Purpose
To examine associations between the
APOE-ε2
and
APOE-ε4
alleles and core Alzheimer’s disease (AD) pathological hallmarks as measured by amyloid-β (Aβ) and tau PET in older individuals without ...dementia.
Methods
We analyzed data from 462 ADNI participants without dementia who underwent Aβ (
18
Fflorbetapir or
18
Fflorbetaben) and tau (
18
Fflortaucipir) PET, structural MRI, and cognitive testing. Employing
APOE-ε3
homozygotes as the reference group, associations between
APOE-ε2
and
APOE-ε4
carriership with global Aβ PET and regional tau PET measures (entorhinal cortex (ERC), inferior temporal cortex, and Braak-V/VI neocortical composite regions) were investigated using linear regression models. In a subset of 156 participants, we also investigated associations between
APOE
genotype and regional tau accumulation over time using linear mixed models. Finally, we assessed whether Aβ mediated the cross-sectional and longitudinal associations between
APOE
genotype and tau.
Results
Compared to
APOE-ε3
homozygotes,
APOE-ε2
carriers had lower global Aβ burden (β
std
95% confidence interval (CI): − 0.31 − 0.45, − 0.16,
p
= 0.034) but did not differ on regional tau burden or tau accumulation over time
. APOE-ε4
participants showed higher Aβ (β
std
95%CI: 0.64 0.42, 0.82,
p
< 0.001) and tau burden (β
std
range: 0.27-0.51, all
p
< 0.006). In mediation analyses,
APOE-ε4
only retained an Aβ-independent effect on tau in the ERC.
APOE-ε4
showed a trend towards increased tau accumulation over time in Braak-V/VI compared to
APOE-ε3
homozygotes (β
std
95%CI: 0.10 − 0.02, 0.18,
p
= 0.11), and this association was fully mediated by baseline Aβ.
Conclusion
Our data suggest that the established protective effect of the
APOE-ε2
allele against developing clinical AD is primarily linked to resistance against Aβ deposition rather than tau pathology.
Several promising plasma biomarkers for Alzheimer's disease have been recently developed, but their neuropathological correlates have not yet been fully determined. To investigate and compare ...independent associations between multiple plasma biomarkers (p‐tau181, p‐tau217, p‐tau231, Aβ42/40, GFAP, and NfL) and neuropathologic measures of amyloid and tau, we included 105 participants from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) with antemortem plasma samples and a postmortem neuropathological exam, 48 of whom had longitudinal p‐tau217 and p‐tau181. When simultaneously including plaque and tangle loads, the Aβ42/40 ratio and p‐tau231 were only associated with plaques (ρAβ42/4095%CI = −0.53−0.65, −0.35, ρp‐tau23195%CI = 0.280.10, 0.43), GFAP was only associated with tangles (ρGFAP95%CI = 0.390.17, 0.57), and p‐tau217 and p‐tau181 were associated with both plaques (ρp‐tau21795%CI = 0.400.21, 0.56, ρp‐tau18195%CI = 0.360.15, 0.50) and tangles (ρp‐tau21795%CI = 0.520.34, 0.66; ρp‐tau18195%CI = 0.360.17, 0.52). A model combining p‐tau217 and the Aβ42/40 ratio showed the highest accuracy for predicting the presence of Alzheimer's disease neuropathological change (ADNC, AUC95%CI = 0.890.82, 0.96) and plaque load (R2 = 0.55), while p‐tau217 alone was optimal for predicting tangle load (R2 = 0.45). Our results suggest that high‐performing assays of plasma p‐tau217 and Aβ42/40 might be an optimal combination to assess Alzheimer's‐related pathology in vivo.
Synopsis
This study conducted a head‐to‐head comparison between multiple plasma biomarkers and neuropathological measures of amyloid plaques and neurofibrillary tangles.
Plasma p‐tau217 and p‐tau181 are independently associated with both amyloid plaques and tau neurofibrillary tangles, the main pathological hallmarks of Alzheimer's disease.
