Positron Emission Tomography Status Research Articles

A-086 Clinical Performance of a Plasma ATN Panel for Assessment of Alzheimer’s Disease

Abstract Background In recent years, the progression of Alzheimer’s disease has widely been characterized through the utilization of an ATN classification system consisting of biomarkers for three areas of neuropathologic change: development of Amyloid associated plaques, formation of neurofibrillary tangles associated with Tau proteins, and onset of Neurodegeneration. However, the assessment of biomarkers related to each of these stages has predominantly relied on neuroimaging or CSF measurements which are costly and invasive. With the advent of high sensitivity immunoassays, measurements of ATN biomarkers in venous plasma has become possible and would provide a more accessible and affordable tool to assist physicians with the diagnosis of AD. Methods Assessment of amyloid status was performed by determining the ratio of amyloid-beta 1-42 to amyloid-beta 1-40 (Aβ42/40) in plasma where measurements for individual analytes were performed in parallel on a SysmexTM HISCL-5000 platform. Assessments of tau and neurodegeneration were performed using a Roche cobas® e801 platform to measure phosphorylated-tau181 (pTau181) and neurofilament light chain (NfL), respectively. As these assays have not yet received FDA approval, each was validated internally using CLSI guidance. The clinical efficacy of each assay was investigated using 200 clinical specimens with amyloid status defined using positron emission tomography (PET) imaging. Assay results were analyzed using receiver operator characteristic (ROC) analysis with respect to amyloid PET results. In addition, results from the clinical cohort were also assessed with respect: amyloid PET centiloid results, clinically defined cognitive status, and mental state as determined using a Mini-Mental State Exam (MMSE). Results ROC analysis of clinical sample results from validated assays produced an area-under-the-curve (AUC) of 0.941 for Aβ42/40, 0.847 for pTau181, and 0.666 for NfL. These results are consistent with amyloid PET status as well as the progression of AD along the ATN continuum. With respect to Aβ+ subjects, Aβ42/40 results did not change due to worsening cognitive status, increasing amyloid PET results, or worsening MMSE scores. Levels of pTau181, however, were found to increase with worsening cognitive status (p < 0.01), increasing amyloid PET centiloid results (p < 0.05), as well as worsening MMSE scores (p < 0.05). In addition, NfL levels become elevated with worsening MMSE scores (p < 0.01). Conclusions The clinical utility of the plasma ATN panel was found to be appropriate for assisting with diagnosis of AD and is now available for physician use.

Optimizing cutpoints for clinical interpretation of brain amyloid status using plasma p-tau217 immunoassays.

We aimed to evaluate clinical interpretation cutpoints for two plasma phosphorylated tau (p-tau)217 assays (ALZpath and Lumipulse) as predictors of amyloid status for implementation in clinical practice. Clinical performance of plasma p-tau217 against amyloid positron emission tomography status was evaluated in participants with mild cognitive impairment or mild dementia (n=427). Using a one-cutpoint approach (negative/positive), neither assay achieved ≥ 90% in both sensitivity and specificity. A two-cutpoint approach yielding 92% sensitivity and 96% specificity provided the desired balance of false positives and false negatives, while categorizing 20% and 39% of results as indeterminate for the Lumipulse and ALZpath assays, respectively. This study provides a systematic framework for selection of assay-specific cutpoints for clinical use of plasma p-tau217 for determination of amyloid status. Our findings suggest that a two-cutpoint approach may have advantages in optimizing diagnostic accuracy while minimizing potential harm from false positive results. Phosphorylated tau (p-tau)217 cutpoints for detection of amyloid pathology were established. A two-cutpoint approach exhibited the best performance for clinical laboratory use. p-tau217 assays differed in the percentage of results categorized as intermediate.

Diffusion MRI relates to plasma Aβ42/40 in PET negative participants without dementia.

Magnetic resonance imaging (MRI) biomarkers are needed for indexing early biological stages of Alzheimer's disease (AD), such as plasma amyloid-β (Aβ42/40) positivity in Aβ positron emission tomography (PET) negative individuals. Diffusion free-water (FW) MRI was acquired in individuals with normal cognition (NC) and mild cognitive impairment (MCI) with Aβ plasma-/PET- (NC=22, MCI=60), plasma+/PET- (NC=5, MCI=20), and plasma+/PET+ (AD dementia=21) biomarker status. Gray and white matter FW and fractional anisotropy (FAt) were compared cross-sectionally and the relationships between imaging, plasma and PET biomarkers were assessed. Plasma+/PET- demonstrated increased FW (24 regions) and decreased FAt (66 regions) compared to plasma-/PET-. FW (16 regions) and FAt (51 regions) were increased in plasma+/PET+ compared to plasma+/PET-. Composite brain FW correlated with plasma Aβ42/40 and p-tau181. FW imaging changes distinguish plasma Aβ42/40 positive and negative groups, independent of group differences in cognitive status, Aβ PET status, and other plasma biomarkers (i.e., t-tau, p-tau181, glial fibrillary acidic protein, neurofilament light). Plasma Aβ42/40 positivity is associated with brain microstructure decline. Plasma+/PET- demonstrated increased FW in 24 total GM and WM regions. Plasma+/PET- demonstrated decreased FAt in 66 total GM and WM regions. Whole-brain FW correlated with plasma Aβ42/40 and p-tau181 measures. Plasma+/PET- demonstrated decreased cortical volume and thickness.

