Detailed comparison of amyloid PET and CSF biomarkers for identifying early Alzheimer disease

Developing the ATX(N) classification for use across the Alzheimer disease continuum

Breakthroughs in the development of highly accurate fluid and neuroimaging biomarkers have catalysed the conceptual transformation of Alzheimer disease (AD) from the traditional clinical symptom-based definition to a clinical-biological construct along a temporal continuum. The AT(N) system is a symptom-agnostic classification scheme that categorizes individuals using biomarkers that chart core AD pathophysiological features, namely the amyloid-β (Aβ) pathway (A), tau-mediated pathophysiology (T) and neurodegeneration (N). This biomarker matrix is now expanding towards an ATX(N) system, where X represents novel candidate biomarkers for additional pathophysiological mechanisms such as neuroimmune dysregulation, synaptic dysfunction and blood-brain barrier alterations. In this Perspective, we describe the conceptual framework and clinical importance of the existing AT(N) system and the evolving ATX(N) system. We provide a state-of-the-art summary of the potential contexts of use of these systems in AD clinical trials and future clinical practice. We also discuss current challenges related to the validation, standardization and qualification process and provide an outlook on the real-world application of the AT(N) system.

Optimal Combinations of AT(N) Biomarkers to Determine Longitudinal Cognition in the Alzheimer's Disease

Background: National Institute on Aging-Alzheimer's Association (NIA-AA) proposed the AT(N) system based on β-amyloid deposition, pathologic tau, and neurodegeneration, which considered the definition of Alzheimer's disease (AD) as a biological construct. However, the associations between different AT(N) combinations and cognitive progression have been poorly explored systematically. The aim of this study is to compare different AT(N) combinations using recognized biomarkers within the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Methods: A total of 341 participants were classified into cognitively unimpaired (CU; n = 200) and cognitively impaired (CI; n = 141) groups according to the clinical manifestations and neuropsychological tests. Cerebrospinal fluid (CSF) Aβ42 and amyloid-PET ([18F]flutemetamol) were used as biomarkers for A; CSF phosphorylated tau (p-tau) and tau-PET ([18F]flortaucipir) were used as biomarkers for T; CSF total tau (t-tau), hippocampal volume, temporal cortical thickness, [18F]fluorodeoxyglucose (FDG) PET, and plasma neurofilament light (NfL) were used as biomarkers for (N). Binary biomarkers were obtained from the Youden index and publicly available cutoffs. Prevalence of AT(N) categories was compared between different biomarkers within the group using related independent sample non-parametric test. The relationship between AT(N) combinations and 12-year longitudinal cognition was assessed using linear mixed-effects modeling. Results: Among the CU participants, A-T-(N)- was most common. More T+ were detected using p-tau than tau PET (p < 0.05), and more (N)+ were observed using fluid biomarkers (p < 0.001). A+T+(N)+ was more common in the CI group. Tau PET combined with cortical thickness best predicted cognitive changes in the CI group and MRI predicted changes in the CU group. Conclusions: These findings suggest that optimal AT(N) combinations to determine longitudinal cognition differ by cognitive status. Different biomarkers within a specific component for defining AT(N) cannot be used identically. Furthermore, different strategies for discontinuous biomarkers will be an important area for future studies.

Practical recommendations for timely, accurate diagnosis of symptomatic Alzheimer's disease (MCI and dementia) in primary care: a review and synthesis

The critical role of primary care clinicians (PCCs) in Alzheimer's disease (AD) prevention, diagnosis and management must evolve as new treatment paradigms and disease-modifying therapies (DMTs) emerge. Our understanding of AD has grown substantially: no longer conceptualized as a late-in-life syndrome of cognitive and functional impairments, we now recognize that AD pathology builds silently for decades before cognitive impairment is detectable. Clinically, AD first manifests subtly as mild cognitive impairment (MCI) due to AD before progressing to dementia. Emerging optimism for improved outcomes in AD stems from a focus on preventive interventions in midlife and timely, biomarker-confirmed diagnosis at early signs of cognitive deficits (i.e. MCI due to AD and mild AD dementia). A timely AD diagnosis is particularly important for optimizing patient care and enabling the appropriate use of anticipated DMTs. An accelerating challenge for PCCs and AD specialists will be to respond to innovations in diagnostics and therapy for AD in a system that is not currently well positioned to do so. To overcome these challenges, PCCs and AD specialists must collaborate closely to navigate and optimize dynamically evolving AD care in the face of new opportunities. In the spirit of this collaboration, we summarize here some prominent and influential models that inform our current understanding of AD. We also advocate for timely and accurate (i.e. biomarker-defined) diagnosis of early AD. In doing so, we consider evolving issues related to prevention, detecting emerging cognitive impairment and the role of biomarkers in the clinic.

MRI-Visible Perivascular Spaces in the Centrum Semiovale Are Associated with Brain Amyloid Deposition in Patients with Alzheimer Disease-Related Cognitive Impairment

BACKGROUND AND PURPOSE

The association of perivascular spaces in the centrum semiovale with amyloid accumulation among patients with Alzheimer disease-related cognitive impairment is unknown. We evaluated this association in patients with Alzheimer disease-related cognitive impairment and β-amyloid deposition, assessed with [¹⁸F] florbetaben PET/CT.

MATERIALS AND METHODS

MR imaging and [¹⁸F] florbetaben PET/CT images of 144 patients with Alzheimer disease-related cognitive impairment were retrospectively evaluated. MR imaging-visible perivascular spaces were rated on a 4-point visual scale: a score of ≥3 or <3 indicated a high or low degree of MR imaging-visible perivascular spaces, respectively. Amyloid deposition was evaluated using the brain β-amyloid plaque load scoring system.

RESULTS

Compared with patients negative for β-amyloid, those positive for it were older and more likely to have lower cognitive function, a diagnosis of Alzheimer disease, white matter hyperintensity, the Apolipoprotein E ε4 allele, and a high degree of MR imaging-visible perivascular spaces in the centrum semiovale. Multivariable analysis, adjusted for age and Apolipoprotein E status, revealed that a high degree of MR imaging-visible perivascular spaces in the centrum semiovale was independently associated with β-amyloid positivity (odds ratio, 2.307; 95% CI, 1.036-5.136; P = .041).

CONCLUSIONS

A high degree of MR imaging-visible perivascular spaces in the centrum semiovale independently predicted β-amyloid positivity in patients with Alzheimer disease-related cognitive impairment. Thus, MR imaging-visible perivascular spaces in the centrum semiovale are associated with amyloid pathology of the brain and could be an indirect imaging marker of amyloid burden in patients with Alzheimer disease-related cognitive impairment.

A multicentre validation study of the diagnostic value of plasma neurofilament light

Increased cerebrospinal fluid neurofilament light (NfL) is a recognized biomarker for neurodegeneration that can also be assessed in blood. Here, we investigate plasma NfL as a marker of neurodegeneration in 13 neurodegenerative disorders, Down syndrome, depression and cognitively unimpaired controls from two multicenter cohorts: King’s College London (n = 805) and the Swedish BioFINDER study (n = 1,464). Plasma NfL was significantly increased in all cortical neurodegenerative disorders, amyotrophic lateral sclerosis and atypical parkinsonian disorders. We demonstrate that plasma NfL is clinically useful in identifying atypical parkinsonian disorders in patients with parkinsonism, dementia in individuals with Down syndrome, dementia among psychiatric disorders, and frontotemporal dementia in patients with cognitive impairment. Data-driven cut-offs highlighted the fundamental importance of age-related clinical cut-offs for disorders with a younger age of onset. Finally, plasma NfL performs best when applied to indicate no underlying neurodegeneration, with low false positives, in all age-related cut-offs.

Cerebrospinal fluid neurofilament light (NfL) is a biomarker for neurodegeneration that can also be assessed in blood. Here the authors show in a validation study the potential for plasma NfL as a biomarker for several neurodegenerative diseases.

