The use of biomarkers for the etiologic diagnosis of MCI in Europe: an EADC survey

LiveDrive AI: A Pilot Study of a Machine Learning-Powered Diagnostic System for Real-Time, Non-Invasive Detection of Mild Cognitive Impairment

Alzheimer's disease (AD) represents a significant global health issue, affecting over 55 million individuals worldwide, with a progressive impact on cognitive and functional abilities. Early detection, particularly of mild cognitive impairment (MCI) as an indicator of potential AD onset, is crucial yet challenging, given the limitations of current diagnostic biomarkers and the need for non-invasive, accessible tools. This study aims to address these gaps by exploring driving performance as a novel, non-invasive biomarker for MCI detection. Using the LiveDrive AI system, equipped with multimodal sensing (MMS) technology and a driving performance assessment strategy, the proposed work analyzes the predictive capacity of driving patterns in indicating cognitive decline. Machine learning models, trained on an expert-annotated in-house dataset, were employed to detect MCI status from driving performance. Key findings demonstrate the feasibility of using nuanced driving features, such as velocity and acceleration during turning, as indicators of cognitive decline. This approach holds promise for integration into smartphone or car applications, enabling real-time, continuous cognitive health monitoring. The implications of this work suggest a transformative step towards scalable, real-world solutions for early AD diagnosis, with the potential to improve patient outcomes and disease management.

Aβ status assessment in a hypothetical scenario prior to treatment with disease-modifying therapies: Evidence from 10-year real-world experience at university memory clinics

INTRODUCTION

With the advent of disease-modifying therapies, accurate assessment of biomarkers indicating the presence of disease-associated amyloid beta (Aβ) pathology becomes crucial in patients with clinically suspected Alzheimer's disease (AD). We evaluated Aβ levels in cerebrospinal fluid (Aβ CSF) and Aβ levels in positron emission tomography (Aβ PET) biomarkers in a real-world memory-clinic setting to develop an efficient algorithm for clinical use.

METHODS

Patients were evaluated for AD-related Aβ pathology from two independent cohorts (Ludwig Maximilian University [LMU], n = 402, and Medical University of Vienna [MUV], n = 144). Optimal thresholds of CSF biomarkers were deduced from receiver operating characteristic curves and validated against Aβ PET positivity.

RESULTS

In both cohorts, a CSF Aβ42/40 ratio ≥ 7.1% was associated with a low risk of a positive Aβ PET scan (negative predictive value: 94.3%). Implementing two cutoffs revealed 14% to 16% of patients with intermediate results (CSF Aβ42/40 ratio: 5.5%-7.1%), which had a strong benefit from Aβ PET imaging (44%-52% Aβ PET positivity).

DISCUSSION

A two-cutoff approach for CSF Aβ42/40 including Aβ PET imaging at intermediate results provides an effective assessment of Aβ pathology in real-world settings.

Highlights

We evaluated cerebrospinal fluid (CSF) and positron emission tomography (PET) amyloid beta (Aβ) biomarkers for Alzheimer's disease in real-world cohorts.A CSF Aβ 42/40 ratio between 5.5% and 7.1% defines patients at borderline levels.Patients at borderline levels strongly benefit from additional Aβ PET imaging.Two-cutoff CSF Aβ 42/40 and PET will allow effective treatment stratification.

Frontiers and hotspots evolution in mild cognitive impairment: a bibliometric analysis of from 2013 to 2023

Background

Mild cognitive impairment is a heterogeneous syndrome. The heterogeneity of the syndrome and the absence of consensus limited the advancement of MCI. The purpose of our research is to create a visual framework of the last decade, highlight the hotspots of current research, and forecast the most fruitful avenues for future MCI research.

Methods

We collected all the MCI-related literature published between 1 January 2013, and 24 April 2023, on the "Web of Science." The visual graph was created by the CiteSpace and VOSviewer. The current research hotspots and future research directions are summarized through the analysis of keywords and co-cited literature.

Results

There are 6,075 articles were included in the final analysis. The number of publications shows an upward trend, especially after 2018. The United States and the University of California System are the most prolific countries and institutions, respectively. Petersen is the author who ranks first in terms of publication volume and influence. Journal of Alzheimer's Disease was the most productive journal. "neuroimaging," "fluid markers," and "predictors" are the focus of current research, and "machine learning," "electroencephalogram," "deep learning," and "blood biomarkers" are potential research directions in the future.

Conclusion

The cognition of MCI has been continuously evolved and renewed by multiple countries' joint efforts in the past decade. Hotspots for current research are on diagnostic biomarkers, such as fluid markers, neuroimaging, and so on. Future hotspots might be focused on the best prognostic and diagnostic models generated by machine learning and large-scale screening tools such as EEG and blood biomarkers.

Clinical utility of diffusion MRI-derived measures of cortical microstructure in a real-world memory clinic setting

OBJECTIVE

To investigate cortical microstructural measures from diffusion MRI as "neurodegeneration" markers that could improve prognostic accuracy in mild cognitive impairment (MCI).

METHODS

The prognostic power of Amyloid/Tau/Neurodegeneration (ATN) biomarkers to predict progression from MCI to AD or non-AD dementia was investigated. Ninety patients underwent clinical evaluation (follow-up interval 32 ± 18 months), lumbar puncture, and MRI. Participants were grouped by clinical stage and cerebrospinal fluid Amyloid and Tau status. T1-structural and diffusion MRI scans were analyzed to calculate diffusion metrics related to cortical columnar structure (AngleR, ParlPD, PerpPD+), cortical mean diffusivity, and fractional anisotropy. Statistical tests were corrected for multiple comparisons. Prognostic power was assessed using receiver operating characteristic (ROC) analysis and related indices.

RESULTS

A progressive increase of whole-brain cortical diffusion values was observed along the AD continuum, with all A+ groups showing significantly higher AngleR than A-T-. Investigating clinical progression to dementia, the AT biomarkers together showed good positive predictive value (with 90.91% of MCI A+T+ converting to dementia) but poor negative predictive value (with 40% of MCI A-T- progressing to a mix of AD and non-AD dementias). Adding whole-brain AngleR as an N marker, produced good differentiation between stable and converting MCI A-T- patients (0.8 area under ROC curve) and substantially improved negative predictive value (+21.25%).

INTERPRETATION

Results support the clinical utility of cortical microstructure to aid prognosis, especially in A-T- patients. Further work will investigate other complexities of the real-world clinical setting, including A-T+ groups. Diffusion MRI measures of neurodegeneration may complement fluid AT markers to support clinical decision-making.

European intersocietal recommendations for the biomarker-based diagnosis of neurocognitive disorders

The recent commercialisation of the first disease-modifying drugs for Alzheimer's disease emphasises the need for consensus recommendations on the rational use of biomarkers to diagnose people with suspected neurocognitive disorders in memory clinics. Most available recommendations and guidelines are either disease-centred or biomarker-centred. A European multidisciplinary taskforce consisting of 22 experts from 11 European scientific societies set out to define the first patient-centred diagnostic workflow that aims to prioritise testing for available biomarkers in individuals attending memory clinics. After an extensive literature review, we used a Delphi consensus procedure to identify 11 clinical syndromes, based on clinical history and examination, neuropsychology, blood tests, structural imaging, and, in some cases, EEG. We recommend first-line and, if needed, second-line testing for biomarkers according to the patient's clinical profile and the results of previous biomarker findings. This diagnostic workflow will promote consistency in the diagnosis of neurocognitive disorders across European countries.

Visual Functions Are Associated with Biomarker Changes in Alzheimer's Disease

Background

While various biomarkers of Alzheimer's disease (AD) have been associated with general cognitive function, their association to visual-perceptive function across the AD spectrum warrant more attention due to its significant impact on quality of life. Thus, this study explores how AD biomarkers are associated with decline in this cognitive domain.

Objective

To explore associations between various fluid and imaging biomarkers and visual-based cognitive assessments in participants across the AD spectrum.

Methods

Data from participants (N = 1,460) in the Alzheimer's Disease Neuroimaging Initiative were analyzed, including fluid and imaging biomarkers. Along with the Mini-Mental State Examination (MMSE), three specific visual-based cognitive tests were investigated: Trail Making Test (TMT) A and TMT B, and the Boston Naming Test (BNT). Locally estimated scatterplot smoothing curves and Pearson correlation coefficients were used to examine associations.

