Recommendations for cerebrospinal fluid Alzheimer's disease biomarkers in the diagnostic evaluation of mild cognitive impairment

Lateralization of the Aberrant Amplitude of Low-Frequency Fluctuation within the Default Mode Network in Patients with Mild Cognitive Impairment

RATIONALE AND OBJECTIVES

Alzheimer's disease (AD) is the most common pathogenesis of dementia, and mild cognitive impairment (MCI) is considered as the intermediate stage from normal elderly to AD. Early detection of MCI is an essential step for the timely intervention of AD to slow the progression of this disease. Different form previous studies in the whole-brain spontaneous activities, this research aimed to explore the low-frequency amplitude spectrum activities of patients with MCI within the default mode network (DMN), which has been involved in the process of maintaining normal cognitive function.

MATERIALS AND METHODS

Based on resting-state functional magnetic resonance imaging, the amplitude of low-frequency fluctuation (ALFF) was used to analyze alterations in brain regions. The Mini-Mental State Examination and Montreal Cognitive Assessment were used for cognitive assessments. The correlation between imaging and behavioral results was analyzed among patients with MCI (n=36) and normal controls (n=26).

RESULTS

The DMN is the highest coverage of brain network regarding changes in local brain activity in patients with MCI. And the MCI group showed significant aberrant lateralization of the ALFF value.

CONCLUSION

The current results of our study has confirmed the hypothesis of cerebral functional impairment and compensation, and suggests that functional changes in the brain regions with reduced values of the ALFF occurred earlier than those with increased values. In a word, it suggested that the aberrant spontaneous brain activity in the DMN might be a specific imaging marker for improving MCI diagnoses.

Altered tear fluid protein expression in persons with mild Alzheimer's disease in proteins involved in oxidative stress, protein synthesis, and energy metabolism

BackgroundTear fluid (TF) is a protein-rich solution that reflects pathophysiological changes in Alzheimer's disease (AD).ObjectiveIn this study, we examined whether TF proteins were differently expressed in persons with mild AD dementia compared to cognitively healthy controls (CO).MethodsWe analyzed data from 53 study participants including 34 CO (mean age, 71 years; Mini-Mental State Examination [MMSE] score, 28.9 ± 1.4), and 19 patients with AD (Clinical Dementia Rating, 0.5-1; mean age, 72 years; MMSE score, 23.8 ± 2.8). All participants underwent cognitive testing, as well as neurological and ophthalmological examinations. TF was collected using Schirmer strips, and TF protein content was evaluated using mass spectrometry-based proteomics and label-free quantification.ResultsWe found that 16 proteins exhibited significantly upregulated expression in the AD group compared to the CO group (p ≤ 0.05). These proteins were NP1L4, BBOX1, CYTC, RNAS4, PCD, RNT2, AL1A3, SYSC, TPIS, CLH1, PGAM1, EIF3L, 5NTC, HNRNPA2B1, PYGL, and ERO1α. No proteins were significantly downregulated in the AD group compared to the CO group.ConclusionsOur results support the hypothesis that TF is a potential source of biomarkers for AD. Part of those proteins with altered expression have previously linked to increased oxidative stress, changed protein synthesis, and disturbed regulation of energy metabolism related to AD or neurodegenerative disease. The present results indicate the value of continued investigation of TF proteins in AD.

A Speech-Based Mobile Screening Tool for Mild Cognitive Impairment: Technical Performance and User Engagement Evaluation

Traditional screening methods for Mild Cognitive Impairment (MCI) face limitations in accessibility and scalability. To address this, we developed and validated a speech-based automatic screening app implementing three speech-language tasks with user-centered design and server-client architecture. The app integrates automated speech processing and SVM classifiers for MCI detection. Functionality validation included comparison with manual assessment and testing in real-world settings (n = 12), with user engagement evaluated separately (n = 22). The app showed comparable performance with manual assessment (F1 = 0.93 vs. 0.95) and maintained reliability in real-world settings (F1 = 0.86). Task engagement significantly influenced speech patterns: users rating tasks as "most interesting" produced more speech content (p < 0.05), though behavioral observations showed consistent cognitive processing across perception groups. User engagement analysis revealed high technology acceptance (86%) across educational backgrounds, with daily cognitive exercise habits significantly predicting task benefit perception (H = 9.385, p < 0.01). Notably, perceived task difficulty showed no significant correlation with cognitive performance (p = 0.119), suggesting the system's accessibility to users of varying abilities. While preliminary, the mobile app demonstrated both robust assessment capabilities and sustained user engagement, suggesting the potential viability of widespread cognitive screening in the geriatric population.

Facing the new diagnostic and treatment options of Alzheimer's disease: The necessity of informed consent

With advances in biomarker-based detection of Alzheimer's disease (AD) and new treatment options with disease-modifying treatments (DMTs), we are heading toward a new conceptualization of diagnostics and therapy in the early stages of AD. Yet consensus guidelines on best clinical practices in predictive AD diagnostics are still developing. Currently, there is a knowledge gap regarding counseling and disclosure practices in early symptomatic disease stages, its implications for dementia risk estimation, and DMTs with associated risks and benefits. The crucial feature is the capacity of patients with (mild) cognitive impairment, eligible for DMTs, to consent. This perspective aims to (1) discuss the current challenges in assessing capacity to consent and (2) highlight the importance of a supported (informed) decision-making process. Measures to facilitate informed decision-making of patients constitute an ethical approach to enhancing the quality of care in this evolving therapeutic landscape. HIGHLIGHTS: This perspective: Explores biomarker-based early symptomatic AD detection and the implications for patient care. Emphasizes supported decision-making in DMTs for MCI and dementia patients. Discusses the need for standardized tools to assess the capacity to consent. Aligns diagnostic and treatment approaches with ethical care standards. Enhances patient autonomy in the evolving AD therapeutic landscape.

Counseling and disclosure practices in predictive Alzheimer's disease diagnostics: A scoping review

New possibilities of biomarker-based predictive technologies for Alzheimer's disease (AD) have become more reliable as well as more accessible. Standardized clinical recommendations and guidance for counseling and disclosure in this context are not yet well developed. Our scoping review identified publications from database searches in PubMed, PsycINFO, LIVIVO, and Web of Science. Inclusion criteria were: (1) information or counseling, (2) biomarkers and a type of cognitive impairment or AD, and (3) published between 2005 and 2024. We identified 63 articles and synthesized them along the categories of staged information provision: pre-test counseling, disclosure, and post-disclosure follow-up. Most publications referred to the context of disclosure (48), followed by pre-test counseling (33), and post-disclosure follow-up (31). Some publications referred to all stages of counseling (17). Our findings highlight the need to further develop and specify comprehensive and standardized guidelines for counseling, disclosure, and post-disclosure follow-up in the context of AD biomarker testing. HIGHLIGHTS: New possibilities of biomarker-based predictive technologies for Alzheimer's disease (AD) have become more reliable and also more accessible. However, clinical recommendations and guidance for counseling and disclosure in the context of AD biomarker testing are currently not well developed. We carried out a scoping review with the aim to generate an overview of the scientific literature and guidance available regarding counseling, biomarker test result and dementia risk disclosure, and clinical management prior to and in the course of a biomarker-based diagnosis in early stages of AD. We identified 63 relevant articles. Most publications referred to the context of disclosure (48), followed by pre-test counseling (33), and post-disclosure follow-up (31). Some publications referred to all stages of counseling (17). Our findings highlight the urgent need for national and international consensus guidelines for comprehensive and staged counseling and disclosure practices. While most publications identify relevant ethical challenges posed for counseling practices in the context of AD biomarker testing, they rarely present any practical recommendations for clinicians, on how and what to counsel on a concrete level.

