A/T/(N) Profile in Cerebrospinal Fluid of Parkinson's Disease with/without Cognitive Impairment and Dementia with Lewy Bodies

Fully automated measurement of plasma Aβ42/40 and p-tau181: Analytical robustness and concordance with cerebrospinal fluid profile along the Alzheimer's disease continuum in two independent cohorts

INTRODUCTION

For routine clinical implementation of Alzheimer's disease (AD) plasma biomarkers, fully automated random-access platforms are crucial to ensure reproducible measurements. We aimed to perform an analytical validation and to establish cutoffs for AD plasma biomarkers measured with Lumipulse.

METHODS

Two cohorts were included. UNIPG: n = 450 paired cerebrospinal fluid (CSF)/plasma samples from subjects along the AD-continuum, subjects affected by other neurodegenerative diseases, and controls with known CSF profile; AMS: n = 40 plasma samples from AD and n = 40 controls. Plasma amyloid β (Aβ)42, Aβ40, and p-tau181 were measured with Lumipulse. We evaluated analytical and diagnostic performance.

RESULTS

Lumipulse assays showed high analytical performance. Plasma p-tau181 levels accurately reflected CSF A+/T+ profile in AD-dementia and mild cognitive impairment (MCI)-AD, but not in asymptomatic-AD. Plasma and CSF Aβ42/40 values were concordant across clinical AD stages. Cutoffs and probability-based models performed satisfactorily in both cohorts.

DISCUSSION

The identified cutoffs and probability-based models represent a significant step toward plasma AD molecular diagnosis.

Evaluation of ATNPD Framework and Biofluid Markers to Predict Cognitive Decline in Early Parkinson Disease

BACKGROUND AND OBJECTIVES

In Parkinson disease (PD), Alzheimer disease (AD) copathology is common and clinically relevant. However, the longitudinal progression of AD CSF biomarkers-β-amyloid 1-42 (Aβ42), phosphorylated tau 181 (p-tau181), and total tau (t-tau)-in PD is poorly understood and may be distinct from clinical AD. Moreover, it is unclear whether CSF p-tau181 and serum neurofilament light (NfL) have added prognostic utility in PD, when combined with CSF Aβ42. First, we describe longitudinal trajectories of biofluid markers in PD. Second, we modified the AD β-amyloid/tau/neurodegeneration (ATN) framework for application in PD (ATNPD) using CSF Aβ42 (A), p-tau181 (T), and serum NfL (N) and tested ATNPD prediction of longitudinal cognitive decline in PD.

METHODS

Participants were selected from the Parkinson's Progression Markers Initiative cohort, clinically diagnosed with sporadic PD or as controls, and followed up annually for 5 years. Linear mixed-effects models (LMEMs) tested the interaction of diagnosis with longitudinal trajectories of analytes (log transformed, false discovery rate [FDR] corrected). In patients with PD, LMEMs tested how baseline ATNPD status (AD [A+T+N±] vs not) predicted clinical outcomes, including Montreal Cognitive Assessment (MoCA; rank transformed, FDR corrected).

RESULTS

Participants were 364 patients with PD and 168 controls, with comparable baseline mean (±SD) age (patients with PD = 62 ± 10 years; controls = 61 ± 11 years]; Mann-Whitney Wilcoxon: p = 0.4) and sex distribution (patients with PD = 231 male individuals [63%]; controls = 107 male individuals [64%]; χ2: p = 1). Patients with PD had overall lower CSF p-tau181 (β = -0.16, 95% CI -0.23 to -0.092, p = 2.2e-05) and t-tau than controls (β = -0.13, 95% CI -0.19 to -0.065, p = 4e-04), but not Aβ42 (p = 0.061) or NfL (p = 0.32). Over time, patients with PD had greater increases in serum NfL than controls (β = 0.035, 95% CI 0.022 to 0.048, p = 9.8e-07); slopes of patients with PD did not differ from those of controls for CSF Aβ42 (p = 0.18), p-tau181 (p = 1), or t-tau (p = 0.96). Using ATNPD, PD classified as A+T+N± (n = 32; 9%) had worse cognitive decline on global MoCA (β = -73, 95% CI -110 to -37, p = 0.00077) than all other ATNPD statuses including A+ alone (A+T-N-; n = 75; 21%).

