CSF neurofilament light chain profiling and quantitation in neurological diseases.

Neurofilament light chain is an established marker of neuroaxonal injury that is elevated in CSF and blood across various neurological diseases. It is increasingly used in clinical practice to aid diagnosis and monitor progression and as an outcome measure to assess safety and efficacy of disease-modifying therapies across the clinical translational neuroscience field. Quantitative methods for neurofilament light chain in human biofluids have relied on immunoassays, which have limited capacity to describe the structure of the protein in CSF and how this might vary in different neurodegenerative diseases. In this study, we characterized and quantified neurofilament light chain species in CSF across neurodegenerative and neuroinflammatory diseases and healthy controls using targeted mass spectrometry. We show that the quantitative immunoprecipitation-tandem mass spectrometry method developed in this study strongly correlates to single-molecule array measurements in CSF across the broad spectrum of neurodegenerative diseases and was replicable across mass spectrometry methods and centres. In summary, we have created an accurate and cost-effective assay for measuring a key biomarker in translational neuroscience research and clinical practice, which can be easily multiplexed and translated into clinical laboratories for the screening and monitoring of neurodegenerative disease or acute brain injury.

Novel non-linear models for clinical trial analysis with longitudinal data: A tutorial using SAS for both frequentist and Bayesian methods.

Longitudinal data from clinical trials are commonly analyzed using mixed models for repeated measures (MMRM) when the time variable is categorical or linear mixed-effects models (ie, random effects model) when the time variable is continuous. In these models, statistical inference is typically based on the absolute difference in the adjusted mean change (for categorical time) or the rate of change (for continuous time). Previously, we proposed a novel approach: modeling the percentage reduction in disease progression associated with the treatment relative to the placebo decline using proportional models. This concept of proportionality provides an innovative and flexible method for simultaneously modeling different cohorts, multivariate endpoints, and jointly modeling continuous and survival endpoints. Through simulated data, we demonstrate the implementation of these models using SAS procedures in both frequentist and Bayesian approaches. Additionally, we introduce a novel method for implementing MMRM models (ie, analysis of response profile) using the nlmixed procedure.

Comparison of tau spread in people with Down syndrome versus autosomal-dominant Alzheimer's disease: a cross-sectional study.

BACKGROUND: In people with genetic forms of Alzheimer's disease, such as in Down syndrome and autosomal-dominant Alzheimer's disease, pathological changes specific to Alzheimer's disease (ie, accumulation of amyloid and tau) occur in the brain at a young age, when comorbidities related to ageing are not present. Studies including these cohorts could, therefore, improve our understanding of the early pathogenesis of Alzheimer's disease and be useful when designing preventive interventions targeted at disease pathology or when planning clinical trials. We compared the magnitude, spatial extent, and temporal ordering of tau spread in people with Down syndrome and autosomal-dominant Alzheimer's disease. METHODS: In this cross-sectional observational study, we included participants (aged ≥25 years) from two cohort studies. First, we collected data from the Dominantly Inherited Alzheimer's Network studies (DIAN-OBS and DIAN-TU), which include carriers of autosomal-dominant Alzheimer's disease genetic mutations and non-carrier familial controls recruited in Australia, Europe, and the USA between 2008 and 2022. Second, we collected data from the Alzheimer Biomarkers Consortium-Down Syndrome study, which includes people with Down syndrome and sibling controls recruited from the UK and USA between 2015 and 2021. Controls from the two studies were combined into a single group of familial controls. All participants had completed structural MRI and tau PET (18F-flortaucipir) imaging. We applied Gaussian mixture modelling to identify regions of high tau PET burden and regions with the earliest changes in tau binding for each cohort separately. We estimated regional tau PET burden as a function of cortical amyloid burden for both cohorts. Finally, we compared the temporal pattern of tau PET burden relative to that of amyloid. FINDINGS: We included 137 people with Down syndrome (mean age 38·5 years [SD 8·2], 74 [54%] male, and 63 [46%] female), 49 individuals with autosomal-dominant Alzheimer's disease (mean age 43·9 years [11·2], 22 [45%] male, and 27 [55%] female), and 85 familial controls, pooled from across both studies (mean age 41·5 years [12·1], 28 [33%] male, and 57 [67%] female), who satisfied the PET quality-control procedure for tau-PET imaging processing. 134 (98%) people with Down syndrome, 44 (90%) with autosomal-dominant Alzheimer's disease, and 77 (91%) controls also completed an amyloid PET scan within 3 years of tau PET imaging. Spatially, tau PET burden was observed most frequently in subcortical and medial temporal regions in people with Down syndrome, and within the medial temporal lobe in people with autosomal-dominant Alzheimer's disease. Across the brain, people with Down syndrome had greater concentrations of tau for a given level of amyloid compared with people with autosomal-dominant Alzheimer's disease. Temporally, increases in tau were more strongly associated with increases in amyloid for people with Down syndrome compared with autosomal-dominant Alzheimer's disease. INTERPRETATION: Although the general progression of amyloid followed by tau is similar for people Down syndrome and people with autosomal-dominant Alzheimer's disease, we found subtle differences in the spatial distribution, timing, and magnitude of the tau burden between these two cohorts. These differences might have important implications; differences in the temporal pattern of tau accumulation might influence the timing of drug administration in clinical trials, whereas differences in the spatial pattern and magnitude of tau burden might affect disease progression. FUNDING: None.

