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.
IMPORTANCEThe diagnostic evaluation for Alzheimer disease may be improved by a blood-based diagnostic test identifying presence of brain amyloid plaque pathology. OBJECTIVE 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. DESIGN, SETTING, AND PARTICIPANTS 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. EXPOSURES Amyloid detected in blood and by positron emission tomography (PET) imaging. MAIN OUTCOMES AND MEASURESThe 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). RESULTSAll 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. (continued) Key Points Question Is an amyloid probability score based on a mass spectrometrybased blood test measuring plasma amyloid β 42:40 ratio and apoE proteotype plus age, associated with identifying brain amyloidosis among patients with cognitive impairment? Findings In this cohort study of 686 participants from 2 separate studies, the developed Amyloid Probability Score showed high concordance with amyloid PET status, with an area under the curve of 0.88 and overall accuracy of 81%. The test's findings were significantly associated with the presence or absence of brain amyloidosi...
Sacubitril/valsartan (LCZ696) is the first angiotensin receptor neprilysin inhibitor approved to reduce cardiovascular mortality and hospitalization in patients with heart failure with reduced ejection fraction. As neprilysin (NEP) is one of several enzymes known to degrade amyloid-β (Aβ), there is a theoretical risk of Aβ accumulation following long-term NEP inhibition. The primary objective of this study was to evaluate the potential effects of sacubitril/valsartan on central nervous system clearance of Aβ isoforms in cynomolgus monkeys using the sensitive Stable Isotope Labeling Kinetics (SILK™)-Aβ methodology. The in vitro selectivity of valsartan, sacubitril, and its active metabolite sacubitrilat was established; sacubitrilat did not inhibit other human Aβ-degrading metalloproteases. In a 2-week study, sacubitril/valsartan (50mg/kg/day) or vehicle was orally administered to female cynomolgus monkeys in conjunction with SILK™-Aβ. Despite low cerebrospinal fluid (CSF) and brain penetration, CSF exposure to sacubitril was sufficient to inhibit NEP and resulted in an increase in the elimination half-life of Aβ1-42 (65.3%; p=0.026), Aβ1-40 (35.2%; p=0.04) and Aβtotal (29.8%; p=0.04) acutely; this returned to normal as expected with repeated dosing for 15days. CSF concentrations of newly generated Aβ (AUC) indicated elevations in the more aggregable form Aβ1-42 on day 1 (20.4%; p=0.039) and day 15 (34.7%; p=0.0003) and in shorter forms Aβ1-40 (23.4%; p=0.009), Aβ1-38 (64.1%; p=0.0001) and Aβtotal (50.45%; p=0.00002) on day 15. However, there were no elevations in any Aβ isoforms in the brains of these monkeys on day 16. In a second study cynomolgus monkeys were administered sacubitril/valsartan (300mg/kg) or vehicle control for 39weeks; no microscopic brain changes or Aβ deposition, as assessed by immunohistochemical staining, were present. Further clinical studies are planned to address the relevance of these findings.
