Algeciras‐Schimnich, Alicia

AbstractINTRODUCTIONThis study evaluated the performance of the Lumipulse plasma beta‐amyloid (Aβ) 42/40 and pTau181 compared to other assays to detect an abnormal amyloid‐positron emission tomography (PET).METHODSPlasma samples from cognitively unimpaired (N = 179) and MCI/AD dementia (N = 36) individuals were retrospectively evaluated. Plasma Aβ42/40 and pTau181 were measured using the Lumipulse and Simoa immunoassays. An immunoprecipitation mass spectrometry (IP‐MS) assay for plasma Aβ42/40 was also evaluated. Amyloid‐PET status was the outcome measure.RESULTSLumipulse and IP‐MS Aβ42/40 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 Aβ42/40 assay demonstrated the lowest diagnostic accuracy (AUC 0.57). Combining Aβ42/40 and pTau181 did not significantly improve performance over Aβ42/40 alone for Lumipulse (AUC 0.83) or over pTau181 alone for Simoa (AUC 0.71)DISCUSSIONThe Lumipulse Aβ42/40 assay showed similar performance to the IP‐MS Aβ42/40 assay for detection of an abnormal amyloid‐PET; and both assays performed better than the two p‐tau181 immunoassays. The Simoa Aβ42/Aβ40 assay was the least accurate at predicting an abnormal amyloid‐PET status.Highlights Lumipulse plasma Aβ42/Aβ40 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.

Abstract BACKGROUND We compared the ability of several plasma biomarkers versus amyloid positron emission tomography (PET) to predict rates of memory decline among cognitively unimpaired individuals. METHODS We studied 645 Mayo Clinic Study of Aging participants. Predictor variables were age, sex, education, apolipoprotein E ( APOE ) ε 4 genotype, amyloid PET, and plasma amyloid beta (Aβ)42/40, phosphorylated tau (p‐tau)181, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and p‐tau217. The outcome was a change in a memory composite measure. RESULTS All plasma biomarkers, except NfL, were associated with mean memory decline in models with individual biomarkers. However, amyloid PET and plasma p‐tau217, along with age, were key variables independently associated with mean memory decline in models combining all predictors. Confidence intervals were narrow for estimates of population mean prediction, but person‐level prediction intervals were wide. DISCUSSION Plasma p‐tau217 and amyloid PET provide useful information about predicting rates of future cognitive decline in cognitively unimpaired individuals at the population mean level, but not at the individual person level.

AbstractBackgroundPatients with dementia with Lewy bodies (DLB) may have Alzheimer´s disease (AD) pathology. Plasma biomarkers of beta‐amyloid (Aβ), phosphorylated tau (pTau), and neurodegeneration are sensitive to AD neuropathologic changes in AD dementia. While these plasma biomarkers are well tested in the AD continuum, their performance for concomitant AD pathology in the DLB continuum is still unclear.MethodWe included patients with isolated REM sleep behavior disorder (iRBD; n = 15), with mild cognitive impairment with Lewy bodies (MCI‐LB; n = 37), and with DLB (n = 70) from the Mayo Clinic Alzheimer’s Disease Research Center. Cognitively unimpaired individuals (CU; n = 100) included from the Mayo Clinic Study of Aging were balanced on age and sex. A panel of plasma biomarkers of Aβ40, Aβ42, p‐tau181, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) measures was obtained. We calculated the ratio of plasma Aβ40/42. Lower Aβ40/42 indicates increased Aβ pathology. Plasma Aβ40, Aβ42, GFAP, and NfL were measured using the Simoa® Neurology 4‐Plex E Advantage kit and pTau‐181 was measured with the Simoa® pTau‐181 Advantage V2 kit. Both were run on a Quanterix HD‐X analyzer. AD imaging biomarkers were assessed on PET using Pittsburgh compound B (PiB) for Aβ and 18F‐Flortaucipir for tau.ResultHigher levels of plasma GFAP were observed in the MCI‐LB (p = 0.014) and DLB (p<0.001) groups compared to CU (Figure). DLB patients also showed higher levels of plasma pTau181 (p<0.001) and NfL (p<0.001). Higher amyloid and tau PET standardized uptake value ratio (SUVr) in the DLB continuum were associated with higher levels of plasma p‐tau181, NfL, and GFAP (p<0.001). After accounting for age, plasma Aβ40/42 did not correlate with amyloid or tau PET SUVr.ConclusionIn the DLB continuum, abnormal levels of GFAP in plasma can be detected as early as the prodromal stages of the disease. Plasma pTau181 reached abnormal levels in the DLB stage. Higher plasma GFAP, NfL, and p‐tau181 are associated with higher amyloid and tau PET SUVr in the DLB continuum. Plasma biomarkers have the potential to contribute to screening and early diagnosis in the DLB continuum, which has implications in designing new treatments.