α-Synuclein seed amplification assay detects Lewy body co-pathology in autosomal dominant Alzheimer's disease late in the disease course and dependent on Lewy pathology burden.

INTRODUCTION: Amyloid beta and tau pathology are the hallmarks of sporadic Alzheimer's disease (AD) and autosomal dominant AD (ADAD). However, Lewy body pathology (LBP) is found in ≈ 50% of AD and ADAD brains. METHODS: Using an α-synuclein seed amplification assay (SAA) in cerebrospinal fluid (CSF) from asymptomatic (n = 26) and symptomatic (n = 27) ADAD mutation carriers, including 12 with known neuropathology, we investigated the timing of occurrence and prevalence of SAA positive reactivity in ADAD in vivo. RESULTS: No asymptomatic participant and only 11% (3/27) of the symptomatic patients tested SAA positive. Neuropathology revealed LBP in 10/12 cases, primarily affecting the amygdala or the olfactory areas. In the latter group, only the individual with diffuse LBP reaching the neocortex showed α-synuclein seeding activity in CSF in vivo. DISCUSSION: Results suggest that in ADAD LBP occurs later than AD pathology and often as amygdala- or olfactory-predominant LBP, for which CSF α-synuclein SAA has low sensitivity. HIGHLIGHTS: Cerebrospinal fluid (CSF) real-time quaking-induced conversion (RT-QuIC) detects misfolded α-synuclein in ≈ 10% of symptomatic autosomal dominant Alzheimer's disease (ADAD) patients. CSF RT-QuIC does not detect α-synuclein seeding activity in asymptomatic mutation carriers. Lewy body pathology (LBP) in ADAD mainly occurs as olfactory only or amygdala-predominant variants. LBP develops late in the disease course in ADAD. CSF α-synuclein RT-QuIC has low sensitivity for focal, low-burden LBP.

Downstream Biomarker Effects of Gantenerumab or Solanezumab in Dominantly Inherited Alzheimer Disease: The DIAN-TU-001 Randomized Clinical Trial.