BackgroundAfrican Americans (AA) are under‐represented in Alzheimer’s disease (AD) biomarker research. Blood‐based biomarkers for AD offer the promise of greater diversity in research studies, but little is known about the performance of these biomarkers within an AA cohort. We examined the association between modifiable and non‐modifiable risk factors on the trajectory of plasma measures of Aβ42/40 in a large well‐characterized AA cohort.MethodN=318 AA participants enrolled in in African Americans Fighting Alzheimer’s in Mid‐Life (AA‐FAIM) provided 690 plasma samples. The ratio Ab42/40 was calculated from plasma Aβ40 and Aβ42 quantified by C2N Diagnostics (PrecivityAD™; Figure 1). Age range was 39 ‐ 87 years at baseline (see Table 1); 52% of the cohort provided ≥2 plasma samples. Mixed‐effects linear models were used to test for longitudinal change in Aβ42/40 where years since baseline was the measure of time (M= 4.13 years, range = 1 to 16 years). To determine if risk factors modified Aβ42/40 trajectory, we tested the interactions between time and the following AD risk factors: APOE genetic risk, cardiovascular factors measured at baseline plasma sample (blood pressure, BMI, total cholesterol), and amyloid PET positivity.ResultRaw Aβ42/40 values plotted against time are shown in Figure 2. None of the risk factors modified the trajectory of Aβ42/40 (p values ranged .22 to .84), which declined by approximately 1% per year over baseline (p <.001; Table 2). After accounting for longitudinal trajectory, Ab42/40 was 3% lower among APOE ε4 carriers, while higher baseline total cholesterol was associated with higher Aβ42/40. In a subset of participants with PiB‐PET visual ratings (N=35), amyloid positive participants (N=10) had 12% lower plasma Aβ42/40 values than amyloid negative participants (p<.001) after accounting for longitudinal trajectory.ConclusionThese initial analyses conducted exclusively in African Americans suggest that clinical risk factors (total cholesterol, APOE) can influence brain amyloid pathology, as determined using plasma Aβ42/40. More research is needed to fully characterize AD pathology and dementia risk in AAs. This research is imperative in light of the disproportionate burden of dementia in the AA community and the increasing use of biomarkers in research and clinical practice.
BackgroundAccumulation of amyloid beta plaques and tau tangles in the brain are sequential pathological hallmarks of Alzheimer’s disease. Specific measurement of tau phosphorylation sites in plasma samples can be used to investigate the presence of both amyloid plaque and tau tangle brain pathology.MethodA tandem mass spectrometry assay that quantifies phosphorylation of tau at threonine residues 181 and 217 in plasma was developed. Both phosphorylated (phospho) and non‐phosphorylated (non‐phospho) peptides containing tau residues 181 and 217 as well as the ratio of phospho to non‐phospho at each of these phosphorylation sites can be calculated from a blood sample. We tested the concordance between these measures and brain amyloid burden in PARIS study participants, an IDEAS sub‐study in patients with mild cognitive impairment or dementia. K2EDTA plasma samples from PARIS participants (n=221) were analyzed for tau phosphorylation and Aβ42/40.ResultsThe amount of phosphorylation at both 181 and 217 sited were significantly higher in patients who were amyloid PET positive, while PET negative patients showed very low amounts of phosphorylation at 217 (1.2 pg/mL vs. 4.9 pg/mL; p <2e‐16). The ratio of phospho‐tau to non‐phospho‐tau 217 showed high correlation (Spearman’s rank correlation r=0.78; p <2e‐16) with quantitative amyloid PET, demonstrating that phosphorylation of tau on threonine‐217 can quantitatively identify the amount of amyloid burden. This ratio of phospho‐tau to non‐phospho‐tau also correlated better with amyloid status than the concentration of phospho‐tau alone, with area under the curve (AUC) for detecting brain amyloid burden improving from 0.74 (95%CI 0.67‐0.82) to 0.81 (95%CI 0.75‐0.88) for 181 and from 0.92 (95%CI 0.88‐0.96) to 0.95 (95%CI 0.92‐0.98) for 217. Combining the phospho‐tau‐217 with the Aβ42/40 ratios for the same sample further increased the AUC to 0.96 (95%CI 0.93‐0.99).ConclusionThis novel mass spectrometry‐based quantitative assay for plasma phospho‐tau and non‐phospho‐tau species has excellent analytical and clinical validity performance characteristics. Combining the ratio of tau phosphorylation at 217 with plasma Aβ42/40 can help identify brain amyloid pathology with a performance that rivals that of CSF or PET tests.