Results

MMSE showed the strongest correlations with most biomarkers, followed by TMT-B. The p-tau181/Aβ1-42 ratio, along with the volume of the hippocampus and entorhinal cortex, had the strongest associations among the biomarkers.

Conclusions

Several biomarkers are associated with visual processing across the disease spectrum, emphasizing their potential in assessing disease severity and contributing to progression models of visual function and cognition.

Integrated transcriptomics reveals the brain and blood biomarkers in Alzheimer's disease

BACKGROUND

The systematic molecular associations between the peripheral blood cells and brain in Alzheimer's disease (AD) remains unclear, which hinders our understanding of AD pathological mechanisms and the exploration of new diagnostic biomarkers.

METHODS

Here, we performed an integrated analysis of the brain and peripheral blood cells transcriptomics to establish peripheral biomarkers of AD. By employing multiple statistical analyses plus machine learning, we identified and validated multiple regulated central and peripheral network in patients with AD.

RESULTS

By bioinformatics analysis, a total of 243 genes were differentially expressed in the central and peripheral systems, mainly enriched in three modules: immune response, glucose metabolism and lysosome. In addition, lysosome related gene ATP6V1E1 and immune response related genes (IL2RG, OSM, EVI2B TNFRSF1A, CXCR4, STAT5A) were significantly correlated with Aβ or Tau pathology. Finally, receiver operating characteristic (ROC) analysis revealed that ATP6V1E1 showed high-diagnostic potential for AD.

CONCLUSION

Taken together, our data identified the main pathological pathways in AD progression, particularly the systemic dysregulation of the immune response, and provided peripheral biomarkers for AD diagnosis.

A Case-Control Clinical Trial on a Deep Learning-Based Classification System for Diagnosis of Amyloid-Positive Alzheimer's Disease

OBJECTIVE

A deep learning-based classification system (DLCS) which uses structural brain magnetic resonance imaging (MRI) to diagnose Alzheimer's disease (AD) was developed in a previous recent study. Here, we evaluate its performance by conducting a single-center, case-control clinical trial.

METHODS

We retrospectively collected T1-weighted brain MRI scans of subjects who had an accompanying measure of amyloid-beta (Aβ) positivity based on a 18F-florbetaben positron emission tomography scan. The dataset included 188 Aβ-positive patients with mild cognitive impairment or dementia due to AD, and 162 Aβ-negative controls with normal cognition. We calculated the sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of the DLCS in the classification of Aβ-positive AD patients from Aβ-negative controls.

RESULTS

The DLCS showed excellent performance, with sensitivity, specificity, positive predictive value, negative predictive value, and AUC of 85.6% (95% confidence interval [CI], 79.8-90.0), 90.1% (95% CI, 84.5-94.2), 91.0% (95% CI, 86.3-94.1), 84.4% (95% CI, 79.2-88.5), and 0.937 (95% CI, 0.911-0.963), respectively.

CONCLUSION

The DLCS shows promise in clinical settings where it could be routinely applied to MRI scans regardless of original scan purpose to improve the early detection of AD.

Dementia prevention in memory clinics: recommendations from the European task force for brain health services

Observational population studies indicate that prevention of dementia and cognitive decline is being accomplished, possibly as an unintended result of better vascular prevention and healthier lifestyles. Population aging in the coming decades requires deliberate efforts to further decrease its prevalence and societal burden. Increasing evidence supports the efficacy of preventive interventions on persons with intact cognition and high dementia risk. We report recommendations for the deployment of second-generation memory clinics (Brain Health Services) whose mission is evidence-based and ethical dementia prevention in at-risk individuals. The cornerstone interventions consist of (i) assessment of genetic and potentially modifiable risk factors including brain pathology, and risk stratification, (ii) risk communication with ad-hoc protocols, (iii) risk reduction with multi-domain interventions, and (iv) cognitive enhancement with cognitive and physical training. A roadmap is proposed for concept validation and ensuing clinical deployment.

Attitudes of Neurologists Toward the Use of Biomarkers in the Diagnosis of Early Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) biomarkers reflect key elements of pathophysiology and improve the diagnostic process. However, their use in routine clinical practice is still limited.

OBJECTIVE

We aimed to assess neurologists' barriers and enablers to early AD diagnosis using core AD biomarkers.

METHODS

We conducted an online study in collaboration with the Spanish Society of Neurology. Neurologists answered a survey exploring their attitudes towards AD diagnosis using biomarkers in mild cognitive impairment (MCI) or mild AD dementia. Multivariate logistic regression analyses were conducted to determine the association between neurologists' characteristics and diagnostic attitudes.

RESULTS

We included 188 neurologists with a mean age (SD) of 40.6 (11.3) years, 52.7% male. Most participants had access to AD biomarkers, mainly in cerebrospinal fluid (CSF) (89.9%,#x0025;, n = 169). The majority of participants (95.2%,#x0025;, n = 179) considered CSF biomarkers useful for an etiological diagnosis in MCI. However, 85.6% of respondents (n = 161) used them in less than 60% of their MCI patients in routine clinical practice. Facilitating patients and their families to plan for the future was the most frequent enabler for the use of biomarkers. Short consultation time and practicalities associated with the programming of a lumbar puncture were the most common barriers. A younger neurologist age (p = 0.010) and a higher number of patients managed weekly (p = 0.036) were positively associated with the use of biomarkers.

CONCLUSION

Most neurologists had a favorable attitude to the use of biomarkers, especially in MCI patients. Improvements in resources and consultation time may increase their use in routine clinical practice.

Neuropsychological Assessment in the Distinction Between Biomarker Defined Frontal-Variant of Alzheimer's Disease and Behavioral-Variant of Frontotemporal Dementia

BACKGROUND

Frontal-variant of Alzheimer's disease (fvAD) was purposed for patients with AD pathology that, despite the typical amnestic presentation, show early and progressive deterioration of behavior and executive functions, closely resembling the behavioral-variant of frontotemporal dementia (bvFTD). This leads to a challenging differential diagnosis where neuropsychological evaluation and in vivo pathological evidence are essential.

OBJECTIVE

To evaluate the contribution of a comprehensive neuropsychological assessment (NP) battery in distinguishing between fvAD-dementia and bvFTD supported by cerebrospinal fluid (CSF) biomarkers.

METHODS

We included 40 patients with a baseline NP profile with prominent early executive and/or behavioral dysfunction, who meet both diagnosis of bvFTD and fvAD-dementia, according to international criteria. All patients underwent comprehensive NP assessment and CSF-AD biomarker evaluation. Neuropsychological domains as well as clinical and sociodemographic features, and APOE genotype were compared between groups.

RESULTS

21 patients (52.5%) met the biological criteria for AD (decreased Aβ42 together with increased T-tau or P-tau in CSF) and were therefore classified as fvAD (mean age was 64.57, with 47.6% female). There were no differences between groups regarding age/age-at-onset, gender, or educational level. Regarding neuropsychological profile, performances in language and memory functions were equivalent in both groups. Significant differences were found in visuo-constructional abilities (p = 0.004), Trail Making Test A (p < 0.001), and Raven's Colored Progressive Matrices (p = 0.019), with fvAD patients showing worst performances.

CONCLUSION

In patients with an early prominent frontal profile, a higher impairment in attention and visuo-spatial functions, signaling additional right hemisphere fronto-parietal dysfunction, point towards a diagnosis of fvAD-dementia and may be useful in clinical practice.

Clinical research in dementia: A perspective on implementing innovation

The increasing global prevalence of dementia demands concrete actions that are aimed strategically at optimizing processes that drive clinical innovation. The first step in this direction requires outlining hurdles in the transition from research to practice. The different parties needed to support translational processes have communication mismatches; methodological gaps hamper evidence-based decision-making; and data are insufficient to provide reliable estimates of long-term health benefits and costs in decisional models. Pilot projects are tackling some of these gaps, but appropriate methods often still need to be devised or adapted to the dementia field. A consistent implementation perspective along the whole translational continuum, explicitly defined and shared among the relevant stakeholders, should overcome the "research-versus-adoption" dichotomy, and tackle the implementation cliff early on. Concrete next steps may consist of providing tools that support the effective participation of heterogeneous stakeholders and agreeing on a definition of clinical significance that facilitates the selection of proper outcome measures.