Cognitive Intra-individual Variability in Cognitively Healthy APOE ε4 Carriers, Mild Cognitive Impairment, and Alzheimer's Disease: a Meta-analysis

Intra-individual variability (IIV) quantifies an individual's scatter in performances across a test battery (dispersion) or across reaction times within a single task (consistency). No studies have meta-analyzed the cross-sectional IIV literature in those with mild cognitive impairment (MCI) and Alzheimer's dementia (AD). An additional aim of this meta-analysis was to examine IIV in APOE ε4 + healthy control (HC) samples. A systematic search strategy was applied to six databases (Academic Search Complete, PsycINFO, MEDLINE, CINAHL Complete, ERIC, and ProQuest Dissertations & Theses) to identify studies comparing the extent of dispersion- and consistency-based cognitive IIV between clinical (MCI, AD) and HC samples. Thirty-five studies met the inclusion criteria for our random-effects cross-sectional meta-analysis. Hedges' g was used to aggregate between-group effect sizes, with higher positive values indicating clinical > HC IIV. Meta-regression and subgroup-analyses were conducted to evaluate continuous and categorical moderator variables, respectively. Omnibus models yielded analogous moderate-strength, albeit heterogeneous, effects for dispersion and consistency (g = 0.65). Clinical severity was a robust moderator of dispersion (MCI = 0.47, AD = 1.16) and consistency (MCI = 0.51, AD = 1.31) effects. Supplemental analysis of APOE ε4 status in HCs revealed a nonsignificant trend of elevated overall (i.e., dispersion + consistency) IIV in APOE ε4 + vs. APOE ε4 - HC samples (g = 0.24). Cognitive IIV is sensitive to the presence of AD-related genetic risk as well as neurocognitive impairment across the neurocognitive disorder severity spectrum, with a graded-pattern of HC < MCI < AD samples.

Psychological outcomes of dementia risk estimation in MCI patients: Results from the PreDADQoL project

INTRODUCTION

Understanding the impact of biomarker-based dementia risk estimation in people with mild cognitive impairment (MCI) and their care partners is critical for patient care.

METHODS

MCI patients and study partners were counseled on Alzheimer's disease (AD) biomarker and dementia risk was disclosed. Data on mood, quality of life (QoL), and satisfaction with life (SwL) were obtained 1 week and 3 months after disclosure.

RESULTS

Seventy-five dyads were enrolled, and two-thirds of the patients opted for biomarker testing. None of the participants experienced clinically relevant depression or anxiety after disclosure. All dyads reported moderate to high QoL and SwL throughout the study. Patients reported more subthreshold depressive symptoms 1 week and lower QoL and SwL 3 months after disclosure. In patients, depression (odds ratio [OR]: 0.76) and anxiety (OR: 0.81) were significant predictors for the decision against biomarker testing.

DISCUSSION

No major psychological harm is to be expected in MCI patients and care partners after dementia risk disclosure.

TRIAL REGISTRATION

This study is registered in the German clinical trials register (Deutsches Register Klinischer Studien, DRKS): http://www.drks.de/DRKS00011155, DRKS registration number: DRKS00011155, date of registration: 18.08.2017.

HIGHLIGHTS

Patients with mild cognitive impairment (MCI) and study partners were counseled on Alzheimer's disease (AD) biomarker-based dementia risk estimation. About two-thirds of patients opted for biomarker testing and received their dementia risk based on their AD biomarker status. Patients who decided in favor or against CSF biomarker testing differed in psychological features. We did not observe major psychological harm after the dementia risk disclosure. Coping strategies were associated with better subsequent mood and well-being in all participants.

Mild cognitive impairment detection from facial video interviews by applying spatial-to-temporal attention module

Early detection of Mild Cognitive Impairment (MCI) leads to early interventions to slow the progression from MCI into dementia. Deep Learning (DL) algorithms could help achieve early non-invasive and low-cost detection of MCI. This paper presents the detection of MCI in older adults using DL models based only on facial features extracted from video-recorded conversations at home. We used the data collected from the I-CONECT behavioral intervention study (NCT02871921), where several sessions of semi-structured interviews between socially isolated older individuals and interviewers were video recorded. We develop a framework that extracts holistic spatial facial features using a convolutional autoencoder and temporal information using transformers. We proposed the Spatial-to-Temporal Attention Module (STAM) to detect the I-CONECT study participants' cognitive conditions (MCI vs. those with normal cognition (NC)) using facial and interaction features. The interaction features of the facial features improved the prediction performance compared with applying facial features solely. The detection accuracy using this combined method reached 88%, whereas the accuracy without applying the segments and sequences information of the facial features within a video on a certain theme was 84%. Overall, the results show that spatiotemporal facial features modeled using DL algorithms have a discriminating power for the detection of MCI.

Platelets and Neurodegenerative Diseases: Current Knowledge and Future Perspectives

Platelets have a fundamental role in mediating hemostasis and thrombosis. However, more recently, a new idea is making headway, highlighting the importance of platelets as significant actors in modulating immune and inflammatory responses. In particular, platelets have an important role in the development of vascular amyloid-b-peptide(ab) deposits, known to play a relevant role in Alzheimer's disease (AD) through accumulation and deposition within the frontal cortex and hippocampus in the brain. The involvement of platelets in the pathogenesis of AD opens up the highly attractive possibility of applying antiplatelet therapy for the treatment and/or prevention of AD, but conclusive results are scarce. Even less is known about the potential role of platelets in mild cognitive impairment (MCI). The aim to this brief review is to summarize current knowledge on this topic and to introduce the new perspectives on the possible role of platelet activation as therapeutic target both in AD and MCI.

Ultrasensitive and Multiple Biomarker Discrimination for Alzheimer's Disease via Plasmonic & Microfluidic Sensing Technologies

As the population ages, the worldwide prevalence of Alzheimer's disease (AD) as the most common dementia in the elderly is increasing dramatically. However, a long-term challenge is to achieve rapid and accurate early diagnosis of AD by detecting hallmarks such as amyloid beta (Aβ42). Here, a multi-channel microfluidic-based plasmonic fiber-optic biosensing platform is established for simultaneous detection and differentiation of multiple AD biomarkers. The platform is based on a gold-coated, highly-tilted fiber Bragg grating (TFBG) and a custom-developed microfluidics. TFBG excites a high-density, narrow-cladding-mode spectral comb that overlaps with the broad absorption of surface plasmons for high-precision interrogation, enabling ultrasensitive monitoring of analytes. In situ detection and in-parallel discrimination of different forms of Aβ42 in cerebrospinal fluid (CSF) are successfully demonstrated with a detection of limit in the range of ≈30-170 pg mL-1, which is one order of magnitude below the clinical cut-off level in AD onset, providing high detection sensitivity for early diagnosis of AD. The integration of the TFBG sensor with multi-channel microfluidics enables simultaneous detection of multiple biomarkers using sub-µL sample volumes, as well as combining initial binding rate and real-time response time to differentiate between multiple biomarkers in terms of binding kinetics. With the advantages of multi-parameter, low consumption, and highly sensitive detection, the sensor represents an urgently needed potentials for large-scale diagnosis of diseases at early stage.

The Australian Traumatic Brain Injury Initiative: Statement of Working Principles and Rapid Review of Methods to Define Data Dictionaries for Neurological Conditions

The Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to develop a health informatics approach to collect data predictive of outcomes for persons with moderate-severe TBI across Australia. Central to this approach is a data dictionary; however, no systematic reviews of methods to define and develop data dictionaries exist to-date. This rapid systematic review aimed to identify and characterize methods for designing data dictionaries to collect outcomes or variables in persons with neurological conditions. Database searches were conducted from inception through October 2021. Records were screened in two stages against set criteria to identify methods to define data dictionaries for neurological conditions (International Classification of Diseases, 11th Revision: 08, 22, and 23). Standardized data were extracted. Processes were checked at each stage by independent review of a random 25% of records. Consensus was reached through discussion where necessary. Thirty-nine initiatives were identified across 29 neurological conditions. No single established or recommended method for defining a data dictionary was identified. Nine initiatives conducted systematic reviews to collate information before implementing a consensus process. Thirty-seven initiatives consulted with end-users. Methods of consultation were "roundtable" discussion (n = 30); with facilitation (n = 16); that was iterative (n = 27); and frequently conducted in-person (n = 27). Researcher stakeholders were involved in all initiatives and clinicians in 25. Importantly, only six initiatives involved persons with lived experience of TBI and four involved carers. Methods for defining data dictionaries were variable and reporting is sparse. Our findings are instructive for AUS-TBI and can be used to further development of methods for defining data dictionaries.

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.

A data-driven approach to complement the A/T/(N) classification system using CSF biomarkers

AIMS

The AT(N) classification system not only improved the biological characterization of Alzheimer's disease (AD) but also raised challenges for its clinical application. Unbiased, data-driven techniques such as clustering may help optimize it, rendering informative categories on biomarkers' values.

METHODS

We compared the diagnostic and prognostic abilities of CSF biomarkers clustering results against their AT(N) classification. We studied clinical (patients from our center) and research (Alzheimer's Disease Neuroimaging Initiative) cohorts. The studied CSF biomarkers included Aβ(1-42), Aβ(1-42)/Aβ(1-40) ratio, tTau, and pTau.