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-β (Aβ) 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 Aβ42/40 and p-tau181/Aβ42. The primary and secondary outcomes were detection of brain Aβ 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 Aβ 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 Aβ 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.

The Use of Event Related Potentials to Predict Amyloid PET Status Among Patients from a Memory Disorders Clinic.

Amyloid positron emission tomography (PET) scans provide in vivo evidence of Alzheimer's disease (AD); however, their high cost limits their use in standard clinical care. Event related potentials (ERPs) may represent an inexpensive and non-invasive additional method for detecting AD pathology. We investigated whether ERPs, along with neuropsychological data, serve as predictors of amyloid PET status in patients with memory complaints. Veterans aged 50-100 were recruited from a memory disorders clinic. Participants underwent a neuropsychological battery and an ERP auditory oddball protocol. Twenty-eight patients had a positive amyloid PET scan, and thirty-nine patients had a negative scan. ERP-P200 target amplitude and P200 standard latency were predictors of amyloid PET status. When submitting to ROC analysis, P200 standard latency exhibited the highest specificity and sensitivity in predicting amyloid PET positivity, correctly classifying the amyloid PET status for 86% of patients. ERP-P200 measures are strong indicators of amyloid-β presence in patients from a memory disorder clinic. Increased P200 amplitude and decreased P200 latency in patients with a positive amyloid PET scan may be attributed to hyperactivation of perceptual bottom-up processes compensating for AD-related synaptic loss in the fronto-parietal networks.

Contribution of clinical information to the predictive performance of plasma Aβ levels for Aβ PET positivity

AbstractBackgroundEarly detection of β‐amyloid (Aβ) accumulation, a major biomarker for Alzheimer’s disease (AD), has become important. While Aβ deposition can be detected by positron emission tomography (PET), practical fluid Aβ biomarker is also being developed recently. In the present study, we aimed to determine whether APOE genotypes, age, and cognitive status increase the predictive performance of fluid Aβ levels for amyloid PET positivity.MethodsWe recruited 488 participants who underwent both plasma Aβ and Aβ PET studies (Cohort 1) and 217 participants who underwent both cerebrospinal fluid (CSF) Aβ and Aβ PET studies (Cohort 2). Plasma and CSF samples were analyzed using ABtest‐MS, an antibody‐free liquid chromatography‐differential mobility spectrometry‐triple quadrupole mass spectrometry method and INNOTEST enzyme‐linked immunosorbent assay kits, respectively. To evaluate the predictive performance of plasma Aβ and CSF Aβ, respectively, logistic regression and receiver operating characteristic analyses were performed.ResultsWhen predicting Aβ PET status, both plasma Aβ42/40 ratio and CSF Aβ42 showed high accuracy (plasma Aβ area under the curve (AUC) 0.814; CSF Aβ AUC 0.848). In the plasma Aβ models, the AUC values were higher than plasma Aβ alone model, when the models were combined with either cognitive stage (p < 0.001) or APOE genotype (p = 0.011). On the other hand, there was no difference between the CSF Aβ models, when these variables were added.ConclusionsPlasma Aβ might be a useful predictor of Aβ PET status as much as CSF Aβ, particularly when considered with clinical information.

Plasma Aβ42/Aβ40 and phospho-tau217 concentration ratios increase the accuracy of amyloid PET classification in preclinical Alzheimer's disease.