The Clinical Use of Alzheimer's Disease Biomarkers in Patients with Mild Cognitive Impairment: A European Alzheimer's Disease Consortium Survey

BACKGROUND

Recent advances occurred in the field of Alzheimer's disease (AD) biomarkers and the introduction of a research framework grounded on a biomarker-based definition of AD might have fostered an increased clinical use of AD biomarkers. For this reason, an up-to-date depiction of the clinical use of AD biomarkers is needed.

OBJECTIVE

To investigate the clinical use of the main AD biomarkers in patients with mild cognitive impairment (MCI) by examining the beliefs and preferences of professionals (clinicians and biomarker experts) of the European Alzheimer's Disease Consortium (EADC).

METHODS

150 professionals filled in an online survey from May to September 2020. The investigated biomarkers were medial temporal lobe atrophy score (MTA) on structural MRI, typical AD (i.e., temporoparietal and posterior cingulate) hypometabolism on FDG-PET, CSF (Aβ42, p-tau, t-tau), amyloid-PET and tau-PET.

RESULTS

The frequency of responders reporting a frequent-to-constant use of MTA (77%) is higher than that of those reporting a frequent-to-constant use of the other AD biomarkers (i.e.

, CSF

45%, p = 0.014; FDG-PET: 32%, p &lt; 0.001; amyloid-PET: 8%, p &lt; 0.001; and tau-PET: 2%, p &lt; 0.001). CSF is considered the most valuable biomarker in terms of additional diagnostic value, followed by amyloid-PET, tau-PET, and typical AD hypometabolism on FDG-PET.

CONCLUSION

AD biomarkers are widely used across European memory clinics with a clinical research background for the diagnosis of MCI. Overall, we observed that CSF is currently considered as the most useful biomarker, followed by amyloid-PET.

Early diagnosis of Alzheimer's disease using machine learning: a multi-diagnostic, generalizable approach

BACKGROUND

Early and accurate diagnosis of Alzheimer's disease (AD) is essential for disease management and therapeutic choices that can delay disease progression. Machine learning (ML) approaches have been extensively used in attempts to develop algorithms for reliable early diagnosis of AD, although clinical usefulness, interpretability, and generalizability of the classifiers across datasets and MRI protocols remain limited.

METHODS

We report a multi-diagnostic and generalizable approach for mild cognitive impairment (MCI) and AD diagnosis using structural MRI and ML. Classifiers were trained and tested using subjects from the AD Neuroimaging Initiative (ADNI) database (n = 570) and the Open Access Series of Imaging Studies (OASIS) project database (n = 531). Several classifiers are compared and combined using voting for a decision. Additionally, we report tests of generalizability across datasets and protocols (IR-SPGR and MPRAGE), the impact of using graph theory measures on diagnostic classification performance, the relative importance of different brain regions on classification for better interpretability, and an evaluation of the potential for clinical applicability of the classifier.

RESULTS

Our "healthy controls (HC) vs. AD" classifier trained and tested on the combination of ADNI and OASIS datasets obtained a balanced accuracy (BAC) of 90.6% and a Matthew's correlation coefficient (MCC) of 0.811. Our "HC vs. MCI vs. AD" classifier trained and tested on the ADNI dataset obtained a 62.1% BAC (33.3% being the by-chance cut-off) and 0.438 MCC. Hippocampal features were the strongest contributors to the classification decisions (approx. 25-45%), followed by temporal (approx. 13%), cingulate, and frontal regions (approx. 8-13% each), which is consistent with our current understanding of AD and its progression. Classifiers generalized well across both datasets and protocols. Finally, using graph theory measures did not improve classification performance.

CONCLUSIONS

In sum, we present a diagnostic tool for MCI and AD trained using baseline scans and a follow-up diagnosis regardless of progression, which is multi-diagnostic, generalizable across independent data sources and acquisition protocols, and with transparently reported performance. Rated as potentially clinically applicable, our tool may be clinically useful to inform diagnostic decisions in dementia, if successful in real-world prospective clinical trials.

The Outcome of Patients with Amyloid-Negative Amnestic Mild Cognitive Impairment

Background: Patients with amnestic mild cognitive impairment (aMCI) are usually at an initial stage of Alzheimer’s disease (AD). However, some patients with aMCI do not present biomarkers of amyloid pathology characteristic of AD. The significance of amyloid-negative aMCI is not presently clear. Objective: To know the etiology and prognosis of amyloid-negative aMCI. Methods: Patients who fulfilled criteria for aMCI and were amyloid negative were selected from a large cohort of non-demented patients with cognitive complaints and were followed with clinical and neuropsychological assessments. Results: Few amyloid-negative aMCI had evidence of neurodegeneration at the baseline, as reflected in cerebrospinal fluid elevated tau protein levels. About half of the patients remained essentially stable for long periods of time. Others manifested a psychiatric disorder that was not apparent at baseline, namely major depression or bipolar disorder. Remarkably, about a quarter of patients developed neurodegenerative disorders other than AD, mostly frontotemporal dementia or Lewy body disease. Conclusion: Amyloid-negative aMCI is a heterogeneous condition. Many patients remain clinically stable, but others may later manifest psychiatric conditions or evolve to neurodegenerative disorders. Prudence is needed when communicating to the patient and family the results of biomarkers, and clinical follow-up should be advised.

Periphery Biomarkers for Objective Diagnosis of Cognitive Decline in Type 2 Diabetes Patients

Introduction: Type 2 diabetes mellitus (T2DM) is an independent risk factor of Alzheimer’s disease (AD), and populations with mild cognitive impairment (MCI) have high incidence to suffer from AD. Therefore, discerning who may be more vulnerable to MCI, among the increasing T2DM populations, is important for early intervention and eventually decreasing the prevalence rate of AD. This study was to explore whether the change of plasma β-amyloid (Aβ) could be a biomarker to distinguish MCI (T2DM-MCI) from non-MCI (T2DM-nMCI) in T2DM patients.

Methods: Eight hundred fifty-two T2DM patients collected from five medical centers were assigned randomly to training and validation cohorts. Plasma Aβ, platelet glycogen synthase kinase-3β (GSK-3β), apolipoprotein E (ApoE) genotypes, and olfactory and cognitive functions were measured by ELISA, dot blot, RT-PCR, Connecticut Chemosensory Clinical Research Center (CCCRC) olfactory test based on the diluted butanol, and Minimum Mental State Examination (MMSE) test, respectively, and multivariate logistic regression analyses were applied.

Results: Elevation of plasma Aβ1-42/Aβ1-40 is an independent risk factor of MCI in T2DM patients. Although using Aβ1-42/Aβ1-40 alone only reached an AUC of 0.631 for MCI diagnosis, addition of the elevated Aβ1-42/Aβ1-40 to our previous model (i.e., activated platelet GSK-3β, ApoE ε4 genotype, olfactory decline, and aging) significantly increased the discriminating efficiency of T2DM-MCI from T2DM-nMCI, with an AUC of 0.846 (95% CI: 0.794–0.897) to 0.869 (95% CI: 0.822–0.916) in the training cohort and an AUC of 0.848 (95% CI: 0.815–0.882) to 0.867 (95% CI: 0.835–0.899) in the validation cohort, respectively.

Conclusion: A combination of the elevated plasma Aβ1-42/Aβ1-40 with activated platelet GSK-3β, ApoE ε4 genotype, olfactory decline, and aging could efficiently diagnose MCI in T2DM patients. Further longitudinal studies may consummate the model for early prediction of AD.

The strategic biomarker roadmap for the validation of Alzheimer's diagnostic biomarkers: methodological update

BACKGROUND

The 2017 Alzheimer's disease (AD) Strategic Biomarker Roadmap (SBR) structured the validation of AD diagnostic biomarkers into 5 phases, systematically assessing analytical validity (Phases 1-2), clinical validity (Phases 3-4), and clinical utility (Phase 5) through primary and secondary Aims. This framework allows to map knowledge gaps and research priorities, accelerating the route towards clinical implementation. Within an initiative aimed to assess the development of biomarkers of tau pathology, we revised this methodology consistently with progress in AD research.