RESULTS

The optimal solution yielded three clusters in both cohorts, significantly different in diagnosis, AT(N) classification, values distribution, and survival. We defined these three CSF groups as (i) non-defined or unrelated to AD, (ii) early stages and/or more delayed risk of conversion to dementia, and (iii) more severe cognitive impairment subjects with faster progression to dementia.

CONCLUSION

We propose this data-driven three-group classification as a meaningful and straightforward approach to evaluating the risk of conversion to dementia, complementary to the AT(N) system classification.

Automated magnetic-bead-assisted sequential extraction technology for simultaneous detection of Aβ1-42 and Aβ1-40 in cerebrospinal fluid: An advance toward fully automated liquid chromatography-tandem mass spectrometry method

Traditional solid-phase extraction (SPE) LC-MS/MS is limited by high costs, turnaround times, and procedural complexity, which limited the usage in clinical practice. This study aimed to establish a robust UPLC-MS/MS method with automated magnetic-bead-assisted sequential extraction (MBASE) technology to simultaneously measure Aβ1-42 and Aβ1-40 in cerebrospinal fluid (CSF). A Waters TQ-XS triple quadrupole mass spectrometer and Acquity UPLC Protein BEH C4 column were used. The targeted analytes were extracted and concentrated using the automated MBASE technology with chemically modified magnetic MCX beads. Analytical performance was verified referring to the CLSI C62-A and EP-15-A3 guidelines. A total of 68 CSF samples were collected and analyzed using the MBASE UPLC-MS/MS method, traditional SPE UPLC-MS/MS method, and Lumipulse G fully automated chemiluminescence detection system, and method comparison analysis is conducted. The MBASE UHPLC-MS/MS method showed an analytical performance equivalent to that of traditional SPE technology, with a higher sample throughput and smaller amount of materials ($34.98 vs. $493.96) and labor cost (101 min vs. 140 min) for 96 samples. The limit of quantification (LOQ) of Aβ1-42 and Aβ1-40 was 0.10 ng/mL and 0.05 ng/mL; recovery was 88.35-107.07 % and 95.72-96.60 %; and total imprecision was 3.69-6.83 % and 3.02-3.61 %, respectively. The measurements were faithfully reproduced within the allowable levels of uncertainty using certified reference materials. The correlations between this MBASE UPLC-MS/MS method, the SPE UPLC-MS/MS method, and Lumipulse G fully automated biochemical analysis method are all deemed good (r = 0.869-0.936), and the MBASE- and SPE-UPLC-MS/MS methods showed comparable measurements. To our knowledge, our study firstly verified the robust performance of the MBASE UPLC-MS/MS method to simultaneously determine Aβ1-42 and Aβ1-40 in CSF. With further introduce of automation, the assay with high accuracy and low material and labor costs will become a promising clinical technology.

CSF biomarker concordance with amyloid PET in Phase 3 studies of aducanumab

INTRODUCTION

We assessed the use of cerebrospinal fluid (CSF) biomarkers as an alternative to positron emission tomography (PET) for brain amyloid beta (Aβ) pathology confirmation in the EMERGE and ENGAGE clinical trials.

METHODS

EMERGE and ENGAGE were randomized, placebo-controlled, Phase 3 trials of aducanumab in participants with early Alzheimer's disease. Concordance between CSF biomarkers (Aβ42, Aβ40, phosphorylated tau 181, and total tau) and amyloid PET status (visual read) at screening was examined.

RESULTS

Robust concordance between CSF biomarkers and amyloid PET visual status was observed (for Aβ42/Aβ40, AUC: 0.90; 95% CI: 0.83-0.97; p < 0.0001), confirming CSF biomarkers as a reliable alternative to amyloid PET in these studies. Compared with single CSF biomarkers, CSF biomarker ratios showed better agreement with amyloid PET visual reads, demonstrating high diagnostic accuracy.

DISCUSSION

These analyses add to the growing body of evidence supporting CSF biomarkers as reliable alternatives to amyloid PET imaging for brain Aβ pathology confirmation.

HIGHLIGHTS

CSF biomarkers and amyloid PET concordance were assessed in Ph3 aducanumab trials. Robust concordance between CSF biomarkers and amyloid PET was observed. CSF biomarker ratios increased diagnostic accuracy over single CSF biomarkers. CSF Aβ42/Aβ40 demonstrated high concordance with amyloid PET. Results support CSF biomarker testing as a reliable alternative to amyloid PET.

Biomarkers of diagnosis, prognosis, pathogenesis, response to therapy: Convergence or divergence? Lessons from Alzheimer's disease and synucleinopathies

Alzheimer's disease (AD) is the most common disorder associated with cognitive impairment. Recent observations emphasize the pathogenic role of multiple factors inside and outside the central nervous system, supporting the notion that AD is a syndrome of many etiologies rather than a "heterogeneous" but ultimately unifying disease entity. Moreover, the defining pathology of amyloid and tau coexists with many others, such as α-synuclein, TDP-43, and others, as a rule, not an exception. Thus, an effort to shift our AD paradigm as an amyloidopathy must be reconsidered. Along with amyloid accumulation in its insoluble state, β-amyloid is becoming depleted in its soluble, normal states, as a result of biological, toxic, and infectious triggers, requiring a shift from convergence to divergence in our approach to neurodegeneration. These aspects are reflected-in vivo-by biomarkers, which have become increasingly strategic in dementia. Similarly, synucleinopathies are primarily characterized by abnormal deposition of misfolded α-synuclein in neurons and glial cells and, in the process, depleting the levels of the normal, soluble α-synuclein that the brain needs for many physiological functions. The soluble to insoluble conversion also affects other normal brain proteins, such as TDP-43 and tau, accumulating in their insoluble states in both AD and dementia with Lewy bodies (DLB). The two diseases have been distinguished by the differential burden and distribution of insoluble proteins, with neocortical phosphorylated tau deposition more typical of AD and neocortical α-synuclein deposition peculiar to DLB. We propose a reappraisal of the diagnostic approach to cognitive impairment from convergence (based on clinicopathologic criteria) to divergence (based on what differs across individuals affected) as a necessary step for the launch of precision medicine.

Robustness of CSF Aβ42/40 and Aβ42/P-tau181 measured using fully automated immunoassays to detect AD-related outcomes

INTRODUCTION

This study investigated the comparability of cerebrospinal fluid (CSF) cutoffs for Elecsys immunoassays for amyloid beta (Aβ)42/Aβ40 or Aβ42/phosphorylated tau (p-tau)181 and the effects of measurement variability when predicting Alzheimer's disease (AD)-related outcomes (i.e., Aβ-positron emission tomography [PET] visual read and AD neuropathology).

METHODS

We studied 750 participants (BioFINDER study, Alzheimer's Disease Neuroimaging Initiative [ADNI], and University of California San Francisco [UCSF]). Youden's index was used to identify cutoffs and to calculate accuracy (Aβ-PET visual read as outcome). Using longitudinal variability in Aβ-negative controls, we identified a gray zone around cut-points where the risk of an inconsistent predicted outcome was >5%.

RESULTS

For Aβ42/Aβ40, cutoffs across cohorts were <0.059 (BioFINDER), <0.057 (ADNI), and <0.058 (UCSF). For Aβ42/p-tau181, cutoffs were <41.90 (BioFINDER), <39.20 (ADNI), and <46.02 (UCSF). Accuracy was ≈90% for both Aβ42/Aβ40 and Aβ42/p-tau181 using these cutoffs. Using Aβ-PET as an outcome, 8.7% of participants fell within a gray zone interval for Aβ42/Aβ40, compared to 4.5% for Aβ42/p-tau181. Similar findings were observed using a measure of overall AD neuropathologic change (7.7% vs. 3.3%). In a subset with CSF and plasma Aβ42/40, the number of individuals within the gray zone was ≈1.5 to 3 times greater when using plasma Aβ42/40.

DISCUSSION

CSF Aβ42/p-tau181 was more robust to the effects of measurement variability, suggesting that it may be the preferred Elecsys-based measure in clinical practice and trials.

NEURONORMA Cognitive Battery Associations with Cerebrospinal Fluid Amyloid-β and Tau Levels in the Continuum of Alzheimer's Disease

BACKGROUND

Neuropsychological assessments are essential to define the cognitive profile and contribute to the diagnosis of Alzheimer's disease (AD). The progress in knowledge about the pathophysiological process of the disease has allowed conceptualizing AD through biomarkers as a biological continuum that encompasses different clinical stages.

OBJECTIVE

To explore the association between cerebrospinal fluid (CSF) biomarkers of AD and cognition using the NEURONORMA battery, in a sample of cognitively unimpaired (CU), mild cognitive impaired (MCI), and mild dementia of the Alzheimer type (DAT) subjects, and to characterize the cognitive profiles in MCI subjects classified by A/T/N system.

