Dataset Information

Plasma amyloid, tau, and neurodegeneration biomarker profiles predict Alzheimer's disease pathology and clinical progression in older adults without dementia.

ABSTRACT:

Introduction

Plasma markers have been reported to be associated with brain amyloid burden, tau pathology, or neurodegeneration. We aimed to evaluate whether plasma biomarker profiles could predict Alzheimer's disease (AD) pathology and clinical progression in older adults without dementia.

Methods

Cross-sectional and longitudinal data of participants enrolled in this study were from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Plasma amyloid beta (Aβ)_1-42/Aβ_1-40 ratio was selected as the marker for amyloid pathology, p-tau181 for tau pathology, and neurofilament light for neurodegeneration. Cut-offs for these plasma markers were calculated with well-established positron emission tomography and structural imaging biomarkers as reference. Older adults without dementia were categorized into eight groups at baseline by plasma amyloid/tau/neurodegeneration (A/T/N) cut-offs. Clinical progression was analyzed using linear mixed-effects models and Cox proportional hazard models.

Results

A total of 183 participants (97 cognitively normal [CN] subjects and 86 patients with mild cognitive impairment [MCI]; mean age 72.6 years, and 48.1% men) were included. Participants with A+ had significantly higher proportions of apolipoprotein E (APOE) gene ɛ4 carriers than those with A-. Brain atrophy was observed in all groups of CN, whereas cognition decline was obvious in the A+T+N+ group. Compared to A-T-N-, MCI patients with A+T+N+ had faster cognition worsening and faster brain atrophy. In the whole cohort, A+T+N+ and A+T+N- participants were at higher risk of clinical progression.

Discussion

Plasma A/T/N biomarker profiles may predict AD pathology and clinical progression, indicating a potential role for plasma biomarkers in clinical trials. More research is warranted to develop a robust plasma AD framework.

SUBMITTER: Shen XN

PROVIDER: S-EPMC7513626 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Plasma amyloid, tau, and neurodegeneration biomarker profiles predict Alzheimer's disease pathology and clinical progression in older adults without dementia.

Shen Xue-Ning XN Li Jie-Qiong JQ Wang Hui-Fu HF Li Hong-Qi HQ Huang Yu-Yuan YY Yang Yu-Xiang YX Tan Lan L Dong Qiang Q Yu Jin-Tai JT

Alzheimer's & dementia (Amsterdam, Netherlands) 20200924 1

<h4>Introduction</h4>Plasma markers have been reported to be associated with brain amyloid burden, tau pathology, or neurodegeneration. We aimed to evaluate whether plasma biomarker profiles could predict Alzheimer's disease (AD) pathology and clinical progression in older adults without dementia.<h4>Methods</h4>Cross-sectional and longitudinal data of participants enrolled in this study were from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Plasma amyloid beta (Aβ)<sub>1-42</sub>/Aβ< ...[more]

