve prediction of cognitive decline in cognitively unimpaired elderly populations.

Plasma biomarkers of amyloid, tau, and neurodegeneration (ATN) need to be characterized in cognitively unimpaired (CU) elderly individuals. We therefore tested if plasma measurements of amyloid-ß (Aß)42/40, phospho-tau217 (P-tau217), and neurofilament light (NfL) together predict clinical deterioration in 435 CU individuals followed for an average of 4.8 ± 1.7 years in the BioFINDER study. A combination of all three plasma biomarkers and basic demographics best predicted change in cognition (Pre-Alzheimer's Clinical Composite; R2 = 0.14, 95% CI [0.12-0.17]; P < 0.0001) and subsequent AD dementia (AUC = 0.82, 95% CI [0.77-0.91], P < 0.0001). In a simulated clinical trial, a screening algorithm combining all three plasma biomarkers would reduce the required sample size by 70% (95% CI [54-81]; P < 0.001) with cognition as trial endpoint, and by 63% (95% CI [53-70], P < 0.001) with subsequent AD dementia as trial endpoint. Plasma ATN biomarkers show usefulness in cognitively unimpaired populations and could make large clinical trials more feasible and cost-effective.

Individualized prognosis of cognitive decline and dementia in mild cognitive impairment based on plasma biomarker combinations.

We developed models for individualized risk prediction of cognitive decline in mild cognitive impairment (MCI) using plasma biomarkers of ß-amyloid (Aß), tau and neurodegeneration. A total of 573 patients with MCI from the Swedish BioFINDER study and the Alzheimer's Disease Neuroimaging Initiative (ADNI) were included in the study. The primary outcomes were longitudinal cognition and conversion to Alzheimer's disease (AD) dementia. A model combining tau phosphorylated at threonine 181 (P-tau181) and neurofilament light (NfL), but not Aß42/Aß40, had the best prognosis performance of all models (area under the curve = 0.88 for 4-year conversion to AD in BioFINDER, validated in ADNI), was stronger than a basic model of age, sex, education and baseline cognition, and performed similarly to cerebrospinal fluid biomarkers. A publicly available online tool for individualized prognosis in MCI based on our combined plasma biomarker models is introduced. Combination of plasma biomarkers may be of high value to identify individuals with MCI who will progress to AD dementia in clinical trials and in clinical practice.

The ANTsX ecosystem for quantitative biological and medical imaging.

The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis.

Comparing progression biomarkers in clinical trials of early Alzheimer's disease.

OBJECTIVE: To investigate the statistical power of plasma, imaging, and cognition biomarkers as Alzheimer's disease (AD) clinical trial outcome measures. METHODS: Plasma neurofilament light, structural magnetic resonance imaging, and cognition were measured longitudinally in the Alzheimer's Disease Neuroimaging Initiative (ADNI) in control (amyloid PET or CSF Aß42 negative [Aß-] with Clinical Dementia Rating scale [CDR] = 0; n = 330), preclinical AD (Aß + with CDR = 0; n = 218) and mild AD (Aß + with CDR = 0.5-1; n = 697) individuals. A statistical power analysis was performed across biomarkers and groups based on longitudinal mixed effects modeling and using several different clinical trial designs. RESULTS: For a 30-month trial of preclinical AD, both the temporal composite and hippocampal volumes were superior to plasma neurofilament light and cognition. For an 18-month trial of mild AD, hippocampal volume was superior to all other biomarkers. Plasma neurofilament light became more effective with increased trial duration or sampling frequency. Imaging biomarkers were characterized by high slope and low within-subject variability, while plasma neurofilament light and cognition were characterized by higher within-subject variability. INTERPRETATION: MRI measures had properties that made them preferable to cognition and pNFL as outcome measures in clinical trials of early AD, regardless of cognitive status. However, pNfL and cognition can still be effective depending on inclusion criteria, sampling frequency, and response to therapy. Future trials will help to understand how sensitive pNfL and MRI are to detect downstream effects on neurodegeneration of drugs targeting amyloid and tau pathology in AD.