Incorporating blood-based Alzheimer's disease biomarkers such as tau and amyloid beta (Aβ) into screening algorithms may improve screening efficiency. Plasma Aβ, phosphorylated tau (p-tau)181, and p-tau217 concentration levels from AHEAD 3-45 study participants were measured using mass spectrometry. Tau concentration ratios for each proteoform were calculated to normalize for inter-individual differences. Receiver operating characteristic (ROC) curve analysis was performed for each biomarker against amyloid positivity, defined by>20 Centiloids. Mixture of experts analysis assessed the value of including tau concentration ratios into the existing predictive algorithm for amyloid positron emission tomography status. The area under the receiver operating curve (AUC) was 0.87 for Aβ42/Aβ40, 0.74 for phosphorylated variant p-tau181 ratio (p-tau181/np-tau181), and 0.92 for phosphorylated variant p-tau217 ratio (p-tau217/np-tau217). The Plasma Predicted Centiloid (PPC), a predictive model including p-tau217/np-tau217, Aβ42/Aβ40, age, and apolipoprotein E improved AUC to 0.95. Including plasma p-tau217/np-tau217 along with Aβ42/Aβ40 in predictive algorithms may streamline screening preclinical individuals into anti-amyloid clinical trials. gov Identifier: NCT04468659 HIGHLIGHTS: The addition of plasma phosphorylated variant p-tau217 ratio (p-tau217/np-tau217) significantly improved plasma biomarker algorithms for identifying preclinical amyloid positron emission tomography positivity. Prediction performance at higher NAV Centiloid levels was improved with p-tau217/np-tau217. All models generated for this study are incorporated into the Plasma Predicted Centiloid (PPC) app for public use.

48 Psychometric properties of DCTclock™ with commonly used neuropsychological tests and their combined ability to predict Beta-Amyloid Positron Emission Tomography Status

Objective:Sensitive and non-invasive methods of screening for early-stage Alzheimer’s disease (AD) are urgently needed. The digital clock drawing test (DCTclockTM) is an established and well-researched neuropsychological tool that can aid in early detection of dementia. Other simple, yet sensitive, neuropsychological measures able to detect early stages of AD include Trail Making Tests (TMT). We investigated the psychometric properties of DCTclockTM with TMT-A and TMT-B. We then sought to understand the degree to which neuropsychological tools (i.e., DCTclockTM, TMT-A, and B) versus the Montreal Cognitive Assessment (MoCA) predict beta-amyloid (Aß) positron emission tomography (PET) status (positive or negative) in cognitively normal individuals.Participants and Methods:Participants included a sample of cognitively normal older adults (n= 59, M age = 69.2, F = 64%) recruited from the Butler Memory and Aging Program. The Linus Health DCTclockTM uses a digital pen to capture traditional clock drawing test performance and advanced analytics to evaluate the drawing process for indicators of cognitive difficulty. DCTclockTM may have overlapping cognitive properties with TMT measures, like efficiency, processing speed, and spatial reasoning. We compared latency measures (i.e., process efficiency, clock face speed, average latency, and processing speed) and spatial reasoning of the DCTclockTM to z-scores of TMT-A and TMT-B to detect any overlapping psychometric properties. Verbal fluency was included for discriminant validity. We then ran logistic regressions on a subset of the sample to compare neuropsychological tests (DCTclockTM total score [score that captures overall performance], TMT-A/B, and verbal fluency) to the MoCA, a commonly used cognitive screening tool, in determining PET status.Results:Highly correlated (r > .7) DCTclockTM variables were excluded. We found statistically significant correlations between some DCTclockTM measures and TMT-A/B, like DCTclockTM drawing process efficiency and TMT-A and TMT-B (r= .45, p< .001, r=.29, p< .026, respectively), and DCTclockTM average latency and TMT-A and TMT-B (r=.3, p< .024, r= .26, p< .044, respectively). No statistically significant associations were found between any DCTclockTM measures and verbal fluency, or between DCTclockTM spatial reasoning and TMT-A/B. We then investigated the effect of these neuropsychological tests (DCTclockTM total score, TMT-A/B, verbal fluency) and age on the likelihood of PET positivity (subset of sample, total PET, n=31). The model was statistically significant (x2 (5) = 15.35, p< .01). The model explained 53% (Nagelkerke R2) of the variance in PET status and correctly classified 74.2% of cases. DCTclockTM was the only significant predictor (p< .02), after controlling for TMT-A, TMT-B, verbal fluency, and age. Comparatively, there was no effect of MoCA and age (total PET, n= 29) on the likelihood of PET positivity.Conclusions:Overall, these results suggest psychometric convergence on elements of DCTclockTM and TMT-A/B, while there was no association in spatial operations between DCTclockTM and TMT measures. Further, when compared to the MoCA, DCTclockTM and these commonly used neuropsychological tests (verbal fluency and TMT-A/B) were better predictors of PET status, primarily driven by the DCTclockTM. Digitized neuropsychological tools may provide additional metrics not captured by pen-and-paper tests that can detect AD-associated pathology.

