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Background The development of blood-based biomarker tests that are accurate and robust for Alzheimer’s disease (AD) pathology have the potential to aid clinical diagnosis and facilitate enrollment in AD drug trials. We developed a high-resolution mass spectrometry (MS)-based test that quantifies plasma Aβ42 and Aβ40 concentrations and identifies the ApoE proteotype. We evaluated robustness, clinical performance, and commercial viability of this MS biomarker assay for distinguishing brain amyloid status. Methods We used the novel MS assay to analyze 414 plasma samples that were collected, processed, and stored using site-specific protocols, from six independent US cohorts. We used receiver operating characteristic curve (ROC) analyses to assess assay performance and accuracy for predicting amyloid status (positive, negative, and standard uptake value ratio; SUVR). After plasma analysis, sites shared brain amyloid status, defined using diverse, site-specific methods and cutoff values; amyloid PET imaging using various tracers or CSF Aβ42/40 ratio. Results Plasma Aβ42/40 ratio was significantly ( p  < 0.001) lower in the amyloid positive vs. negative participants in each cohort. The area under the ROC curve (AUC-ROC) was 0.81 (95% CI = 0.77–0.85) and the percent agreement between plasma Aβ42/40 and amyloid positivity was 75% at the optimal (Youden index) cutoff value. The AUC-ROC (0.86; 95% CI = 0.82–0.90) and accuracy (81%) for the plasma Aβ42/40 ratio improved after controlling for cohort heterogeneity. The AUC-ROC (0.90; 95% CI = 0.87–0.93) and accuracy (86%) improved further when Aβ42/40, ApoE4 copy number and participant age were included in the model. Conclusions This mass spectrometry-based plasma biomarker test: has strong diagnostic performance; can accurately distinguish brain amyloid positive from amyloid negative individuals; may aid in the diagnostic evaluation process for Alzheimer’s disease; and may enhance the efficiency of enrolling participants into Alzheimer’s disease drug trials.

The objective of this study was to examine clinicians' patient selection and result interpretation of a clinically validated mass spectrometry test measuring amyloid beta and ApoE blood biomarkers combined with patient age (PrecivityAD® blood test) in symptomatic patients evaluated for Alzheimer's disease (AD) or other causes of cognitive decline. The Quality Improvement and Clinical Utility PrecivityAD Clinician Survey (QUIP I, ClinicalTrials.gov Identifier: NCT05477056) was a prospective, single-arm cohort study among 366 patients evaluated by neurologists and other cognitive specialists. Participants underwent blood biomarker testing and received an amyloid probability score (APS), indicating the likelihood of a positive result on an amyloid positron emission tomography (PET) scan. The primary study outcomes were appropriateness of patient selection as well as result interpretation associated with PrecivityAD blood testing. A 95% (347/366) concordance rate was noted between clinicians' patient selection and the test's intended use criteria. In the final analysis including these 347 patients (median age 75 years, 56% women), prespecified test result categories incorporated 133 (38%) low APS, 162 (47%) high APS, and 52 (15%) intermediate APS patients. Clinicians' pretest and posttest AD diagnosis probability changed from 58% to 23% in low APS patients and 71% to 89% in high APS patients (p < 0.0001). Anti-AD drug therapy decreased by 46% in low APS patients (p < 0.0001) and increased by 57% in high APS patients (p < 0.0001). These findings demonstrate the clinical utility of the PrecivityAD blood test in clinical care and may have added relevance as new AD therapies are introduced.

Background The amyloid probability score (APS) is the model read‐out of the analytically validated mass spectrometry‐based PrecivityAD® blood test that incorporates the plasma Aβ42/40 ratio, ApoE proteotype, and age to identify the likelihood of brain amyloid plaques among cognitively impaired individuals being evaluated for Alzheimer's disease. Purpose This study aimed to provide additional independent evidence that the pre‐established APS algorithm, along with its cutoff values, discriminates between amyloid positive and negative individuals. Methods The diagnostic performance of the PrecivityAD test was analyzed in a cohort of 200 nonrandomly selected Australian Imaging, Biomarker & Lifestyle Flagship Study of Aging (AIBL) study participants, who were either cognitively impaired or healthy controls, and for whom a blood sample and amyloid PET imaging were available. Results In a subset of the dataset aligned with the Intended Use population (patients aged 60 and older with CDR ≥0.5), the pre‐established APS algorithm predicted amyloid PET with a sensitivity of 84.9% (CI: 72.9–92.1%) and specificity of 96% (CI: 80.5–99.3%), exclusive of 13 individuals for whom the test was inconclusive. Interpretation The study shows individuals with a high APS are more likely than those with a low APS to have abnormal amounts of amyloid plaques and be on an amyloid accumulation trajectory, a dynamic and evolving process characteristic of progressive AD pathology. Exploratory data suggest APS retains its diagnostic performance in healthy individuals, supporting further screening studies in the cognitively unimpaired.