METHODS

We critically appraised the adequacy of the 2017 Biomarker Roadmap within current diagnostic frameworks, discussed updates at a workshop convening the Alzheimer's Association and 8 leading AD biomarker research groups, and detailed the methods to allow consistent assessment of aims achievement for tau and other AD diagnostic biomarkers.

RESULTS

The 2020 update applies to all AD diagnostic biomarkers. In Phases 2-3, we admitted a greater variety of study designs (e.g., cross-sectional in addition to longitudinal) and reference standards (e.g., biomarker confirmation in addition to clinical progression) based on construct (in addition to criterion) validity. We structured a systematic data extraction to enable transparent and formal evidence assessment procedures. Finally, we have clarified issues that need to be addressed to generate data eligible to evidence-to-decision procedures.

DISCUSSION

This revision allows for more versatile and precise assessment of existing evidence, keeps up with theoretical developments, and helps clinical researchers in producing evidence suitable for evidence-to-decision procedures. Compliance with this methodology is essential to implement AD biomarkers efficiently in clinical research and diagnostics.

Plasma Amyloid Concentration in Alzheimer's Disease: Performance of a High-Throughput Amyloid Assay in Distinguishing Alzheimer's Disease Cases from Controls

Background:

Collection of cerebrospinal fluid (CSF) for measurement of amyloid-β (Aβ) species is a gold standard in Alzheimer’s disease (AD) diagnosis, but has risks. Thus, establishing a low-risk blood Aβ test with high AD sensitivity and specificity is of outmost interest.

Objective:

We evaluated the ability of a commercially available plasma Aβ assay to distinguish AD patients from biomarker-healthy controls.

Method:

In a case-control design, we examined plasma samples from 44 AD patients (A + N+) and 49 controls (A–N–) from a memory clinic. AD was diagnosed using a combination of neuropsychological examination, CSF biomarker analysis and brain imaging. Total Aβ₄₀ and total Aβ₄₂ in plasma were measured through enzyme-linked immunosorbent assay (ELISA) technology using ABtest40 and ABtest42 test kits (Araclon Biotech Ltd.). Receiver operating characteristic (ROC) analyses with outcome AD were performed, and sensitivity and specificity were calculated.

Results:

Plasma Aβ_42/40 was weakly positively correlated with CSF Aβ_42/40 (Spearman’s rho 0.22; p = 0.037). Plasma Aβ_42/40 alone was not able to statistically significantly distinguish between AD patients and controls (AUC 0.58; 95% CI 0.46, 0.70). At a cut-point of 0.076 maximizing sensitivity and specificity, plasma Aβ_42/40 had a sensitivity of 61.2% and a specificity of 63.6%.

Conclusion:

In this sample, the high-throughput blood Aβ assay was not able to distinguish well between AD patients and controls. Whether or not the assay may be useful in large-scale epidemiological settings remains to be seen.

Platelet biomarkers for a descending cognitive function: A proteomic approach

Memory loss is the most common clinical sign in Alzheimer's disease (AD); thus, searching for peripheral biomarkers to predict cognitive decline is promising for early diagnosis of AD. As platelets share similarities to neuron biology, it may serve as a peripheral matrix for biomarkers of neurological disorders. Here, we conducted a comprehensive and in-depth platelet proteomic analysis using TMT-LC-MS/MS in the populations with mild cognitive impairment (MCI, MMSE = 18-23), severe cognitive impairments (AD, MMSE = 2-17), and the age-/sex-matched normal cognition controls (MMSE = 29-30). A total of 360 differential proteins were detected in MCI and AD patients compared with the controls. These differential proteins were involved in multiple KEGG pathways, including AD, AMP-activated protein kinase (AMPK) pathway, telomerase RNA localization, platelet activation, and complement activation. By correlation analysis with MMSE score, three positively correlated pathways and two negatively correlated pathways were identified to be closely related to cognitive decline in MCI and AD patients. Partial least squares discriminant analysis (PLS-DA) showed that changes of nine proteins, including PHB, UQCRH, CD63, GP1BA, FINC, RAP1A, ITPR1/2, and ADAM10 could effectively distinguish the cognitively impaired patients from the controls. Further machine learning analysis revealed that a combination of four decreased platelet proteins, that is, PHB, UQCRH, GP1BA, and FINC, was most promising for predicting cognitive decline in MCI and AD patients. Taken together, our data provide a set of platelet biomarkers for predicting cognitive decline which may be applied for the early screening of AD.

Neuropsychological Contribution to Predict Conversion to Dementia in Patients with Mild Cognitive Impairment Due to Alzheimer's Disease

BACKGROUND

Diagnosis of Alzheimer's disease (AD) confirmed by biomarkers allows the patient to make important life decisions. However, doubt about the fleetness of symptoms progression and future cognitive decline remains. Neuropsychological measures were extensively studied in prediction of time to conversion to dementia for mild cognitive impairment (MCI) patients in the absence of biomarker information. Similar neuropsychological measures might also be useful to predict the progression to dementia in patients with MCI due to AD.

OBJECTIVE

To study the contribution of neuropsychological measures to predict time to conversion to dementia in patients with MCI due to AD.

METHODS

Patients with MCI due to AD were enrolled from a clinical cohort and the effect of neuropsychological performance on time to conversion to dementia was analyzed.

RESULTS

At baseline, converters scored lower than non-converters at measures of verbal initiative, non-verbal reasoning, and episodic memory. The test of non-verbal reasoning was the only statistically significant predictor in a multivariate Cox regression model. A decrease of one standard deviation was associated with 29% of increase in the risk of conversion to dementia. Approximately 50% of patients with more than one standard deviation below the mean in the z score of that test had converted to dementia after 3 years of follow-up.

CONCLUSION

In MCI due to AD, lower performance in a test of non-verbal reasoning was associated with time to conversion to dementia. This test, that reveals little decline in the earlier phases of AD, appears to convey important information concerning conversion to dementia.

2020 update on the clinical validity of cerebrospinal fluid amyloid, tau, and phospho-tau as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework

Purpose

In the last decade, the research community has focused on defining reliable biomarkers for the early detection of Alzheimer’s disease (AD) pathology. In 2017, the Geneva AD Biomarker Roadmap Initiative adapted a framework for the systematic validation of oncological biomarkers to cerebrospinal fluid (CSF) AD biomarkers—encompassing the 42 amino-acid isoform of amyloid-β (Aβ42), phosphorylated-tau (P-tau), and Total-tau (T-tau)—with the aim to accelerate their development and clinical implementation. The aim of this work is to update the current validation status of CSF AD biomarkers based on the Biomarker Roadmap methodology.

Methods

A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of maturity (fully achieved, partly achieved, preliminary evidence, not achieved, unsuccessful) of CSF AD biomarkers was assessed based on the Biomarker Roadmap methodology before the meeting and presented and discussed during the workshop.

Results

By comparison to the previous 2017 Geneva Roadmap meeting, the primary advances in CSF AD biomarkers have been in the area of a unified protocol for CSF sampling, handling and storage, the introduction of certified reference methods and materials for Aβ42, and the introduction of fully automated assays. Additional advances have occurred in the form of defining thresholds for biomarker positivity and assessing the impact of covariates on their discriminatory ability.

Conclusions

Though much has been achieved for phases one through three, much work remains in phases four (real world performance) and five (assessment of impact/cost). To a large degree, this will depend on the availability of disease-modifying treatments for AD, given these will make accurate and generally available diagnostic tools key to initiate therapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05258-7.

Biomarker counseling, disclosure of diagnosis and follow-up in patients with mild cognitive impairment: A European Alzheimer's disease consortium survey

OBJECTIVES

Mild cognitive impairment (MCI) is associated with an increased risk of further cognitive decline, partly depending on demographics and biomarker status. The aim of the present study was to survey the clinical practices of physicians in terms of biomarker counseling, management, and follow-up in European expert centers diagnosing patients with MCI.

METHODS

An online email survey was distributed to physicians affiliated with European Alzheimer's disease Consortium centers (Northern Europe: 10 centers; Eastern and Central Europe: 9 centers; and Southern Europe: 15 centers) with questions on attitudes toward biomarkers and biomarker counseling in MCI and dementia. This included postbiomarker counseling and the process of diagnostic disclosure of MCI, as well as treatment and follow-up in MCI.