5 Intraindividual Variability in Processing Speed on Digital Cognitive Assessments Differs by Amyloidosis Status in Cognitively Normal Older Adults

Objective:Intraindividual variability (IIV) is defined as fluctuations in an individual’s cognitive performance over time1. IIV has been identified as a marker of neurobiological disturbance making it a useful method for detecting changes in cognition among cognitively healthy individuals as well as those with prodromal syndromes2. IIV on laboratory-based computerized tasks has been linked with cognitive decline and conversion to mild cognitive impairment (MCI) and/or dementia (Haynes et al., 2017). Associations between IIV and AD risk factors including apolipoprotein (APOE) ε4 carrier status, neurodegeneration seen on brain imaging, and amyloid (Aß) Positron emission tomography (PET) scan status have also been observed1. Recent studies have demonstrated that evaluating IIV on smartphone-based digital cognitive assessments is feasible, has the capacity to differentiate between cognitively normal (CN) and MCI individuals, and may reduce barriers to cognitive assessment3. This study sought to evaluate whether such differences could be detected in CN participants with and without elevated AD risk.Participants and Methods:Participants (n=57) were cognitively normal older adults who previously received an Aß PET scan through the Butler Hospital Memory and Aging Program. The sample consisted of primarily non-Hispanic (n=49, 86.0%), White (n=52, 91.2%), college-educated (M=16.65 years), females (n=39, 68.4%). The average age of the sample was 68 years old. Approximately 42% of the sample (n=24) received a positive PET scan result. Participants completed brief cognitive assessments (i.e., 3-4 minutes) three times per day for eight days (i.e., 24 sessions) using the Mobile Monitoring of Cognitive Change (M2C2) application, a mobile app-based cognitive testing platform developed as part of the National Institute of Aging’s Mobile Toolbox initiative (Sliwinski et al., 2018). Participants completed visual working memory, processing speed, and episodic memory tasks on the M2C2 platform. Intraindividual standard deviations (ISDs) across trials were computed for each person at each time point (Hultsch et al., 2000). Higher ISD values indicate more variability in performance. Linear mixed effects models were utilized to examine whether differences in IIV existed based on PET scan status while controlling for age, sex at birth, and years of education.Results:n interaction between PET status and time was observed on the processing speed task such that Aß- individuals were less variable over the eight assessment days compared to Aß + individuals (B= -5.79, SE=2.67, p=.04). No main or interaction effects were observed on the visual working memory task or episodic memory task.Conclusions:Our finding that Aß- individuals demonstrate less variability over time on a measure of processing speed is consistent with prior work. No associations were found between IIV in other cognitive domains and PET status. As noted by Allaire and Marsiske (2005), IIV is not a consistent phenomenon across different cognitive domains. Therefore, identifying which tests are the most sensitive to early change is crucial. Additional studies in larger, more diverse samples are needed prior to widespread clinical use for early detection of AD.

Clinical utility of an antibody-free LC-MS method to detect brain amyloid deposition in cognitively unimpaired individuals from the screening visit of the A4 Study.

This study explored the ability of plasma amyloid beta (Aβ)42/Aβ40 to identify brain amyloid deposition in cognitively unimpaired (CU) individuals. Plasma Aβ was quantified with an antibody-free high-performance liquid chromatography tandem mass spectrometry method from Araclon Biotech (ABtest-MS) in a subset of 731 CU individuals from the screening visit of the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study, to assess associations of Aβ42/Aβ40 with Aβ positron emission tomography (PET). A model including Aβ42/Aβ40, age, apolipoprotein E ε4, and recruitment site identified Aβ PET status with an area under the curve of 0.88 and an overall accuracy of 81%. A plasma-based pre-screening step could save up to 42% of the total number of Aβ PET scans. ABtest-MS accurately identified brain amyloid deposition in a population of CU individuals, supporting its implementation in AD secondary prevention trials to reduce recruitment time and costs. Although a certain degree of heterogeneity is inherent to large and multicentric trials, ABtest-MS could be more robust to pre-analytical bias compared to other immunoprecipitation mass spectrometry methods. Plasma amyloid beta (Aβ)42/Aβ40 accurately identified brain Aβ deposition in cognitively unimpaired individuals from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study.The inclusion of the recruitment site in the predictive models has a non-negligible effect.A plasma biomarker-based model could reduce recruitment costs in Alzheimer's disease secondary prevention trials.Antibody-free liquid chromatography mass spectrometry methods may be more robust to pre-analytical variability than other platforms.

Contribution of clinical information to the predictive performance of plasma β-amyloid levels for amyloid positron emission tomography positivity.