Plasma markers predict changes in amyloid, tau, atrophy and cognition in non-demented subjects

It is currently unclear whether plasma biomarkers can be used as independent prognostic tools to predict changes associated with early Alzheimer's disease (AD). In this study we sought to address this question by assessing whether plasma biomarkers can predict changes in amyloid load, tau accumulation, brain atrophy and cognition in non-demented individuals. To achieve this, plasma amyloid-β 42/40 (Aβ42/40), phosphorylated-tau181 (P-tau181), phosphorylated-tau217 (P-tau217) and neurofilament light (NfL) were determined in 159 non-demented individuals, 123 patients with AD dementia and 35 patients with a non-AD dementia from the Swedish BioFINDER-2 study, who underwent longitudinal amyloid (18 F-flutemetamol) and tau (18 F-RO948) positron emission tomography (PET), structural magnetic resonance imaging (T1-weighted) and cognitive testing. Our univariate linear mixed effect models showed there were several significant associations between the plasma biomarkers with imaging and cognitive measures. However, when all biomarkers were included in the same multivariate linear mixed effect models, we found that increased longitudinal amyloid-PET signals were independently predicted by low baseline plasma Aβ42/40 (p = 0.012), whereas increased tau-PET signals, brain atrophy and worse cognition were independently predicted by high plasma P-tau217 (p < 0.004). These biomarkers performed equally well or better than the corresponding biomarkers measured in the cerebrospinal fluid. In addition, they showed a similar performance to binary plasma biomarker values defined using the Youden index, which can be more easily implemented in the clinic. In addition, plasma Aβ42/40 and P-tau217 did not predict longitudinal changes in patients with a non-AD neurodegenerative disorder. In conclusion, our findings indicate that plasma Aβ42/40 and P-tau217 could be useful in clinical practice, research and drug development as prognostic markers of future AD pathology.

Health utility in preclinical and prodromal Alzheimer's disease for establishing the value of new disease-modifying treatments-EQ-5D data from the Swedish BioFINDER study

Quality of life and health utility are important outcomes for patients with Alzheimer's disease (AD) and central for demonstrating the value of new treatments. Estimates in biomarker-confirmed AD populations are missing, potentially delaying payer approval of treatment. We examined whether health utility, assessed with the EuroQoL-5 3-level version (EQ-5D-3L), differed between individuals with a positive or negative amyloid beta (Aβ) biomarker in patients with mild cognitive impairment (MCI) and cognitively unimpaired (CU) participants from the Swedish BioFINDER study (n = 578). Participants with prodromal AD (Aβ-positive MCI) reported better health utility (n = 79, mean = 0.81, 95% confidence interval [CI] 0.77-0.85) than Aβ-negative MCI (mean = 0.71, 95% CI 0.64-0.78), but worse than controls (Aβ-negative CU, mean = 0.87, 95% CI 0.86-0.89). Health utility in preclinical AD (Aβ-positive CU; mean = 0.86, 95% CI 0.83-0.89) was similar to controls. This relatively good health utility in prodromal AD suggests a larger value of delaying progression to dementia than previously anticipated and a great value of delaying clinical progression in preclinical AD.

Predicting Amyloid-β Levels in Amnestic Mild Cognitive Impairment Using Machine Learning Techniques

BACKGROUND

Amyloid-β positivity (Aβ+) based on PET imaging is part of the enrollment criteria for many of the clinical trials of Alzheimer's disease (AD), particularly in trials for amyloid-targeted therapy. Predicting Aβ positivity prior to PET imaging can decrease unnecessary patient burden and costs of running these trials.

OBJECTIVE

The aim of this study was to evaluate the performance of a machine learning model in estimating the individual risk of Aβ+ based on gold-standard of PET imaging.

METHODS

We used data from an amnestic mild cognitive impairment (aMCI) subset of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort to develop and validate the models. The predictors of Aβ status included demographic and ApoE4 status in all models plus a combination of neuropsychological tests (NP), MRI volumetrics, and cerebrospinal fluid (CSF) biomarkers.

RESULTS

The models that included NP and MRI measures separately showed an area under the receiver operating characteristics (AUC) of 0.74 and 0.72, respectively. However, using NP and MRI measures jointly in the model did not improve prediction. The models including CSF biomarkers significantly outperformed other models with AUCs between 0.89 to 0.92.

CONCLUSIONS

Predictive models can be effectively used to identify persons with aMCI likely to be amyloid positive on a subsequent PET scan.

The Role of Free and Cued Selective Reminding Test in Predicting [18F]Florbetaben PET Results in Mild Cognitive Impairment and Mild Dementia

BACKGROUND

Free and Cued Selective Reminding Test (FCSRT) is a reliable cognitive marker for Alzheimer's disease (AD), and the identification of neuropsychological tests sensitive to the early signs of AD pathology is crucial both in research and clinical practice.

OBJECTIVE

The study aimed to ascertain the ability of FCSRT in predicting the amyloid load as determined from amyloid PET imaging (Amy-PET) in patients with cognitive disorders.

METHODS

For our purpose, 79 patients (71 MCI, 8 mild dementia) underwent a complete workup for dementia, including the FCSRT assessment and a [18F]florbetaben PET scan. FCSRT subitem scores were used as predictors in different binomial regression models.

RESULTS

Immediate free recall and delayed free recall were the best predictors overall in the whole sample; whereas in patients <76 years, all models further improved with immediate total recall (ITR) and Index of Sensitivity of Cueing (ISC) resulting the most accurate in anticipating Amy-PET results, with a likelihood of being Amy-PET positive greater than 85% for ITR and ISC scores of less than 25 and 0.5, respectively.

CONCLUSION

FCSRT proved itself to be a valid tool in dementia diagnosis, also being able to correlate with amyloid pathology. The possibility to predict Amy-PET results through a simple and reliable neuropsychological test might be helpful for clinicians in the dementia field, adding value to a paper and pencil tool compared to most costly biomarkers.

Distinguishing Alzheimer's Disease Patients and Biochemical Phenotype Analysis Using a Novel Serum Profiling Platform: Potential Involvement of the VWF/ADAMTS13 Axis

It is important to develop minimally invasive biomarker platforms to help in the identification and monitoring of patients with Alzheimer's disease (AD). Assisting in the understanding of biochemical mechanisms as well as identifying potential novel biomarkers and therapeutic targets would be an added benefit of such platforms. This study utilizes a simplified and novel serum profiling platform, using mass spectrometry (MS), to help distinguish AD patient groups (mild and moderate) and controls, as well as to aid in understanding of biochemical phenotypes and possible disease development. A comparison of discriminating sera mass peaks between AD patients and control individuals was performed using leave one [serum sample] out cross validation (LOOCV) combined with a novel peak classification valuation (PCV) procedure. LOOCV/PCV was able to distinguish significant sera mass peak differences between a group of mild AD patients and control individuals with a p value of 10^-13. This value became non-significant (p = 0.09) when the same sera samples were randomly allocated between the two groups and reanalyzed by LOOCV/PCV. This is indicative of physiological group differences in the original true-pathology binary group comparison. Similarities and differences between AD patients and traumatic brain injury (TBI) patients were also discernable using this novel LOOCV/PCV platform. MS/MS peptide analysis was performed on serum mass peaks comparing mild AD patients with control individuals. Bioinformatics analysis suggested that cell pathways/biochemical phenotypes affected in AD include those involving neuronal cell death, vasculature, neurogenesis, and AD/dementia/amyloidosis. Inflammation, autoimmunity, autophagy, and blood-brain barrier pathways also appear to be relevant to AD. An impaired VWF/ADAMTS13 vasculature axis with connections to F8 (factor VIII) and LRP1 and NOTCH1 was indicated and is proposed to be important in AD development.

Predicting amyloid positivity in patients with mild cognitive impairment using a radiomics approach

Predicting amyloid positivity in patients with mild cognitive impairment (MCI) is crucial. In the present study, we predicted amyloid positivity with structural MRI using a radiomics approach. From MR images (including T1, T2 FLAIR, and DTI sequences) of 440 MCI patients, we extracted radiomics features composed of histogram and texture features. These features were used alone or in combination with baseline non-imaging predictors such as age, sex, and ApoE genotype to predict amyloid positivity. We used a regularized regression method for feature selection and prediction. The performance of the baseline non-imaging model was at a fair level (AUC = 0.71). Among single MR-sequence models, T1 and T2 FLAIR radiomics models also showed fair performances (AUC for test = 0.71-0.74, AUC for validation = 0.68-0.70) in predicting amyloid positivity. When T1 and T2 FLAIR radiomics features were combined, the AUC for test was 0.75 and AUC for validation was 0.72 (p vs. baseline model < 0.001). The model performed best when baseline features were combined with a T1 and T2 FLAIR radiomics model (AUC for test = 0.79, AUC for validation = 0.76), which was significantly better than those of the baseline model (p < 0.001) and the T1 + T2 FLAIR radiomics model (p < 0.001). In conclusion, radiomics features showed predictive value for amyloid positivity. It can be used in combination with other predictive features and possibly improve the prediction performance.