BackgroundVariation in biospecimen collection, processing, and storage parameters can introduce pre‐analytical variables that may confound interpretation of biomarker results. Samples collected under different study protocols or over a long period of time may require different labware, such as storage tubes. Comparability of storage tubes is necessary to better interpretate data collected both longitudinally within studies and across studies that may utilize various labware. The focus of this experiment was to perform comparability studies between plasma biomarkers measured in two polypropylene tube types: Sarstedt tube (72.694.006) and an automation friendly Micronic tube (MP52755).MethodsBlood was collected from healthy controls (N=23) and Alzheimer’s Disease (AD) subjects (N=16) by the Indiana Biobank. Participants’ brain amyloid status was unknown. Plasma from the same subjects was aliquoted (0.5 mL) into both Micronic and Sarstedt polypropylene tubes following standard NCRAD protocols and then frozen and stored at ‐80 °C for <7 months prior to analysis. Blinded samples were thawed once and analyzed for ApoE proteotype, Aβ40 and Aβ42 using liquid chromatography‐high resolution tandem mass spectrometry (LC‐MS/MS; C2N Diagnostics, St. Louis, MO). Data was analyzed in JMP 16.0.0 with the method comparison add‐in and GraphPad PRISM 9.3.1 to determine comparability of the measurements made in the two sample tube types.ResultsComparability analysis found a high correlation of measured Aβ40, Aβ42 and the Aβ42/Aβ40 ratio in plasma stored in Micronic and Sarstedt tubes. Correlation analysis revealed slopes and intercepts within 95% confidence limits of 1 or 0 respectively. Bland Altman analysis showed low measurement bias (4‐7%) between the two tube types. ApoE isoform specific proteotypes were identical between tube types for all subjects.ConclusionResults of the tube type study were within the validated performance range of the measurements. Plasma stored in Micronic and Sarstedt tubes can be used interchangeably when detecting ApoE proteotype and quantifying Aβ40 and Aβ42 concentrations using C2N’s LC‐MS/MS analytical platform. These results support the efforts of large biorepositories, like NCRAD to transition the storage of biospecimens from the larger, less automation friendly Sarstedt tube to the more automation friendly, freezer‐space saving Micronic tube. Supported by U24 AG021886 and UL1TR002529.
BackgroundThe prevalence of clinical Alzheimer’s disease (AD) and type 2 diabetes is higher in African Americans (AA) relative to non‐Hispanic White Americans. Although diabetes is a risk factor for Alzheimer’s clinical syndrome, it is unclear whether diabetes associates with amyloid‐β, a pathological hallmark of AD. We investigated whether diabetic status was associated with age‐related decline in plasma amyloid‐β (Aβ) 42/40 ratio and cognition in a predominantly dementia‐free AA cohort.MethodParticipants (N=314) were middle‐aged and older adults (Table 1) enrolled in the African Americans Fighting Alzheimer’s in Midlife cohort. EDTA plasma was collected at 1‐8 visits for Aβ 42/40 quantification using immunoprecipitation mass spectrometry (C2N Diagnostics, St. Louis, MO). 52% had >1 plasma Aβ 42/40 measurements over an average interval of 4.9 years (SD=3). Recall (immediate and delayed) and executive functioning were assessed using Rey’s Auditory Verbal Learning Test and Trails B, respectively. Diabetic status was determined from clinician‐report, self‐report, self‐report of antidiabetic medication use or fasting glucose ≥126 mg/dL. Cognitive data from the first of 1‐6 visits and diabetic status were obtained at the same visit as baseline plasma Aβ 42/40 for 96% of participants. Linear mixed‐effects models tested diabetic status as a moderator of age‐related decline in plasma Aβ 42/40 ratio and cognition. If age x diabetic status was not significant, diabetic status was tested without the interaction. Covariates included APOE4 carrier status and sex, and education was included when cognition was the outcome.ResultsDiabetic status did not significantly moderate age‐related decline in plasma Aβ 42/40 (β=0.0001, p=.21) or predict average plasma Aβ 42/40 ratio (β=‐0.001, p=.22). Diabetes was also not significantly related to aging‐associated decline in cognition but was a significant predictor of worse average Trails B scores (Table 2). Results from a cognitively unimpaired subsample (n=261) revealed a similar pattern.ConclusionIn a predominantly dementia‐free AA cohort, diabetes was unrelated to plasma Aβ 42/40 but was related to worse Trails B performance. Poor Trails B performance has been linked in previous studies to cerebrovascular dysfunction. Determining mechanisms, vascular and AD pathological pathways, that link diabetes to increased dementia risk in AAs warrants further investigation.
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