Early detection of β-amyloid (Aβ) accumulation, a major biomarker for Alzheimer's disease (AD), has become important. As fluid biomarkers, the accuracy of cerebrospinal fluid (CSF) Aβ for predicting Aβ deposition on positron emission tomography (PET) has been extensively studied, and the development of plasma Aβ is beginning to receive increased attention recently. In the present study, we aimed to determine whether APOE genotypes, age, and cognitive status increase the predictive performance of plasma Aβ and CSF Aβ levels for Aβ PET positivity. We recruited 488 participants who underwent both plasma Aβ and Aβ PET studies (Cohort 1) and 217 participants who underwent both cerebrospinal fluid (CSF) Aβ and Aβ PET studies (Cohort 2). Plasma and CSF samples were analyzed using ABtest-MS, an antibody-free liquid chromatography-differential mobility spectrometry-triple quadrupole mass spectrometry method and INNOTEST enzyme-linked immunosorbent assay kits, respectively. To evaluate the predictive performance of plasma Aβ and CSF Aβ, respectively, logistic regression and receiver operating characteristic analyses were performed. When predicting Aβ PET status, both plasma Aβ42/40 ratio and CSF Aβ42 showed high accuracy (plasma Aβ area under the curve (AUC) 0.814; CSF Aβ AUC 0.848). In the plasma Aβ models, the AUC values were higher than plasma Aβ alone model, when the models were combined with either cognitive stage (p < 0.001) or APOE genotype (p = 0.011). On the other hand, there was no difference between the CSF Aβ models, when these variables were added. Plasma Aβ might be a useful predictor of Aβ deposition on PET status as much as CSF Aβ, particularly when considered with clinical information such as APOE genotype and cognitive stage.

The dynamics of plasma biomarkers across the Alzheimer’s continuum

BackgroundFailures in drug trials strengthen the necessity to further determine the neuropathological events during the development of Alzheimer’s disease (AD). We sought to investigate the dynamic changes and performance of plasma biomarkers across the entire Alzheimer’s continuum in the Chinese population.MethodsPlasma amyloid-β (Αβ)42, Aβ40, Aβ42/Aβ40, phosphorylated tau (p-tau)181, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were measured utilizing the ultrasensitive single-molecule array technology across the AD continuum (n=206), wherein Aβ status was defined by the values of cerebrospinal fluid (CSF) Aβ42 or Aβ positron emission tomography (PET). Their trajectories were compared with those of putative CSF biomarkers.ResultsPlasma GFAP and p-tau181 increased only in Aβ-positive individuals throughout aging, whereas NfL increased with aging regardless of Aβ status. Among the plasma biomarkers studied, GFAP was the one that changed first. It had a prominent elevation early in the cognitively unimpaired (CU) A+T− phase (CU A+T− phase: 97.10±41.29 pg/ml; CU A−T− phase: 49.18±14.39 pg/ml; p<0.001). From preclinical to symptomatic stages of AD, plasma GFAP started to rise sharply as soon as CSF Aβ became abnormal and continued to increase until reaching its highest level during the AD dementia phase. The greatest slope of change was seen in plasma GFAP. This is followed by CSF p-tau181 and total-tau, and, to a lesser extent, then plasma p-tau181. In contrast, the changes in plasma NfL, Aβ42/Aβ40, Aβ42, and Aβ40 were less pronounced. Of note, these plasma biomarkers exhibited smaller dynamic ranges than their CSF counterparts, except for GFAP which was the opposite. Plasma GFAP and p-tau181 were tightly associated with AD pathologies and amyloid tracer uptake in widespread brain areas. Plasma GFAP could accurately identify CSF Aβ42 (area under the curve (AUC)=0.911) and Aβ PET (AUC=0.971) positivity. Plasma p-tau181 also performed well in discriminating Aβ PET status (AUC=0.916), whereas the discriminative accuracy was relatively low for other plasma biomarkers.ConclusionsThis study is the first to delineate the trajectories of plasma biomarkers throughout the Alzheimer’s continuum in the Chinese population, providing important implications for future trials targeting plasma GFAP to facilitate AD prevention and treatment.

Diabetes and hypertension are associated with elevated beta‐amyloid burden: evidence from the prospective population‐based Rotterdam Study

AbstractBackgroundHigher vascular risk increases the likelihood of developing dementia. Better understanding the association between vascular risk and Alzheimer’s disease (AD) pathology at the pre‐dementia stage is critical for developing effective strategies to delay cognitive decline. In this work, we estimated the impact of vascular risk on the presence and severity of in‐vivo measured brain beta‐amyloid (Aβ) plaques in participants from the population‐based Rotterdam Study.MethodsVascular risk factors (hypertension, hypercholesterolemia, diabetes, obesity, physical inactivity, and smoking) were assessed twelve and seven years prior to 18F‐florbetaben positron emission tomography (PET) in 506 dementia‐free participants. Vascualr risk factors were associated with binary amyloid PET status or continuous PET readouts (SUVr values) using logistic and linear regression models respectively, adjusted for age, sex, education, APOE4 risk allele count, and time between vascular risk and PET assessment.ResultsParticipants’ mean age at time of amyloid PET was 68 years (range: 60‐90), 262 (51.8%) were women and 158 (31.2%) carried at least one APOE4 risk allele (Figure 1). The adjusted prevalence estimates of an amyloid‐positive PET status markedly increased with age (12% in 60‐69y vs. 45.5% in 80‐89y age‐groups) and APOE4 allele count (8.3% in non‐carriers vs. 34.8 to 58.8% in carriers of one or two risk allele(s); Figure 2). A diagnosis of diabetes seven years prior to PET assessment was associated with a higher risk of a positive amyloid status (OR[95%CI]=4.07[1.66–9.71], P=0.002; Figure 3) and higher SUVr values, indicating more severe Aβ pathology (standardized beta=0.478[0.205–0.750], P=0.001; Figure 4). We found evidence for an association between hypertension and higher SUVr values in APOE4 carriers, but not in non‐carriers (interaction: standardized beta=0.425[0.092–0.758], P=0.013; Figure 5). Hypercholesterolemia, obesity, physical inactivity and smoking were not related to amyloid PET measures.ConclusionThe current findings suggest a contribution of diabetes and hypertension to the pathophysiology of AD. Since both conditions respond well to lifestyle modification and drug treatment, further research should be conducted to examine the preventative effect of early risk management on the development of AD neuropathology.

Diabetes and hypertension are associated with elevated beta‐amyloid burden: evidence from the population‐based Rotterdam Study

AbstractBackgroundHigher vascular risk increases the likelihood of developing dementia. Better understanding the association between vascular risk and Alzheimer’s disease (AD) pathology at the pre‐dementia stage is critical for developing effective strategies to delay cognitive decline. In this work, we estimated the impact of vascular risk on the presence and severity of in‐vivo measured brain beta‐amyloid (Aβ) plaques in participants from the population‐based Rotterdam Study.MethodVascular risk factors (hypertension, hypercholesterolemia, diabetes, obesity, physical inactivity, and smoking) were assessed twelve and seven years prior to 18F‐florbetaben positron emission tomography (PET) in 506 dementia‐free participants. Vascualr risk factors were associated with binary amyloid PET status or continuous PET readouts (SUVr values) using logistic and linear regression models respectively, adjusted for age, sex, education, APOE4 risk allele count, and time between vascular risk and PET assessmentResultParticipants’ mean age at time of amyloid PET was 68 years (range: 60‐90), 262 (51.8%) were women and 158 (31.2%) carried at least one APOE4 risk allele (Figure 1). The adjusted prevalence estimates of an amyloid‐positive PET status markedly increased with age (12% in 60‐69y vs. 45.5% in 80‐89y age‐groups) and APOE4 allele count (8.3% in non‐carriers vs. 34.8 to 58.8% in carriers of one or two risk allele(s); Figure 2). A diagnosis of diabetes seven years prior to PET assessment was associated with a higher risk of a positive amyloid status (OR[95%CI] = 4.07[1.66‐9.71], P = 0.002; Figure 3) and higher SUVr values, indicating more severe Aβ pathology (standardized beta = 0.478[0.205–0.750], P = 0.001; Figure 4). We found evidence for an association between hypertension and higher SUVr values in APOE4 carriers, but not in non‐carriers (interaction: standardized beta = 0.425[0.092–0.758], P = 0.013; Figure 5). Hypercholesterolemia, obesity, physical inactivity and smoking were not related to amyloid PET measures.ConclusionThe current findings suggest a contribution of diabetes and hypertension to the pathophysiology of AD. Since both conditions respond well to lifestyle modification and drug treatment, further research should be conducted to examine the preventative effect of early risk management on the development of AD neuropathology.

The relationship of soluble p‐tau isoforms with brain amyloid and tau deposition in sporadic AD

AbstractBackgroundHyperphosphorylated tau isoforms (p‐tau) in cerebrospinal fluid (CSF) and plasma represent promising measures to monitor Alzheimer disease (AD) pathological changes. Brain amyloid deposition precedes tau aggregation and associated clinical decline by two decades. Several CSF and plasma p‐tau isoforms have been described as potential surrogates for tau Positron Emission Tomography (PET) imaging, but p‐tau isoforms have a strong association with amyloid PET, and increase without tau pathology. In this study, we investigated the relationship between multiple CSF p‐tau isoforms and brain imaging measures in the Knight ADRC cohort.MethodWe analyzed 10 p‐tau isoforms by mass spectrometry in 1932 CSF samples (1173 participants). Associated data includes 1250 amyloid PET and 442 tau PET scans, as well as CSF Aβ42/Aβ40 by immunoassay for all samples. We measured phosphorylation occupancies (ptau/tau) at T111, T153, T175, T181, S199, S202, T205, S208, T217 and T231, together with corresponding p‐tau and tau concentrations. We compared the accuracy of CSF p‐tau isoforms in predicting amyloid PET and tau PET status stratified according to amyloid PET, tau PET and/or Clinical Dementia Rating (CDR) status.ResultsPT217/T217 best‐predicted abnormal amyloid PET (AUROC=0.980) or CSF Aβ42/Aβ40 (AUC=0.954). PT217/T217 predicted brain amyloidosis in asymptomatic and symptomatic participants with similar accuracy (AUC=0.979 and 0.986 respectively) and was correlated with amyloid PET centiloid and CSF Aβ42/Aβ40 (Spearman R=0.73 and ‐0.76, p&lt;0.0001). Notably, the correlation between pT217/T217 and amyloid PET centiloid was higher in amyloid PET(+)/tau PET(‐) compared to amyloid PET(+)/tau‐PET(+) (R=0.77, p&lt;0.0001 versus 0.16, p=0.007). PT205/T205 and pT217/T217 better predicted tau PET positivity in amyloid PET(+)positive participants (AUC=0.908 and 0.866). These markers were also associated with tau PET signal in tau PET(+) participants (R=0.53 and 0.55 p&lt;0.0001). Other p‐tau isoforms also predicted amyloidosis, except for T175, S199, S202 and T205. Only pT205/T205 and pT217/T217 were correlated with tau‐PET in tau PET(+) participants.ConclusionThese results suggest that tau hyperphosphorylation, notably at T217, is more strongly associated with brain amyloid burden than tau deposition in tau PET(‐) individuals. After tau PET becomes positive, p‐tau217 and p‐tau205 are correlated with tau burden. Soluble p‐tau are markers of both amyloid and tau aggregation in the AD brain.

Clinical utility of cerebrospinal fluid biomarkers measured by LUMIPULSE® system.

Cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) are well-established in research settings, but their use in routine clinical practice remains a largely unexploited potential. Here, we examined the relationship between CSF biomarkers, measured by a fully automated immunoassay platform, and brain β-amyloid (Aβ) deposition status confirmed by amyloid positron emission tomography (PET). One hundred ninety-nine CSF samples from clinically diagnosed AD patients enrolled in a clinical study and who underwent amyloid PET were used for the measurement of CSF biomarkers Aβ 1-40 (Aβ40), Aβ 1-42 (Aβ42), total tau (t-Tau), and phosphorylated tau-181 (p-Tau181) using the LUMIPULSE system. These biomarkers and their combinations were compared to amyloid PET classification (negative or positive) using visual read assessments. Several combinations were also analyzed with a multivariable logistic regression model. Aβ42, t-Tau, and p-Tau181, and the ratios of Aβ42 with other biomarkers had a good diagnostic agreement with amyloid PET imaging. The multivariable logistic regression analysis showed that amyloid PET status was associated with Aβ40 and Aβ42, but other factors, such as MMSE, sex, t-Tau, and p-Tau181, did not significantly add information to the model. CSF biomarkers measured with the LUMIPULSE system showed good agreement with amyloid PET imaging. The ratio of Aβ42 with the other analyzed biomarkers showed a higher correlation with amyloid PET than Aβ42 alone, suggesting that the combinations of biomarkers could be useful in the diagnostic assessment in clinical research and potentially in routine clinical practice.

A flexible modeling approach for biomarker-based computation of absolute risk of Alzheimer's disease dementia.

As Alzheimer's disease (AD) biomarkers rapidly develop, tools are needed that accurately and effectively communicate risk of AD dementia. We analyzed longitudinal data from >10,000 cognitively unimpaired older adults. Five-year risk of AD dementia was modeled using survival analysis. A demographic model was developed and validated on independent data with area under the receiver operating characteristic curve (AUC) for 5-year prediction of AD dementia of 0.79. Clinical and cognitive variables (AUC=0.79), and apolipoprotein E genotype (AUC=0.76) were added to the demographic model. We then incorporated the risk computed from the demographic model with hazard ratios computed from independent data for amyloid positron emission tomography status and magnetic resonance imaging hippocampal volume (AUC=0.84), and for plasma amyloid beta (Aβ)42/Aβ40 (AUC=0.82). An adaptive tool was developed and validated to compute absolute risks of AD dementia. This approach allows for improved accuracy and communication of AD risk among cognitively unimpaired older adults.

Comparative analytical performance of multiple plasma Aβ42 and Aβ40 assays and their ability to predict positron emission tomography amyloid positivity.