Clinical Relevance of [18F]Florbetaben and [18F]FDG PET/CT Imaging on the Management of Patients with Dementia

PET of β-Amyloid plaques (Aβ) using [¹⁸F]florbetaben ([¹⁸F]FBB) and [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) increasingly aid clinicians in early diagnosis of dementia, including Alzheimer’s disease (AD), frontotemporal disease, dementia with Lewy bodies, and vascular dementia. The aim of this retrospective analysis was to evaluate clinical relevance of [¹⁸F]FBB, [¹⁸F]FDG PET and complimentary CSF measurements in patients with suspected dementia. In this study, 40 patients with clinically suspected or history of dementia underwent (1) measurement of Aβ peptides, total tau, and p-tau protein levels in the cerebrospinal fluid (CSF) compared with healthy controls (HC); (2) clinical and neuropsychological assessment, which included Consortium to Establish a Registry for Alzheimer’s Disease neuropsychological assessment battery (CERAD-NAB); (3) [¹⁸F]FBB and [¹⁸F]FDG PET imaging within an average of 3 weeks. The subjects were within 15 days stratified using PET, CSF measurements as HC, mild cognitive impaired (MCI) and dementia including Alzheimer´s disease. The predictive dementia-related cognitive decline values were supporting the measurements. PET images were evaluated visually and quantitatively using standard uptake value ratios (SUVR). Twenty-one (52.5%) subjects were amyloid-positive (Aβ+), with a median neocortical SUVR of 1.80 for AD versus 1.20 relative to the respective 19 (47.5 %) amyloid-negative (Aβ-) subjects. Moreover, the [¹⁸F]FDG and [¹⁸F]FBB confirmed within a sub-group of 10 patients a good complimentary role by correlation between amyloid pathology and brain glucose metabolism in 8 out of 10 subjects. The results suggest the clinical relevance for [¹⁸F]FBB combined with [¹⁸F]FDG PET retention and CFS measurements serving the management of our patients with dementia. Therefore, [¹⁸F]FBB combined with [¹⁸F]FDG PET is a helpful tool for differential diagnosis, and supports the patients’ management as well as treatment.

Relationship between amyloid and tau levels and its impact on tau spreading

Purpose

Previous studies have shown that Aβ-amyloid (Aβ) likely promotes tau to spread beyond the medial temporal lobe. However, the Aβ levels necessary for tau to spread in the neocortex is still unclear.

Methods

Four hundred sixty-six participants underwent tau imaging with [18F]MK6420 and Aβ imaging with [¹⁸F]NAV4694. Aβ scans were quantified on the Centiloid (CL) scale with a cut-off of 25 CL for abnormal levels of Aβ (A+). Tau scans were quantified in three regions of interest (ROI) (mesial temporal (Me); temporoparietal neocortex (Te); and rest of neocortex (R)) and four mesial temporal region (entorhinal cortex, amygdala, hippocampus, and parahippocampus). Regional tau thresholds were established as the 95%ile of the cognitively unimpaired A- subjects. The prevalence of abnormal tau levels (T+) along the Centiloid continuum was determined.

Results

The plots of prevalence of T+ show earlier and greater increase along the Centiloid continuum in the medial temporal area compared to neocortex. Prevalence of T+ was low but associated with Aβ level between 10 and 40 CL reaching 23% in Me, 15% in Te, and 11% in R. Between 40 and 70 CL, the prevalence of T+ subjects per CL increased fourfold faster and at 70 CL was 64% in Me, 51% in Te, and 37% in R. In cognitively unimpaired, there were no T+ in R below 50 CL. The highest prevalence of T+ were found in the entorhinal cortex, reaching 40% at 40 CL and 80% at 60 CL.

Conclusion

Outside the entorhinal cortex, abnormal levels of cortical tau on PET are rarely found with Aβ below 40 CL. Above 40 CL prevalence of T+ accelerates in all areas. Moderate Aβ levels are required before abnormal neocortical tau becomes detectable.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05191-9.

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.

Classification accuracy of TMS for the diagnosis of mild cognitive impairment

OBJECTIVE

To evaluate the performance of a Random Forest (RF) classifier on Transcranial Magnetic Stimulation (TMS) measures in patients with Mild Cognitive Impairment (MCI).

METHODS

We applied a RF classifier on TMS measures obtained from a multicenter cohort of patients with MCI, including MCI-Alzheimer's Disease (MCI-AD), MCI-frontotemporal dementia (MCI-FTD), MCI-dementia with Lewy bodies (MCI-DLB), and healthy controls (HC). All patients underwent TMS assessment at recruitment (index test), with application of reference clinical criteria, to predict different neurodegenerative disorders. The primary outcome measures were the classification accuracy, precision, recall and F1-score of TMS in differentiating each disorder.

RESULTS

160 participants were included, namely 64 patients diagnosed as MCI-AD, 28 as MCI-FTD, 14 as MCI-DLB, and 47 as healthy controls (HC). A series of 3 binary classifiers was employed, and the prediction model exhibited high classification accuracy (ranging from 0.72 to 0.86), high precision (0.72-0.90), high recall (0.75-0.98), and high F1-scores (0.78-0.92), in differentiating each neurodegenerative disorder. By computing a new classifier, trained and validated on the current cohort of MCI patients, classification indices showed even higher accuracy (ranging from 0.83 to 0.93), precision (0.87-0.89), recall (0.83-1.00), and F1-scores (0.85-0.94).

CONCLUSIONS

TMS may be considered a useful additional screening tool to be used in clinical practice in the prodromal stages of neurodegenerative dementias.

Effects of amyloid pathology and the APOE ε4 allele on the association between cerebrospinal fluid Aβ38 and Aβ40 and brain morphology in cognitively normal 70-years-olds

The association between cerebrospinal fluid (CSF) amyloid beta (Aβ) Aβ38 or Aβ40 and brain grey- and white matter integrity is poorly understood. We studied this in 213 cognitively normal 70-year-olds, and in subgroups defined by presence/absence of the APOE ε4 allele and Aβ pathology: Aβ-/APOE-, Aβ+/APOE-, Aβ-/APOE+ and Aβ+/APOE+. CSF Aβ was quantified using ELISA and genotyping for APOE was performed. Low CSF Aβ42 defined Aβ plaque pathology. Brain volumes were assessed using Freesurfer-5.3, and white matter integrity using tract-based statistics in FSL. Aβ38 and Aβ40 were positively correlated with cortical thickness, some subcortical volumes and white matter integrity in the total sample, and in 3 of the subgroups: Aβ-/APOE-, Aβ+/APOE- and Aβ-/APOE+. In Aβ+/APOE+ subjects, higher Aβ38 and Aβ40 were linked to reduced cortical thickness and subcortical volumes. We hypothesize that production of all Aβ species decrease in brain regions with atrophy. In Aβ+/APOE+, Aβ-dysregulation may be linked to cortical atrophy in which high Aβ levels is causing pathological changes in the gray matter of the brain.

Biomarker testing in MCI patients-deciding who to test

BACKGROUND

We aimed to derive an algorithm to define the optimal proportion of patients with mild cognitive impairment (MCI) in whom cerebrospinal fluid (CSF) testing is of added prognostic value.

METHODS

MCI patients were selected from the Amsterdam Dementia Cohort (n = 402). Three-year progression probabilities to dementia were predicted using previously published models with and without CSF data (amyloid-beta1-42 (Abeta), phosphorylated tau (p-tau)). We incrementally augmented the proportion of patients undergoing CSF, starting with the 10% patients with prognostic probabilities based on clinical data around the median (percentile 45-55), until all patients received CSF. The optimal proportion was defined as the proportion where the stepwise algorithm showed similar prognostic discrimination (Harrell's C) and accuracy (three-year Brier scores) compared to CSF testing of all patients. We used the BioFINDER study (n = 221) for validation.

RESULTS

The optimal proportion of MCI patients to receive CSF testing selected by the stepwise approach was 50%. CSF testing in only this proportion improved the performance of the model with clinical data only from Harrell's C = 0.60, Brier = 0.198 (Harrell's C = 0.61, Brier = 0.197 if the information on magnetic resonance imaging was available) to Harrell's C = 0.67 and Brier = 0.190, and performed similarly to a model in which all patients received CSF testing. Applying the stepwise approach in the BioFINDER study would again select half of the MCI patients and yielded robust results with respect to prognostic performance.