RESULTS

The response rate for the survey was 80.9% (34 of 42 centers) across 20 countries. A large majority of physicians had access to biomarkers and found them useful. Pre- and postbiomarker counseling varied across centers, as did practices for referral to support groups and advice on preventive strategies. Less than half reported discussing driving and advance care planning with patients with MCI.

CONCLUSIONS

The variability in clinical practices across centers calls for better biomarker counseling and better training to improve communication skills. Future initiatives should address the importance of communicating preventive strategies and advance planning.

Use of Cerebrospinal Fluid Biomarkers of Alzheimer's Disease Risk in Mild Cognitive Impairment and Subjective Cognitive Decline in Routine Clinical Care in Germany

BACKGROUND

The National Institute of Aging and Alzheimer's Association's diagnostic recommendations for preclinical Alzheimer's disease (AD) and mild cognitive impairment (MCI) define AD by pathological processes which can be detected by biomarkers. These criteria were established as part of a research framework intended for research purposes but progressively enter the clinical practice.

OBJECTIVE

We investigated the availability, frequency of use, interpretation, and therapeutic implications of biomarkers for the etiologic diagnosis and prognosis in MCI and subjective cognitive decline (SCD) in routine clinical care.

METHODS

We conducted a cross-sectional questionnaire survey among 215 expert dementia centers (hospitals and memory clinics) in Germany.

RESULTS

From the 98 centers (45.6% of contacted centers) included, two-thirds reported use of the cerebrospinal fluid (CSF) biomarkers Aβ42, tau, and phospho-tau in the diagnostic workup of MCI and one third in SCD. CSF biomarker analysis was more often employed by neurological (MCI 84%; SCD 42%) compared to psychiatric institutions (MCI 61%; SCD 33%; p≤0.001). Although dementia experts disagreed on the risk of progression associated with different CSF biomarker constellations, CSF biomarker results guided therapeutic decisions: ∼40% of responders reported to initiate cholinesterase inhibitor therapy in MCI and 18% in SCD (p = 0.006), given that all CSF biomarkers were in the pathological range.

CONCLUSION

Considering the vast heterogeneity among dementia expert centers in use of CSF biomarker analysis, interpretation of results, and therapeutic consequences, a standardization of biomarker-based diagnosis practice in pre-dementia stages is needed.

Management of mild cognitive impairment (MCI): The need for national and international guidelines

Objectives: To review available evidence of pharmacological and non-pharmacological treatment for MCI and analyse information and limitations in national and international guidelines.Methods: Experts from several European countries conducted a qualitative review of the literature on MCI and treatments for MCI, as well as respective chapters in national and international guidelines on dementia/MCI. Psychotherapeutic/psychosocial treatments were excluded from the review.Results: Consensus diagnostic criteria for MCI are available, making early recognition and accurate classification of MCI subtypes possible. MCI can be identified in a primary care setting. Further corroboration and differential diagnosis should be done at specialist level. Mixed pathologies are the rule in MCI, thus a multi-target treatment approach is a rational strategy. Promising evidence has been generated for multi-domain interventions. Limited evidence is available for different pharmacological classes that have been investigated in MCI clinical trials (e.g. acetylcholinesterase inhibitors). EGb 761^® improved symptoms in some clinical trials; it is the only pharmacological treatment recommended in existing guidelines for the symptomatic treatment of MCI.Conclusions: MCI is recognised as an important treatment target and some recent national guidelines have considered symptomatic treatment recommendations for MCI. However, more needs to be done, especially at an international level.

Neuropsychological profile of amyloid-positive versus amyloid-negative amnestic Mild Cognitive Impairment

INTRODUCTION

Patients diagnosed with amnestic mild cognitive impairment (aMCI) are at high risk of progressing to dementia. It became possible, through the use of biomarkers, to diagnose those patients with aMCI who have Alzheimer's disease. However, it is presently unfeasible that all patients undergo biomarker testing. Since neuropsychological testing is required to make a formal diagnosis of aMCI, it would be interesting if it could be used to predict the amyloid status of patients with aMCI.

METHODS

Participants with aMCI, known amyloid status (Aβ+ or Aβ-) and a comprehensive neuropsychological evaluation, were selected from the Cognitive Complaints Cohort database for this study. Neuropsychological tests were compared in Aβ+ and Aβ- aMCI patients. A binary logistic regression analysis was conducted to model the probability of being amyloid positive.

RESULTS

Of the 216 aMCI patients studied, 117 were Aβ+ and 99 were Aβ-. Aβ+ aMCI patients performed worse on several memory tests, namely Word Total Recall, Logical Memory Immediate and Delayed Free Recall, and Verbal Paired Associate Learning, as well as on Trail Making Test B, an executive function test. In a binary logistic regression model, only Logical Memory Delayed Free Recall retained significance, so that for each additional score point in this test, the probability of being amyloid positive decreased by 30.6%. The resulting model correctly classified 64.6% of the aMCI cases regarding their amyloid status.

CONCLUSIONS

The neuropsychological assessment remains an essential step to diagnose and characterize patients with aMCI; however, neuropsychological tests have limited value to distinguish the aMCI patients who have amyloid pathology from those who might suffer from other clinical conditions.

Italian consensus recommendations for a biomarker-based aetiological diagnosis in mild cognitive impairment patients

BACKGROUND AND PURPOSE

Biomarkers support the aetiological diagnosis of neurocognitive disorders in vivo. Incomplete evidence is available to drive clinical decisions; available diagnostic algorithms are generic and not very helpful in clinical practice. The aim was to develop a biomarker-based diagnostic algorithm for mild cognitive impairment patients, leveraging on knowledge from recognized national experts.

METHODS

With a Delphi procedure, experienced clinicians making variable use of biomarkers in clinical practice and representing five Italian scientific societies (neurology - Società Italiana di Neurologia per le Demenze; neuroradiology - Associazione Italiana di Neuroradiologia; biochemistry - Società Italiana di Biochimica Clinica; psychogeriatrics - Associazione Italiana di Psicogeriatria; nuclear medicine - Associazione Italiana di Medicina Nucleare) defined the theoretical framework, relevant literature, the diagnostic issues to be addressed and the diagnostic algorithm. An N-1 majority defined consensus achievement.

RESULTS

The panellists chose the 2011 National Institute on Aging and Alzheimer's Association diagnostic criteria as the reference theoretical framework and defined the algorithm in seven Delphi rounds. The algorithm includes baseline clinical and cognitive assessment, blood examination, and magnetic resonance imaging with exclusionary and inclusionary roles; dopamine transporter single-photon emission computed tomography (if no/unclear parkinsonism) or metaiodobenzylguanidine cardiac scintigraphy for suspected dementia with Lewy bodies with clear parkinsonism (round VII, votes (yes-no-abstained): 3-1-1); 18 F-fluorodeoxyglucose positron emission tomography for suspected frontotemporal lobar degeneration and low diagnostic confidence of Alzheimer's disease (round VII, 4-0-1); cerebrospinal fluid for suspected Alzheimer's disease (round IV, 4-1-0); and amyloid positron emission tomography if cerebrospinal fluid was not possible/accepted (round V, 4-1-0) or inconclusive (round VI, 5-0-0).

CONCLUSIONS

These consensus recommendations can guide clinicians in the biomarker-based aetiological diagnosis of mild cognitive impairment, whilst guidelines cannot be defined with evidence-to-decision procedures due to incomplete evidence.

Clinicians' communication with patients receiving a MCI diagnosis: The ABIDE project

BACKGROUND

We aimed to explore clinicians' communication, including the discussion of diagnosis, cause, prognosis and care planning, in routine post-diagnostic testing consultations with patients with Mild Cognitive Impairment (MCI).

METHODS

Thematic content analysis was used to analyze audiotaped consultations in which 10 clinicians (eight neurologists and two geriatricians) from 7 memory clinics, disclosed diagnostic information to 13 MCI patients and their care partners. We assessed clinician-patient communication regarding diagnostic label, cause, prognosis and care planning to identify core findings.

RESULTS

Core findings were: clinicians 1) differed in how they informed about the MCI label; 2) tentatively addressed cause of symptoms; 3) (implicitly) steered against further biomarker testing; 4) rarely informed about the patient's risk of developing dementia; 5) often informed about the expected course of symptoms emphasizing potential symptom stabilization and/or improvement, and; 6) did not engage in a conversation on long-term (care) planning.