METHODS

42 CU, 35 MCI, and 35 mild DAT were assessed using the NEURONORMA battery. Core AD biomarkers [amyloid-β42 (Aβ42) peptide, total tau (t-tau), and phosphorylated tau 181 (p-tau181)] proteins were measured in CSF. Correlation coefficients, multivariate regression, and effect sizes were calculated. We explored the age- and education-adjusted cognitive profiles by A/T/N variants within the MCI group.

RESULTS

Cognitive outcomes were directly associated with CSF Aβ42 and inversely with CSF tau measures. We found differences in both biomarkers and cognitive outcomes comparing all pairs except for CSF measures between cognitively impaired groups. The highest effect size was in memory tasks and biomarkers ratios. Lower performances were in memory and executive domains in MCI subjects with AD pathology (A+T+N±) compared to those with normal levels of AD biomarkers (A- T- N).

CONCLUSION

This study provides further evidence of the validity of Spanish NEURONORMA cognitive battery to characterize cognitive impairment in the AD pathological continuum.

Potential value of cerebrospinal fluid α-synuclein in the identification of postoperative delirium undergoing knee/hip arthroplasty: The perioperative neurocognitive disorder and biomarker lifestyle study

Objective

Postoperative delirium (POD) is a common postoperative complication, which may be associated with α-synuclein (α-syn). The purpose of this study was to explore the association between the expression level of α-syn in cerebrospinal fluid (CSF) and POD.

Methods

We conducted a prospective observational cohort study, which involved in 740 participants (mean age of 61.86 years, range 40–90 years; 40% female) from the Perioperative Neurocognitive Disorder And Biomarker Lifestyle (PNDABLE) study in the final analysis. POD was diagnosed using the Confusion Assessment Scale (CAM), and its severity was measured using the Memorial Delirium Assessment Scale (MDAS). Enzyme-linked immune-sorbent assay (ELISA) was used to detect the concentrations of α-syn, Aβ40, Aβ42, T-tau, and P-tau in CSF.

Results

The incidence of POD was 11.22% (83/740). The logistic regression analysis showed that the increased concentrations of CSF α-syn (OR = 1.005, 95%CI 1.004–1.006, P < 0.001), P-tau (OR = 1.093, 95%CI 1.071–1.115, P < 0.001), and T-tau (OR = 1.008, 95%CI 1.006–1.009, P < 0.001) were risk factors of POD. Linear regression showed that CSF α-syn had positive correlations with P-tau (β = 0.480, P < 0.001), T-tau (β = 0.334, P < 0.001), while negative correlations with Aβ40 (β = –0.378 P < 0.001), Aβ42 (β = -0.800, P = 0.001) in POD patients. Mediation analyses showed the association between α-syn and POD was partially mediated by tau pathologies (proportion: 16–17%).

Conclusion

CSF α-syn is one of the preoperative risk factors for POD, which may be mediated through tau pathologies.

Clinical trial registration

[www.ClinicalTrials.gov], identifier [ChiCTR20 00033439].

The Key Role of Magnetic Resonance Imaging in the Detection of Neurodegenerative Diseases-Associated Biomarkers: A Review

Neurodegenerative diseases (NDs), including chronic disease such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis, and acute diseases like traumatic brain injury and ischemic stroke are characterized by progressive degeneration, brain tissue damage and loss of neurons, accompanied by behavioral and cognitive dysfunctions. So far, there are no complete cures for NDs; thus, early and timely diagnoses are essential and beneficial to patients' treatment. Magnetic resonance imaging (MRI) has become one of the advanced medical imaging techniques widely used in the clinical examination of NDs due to its non-invasive diagnostic value. In this review, research published in English in current decade from PubMed electronic database on the use of MRI to detect specific biomarkers of NDs was collected, summarized, and discussed, which provides valuable suggestions for the early diagnosis, prevention, and treatment of NDs in the clinic.

The cognitive performance in the Phototest is predictor of biological markers of Alzheimer's disease

BACKGROUND

The abnormal cerebrospinal fluid levels of biomarkers, such as β-amyloid and phosphorylated tau (pTau), support the biological diagnosis of Alzheimer Disease (AD) independently of its clinical stage. However, this invasive exam cannot be extensively applied and requires previous sound clinical screen that can be based on brief, well validated cognitive tests, such as the Phototest.

OBJECTIVE

To evaluate the association of partial (naming [NA], total recall [TR], free recall [FR], and verbal fluency) and total scores of the Phototest with the biological diagnosis of AD and the potential use of this test as a screening tool in the clinical work up.

DESIGN

Retrospective study of Individuals attending a Memory Clinic who were applied the Phototest and classified, according to cerebrospinal fluid biomarkers (β-amyloid1-42 and pTau), in the biological AD continuum stage (ContAD) as "no AD" (A-), "AD changes" (A+T-) or "AD" (A+T+). Multivariate analyses were conducted with one fixed factor, ContAD, and partial and total Phototest scores. The area under the receiver operating characteristics curve (AUC) was calculated to estimate the capacity of Phototest scores to predict amyloidosis (A+) and AD.

RESULTS

The study included 170 individuals (92 A-, 23 A+T- and 55 A+T+). FR (7.9, 0.01 [F,p]) and TR (8.1, 0.001) scores were associated with ContAD and had a moderate ability (AUC 0.71-0.74) to detect the presence of "A+" or "AD".

CONCLUSIONS

Partial memory scores of Phototest are associated with ContAD. They predict acceptably the presence of abnormal levels of β-amyloid and AD signature in CSF and can be useful to support further biological diagnostic tests.

A Computational Monte Carlo Simulation Strategy to Determine the Temporal Ordering of Abnormal Age Onset Among Biomarkers of Alzheimer's Disease

To quantitatively determining the temporal ordering of abnormal age onsets (AAO) among various biomarkers for Alzheimer's disease (AD), we introduced a computational Monte-Carlo simulation (CMCS) to statistically examine such ordering of an AAO pair or over all AAOs. The CMCS 1) simulates longitudinal data, estimates AAO for each iteration, and finally assesses the type-I error of an AAO pair or all AAO ordering. Using hippocampus volume (VHC), cerebral glucose hypometabolic convergence index (HCI), plasma neurofilament light (NfL), mini-mental state exam (MMSE), the auditory verbal learning test-long term memory (AVLT-LTM), short term memory (AVLT-STM) and clinical-dementia rating sum of box scale (CDR-SOB) from 382 mild cognitive impairment converters and non-converters, the CMCS estimated type-I error for the earlier AAO of VHC, AVLT_STM and AVLT_LTM each than MMSE was significant (p<0.002). The type-I error for the overall AAO temporal ordering of VHC ≤ AVLT_STM ≤ AVLT_LTM < HCI ≤ MMSE ≤ CDR-SOB ≤ NfL was p = 0.012. These findings showed that our CMCS is capable of providing statistical inferences for quantifying AAO ordering which has important implications in advancing our understanding of AD.

A Metallomic Approach to Assess Associations of Plasma Metal Levels with Amnestic Mild Cognitive Impairment and Alzheimer's Disease: An Exploratory Study

Alzheimer’s disease (AD) involves the abnormal activity of transition metals and metal ion dyshomeostasis; however, the potential of trace metal biomarkers in predicting cognitive decline has not been evaluated. This study aimed to assess the potential of 36 trace elements in predicting cognitive decline in patients with amnestic mild cognitive impairment (aMCI) or AD. Participants (9 controls, 23 aMCI due to AD, and 8 AD dementia) underwent comprehensive cognitive tests, including the Mini-Mental State Examination (MMSE) and trace metal analysis. The correlations between the plasma trace element levels and annual MMSE changes during follow-up were analyzed. We found that an increase in disease severity was linked to lower plasma levels of boron (B), bismuth (Bi), thorium (Th), and uranium (U) (adjusted p < 0.05). Higher baseline calcium levels (r = 0.50, p = 0.026) were associated with less annual cognitive decline; those of B (r = −0.70, p = 0.001), zirconium (r = −0.58, p = 0.007), and Th (r = −0.52, p = 0.020) with rapid annual cognitive decline in the aMCI group; and those of manganese (r = −0.91, p = 0.035) with rapid annual cognitive decline in the AD group. Overall, our exploratory study suggests that plasma metal levels have great potential as in vivo biomarkers for aMCI and AD. Larger sample studies are necessary to confirm these results.

Amyloid-β Oligomers: Multiple Moving Targets

Alzheimer’s Disease (AD) is a neurodegenerative disorder that is characterized clinically by progressive cognitive decline and pathologically by the β-sheet rich fibril plaque deposition of the amyloid-β (Aβ) peptide in the brain. While plaques are a hallmark of AD, plaque burden is not correlated with cognitive impairment. Instead, Aβ oligomers formed during the aggregation process represent the main agents of neurotoxicity, which occurs 10–20 years before patients begin to show symptoms. These oligomers are dynamic in nature and represented by a heterogeneous distribution of aggregates ranging from low- to high-molecular weight, some of which are toxic while others are not. A major difficulty in determining the pathological mechanism(s) of Aβ, developing reliable diagnostic markers for early-stage detection, as well as effective therapeutics for AD are the differentiation and characterization of oligomers formed throughout disease propagation based on their molecular features, effects on biological function, and relevance to disease propagation and pathology. Thus, it is critical to methodically identify the mechanisms of Aβ aggregation and toxicity, as well as describe the roles of different oligomers and aggregates in disease progression and molecular pathology. Here, we describe a variety of biophysical techniques used to isolate and characterize a range of Aβ oligomer populations, as well as discuss proposed mechanisms of toxicity and therapeutic interventions aimed at specific assemblies formed during the aggregation process. The approaches being used to map the misfolding and aggregation of Aβ are like what was done during the fundamental early studies, mapping protein folding pathways using combinations of biophysical techniques in concert with protein engineering. Such information is critical to the design and molecular engineering of future diagnostics and therapeutics for AD.

Clinical application of CSF biomarkers for Alzheimer's disease: From rationale to ratios

Biomarker testing is recommended for the accurate and timely diagnosis of Alzheimer's disease (AD). Using illustrative case narratives we consider how cerebrospinal fluid (CSF) biomarker tests may be used in different presentations of cognitive impairment to facilitate timely and differential diagnosis, improving diagnostic accuracy, providing prognostic information, and guiding personalized management in diverse scenarios. Evidence shows that (1) CSF ratios are superior to amyloid beta (Aβ)1-42 alone; (2) concordance of CSF ratios to amyloid positron emission tomography (PET) is better than Aβ1-42 alone; and (3) phosphorylated tau (p-tau)/Aβ1-42 ratio is superior to p-tau alone. CSF biomarkers are recommended for the exclusion of AD as the underlying cause of cognitive impairment, diagnosis of AD at an early stage, differential diagnosis of AD in individuals presenting with other neuropsychiatric symptoms, accurate diagnosis of AD in an atypical presentation, and for clinical trial enrichment.

Highlights

 Cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarker testing may be underused outside specialist centers.CSF biomarkers improve diagnostic accuracy, guiding personalized management of AD.CSF ratios (amyloid beta [Aβ]1-42/Aβ1-40 and phosphorylated tau/Aβ1-42) perform better than single markers.CSF ratios produce fewer false-negative and false-positive results than individual markers.CSF biomarkers should be included in diagnostic work-up of AD and mild cognitive impairment due to AD.

Soluble APP-α and APP-β in cerebrospinal fluid as potential biomarkers for differential diagnosis of mild cognitive impairment

OBJECTIVES

Concentrations of soluble amyloid precursor proteins-α (sAPPα) and -β (sAPPβ) in cerebrospinal fluid (CSF) may reflect the neuropathology of Alzheimer's disease (AD). We previously reported that the concentrations of both sAPPα and sAPPβ were significantly higher in patients with mild cognitive impairment (MCI) due to AD (MCI-AD) than in control subjects without cognitive impairment. The present study analyzed whether these sAPPs are useful in the differential diagnosis of MCI.

METHODS

A modified and sensitive method was used to analyze concentrations of sAPPα and sAPPβ in CSF of patients with MCI-AD (n = 30) and MCI due to other causes (MCI-others) (n = 24). Phosphorylated tau (p-tau) and amyloid β-protein 42 (Aβ42) were also analyzed using standard methods.

RESULTS

CSF concentrations of sAPPα and sAPPβ were significantly higher in the MCI-AD than in the MCI-others group (p < 0.001). Furthermore, concentrations of both sAPPα and sAPPβ were highly correlated with the concentration of p-tau, consistent with our previous report.

CONCLUSIONS

Measurement of both sAPPs in CSF using sensitive methods can be helpful in the precise differential diagnosis of patients with MCI.

The Road to Personalized Medicine in Alzheimer’s Disease: The Use of Artificial Intelligence

Dementia remains an extremely prevalent syndrome among older people and represents a major cause of disability and dependency. Alzheimer’s disease (AD) accounts for the majority of dementia cases and stands as the most common neurodegenerative disease. Since age is the major risk factor for AD, the increase in lifespan not only represents a rise in the prevalence but also adds complexity to the diagnosis. Moreover, the lack of disease-modifying therapies highlights another constraint. A shift from a curative to a preventive approach is imminent and we are moving towards the application of personalized medicine where we can shape the best clinical intervention for an individual patient at a given point. This new step in medicine requires the most recent tools and analysis of enormous amounts of data where the application of artificial intelligence (AI) plays a critical role on the depiction of disease–patient dynamics, crucial in reaching early/optimal diagnosis, monitoring and intervention. Predictive models and algorithms are the key elements in this innovative field. In this review, we present an overview of relevant topics regarding the application of AI in AD, detailing the algorithms and their applications in the fields of drug discovery, and biomarkers.

Cerebrospinal fluid neurofilament light predicts the rate of executive function decline in younger-onset dementia

INTRODUCTION

Determining disease severity and predicting prognosis in younger onset-dementia (YOD) remains challenging. Whether CSF biomarkers neurofilament light (NfL), tau and amyloidβ 42 (Aβ42) can help provide such information has been underexplored.

METHODS

Patients with YOD and CSF analysis were identified. We compared baseline NfL, tau and Aβ42 concentrations with contemporaneous Neuropsychiatry Unit Cognitive Assessment Tool (NUCOG) scores to assess their association with severity of cognitive impairment. Cognitive decline, as measured by longitudinal NUCOG assessment, was correlated against baseline biomarker levels to assess their utility in predicting the rate of cognitive decline.

RESULTS

78 patients with YOD (mean age = 56 years, SD = 8) and CSF analysis were identified. Dementia types included Alzheimer's disease, behavioural variant frontotemporal dementia, dementia not-otherwise-specified and other. Tau was associated with contemporaneous memory dysfunction (r = -0.556, 95% CI:[-0.702,-0.393], p < .001). 21 patients had longitudinal cognitive assessment up to 82 months from CSF sampling. NfL was associated with the rate of executive function decline (r = 0.755, 95% CI:[0.259,0.937], p < .001). Aβ42 was associated with the rate of memory decline (r = -0.582, 95% CI:[-0.855,-0.274], p = .007) and rate of total NUCOG decline (r = -0.515, 95% CI: [-0.809, -0.227], p = .017).

CONCLUSION

CSF tau is related to contemporaneous memory impairment in YOD. NfL and Aβ42 levels are associated with the rate of executive function and memory decline, respectively, and may have a role in prognostication in YOD.

Elderly Patients with Mild Cognitive Impairment Exhibit Altered Gut Microbiota Profiles

Background

As a transitional state between normal aging and Alzheimer's disease (AD), mild cognitive impairment (MCI) is characterized by a worse cognitive decline than that of natural aging. The association between AD and gut microbiota has been reported in a number of studies; however, microbial research regarding MCI remains limited.

Methods

This study examined 48 participants, of whom 22 were MCI cases and 26 were normal control cases. Fecal samples were collected for 16S ribosomal RNA (rRNA) quantitative arrays and bioinformatics analysis.

Results

A principal coordinates analysis (PCoA) and nonmetric multidimensional scaling (NMDS) both demonstrated that the microbial composition of participants with MCI deviated from that of healthy control participants. Multiple bacterial species were significantly increased (e.g., Staphylococcus intermedius) or decreased (e.g., Bacteroides salyersiae) in samples from the MCI group.

Conclusion

The composition of gut microbiota differed between normal control and MCI cases. This is the first study to identify a signature series of species in the gut microbiota of individuals with MCI. The results provide a new direction for the future development of an early diagnosis and probiotic regimen.