INTERPRETATION

CSF biomarker testing adds prognostic value in half of the MCI patients. As such, we achieve a CSF saving recommendation while simultaneously retaining optimal prognostic accuracy.

Case Report: Usefulness of Biomarkers for Alzheimer's Disease in Two Cases With Very-Late-Onset Schizophrenia-Like Psychosis

The association between primary psychotic disorders emerging in later life and neurodegenerative diseases, including Alzheimer's disease (AD), is controversial. We present two female non-demented cases of psychosis with onset above the age of 60 years. Cases 1 and 2 were aged was 68 and 81 years, respectively. They suffered from persecutory delusions and scored 28 on the Mini-Mental State Examination (MMSE) at the first examination. Although detailed neuropsychological tests detected amnesia, they had preserved daily life function. Brain magnetic resonance imaging, N-isopropyl-p-[123I] iodoamphetamine (123I-IMP) single-photon emission computed tomography, and cardiac [123I]-metaiodobenzylguanidine (123I-MIBG) scintigraphy showed no specific abnormalities in either case. We diagnosed them with very-late-onset schizophrenia-like psychosis (VLOSLP) because there was no evidence that their psychoses were derived from organic diseases or affective disorders. Upon close inspection, the AD biomarkers, cerebrospinal fluid (CSF) testing and Florbetapir F 18 positron emission tomography (PET), were positive in Case 1 and negative in Case 2. Case 1 scored 25 1 year later and 23 2 years later on the MMSE and was finally diagnosed as AD dementia. These two cases suggest that some clinically diagnosed VLOSLPs may be a prodromal AD. Although VLOSLP is a disease entity supposed to be a primary psychotic disorder, some are probably secondary psychosis with insidious neurodegeneration. Advanced biomarkers such as amyloid PET and CSF may contribute to the detection of secondary psychosis from clinically diagnosed VLOSLP.

Neuroimaging Advances in Diagnosis and Differentiation of HIV, Comorbidities, and Aging in the cART Era

In the "cART era" of more widely available and accessible treatment, aging and HIV-related comorbidities, including symptoms of brain dysfunction, remain common among HIV-infected individuals on suppressive treatment. A better understanding of the neurobiological consequences of HIV infection is essential for developing thorough treatment guidelines and for optimizing long-term neuropsychological outcomes and overall brain health. In this chapter, we first summarize magnetic resonance imaging (MRI) methods used in over two decades of neuroHIV research. These methods evaluate brain volumetric differences and circuitry disruptions in adults living with HIV, and help map clinical correlations with brain function and tissue microstructure. We then introduce and discuss aging and associated neurological complications in people living with HIV, and processes by which infection may contribute to the risk for late-onset dementias. We describe how new technologies and large-scale international collaborations are helping to disentangle the effect of genetic and environmental risk factors on brain aging and neurodegenerative diseases. We provide insights into how these advances, which are now at the forefront of Alzheimer's disease research, may advance the field of neuroHIV. We conclude with a summary of how we see the field of neuroHIV research advancing in the decades to come and highlight potential clinical implications.

Iron and Ferroptosis as Therapeutic Targets in Alzheimer's Disease

Alzheimer's disease (AD), one of the most common neurodegenerative diseases worldwide, has a devastating personal, familial, and societal impact. In spite of profound investment and effort, numerous clinical trials targeting amyloid-β, which is thought to have a causative role in the disease, have not yielded any clinically meaningful success to date. Iron is an essential cofactor in many physiological processes in the brain. An extensive body of work links iron dyshomeostasis with multiple aspects of the pathophysiology of AD. In particular, regional iron load appears to be a risk factor for more rapid cognitive decline. Existing iron-chelating agents have been in use for decades for other indications, and there are preliminary data that some of these could be effective in AD. Many novel iron-chelating compounds are under development, some with in vivo data showing potential Alzheimer's disease-modifying properties. This heretofore underexplored therapeutic class has considerable promise and could yield much-needed agents that slow neurodegeneration in AD.

Aducanumab: Appropriate Use Recommendations

Aducanumab has been approved by the US Food and Drug Administration for treatment of Alzheimer's disease (AD). Clinicians require guidance on the appropriate use of this new therapy. An Expert Panel was assembled to construct Appropriate Use Recommendations based on the participant populations, conduct of the pivotal trials of aducanumab, updated Prescribing Information, and expert consensus. Aducanumab is an amyloid-targeting monoclonal antibody delivered by monthly intravenous infusions. The pivotal trials included patients with early AD (mild cognitive impairment due to AD and mild AD dementia) who had confirmed brain amyloid using amyloid positron tomography. The Expert Panel recommends that use of aducanumab be restricted to this population in which efficacy and safety have been studied. Aducanumab is titrated to a dose of 10 mg/kg over a 6-month period. The Expert Panel recommends that the aducanumab be titrated to the highest dose to maximize the opportunity for efficacy. Aducanumab can substantially increase the incidence of amyloid-related imaging abnormalities (ARIA) with brain effusion or hemorrhage. Dose interruption or treatment discontinuation is recommended for symptomatic ARIA and for moderate-severe ARIA. The Expert Panel recommends MRIs prior to initiating therapy, during the titration of the drug, and at any time the patient has symptoms suggestive of ARIA. Recommendations are made for measures less cumbersome than those used in trials for the assessment of effectiveness in the practice setting. The Expert Panel emphasized the critical importance of engaging in a process of patient-centered informed decision-making that includes comprehensive discussions and clear communication with the patient and care partner regarding the requirements for therapy, the expected outcome of therapy, potential risks and side effects, and the required safety monitoring, as well as uncertainties regarding individual responses and benefits.

ATN status in amnestic and non-amnestic Alzheimer's disease and frontotemporal lobar degeneration

Under the ATN framework, CSF analytes provide evidence of the presence or absence of Alzheimer's disease pathological hallmarks: amyloid plaques (A), phosphorylated tau (T), and accompanying neurodegeneration (N). Still, differences in CSF levels across amnestic and non-amnestic variants or due to co-occurring pathologies might lead to misdiagnoses. We assess the diagnostic accuracy of CSF markers for amyloid, tau, and neurodegeneration in an autopsy cohort of 118 Alzheimer's disease patients (98 amnestic; 20 non-amnestic) and 64 frontotemporal lobar degeneration patients (five amnestic; 59 non-amnestic). We calculated between-group differences in CSF concentrations of amyloid-β1-42 peptide, tau protein phosphorylated at threonine 181, total tau, and the ratio of phosphorylated tau to amyloid-β1-42. Results show that non-amnestic Alzheimer's disease patients were less likely to be correctly classified under the ATN framework using independent, published biomarker cut-offs for positivity. Amyloid-β1-42 did not differ between amnestic and non-amnestic Alzheimer's disease, and receiver operating characteristic curve analyses indicated that amyloid-β1-42 was equally effective in discriminating both groups from frontotemporal lobar degeneration. However, CSF concentrations of phosphorylated tau, total tau, and the ratio of phosphorylated tau to amyloid-β1-42 were significantly lower in non-amnestic compared to amnestic Alzheimer's disease patients. Receiver operating characteristic curve analyses for these markers showed reduced area under the curve when discriminating non-amnestic Alzheimer's disease from frontotemporal lobar degeneration, compared to discrimination of amnestic Alzheimer's disease from frontotemporal lobar degeneration. In addition, the ATN framework was relatively insensitive to frontotemporal lobar degeneration, and these patients were likely to be classified as having normal biomarkers or biomarkers suggestive of primary Alzheimer's disease pathology. We conclude that amyloid-β1-42 maintains high sensitivity to A status, although with lower specificity, and this single biomarker provides better sensitivity to non-amnestic Alzheimer's disease than either the ATN framework or the phosphorylated-tau/amyloid-β1-42 ratio. In contrast, T and N status biomarkers differed between amnestic and non-amnestic Alzheimer's disease; standard cut-offs for phosphorylated tau and total tau may thus result in misclassifications for non-amnestic Alzheimer's disease patients. Consideration of clinical syndrome may help improve the accuracy of ATN designations for identifying true non-amnestic Alzheimer's disease.