DISCUSSION

Clinicians' information provision about the underlying cause, prognosis and implications for long-term (care) planning in MCI could be more specific. Since most patients and care partners have a strong need to understand the patient's symptoms, and for information on the prognosis and implications for the future, clinicians' current approach may not match with those needs.

Non-Phosphorylated Tau in Cerebrospinal Fluid is a Marker of Alzheimer's Disease Continuum in Young Urbanites Exposed to Air Pollution

Long-term exposure to fine particulate matter (PM2.5) and ozone (O3) above USEPA standards is associated with Alzheimer's disease (AD) risk. Metropolitan Mexico City (MMC) children exhibit subcortical pretangles in infancy and cortical tau pre-tangles, NFTs, and amyloid phases 1-2 by the 2nd decade. Given their AD continuum, we measured in 507 normal cerebrospinal fluid (CSF) samples (MMC 354, controls 153, 12.82±6.73 y), a high affinity monoclonal non-phosphorylated tau antibody (non-P-Tau), as a potential biomarker of AD and axonal damage. In 81 samples, we also measured total tau (T-Tau), tau phosphorylated at threonine 181 (P-Tau), amyloid-β1-42, BDNF, and vitamin D. We documented by electron microscopy myelinated axonal size and the pathology associated with combustion-derived nanoparticles (CDNPs) in anterior cingulate cortex white matter in 6 young residents (16.25±3.34 y). Non-P-Tau showed a strong increase with age significantly faster among MMC versus controls (p = 0.0055). Aβ1 - 42 and BDNF concentrations were lower in MMC children (p = 0.002 and 0.03, respectively). Anterior cingulate cortex showed a significant decrease (p = <0.0001) in the average axonal size and CDNPs were associated with organelle pathology. Significant age increases in non-P-Tau support tau changes early in a population with axonal pathology and evolving AD hallmarks in the first two decades of life. Non-P-Tau is an early biomarker of axonal damage and potentially valuable to monitor progressive longitudinal changes along with AD multianalyte classical CSF markers. Neuroprotection of young urbanites with PM2.5 and CDNPs exposures ought to be a public health priority to halt the development of AD in the first two decades of life.

Potential Fluid Biomarkers for the Diagnosis of Mild Cognitive Impairment

Mild cognitive impairment (MCI) is characterized by a level of cognitive impairment that is lower than normal for a person’s age, but a higher function than that that observed in a demented person. MCI represents a transitional state between normal aging and dementia disorders, especially Alzheimer’s disease (AD). Much effort has been made towards determining the prognosis of a person with MCI who will convert to AD. It is now clear that cerebrospinal fluid (CSF) levels of Aβ40, Aβ42, total tau and phosphorylated tau are useful for predicting the risk of progression from MCI to AD. This review highlights the advantages of the current blood-based biomarkers in MCI, and discusses some of these challenges, with an emphasis on recent studies to provide an overview of the current state of MCI.

Use of mild cognitive impairment and prodromal AD/MCI due to AD in clinical care: a European survey

Introduction

The diagnosis of mild cognitive impairment (MCI) refers to cognitive impairment not meeting dementia criteria. A survey among members of the American Association of Neurology (AAN) showed that MCI was considered a useful diagnosis. Recently, research criteria have been proposed for the diagnosis of Alzheimer’s disease (AD) in MCI based on AD biomarkers (prodromal AD/MCI due to AD). The aim of this study was to investigate the attitudes of clinicians in Europe on the clinical utility of MCI and prodromal AD/MCI due to AD criteria. We also investigated whether the prodromal AD/MCI due to AD criteria impacted management of MCI patients.

Methods

An online survey was performed in 2015 among 102 members of the European Academy of Neurology (EAN) and the European Alzheimer’s Disease Consortium (EADC). Questions were asked on how often criteria were used, how they were operationalized, how they changed patient management, and what were considered advantages and limitations of MCI and prodromal AD/MCI due to AD. The questionnaire consisted of 47 questions scored on a Likert scale.

Results

Almost all respondents (92%) used the MCI diagnosis in clinical practice. Over 80% of the EAN/EADC respondents found a MCI diagnosis useful because it helped to label the cognitive problem, involve patients in planning for the future, and start risk reduction activities. These findings were similar to those reported in the AAN survey. Research criteria for prodromal AD/MCI due to AD were used by 68% of the EAN/EADC respondents. The most common reasons to use the criteria were increased certainty of diagnosis (86%), increased possibilities to provide counseling (51%), facilitation of follow-up planning (48%), start of medical intervention (49%), and response to patients’ wish for a diagnosis (41%). Over 70% of the physicians considered that a diagnosis of prodromal AD/MCI due to AD had an added value over the MCI diagnosis.

Conclusions

The diagnostic criteria of MCI and prodromal AD/MCI due to AD are commonly used among EAN/EADC members. The prodromal AD/MCI due to AD were considered clinically useful and impacted patient management and communication.

Electronic supplementary material

The online version of this article (10.1186/s13195-019-0525-9) contains supplementary material, which is available to authorized users.

Innovative Biomarkers for Alzheimer's Disease: Focus on the Hidden Disease Biomarkers

The criteria for the clinical diagnosis of AD include the analysis of biomarkers of the underlying brain disease pathology; a set of cerebrospinal fluid (CSF) tests, amyloid-β1-42 (Aβ42), total-tau (t-tau), and phosphorylated tau (p-tau), are available and their performance in a clinical setting has been assessed in several studies. Thus, in dementia research, great advances have been made in the discovery of putative biomarkers; however, disappointingly, few of them have been translated into clinically applicable assays. To find biomarkers able to reliably detect AD pathology already at prodromal stages and in blood is even more important. Recent technical breakthroughs have provided ultrasensitive methods that allow the detection of brain-specific proteins in blood. In the present review, we will focus on the usefulness of ultrasensitive technologies for biomarker discovery and trace elements detection; moreover, we will review studies on circulating nano-compartments, a promising novel source of material for molecular diagnostics.

Prediction and Early Detection of Alzheimer's Dementia: Professional Disclosure Practices and Ethical Attitudes

BACKGROUND

Biomarker-supported testing for preclinical and prodromal Alzheimer's disease (AD) finds its way into clinical practice. Professional attitudes and practices regarding disclosure and ethical issues are controversial in many countries.

OBJECTIVES

Against this background, the objective was to survey the actual practice and the attitudes of physicians in German hospitals and memory clinics in order to explore possible practical insecurities and ethical concerns.

METHODS

A detailed survey with 37 items was conducted among medical professionals at German hospitals and memory clinics (n = 108). Analyses were performed using SPSS 21.0 (IBM). Findings were based on frequency and percentage distribution.

RESULTS

Nearly half of the respondents stated that persons with mild cognitive impairment and pathological cerebrospinal fluid biomarkers were informed they had or would soon develop AD. While 81% acknowledged a 'right not to know', 75% said that results were always communicated. A majority agreed there was a benefit of prediction or later life planning [end-of-life, financial, family, housing (73-75%)] but also expected high psychological stress (82%) and self-stigmatization (70%) for those tested.

CONCLUSIONS

There is considerable heterogeneity and insecurity regarding prediction and early detection in the context of AD in Germany. Information of professionals and standardization of professional testing and disclosure practices are needed.

Physician Practice Patterns Associated with Diagnostic Evaluation of Patients with Suspected Mild Cognitive Impairment and Alzheimer's Disease

The diagnostic process for patients presenting with cognitive decline and suspected dementia is complex. Physicians face challenges distinguishing between normal aging, mild cognitive impairment, Alzheimer's disease, and other dementias. Although there is some evidence for improving attitudes towards the importance of prompt diagnosis, there is limited information describing how physicians approach this diagnostic challenge in practice. This was explored in the present study. Across-sectional survey of primary care and specialist physicians, in 5 European countries, Canada, and the United States, was conducted. Participants were asked about their use of cognitive screening tools and diagnostic technologies, as well as the rationales and barriers for use. In total, 1365 physicians participated in the survey, 63% of whom were specialists. Most physicians stated they use objective cognitive tools to aid the early detection of suspected mild cognitive impairment or Alzheimer's disease in patients. The Mini-Mental State Examination was the most common tool used for initial screening; respondents cited speed and ease of use but noted its lack of specificity. Cerebrospinal fluid biomarker and amyloid positron emission tomography tests, respectively, had been used by only 26% and 32% of physicians in the preceding 6 months, although patterns of use varied across countries. The most commonly cited reasons for not ordering such tests were invasiveness (for cerebrospinal fluid biomarker testing) and cost (for amyloid positron emission tomography imaging). Data reported by physicians reveal differences in the approaches to the diagnostics process in Alzheimer's. A higher proportion of primary care physicians in the United States are routinely incorporating cognitive assessment tools into annual visits, but this is due to country differences in clinical practice. The value of screening tools and regular use could be discussed further with physicians; however, lack of specificity associated with cognitive tools and the investment required from patients and the healthcare system are limiting factors.