DISCUSSION

In patients with early PD, CSF p-tau181 and t-tau were low compared with those in controls and did not increase over 5 years of follow-up. Our study shows that classification using modified ATNPD (incorporating CSF Aβ42, CSF p-tau181, and serum NfL) can identify biologically relevant subgroups of PD to improve prediction of cognitive decline in early PD.

Multiomics Blood-Based Biomarkers Predict Alzheimer's Predementia with High Specificity in a Multicentric Cohort Study

BACKGROUND

The primary criteria for diagnosing mild cognitive impairment (MCI) due to Alzheimer's Disease (AD) or probable mild AD dementia rely partly on cognitive assessments and the presence of amyloid plaques. Although these criteria exhibit high sensitivity in predicting AD among cognitively impaired patients, their specificity remains limited. Notably, up to 25% of non-demented patients with amyloid plaques may be misdiagnosed with MCI due to AD, when in fact they suffer from a different brain disorder. The introduction of anti-amyloid antibodies complicates this scenario. Physicians must prioritize which amyloid-positive MCI patients receive these treatments, as not all are suitable candidates. Specifically, those with non-AD amyloid pathologies are not primary targets for amyloid-modifying therapies. Consequently, there is an escalating medical necessity for highly specific blood biomarkers that can accurately detect pre-dementia AD, thus optimizing amyloid antibody prescription.

OBJECTIVES

The objective of this study was to evaluate a predictive model based on peripheral biomarkers to identify MCI and mild dementia patients who will develop AD dementia symptoms in cognitively impaired population with high specificity.

DESIGN

Peripheral biomarkers were identified in a gene transfer-based animal model of AD and then validated during a retrospective multi-center clinical study.

SETTING

Participants from 7 retrospective cohorts (US, EU and Australia).

PARTICIPANTS

This study followed 345 cognitively impaired individuals over up to 13 years, including 193 with MCI and 152 with mild dementia, starting from their initial visits. The final diagnoses, established during their last assessments, classified 249 participants as AD patients and 96 as having non-AD brain disorders, based on the specific diagnostic criteria for each disorder subtype. Amyloid status, assessed at baseline, was available for 82.9% of the participants, with 61.9% testing positive for amyloid. Both amyloid-positive and negative individuals were represented in each clinical group. Some of the AD patients had co-morbidities such as metabolic disorders, chronic diseases, or cardiovascular pathologies.

MEASUREMENTS

We developed targeted mass spectrometry assays for 81 blood-based biomarkers, encompassing 45 proteins and 36 metabolites previously identified in AAV-AD rats.

METHODS

We analyzed blood samples from study participants for the 81 biomarkers. The B-HEALED test, a machine learning-based diagnostic tool, was developed to differentiate AD patients, including 123 with Prodromal AD and 126 with mild AD dementia, from 96 individuals with non-AD brain disorders. The model was trained using 70% of the data, selecting relevant biomarkers, calibrating the algorithm, and establishing cutoff values. The remaining 30% served as an external test dataset for blind validation of the predictive accuracy.

RESULTS

Integrating a combination of 19 blood biomarkers and participant age, the B-HEALED model successfully distinguished participants that will develop AD dementia symptoms (82 with Prodromal AD and 83 with AD dementia) from non-AD subjects (71 individuals) with a specificity of 93.0% and sensitivity of 65.4% (AUROC=81.9%, p<0.001) during internal validation. When the amyloid status (derived from CSF or PET scans) and the B-HEALED model were applied in association, with individuals being categorized as AD if they tested positive in both tests, we achieved 100% specificity and 52.8% sensitivity. This performance was consistent in blind external validation, underscoring the model's reliability on independent datasets.

CONCLUSIONS

The B-HEALED test, utilizing multiomics blood-based biomarkers, demonstrates high predictive specificity in identifying AD patients within the cognitively impaired population, minimizing false positives. When used alongside amyloid screening, it effectively identifies a nearly pure prodromal AD cohort. These results bear significant implications for refining clinical trial inclusion criteria, facilitating drug development and validation, and accurately identifying patients who will benefit the most from disease-modifying AD treatments.