Comparison of ELISA- and SIMOA-based quantification of plasma Aβ ratios for early detection of cerebral amyloidosis

BACKGROUND

Blood-based amyloid biomarkers may provide a non-invasive, cost-effective and scalable manner for detecting cerebral amyloidosis in early disease stages.

METHODS

In this prospective cross-sectional study, we quantified plasma Aβ1-42/Aβ1-40 ratios with both routinely available ELISAs and novel SIMOA Amyblood assays, and provided a head-to-head comparison of their performances to detect cerebral amyloidosis in a nondemented elderly cohort (n = 199). Participants were stratified according to amyloid-PET status, and the performance of plasma Aβ1-42/Aβ1-40 to detect cerebral amyloidosis was assessed using receiver operating characteristic analysis. We additionally investigated the correlations of plasma Aβ ratios with amyloid-PET and CSF Alzheimer's disease biomarkers, as well as platform agreement using Passing-Bablok regression and Bland-Altman analysis for both Aβ isoforms.

RESULTS

ELISA and SIMOA plasma Aβ1-42/Aβ1-40 detected cerebral amyloidosis with identical accuracy (ELISA: area under curve (AUC) 0.78, 95% CI 0.72-0.84; SIMOA: AUC 0.79, 95% CI 0.73-0.85), and both increased the performance of a basic demographic model including only age and APOE-ε4 genotype (p ≤ 0.02). ELISA and SIMOA had positive predictive values of respectively 41% and 36% in cognitively normal elderly and negative predictive values all exceeding 88%. Plasma Aβ1-42/Aβ1-40 correlated similarly with amyloid-PET for both platforms (Spearman ρ = - 0.32, p <  0.0001), yet correlations with CSF Aβ1-42/t-tau were stronger for ELISA (ρ = 0.41, p = 0.002) than for SIMOA (ρ = 0.29, p = 0.03). Plasma Aβ levels demonstrated poor agreement between ELISA and SIMOA with concentrations of both Aβ1-42 and Aβ1-40 measured by SIMOA consistently underestimating those measured by ELISA.

CONCLUSIONS

ELISA and SIMOA demonstrated equivalent performances in detecting cerebral amyloidosis through plasma Aβ1-42/Aβ1-40, both with high negative predictive values, making them equally suitable non-invasive prescreening tools for clinical trials by reducing the number of necessary PET scans for clinical trial recruitment.

TRIAL REGISTRATION

EudraCT 2009-014475-45 (registered on 23 Sept 2009) and EudraCT 2013-004671-12 (registered on 20 May 2014, https://www.clinicaltrialsregister.eu/ctr-search/trial/2013-004671-12/BE ).

Plasma N-terminal tau fragment levels predict future cognitive decline and neurodegeneration in healthy elderly individuals

The availability of blood-based assays detecting Alzheimer's disease (AD) pathology should greatly accelerate AD therapeutic development and improve clinical care. This is especially true for markers that capture the risk of decline in pre-symptomatic stages of AD, as this would allow one to focus interventions on participants maximally at risk and at a stage prior to widespread synapse loss and neurodegeneration. Here we quantify plasma concentrations of an N-terminal fragment of tau (NT1) in a large, well-characterized cohort of clinically normal elderly who were followed longitudinally. Plasma NT1 levels at study entry (when all participants were unimpaired) were highly predictive of future cognitive decline, pathological tau accumulation, neurodegeneration, and transition to a diagnosis of MCI/AD. These predictive effects were particularly strong in participants with even modestly elevated brain β-amyloid burden at study entry, suggesting plasma NT1 levels capture very early cognitive, pathologic and neurodegenerative changes along the AD trajectory.

Amyloid biomarkers as predictors of conversion from mild cognitive impairment to Alzheimer's dementia: a comparison of methods

Background

Amyloid-β (Aβ) PET is an established predictor of conversion from mild cognitive impairment (MCI) to Alzheimer’s dementia (AD). We compared three PET (including an approach based on voxel-wise Cox regression) and one cerebrospinal fluid (CSF) outcome measures in their predictive power.

Methods

Datasets were retrieved from the ADNI database. In a training dataset (N = 159), voxel-wise Cox regression and principal component analyses were used to identify conversion-related regions (Cox-VOI and AD conversion-related pattern (ADCRP), respectively). In a test dataset (N = 129), the predictive value of mean normalized ¹⁸F-florbetapir uptake (SUVR) in AD-typical brain regions (composite SUVR) or the Cox-VOI and the pattern expression score (PES) of ADCRP and CSF Aβ₄₂/Aβ₄₀ as predictors were compared by Cox models (corrected for age and sex).

Results

All four Aβ measures were significant predictors (p < 0.001). Prediction accuracies (Harrell’s c) showed step-wise significant increases from Cox-SUVR (c = 0.71; HR = 1.84 per Z-score increase), composite SUVR (c = 0.73; HR = 2.18), CSF Aβ₄₂/Aβ₄₀ (c = 0.75; HR = 3.89) to PES (c = 0.77; HR = 2.71).

Conclusion

The PES of ADCRP is the most predictive Aβ PET outcome measure, comparable to CSF Aβ₄₂/Aβ₄₀, with a slight but statistically significant advantage.

Detection of Alzheimer's Disease using cortical diffusion tensor imaging

The aim of this research was to test a novel in‐vivo brain MRI analysis method that could be used in clinical cohorts to investigate cortical architecture changes in patients with Alzheimer's Disease (AD). Three cohorts of patients with probable AD and healthy volunteers were used to assess the results of the method. The first group was used as the “Discovery” cohort, the second as the “Test” cohort and the last “ATN” (Amyloid, Tau, Neurodegeneration) cohort was used to test the method in an ADNI 3 cohort, comparing to amyloid and Tau PET. The method can detect altered quality of cortical grey matter in AD patients, providing an additional tool to assess AD, distinguishing between these and healthy controls with an accuracy range between good and excellent. These new measurements could be used within the “ATN” framework as an index of cortical microstructure quality and a marker of Neurodegeneration. Further development may aid diagnosis, patient selection, and quantification of the “Neurodegeneration” component in response to therapies in clinical trials.

APOE2: protective mechanism and therapeutic implications for Alzheimer's disease

Investigations of apolipoprotein E (APOE) gene, the major genetic risk modifier for Alzheimer's disease (AD), have yielded significant insights into the pathogenic mechanism. Among the three common coding variants, APOE*ε4 increases, whereas APOE*ε2 decreases the risk of late-onset AD compared with APOE*ε3. Despite increased understanding of the detrimental effect of APOE*ε4, it remains unclear how APOE*ε2 confers protection against AD. Accumulating evidence suggests that APOE*ε2 protects against AD through both amyloid-β (Aβ)-dependent and independent mechanisms. In addition, APOE*ε2 has been identified as a longevity gene, suggesting a systemic effect of APOE*ε2 on the aging process. However, APOE*ε2 is not entirely benign; APOE*ε2 carriers exhibit increased risk of certain cerebrovascular diseases and neurological disorders. Here, we review evidence from both human and animal studies demonstrating the protective effect of APOE*ε2 against AD and propose a working model depicting potential underlying mechanisms. Finally, we discuss potential therapeutic strategies designed to leverage the protective effect of APOE2 to treat AD.

Contributions of Molecular and Optical Techniques to the Clinical Diagnosis of Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder worldwide. The distinctive neuropathological feature of AD is the intracerebral accumulation of two abnormally folded proteins: β-amyloid (Aβ) in the form of extracellular plaques, and tau in the form of intracellular neurofibrillary tangles. These proteins are considered disease-specific biomarkers, and the definite diagnosis of AD relies on their post-mortem identification in the brain. The clinical diagnosis of AD is challenging, especially in the early stages. The disease is highly heterogeneous in terms of clinical presentation and neuropathological features. This phenotypic variability seems to be partially due to the presence of distinct Aβ conformers, referred to as strains. With the development of an innovative technique named Real-Time Quaking-Induced Conversion (RT-QuIC), traces of Aβ strains were found in the cerebrospinal fluid of AD patients. Emerging evidence suggests that different conformers may transmit their strain signature to the RT-QuIC reaction products. In this review, we describe the current challenges for the clinical diagnosis of AD and describe how the RT-QuIC products could be analyzed by a surface-enhanced Raman spectroscopy (SERS)-based systems to reveal the presence of strain signatures, eventually leading to early diagnosis of AD with the recognition of individual disease phenotype.