AbstractBackgroundSmall vessel disease (SVD) is a common vascular contributor to cognitive impairment and dementia. In this work, we evaluated and compared non‐imaging measures that can predict variability in SVD related white matter (WM) damage in a population‐based sample.MethodWe identified 752 participants in the population‐based sample of Mayo Clinic Study of Aging (≥50 years of age), who had at least 2 diffusion tensor imaging (DTI) scans and white matter hyperintensity (WMH) assessments along with baseline demographics, systemic vascular health, lifestyle, motor impairment, behavioral symptoms, and plasma markers (Summarized in Figure 1). We computed the WM markers of SVD: fractional anisotropy of genu of the corpus callosum (Genu‐FA) representative of early WM changes, WMH representative of late WM changes, and Vascular WM score (combination of Genu‐FA and WMH). Using all available data, we fit linear mixed effect models and evaluated predictors of WM markers by considering each category of features independently (with demographics) as well as by combining all categories of featuresResultPlasma, gait, systemic vascular, and life‐style measures were significant predictors of all three WM markers of SVD (Figure 2). The predictors of early and late WM slightly differed such that there were no additional significant contributions from behavioral and plasma measures to Genu‐FA. In the final composite models shown in Table 1, higher gait speed, lower number of cardiovascular and metabolic conditions (CMC) and lower Unified Parkinson’s disease rating scale scores were associated with better Genu‐FA whereas higher CMC, Beck Anxiety Inventory scores (BAI), and glial acidic protein (GFAP) levels were associated with higher burden of WMH.ConclusionOur observations evaluated the non‐imaging markers of greater WM damage that are relevant to vascular contributions to cognitive impairment to dementia (VCID). We found that in addition to higher vascular risk, worse plasma GFAP, gait measures, and BAI scores were predictors of greater WM damage. Some non‐imaging markers were more associated with early WM changes and others with late WM changes.