AMYPAD Diagnostic and Patient Management Study: Rationale and design

INTRODUCTION

Reimbursement of amyloid-positron emission tomography (PET) is lagging due to the lack of definitive evidence on its clinical utility and cost-effectiveness. The Amyloid Imaging to Prevent Alzheimer's Disease-Diagnostic and Patient Management Study (AMYPAD-DPMS) is designed to fill this gap.

METHODS

AMYPAD-DPMS is a phase 4, multicenter, prospective, randomized controlled study. Nine hundred patients with subjective cognitive decline plus, mild cognitive impairment, and dementia possibly due to Alzheimer's disease will be randomized to ARM1, amyloid-PET performed early in the diagnostic workup; ARM2, amyloid-PET performed after 8 months; and ARM3, amyloid-PET performed whenever the physician chooses to do so.

ENDPOINTS

The primary endpoint is the difference between ARM1 and ARM2 in the proportion of patients receiving a very-high-confidence etiologic diagnosis after 3 months. Secondary endpoints address diagnosis and diagnostic confidence, diagnostic/therapeutic management, health economics and patient-related outcomes, and methods for image quantitation.

EXPECTED IMPACTS

AMYPAD-DPMS will supply physicians and health care payers with real-world data to plan management decisions.

Biomarkers study in atypical dementia: proof of a diagnostic work-up

BACKGROUND

An early differentiation between Alzheimer's Disease (AD) and other dementias is crucial for an adequate patients' management, albeit it may result difficult for the occurrence of "atypical presentations." Current diagnostic criteria recognize the importance of biomarkers for AD diagnosis, but still an optimal diagnostic work-up isn't available.

OBJECTIVE

Evaluate the utility and reproducibility of biomarkers and propose an "optimal" diagnostic work-up in atypical dementia.

METHODS

(1) a retrospective selection of "atypical dementia cases"; (2) a repetition of diagnostic assessment by two neurologists following two different diagnostic work-ups, each consisting of multiple steps; (3) a comparison between diagnostic accuracy and confidence reached at each step by both neurologists and evaluation of the inter-rater agreement.

RESULTS

In AD, regardless of the undertaken diagnostic work-up, a significant gain in accuracy was reached by both neurologists after the second step, whereas in frontotemporal dementia (FTD), adding subsequent steps was not always sufficient to increase significantly the baseline accuracy. A relevant increment in diagnostic confidence was detectable after studying pathophysiological markers in AD, and after assessing brain metabolism in FTD. The inter-rater agreement was higher at the second step for the AD group when the pathophysiological markers were available and for the FTD group when the results of FDG-PET were accessible.

CONCLUSIONS

In atypical cases of dementia, biomarkers significantly raise diagnostic accuracy, confidence, and agreement. This study introduces a proof of diagnostic work-up that combines imaging and CSF biomarkers and suggests distinct ways to proceed on the basis of a greater diagnostic likelihood.

The Clinical Use of Cerebrospinal Fluid Biomarkers for Alzheimer's Disease Diagnosis: The Italian Selfie

Although the use of cerebrospinal fluid (CSF) amyloid β1-42 (Aβ42), tau (T-tau), and phosphorylated tau (p-tau181) gives added diagnostic and prognostic values, the diffusion is still limited in clinical practice and only a restricted number of patients receive an integrated clinico-biological diagnosis. By a survey, we aimed to do a "selfie" of the use and diffusion of CSF biomarkers of dementia in Italy, the standardization of pre-analytical procedures, the harmonization of ranges, and the participation to Quality Control programs. An online questionnaire was sent to the members of SIBioC and SINdem-ITALPLANED and to main neurological clinics all over Italy. In Italy, 25 laboratories provide biomarkers analysis in addition to a network of 15 neighboring hospitals. In sum, 40 neurological centers require CSF analyses. 7/20 regions (35%) lack CSF laboratories. Standardization of pre-analytical procedures is present in 62.02% of the laboratories; only 56.00% of the laboratories participate in International Quality Control. There is no harmonization of cut-offs. In Italy, the use of CSF biomarkers is still limited in clinical practice. Standardization and harmonization of normal ranges are needed. To optimize and expand the use of CSF biomarkers, a cost-benefit analysis should be promoted by scientific societies and national health services.

Cerebrospinal Fluid Biomarkers in Highly Exposed PM2.5 Urbanites: The Risk of Alzheimer's and Parkinson's Diseases in Young Mexico City Residents

Exposure to fine particulate matter (PM2.5) and ozone (O3) above US EPA standards is associated with Alzheimer's disease (AD) risk, while Mn toxicity induces parkinsonism. Mexico City Metropolitan Area (MCMA) children have pre- and postnatal sustained and high exposures to PM2.5, O3, polycyclic aromatic hydrocarbons, and metals. Young MCMA residents exhibit frontal tau hyperphosphorylation and amyloid-β (Aβ)1 - 42 diffuse plaques, and aggregated and hyperphosphorylated α-synuclein in olfactory nerves and key brainstem nuclei. We measured total prion protein (TPrP), total tau (T-tau), tau phosphorylated at threonine 181 (P-Tau), Aβ1-42, α-synuclein (t-α-syn and d-α-synuclein), BDNF, insulin, leptin, and/or inflammatory mediators, in 129 normal CSF samples from MCMA and clean air controls. Aβ1-42 and BDNF concentrations were significantly lower in MCMA children versus controls (p = 0.005 and 0.02, respectively). TPrP increased with cumulative PM2.5 up to 5 μg/m3 and then decreased, regardless of cumulative value or age (R2 = 0.56). TPrP strongly correlated with T-Tau and P-Tau, while d-α-synuclein showed a significant correlation with TNFα, IL10, and IL6 in MCMA children. Total synuclein showed an increment in childhood years related to cumulated PM2.5, followed by a decrease after age 12 years (R2 = 0.47), while d-α-synuclein exhibited a tendency to increase with cumulated PM2.5 (R2 = 0.30). CSF Aβ1-42, BDNF, α-synuclein, and TPrP changes are evolving in young MCMA urbanites historically showing underperformance in cognitive processes, odor identification deficits, downregulation of frontal cellular PrP, and neuropathological AD and PD hallmarks. Neuroprotection of young MCMA residents ought to be a public health priority.

Update on Vascular Cognitive Impairment Associated with Subcortical Small-Vessel Disease

Subcortical small-vessel disease (SSVD) is a disorder well characterized from the clinical, imaging, and neuropathological viewpoints. SSVD is considered the most prevalent ischemic brain disorder, increasing in frequency with age. Vascular risk factors include hypertension, diabetes, hyperlipidemia, elevated homocysteine, and obstructive sleep apnea. Ischemic white matter lesions are the hallmark of SSVD; other pathological lesions include arteriolosclerosis, dilatation of perivascular spaces, venous collagenosis, cerebral amyloid angiopathy, microbleeds, microinfarcts, lacunes, and large infarcts. The pathogenesis of SSVD is incompletely understood but includes endothelial changes and blood-brain barrier alterations involving metalloproteinases, vascular endothelial growth factors, angiotensin II, mindin/spondin, and the mammalian target of rapamycin pathway. Metabolic and genetic conditions may also play a role but hitherto there are few conclusive studies. Clinical diagnosis of SSVD includes early executive dysfunction manifested by impaired capacity to use complex information, to formulate strategies, and to exercise self-control. In comparison with Alzheimer's disease (AD), patients with SSVD show less pronounced episodic memory deficits. Brain imaging has advanced substantially the diagnostic tools for SSVD. With the exception of cortical microinfarcts, all other lesions are well visualized with MRI. Diagnostic biomarkers that separate AD from SSVD include reduction of cerebrospinal fluid amyloid-β (Aβ)42 and of the ratio Aβ42/Aβ40 often with increased total tau levels. However, better markers of small-vessel function of intracerebral blood vessels are needed. The treatment of SSVD remains unsatisfactory other than control of vascular risk factors. There is an urgent need of finding targets to slow down and potentially halt the progression of this prevalent, but often unrecognized, disorder.