PMID: 33005724

Similar Datasets

Project description:ImportanceA National Institute on Aging and Alzheimer's Association workgroup proposed a research framework for Alzheimer disease in which biomarker classification of research participants is labeled AT(N) for amyloid, tau, and neurodegeneration biomarkers.ObjectiveTo determine the associations between AT(N) biomarker profiles and memory decline in a population-based cohort of individuals without dementia age 60 years or older, and to determine whether biomarkers provide incremental prognostic value beyond more readily available clinical and genetic information.Design, setting, and participantsPopulation-based cohort study of cognitive aging in Olmsted County, Minnesota, that included 480 nondemented Mayo Clinic Study of Aging participants who had a clinical evaluation and amyloid positron emission tomography (PET) (A), tau PET (T), and magnetic resonance imaging (MRI) cortical thickness (N) measures between April 16, 2015, and November 1, 2017, and at least 1 clinical evaluation follow-up by November 12, 2018.ExposuresAge, sex, education, cardiovascular and metabolic conditions score, APOE genotype, and AT(N) biomarker profiles. Each of A, T, or (N) can be abnormal (+) or normal (-), resulting in 8 AT(N) profiles.Main outcomes and measuresPrimary outcome was a composite memory score measured longitudinally at 15-month intervals. Analyses measured the associations between predictor variables and the memory score, and whether AT(N) biomarker profiles significantly improved prediction of memory z score rates of change beyond a model with clinical and genetic variables only.ResultsParticipants were followed up for a median of 4.8 years (interquartile range [IQR], 3.8-5.1) and 44% were women (211/480). Median (IQR) ages ranged from 67 years (65-73) in the A-T-(N)- group to 83 years (76-87) in the A+T+(N)+ group. Of the participants, 92% (441/480) were cognitively unimpaired but the A+T+(N)+ group had the largest proportion of mild cognitive impairment (30%). AT(N) biomarkers improved the prediction of memory performance over a clinical model from an R2 of 0.26 to 0.31 (P < .001). Memory declined fastest in the A+T+(N)+, A+T+(N)-, and A+T-(N)+ groups compared with the other 5 AT(N) groups (P = .002). Estimated rates of decline in the 3 fastest declining groups were -0.13 (95% CI, -0.17 to -0.09), -0.10 (95% CI, -0.16 to -0.05), and -0.10 (95% CI, -0.13 to -0.06) z score units per year, respectively, for an 85-year-old APOE ε4 noncarrier.Conclusions and relevanceAmong older persons without baseline dementia followed for a median of 4.8 years, a prediction model that included amyloid PET, tau PET, and MRI cortical thickness resulted in a small but statistically significant improvement in predicting memory decline over a model with more readily available clinical and genetic variables. The clinical importance of this difference is uncertain.

Project description:PurposeBiomarkers used for predicting longitudinal cognitive change in Alzheimer's disease (AD) continuum are still elusive. Tau pathology, neuroinflammation, and neurodegeneration are the leading candidate predictors. We aimed to determine these three aspects of biomarkers in cerebrospinal fluid (CSF) and plasma to predict longitudinal cognition status using Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort.Patients and methodsA total of 430 subjects including, 96 cognitive normal (CN) with amyloid β (Aβ)-negative, 54 CN with Aβ-positive, 195 mild cognitive impairment (MCI) with Aβ-positive, and 85 AD with amyloid-positive (Aβ-positive are identified by CSF Aβ42/Aβ40 < 0.138). Aβ burden was evaluated by CSF and plasma Aβ42/Aβ40 ratio; tau pathology was evaluated by CSF and plasma phosphorylated-tau (p-tau181); microglial activation was measured by CSF soluble TREM2 (sTREM2) and progranulin (PGRN); neurodegeneration was measured by CSF and plasma t-tau and structural magnetic resonance imaging (MRI); cognition was examined annually over the subsequent 8 years using the Alzheimer's Disease Assessment Scale Cognition 13-item scale (ADAS13) and Mini-Mental State Exam (MMSE). Linear mixed-effects models (LME) were applied to assess the correlation between biomarkers and longitudinal cognition decline, as well as their effect size on the prediction of longitudinal cognitive decline.ResultsBaseline CSF Aβ42/Aβ40 ratio was decreased in MCI and AD compared to CN, while CSF p-tau181 and t-tau increased. Baseline CSF sTREM2 and PGRN did not show any differences in MCI and AD compared to CN. Baseline brain volumes (including the hippocampal, entorhinal, middle temporal lobe, and whole-brain) decreased in MCI and AD groups. For the longitudinal study, there were significant interaction effects of CSF p-tau181 × time, plasma p-tau181 × time, CSF sTREM2 × time, and brain volumes × time, indicating CSF, and plasma p-tau181, CSF sTREM2, and brain volumes could predict longitudinal cognition deterioration rate. CSF sTREM2, CSF, and plasma p-tau181 had similar medium prediction effects, while brain volumes showed stronger effects in predicting cognition decline.ConclusionOur study reported that baseline CSF sTREM2, CSF, and plasma p-tau181, as well as structural MRI, could predict longitudinal cognitive decline in subjects with positive AD pathology. Plasma p-tau181 can be used as a relatively noninvasive reliable biomarker for AD longitudinal cognition decline prediction.