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 (Aβ)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.

The diagnostic evaluation for Alzheimer disease may be improved by a blood-based diagnostic test identifying presence of brain amyloid plaque pathology. To determine the clinical performance associated with a diagnostic algorithm incorporating plasma amyloid-β (Aβ) 42:40 ratio, patient age, and apoE proteotype to identify brain amyloid status. This cohort study includes analysis from 2 independent cross-sectional cohort studies: the discovery cohort of the Plasma Test for Amyloidosis Risk Screening (PARIS) study, a prospective add-on to the Imaging Dementia-Evidence for Amyloid Scanning study, including 249 patients from 2018 to 2019, and MissionAD, a dataset of 437 biobanked patient samples obtained at screenings during 2016 to 2019. Data were analyzed from May to November 2020. Amyloid detected in blood and by positron emission tomography (PET) imaging. The main outcome was the diagnostic performance of plasma Aβ42:40 ratio, together with apoE proteotype and age, for identifying amyloid PET status, assessed by accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). All 686 participants (mean [SD] age 73.2 [6.3] years; 368 [53.6%] men; 378 participants [55.1%] with amyloid PET findings) had symptoms of mild cognitive impairment or mild dementia. The AUC of plasma Aβ42:40 ratio for PARIS was 0.79 (95% CI, 0.73-0.85) and 0.86 (95% CI, 0.82-0.89) for MissionAD. Ratio cutoffs for Aβ42:40 based on the Youden index were similar between cohorts (PARIS: 0.089; MissionAD: 0.092). A logistic regression model (LRM) incorporating Aβ42:40 ratio, apoE proteotype, and age improved diagnostic performance within each cohort (PARIS: AUC, 0.86 [95% CI, 0.81-0.91]; MissionAD: AUC, 0.89 [95% CI, 0.86-0.92]), and overall accuracy was 78% (95% CI, 72%-83%) for PARIS and 83% (95% CI, 79%-86%) for MissionAD. The model developed on the prospectively collected samples from PARIS performed well on the MissionAD samples (AUC, 0.88 [95% CI, 0.84-0.91]; accuracy, 78% [95% CI, 74%-82%]). Training the LRM on combined cohorts yielded an AUC of 0.88 (95% CI, 0.85-0.91) and accuracy of 81% (95% CI, 78%-84%). The output of this LRM is the Amyloid Probability Score (APS). For clinical use, 2 APS cutoff values were established yielding 3 categories, with low, intermediate, and high likelihood of brain amyloid plaque pathology. These findings suggest that this blood biomarker test could allow for distinguishing individuals with brain amyloid-positive PET findings from individuals with amyloid-negative PET findings and serve as an aid for Alzheimer disease diagnosis.

Abstract There is an important unmet need for timely, noninvasive, low-burden evaluation of patients presenting with mild cognitive impairment (MCI). The PrecivityAD™ blood test quantifies plasma concentrations of amyloid-β 42 and 40 and apolipoprotein E-specific peptides that are combined with age in an algorithm to identify the likelihood of amyloid plaques in the brain as measured by amyloid PET scans. This test has previously demonstrated 92% sensitivity and 77% specificity. The study objective was to evaluate the clinical utility of the test and the Amyloid Probability Score (APS), the test output value. Eighteen patients (median age 72, 55% male, 88% white) with MCI received the PrecivityAD blood-based biomarker test. The mean APS was 31 (range 0-91): 13 patients had low scores (APS 0-35), 2 had high scores (58-100) and 3 had intermediate (inconclusive) scores (APS 36-57). The mean probability of Alzheimer's disease (AD) diagnosis was rated by clinicians as 63% (range 25-80) pre-test and 31% post-test (range 5-95) (p < 0.0005). AD probability rated by clinicians was decreased in 12/13 low APS patients and increased in 2/2 high APS patients. Donepezil was discontinued in 5/8 low APS patients on therapy and initiated in 1/1 high APS patients not on therapy, representing a change in treatment management in 33% (6/18) of study patients. In summary, this blood-based biomarker test showed clinical utility in its association with physician decision-making around diagnostic certainty and drug therapy management in MCI patients.

The diagnostic performance of the Amyloid Probability Score 2 (APS2; the algorithmic result of the PrecivityAD2™ blood test) was originally trained and validated in two cohorts of cognitively impaired (CI) individuals and is in clinical use. Here, we further test the repeatability and reliability of the prespecified APS2 algorithm and cut point in an independent cohort. APS2 diagnostic performance was determined using amyloid positron emission tomography (PET) as the reference standard. Concordance with amyloid PET was high (AUC–ROC 0.95 (95% CI): 0.93–0.98); 54% of participants had a positive APS2. The previously validated APS2 cut point yielded an overall accuracy of 91% (95% CI: 86–94%), sensitivity 90% (95% CI: 83–94%) and specificity 92% (95% CI: 84–96%). Our findings demonstrate that the prespecified APS2 algorithm and cut point are repeatable, reliable, robust, accurate, and generalizable for identifying brain beta-amyloid pathology in patients with cognitive impairment and being evaluated in a clinical care setting.

The development of blood-based biomarker tests that are accurate and robust for Alzheimer's disease (AD) pathology have the potential to aid clinical diagnosis and facilitate enrollment in AD drug trials. We developed a high-resolution mass spectrometry (MS)-based test that quantifies plasma A[beta]42 and A[beta]40 concentrations and identifies the ApoE proteotype. We evaluated robustness, clinical performance, and commercial viability of this MS biomarker assay for distinguishing brain amyloid status. We used the novel MS assay to analyze 414 plasma samples that were collected, processed, and stored using site-specific protocols, from six independent US cohorts. We used receiver operating characteristic curve (ROC) analyses to assess assay performance and accuracy for predicting amyloid status (positive, negative, and standard uptake value ratio; SUVR). After plasma analysis, sites shared brain amyloid status, defined using diverse, site-specific methods and cutoff values; amyloid PET imaging using various tracers or CSF A[beta]42/40 ratio. Plasma A[beta]42/40 ratio was significantly (p < 0.001) lower in the amyloid positive vs. negative participants in each cohort. The area under the ROC curve (AUC-ROC) was 0.81 (95% CI = 0.77-0.85) and the percent agreement between plasma A[beta]42/40 and amyloid positivity was 75% at the optimal (Youden index) cutoff value. The AUC-ROC (0.86; 95% CI = 0.82-0.90) and accuracy (81%) for the plasma A[beta]42/40 ratio improved after controlling for cohort heterogeneity. The AUC-ROC (0.90; 95% CI = 0.87-0.93) and accuracy (86%) improved further when A[beta]42/40, ApoE4 copy number and participant age were included in the model. This mass spectrometry-based plasma biomarker test: has strong diagnostic performance; can accurately distinguish brain amyloid positive from amyloid negative individuals; may aid in the diagnostic evaluation process for Alzheimer's disease; and may enhance the efficiency of enrolling participants into Alzheimer's disease drug trials.

Bacteriophage phiX174 immunization was used to measure CD4+ T cell function in vivo in human immunodeficiency virus (HIV)—infected patients across all disease stages. function was evaluated by measuring the ability of T cells to provide help to B cells in antibody production, amplification, and isotype switching. A total of 33 patients and 10 controls received 3 bacteriophage phiX174 immunizations 6 weeks apart. The patients' responses regarding bacteriophage-specific total antibody titers and IgG titers were quantitatively and qualitatively inferior to the controls' responses. Overall, 7 of 33 patients had normal T cell function. Baseline CD4 counts provided the strongest correlation with total antibody and IgG titers. HIV RNA had a weaker association with responses but had some predictive power among patients with a CD4 count >200 cells/µL. Bacteriophage phiX174 immunization seems to be a useful tool for measuring immune function in vivo, which suggests that most HIV-infected patients may have abnormal CD4+ T cell function despite adequate antiretroviral treatment.

The AIDS Clinical Trials Group (ACTG) is a large consortium whose members perform clinical trials and other studies of human immunodeficiency virus (HIV) infection in the United States, sponsored by the National Institute of Allergy and Infectious Diseases (NIAID) and directed by NIAID's Division of AIDS (DAIDS). The ACTG has experienced enormous growth since its inception in 1986, with 47 separate units at 150 sites now operational and over 200 protocols completed or in progress.