Anti-Inflammatory Agents: An Approach to Prevent Cognitive Decline in Alzheimer's Disease

Systemic inflammation is an organism's response to an assault by the non-self. However, that inflammation may predispose humans to illnesses targeted to organs, including Alzheimer's disease (AD). Lesions in AD have pro-inflammatory cytokines and activated microglial/monocyte/macrophage cells. Up to this point, clinical trials using anti-amyloid monoclonal antibodies have not shown success. Maybe it is time to look elsewhere by combating inflammation. Neuroinflammation with CNS cellular activation and excessive expression of immune cytokines is suspected as the "principal culprit" in the higher risk for sporadic AD. Microglia, the resident immune cell of the CNS, perivascular myeloid cells, and activated macrophages produce IL-1, IL-6 at higher levels in patients with AD. Anti-inflammatory measures that target cellular/cytokine-mediated damage provide a rational therapeutic strategy. We propose a clinical trial using oral type 1 IFNs to act as such an agent; one that decreases IL-1 and IL-6 secretion by activating lamina propria lymphocytes in the gut associated lymphoid tissue with subsequent migration to the brain undergoing inflammatory responses. A clinical trial would be double-blind, parallel 1-year clinical trial randomized 1 : 1 oral active type 1 IFN versus best medical therapy to determine whether ingested type I IFN would decrease the rate of cognitive decline in mild cognitive impairment or mild AD. Using cognitive psychometrics, imaging, and fluid biomarkers (MxA for effective type I IFN activity beyond the gut), we can determine if oral type I IFN can prevent cognitive decline in AD.

Diagnosis and Treatment for Mild Cognitive Impairment: A Systematic Review of Clinical Practice Guidelines and Consensus Statements

Background: Mild cognitive impairment (MCI) is an important stage between the normal cognitive decline of aging and dementia. The aim of this study was to compare and harmonize the recommendations for the diagnosis and treatment of MCI based on current clinical practice guidelines. Methods: We searched the PubMed, EMBASE, China National Knowledge Infrastructure, Wanfang Database, Chinese Science and Technology Periodical Database, and Chinese Biological Medicine Database from their inception date to April 24, 2021 to identify all published guidelines on MCI. The qualities of the eligible guidelines were appraised by two reviewers using the Appraisal of Guidelines for Research and Evaluation II instrument. Results: Thirteen guidance documents (four guidelines and nine consensus statements) with specific recommendations were included. Nine guidelines and consensus statements covered the screening and diagnosis of MCI. The evaluation of the documents showed that neuropsychological testing and biomarker assessments were the most common recommendations for the diagnosis of MCI. Nine of the 13 guidance documents covered the treatment and management of MCI. The recommendations for the treatment and management were classified into four categories, namely: intervention for risk reduction, pharmacologic interventions, non-pharmacologic interventions, and counseling. Regarding pharmacological interventions, three guidelines recommend no pharmacologic intervention. The use of cholinesterase inhibitors for MCI is contraindicated in three guidance documents, whereas one proposes that cholinesterase inhibitors and memantine should be deprescribed. EHb761^®, Chinese herbal decoctions, and Chinese traditional patent medicine are recommended in two documents. A total of seven guidance documents recommend non-pharmacological interventions, including physical activity interventions, cognitive interventions, dietary and nutritional interventions, and acupuncture. Conclusion: An updated search for possible evidence on the diagnosis and treatment of MCI is needed. Potentially effective diagnoses and treatments, either conventional or complementary, and alternative therapies should be highly valued and addressed in correlation with the supporting evidence.

Network-constrained technique to characterize pathology progression rate in Alzheimer's disease

Current methods for measuring the chronic rates of cognitive decline and degeneration in Alzheimer’s disease rely on the sensitivity of longitudinal neuropsychological batteries and clinical neuroimaging, particularly structural magnetic resonance imaging of brain atrophy, either at a global or regional scale. There is particular interest in approaches predictive of future disease progression and clinical outcomes using a single time point. If successful, such approaches could have great impact on differential diagnosis, therapeutic treatment and clinical trial inclusion. Unfortunately, it has proven quite challenging to accurately predict clinical and degeneration progression rates from baseline data. Specifically, a key limitation of the previously proposed approaches for disease progression based on the brain atrophy measures has been the limited incorporation of the knowledge from disease pathology progression models, which suggest a prion-like spread of disease pathology and hence the neurodegeneration. Here, we present a new metric for disease progression rate in Alzheimer that uses only MRI-derived atrophy data yet is able to infer the underlying rate of pathology transmission. This is enabled by imposing a spread process driven by the brain networks using a Network Diffusion Model. We first fit this model to each patient’s longitudinal brain atrophy data defined on a brain network structure to estimate a patient-specific rate of pathology diffusion, called the pathology progression rate. Using machine learning algorithms, we then build a baseline data model and tested this rate metric on data from longitudinal Alzheimer’s Disease Neuroimaging Initiative study including 810 subjects. Our measure of disease progression differed significantly across diagnostic groups as well as between groups with different genetic risk factors. Remarkably, hierarchical clustering revealed 3 distinct clusters based on CSF profiles with >90% accuracy. These pathological clusters exhibit progressive atrophy and clinical impairments that correspond to the proposed rate measure. We demonstrate that a subject’s degeneration speed can be best predicted from baseline neuroimaging volumetrics and fluid biomarkers for subjects in the middle of their degenerative course, which may be a practical, inexpensive screening tool for future prognostic applications.

Cobalt induces neurodegenerative damages through Pin1 inactivation in mice and human neuroglioma cells

Cobalt is a hazardous material that has harmful effects on neurotoxicity. Excessive exposure to cobalt or inactivation of the unique proline isomerase Pin1 contributes to age-dependent neurodegeneration. However, nothing is known about the role of Pin1 in cobalt-induced neurodegeneration. Here we find that out of several hazardous materials, only cobalt dose-dependently decreased Pin1 expression and alterations in its substrates, including cis and trans phosphorylated Tau in human neuronal cells, concomitant with neurotoxicity. Cobalt-induced neurotoxicity was aggravated by Pin1 genetic or chemical inhibition, but rescued by Pin1 upregulation. Furthermore, less than 4 μg/l of blood cobalt induced dose- and age-dependent Pin1 downregulation in murine brains, ensuing neurodegenerative changes. These defects were corroborated by changes in Pin1 substrates, including cis and trans phosphorylated Tau, amyloid precursor protein, β amyloid and GSK3β. Moreover, blood Pin1 was downregulated in human hip replacement patients with median blood cobalt level of 2.514 μg/l, which is significantly less than the safety threshold of 10 μg/l, suggesting an early role Pin1 played in neurodegenerative damages. Thus, Pin1 inactivation by cobalt contributes to age-dependent neurodegeneration, revealing that cobalt is a hazardous material triggering AD-like neurodegenerative damages.

CSF in Epileptic Prodromal Alzheimer's Disease: No Diagnostic Contribution but a Pathophysiological One

Objective: To study whether cerebrospinal fluid (CSF) analysis may serve as a diagnostic test for the screening of epilepsy in sporadic prodromal Alzheimer's disease (AD).

Methods: A total of 29 patients with epileptic prodromal sporadic AD patients (epADs) were included and were retrospectively compared with 38 non-epileptic prodromal AD patients (nepADs) for demographics, clinical features, Mini-Mental Status Examination (MMSE) results, CSF biomarkers, and electro-radiological features.

Results: Our study did not show any significant differences in CSF biomarkers regarding neurodegeneration, albumin levels, and inflammation between epADs and nepADs. The epADs were significantly older at diagnosis (p = 0.001), more hypertensive (p = 0.01), and displayed larger white matter hyperintensities on brain magnetic resonance imaging (MRI; p = 0.05). There was a significant correlation between the CSF Aβ-42 and Aβ-40 levels with interictal epileptiform discharges and delta slowing on EEGs recordings, respectively (p = 0.03).

Conclusions: Our study suggests that CSF may not serve as a surrogate marker of epilepsy in prodromal AD and cannot circumvent the operator-dependent and time-consuming interpretation of EEG recordings. In humans, AD-related epileptogenesis appears to involve the Aβ peptides but likely also additional non-amyloid factors such as small-vessel disease (i.e., white matter hyperintensities).