Plasma p‐tau217 may be a better Alzheimer's biomarker than p‐tau181 as it shows stronger associations with Alzheimer's pathology and is more sensitive to early pathological changes.
Plasma p‐tau217 longitudinal changes may help in predicting the presence of Alzheimer's pathology.
Plasma Aβ42/40 and plasma p‐tau231 are specifically associated with amyloid pathology, whereas plasma glial fibrillary acidic protein (GFAP) is specifically associated with tau pathology.
Plasma neurofilament light (NfL) is increased in participants with cerebral white matter rarefaction even after accounting for the presence of Alzheimer's disease pathology.
This study conducted a head‐to‐head comparison between multiple plasma biomarkers and neuropathological measures of amyloid plaques and neurofibrillary tangles.
•Consistent evidence has linked air pollution and Alzheimer’s disease (AD).•We examined the association between air pollutants and AD biomarkers.•Air pollution was adversely associated with brain Aβ ...deposition and NfL biomarkers.•Most associations were driven by individuals that were Aβ-positive.•Our findings support air pollution as a modifiable environmental risk factor for AD.
Air quality contributes to incidence of Alzheimer’s disease (AD) although the underlying neurobiological mechanisms are unclear. This study was aimed to examine the association between air pollution and concentrations of cerebrospinal fluid (CSF) AD biomarkers and amyloid-β (Aβ) deposition.
Participants and methods
The sample included 156 cognitively unimpaired adults aged 57 years (61 at biomarkers assessment) with increased risk of AD from the ALFA + Study. We examined CSF levels of Aβ42, Aβ40, p-Tau, t-Tau, neurofilament light (NfL) and cerebral amyloid load (Centiloid). A Land Use Regression model from 2009 was used to estimate residential exposure to air pollutants including nitrogen dioxide (NO2,) and particulate matter (PM2.5, PM2.5 abs, PM10). This model was considered a surrogate of long-term exposure until time of data collection in 2013–2014. Participants have resided in the same residence for at least the previous 3 years. Multiple linear regression models were used to estimate associations between air pollutants and biomarkers. The effect modification by CSF Aβ status and APOE-ε4 carriership was also assessed.
A consistent pattern of results indicated that greater exposure to NO2 and PM2.5 absorbance was associated with higher levels of brain Aβ deposition, while greater exposure to PM10 and PM2.5was associated with higher levels of CSF NfL. Most associations were driven by individuals that were Aβ-positive. Although APOE-ε4 status did not significantly modify these associations, the effect of air pollutants exposure on CSF NfL levels was stronger in APOE-ε4 carriers.
In a population of cognitively unimpaired adults with increased risk of AD, long-term exposure to air pollution was associated with higher levels in biomarkers of AD pathology. While further research is granted to elucidate the mechanisms involved in such associations, our results reinforce the role of air pollution as an environmental risk factor for AD.