This report details the approach taken to providing a dataset allowing for analyses on the performance of recently developed assays of amyloid beta (Aβ) peptides in plasma and the extent to which they improve the prediction of amyloid positivity. Alzheimer's Disease Neuroimaging Initiative plasma samples with corresponding amyloid positron emission tomography (PET) data were run on six plasma Aβ assays. Statistical tests were performed to determine whether the plasma Aβ measures significantly improved the area under the receiver operating characteristic curve for predicting amyloid PET status compared to age and apolipoprotein E (APOE) genotype. The age and APOE genotype model predicted amyloid status with an area under the curve (AUC) of 0.75. Three assays improved AUCs to 0.81, 0.81, and 0.84 (P < .05, uncorrected for multiple comparisons). Measurement of Aβ in plasma contributes to addressing the amyloid component of the ATN (amyloid/tau/neurodegeneration) framework and could be a first step before or in place of a PET or cerebrospinal fluid screening study. The Foundation of the National Institutes of Health Biomarkers Consortium evaluated six plasma amyloid beta (Aβ) assays using Alzheimer's Disease Neuroimaging Initiative samples. Three assays improved prediction of amyloid status over age and apolipoprotein E (APOE) genotype. Plasma Aβ42/40 predicted amyloid positron emission tomography status better than Aβ42 or Aβ40 alone.

Fully automated and highly specific plasma β-amyloid immunoassays predict β-amyloid status defined by amyloid positron emission tomography with high accuracy

BackgroundClinicians, researchers, and patients alike would greatly benefit from more accessible and inexpensive biomarkers for neural β-amyloid (Aβ). We aimed to assess the performance of fully automated plasma Aβ immunoassays, which correlate significantly with immunoprecipitation mass spectrometry assays, in predicting brain Aβ status as determined by visual read assessment of amyloid positron emission tomography (PET).MethodsThe plasma Aβ42/Aβ40 ratio was measured using a fully automated immunoassay platform (HISCL series) in two clinical studies (discovery and validation studies). The discovery and validation sample sets were retrospectively and randomly selected from participants with early Alzheimer’s disease (AD) identified during screening for the elenbecestat Phase 3 program.ResultsWe included 197 participants in the discovery study (mean [SD] age 71.1 [8.5] years; 112 females) and 200 in the validation study (age 70.8 [7.9] years; 99 females). The plasma Aβ42/Aβ40 ratio predicted amyloid PET visual read status with areas under the receiver operating characteristic curves of 0.941 (95% confidence interval [CI] 0.910–0.973) and 0.868 (95% CI 0.816–0.920) in the discovery and validation studies, respectively. In the discovery study, a cutoff value of 0.102 was determined based on maximizing the Youden Index, and the sensitivity and specificity were calculated to be 96.0% (95% CI 90.1–98.9%) and 83.5% (95% CI 74.6–90.3%), respectively. Using the same cutoff value, the sensitivity and specificity in the validation study were calculated to be 88.0% (95% CI 80.0–93.6%) and 72.0% (95% CI 62.1–80.5%), respectively.ConclusionsThe plasma Aβ42/Aβ40 ratio measured using the HISCL series achieved high accuracy in predicting amyloid PET status. Since our blood-based immunoassay system is less invasive and more accessible than amyloid PET and cerebrospinal fluid testing, it may contribute to the diagnosis of AD in routine clinical practice.

A combination model of AD biomarkers revealed by machine learning precisely predicts Alzheimer's dementia: China Aging and Neurodegenerative Initiative (CANDI) study.

To test the utility of the "A/T/N" system in the Chinese population, we study core Alzheimer's disease (AD) biomarkers in a newly established Chinese cohort. A total of 411 participants were selected, including 96 cognitively normal individuals, 94 patients with mild cognitive impairment (MCI) patients, 173 patients with AD, and 48 patients with non-AD dementia. Fluid biomarkers were measured with single molecule array. Amyloid beta (Aβ) deposition was determined by18F-Flobetapir positron emission tomography (PET), and brain atrophy was quantified using magnetic resonance imaging (MRI). Aβ42/Aβ40 was decreased, whereas levels of phosphorylated tau (p-tau) were increased in cerebrospinal fluid (CSF) and plasma from patients with AD. CSF Aβ42/Aβ40, CSF p-tau, and plasma p-tau showed a high concordance in discriminating between AD and non-AD dementia or elderly controls. A combination of plasma p-tau,apolipoprotein E (APOE)genotype, and MRI measures accurately predicted amyloid PET status. These results revealed a universal applicability of the "A/T/N" framework in a Chinese population and established an optimal diagnostic model consisting of cost-effective and non-invasive approaches for diagnosing AD.