ATN cerebrospinal fluid biomarkers in dementia with Lewy bodies: Initial results from the United States Dementia with Lewy Bodies Consortium

INTRODUCTION

The National Institute on Aging - Alzheimer's Association (NIA-AA) ATN research framework proposes to use biomarkers for amyloid (A), tau (T), and neurodegeneration (N) to stage individuals with AD pathological features and track changes longitudinally. The overall aim was to utilize this framework to characterize pre-mortem ATN status longitudinally in a clinically diagnosed cohort of dementia with Lewy bodies (DLB) and to correlate it with the post mortem diagnosis.

METHODS

The cohort was subtyped by cerebrospinal fluid (CSF) ATN category. A subcohort had longitudinal data, and a subgroup was neuropathologically evaluated.

RESULTS

We observed a significant difference in Aβ42/40 after 12 months in the A+T- group. Post mortem neuropathologic analyses indicated that most of the p-Tau 181 positive (T+) cases also had a high Braak stage.

DISCUSSION

This suggests that DLB patients who are A+ but T- may need to be monitored to determine whether they remain A+ or ever progress to T positivity.

HIGHLIGHTS

Some A+T- DLB subjects transition from A+ to negative after 12-months. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Monitoring of the A+T- sub-type of DLB may be necessary.

CSF neurochemical profile and cognitive changes in Parkinson's disease with mild cognitive impairment

Pathophysiological substrate(s) and progression of Parkinson's disease (PD) with mild cognitive impairment (PD-MCI) are still matter of debate. Baseline cerebrospinal fluid (CSF) neurochemical profile and cognitive changes after 2 years were investigated in a retrospective series of PD-MCI (n = 48), cognitively normal PD (PD-CN, n = 40), prodromal Alzheimer's disease (MCI-AD, n = 25) and cognitively healthy individuals with other neurological diseases (OND, n = 44). CSF biomarkers reflecting amyloidosis (Aβ42/40 ratio, sAPPα, sAPPβ), tauopathy (p-tau), neurodegeneration (t-tau, NfL, p-NfH), synaptic damage (α-syn, neurogranin) and glial activation (sTREM2, YKL-40) were measured. The great majority (88%) of PD-MCI patients was A-/T-/N-. Among all biomarkers considered, only NfL/p-NfH ratio was significantly higher in PD-MCI vs. PD-CN (p = 0.02). After 2 years, one-third of PD-MCI patients worsened; such worsening was associated with higher baseline levels of NfL, p-tau, and sTREM2. PD-MCI is a heterogeneous entity requiring further investigations on larger, longitudinal cohorts with neuropathological verification.

Cerebrospinal fluid β-synuclein as a synaptic biomarker for preclinical Alzheimer's disease

INTRODUCTION

β-synuclein (β-syn) is a presynaptic protein, whose cerebrospinal fluid (CSF) levels are increased in patients with Alzheimer's diseases (AD) showing mild cognitive impairment (MCI) and dementia (dem). Here, we aimed to investigate CSF β-syn in subjects at different AD stages, including preclinical AD (pre-AD), and to compare its behaviour with another synaptic biomarker, α-synuclein (α-syn), and two biomarkers of neuro-axonal damage, namely neurofilament light chain protein (NfL) and total tau protein (t-tau).

METHODS

We measured β-syn, α-syn, t-tau and NfL in CSF of 75 patients with AD (pre-AD n=17, MCI-AD n=28, dem-AD n=30) and 35 controls (subjective memory complaints, SMC-Ctrl n=13, non-degenerative neurological disorders, Dis-Ctrl n=22).

RESULTS

CSF β-syn, α-syn, t-tau were significantly elevated in pre-AD patients compared with controls (p<0.0001, p=0.02 and p=0.0001, respectively), while NfL only increased in dem-AD (p=0.001). Pre-AD cases showed lower t-tau concentrations than MCI-AD (p=0.04) and dem-AD (p=0.01). CSF β-syn had the best diagnostic performance for the discrimination of pre-AD subjects from all controls (area under the curve, AUC=0.97) and from SMC-Ctrl subjects (AUC=0.99).