AbstractBackgroundFor blood‐based biomarkers to fulfill their potential to revolutionize diagnosis and management of Alzheimer’s disease (AD), additional research in diverse populations remains critical. Here, we analyzed a biracial sample to assess the profiles of blood‐based AD biomarkers and their relationships to cognition and medical comorbidities.MethodsSelf‐reported African‐American (AA; n = 267) and non‐Hispanic White (NHW; n = 268) participants evaluated through the Mayo Jacksonville Alzheimer’s Disease Research Center were matched on age, sex, and clinical diagnosis. Plasma AD biomarkers (Aβ42/40, p‐tau181, GFAP, NfL) were measured using the Quanterix SiMoA HD‐X analyzer. Cognition was assessed with the Mini Mental State Examination. Wilcoxon rank sum tests were used to assess for differences in plasma biomarker levels by sex. Linear models tested for associations of race, chronic kidney disease (CKD), and vascular risk factors with plasma AD biomarker levels, covarying for age and sex. Additional models assessed for interactions between race and plasma biomarkers in predicting cognition, further covarying for education.ResultsThe sample included adults aged 43‐100 years, with 69% women. Education was higher in NHW participants (median 16 vs. 12 years, p<0.001). APOE (apolipoprotein E) ε4 positivity was higher in AA participants (43% vs. 34%; p = 0.04). There were no differences in plasma AD biomarker levels between AA and NHW participants. These findings were unchanged after stratifying by cognitive status (unimpaired versus impaired). Although the association between p‐tau181 and cognition appeared stronger in NHW participants while the association between Aβ42/40 and cognition appeared stronger in AA participants, these findings did not survive after excluding individuals with CKD. Women displayed higher GFAP (p = 0.002) and lower p‐tau181 (p = 0.001) levels than men. Diabetes was inversely associated with GFAP levels (p<0.001).ConclusionsIn a biracial, community‐based sample, we observed that sex differences, CKD, and vascular risk factors contributed to variation in plasma AD biomarkers, while self‐reported race did not. Our results reinforce the critical need to account for sex and systemic medical comorbidities in equitably deploying blood‐based AD biomarkers in the general population.

AbstractBackgroundPlasma biomarkers for Alzheimer’s disease (AD) such as phosphorylated tau protein 181 (p‐tau 181), neurofilament light chain (NfL), amyloid‐β 42/40 ratio (Aβ42/40), and glial fibrillary acidic protein (GFAP) have shown high performance in the discrimination of those with clinical mild cognitive impairment (MCI) or dementia from cognitively unimpaired individuals, but few population‐based autopsy studies have evaluated the neuropathological correlates of plasma biomarkers.MethodWe utilized a population‐based prospective study of 350 participants with autopsy and antemortem plasma biomarker data. Plasma biomarkers Aβ42/40 ratio, p‐tau181, GFAP, and NfL were measured using Quanterix Simoa assays. We predicted AD neuropathological change (ADNC), Braak staging, and neuritic plaque score using these plasma biomarkers and investigated the added utility of cognitive and demographic information. We utilized a variable selection procedure in cross‐validated (CV) logistic regression models by minimizing the Bayesian Information Criterion to identify the best set of predictors for a given outcome among plasma biomarkers, demographic variables, and neuropsychological tests included in the Mayo Clinic Preclinical Alzheimer Cognitive Composite (Mayo‐PACC).ResultADNC was best predicted with plasma GFAP, NfL, p‐tau181 biomarkers along with APOE ε4 carrier status and Mayo‐PACC cognitive score (CV AUC = 0.821). Braak staging was best predicted using plasma GFAP, p‐tau181, and cognitive scores (CV AUC = 0.788). Neuritic plaque score was best predicted using plasma Aβ42/40 ratio, p‐tau181, GFAP, and NfL biomarkers (CV AUC = 0.778). Inclusion of plasma biomarkers demonstrated significantly better prediction of Braak staging (p<0.01) and neuritic plaque score (p<0.01), but not ADNC (p = 0.13), when compared to models that included only cognitive and demographic information. Univariate models consistently underperformed in comparison to multivariate models.ConclusionPlasma biomarkers can provide valuable predictive information about the presence of AD pathology, which can facilitate earlier recognition and diagnosis of AD. Incorporation of demographic and cognitive variables along with plasma variables in multivariable models will improve prediction accuracy of AD pathology, specifically Braak staging and ADNC.