The impact of automated hippocampal volumetry on diagnostic confidence in patients with suspected Alzheimer's disease: A European Alzheimer's Disease Consortium study

INTRODUCTION

Hippocampal volume is a core biomarker of Alzheimer's disease (AD). However, its contribution over the standard diagnostic workup is unclear.

METHODS

Three hundred fifty-six patients, under clinical evaluation for cognitive impairment, with suspected AD and Mini-Mental State Examination ≥20, were recruited across 17 European memory clinics. After the traditional diagnostic workup, diagnostic confidence of AD pathology (DCAD) was estimated by the physicians in charge. The latter were provided with the results of automated hippocampal volumetry in standardized format and DCAD was reassessed.

RESULTS

An increment of one interquartile range in hippocampal volume was associated with a mean change of DCAD of -8.0% (95% credible interval: [-11.5, -5.0]). Automated hippocampal volumetry showed a statistically significant impact on DCAD beyond the contributions of neuropsychology, ¹⁸F-fluorodeoxyglucose positron emission tomography/single-photon emission computed tomography, and cerebrospinal fluid markers (-8.5, CrI: [-11.5, -5.6]; -14.1, CrI: [-19.3, -8.8]; -10.6, CrI: [-14.6, -6.1], respectively).

DISCUSSION

There is a measurable effect of hippocampal volume on DCAD even when used on top of the traditional diagnostic workup.

Unbiased estimates of cerebrospinal fluid β-amyloid 1-42 cutoffs in a large memory clinic population

Background

We sought to define a cutoff for β-amyloid 1–42 in cerebrospinal fluid (CSF), a key marker for Alzheimer’s disease (AD), with data-driven Gaussian mixture modeling in a memory clinic population.

Methods

We performed a combined cross-sectional and prospective cohort study. We selected 2462 subjects with subjective cognitive decline, mild cognitive impairment, AD-type dementia, and dementia other than AD from the Amsterdam Dementia Cohort. We defined CSF β-amyloid 1–42 cutoffs by data-driven Gaussian mixture modeling in the total population and in subgroups based on clinical diagnosis, age, and apolipoprotein E (APOE) genotype. We investigated whether abnormal β-amyloid 1–42 as defined by the data-driven cutoff could better predict progression to AD-type dementia than abnormal β-amyloid 1–42 defined by a clinical diagnosis-based cutoff using Cox proportional hazards regression.

Results

In the total group of patients, we found a cutoff for abnormal CSF β-amyloid 1–42 of 680 pg/ml (95% CI 660–705 pg/ml). Similar cutoffs were found within diagnostic and APOE genotype subgroups. The cutoff was higher in elderly subjects than in younger subjects. The data-driven cutoff was higher than our clinical diagnosis-based cutoff and had a better predictive accuracy for progression to AD-type dementia in nondemented subjects (HR 7.6 versus 5.2, p < 0.01).

Conclusions

Mixture modeling is a robust method to determine cutoffs for CSF β-amyloid 1–42. It might better capture biological changes that are related to AD than cutoffs based on clinical diagnosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13195-016-0233-7) contains supplementary material, which is available to authorized users.

Does Caffeine Consumption Modify Cerebrospinal Fluid Amyloid-β Levels in Patients with Alzheimer's Disease?

Caffeine may be protective against Alzheimer's disease (AD) by modulating amyloid-β (Aβ) metabolic pathways. The present work aimed to study a possible association of caffeine consumption with the cerebrospinal fluid (CSF) biomarkers, particularly Aβ. The study included 88 patients with AD or mild cognitive impairment. The consumption of caffeine and theobromine was evaluated using a validated food questionnaire. Quantification of caffeine and main active metabolites was performed with liquid chromatography coupled to tandem mass spectrometry. The levels of A(1-42), total tau, and phosphorylated tau in the CSF were determined using sandwich ELISA methods and other Aβ species, Aβ(X-38), Aβ(X-40), and Aβ(X-42), with the MSD Aβ Triplex assay. The concentration of caffeine was 0.79±1.15 μg/mL in the CSF and 1.20±1.88 μg/mL in the plasma. No correlation was found between caffeine consumption and Aβ42 in the CSF. However, a significant positive correlation was found between the concentrations of theobromine, both in the CSF and in the plasma, with Aβ42 in the CSF. Theobromine in the CSF was positively correlated with the levels of other xanthines in the CSF, but not in the plasma, suggesting that it may be formed by central metabolic pathways. In conclusion, caffeine consumption does not modify the levels of CSF biomarkers, and does not require to be controlled for when measuring CSF biomarkers in a clinical setting. Since theobromine is associated with a favorable Aβ profile in the CSF, the possibility that it might have a protective role in AD should be further investigated.

Critical Comparison of Different Biomarkers for Alzheimer's Disease in a Clinical Setting

BACKGROUND

Biomarkers of neuronal injury and amyloid pathology play a pivotal role in the diagnosis of Alzheimer's disease (AD). The degree of AD biomarker congruence is still unclear in clinical practice.

OBJECTIVE

Diagnosis of AD with regard to the congruence of the clinical diagnosis and different biomarkers.

METHODS

In this prospective cross-sectional observational study, 54 patients with mild cognitive impairment or dementia due to AD or not due to AD were investigated. Biomarkers of neuronal injury were medial temporal lobe atrophy (MTA) on magnetic resonance imaging (MRI) and tau concentration in the cerebrospinal fluid (CSF). CSF Aβ(1-42) and amyloid-targeting positron emission tomography (PET) were considered as biomarkers of amyloid pathology.

RESULTS

Forty cases were diagnosed as AD and 14 cases were diagnosed as non-AD based on clinical and routine MRI assessment. AD cases had higher MTA scores, higher levels of CSF tau and lower levels of CSF Aβ(1- 42), and higher amyloid load on PET compared to the non-AD group. In the AD group, completely consistently pathological biomarkers were found in 32.5% , non-pathological in 5% . In 62.5% the findings were inconsistent. Congruence of biomarkers was 67.5% for neuronal injury and for amyloid dysfunction, respectively. In two patients, clinical diagnosis switched to non-AD due to completely consistent non-pathological biomarker findings. The criteria of the international working group were met in 75.0% .

CONCLUSION

Surprisingly, the number of completely congruent biomarkers was relatively low. Interpretation of AD biomarkers is complicated by multiple biomarker constellations. However, the level of biomarker consistency required to reliably diagnose AD remains uncertain.

"New Old Pathologies": AD, PART, and Cerebral Age-Related TDP-43 With Sclerosis (CARTS)

The pathology-based classification of Alzheimer's disease (AD) and other neurodegenerative diseases is a work in progress that is important for both clinicians and basic scientists. Analyses of large autopsy series, biomarker studies, and genomics analyses have provided important insights about AD and shed light on previously unrecognized conditions, enabling a deeper understanding of neurodegenerative diseases in general. After demonstrating the importance of correct disease classification for AD and primary age-related tauopathy, we emphasize the public health impact of an underappreciated AD "mimic," which has been termed "hippocampal sclerosis of aging" or "hippocampal sclerosis dementia." This pathology affects >20% of individuals older than 85 years and is strongly associated with cognitive impairment. In this review, we provide an overview of current hypotheses about how genetic risk factors (GRN, TMEM106B, ABCC9, and KCNMB2), and other pathogenetic influences contribute to TDP-43 pathology and hippocampal sclerosis. Because hippocampal sclerosis of aging affects the "oldest-old" with arteriolosclerosis and TDP-43 pathologies that extend well beyond the hippocampus, more appropriate terminology for this disease is required. We recommend "cerebral age-related TDP-43 and sclerosis" (CARTS). A detailed case report is presented, which includes neuroimaging and longitudinal neurocognitive data. Finally, we suggest a neuropathology-based diagnostic rubric for CARTS.