Dual-Task Performance and Neurodegeneration: Correlations Between Timed Up-and-Go Dual-Task Test Outcomes and Alzheimer's Disease Cerebrospinal Fluid Biomarkers

BACKGROUND

Tools to identify individuals at preclinical stages of dementia disorders are needed to enable early interventions. Alterations in dual-task performance have been detected early in progressive neurodegenerative disorders. Hence, dual-task testing may have the potential to screen for cognitive impairment caused by neurodegeneration. Exploring correlations between dual-task performance and biomarkers of neurodegeneration is therefore of interest.

OBJECTIVE

To investigate correlations between Timed Up-and-Go dual-task (TUGdt) outcomes and Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers amyloid-β 42 (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau).

METHODS

This cross-sectional cohort study included 90 participants (age range 49-84 years) undergoing memory assessment, who were subsequently diagnosed with AD, other dementia disorders, mild cognitive impairment, or subjective cognitive impairment. TUG combined with "Naming Animals" (TUGdt NA) and "Months Backwards" (TUGdt MB), respectively, were used to assess dual-task performance. The number of correct words and time taken to complete the tests were measured. The CSF biomarkers were analysed by ELISA. Spearman's rank correlation was used for analyses between TUGdt outcomes (TUGdt NA and TUGdt MB), and CSF biomarkers, adjusted for age, gender, and educational level.

RESULTS

The number of correct words, as well as the number of correct words/10 s during TUGdt NA correlated negatively to CSF t-tau and p-tau. No correlations were found between any time scores and CSF biomarkers.

CONCLUSION

The correlations between TUGdt NA and t-tau and p-tau may indicate that neurodegeneration affects dual-task performance. Longitudinal studies are needed to further explore dual-task testing in screening for cognitive impairment due to neurodegeneration.

Light sheet fluorescence microscopy of optically cleared brains for studying the glymphatic system

Fluid transport in the perivascular space by the glia-lymphatic (glymphatic) system is important for the removal of solutes from the brain parenchyma, including peptides such as amyloid-beta which are implicated in the pathogenesis of Alzheimer's disease. The glymphatic system is highly active in the sleep state and under the influence of certain of anaesthetics, while it is suppressed in the awake state and by other anaesthetics. Here we investigated whether light sheet fluorescence microscopy of whole optically cleared murine brains was capable of detecting glymphatic differences in sleep- and awake-mimicking anaesthesia, respectively. Using light-sheet imaging of whole brains, we found anaesthetic-dependent cerebrospinal fluid (CSF) influx differences, including reduced tracer influx along tertiary branches of the middle cerebral artery and reduced influx along dorsal and anterior penetrating arterioles, in the awake-mimicking anaesthesia. This study establishes that light sheet microscopy of optically cleared brains is feasible for quantitative analyses and can provide images of the entire glymphatic system in whole brains.

Diagnostic Impact of Cerebrospinal Fluid Biomarkers in Atypical Dementias in Canada

BACKGROUND

In Canada, standard dementia workup consists of clinical, neurological, and cognitive evaluation, as well as structural brain imaging. For atypical dementia presentations, additional FDG-PET brain imaging is recommended. Cerebrospinal fluid (CSF) biomarkers have recently been proposed as the gold standard for in vivo detection of Alzheimer's disease (AD) pathophysiology (NIA-AA research framework, 2018). As clinical implementation of CSF assessment is still limited in Canada, the present study assessed its impact on diagnostic accuracy in atypical neurodegenerative disorders in the clinical practice.

METHODS

This retrospective clinical chart review included patients with cognitive complaints who underwent lumbar puncture (LP) in addition to the standard diagnostic workup. CSF analysis determined the presence of biological AD based on reduced amyloid-β42-to-total-tau index (ATI) and increased phosphorylated-tau (p-tau) levels. CSF-based diagnoses were compared to standard workup and FDG-PET-based diagnoses.

RESULTS

A total of 28 patients with atypical dementia presentations were included in the present study after evaluation for cognitive complaints at a specialized dementia clinic between November 2017 and July 2019. CSF analysis changed or better specified the initial clinical diagnosis in 43.0% of cases (alternative diagnosis revealed in 25% and excluded in 18%). In patients with additional FDG-PET imaging (n = 23), FDG-PET and CSF-based diagnosis did not correspond in 35% of patients, even though FDG-PET appeared to increase diagnostic accuracy compared to the initial clinical diagnosis.

CONCLUSION

CSF biomarkers improved diagnostic accuracy in atypical cognitively-impaired patients beyond standard workup and FDG-PET imaging. These results support CSF analysis implementation for atypical dementias in Canada, in addition to the standard diagnostic workup.

LTP-like plasticity is impaired in amyloid-positive amnestic MCI but independent of PET-amyloid burden

Transcranial magnetic stimulation (TMS) reveals decreased efficacy of long-term potentiation-like (LTP-like) neuroplastic mechanisms in Alzheimer's disease (AD). However, it is not yet known whether LTP-like plasticity is also impaired in prodromal AD, or how abnormal TMS measures are related to established AD biomarkers. Here, we investigated the LTP-like response to intermittent theta-burst stimulation in 17 amyloid-positive participants with amnestic mild cognitive impairment (MCI) and 10 cognitively unimpaired controls. Our results showed a lack of LTP-like neuromodulation in MCI compared with controls that was unrelated to quantitative amyloid-beta burden on positron emission tomography. Surprisingly, greater LTP-like response was related to worse memory function in the MCI group, highlighting the complex role of neuroplasticity in the prodromal stages of AD. Overall, our results demonstrate abnormal LTP-like plasticity using intermittent theta-burst stimulation assessment in amyloid-positive participants with MCI. These findings support the potential for development of TMS measures as prognostic markers or therapeutic targets in early-stage symptomatic AD.

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.

Retinal involvement in Alzheimer's disease (AD): evidence and current progress on the non-invasive diagnosis and monitoring of AD-related pathology using the eye

Alzheimer's disease (AD) is a common form of age-related dementia that mostly affects the aging population. Clinically, it is a disease characterized by impaired memory and progressive cognitive decline. Although the pathological hallmarks of AD have been traditionally described with a general confinement in the brain, recent studies have shown similar pathological changes in the retina, which is a developmental outgrowth of the forebrain. These AD-related neurodegenerative changes in the retina have been implicated to cause early visual problems in AD even before cognitive impairment becomes apparent. With recent advances in research, the commonly held view that AD-related cerebral pathology causes visual dysfunction through disruption of central visual pathways has been re-examined. Currently, several studies have already explored how AD manifests in the retina and the possibility of using the same retina as a window to non-invasively examine AD-related pathology in the brain. Non-invasive screening of AD through the retina has the potential to improve on early detection and management of the disease since the majority of AD cases are usually diagnosed very late. The purpose of this review is to provide evidence on the involvement of the retina in AD and to suggest a possible direction for future research into the non-invasive screening, diagnosis, and monitoring of AD using the retina.

Cerebrospinal fluid endo-lysosomal proteins as potential biomarkers for Huntington's disease

Molecular markers derived from cerebrospinal fluid (CSF) represent an accessible means of exploring the pathobiology of Huntington's disease (HD) in vivo. The endo-lysosomal/autophagy system is dysfunctional in HD, potentially contributing to disease pathogenesis and representing a potential target for therapeutic intervention. Several endo-lysosomal proteins have shown promise as biomarkers in other neurodegenerative diseases; however, they have yet to be fully explored in HD. We performed parallel reaction monitoring mass spectrometry analysis (PRM-MS) of multiple endo-lysosomal proteins in the CSF of 60 HD mutation carriers and 20 healthy controls. Using generalised linear models controlling for age and CAG, none of the 18 proteins measured displayed significant differences in concentration between HD patients and controls. This was affirmed by principal component analysis, in which no significant difference across disease stage was found in any of the three components representing lysosomal hydrolases, binding/transfer proteins and innate immune system/peripheral proteins. However, several proteins were associated with measures of disease severity and cognition: most notably amyloid precursor protein, which displayed strong correlations with composite Unified Huntington's Disease Rating Scale, UHDRS Total Functional Capacity, UHDRS Total Motor Score, Symbol Digit Modalities Test and Stroop Word Reading. We conclude that although endo-lysosomal proteins are unlikely to have value as disease state CSF biomarkers for Huntington's disease, several proteins demonstrate associations with clinical severity, thus warranting further, targeted exploration and validation in larger, longitudinal samples.