AbstractBackgroundPlasma biomarkers of Alzheimer’s disease (AD) and neurodegeneration have demonstrated diagnostic utility and associations with AD pathology. Our objective was to map the average trajectories over age of plasma biomarkers and more established biomarkers including cognition, amyloid PET, and hippocampal volume.MethodWe included 1731 cognitively unimpaired (CU) and 226 mild cognitive impairment (MCI) participants from the Mayo Clinic Study of Aging (mean age of 70.3 years; 46.3% female; 14.8 years of mean education) with one or more measurements of amyloid‐PET, MRI with hippocampal volume measurements adjusted for head size (HVa), and plasma biomarkers (Aβ42/40 ratio, p‐tau181, GFAP, and NfL measured using Quanterix Simoa assays). A global cognitive z‐score was created by averaging the z‐scores of memory, language, executive function, and visuospatial domains. Smoothing spline curves were calculated for the values of each variable over age and placed on the same plot. Since each variable has a different scale, the smoothed curves were centered at the predicted value at age 50 and scaled so that a value of 1 would be one standard deviation of the fitted values from ages 50‐80.ResultAt age 50, GFAP and NfL start to increase, and Aβ42/40 was observed to decrease. At age 55, amyloid‐PET and p‐tau181 had a smooth and upward‐curving increase. After age 70, the average values of p‐tau181 increased at a higher rate. Average cognition started declining after 55 years. HVa began to decline after age 60 and then showed a steeper decline at age 72.ConclusionThis study demonstrates that predicted values of plasma GFAP, NfL, and Aβ42/40 across participants begin to change at younger ages than cognitive decline or increases observed in amyloid PET. The changes observed during middle age in GFAP and NfL likely reflect non‐AD pathologies and aging processes, while Aβ42/40 may be a leading indicator of future cerebral amyloidosis. Predicted plasma neurodegenerative biomarkers (GFAP and NfL) begin to change at younger ages than a traditional biomarker of neurodegeneration (HVa). Predicted ptau181 increases were observed in tandem with amyloid PET likely reflecting current amyloid status.

AbstractBackgroundPatients with dementia with Lewy bodies (DLB) may have Alzheimer´s disease (AD) pathology. Plasma biomarkers of beta‐amyloid (Aß), phosphorylated tau (pTau), and neurodegeneration are sensitive to AD neuropathologic changes in AD dementia. While these plasma biomarkers are well tested in the AD continuum, their performance for concomitant AD pathology in the DLB continuum is still unclear.MethodWe included patients with isolated REM sleep behavior disorder (iRBD; n = 15), with mild cognitive impairment with Lewy bodies (MCI‐LB; n = 37), and with DLB (n = 70) from the Mayo Clinic Alzheimer’s Disease Research Center. Cognitively unimpaired individuals (CU; n = 100) included from the Mayo Clinic Study of Aging were balanced on age and sex. A panel of plasma biomarkers of Aß40, Aß42, p‐tau181, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) measures was obtained. We calculated the ratio of plasma Aß40/42. Lower Aß40/42 indicates increased Aß pathology. Plasma Aß40, Aß42, GFAP, and NfL were measured using the Simoa® Neurology 4‐Plex E Advantage kit and pTau‐181 was measured with the Simoa® pTau‐181 Advantage V2 kit. Both were run on a Quanterix HD‐X analyzer. AD imaging biomarkers were assessed on PET using Pittsburgh compound B (PiB) for Aß and 18F‐Flortaucipir for tau.ResultHigher levels of plasma GFAP were observed in the MCI‐LB (p = 0.014) and DLB (p<0.001) groups compared to CU (Figure). DLB patients also showed higher levels of plasma pTau181 (p<0.001) and NfL (p<0.001). Higher amyloid and tau PET standardized uptake value ratio (SUVr) in the DLB continuum were associated with higher levels of plasma p‐tau181, NfL, and GFAP (p<0.001). After accounting for age, plasma Aß40/42 did not correlate with amyloid or tau PET SUVr.ConclusionIn the DLB continuum, abnormal levels of GFAP in plasma can be detected as early as the prodromal stages of the disease. Plasma pTau181 reached abnormal levels in the DLB stage. Higher plasma GFAP, NfL, and p‐tau181 are associated with higher amyloid and tau PET SUVr in the DLB continuum. Plasma biomarkers have the potential to contribute to screening and early diagnosis in the DLB continuum, which has implications in designing new treatments.