Proteomic landscape of Alzheimer's Disease: novel insights into pathogenesis and biomarker discovery

Mass spectrometry-based proteomics empowers deep profiling of proteome and protein posttranslational modifications (PTMs) in Alzheimer's disease (AD). Here we review the advances and limitations in historic and recent AD proteomic research. Complementary to genetic mapping, proteomic studies not only validate canonical amyloid and tau pathways, but also uncover novel components in broad protein networks, such as RNA splicing, development, immunity, membrane transport, lipid metabolism, synaptic function, and mitochondrial activity. Meta-analysis of seven deep datasets reveals 2,698 differentially expressed (DE) proteins in the landscape of AD brain proteome (n = 12,017 proteins/genes), covering 35 reported AD genes and risk loci. The DE proteins contain cellular markers enriched in neurons, microglia, astrocytes, oligodendrocytes, and epithelial cells, supporting the involvement of diverse cell types in AD pathology. We discuss the hypothesized protective or detrimental roles of selected DE proteins, emphasizing top proteins in "amyloidome" (all biomolecules in amyloid plaques) and disease progression. Comprehensive PTM analysis represents another layer of molecular events in AD. In particular, tau PTMs are correlated with disease stages and indicate the heterogeneity of individual AD patients. Moreover, the unprecedented proteomic coverage of biofluids, such as cerebrospinal fluid and serum, procures novel putative AD biomarkers through meta-analysis. Thus, proteomics-driven systems biology presents a new frontier to link genotype, proteotype, and phenotype, accelerating the development of improved AD models and treatment strategies.

European Academy of Neurology/European Alzheimer's Disease Consortium position statement on diagnostic disclosure, biomarker counseling, and management of patients with mild cognitive impairment

BACKGROUND AND PURPOSE

Careful counseling through the diagnostic process and adequate postdiagnostic support in patients with mild cognitive impairment (MCI) is important. Previous studies have indicated heterogeneity in practice and the need for guidance for clinicians.

METHODS

A joint European Academy of Neurology/European Alzheimer's Disease Consortium panel of dementia specialists was appointed. Through online meetings and emails, positions were developed regarding disclosing a syndrome diagnosis of MCI, pre- and postbiomarker sampling counseling, and postdiagnostic support.

RESULTS

Prior to diagnostic evaluation, motives and wishes of the patient should be sought. Diagnostic disclosure should be carried out by a dementia specialist taking the ethical principles of "the right to know" versus "the wish not to know" into account. Disclosure should be accompanied by written information and a follow-up plan. It should be made clear that MCI is not dementia. Prebiomarker counseling should always be carried out if biomarker sampling is considered and postbiomarker counseling if sampling is carried out. A dementia specialist knowledgeable about biomarkers should inform about pros and cons, including alternatives, to enable an autonomous and informed decision. Postbiomarker counseling will depend in part on the results of biomarkers. Follow-up should be considered for all patients with MCI and include brain-healthy advice and possibly treatment for specific underlying causes. Advice on advance directives may be relevant.

CONCLUSIONS

Guidance to clinicians on various aspects of the diagnostic process in patients with MCI is presented here as position statements. Further studies are needed to enable more evidence-based and standardized recommendations in the future.

Use of a panel of four microRNAs in CSF as a predicted biomarker for postoperative neoangiogenesis in moyamoya disease

INTRODUCTION AND AIMS

At present, the treatment for moyamoya disease (MMD) primarily consists of combined direct and indirect bypass surgery. Nevertheless, more than half of indirect bypass surgeries fail to develop good collaterals from the dura and temporal muscle. This study aimed to investigate whether microRNAs (miRNAs) in cerebrospinal fluid (CSF) could serve as biomarkers for the prediction of postoperative collateral formation.

METHODS

Moyamoya disease patients with indirect bypass surgery were divided into angiogenesis and non-angiogenesis groups, CSF was obtained, and miRNA sequencing was performed using the CSF. Candidate miRNAs were filtered and subsequently verified through qRT-PCR. The diagnostic utility of these differential miRNAs was investigated by using receiver operating characteristic (ROC) curve analysis. Finally, the potential biological processes and signaling pathways associated with candidate miRNAs were analyzed using R software.

RESULTS

The expression levels of four miRNAs (miR-92a-3p, miR-486-3p, miR-25-3p, and miR-155-5p) were significantly increased in the angiogenesis group. By combining these four miRNAs (area under the curve [AUC] =0.970), we established an accurate predictive model of collateral circulation after indirect bypass surgery in MMD patients. GO and KEGG analyses demonstrated a high correlation with biological processes and signaling pathways related to angiogenesis.

CONCLUSION

The 4-miRNA signature is a good model to predict angiogenesis after indirect bypass surgery and help the surgeon to select a appreciate bypass strategy.

A blood-based diagnostic test incorporating plasma Aβ42/40 ratio, ApoE proteotype, and age accurately identifies brain amyloid status: findings from a multi cohort validity analysis

BACKGROUND

The development of blood-based biomarker tests that are accurate and robust for Alzheimer's disease (AD) pathology have the potential to aid clinical diagnosis and facilitate enrollment in AD drug trials. We developed a high-resolution mass spectrometry (MS)-based test that quantifies plasma Aβ42 and Aβ40 concentrations and identifies the ApoE proteotype. We evaluated robustness, clinical performance, and commercial viability of this MS biomarker assay for distinguishing brain amyloid status.

METHODS

We used the novel MS assay to analyze 414 plasma samples that were collected, processed, and stored using site-specific protocols, from six independent US cohorts. We used receiver operating characteristic curve (ROC) analyses to assess assay performance and accuracy for predicting amyloid status (positive, negative, and standard uptake value ratio; SUVR). After plasma analysis, sites shared brain amyloid status, defined using diverse, site-specific methods and cutoff values; amyloid PET imaging using various tracers or CSF Aβ42/40 ratio.

RESULTS

Plasma Aβ42/40 ratio was significantly (p < 0.001) lower in the amyloid positive vs. negative participants in each cohort. The area under the ROC curve (AUC-ROC) was 0.81 (95% CI = 0.77-0.85) and the percent agreement between plasma Aβ42/40 and amyloid positivity was 75% at the optimal (Youden index) cutoff value. The AUC-ROC (0.86; 95% CI = 0.82-0.90) and accuracy (81%) for the plasma Aβ42/40 ratio improved after controlling for cohort heterogeneity. The AUC-ROC (0.90; 95% CI = 0.87-0.93) and accuracy (86%) improved further when Aβ42/40, ApoE4 copy number and participant age were included in the model.

CONCLUSIONS

This mass spectrometry-based plasma biomarker test: has strong diagnostic performance; can accurately distinguish brain amyloid positive from amyloid negative individuals; may aid in the diagnostic evaluation process for Alzheimer's disease; and may enhance the efficiency of enrolling participants into Alzheimer's disease drug trials.

Use of Alzheimer's Disease Cerebrospinal Fluid Biomarkers in A Tertiary Care Memory Clinic

INTRODUCTION

Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers are promising tools to help identify the underlying pathology of neurocognitive disorders. In this manuscript, we report our experience with AD CSF biomarkers in 262 consecutive patients in a tertiary care memory clinic.

METHODS

We retrospectively reviewed 262 consecutive patients who underwent lumbar puncture (LP) and CSF measurement of AD biomarkers (Aβ1-42, total tau or t-tau, and p-tau181). We studied the safety of the procedure and its impact on patient's diagnosis and management.

RESULTS

The LP allowed to identify underlying AD pathology in 72 of the 121 patients (59%) with early onset amnestic mild cognitive impairment (aMCI) with a high probability of progression to AD; to distinguish the behavioral/dysexecutive variant of AD from the behavioral variant of frontotemporal dementia (bvFTD) in 25 of the 45 patients (55%) with an atypical neurobehavioral profile; to identify AD as the underlying pathology in 15 of the 27 patients (55%) with atypical or unclassifiable primary progressive aphasia (PPA); and to distinguish AD from other disorders in 9 of the 29 patients (31%) with psychiatric differential diagnoses and 19 of the 40 patients (47%) with lesional differential diagnoses (normal pressure hydrocephalus, encephalitis, prion disease, etc.). No major complications occurred following the LP.

INTERPRETATION

Our results suggest that CSF analysis is a safe and effective diagnostic tool in select patients with neurocognitive disorders. We advocate for a wider use of this biomarker in tertiary care memory clinics in Canada.

Pyroptosis executive protein GSDMD as a biomarker for diagnosis and identification of Alzheimer's disease

OBJECTIVE

This study was mainly conducted to explore the expression changes of GSDMD and conventional markers (including T-Tau, Tau181p, and Aβ_1-42 ) in the cerebrospinal fluid among patients with Alzheimer's disease (AD) and vascular dementia (VD), followed by determination of role of GSDMD in diagnosing and identifying AD and VD.

METHODS

In this study, 60 patients with VD, 60 patients with AD, and 50 healthy controls were enrolled. Lumbar puncture was performed to collect cerebrospinal fluid samples. Patients with VD and patients with AD were evaluated using the Mini-Mental State Examination (MMSE) scale, Montreal Cognitive Assessment (MoCA) scale, Clinical Dementia Rating (CDR) scale, Activity of Daily Living (ADL) scale, and Neuropsychiatric Inventory (NPI) questionnaire, aiming to determine the behavioral ability of patients. ELISA kit was purchased to determine the levels of GSDMD, T-Tau, Tau181p, and Aβ_1-42 in cerebrospinal fluid, and the expression of inflammatory factors, IL-1β and IL-6, was also detected.

RESULTS

(1) The levels of GSDMD, T-Tau, and Tau181p in the cerebrospinal fluid were higher in patients with AD than those of patients with VD and healthy controls, while the levels of Aβ_1-42 in the cerebrospinal fluid were lower in patients with AD than that in healthy controls and patients with VD. (2) GSDMD had good diagnostic accuracy in AD. Additionally, GSDMD, T-Tau, Tau181p, and Aβ_1-42 had good discrimination accuracy in distinguishing AD and VD. (3) The expression levels of inflammatory factors (IL-1β and IL-6) in cerebrospinal fluid were higher in patients with AD than those of healthy controls and patients with VD, which were positively correlated with GSDMD expression.

CONCLUSION

The expression of GSDMD was increased in patients with AD, which could be used as a biomarker for AD diagnosis and identification from VD.

Biomarker-Based Risk Prediction of Alzheimer’s Disease Dementia in Mild Cognitive Impairment: Psychosocial, Ethical, and Legal Aspects

Background: Today, a growing number of individuals with mild cognitive impairment (MCI) wish to assess their risk of developing Alzheimer’s disease (AD) dementia. The expectations as well as the effects on quality of life (QoL) in MCI patients and their close others through biomarker-based dementia risk estimation are not well studied. Objective: The PreDADQoL project aims at providing empirical data on effects of such prediction on QoL and at developing an ethical and legal framework of biomarker-based dementia risk estimation in MCI. Methods: In the empirical study, 100 MCI-patients and their close others will be recruited from two sites (Germany and Spain). They receive standardized counselling on cerebrospinal fluid (CSF) biomarker-based prediction of AD dementia and a risk disclosure based on their AD biomarker status. A mixed methods approach will be applied to assess outcomes. Results: The pilot-study yielded a specification of the research topics and newly developed questionnaires for the main assessment. Within this binational quantitative and qualitative study, data on attitudes and expectations toward AD risk prediction, QoL, risk communication, coping strategies, mental health, lifestyle changes, and healthcare resource utilization will be obtained. Together with the normative part of the project, an empirically informed ethical and legal framework for biomarker-based dementia risk estimation will be developed. Conclusion: The empirical research of the PreDADQoL study together with the ethical and legal considerations and implications will help to improve the process of counselling and risk disclosure and thereby positively affect QoL and health of MCI-patients and their close others in the context of biomarker-based dementia risk estimation.

Fluid Biomarkers in Clinical Trials for Alzheimer's Disease: Current and Future Application

Alzheimer's disease (AD) research is entering a unique moment in which enormous information about the molecular basis of this disease is being translated into therapeutics. However, almost all drug candidates have failed in clinical trials over the past 30 years. These many trial failures have highlighted a need for the incorporation of biomarkers in clinical trials to help improve the trial design. Fluid biomarkers measured in cerebrospinal fluid and circulating blood, which can reflect the pathophysiological process in the brain, are becoming increasingly important in AD clinical trials. In this review, we first succinctly outline a panel of fluid biomarkers for neuropathological changes in AD. Then, we provide a comprehensive overview of current and future application of fluid biomarkers in clinical trials for AD. We also summarize the many challenges that have been encountered in efforts to integrate fluid biomarkers in clinical trials, and the barriers that have begun to be overcome. Ongoing research efforts in the field of fluid biomarkers will be critical to make significant progress in ultimately unveiling disease-modifying therapies in AD.

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 Testing: Piercing the Fog of Alzheimer's and Related Dementia

Alzheimer's disease (AD) and related dementia is one of the growing threats to the sustainability of health and care systems in developed countries, and efforts to find therapies have had scant success. The main reasons for this are lack of efficient therapy, which is linked to too late discovery of the disease itself. With this in mind, biomarkers are recognised as an element which can bring a major contribution to research, helping elucidate the disease and the search for treatments. They are also playing an increasing role in early detection and timely diagnosis, which are considered the principal hopes of effective management in the absence of an effective drug. The current arsenal of biomarkers could already, if more widely deployed, provide an effective minimum service to patients and health systems. A concerted action by policy makers and stakeholders could drive progress in access to AD biomarker testing to provide an optimum service in the medium term. This paper discusses how to improve the use of and access to biomarker testing in the detection and diagnosis of AD and other diseases featuring dementia, and how EU healthcare systems could benefit. It outlines the challenges, lists the achievements to date, and highlights the actions needed to allow biomarker testing to deliver more fully on their potential in AD.

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.

CCCDTD5: Clinical role of neuroimaging and liquid biomarkers in patients with cognitive impairment

Since 1989, four Canadian Consensus Conferences on the Diagnosis and Treatment of Dementia (CCCDTDs) have provided evidence-based dementia diagnostic and treatment guidelines for Canadian clinicians and researchers. We present the results from the Neuroimaging and Fluid Biomarkers Group of the 5th CCCDTD (CCCDTD5), which addressed topics chosen by the steering committee to reflect advances in the field and build on our previous guidelines. Recommendations on Imaging and Fluid Biomarker Use from this Conference cover a series of different fields. Prior structural imaging recommendations for both computerized tomography (CT) and magnetic resonance imaging (MRI) remain largely unchanged, but MRI is now more central to the evaluation than before, with suggested sequences described here. The use of visual rating scales for both atrophy and white matter anomalies is now included in our recommendations. Molecular imaging with [18F]-fluorodeoxyglucose ([18F]-FDG) Positron Emisson Tomography (PET) or [99mTc]-hexamethylpropyleneamine oxime/ethylene cysteinate dimer ([99mTc]-HMPAO/ECD) Single Photon Emission Tomography (SPECT), should now decidedly favor PET. The value of [18F]-FDG PET in the assessment of neurodegenerative conditions has been established with greater certainty since the previous conference, and it has now been recognized as a useful biomarker to establish the presence of neurodegeneration by a number of professional organizations around the world. Furthermore, the role of amyloid PET has been clarified and our recommendations follow those from other groups in multiple countries. SPECT with [123I]-ioflupane (DaTscanTM) is now included as a useful study in differentiating Alzheimer's disease (AD) from Lewy body disease. Finally, liquid biomarkers are in a rapid phase of development and, could lead to a revolution in the assessment AD and other neurodegenerative conditions at a reasonable cost. We hope these guidelines will be useful for clinicians, researchers, policy makers, and the lay public, to inform a current and evidence-based approach to the use of neuroimaging and liquid biomarkers in clinical dementia evaluation and management.

Optical Coherence Tomography in Patients with Alzheimer's Disease: What Can It Tell Us?

PURPOSE

Although Alzheimer's disease (AD) is a leading cause of dementia worldwide, its clinical diagnosis remains a challenge. Optical coherence tomography (OCT) and OCT with angiography (OCTA) are non-invasive ophthalmic imaging tools with the potential to detect retinal structural and microvascular changes in patients with AD, which may serve as biomarkers for the disease. In this systematic review, we evaluate whether certain OCT and OCTA parameters are significantly associated with AD and mild cognitive impairment (MCI).

METHODS

PubMed database was searched using a combination of MeSH terms to identify studies for review. Studies were organized by participant diagnostic groups, type of imaging modality, and OCT/OCTA parameters of interest. Participant demographic data was also collected and baseline descriptive statistics were calculated for the included studies.

RESULTS

Seventy-one studies were included for review, representing a total of 6757 patients (2350 AD, 793 MCI, 2902 healthy controls (HC), and 841 others with a range of other neurodegenerative diagnoses). The mean baseline ages were 72.78±3.69, 71.52±2.88, 70.55±3.85 years for AD, MCI and HC groups, respectively. The majority of studies noted significant structural and functional decline in AD patients when compared to HC. Although analysis of MCI groups yielded more mixed results, a similar pattern of decline was often noted amongst patients with MCI relative to HC. OCT and OCTA measurements were also shown to correlate with established measures of AD such as neuropsychological testing or neuroimaging.

CONCLUSION

OCT and OCTA show great potential as non-invasive technologies for the diagnosis of AD. However, further research is needed to determine whether there are AD-specific patterns of structural or microvascular change in the retina and optic nerve that distinguish AD from other neurodegenerative diseases. Development of sensitive and specific OCT/OCTA parameters will be necessary before they can be used to detect AD in clinical settings.

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.