DISCUSSION

CSF β-syn increases in the whole AD continuum since the preclinical stage and represents a promising biomarker of synaptic damage in AD.

Subjective cognitive complaints are important in PD-MCI criteria: Associations with CSF markers and cognitive decline

INTRODUCTION

According to the Movement Disorder Society (MDS), subjective cognitive complaints (SCC) are a diagnostic criterion for PD-mild cognitive impairment (PD-MCI); however, studies often do not incorporate SCC when classifying PD-MCI. This inconsistent use may reflect mixed findings regarding the association between SCC and objective measures of cognitive impairment. Our study aimed to describe the extent that inclusion/exclusion of SCC affects the occurrence of PD-MCI, and if the inclusion of SCC is associated with faster cognitive decline and cerebrospinal fluid markers (CSF) of alpha-synuclein, amyloid beta, total tau, and phophorylated-tau.

METHODS

Individuals with PD (N = 358) from the PPMI cohort whom completed measures of neuropsychological performance, subjective cognitive complaints, motor severity, and CSF markers were included. Participants were classified as cognitively normal (CN), PD-MCI with subjective cognitive complaints (PD-MCI + SCC) and PD-MCI without subjective cognitive complaints (PD-MCI -SCC).

RESULTS

PD-MCI rates were consistently higher (16.5-19.1%) across the 5 years when SCC was not included in the diagnostic criteria as opposed to when SCC was included (4.4-11.0%). PD-MCI + SCC experienced greater cognitive decline and had significantly higher levels of tau/ab and p-tau/ab relative to both the CN and PD-MCI - SCC groups.

CONCLUSIONS

Inconsistent implementation of an SCC requirement in PD-MCI classifications may have important implications in terms of the occurrence of PD-MCI and its prognostic value. Classifying PD-MCI only using neuropsychological cut-off criterion, without regard to SCC, may lead to higher rates of PD-MCI. Inclusions of SCC in PD-MCI criteria in newly diagnosed PD participants may strengthen the ability to detect individuals at risk for future cognitive decline, though it is possible that this decline is related to Alzheimer's disease changes rather than worse PD pathology.

Specific Cerebrospinal Fluid SerpinA1 Isoform Pattern in Alzheimer's Disease

SerpinA1 (α1-antitrypsin) is a soluble glycoprotein, the cerebrospinal fluid (CSF) isoforms of which showed disease-specific changes in neurodegenerative disorders that are still unexplored in Alz-heimer’s disease (AD). By means of capillary isoelectric focusing immunoassay, we investigated six serpinA1 isoforms in CSF samples of controls (n = 29), AD-MCI (n = 29), AD-dem (n = 26) and Lewy body disease (LBD, n = 59) patients and correlated the findings with CSF AD core biomarkers (Aβ42/40 ratio, p-tau, t-tau). Four CSF serpinA1 isoforms were differently expressed in AD patients compared to controls and LBD patients, especially isoforms 2 and 4. AD-specific changes were found since the MCI stage and significantly correlated with decreased Aβ42/40 (p < 0.05) and in-creased p-tau and t-tau levels in CSF (p < 0.001). Analysis of serpinA1 isoform provided good di-agnostic accuracy in discriminating AD patients versus controls (AUC = 0.80) and versus LBD patients (AUC = 0.92), with best results in patients in the dementia stage (AUC = 0.97). SerpinA1 isoform expression is altered in AD patients, suggesting a common, albeit disease-specific, in-volvement of serpinA1 in most neurodegenerative disorders.