Project description:BackgroundPlasma-derived β-amyloid, tau, and neurodegeneration (ATN) biomarkers can accurately diagnose Alzheimer's disease (AD) and predict its progression. Few studies have investigated the relationship between plasma biomarkers and changes in plasma inflammatory markers in clinically diagnosed AD.MethodsSeventy-four participants were recruited, including 30 mild-to-moderate AD dementia patients and 44 normal controls (NC). All participants underwent neuropsychological testing and blood sampling for biomarker testing. AD was clinically diagnosed according to the National Institute on Aging-Alzheimer's Association (NIA-AA) core criteria and required age-mismatched hippocampal atrophy. We performed Single Molecule Array (Simoa), an ultra-sensitive enzyme-linked immunosorbent assay (ELISA), to examine plasma ATN markers, including β-amyloid (Aβ) 40, Aβ42, p-tau181, total (t)-tau, neurofilament protein light chain (NfL), and inflammatory factors (TNF-α, IL-1β, IL-6, and IL-8).ResultsThe level of the plasma Aβ42/Aβ40 ratio was significantly declined and the levels of the plasma p-tau181, NfL and TNF-α were significantly higher in the AD group than the NC group, but there was no significant difference in the levels of plasma t-tau, IL-1β, IL-6, and IL-8 between the AD and NC groups. The levels of plasma p-tau181, NfL, Aβ42/Aβ40 ratio, and TNF-α were all associated with impairments in multiple cognitive domains. Among them, the plasma Aβ42/Aβ40 ratio, and the p-tau181 and TNF-α levels were associated with impairments in global cognition, memory, and visuospatial abilities, but not with executive function, only plasma NfL level was associated with executive function. Plasma NfL showed higher diagnostic performance in AD than in NC individuals (AUC = 0.833). A combined diagnostic prediction model of plasma Aβ42/Aβ40 ratio, p-tau 181, and NfL had the highest value than each factor alone (AUC = 0.902),with a sensitivity and specificity of 0.867 and 0.886, respectively.ConclusionThe levels of plasma ATN biomarkers (Aβ42/Aβ40 ratio, p-tua181, and NfL) were significantly changed in clinically diagnosed AD patients and they all associated with different domains of cognitive impairment. Plasma ATN biomarkers better differentiate mild-to-moderate AD dementia from NC when they are incorporated into diagnostic models together rather than individually. Plasma ATN biomarkers have the potential to be a screening tool for AD. However, the expression of inflammatory factors in AD patients requires further research.

Project description:Mild cognitive impairment (MCI) can be an early manifestation of Alzheimer's disease (AD) pathology, other pathologic entities [e.g., cerebrovascular disease, Lewy body disease, LATE (limbic-predominant age-related TDP-43 encephalopathy)], or mixed pathologies, with concomitant AD- and non-AD pathology being particularly common, albeit difficult to identify, in living MCI patients. The National Institute on Aging and Alzheimer's Association (NIA-AA) A/T/(N) [β-Amyloid/Tau/(Neurodegeneration)] AD research framework, which classifies research participants according to three binary biomarkers [β-amyloid (A+/A-), tau (T+/T-), and neurodegeneration (N+/N-)], provides an indirect means of identifying such cases. Individuals with A+T-(N+) MCI are thought to have both AD pathologic change, given the presence of β-amyloid, and non-AD pathophysiology, given neurodegeneration without tau, because in typical AD it is tau accumulation that is most tightly linked to neuronal injury and cognitive decline. Thus, in A+T-(N+) MCI (hereafter referred to as "mismatch MCI" for the tau-neurodegeneration mismatch), non-AD pathology is hypothesized to drive neurodegeneration and symptoms, because β-amyloid, in the absence of tau, likely reflects a preclinical stage of AD. We compared a group of individuals with mismatch MCI to groups with A+T+(N+) MCI (or "prodromal AD") and A-T-(N+) MCI (or "neurodegeneration-only MCI") on cross-sectional and longitudinal cognition and neuroimaging characteristics. β-amyloid and tau status were determined by CSF assays, while neurodegeneration status was based on hippocampal volume on MRI. Overall, mismatch MCI was less "AD-like" than prodromal AD and generally, with some exceptions, more closely resembled the neurodegeneration-only group. At baseline, mismatch MCI had less episodic memory loss compared to prodromal AD. Longitudinally, mismatch MCI declined more slowly than prodromal AD across all included cognitive domains, while mismatch MCI and neurodegeneration-only MCI declined at comparable rates. Prodromal AD had smaller baseline posterior hippocampal volume than mismatch MCI, and whole brain analyses demonstrated cortical thinning that was widespread in prodromal AD but largely restricted to the medial temporal lobes (MTLs) for the mismatch and neurodegeneration-only MCI groups. Longitudinally, mismatch MCI had slower rates of volume loss than prodromal AD throughout the MTLs. Differences in cross-sectional and longitudinal cognitive and neuroimaging measures between mismatch MCI and prodromal AD may reflect disparate underlying pathologic processes, with the mismatch group potentially being driven by non-AD pathologies on a background of largely preclinical AD. These findings suggest that β-amyloid status alone in MCI may not reveal the underlying driver of symptoms with important implications for enrollment in clinical trials and prognosis.