Statistical Disease Progression Modeling in Alzheimer Disease

Background: The characterizing symptom of Alzheimer disease (AD) is cognitive deterioration. While much recent work has focused on defining AD as a biological construct, most patients are still diagnosed, staged, and treated based on their cognitive symptoms. But the cognitive capability of a patient at any time throughout this deterioration reflects not only the disease state, but also the effect of the cognitive decline on the patient's pre-disease cognitive capability. Patients with high pre-disease cognitive capabilities tend to score better on cognitive tests that are sensitive early in disease relative to patients with low pre-disease cognitive capabilities at a similar disease stage. Thus, a single assessment with a cognitive test is often not adequate for determining the stage of an AD patient. Repeated evaluation of patients' cognition over time may improve the ability to stage AD patients, and such longitudinal assessments in combinations with biomarker assessments can help elucidate the time dynamics of biomarkers. In turn, this can potentially lead to identification of markers that are predictive of disease stage and future cognitive decline, possibly before any cognitive deficit is measurable.

Methods and Findings: This article presents a class of statistical disease progression models and applies them to longitudinal cognitive scores. These non-linear mixed-effects disease progression models explicitly model disease stage, baseline cognition, and the patients' individual changes in cognitive ability as latent variables. Maximum-likelihood estimation in these models induces a data-driven criterion for separating disease progression and baseline cognition. Applied to data from the Alzheimer's Disease Neuroimaging Initiative, the model estimated a timeline of cognitive decline that spans ~15 years from the earliest subjective cognitive deficits to severe AD dementia. Subsequent analyses demonstrated how direct modeling of latent factors that modify the observed data patterns provides a scaffold for understanding disease progression, biomarkers, and treatment effects along the continuous time progression of disease.

Conclusions: The presented framework enables direct interpretations of factors that modify cognitive decline. The results give new insights to the value of biomarkers for staging patients and suggest alternative explanations for previous findings related to accelerated cognitive decline among highly educated patients and patients on symptomatic treatments.

Association Between Earliest Amyloid Uptake and Functional Connectivity in Cognitively Unimpaired Elderly

Alterations in cognitive performance have been noted in nondemented subjects with elevated accumulation of amyloid-β (Aβ) fibrils. However, it is not yet understood whether brain function is already influenced by Aβ deposition during the very earliest stages of the disease. We therefore investigated associations between [¹⁸F]Flutemetamol PET, resting-state functional connectivity, gray and white matter structure and cognitive performance in 133 cognitively normal elderly that exhibited normal global Aβ PET levels. [¹⁸F]Flutemetamol uptake in regions known to accumulate Aβ fibrils early in preclinical AD (i.e., mainly certain parts of the default-mode network) was positively associated with dynamic but not static functional connectivity (r = 0.77). Dynamic functional connectivity was further related to better cognitive performance (r = 0.21–0.72). No significant associations were found for Aβ uptake with gray matter volume or white matter diffusivity. The findings demonstrate that the earliest accumulation of Aβ fibrils is associated with increased functional connectivity, which occurs before any structural alterations. The enhanced functional connectivity may reflect a compensatory mechanism to maintain high cognitive performance in the presence of increasing amyloid accumulation during the earliest phases of AD.

Clinical significance of fluid biomarkers in Alzheimer's Disease

The number of patients with Alzheimer's Disease (AD) and other types of dementia disorders has drastically increased over the last decades. AD is a complex progressive neurodegenerative disease affecting about 14 million patients in Europe and the United States. The hallmarks of this disease are neurotic plaques consist of the Amyloid-β peptide (Aβ) and neurofibrillary tangles (NFTs) formed of hyperphosphorylated Tau protein (pTau). Currently, four CSF biomarkers: Amyloid beta 42 (Aβ42), Aβ42/40 ratio, Tau protein, and Tau phosphorylated at threonine 181 (pTau181) have been indicated as core neurochemical AD biomarkers. However, the identification of additional fluid biomarkers, useful in the prognosis, risk stratification, and monitoring of drug response is sorely needed to better understand the complex heterogeneity of AD pathology as well as to improve diagnosis of patients with the disease. Several novel biomarkers have been extensively investigated, and their utility must be proved and eventually integrated into guidelines for use in clinical practice. This paper presents the research and development of CSF and blood biomarkers for AD as well as their potential clinical significance. Upper panel: Aβ peptides are released from transmembrane Amyloid Precursor Protein (APP) under physiological conditions (blue arrow). In AD, however, pathologic accumulation of Aβ monomers leads to their accumulation in plaques (red arrow). This is reflected in decreased concentration of Aβ1-42 and decreased Aβ42/40 concentration ratio in the CSF. Lower panel: Phosphorylated Tau molecules maintain axonal structures; hyperphosphorylation of Tau (red arrow) in AD leads to degeneration of axons, and release of pTau molecules, which then accumulate in neurofibrillary tangles. This process is reflected by increased concentrations of Tau and pTau in the CSF.

The Incremental Diagnostic Value of [18F]Florbetaben PET and the Pivotal Role of the Neuropsychological Assessment in Clinical Practice

BACKGROUND

Amyloid pathology is a key feature of Alzheimer's disease (AD) and can be assessed in vivo with amyloid positron emission tomography (PET) imaging.

OBJECTIVE

The objective of this study was to evaluate the incremental value of a PET scan with [18F]florbetaben, in terms of changes of diagnosis, diagnostic confidence, and treatment plan when added to a standardized diagnostic workup for cognitive disorders, with particular focus on the role of the neuropsychological assessment, including the Free and Cued Selective Reminding Test (FCSRT).

METHODS

A total of 104 patients (69 mild cognitive impairment, 35 dementia), with diagnostic uncertainty after diagnostic workup, were recruited from our memory clinic. [18F]florbetaben PET scans were interpreted as amyloid negative or positive on the basis of a semi-quantitative visual rating. Clinical diagnosis and diagnostic confidence for AD or non-AD dementia were rated before and after PET result disclosure, as was the impact of PET on the patient management plan.

RESULTS

There were 69/104 (66%) [18F]florbetaben positive scans, 51/62 (82%) patients were suspected as having AD before the PET scan and 18/42 (43%) were not. Overall, the data obtained at PET changed 18/104 diagnoses (17%) and increased diagnostic confidence from 69.1±8.1% to 83.5±9.1 (p < 0.001), with the greatest impact on diagnosis and confidence in PET negative patients with an initial diagnosis of AD (p < 0.01) and in early-onset patients (p = 0.01).

CONCLUSION

Amyloid PET represents a source of added value in dementia diagnosis, with a significant effect on diagnosis and diagnostic confidence. However, the use of a complete neuropsychological assessment has an add-on value on limiting the amyloid PET influence on change of diagnosis, and the real impact of amyloid PET should always be weighed up together with an accurate standardized diagnostic workup.

Spread of pathological tau proteins through communicating neurons in human Alzheimer's disease

Tau is a hallmark pathology of Alzheimer's disease, and animal models have suggested that tau spreads from cell to cell through neuronal connections, facilitated by β-amyloid (Aβ). We test this hypothesis in humans using an epidemic spreading model (ESM) to simulate tau spread, and compare these simulations to observed patterns measured using tau-PET in 312 individuals along Alzheimer's disease continuum. Up to 70% of the variance in the overall spatial pattern of tau can be explained by our model. Surprisingly, the ESM predicts the spatial patterns of tau irrespective of whether brain Aβ is present, but regions with greater Aβ burden show greater tau than predicted by connectivity patterns, suggesting a role of Aβ in accelerating tau spread. Altogether, our results provide evidence in humans that tau spreads through neuronal communication pathways even in normal aging, and that this process is accelerated by the presence of brain Aβ.

Amyloid-β Positivity Predicts Cognitive Decline but Cognition Predicts Progression to Amyloid-β Positivity

BACKGROUND

Stage 1 of the National Institute on Aging-Alzheimer's Association's proposed Alzheimer's disease continuum is defined as amyloid-β (Aβ) positive but cognitively normal. Identifying at-risk individuals before Aβ reaches pathological levels could have great benefits for early intervention. Although Aβ levels become abnormal long before severe cognitive impairments appear, increasing evidence suggests that subtle cognitive changes may begin early, potentially before Aβ surpasses the threshold for abnormality. We examined whether baseline cognitive performance would predict progression from normal to abnormal levels of Aβ.

METHODS

We examined the association of baseline cognitive composites (Preclinical Alzheimer Cognitive Composite, Alzheimer's Disease Neuroimaging Initiative (ADNI) memory factor composite) with progression to Aβ positivity in 292 nondemented, Aβ-negative ADNI participants. Additional analyses included continuous cerebrospinal fluid biomarker levels to examine the effects of subthreshold pathology.

RESULTS

Forty participants progressed to Aβ positivity during follow-up. Poorer baseline performance on both cognitive measures was significantly associated with increased odds of progression. More abnormal levels of baseline cerebrospinal fluid phosphorylated tau and subthreshold Aβ were associated with increased odds of progression to Aβ positivity. Nevertheless, baseline ADNI memory factor composite performance predicted progression even after controlling for baseline biomarker levels and APOE genotype (Preclinical Alzheimer Cognitive Composite was trend level). Survival analyses were largely consistent: controlling for baseline biomarker levels, baseline Preclinical Alzheimer Cognitive Composite still significantly predicted progression time to Aβ positivity (ADNI memory factor composite was trend level).

CONCLUSIONS

The possibility of intervening before Aβ reaches pathological levels is of obvious benefit. Low-cost, noninvasive cognitive measures can be informative for determining who is likely to progress to Aβ positivity, even after accounting for baseline subthreshold biomarker levels.

Predicting MCI progression with FDG-PET and cognitive scores: a longitudinal study

BACKGROUND

Mild cognitive impairment (MCI) is an intermediate stage between normal aging and dementia. Studies on MCI progression are important for Alzheimer's disease (AD) prevention. 18F fluoro-deoxy-glucose positron emission tomography (FDG-PET) has been proven to be a powerful tool for measuring cerebral glucose metabolism. In this study, we proposed a classification framework for MCI prediction with both baseline and multiple follow-up FDG-PET scans as well as cognitive scores of 33 progressive MCI (pMCI) patients and 46 stable MCI (sMCI) patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

METHOD

First, PET images were normalized using the Yakushev normalization procedure and registered to the Brainnetome Atlas (BNA). The average metabolic intensities of brain regions were defined as static features. Dynamic features were the intensity variation between baseline and the other three time points and change ratios with the intensity obtained at baseline considered as reference. Mini-mental State Examination (MMSE) scores and Alzheimer's disease Assessment Scale-Cognitive section (ADAS-cog) scores of each time point were collected as cognitive features. And F-score was applied for feature selection. Finally, support vector machine (SVM) with radial basis function (RBF) kernel was used for the three above features.

RESULTS

Dynamic features showed the best classification performance in accuracy of 88.61% than static features (accuracy of 78.48%). And the combination of cognitive features and dynamic features improved the classification performance in specificity of 95.65% and Area Under Curve (AUC) of 0.9308.

CONCLUSION

Our results reported that dynamic features are more representative in longitudinal research for MCI prediction work. And dynamic features and cognitive scores complementarily enhance the classification performance in specificity and AUC. These findings may predict the disease course and clinical changes in individuals with mild cognitive impairment.

Elecsys CSF biomarker immunoassays demonstrate concordance with amyloid-PET imaging

Background

β-amyloid (Aβ) positron emission tomography (PET) imaging is currently the only Food and Drug Administration-approved method to support clinical diagnosis of Alzheimer’s disease (AD). However, numerous research studies support the use of cerebrospinal fluid (CSF) biomarkers, as a cost-efficient, quick and equally valid method to define AD pathology.

Methods

Using automated Elecsys® assays (Roche Diagnostics) for Aβ (1–42) (Aβ42), Aβ (1–40) (Aβ40), total tau (tTau) and phosphorylated tau (181P) (pTau), we examined CSF samples from 202 participants of the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing cohort, to demonstrate the concordance with pathological AD via PET imaging.

Results

Ratios Aβ42/Aβ40, tTau/Aβ42 and pTau/Aβ42 had higher receiver operator characteristic—area under the curve (all 0.94), and greater concordance with Aβ-PET (overall percentage agreement ~ 90%), compared with individual biomarkers.

Conclusion

Strong concordance between CSF biomarkers and Aβ-PET status was observed overall, including for cognitively normal participants, further strengthening the association between these markers of AD neuropathological burden for both developmental research studies and for use in clinical trials.

Supplementary information

The online version of this article (10.1186/s13195-020-00595-5).

Diagnostic value of plasma phosphorylated tau181 in Alzheimer's disease and frontotemporal lobar degeneration

With the potential development of new disease-modifying Alzheimer's disease (AD) therapies, simple, widely available screening tests are needed to identify which individuals, who are experiencing symptoms of cognitive or behavioral decline, should be further evaluated for initiation of treatment. A blood-based test for AD would be a less invasive and less expensive screening tool than the currently approved cerebrospinal fluid or amyloid β positron emission tomography (PET) diagnostic tests. We examined whether plasma tau phosphorylated at residue 181 (pTau181) could differentiate between clinically diagnosed or autopsy-confirmed AD and frontotemporal lobar degeneration. Plasma pTau181 concentrations were increased by 3.5-fold in AD compared to controls and differentiated AD from both clinically diagnosed (receiver operating characteristic area under the curve of 0.894) and autopsy-confirmed frontotemporal lobar degeneration (area under the curve of 0.878). Plasma pTau181 identified individuals who were amyloid β-PET-positive regardless of clinical diagnosis and correlated with cortical tau protein deposition measured by 18F-flortaucipir PET. Plasma pTau181 may be useful to screen for tau pathology associated with AD.

PET Radiopharmaceuticals for Alzheimer's Disease and Parkinson's Disease Diagnosis, the Current and Future Landscape

Ironically, population aging which is considered a public health success has been accompanied by a myriad of new health challenges, which include neurodegenerative disorders (NDDs), the incidence of which increases proportionally to age. Among them, Alzheimer's disease (AD) and Parkinson's disease (PD) are the most common, with the misfolding and the aggregation of proteins being common and causal in the pathogenesis of both diseases. AD is characterized by the presence of hyperphosphorylated τ protein (tau), which is the main component of neurofibrillary tangles (NFTs), and senile plaques the main component of which is β-amyloid peptide aggregates (Aβ). The neuropathological hallmark of PD is α-synuclein aggregates (α-syn), which are present as insoluble fibrils, the primary structural component of Lewy body (LB) and neurites (LN). An increasing number of non-invasive PET examinations have been used for AD, to monitor the pathological progress (hallmarks) of disease. Notwithstanding, still the need for the development of novel detection tools for other proteinopathies still remains. This review, although not exhaustively, looks at the timeline of the development of existing tracers used in the imaging of Aβ and important moments that led to the development of these tracers.

Cerebrospinal Fluid and MRI Biomarkers in Neurodegenerative Diseases: A Retrospective Memory Clinic-Based Study

BACKGROUND

Cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) biomarkers of neurodegenerative diseases are relatively sensitive and specific in highly curated research cohorts, but proper validation for clinical use is mostly missing.

OBJECTIVE

We studied these biomarkers in a novel memory clinic cohort with a variety of different neurodegenerative diseases.

METHODS

This study consisted of 191 patients with subjective or objective cognitive impairment who underwent neurological, CSF biomarker (Aβ42, p-tau, and tau) and T1-weighted MRI examinations at Kuopio University Hospital. We assessed CSF and imaging biomarkers, including structural MRI focused on volumetric and cortical thickness analyses, across groups stratified based on different clinical diagnoses, including Alzheimer's disease (AD), frontotemporal dementia, dementia with Lewy bodies, Parkinson's disease, vascular dementia, and mild cognitive impairment (MCI), and subjects with no evidence of neurodegenerative disease underlying the cognitive symptoms. Imaging biomarkers were also studied by profiling subjects according to the novel amyloid, tau, and, neurodegeneration (AT(N)) classification.

RESULTS

Numerous imaging variables differed by clinical diagnosis, including hippocampal, amygdalar and inferior lateral ventricular volumes and entorhinal, lingual, inferior parietal and isthmus cingulate cortical thicknesses, at a false discovery rate (FDR)-corrected threshold for significance (analysis of covariance; p < 0.005). In volumetric comparisons by AT(N) profile, hippocampal volume significantly differed (p < 0.001) between patients with normal AD biomarkers and patients with amyloid pathology.

CONCLUSION

Our analysis suggests that CSF and MRI biomarkers function well also in clinical practice across multiple clinical diagnostic groups in addition to AD, MCI, and cognitively normal groups.