Importance: Effects of antiamyloid agents, targeting either fibrillar or soluble monomeric amyloid peptides, on downstream biomarkers in cerebrospinal fluid (CSF) and plasma are largely unknown in dominantly inherited Alzheimer disease (DIAD). Objective: To investigate longitudinal biomarker changes of synaptic dysfunction, neuroinflammation, and neurodegeneration in individuals with DIAD who are receiving antiamyloid treatment. Design, Setting, and Participants: From 2012 to 2019, the Dominantly Inherited Alzheimer Network Trial Unit (DIAN-TU-001) study, a double-blind, placebo-controlled, randomized clinical trial, investigated gantenerumab and solanezumab in DIAD. Carriers of gene variants were assigned 3:1 to either drug or placebo. The present analysis was conducted from April to June 2023. DIAN-TU-001 spans 25 study sites in 7 countries. Biofluids and neuroimaging from carriers of DIAD gene variants in the gantenerumab, solanezumab, and placebo groups were analyzed. Interventions: In 2016, initial dosing of gantenerumab, 225 mg (subcutaneously every 4 weeks) was increased every 8 weeks up to 1200 mg. In 2017, initial dosing of solanezumab, 400 mg (intravenously every 4 weeks) was increased up to 1600 mg every 4 weeks. Main Outcomes and Measures: Longitudinal changes in CSF levels of neurogranin, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), chitinase 3-like 1 protein (YKL-40), glial fibrillary acidic protein (GFAP), neurofilament light protein (NfL), and plasma levels of GFAP and NfL. Results: Of 236 eligible participants screened, 43 were excluded. A total of 142 participants (mean [SD] age, 44 [10] years; 72 female [51%]) were included in the study (gantenerumab, 52 [37%]; solanezumab, 50 [35%]; placebo, 40 [28%]). Relative to placebo, gantenerumab significantly reduced CSF neurogranin level at year 4 (mean [SD] ß = -242.43 [48.04] pg/mL; P < .001); reduced plasma GFAP level at year 1 (mean [SD] ß = -0.02 [0.01] ng/mL; P = .02), year 2 (mean [SD] ß = -0.03 [0.01] ng/mL; P = .002), and year 4 (mean [SD] ß = -0.06 [0.02] ng/mL; P < .001); and increased CSF sTREM2 level at year 2 (mean [SD] ß = 1.12 [0.43] ng/mL; P = .01) and year 4 (mean [SD] ß = 1.06 [0.52] ng/mL; P = .04). Solanezumab significantly increased CSF NfL (log) at year 4 (mean [SD] ß = 0.14 [0.06]; P = .02). Correlation analysis for rates of change found stronger correlations between CSF markers and fluid markers with Pittsburgh compound B positron emission tomography for solanezumab and placebo. Conclusions and Relevance: This randomized clinical trial supports the importance of fibrillar amyloid reduction in multiple AD-related processes of neuroinflammation and neurodegeneration in CSF and plasma in DIAD. Additional studies of antiaggregated amyloid therapies in sporadic AD and DIAD are needed to determine the utility of nonamyloid biomarkers in determining disease modification. Trial Registration: ClinicalTrials.gov Identifier: NCT04623242.

A multicenter, randomized, double-blind, placebo-controlled ascending dose study to evaluate the safety, tolerability, pharmacokinetics (PK) and pharmacodynamic (PD) effects of Posiphen in subjects with Early Alzheimer's Disease.

Background: Amyloid beta protein (Aß) is a treatment target in Alzheimer's Disease (AD). Lowering production of its parent protein, APP, has benefits in preclinical models. Posiphen binds to an iron-responsive element in APP mRNA and decreases translation of APP and Aß. To augment human data for Posiphen, we evaluated safety, tolerability and pharmacokinetic and pharmacodynamic (PD) effects on Aß metabolism using Stable Isotope Labeling Kinetic (SILK) analysis. Methods: Double-blind phase 1b randomized ascending dose clinical trial, at five sites, under an IRB-approved protocol. Participants with mild cognitive impairment or mild AD (Early AD) with positive CSF biomarkers were randomized (within each dose arm) to Posiphen or placebo. Pretreatment assessment included lumbar puncture for CSF. Participants took Posiphen or placebo for 21-23 days, then underwent CSF catheter placement, intravenous infusion of 13C6-leucine, and CSF sampling for 36 hours. Safety and tolerability were assessed through participant reports, EKG and laboratory tests. CSF SILK analysis measured Aß40, 38 and 42 with immunoprecipitation-mass spectrometry. Baseline and day 21 CSF APP, Aß and other biomarkers were measured with immunoassays. The Mini-Mental State Exam and ADAS-cog12 were given at baseline and day 21. Results: From June 2017 to December 2021, 19 participants were enrolled, in dose cohorts (6 active: 2 placebo) of 60 mg once/day and 60 mg twice/day; 1 participant was enrolled and completed 60 mg three times/day. 10 active drug and 5 placebo participants completed all study procedures. Posiphen was safe and well-tolerated. 8 participants had headaches related to CSF catheterization; 5 needed blood patches. Prespecified SILK analyses of Fractional Synthesis Rate (FSR) for CSF Aß40 showed no significant overall or dose-dependent effects of Posiphen vs. placebo. Comprehensive multiparameter modeling of APP kinetics supported dose-dependent lowering of APP production by Posiphen. Cognitive measures and CSF biomarkers did not change significantly from baseline to 21 days in Posiphen vs placebo groups. Conclusions: Posiphen was safe and well-tolerated in Early AD. A multicenter SILK study was feasible. Findings are limited by small sample size but provide additional supportive safety and PK data. Comprehensive modeling of biomarker dynamics using SILK data may reveal subtle drug effects. Trial registration: NCT02925650 on clinicaltrials.gov.