Project description:Neuropathological and in vivo studies have revealed a tight relationship between tau pathology and cognitive impairment across the Alzheimer's disease spectrum. However, tau pathology is also intimately associated with neurodegeneration and amyloid pathology. The aim of the present study was therefore to assess whether grey matter atrophy and amyloid pathology contribute to the relationship between tau pathology, as measured with 18F-AV-1451-PET imaging, and cognitive deficits in Alzheimer's disease. We included 40 amyloid-positive patients meeting criteria for mild cognitive impairment due to Alzheimer's disease (n = 5) or probable Alzheimer's disease dementia (n = 35). Twelve patients additionally fulfilled the diagnostic criteria for posterior cortical atrophy and eight for logopenic variant primary progressive aphasia. All participants underwent 3 T magnetic resonance imaging, amyloid (11C-PiB) positron emission tomography and tau (18F-AV-1451) positron emission tomography, and episodic and semantic memory, language, executive and visuospatial functions assessment. Raw cognitive scores were converted to age-adjusted Z-scores (W-scores) and averaged to compute composite scores for each cognitive domain. Independent regressions were performed between 18F-AV-1451 binding and each cognitive domain, and we used the Biological Parametric Mapping toolbox to further control for local grey matter volumes, 11C-PiB uptake, or both. Partial correlations and causal mediation analyses (mediation R package) were then performed in brain regions showing an association between cognition and both 18F-AV-1451 uptake and grey matter volume. Our results showed that decreased cognitive performance in each domain was related to increased 18F-AV-1451 binding in specific brain regions conforming to established brain-behaviour relationships (i.e. episodic memory: medial temporal lobe and angular gyrus; semantic memory: left anterior temporal regions; language: left posterior superior temporal lobe and supramarginal gyrus; executive functions: bilateral frontoparietal regions; visuospatial functions: right more than left occipitotemporal regions). This pattern of regional associations remained essentially unchanged-although less spatially extended-when grey matter volume or 11C-PiB uptake maps were added as covariates. Mediation analyses revealed both direct and grey matter-mediated effects of 18F-AV-1451 uptake on cognitive performance. Together, these results show that tau pathology is related in a region-specific manner to cognitive impairment in Alzheimer's disease. These regional relationships are weakly related to amyloid burden, but are in part mediated by grey matter volumes. This suggests that tau pathology may lead to cognitive deficits through a variety of mechanisms, including, but not restricted to, grey matter loss. These results might have implications for future therapeutic trials targeting tau pathology.

Dataset Information

Plasma amyloid, tau, and neurodegeneration biomarker profiles predict Alzheimer's disease pathology and clinical progression in older adults without dementia.

Introduction

Methods

Results

Discussion

Publications

Plasma amyloid, tau, and neurodegeneration biomarker profiles predict Alzheimer's disease pathology and clinical progression in older adults without dementia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets