PET and CSF amyloid-β status are differently predicted by patient features: information from discordant cases

Continuous β-Amyloid CSF/PET Imbalance Model to Capture Alzheimer Disease Heterogeneity

BACKGROUND AND OBJECTIVES

Discordance between CSF and PET biomarkers of β-amyloid (Aβ) might reflect an imbalance between soluble and aggregated species, possibly reflecting disease heterogeneity. Previous studies generally used binary cutoffs to assess discrepancies in CSF/PET biomarkers, resulting in a loss of information on the extent of discordance. In this study, we (1) jointly modeled Aβ-CSF/PET data to derive a continuous measure of the imbalance between soluble and fibrillar pools of Aβ, (2) investigated factors contributing to this imbalance, and (3) examined associations with cognitive trajectories.

METHODS

Across 822 cognitively unimpaired (n = 261) and cognitively impaired (n = 561) Alzheimer's Disease Neuroimaging Initiative individuals (384 [46.7%] females, mean age 73.0 ± 7.4 years), we fitted baseline CSF-Aβ42 and global Aβ-PET to a hyperbolic regression model, deriving a participant-specific Aβ-aggregation score (standardized residuals); negative values represent more soluble relative to aggregated Aβ and positive values more aggregated relative to soluble Aβ. Using linear models, we investigated whether methodological factors, demographics, CSF biomarkers, and vascular burden contributed to Aβ-aggregation scores. With linear mixed models, we assessed whether Aβ-aggregation scores were predictive of cognitive functioning. Analyses were repeated in an early independent validation cohort of 383 Amyloid Imaging to Prevent Alzheimer's Disease Prognostic and Natural History Study individuals (224 [58.5%] females, mean age 65.2 ± 6.9 years).

RESULTS

The imbalance model could be fit (pseudo-R2 = 0.94) in both cohorts, across CSF kits and PET tracers. Although no associations were observed with the main methodological factors, lower Aβ-aggregation scores were associated with larger ventricular volume (β = 0.13, p < 0.001), male sex (β = -0.18, p = 0.019), and homozygous APOE-ε4 carriership (β = -0.56, p < 0.001), whereas higher scores were associated with increased uncorrected CSF p-tau (β = 0.17, p < 0.001) and t-tau (β = 0.16, p < 0.001), better baseline executive functioning (β = 0.12, p < 0.001), and slower global cognitive decline (β = 0.14, p = 0.006). In the validation cohort, we replicated the associations with APOE-ε4, CSF t-tau, and, although modestly, with cognition.

DISCUSSION

We propose a novel continuous model of Aβ CSF/PET biomarker imbalance, accurately describing heterogeneity in soluble vs aggregated Aβ pools in 2 independent cohorts across the full Aβ continuum. Aβ-aggregation scores were consistently associated with genetic and AD-associated CSF biomarkers, possibly reflecting disease heterogeneity beyond methodological influences.

MRI or 18F-FDG PET for Brain Age Gap Estimation: Links to Cognition, Pathology, and Alzheimer Disease Progression

Deviations of brain age from chronologic age, known as the brain age gap (BAG), have been linked to neurodegenerative diseases such as Alzheimer disease (AD). Here, we compare the associations of MRI-derived (atrophy) or 18F-FDG PET-derived (brain metabolism) BAG with cognitive performance, neuropathologic burden, and disease progression in cognitively normal individuals (CNs) and individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI). Methods: Machine learning pipelines were trained to estimate brain age from 185 matched T1-weighted MRI or 18F-FDG PET scans of CN from the Alzheimer's Disease Neuroimaging Initiative and validated in external test sets from the Open Access of Imaging and German Center for Neurodegenerative Diseases-Longitudinal Cognitive Impairment and Dementia studies. BAG was correlated with measures of cognitive performance and AD neuropathology in CNs, SCD subjects, and MCI subjects. Finally, BAG was compared between cognitively stable and declining individuals and subsequently used to predict disease progression. Results: MRI (mean absolute error, 2.49 y) and 18F-FDG PET (mean absolute error, 2.60 y) both estimated chronologic age well. At the SCD stage, MRI-based BAG correlated significantly with beta-amyloid1-42 (Aβ1-42) in cerebrospinal fluid, whereas 18F-FDG PET BAG correlated with memory performance. At the MCI stage, both BAGs were associated with memory and executive function performance and cerebrospinal fluid Aβ1-42, but only MRI-derived BAG correlated with phosphorylated-tau181/Aβ1-42 Lastly, MRI-estimated BAG predicted MCI-to-AD progression better than 18F-FDG PET-estimated BAG (areas under the curve, 0.73 and 0.60, respectively). Conclusion: Age was reliably estimated from MRI or 18F-FDG PET. MRI BAG reflected cognitive and pathologic markers of AD in SCD and MCI, whereas 18F-FDG PET BAG was sensitive mainly to early cognitive impairment, possibly constituting an independent biomarker of brain age-related changes.

Mapping the human brain proteome: opportunities, challenges, and clinical potential

INTRODUCTION

Due to the segmented functions and complexity of the human brain, the characterization of molecular profiles within specific areas such as brain structures and biofluids is essential to unveil the molecular basis for structure specialization as well as the molecular imbalance associated with neurodegenerative and psychiatric diseases.

AREAS COVERED

Much of our knowledge about brain functionality derives from neurophysiological, anatomical, and transcriptomic approaches. More recently, laser capture and imaging proteomics, technological and computational developments in LC-MS/MS, as well as antibody/aptamer-based platforms have allowed the generation of novel cellular, spatial, and posttranslational dimensions as well as innovative facets in biomarker validation and druggable target identification.

EXPERT OPINION

Proteomics is a powerful toolbox to functionally characterize, quantify, and localize the extensive protein catalog of the human brain across physiological and pathological states. Brain function depends on multi-dimensional protein homeostasis, and its elucidation will help us to characterize biological pathways that are essential to properly maintain cognitive functions. In addition, comprehensive human brain pathological proteomes may be the basis in computational drug-repositioning methods as a strategy for unveiling potential new therapies in neurodegenerative and psychiatric disorders.

A Pragmatic, Data-Driven Method to Determine Cutoffs for CSF Biomarkers of Alzheimer Disease Based on Validation Against PET Imaging

BACKGROUND AND OBJECTIVES

To elaborate a new algorithm to establish a standardized method to define cutoffs for CSF biomarkers of Alzheimer disease (AD) by validating the algorithm against CSF classification derived from PET imaging.

METHODS

Low and high levels of CSF phosphorylated tau were first identified to establish optimal cutoffs for CSF β-amyloid (Aβ) peptide biomarkers. These Aβ cutoffs were then used to determine cutoffs for CSF tau and phosphorylated tau markers. We compared this algorithm to a reference method, based on tau and amyloid PET imaging status (ADNI study), and then applied the algorithm to 10 large clinical cohorts of patients.

RESULTS

A total of 6,922 patients with CSF biomarker data were included (mean [SD] age: 70.6 [8.5] years, 51.0% women). In the ADNI study population (n = 497), the agreement between classification based on our algorithm and the one based on amyloid/tau PET imaging was high, with Cohen's kappa coefficient between 0.87 and 0.99. Applying the algorithm to 10 large cohorts of patients (n = 6,425), the proportion of persons with AD ranged from 25.9% to 43.5%.

DISCUSSION

The proposed novel, pragmatic method to determine CSF biomarker cutoffs for AD does not require assessment of other biomarkers or assumptions concerning the clinical diagnosis of patients. Use of this standardized algorithm is likely to reduce heterogeneity in AD classification.

Detection of Alzheimer's disease amyloid beta 1-42, p-tau, and t-tau assays

INTRODUCTION

We aimed to provide cut points for the automated Elecsys Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers.

METHODS

Cut points for Elecsys amyloid beta 42 (Aβ42), total tau (t-tau), hyperphosphorylated tau (p-tau), and t-tau/Aβ42 and p-tau/Aβ42 ratios were evaluated in Mayo Clinic Study of Aging (n = 804) and Mayo Clinic Alzheimer's Disease Research Center (n = 70) participants.

RESULTS

The t-tau/Aβ42 and p-tau/Aβ42 ratios had a higher percent agreement with normal/abnormal amyloid positron emission tomography (PET) than the individual CSF markers. Reciever Operating Characteristic (ROC)-based cut points were 0.26 (0.24-0.27) for t-tau/Aβ42 and 0.023 (0.020-0.025) for p-tau/Aβ42. Ratio cut points derived from other cohorts performed as well in our cohort as our own did. Individual biomarkers had worse diagnostic properties and more variable results in terms of positive and negative percent agreement (PPA and NPA).

CONCLUSION

CSF t-tau/Aβ42 and p-tau/Aβ42 ratios are very robust indicators of AD. For individual biomarkers, the intended use should determine which cut point is chosen.

Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum

IMPORTANCE

One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.

OBJECTIVE

To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.

EXPOSURES

Alzheimer disease biomarkers detected on PET or in CSF.

MAIN OUTCOMES AND MEASURES

Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.

RESULTS

Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18).

CONCLUSIONS AND RELEVANCE

This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.

Cerebrospinal fluid dynamics and discordant amyloid biomarkers

Do MRI-based metrics of a CSF-dynamics disorder, disproportionately enlarged subarachnoid-space hydrocephalus (DESH), correlate with discordant amyloid biomarkers (low CSF β-amyloid 1-42, normal Aβ-PET scan)? Individuals ≥50 years from the Mayo Clinic Study of Aging, with MRI, 11C-Pittsburgh compound B (Aβ) PET scans, and CSF phosphorylated-tau protein and Aβ42, were categorized into 4 groups: normal and/or abnormal by CSF β-amyloid 1-42 and Aβ amyloid PET. Within groups, we noted MRI patterns of CSF-dynamics disorders and Aβ-PET accumulation-change rate. One-hundred participants (21%) in the abnormal-CSF and/or normal-PET group had highest DESH-pattern scores and lowest CSF-phosphorylated-tau levels. Among normal amyloid-PET individuals, a 1-unit DESH-pattern score increase correlated with 30%-greater odds of abnormal amyloid CSF after age, and sex adjustment. Mean rate over time of amyloid-PET accumulation in abnormal-CSF and/or normal-PET individuals approximated individuals with normal amyloid values. Adjusting for phosphorylated-tau, abnormal CSF-amyloid and/or normal amyloid-PET individuals had higher mean amyloid-PET accumulation rates than normal individuals. CSF dynamics disorders confound β-amyloid and phosphorylated-tau CSF-biomarker interpretation.

Cognitive impairment and World Trade Centre-related exposures

On 11 September 2001 the World Trade Center (WTC) in New York was attacked by terrorists, causing the collapse of multiple buildings including the iconic 110-story 'Twin Towers'. Thousands of people died that day from the collapse of the buildings, fires, falling from the buildings, falling debris, or other related accidents. Survivors of the attacks, those who worked in search and rescue during and after the buildings collapsed, and those working in recovery and clean-up operations were exposed to severe psychological stressors. Concurrently, these 'WTC-affected' individuals breathed and ingested a mixture of organic and particulate neurotoxins and pro-inflammogens generated as a result of the attack and building collapse. Twenty years later, researchers have documented neurocognitive and motor dysfunctions that resemble the typical features of neurodegenerative disease in some WTC responders at midlife. Cortical atrophy, which usually manifests later in life, has also been observed in this population. Evidence indicates that neurocognitive symptoms and corresponding brain atrophy are associated with both physical exposures at the WTC and chronic post-traumatic stress disorder, including regularly re-experiencing traumatic memories of the events while awake or during sleep. Despite these findings, little is understood about the long-term effects of these physical and mental exposures on the brain health of WTC-affected individuals, and the potential for neurocognitive disorders. Here, we review the existing evidence concerning neurological outcomes in WTC-affected individuals, with the aim of contextualizing this research for policymakers, researchers and clinicians and educating WTC-affected individuals and their friends and families. We conclude by providing a rationale and recommendations for monitoring the neurological health of WTC-affected individuals.

Performance of the plasma Aβ42/Aβ40 ratio, measured with a novel HPLC-MS/MS method, as a biomarker of amyloid PET status in a DPUK-KOREAN cohort

Background

We assessed the feasibility of plasma Aβ42/Aβ40 determined using a novel liquid chromatography-mass spectrometry method (LC-MS) as a useful biomarker of PET status in a Korean cohort from the DPUK Study.

Methods

A total of 580 participants belonging to six groups, Alzheimer’s disease dementia (ADD, n = 134), amnestic mild cognitive impairment (aMCI, n = 212), old controls (OC, n = 149), young controls (YC, n = 15), subcortical vascular cognitive impairment (SVCI, n = 58), and cerebral amyloid angiopathy (CAA, n = 12), were included in this study. Plasma Aβ40 and Aβ42 were quantitated using a new antibody-free, LC-MS, which drastically reduced the sample preparation time and cost. We performed receiver operating characteristic (ROC) analysis to develop the cutoff of Aβ42/Aβ40 and investigated its performance predicting centiloid-based PET positivity (PET+).

Results

Plasma Aβ42/Aβ40 were lower for PET+ individuals in ADD, aMCI, OC, and SVCI (p < 0.001), but not in CAA (p = 0.133). In the group of YC, OC, aMCI, and ADD groups, plasma Aβ42/Aβ40 predicted PET+ with an area under the ROC curve (AUC) of 0.814 at a cutoff of 0.2576. When adding age, APOE4, and diagnosis, the AUC significantly improved to 0.912.

Conclusion

Plasma Aβ42/Aβ40, as measured by this novel LC-MS method, showed good discriminating performance based on PET positivity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00911-7.

Prognostic Impact of 18-F-Florbetaben Amyloid PET Imaging in Patients with Isolated Increases in Cerebrospinal Fluid Phospho-Tau Biomarkers: A Longitudinal Study

This longitudinal study evaluates the prognostic impact of amyloid PET in patients suspected of Alzheimer's disease and presenting with isolated cerebrospinal fluid (CSF) increases in P-Tau proteins (NCT02556502). The rate of conversion, based on the DSM-5 criteria and all collected data (average follow-up of 39.2±13.2 months), was determined by a panel of experts blinded to the PET results and was 75%(6/8) for positive and 35%(6/17) for negative baseline amyloid PET. In this population with isolated CSF increases in P-Tau, a positive baseline amyloid PET was associated with greater than twice the proportion of dementia conversions within the following three years.

The complexity of Alzheimer's disease: an evolving puzzle

The history of Alzheimer's disease (AD) started in 1907, but we needed to wait until the end of the century to identify the components of pathological hallmarks and genetic subtypes and to formulate the first pathogenic hypothesis. Thanks to biomarkers and new technologies, the concept of AD then rapidly changed from a static view of an amnestic dementia of the presenium to a biological entity that could be clinically manifested as normal cognition or dementia of different types. What is clearly emerging from studies is that AD is heterogeneous in each aspect, such as amyloid composition, tau distribution, relation between amyloid and tau, clinical symptoms, and genetic background, and thus it is probably impossible to explain AD with a single pathological process. The scientific approach to AD suffers from chronological mismatches between clinical, pathological, and technological data, causing difficulty in conceiving diagnostic gold standards and in creating models for drug discovery and screening. A recent mathematical computer-based approach offers the opportunity to study AD in real life and to provide a new point of view and the final missing pieces of the AD puzzle.

Matching Clinical Diagnosis and Amyloid Biomarkers in Alzheimer's Disease and Frontotemporal Dementia

BACKGROUND

The aims of this study were to compare the diagnostic accuracy, sensitivity, specificity, and positive and negative predictive values (PPV, NPV) of different cerebrospinal fluid (CSF) amyloid biomarkers and amyloid-Positron Emission Tomography (PET) in patients with a clinical diagnosis of Alzheimer's disease (AD) and Frontotemporal Dementia (FTD); to compare concordance between biomarkers; and to provide an indication of their use and interpretation.

METHODS

We included 148 patients (95 AD and 53 FTD), who underwent clinical evaluation, neuropsychological assessment, and at least one amyloid biomarker (CSF analysis or amyloid-PET). Thirty-six patients underwent both analyses. One-hundred-thirteen patients underwent Apolipoprotein E (ApoE) genotyping.

RESULTS

Amyloid-PET presented higher diagnostic accuracy, sensitivity, and NPV than CSF Aβ_1-42 but not Aβ_42/40 ratio. Concordance between CSF biomarkers and amyloid-PET was higher in FTD patients compared to AD cases. None of the AD patients presented both negative Aβ biomarkers.

CONCLUSIONS

CSF Aβ_42/40 ratio significantly increased the diagnostic accuracy of CSF biomarkers. On the basis of our current and previous data, we suggest a flowchart to guide the use of biomarkers according to clinical suspicion: due to the high PPV of both amyloid-PET and CSF analysis including Aβ_42/40, in cases of concordance between at least one biomarker and clinical diagnosis, performance of the other analysis could be avoided. A combination of both biomarkers should be performed to better characterize unclear cases. If the two amyloid biomarkers are both negative, an underlying AD pathology can most probably be excluded.

PET Amyloid and Tau Status Are Differently Affected by Patient Features

BACKGROUND

Amyloid-β (Aβ) plaques and tau neurofibrillary tangles are two neuropathological hallmarks of Alzheimer's disease (AD), which both can be visualized in vivo using PET radiotracers, opening new opportunities to study disease mechanisms.

OBJECTIVE

Our study investigated 11 non-PET factors in 5 categories (including demographic, clinical, genetic, MRI, and cerebrospinal fluid (CSF) features) possibly affecting PET amyloid and tau status to explore the relationships between amyloid and tau pathology, and whether these features had a different association with amyloid and tau status.

METHODS

We included 372 nondemented elderly from the Alzheimer's Disease Neuroimaging Initiative cohort. All underwent PET amyloid and tau analysis simultaneously, and were grouped into amyloid/tau quadrants based on previously established abnormality cut points. We examined the associations of above selected features with PET amyloid and tau status using a multivariable logistic regression model, then explored whether there was an obvious correlation between the significant features and PET amyloid or tau levels.

RESULTS

Our results demonstrated that PET amyloid and tau status were differently affected by patient features, and CSF biomarker features provided most significant values associating PET findings. CSF Aβ42/40 was the most important factor affecting amyloid PET status, and negatively correlated with amyloid PET levels. CSF pTau could significantly influence both amyloid and tau PET status. Besides CSF pTau and Aβ42, APOEɛ4 allele status and Mini-Mental State Examination scores also could influence tau PET status, and significantly correlated with tau PET levels.

CONCLUSION

Our results support that tau pathology possibly affected by Aβ-independent factors, implicating the importance of tau pathology in AD pathogenesis.

Clinical Utility of the Pathogenesis-Related Proteins in Alzheimer's Disease

Research on the Aβ cascade and alternations of biomarkers in neuro-inflammation, synaptic dysfunction, and neuronal injury followed by Aβ have progressed. But the question is how to use the biomarkers. Here, we examine the evidence and pathogenic implications of protein interactions and the time order of alternation. After the deposition of Aβ, the change of tau, neurofilament light chain (NFL), and neurogranin (Ng) is the main alternation and connection to others. Neuro-inflammation, synaptic dysfunction, and neuronal injury function is exhibited prior to the structural and metabolic changes in the brain following Aβ deposition. The time order of such biomarkers compared to the tau protein is not clear. Despite the close relationship between biomarkers and plaque Aβ deposition, several factors favor one or the other. There is an interaction between some proteins that can predict the brain amyloid burden. The Aβ cascade hypothesis could be the pathway, but not all subjects suffer from Alzheimer's disease (AD) within a long follow-up, even with very elevated Aβ. The interaction of biomarkers and the time order of change require further research to identify the right subjects and right molecular target for precision medicine therapies.

PET-Amyloid After Inconclusive Cerebrospinal Fluid Biomarkers in Clinical Practice. Is it Necessary to Duplicate Procedures?

INTRODUCTION

In the absence of a gold standard for in vivo Alzheimer disease (AD) diagnosis, AD biomarkers such as cerebrospinal fluid biomarkers (CSF-B) and PET-Amyloid are considered diagnostically useful in clinical practice guidelines and have consensual appropriate use criteria (AUC). However, little evidence has been published on their utilization in the clinical setting or on approaches to mismatched results. The objective of this work was to evaluate the use of AD biomarkers in clinical practice, focusing on the implementation of PET-Amyloid in cases of inconclusive CSF-B.

METHODS

This naturalistic, ambispective case series included patients fulfilling AUC for CSF-B and PET-Amyloid whose CSF-B results were non-diagnostic (target population), analyzing the diagnostic certainty, the treatment approach, and the relationship between CSF-B and PET-Amyloid results.

RESULTS

Out of 2373 eligible patients, AD biomarkers were studied in 417 (17.6%), most frequently due to cognitive impairment in under 65-year-olds, using CSF-B in 311 patients and PET-Amyloid in 150. CSF-B results were non-diagnostic for 44 patients (52.3% male; aged 60.9±6.6 years), who then underwent PET-Amyloid study, which was positive in 31. A 'k' coefficient of 0.108 was obtained between CSF-B and PET-amyloid (54.5% concordance). In multivariate regression analysis, Aβ42 was the only significant predictor (p= 0.018) of a positive PET-Amyloid result. In the target population, PETAmyloid increased diagnostic confidence by 53.7% (p <0.001) and modified the therapeutic approach in 36.4% of cases.

CONCLUSION

These findings support the duplication of AD biomarkers and demonstrate that the implementation of PET-Amyloid provides an early and certain diagnosis to guide appropriate treatment.

Association of amyloid-β CSF/PET discordance and tau load 5 years later

OBJECTIVE

To investigate the association between discordant β-amyloid (Aβ) PET and CSF biomarkers at baseline and the emergence of tau pathology 5 years later.

METHODS

We included 730 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants without dementia (282 cognitively normal, 448 mild cognitive impairment) with baseline [18F]florbetapir PET and CSF Aβ42 available. Aβ CSF/PET status was determined at baseline using established cutoffs. Longitudinal data were available for [18F]florbetapir (Aβ) PET (baseline to 4.3 ± 1.9 years), CSF (p)tau (baseline to 2.0 ± 0.1 years), cognition (baseline to 4.3 ± 2.0 years), and [18F]flortaucipir (tau) PET (measured 5.2 ± 1.2 years after baseline to 1.6 ± 0.7 years later). We used linear mixed modeling to study the association between Aβ CSF/PET status and tau pathology measured in CSF or using PET. We calculated the proportion of CSF+/PET- participants who during follow-up (1) progressed to Aβ CSF+/PET+ or (2) became tau-positive based on [18F]flortaucipir PET.

RESULTS

Aβ CSF+/PET+ (n = 318) participants had elevated CSF (p)tau levels and worse cognitive performance at baseline, while CSF+/PET- (n = 80) participants were overall similar to the CSF-/PET- (N = 306) group. Five years after baseline, [18F]flortaucipir PET uptake in the CSF+/PET- group (1.20 ± 0.13) did not differ from CSF-/PET- (1.18 ± 0.08, p = 0.69), but was substantially lower than CSF+/PET+ (1.48 ± 0.44, p < 0.001). Of the CSF+/PET- participants, 21/64 (33%) progressed to Aβ CSF+/PET+, whereas only one (3%, difference p < 0.05) became tau-positive based on [18F]flortaucipir PET.

CONCLUSIONS

Aβ load detectable by both CSF and PET seems to precede substantial tau deposition. Compared to participants with abnormal Aβ levels on both PET and CSF, the CSF+/PET- group has a distinctly better prognosis.

Intracisternal injection of beta-amyloid seeds promotes cerebral amyloid angiopathy

Beta amyloid (Aβ) is a key component of parenchymal Aβ plaques and vascular Aβ fibrils, which lead to cerebral amyloid angiopathy (CAA) in Alzheimer's disease (AD). Recent studies have revealed that Aβ contained in the cerebrospinal fluid (CSF) can re-enter into brain through paravascular spaces. However, whether Aβ in CSF may act as a constant source of pathogenic Aβ in AD is still unclear. This study aimed to examine whether Aβ pathology could be worsened when CSF Aβ level was enhanced by intra-cisternal infusion of aged brain extract containing abundant Aβ in TgCRND8 host mice. TgCRND8 mouse is an AD animal model which develops predominant parenchymal Aβ plaques in the brain at as early as 3 months of age. Here, we showed that single intracisternal injection of Aβ seeds into TgCRND8 mice before the presence of Aβ pathology induced robust prion-like propagation of CAA within 90 days. The induced CAA is mainly distributed in the cerebral cortex, hippocampus and thalamus of TgCRND8 mice. Surprisingly, despite the robust increase in CAA levels, the TgCRND8 mice had a marked decrease in parenchymal Aβ plaques and the plaques related neuroinflammation in the brains compared with the control mice. These results amply indicate that Aβ in CSF may act as a source of Aβ contributing to the growth of vascular Aβ deposits in CAA. Our findings provide experimental evidence to unravel the mechanisms of CAA formation and the potential of targeting CSF Aβ for CAA.

Effects of long-term sleep disruption on cognitive function and brain amyloid-β burden: a case-control study

Background

Recent evidence indicates that disrupted sleep could contribute to the development of Alzheimer’s disease by influencing the production and/or clearance of the amyloid-β protein. We set up a case-control study to investigate the association between long-term work-induced sleep disruption, cognitive function, and brain amyloid-β burden.

Methods

Nineteen male maritime pilots (aged 48–60 years) with chronic work-related sleep disruption and a sex-, age-, and education-matched control sample (n = 16, aged 50–60 years) with normal sleep completed the study. Primary sleep disorders were ruled out with in-lab polysomnography. Additional sleep measurements were obtained at home using actigraphy, sleep-wake logs, and a single-lead EEG device. Cognitive function was assessed with a neuropsychological test battery, sensitive to early symptomatic Alzheimer’s disease. Brain amyloid-β burden was assessed in maritime pilots using ¹⁸F-flutemetamol amyloid PET-CT.

Results

Maritime pilots reported significantly worse sleep quality (Pittsburgh Sleep Quality Index (PSQI) = 8.8 ± 2.9) during work weeks, compared to controls (PSQI = 3.2 ± 1.4; 95% CI 0.01 to 2.57; p = 0.049). This was confirmed with actigraphy-based sleep efficiency (86% ± 3.8 vs. 89.3% ± 4.3; 95% CI 0.43 to 6.03; p = 0.03). Home-EEG recordings showed less total sleep time (TST) and deep sleep time (DST) during work weeks compared to rest weeks (TST 318.56 (250.21–352.93) vs. TST 406.17 (340–425.98); p = 0.001; DST 36.75 (32.30–58.58) vs. DST 51.34 (48.37–69.30); p = 0.005)). There were no differences in any of the cognitive domains between the groups. For brain amyloid-β levels, mean global cortical standard uptake value ratios of ¹⁸F-flutemetamol were all in the normal range (1.009 ± 0.059; 95% CI 0.980 to 1.037), confirmed by visual reads.

Conclusions

Capitalizing on the particular work-rest schedule of maritime pilots, this study with a small sample size observed that long-term intermittent sleep disruption had no effects on global brain amyloid-β levels or cognitive function.