IMPORTANCE: Glial fibrillary acidic protein (GFAP) is a marker of reactive astrogliosis that increases in the cerebrospinal fluid (CSF) and blood of individuals with Alzheimer disease (AD). However, ...it is not known whether there are differences in blood GFAP levels across the entire AD continuum and whether its performance is similar to that of CSF GFAP. OBJECTIVE: To evaluate plasma GFAP levels throughout the entire AD continuum, from preclinical AD to AD dementia, compared with CSF GFAP. DESIGN, SETTING, AND PARTICIPANTS: This observational, cross-sectional study collected data from July 29, 2014, to January 31, 2020, from 3 centers. The Translational Biomarkers in Aging and Dementia (TRIAD) cohort (Montreal, Canada) included individuals in the entire AD continuum. Results were confirmed in the Alzheimer’s and Families (ALFA+) study (Barcelona, Spain), which included individuals with preclinical AD, and the BioCogBank Paris Lariboisière cohort (Paris, France), which included individuals with symptomatic AD. MAIN OUTCOMES AND MEASURES: Plasma and CSF GFAP levels measured with a Simoa assay were the main outcome. Other measurements included levels of CSF amyloid-β 42/40 (Aβ42/40), phosphorylated tau181 (p-tau181), neurofilament light (NfL), Chitinase-3-like protein 1 (YKL40), and soluble triggering receptor expressed on myeloid cells 2 (sTREM2) and levels of plasma p-tau181 and NfL. Results of amyloid positron emission tomography (PET) were available in TRIAD and ALFA+, and results of tau PET were available in TRIAD. RESULTS: A total of 300 TRIAD participants (177 women 59.0%; mean SD age, 64.6 17.6 years), 384 ALFA+ participants (234 women 60.9%; mean SD age, 61.1 4.7 years), and 187 BioCogBank Paris Lariboisière participants (116 women 62.0%; mean SD age, 69.9 9.2 years) were included. Plasma GFAP levels were significantly higher in individuals with preclinical AD in comparison with cognitively unimpaired (CU) Aβ-negative individuals (TRIAD: Aβ-negative mean SD, 185.1 93.5 pg/mL, Aβ-positive mean SD, 285.0 142.6 pg/mL; ALFA+: Aβ-negative mean SD, 121.9 42.4 pg/mL, Aβ-positive mean SD, 169.9 78.5 pg/mL). Plasma GFAP levels were also higher among individuals in symptomatic stages of the AD continuum (TRIAD: CU Aβ-positive mean SD, 285.0 142.6 pg/mL, mild cognitive impairment MCI Aβ-positive mean SD, 332.5 153.6 pg/mL; AD mean SD, 388.1 152.8 pg/mL vs CU Aβ-negative mean SD, 185.1 93.5 pg/mL; Paris: MCI Aβ-positive, mean SD, 368.6 158.5 pg/mL; AD dementia, mean SD, 376.4 179.6 pg/mL vs CU Aβ-negative mean SD, 161.2 67.1 pg/mL). Plasma GFAP magnitude changes were consistently higher than those of CSF GFAP. Plasma GFAP more accurately discriminated Aβ-positive from Aβ-negative individuals than CSF GFAP (area under the curve for plasma GFAP, 0.69-0.86; area under the curve for CSF GFAP, 0.59-0.76). Moreover, plasma GFAP levels were positively associated with tau pathology only among individuals with concomitant Aβ pathology. CONCLUSIONS AND RELEVANCE: This study suggests that plasma GFAP is a sensitive biomarker for detecting and tracking reactive astrogliosis and Aβ pathology even among individuals in the early stages of AD.
IMPORTANCE: Alzheimer disease (AD) pathology starts with a prolonged phase of β-amyloid (Aβ) accumulation without symptoms. The duration of this phase differs greatly among individuals. While this ...disease phase has high relevance for clinical trial designs, it is currently unclear how to best predict the onset of clinical progression. OBJECTIVE: To evaluate combinations of different plasma biomarkers for predicting cognitive decline in Aβ-positive cognitively unimpaired (CU) individuals. DESIGN, SETTING, AND PARTICIPANTS: This prospective population-based prognostic study evaluated data from 2 prospective longitudinal cohort studies (the Swedish BioFINDER-1 and the Wisconsin Registry for Alzheimer Prevention WRAP), with data collected from February 8, 2010, to October 21, 2020, for the BioFINDER-1 cohort and from August 11, 2011, to June 27, 2021, for the WRAP cohort. Participants were CU individuals recruited from memory clinics who had brain Aβ pathology defined by cerebrospinal fluid (CSF) Aβ42/40 in the BioFINDER-1 study and by Pittsburgh Compound B (PiB) positron emission tomography (PET) in the WRAP study. A total of 564 eligible Aβ-positive and Aβ-negative CU participants with available relevant data from the BioFINDER-1 and WRAP cohorts were included in the study; of those, 171 Aβ-positive participants were included in the main analyses. EXPOSURES: Baseline P-tau181, P-tau217, P-tau231, glial fibrillary filament protein, and neurofilament light measured in plasma; CSF biomarkers in the BioFINDER-1 cohort, and PiB PET uptake in the WRAP cohort. MAIN OUTCOMES AND MEASURES: The primary outcome was longitudinal measures of cognition (using the Mini-Mental State Examination MMSE and the modified Preclinical Alzheimer Cognitive Composite mPACC) over a median of 6 years (range, 2-10 years). The secondary outcome was conversion to AD dementia. Baseline biomarkers were used in linear regression models to predict rates of longitudinal cognitive change (calculated separately). Models were adjusted for age, sex, years of education, apolipoprotein E ε4 allele status, and baseline cognition. Multivariable models were compared based on model R2 coefficients and corrected Akaike information criterion. RESULTS: Among 171 Aβ-positive CU participants included in the main analyses, 119 (mean SD age, 73.0 5.4 years; 60.5% female) were from the BioFINDER-1 study, and 52 (mean SD age, 64.4 4.6 years; 65.4% female) were from the WRAP study. In the BioFINDER-1 cohort, plasma P-tau217 was the best marker to predict cognitive decline in the mPACC (model R2 = 0.41) and the MMSE (model R2 = 0.34) and was superior to the covariates-only models (mPACC: R2 = 0.23; MMSE: R2 = 0.04; P < .001 for both comparisons). Results were validated in the WRAP cohort; for example, plasma P-tau217 was associated with mPACC slopes (R2 = 0.13 vs 0.01 in the covariates-only model; P = .01) and MMSE slopes (R2 = 0.29 vs 0.24 in the covariates-only model; P = .046). Sparse models were identified with plasma P-tau217 as a predictor of cognitive decline. Power calculations for enrichment in hypothetical clinical trials revealed large relative reductions in sample sizes when using plasma P-tau217 to enrich for CU individuals likely to experience cognitive decline over time. CONCLUSIONS AND RELEVANCE: In this study, plasma P-tau217 predicted cognitive decline in patients with preclinical AD. These findings suggest that plasma P-tau217 may be used as a complement to CSF or PET for participant selection in clinical trials of novel disease-modifying treatments.
Purpose
To investigate the sensitivity of visual read (VR) to detect early amyloid pathology and the overall utility of regional VR.
Methods
18
FFlutemetamol PET images of 497 subjects (ALFA+
N
= ...352; ADC
N
= 145) were included. Scans were visually assessed according to product guidelines, recording the number of positive regions (0–5) and a final negative/positive classification. Scans were quantified using the standard and regional Centiloid (CL) method. The agreement between VR-based classification and published CL-based cut-offs for early (CL = 12) and established (CL = 30) pathology was determined. An optimal CL cut-off maximizing Youden’s index was derived. Global and regional CL quantification was compared to VR. Finally, 28 post-mortem cases from the
18
Fflutemetamol phase III trial were included to assess the percentage agreement between VR and neuropathological classification of neuritic plaque density.
Results
VR showed excellent agreement against CL = 12 (
κ
= .89, 95.2%) and CL = 30 (
κ
= .88, 95.4%) cut-offs. ROC analysis resulted in an optimal CL = 17 cut-off against VR (sensitivity = 97.9%, specificity = 97.8%). Each additional positive VR region corresponded to a clear increase in global CL. Regional VR was also associated with regional CL quantification. Compared to mCERAD
SOT
-based classification (i.e., any region mCERAD
SOT
> 1.5), VR was in agreement in 89.3% of cases, with 13 true negatives, 12 true positives, and 3 false positives (FP). Regional sparse-to-moderate neuritic and substantial diffuse Aβ plaque was observed in all FP cases. Regional VR was also associated with regional plaque density.
Conclusion
VR is an appropriate method for assessing early amyloid pathology and that grading the
extent
of visual amyloid positivity could present clinical value.