Biomarker-based staging of Alzheimer disease: rationale and clinical applications.

Disease staging, whereby the spatial extent and load of brain pathology are used to estimate the severity of Alzheimer disease (AD), is pivotal to the gold-standard neuropathological diagnosis of AD. Current in vivo diagnostic frameworks for AD are based on abnormal concentrations of amyloid-ß and tau in the cerebrospinal fluid or on PET scans, and breakthroughs in molecular imaging have opened up the possibility of in vivo staging of AD. Focusing on the key principles of disease staging shared across several areas of medicine, this Review highlights the potential for in vivo staging of AD to transform our understanding of preclinical AD, refine enrolment criteria for trials of disease-modifying therapies and aid clinical decision-making in the era of anti-amyloid therapeutics. We provide a state-of-the-art review of recent biomarker-based AD staging systems and highlight their contributions to the understanding of the natural history of AD. Furthermore, we outline hypothetical frameworks to stage AD severity using more accessible fluid biomarkers. In addition, by applying amyloid PET-based staging to recently published anti-amyloid therapeutic trials, we highlight how biomarker-based disease staging frameworks could illustrate the numerous pathological changes that have already taken place in individuals with mildly symptomatic AD. Finally, we discuss challenges related to the validation and standardization of disease staging and provide a forward-looking perspective on potential clinical applications.

Evaluation of Exploratory Fluid Biomarker Results from a Phase 1 Senolytic Trial in Mild Alzheimer's Disease.

Senescent cell accumulation contributes to the progression of age-related disorders including Alzheimer's disease (AD). Clinical trials evaluating senolytics, drugs that clear senescent cells, are underway, but lack standardized outcome measures. Our team recently published data from the first open-label trial to evaluate senolytics (dasatinib plus quercetin) in AD. After 12-weeks of intermittent treatment, we reported brain exposure to dasatinib, favorable safety and tolerability, and modest post-treatment changes in cerebrospinal fluid (CSF) inflammatory and AD biomarkers using commercially available assays. Herein, we present more comprehensive exploratory analyses of senolytic associated changes in AD relevant proteins, metabolites, lipids, and transcripts measured across blood, CSF, and urine. These analyses included mass spectrometry for precise quantification of amyloid beta (Aß) and tau in CSF; immunoassays to assess senescence associated secretory factors in plasma, CSF, and urine; mass spectrometry analysis of urinary metabolites and lipids in blood and CSF; and transcriptomic analyses relevant to chronic stress measured in peripheral blood cells. Levels of Aß and tau species remained stable. Targeted cytokine and chemokine analyses revealed treatment-associated increases in inflammatory plasma fractalkine and MMP-7 and CSF IL-6. Urinary metabolites remained unchanged. Modest treatment-associated lipid profile changes suggestive of decreased inflammation were observed both peripherally and centrally. Blood transcriptomic analysis indicated downregulation of inflammatory genes including FOS, FOSB, IL1ß, IL8, JUN, JUNB, PTGS2. These data provide a foundation for developing standardized outcome measures across senolytic studies and indicate distinct biofluid-specific signatures that will require validation in future studies. ClinicalTrials.gov: NCT04063124.

Comparison of cerebrospinal fluid, plasma and neuroimaging biomarker utility in Alzheimer's disease.

Alzheimer's disease biomarkers are crucial to understanding disease pathophysiology, aiding accurate diagnosis and identifying target treatments. Although the number of biomarkers continues to grow, the relative utility and uniqueness of each is poorly understood as prior work has typically calculated serial pairwise relationships on only a handful of markers at a time. The present study assessed the cross-sectional relationships among 27 Alzheimer's disease biomarkers simultaneously and determined their ability to predict meaningful clinical outcomes using machine learning. Data were obtained from 527 community-dwelling volunteers enrolled in studies at the Charles F. and Joanne Knight Alzheimer Disease Research Center at Washington University in St Louis. We used hierarchical clustering to group 27 imaging, CSF and plasma measures of amyloid beta, tau [phosphorylated tau (p-tau), total tau t-tau)], neuronal injury and inflammation drawn from MRI, PET, mass-spectrometry assays and immunoassays. Neuropsychological and genetic measures were also included. Random forest-based feature selection identified the strongest predictors of amyloid PET positivity across the entire cohort. Models also predicted cognitive impairment across the entire cohort and in amyloid PET-positive individuals. Four clusters emerged reflecting: core Alzheimer's disease pathology (amyloid and tau), neurodegeneration, AT8 antibody-associated phosphorylated tau sites and neuronal dysfunction. In the entire cohort, CSF p-tau181/Aß40lumi and Aß42/Aß40lumi and mass spectrometry measurements for CSF pT217/T217, pT111/T111, pT231/T231 were the strongest predictors of amyloid PET status. Given their ability to denote individuals on an Alzheimer's disease pathological trajectory, these same markers (CSF pT217/T217, pT111/T111, p-tau/Aß40lumi and t-tau/Aß40lumi) were largely the best predictors of worse cognition in the entire cohort. When restricting analyses to amyloid-positive individuals, the strongest predictors of impaired cognition were tau PET, CSF t-tau/Aß40lumi, p-tau181/Aß40lumi, CSF pT217/217 and pT205/T205. Non-specific CSF measures of neuronal dysfunction and inflammation were poor predictors of amyloid PET and cognitive status. The current work utilized machine learning to understand the interrelationship structure and utility of a large number of biomarkers. The results demonstrate that, although the number of biomarkers has rapidly expanded, many are interrelated and few strongly predict clinical outcomes. Examining the entire corpus of available biomarkers simultaneously provides a meaningful framework to understand Alzheimer's disease pathobiological change as well as insight into which biomarkers may be most useful in Alzheimer's disease clinical practice and trials.

Clinical validation of the PrecivityAD2 blood test: A mass spectrometry-based test with algorithm combining %p-tau217 and Aß42/40 ratio to identify presence of brain amyloid.

BACKGROUND: With the availability of disease-modifying therapies for Alzheimer's disease (AD), it is important for clinicians to have tests to aid in AD diagnosis, especially when the presence of amyloid pathology is a criterion for receiving treatment. METHODS: High-throughput, mass spectrometry-based assays were used to measure %p-tau217 and amyloid beta (Aß)42/40 ratio in blood samples from 583 individuals with suspected AD (53% positron emission tomography [PET] positive by Centiloid > 25). An algorithm (PrecivityAD2 test) was developed using these plasma biomarkers to identify brain amyloidosis by PET. RESULTS: The area under the receiver operating characteristic curve (AUC-ROC) for %p-tau217 (0.94) was statistically significantly higher than that for p-tau217 concentration (0.91). The AUC-ROC for the PrecivityAD2 test output, the Amyloid Probability Score 2, was 0.94, yielding 88% agreement with amyloid PET. Diagnostic performance of the APS2 was similar by ethnicity, sex, age, and apoE4 status. DISCUSSION: The PrecivityAD2 blood test showed strong clinical validity, with excellent agreement with brain amyloidosis by PET.

Deconstructing pathological tau by biological process in early stages of Alzheimer disease: a method for quantifying tau spatial spread in neuroimaging.

BACKGROUND: Neuroimaging studies often quantify tau burden in standardized brain regions to assess Alzheimer disease (AD) progression. However, this method ignores another key biological process in which tau spreads to additional brain regions. We have developed a metric for calculating the extent tau pathology has spread throughout the brain and evaluate the relationship between this metric and tau burden across early stages of AD. METHODS: 445 cross-sectional participants (aged ≥ 50) who had MRI, amyloid PET, tau PET, and clinical testing were separated into disease-stage groups based on amyloid positivity and cognitive status (older cognitively normal control, preclinical AD, and symptomatic AD). Tau burden and tau spatial spread were calculated for all participants. FINDINGS: We found both tau metrics significantly elevated across increasing disease stages (p < 0.0001) and as a function of increasing amyloid burden for participants with preclinical (p < 0.0001, p = 0.0056) and symptomatic (p = 0.010, p = 0.0021) AD. An interaction was found between tau burden and tau spatial spread when predicting amyloid burden (p = 0.00013). Analyses of slope between tau metrics demonstrated more spread than burden in preclinical AD (ß = 0.59), but then tau burden elevated relative to spread (ß = 0.42) once participants had symptomatic AD, when the tau metrics became highly correlated (R = 0.83). INTERPRETATION: Tau burden and tau spatial spread are both strong biomarkers for early AD but provide unique information, particularly at the preclinical stage. Tau spatial spread may demonstrate earlier changes than tau burden which could have broad impact in clinical trial design. FUNDING: This research was supported by the Knight Alzheimer Disease Research Center (Knight ADRC, NIH grants P30AG066444, P01AG026276, P01AG003991), Dominantly Inherited Alzheimer Network (DIAN, NIH grants U01AG042791, U19AG03243808, R01AG052550-01A1, R01AG05255003), and the Barnes-Jewish Hospital Foundation Willman Scholar Fund.

Disease staging of Alzheimer's disease using a CSF-based biomarker model.

Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic workup of dementia in clinical practice and the design of clinical trials. In this study, we used the Subtype and Stage Inference (SuStaIn) algorithm to establish a robust biological staging model for AD using cerebrospinal fluid (CSF) biomarkers. Our analysis involved 426 participants from BioFINDER-2 and was validated in 222 participants from the Knight Alzheimer Disease Research Center cohort. SuStaIn identified a singular biomarker sequence and revealed that five CSF biomarkers effectively constituted a reliable staging model (ordered: Aß42/40, pT217/T217, pT205/T205, MTBR-tau243 and non-phosphorylated mid-region tau). The CSF stages (0-5) demonstrated a correlation with increased abnormalities in other AD-related biomarkers, such as Aß-PET and tau-PET, and aligned with longitudinal biomarker changes reflective of AD progression. Higher CSF stages at baseline were associated with an elevated hazard ratio of clinical decline. This study highlights a common molecular pathway underlying AD pathophysiology across all patients, suggesting that a single CSF collection can accurately indicate the presence of AD pathologies and characterize the stage of disease progression. The proposed staging model has implications for enhancing diagnostic and prognostic assessments in both clinical practice and the design of clinical trials.

Use of a Blood Biomarker Test Improves Economic Utility in the Evaluation of Older Patients Presenting with Cognitive Impairment.

More than 16 million Americans living with cognitive impairment warrant a diagnostic evaluation to determine the cause of this disorder. The recent availability of disease-modifying therapies for Alzheimer's disease (AD) is expected to significantly drive demand for such diagnostic testing. Accurate, accessible, and affordable methods are needed. Blood biomarkers (BBMs) offer advantages over usual care amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in these regards. This study used a budget impact model to assess the economic utility of the PrecivityAD® blood test, a clinically validated BBM test for the evaluation of brain amyloid, a pathological hallmark of AD. The model compared 2 scenarios: (1) baseline testing involving usual care practice, and (2) early use of a BBM test before usual care CSF and PET biomarker use. At a modest 40% adoption rate, the BBM test scenario had comparable sensitivity and specificity to the usual care scenario and showed net savings in the diagnostic work-up of $3.57 million or $0.30 per member per month in a 1 million member population, translating to over $1B when extrapolated to the US population as a whole and representing a 11.4% cost reduction. Savings were driven by reductions in the frequency and need for CSF and PET testing. Additionally, BBM testing was associated with a cost savings of $643 per AD case identified. Use of the PrecivityAD blood test in the clinical care pathway may prevent unnecessary testing, provide cost savings, and reduce the burden on both patients and health plans.