Recent advances in Lewy body dementia: A comprehensive review

Lewy Body Dementia is the second most frequent neurodegenerative illness proven to cause dementia, after Alzheimer's disease (AD). It is believed to be vastly underdiagnosed, as there is a significant disparity between the number of cases diagnosed clinically and those diagnosed via neuropathology at the time of postmortem autopsy. Strikingly, many of the pharmacologic treatments used to treat behavioral and cognitive symptoms in other forms of dementia exacerbate the symptoms of DLB. Therefore, it is critical to accurately diagnose DLB as these patients require a specific treatment approach. This article focuses on its pathophysiology, risk factors, differentials, and its diverse treatment modalities. In this study, an English language literature search was conducted on Medline, Cochrane, Embase, and Google Scholar till April 2022. The following search strings and Medical Subject Headings (MeSH) terms were used: "Lewy Body Dementia," "Dementia with Lewy bodies," and "Parkinson's Disease Dementia." We explored the literature on Lewy Body Dementia for its epidemiology, pathophysiology, the role of various genes and how they bring about the disease, biomarkers, its differential diagnoses and treatment options.

Alpha synuclein seed amplification assays for diagnosing synucleinopathies: the way forward

Parkinson's disease (PD) is the second most common neurodegenerative disease and the most common synucleinopathy, as alpha-synuclein (α-syn), a prion-like protein, plays an important pathophysiological role in its onset and progression. Although neuropathological changes begin many years before the onset of motor manifestations, diagnosis still relies on the identification of the motor symptoms, which hinders to formulate an early diagnosis. Since α-syn misfolding and aggregation precede clinical manifestations, the possibility to identify these phenomena in PD patients would allow us to recognize the disease at the earliest, premotor phases, as a consequence of the transition from a clinical to a molecular diagnosis.

Seed amplification assays (SAAs) are a group of techniques that currently support the diagnosis of prion subacute encephalopathies, namely Creutzfeldt Jakob disease. These techniques enable the detection of minimal amounts of prions in cerebrospinal fluid (CSF) and other matrices of affected patients. Recently, SAAs have been successfully applied to detect misfolded α-syn in CSF, olfactory mucosa, submandibular gland biopsies, skin and saliva, of patients with PD and other synucleinopathies. In these categories, they can differentiate PD and dementia with Lewy bodies (DLB) from control subjects, even in the prodromal stages of the disease. In terms of differential diagnosis, SAAs satisfactorily differentiated PD, DLB, and multiple system atrophy (MSA) from non-synucleinopathy parkinsonisms. The kinetic analysis of the SAA fluorescence profiles allowed the identification of synucleinopathy-dependent α-syn fibrils conformations, commonly referred to as strains, which have demonstrated diagnostic potential in differentiating among synucleinopathies, especially between Lewy body diseases (PD, DLB) and MSA. In front of these highly promising data, which make the α-syn seeding activity detected by SAAs as the most promising diagnostic biomarker for synucleinopathies, there are still preanalytical and analytical issues, mostly related to the assay standardization, which need to be solved. In this review, we discuss the key findings supporting the clinical application of α-syn SAAs to identify PD and other synucleinopathies, the unmet needs, and future perspectives.

Biomarkers and diagnosis of dementia with Lewy bodies including prodromal: Practical aspects

Dementia with Lewy Bodies (DLB) is a common form of cognitive neurodegenerative disease. More than half of the patients affected are not or misdiagnosed because of the clinical similarity with Alzheimer's disease (AD), Parkinson's disease but also psychiatric diseases such as depression or psychosis. In this review, we evaluate the interest of different biomarkers in the diagnostic process: cerebrospinal fluid (CSF), brain MRI, FP-CIT SPECT, MIBG SPECT, perfusion SPECT, FDG-PET by focusing more specifically on differential diagnosis between DLB and AD. FP-CIT SPECT is of high interest to discriminate DLB and AD, but not at the prodromal stage. Brain MRI has shown differences in group study with lower grey matter concentration of the Insula in prodromal DLB, but its interest in clinical routine is not demonstrated. Among the AD biomarkers (t-Tau, phospho-Tau₁₈₁, Aβ42 and Aβ40) used routinely, t-Tau and phospho-Tau₁₈₁ have shown excellent discrimination whatever the clinical stages severity. CSF Alpha-synuclein assay in the CSF has also an interest in the discrimination between DLB and AD but not in segregation between DLB and healthy elderly subjects. CSF synuclein RT-QuIC seems to be an excellent biomarker but its application in clinical routine remains to be demonstrated, given the non-automation of the process.