In Alzheimer’s disease (AD), tau phosphorylation in the brain and its subsequent release into cerebrospinal fluid (CSF) and blood is a dynamic process that changes during disease evolution. The main ...aim of our study was to characterize the pattern of changes in phosphorylated tau (p‐tau) in the preclinical stage of the Alzheimer’s continuum. We measured three novel CSF p‐tau biomarkers, phosphorylated at threonine‐181 and threonine‐217 with an N‐terminal partner antibody and at threonine‐231 with a mid‐region partner antibody. These were compared with an automated mid‐region p‐tau181 assay (Elecsys) as the gold standard p‐tau measure. We demonstrate that these novel p‐tau biomarkers increase more prominently in preclinical Alzheimer, when only subtle changes of amyloid‐β (Aβ) pathology are detected, and can accurately differentiate Aβ‐positive from Aβ‐negative cognitively unimpaired individuals. Moreover, we show that the novel plasma N‐terminal p‐tau181 biomarker is mildly but significantly increased in the preclinical stage. Our results support the idea that early changes in neuronal tau metabolism in preclinical Alzheimer, likely in response to Aβ exposure, can be detected with these novel p‐tau assays.
SYNOPSIS
This study investigated novel CSF and plasma p‐tau biomarkers in the preclinical stage of the Alzheimer’s continuum and compared them with the widely used CSF Mid‐ptau181.
Novel p‐tau biomarkers CSF N‐p‐tau181, N‐p‐tau217 and Mid‐p‐tau231 increase early in the Alzheimer’s continuum, when only subtle changes in Aβ pathology are detected.
CSF N‐p‐tau181, N‐p‐tau217 and Mid‐p‐tau231 can accurately differentiate Aβ‐positive, cognitively unimpaired individuals from those that are Aβ‐negative.
Plasma N‐p‐tau181 biomarker is significantly increased in the preclinical stage of the Alzheimer’s continuum.
These results suggest that there are early changes in tau metabolism in preclinical Alzheimer, probably in response to emerging Aβ pathology.
This study investigated novel CSF and plasma p‐tau biomarkers in the preclinical stage of the Alzheimer’s continuum and compared them with the widely used CSF Mid‐ptau181.
Background
18
Fflutemetamol PET scanning provides information on brain amyloid load and has been approved for routine clinical use based upon visual interpretation as either negative (equating to ...none or sparse amyloid plaques) or amyloid positive (equating to moderate or frequent plaques). Quantitation is however fundamental to the practice of nuclear medicine and hence can be used to supplement amyloid reading methodology especially in unclear cases.
Methods
A total of 2770
18
Fflutemetamol images were collected from 3 clinical studies and 6 research cohorts with available visual reading of
18
Fflutemetamol and quantitative analysis of images. These were assessed further to examine both the discordance and concordance between visual and quantitative imaging primarily using thresholds robustly established using pathology as the standard of truth. Scans covered a wide range of cases (i.e. from cognitively unimpaired subjects to patients attending the memory clinics). Methods of quantifying amyloid ranged from using CE/510K cleared marked software (e.g. CortexID, Brass), to other research-based methods (e.g. PMOD, CapAIBL). Additionally, the clinical follow-up of two types of discordance between visual and quantitation (V+Q- and V-Q+) was examined with competing risk regression analysis to assess possible differences in prediction for progression to Alzheimer’s disease (AD) and other diagnoses (OD).
Results
Weighted mean concordance between visual and quantitation using the autopsy-derived threshold was 94% using pons as the reference region. Concordance from a sensitivity analysis which assessed the maximum agreement for each cohort using a range of cut-off values was also estimated at approximately 96% (weighted mean). Agreement was generally higher in clinical cases compared to research cases. V-Q+ discordant cases were 11% more likely to progress to AD than V+Q- for the SUVr with pons as reference region.
Conclusions
Quantitation of amyloid PET shows a high agreement vs binary visual reading and also allows for a continuous measure that, in conjunction with possible discordant analysis, could be used in the future to identify possible earlier pathological deposition as well as monitor disease progression and treatment effectiveness.
Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer’s disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo ...using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD
continuum
and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.
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