Performance of the Lumipulse plasma Aß42/40 and pTau181 immunoassays in the detection of amyloid pathology.

INTRODUCTION: This study evaluated the performance of the Lumipulse plasma beta-amyloid (Aß) 42/40 and pTau181 compared to other assays to detect an abnormal amyloid-positron emission tomography (PET). METHODS: Plasma samples from cognitively unimpaired (N = 179) and MCI/AD dementia (N = 36) individuals were retrospectively evaluated. Plasma Aß42/40 and pTau181 were measured using the Lumipulse and Simoa immunoassays. An immunoprecipitation mass spectrometry (IP-MS) assay for plasma Aß42/40 was also evaluated. Amyloid-PET status was the outcome measure. RESULTS: Lumipulse and IP-MS Aß42/40 exhibited the highest diagnostic accuracy for detecting an abnormal amyloid-PET (areas under the curve [AUCs] of 0.81 and 0.84, respectively). The Lumipulse and Simoa pTau181 assays exhibited lower performance (AUCs of 0.74 and 0.72, respectively). The Simoa Aß42/40 assay demonstrated the lowest diagnostic accuracy (AUC 0.57). Combining Aß42/40 and pTau181 did not significantly improve performance over Aß42/40 alone for Lumipulse (AUC 0.83) or over pTau181 alone for Simoa (AUC 0.71). DISCUSSION: The Lumipulse Aß42/40 assay showed similar performance to the IP-MS Aß42/40 assay for detection of an abnormal amyloid-PET; and both assays performed better than the two p-tau181 immunoassays. The Simoa Aß42/Aß40 assay was the least accurate at predicting an abnormal amyloid-PET status. Highlights: Lumipulse plasma Aß42/Aß40 AUC for abnormal amyloid-PET detection was 0.81.This performance was comparable to previously reported IP-MS and higher than Simoa.Performance of Alzheimer's disease blood biomarkers varies between assays.

Highly accurate blood test for Alzheimer's disease is similar or superior to clinical cerebrospinal fluid tests.

With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-ß (Aß) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aß42/40 and p-tau181/Aß42. The primary and secondary outcomes were detection of brain Aß or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aß PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aß PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.

Timing of Biomarker Changes in Sporadic Alzheimer's Disease in Estimated Years from Symptom Onset.

OBJECTIVE: A clock relating amyloid positron emission tomography (PET) to time was used to estimate the timing of biomarker changes in sporadic Alzheimer disease (AD). METHODS: Research participants were included who underwent cerebrospinal fluid (CSF) collection within 2 years of amyloid PET. The ages at amyloid onset and AD symptom onset were estimated for each individual. The timing of change for plasma, CSF, imaging, and cognitive measures was calculated by comparing restricted cubic splines of cross-sectional data from the amyloid PET positive and negative groups. RESULTS: The amyloid PET positive sub-cohort (n = 118) had an average age of 70.4 ± 7.4 years (mean ± standard deviation) and 16% were cognitively impaired. The amyloid PET negative sub-cohort (n = 277) included individuals with low levels of amyloid plaque burden at all scans who were cognitively unimpaired at the time of the scans. Biomarker changes were detected 15-19 years before estimated symptom onset for CSF Aß42/Aß40, plasma Aß42/Aß40, CSF pT217/T217, and amyloid PET; 12-14 years before estimated symptom onset for plasma pT217/T217, CSF neurogranin, CSF SNAP-25, CSF sTREM2, plasma GFAP, and plasma NfL; and 7-9 years before estimated symptom onset for CSF pT205/T205, CSF YKL-40, hippocampal volumes, and cognitive measures. INTERPRETATION: The use of an amyloid clock enabled visualization and analysis of biomarker changes as a function of estimated years from symptom onset in sporadic AD. This study demonstrates that estimated years from symptom onset based on an amyloid clock can be used as a continuous staging measure for sporadic AD and aligns with findings in autosomal dominant AD. ANN NEUROL 2024;95:951-965.

Examining amyloid reduction as a surrogate endpoint through latent class analysis using clinical trial data for dominantly inherited Alzheimer's disease.

INTRODUCTION: Increasing evidence suggests that amyloid reduction could serve as a plausible surrogate endpoint for clinical and cognitive efficacy. The double-blind phase 3 DIAN-TU-001 trial tested clinical and cognitive declines with increasing doses of solanezumab or gantenerumab. METHODS: We used latent class (LC) analysis on data from the Dominantly Inherited Alzheimer Network Trials Unit 001 trial to test amyloid positron emission tomography (PET) reduction as a potential surrogate biomarker. RESULTS: LC analysis categorized participants into three classes: amyloid no change, amyloid reduction, and amyloid growth, based on longitudinal amyloid Pittsburgh compound B PET standardized uptake value ratio data. The amyloid-no-change class was at an earlier disease stage for amyloid amounts and dementia. Despite similar baseline characteristics, the amyloid-reduction class exhibited reductions in the annual decline rates compared to the amyloid-growth class across multiple biomarker, clinical, and cognitive outcomes. DISCUSSION: LC analysis indicates that amyloid reduction is associated with improved clinical outcomes and supports its use as a surrogate biomarker in clinical trials. HIGHLIGHTS: We used latent class (LC) analysis to test amyloid reduction as a surrogate biomarker. Despite similar baseline characteristics, the amyloid-reduction class exhibited remarkably better outcomes compared to the amyloid-growth class across multiple measures. LC analysis proves valuable in testing amyloid reduction as a surrogate biomarker in clinical trials lacking significant treatment effects.

Baseline levels and longitudinal rates of change in plasma Aß42/40 among self-identified Black/African American and White individuals.

Objective: The use of blood-based biomarkers of Alzheimer disease (AD) may facilitate access to biomarker testing of groups that have been historically under-represented in research. We evaluated whether plasma Aß42/40 has similar or different baseline levels and longitudinal rates of change in participants racialized as Black or White. Methods: The Study of Race to Understand Alzheimer Biomarkers (SORTOUT-AB) is a multi-center longitudinal study to evaluate for potential differences in AD biomarkers between individuals racialized as Black or White. Plasma samples collected at three AD Research Centers (Washington University, University of Pennsylvania, and University of Alabama-Birmingham) underwent analysis with C2N Diagnostics' PrecivityAD™ blood test for Aß42 and Aß40. General linear mixed effects models were used to estimate the baseline levels and rates of longitudinal change for plasma Aß measures in both racial groups. Analyses also examined whether dementia status, age, sex, education, APOE ε4 carrier status, medical comorbidities, or fasting status modified potential racial differences. Results: Of the 324 Black and 1,547 White participants, there were 158 Black and 759 White participants with plasma Aß measures from at least two longitudinal samples over a mean interval of 6.62 years. At baseline, the group of Black participants had lower levels of plasma Aß40 but similar levels of plasma Aß42 as compared to the group of White participants. As a result, baseline plasma Aß42/40 levels were higher in the Black group than the White group, consistent with the Black group having lower levels of amyloid pathology. Racial differences in plasma Aß42/40 were not modified by age, sex, education, APOE ε4 carrier status, medical conditions (hypertension and diabetes), or fasting status. Despite differences in baseline levels, the Black and White groups had a similar longitudinal rate of change in plasma Aß42/40. Interpretation: Black individuals participating in AD research studies had a higher mean level of plasma Aß42/40, consistent with a lower level of amyloid pathology, which, if confirmed, may imply a lower proportion of Black individuals being eligible for AD clinical trials in which the presence of amyloid is a prerequisite. However, there was no significant racial difference in the rate of change in plasma Aß42/40, suggesting that amyloid pathology accumulates similarly across racialized groups.

Systematic proteomics in Autosomal dominant Alzheimer's disease reveals decades-early changes of CSF proteins in neuronal death, and immune pathways.

Background: To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies. Methods: We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models. Findings: We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aß42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89). Interpretation: Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs. Funding: Proteomic data generation was supported by NIH: RF1AG044546.