Quantification of Brain β-Amyloid Load in Parkinson's Disease With Mild Cognitive Impairment: A PET/MRI Study

Background

Mild cognitive impairment in Parkinson's disease (PD-MCI) is associated with faster cognitive decline and conversion to dementia. There is uncertainty about the role of β-amyloid (Aβ) co-pathology and its contribution to the variability in PD-MCI profile and cognitive progression.

Objective

To study how presence of Aβ affects clinical and cognitive manifestations as well as regional brain volumes in PD-MCI.

Methods

Twenty-five PD-MCI patients underwent simultaneous PET/3T-MRI with [¹⁸F]flutemetamol and a clinical and neuropsychological examination allowing level II diagnosis. We tested pairwise differences in motor, clinical, and cognitive features with Mann–Whitney U test. We calculated [¹⁸F]flutemetamol (FMM) standardized uptake value ratios (SUVR) in striatal and cortical ROIs, and we performed a univariate linear regression analysis between the affected cognitive domains and the mean SUVR. Finally, we investigated differences in cortical and subcortical brain regional volumes with magnetic resonance imaging (MRI).

Results

There were 8 Aβ+ and 17 Aβ- PD-MCI. They did not differ for age, disease duration, clinical, motor, behavioral, and global cognition scores. PD-MCI-Aβ+ showed worse performance in the overall executive domain (p = 0.037). Subcortical ROIs analysis showed significant Aβ deposition in PD-MCI-Aβ+ patients in the right caudal and rostral middle frontal cortex, in precuneus, in left paracentral and pars triangularis (p < 0.0001), and bilaterally in the putamen (p = 0.038). Cortical regions with higher amyloid load correlated with worse executive performances (p < 0.05). Voxel-based morphometry (VBM) analyses showed no between groups differences.

Conclusions

Presence of cerebral Aβ worsens executive functions, but not motor and global cognitive abilities in PD-MCI, and it is not associated with middle-temporal cortex atrophy. These findings, together with the observation of significant proportion of PD-MCI-Aβ-, suggest that Aβ may not be the main pathogenetic determinant of cognitive deterioration in PD-MCI, but it would rather aggravate deficits in domains vulnerable to Parkinson primary pathology.

Analysis of complexity and dynamic functional connectivity based on resting-state EEG in early Parkinson’s disease patients with mild cognitive impairment

To explore the abnormal brain activity of early Parkinson's disease with mild cognitive impairment (ePD-MCI) patients, the study analyzed the dynamic fluctuation of electroencephalogram (EEG) signals and the dynamic change of information communication between EEG signals of ePD-MCI patients. In this study, we recorded resting-state EEG signals of 30 ePD-MCI patients and 37 early Parkinson's disease without mild cognitive impairment (ePD-nMCI) patients. First, we analyzed the difference of the complexity of EEG signals between the two groups. And we found that the complexity in the ePD-MCI group was significantly higher than that in the ePD-nMCI group. Then, by analyzing the dynamic functional network (DFN) topology based on the optimal sliding-window, we found that the temporal correlation coefficients of ePD-MCI patients were lower in the delta and theta bands than those in the ePD-nMCI patients. The temporal characteristic path length of ePD-MCI patients in the alpha band was higher than that of ePD-nMCI patients. In the theta and alpha bands, the temporal small world degrees of ePD-MCI patients were lower than that of patients with ePD-nMCI. In addition, the functional connectivity strength of ePD-MCI patients affected by cognitive impairment was weaker than that of ePD-nMCI patients, and the stability of dynamic functional connectivity network was decreased. This finding may serve as a biomarker to identify ePD-MCI and contribute to the early intervention treatment of ePD-MCI.

Genetic Architecture and Molecular, Imaging and Prodromic Markers in Dementia with Lewy Bodies: State of the Art, Opportunities and Challenges

Dementia with Lewy bodies (DLB) is one of the most common causes of dementia and belongs to the group of α-synucleinopathies. Due to its clinical overlap with other neurodegenerative disorders and its high clinical heterogeneity, the clinical differential diagnosis of DLB from other similar disorders is often difficult and it is frequently underdiagnosed. Moreover, its genetic etiology has been studied only recently due to the unavailability of large cohorts with a certain diagnosis and shows genetic heterogeneity with a rare contribution of pathogenic mutations and relatively common risk factors. The rapid increase in the reported cases of DLB highlights the need for an easy, efficient and accurate diagnosis of the disease in its initial stages in order to halt or delay the progression. The currently used diagnostic methods proposed by the International DLB consortium rely on a list of criteria that comprises both clinical observations and the use of biomarkers. Herein, we summarize the up-to-now reported knowledge on the genetic architecture of DLB and discuss the use of prodromal biomarkers as well as recent promising candidates from alternative body fluids and new imaging techniques.

Machine Learning Driven Profiling of Cerebrospinal Fluid Core Biomarkers in Alzheimer's Disease and Other Neurological Disorders

Amyloid-beta (Aβ) 42/40 ratio, tau phosphorylated at threonine-181 (p-tau), and total-tau (t-tau) are considered core biomarkers for the diagnosis of Alzheimer’s disease (AD). The use of fully automated biomarker assays has been shown to reduce the intra- and inter-laboratory variability, which is a critical factor when defining cut-off values. The calculation of cut-off values is often influenced by the composition of AD and control groups. Indeed, the clinically defined AD group may include patients affected by other forms of dementia, while the control group is often very heterogeneous due to the inclusion of subjects diagnosed with other neurological diseases (OND). In this context, unsupervised machine learning approaches may overcome these issues providing unbiased cut-off values and data-driven patient stratification according to the sole distribution of biomarkers. In this work, we took advantage of the reproducibility of automated determination of the CSF core AD biomarkers to compare two large cohorts of patients diagnosed with different neurological disorders and enrolled in two centers with established expertise in AD biomarkers. We applied an unsupervised Gaussian mixture model clustering algorithm and found that our large series of patients could be classified in six clusters according to their CSF biomarker profile, some presenting a typical AD-like profile and some a non-AD profile. By considering the frequencies of clinically defined OND and AD subjects in clusters, we subsequently computed cluster-based cut-off values for Aβ42/Aβ40, p-tau, and t-tau. This approach promises to be useful for large-scale biomarker studies aimed at providing efficient biochemical phenotyping of neurological diseases.

Application of Cerebrospinal Fluid AT(N) Framework on the Diagnosis of AD and Related Cognitive Disorders in Chinese Han Population

Background

Studies concerning the impact of the AT(N) framework on diagnostic capability in the dementia population are lacking. We aimed to explore the diagnostic application of CSF AT(N) framework in clinical routines of Alzheimer's disease (AD) as well as differential diagnosis of other cognitive diseases in the Chinese Han population.

Patients and Methods

A total of 137 patients with cognitive disorders received CSF tests of Aβ₄₂, t-tau and p-tau₁₈₁. Their CSF biomarker results were categorized and interpreted by the AT(N) framework. Neurologists provided a diagnosis both pre- and post-CSF biomarker disclosure with corresponding diagnostic confidence.

Results

The total initial diagnosis included 79 patients with AD and 58 patients with non-AD (NAD). The results of CSF biomarkers led to a diagnostic change of 28% in the cohort. Approximately 81.5% (n=53) of 65 patients whose CSF biomarker showed an underlying AD pathology were finally diagnosed as AD, with an increase of 17.5% in diagnostic confidence. Thirty-seven CSF results indicating NAD pathologic changes contributed to an exclusion of AD in 56.8% (n=21) of the patients along with a modest increase of 9.8% in average confidence. Thirty-five patients with normal CSF biomarkers maintained the diagnosis of NAD in 68.6% (n=24) of the group, leading to a slight elevation of 7.6% in confidence.

Conclusion

We found that the presence of amyloid pathology (A+) is contributable to diagnosing AD and improving confidence. On occasion of negative amyloid pathology (A-), with or without tau pathology, gaining uncertainty of the primary AD diagnosis would diminish the corresponding confidence. To the best of our knowledge, this is the first study performed in the Chinese Han population with cognitive disorders that explores the clinical capability of CSF AT(N) framework in a quantitative way.