Exploring the potential of fully automated LUMIPULSE G plasma assays for detecting Alzheimer's disease pathology.

BACKGROUND: LUMIPULSE G-automated immunoassays represent a widely used method for the quantification of Alzheimer's disease (AD) biomarkers in the cerebrospinal fluid (CSF). Less invasive blood-based markers confer a promising tool for AD diagnosis at prodromal stages (mild cognitive impairment (MCI)). Highly sensitive assays for the quantification of amyloid-beta (Aß) and phosphorylated Tau-181 (p-Tau181) in the blood are showing promising results. In this study, we evaluated the clinical performance of the recently available fully automated LUMIPULSE plasma marker assays for detecting brain AD pathology and for predicting progression from MCI to AD dementia stage. METHODS: A retrospective exploratory cohort of 138 individuals (22 neurological controls [NC], 72 MCI, and 44 AD dementia patients) was included. Data regarding baseline CSF concentrations of Aß42, Aß40, t-Tau, and p-Tau181 was available and used to establish the presence of AD brain pathology. Baseline Aß42, Aß40, and p-Tau181 concentrations were determined in stored plasma samples using high-throughput fully automated LUMIPULSE assays. Progression from MCI to AD dementia was evaluated during follow-up (mean 6.4 ± 2.5 years). Moreover, a prospective validation cohort of 72 individuals with memory complaints underwent AD biomarker quantification, closely mirroring typical clinical practice. This cohort aimed to confirm the study's main findings. RESULTS: In the exploratory cohort, correlations between CSF and plasma were moderate for p-Tau181 (ρ = 0.61, p < 0.001) and weak for Aß42/Aß40 ratio (ρ = 0.39, p < 0.001). Plasma p-Tau181 and p-Tau181/Aß42 concentrations were significantly increased while Aß42/Aß40 was significantly decreased (p < 0.001) in patients with AD dementia and prodromal AD, as well as in individuals with CSF abnormal amyloid concentrations (A +). Plasma p-Tau181 showed a robust performance in differentiating patients clinically diagnosed as AD (AUC = 0.89; 95% CI 0.83-0.94); A + vs. A - (AUC = 0.84, 95% CI 0.77-0.91) and also in predicting conversion to AD dementia in MCI patients (AUC = 0.89, 95% CI 0.81-0.96). When tested in the validation cohort, plasma p-Tau181 displayed 83.3% of the overall percentage of agreement according to amyloid status. CONCLUSIONS: Our results show that the measurement of p-Tau181 in plasma has great potential as a non-invasive prognostic screening tool for implementation in a clinical setting.

Montreal Cognitive Assessment in Mild Cognitive Impairment: Relationship with Cerebrospinal Fluid Biomarkers and Conversion to Dementia.

BACKGROUND: Mild cognitive impairment (MCI) is considered a prodromal state of dementia. Abnormal values of cerebrospinal fluid Alzheimer's disease biomarkers (CSF-AD-b) have been associated with a higher risk of conversion to dementia (due to Alzheimer's disease), but studies evaluating the ability of Montreal Cognitive Assessment (MoCA) in this task are lacking. OBJECTIVE: This study aims to investigate the relationship between MoCA and CSF-AD-b, as well as the ability of those tools to predict conversion to dementia. METHODS: Taking advantage of our MCI cohort with biological characterization on longitudinal follow-up (180 patients followed for 62.6 months during which 41.3% converted), we computed MoCA and MMSE z-scores, using Portuguese normative data. The performance in MoCA z-score was correlated with CSF-AD-b and the relative time to conversion and risk according to baseline characteristics were analyzed using Kaplan-Meier analysis and Cox regression models. RESULTS: MoCA z-scores were correlated with Aß42 (p = 0.026), t-tau (p = 0.033), and p-tau (p = 0.01). Impaired MMSE (p < 0.001) and MoCA z-scores (p = 0.019), decreased Aß42 (p < 0.001) and increased t-tau (p < 0.001) and p-tau (p < 0.001) were associated with shorter estimated time of conversion. Aß42 (p < 0.001) and MMSE z-scores (p = 0.029) were independent predictors of conversion. For those with at least 9 years of education, MoCA z-score (p = 0.004) (but not MMSE) was an independent predictor of conversion as well as Aß42. CONCLUSIONS: This study confirms the role of CSF-AD-b, namely Aß42, in predicting conversion from MCI to dementia and suggests the utility of MoCA in predicting conversion in highly educated subjects, supporting its use in the evaluation of MCI patients.

Serum Neurofilament Light Chain in the Diagnostic Evaluation of Patients with Cognitive Symptoms in the Neurological Consultation of a Tertiary Center.

Serum light-chain neurofilaments (sNfL) have been investigated as a potential minimally invasive biomarker that could help in the diagnosis of patients with cognitive symptoms. We assessed the correlation between sNfL and cerebrospinal fluid (CSF) biomarkers (sNfL versus CSF NfL, ρ= 0.70, p < 0.001), the performance of sNfL in distinguishing controls from patients (controls versus frontotemporal dementia, area under curve 0.86), and sNfL differences in mild cognitive impairment according to amyloid-ß (Aß) deposition (Aß versus non-Aß, p = 0.017). Our results support the role of this biomarker in the screening and risk stratification of patients followed in a neurological consultation of a tertiary center.

Blood biomarkers in mild cognitive impairment patients: Relationship between analytes and progression to Alzheimer disease dementia.

BACKGROUND AND PURPOSE: Blood-based biomarkers are promising tools for the diagnosis of Alzheimer disease (AD) at prodromal stages (mild cognitive impairment [MCI]) and are hoped to be implemented as screening tools for patients with cognitive complaints. In this work, we evaluated the potential of peripheral neurological biomarkers to predict progression to AD dementia and the relation between blood and cerebrospinal fluid (CSF) AD markers in MCI patients referred from a general neurological department. METHODS: A group of 106 MCI patients followed at the Neurology Department of Coimbra University Hospital was included. Data regarding baseline neuropsychological evaluation, CSF levels of amyloid ß 42 (Aß42), Aß40, total tau (t-Tau), and phosphorylated tau 181 (p-Tau181) were available for all the patients. Aß42, Aß40, t-Tau, p-Tau181, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) levels were determined in baseline stored serum and plasma samples by commercial SiMoA (Single Molecule Array) assays. Progression from MCI to AD dementia was assessed at follow-up (mean = 5.8 ± 3.4 years). RESULTS: At baseline, blood markers NfL, GFAP, and p-Tau181 were significantly increased in patients who progressed to AD at follow-up (p < 0.001). In contrast, plasma Aß42/40 ratio and t-Tau showed no significant differences between groups. NfL, GFAP, and p-Tau181 demonstrated good diagnostic accuracy to identify progression to AD dementia (area under the curve [AUC] = 0.81, 0.80, and 0.76, respectively), which improved when combined (AUC = 0.89). GFAP and p-Tau181 were correlated with CSF Aß42. Association of p-Tau181 with NfL was mediated by GFAP, with a significant indirect association of 88% of the total effect. CONCLUSIONS: Our findings highlight the potential of combining blood-based GFAP, NfL, and p-Tau181 to be applied as a prognostic tool in MCI.

Alzheimer's Disease Diagnosis Based on the Amyloid, Tau, and Neurodegeneration Scheme (ATN) in a Real-Life Multicenter Cohort of General Neurological Centers.

BACKGROUND: The ATN scheme was proposed as an unbiased biological characterization of the Alzheimer's disease (AD) spectrum, grouping biomarkers into three categories: brain Amyloidosis-A, Tauopathy-T, Neurodegeneration-N. Although this scheme was mainly recommended for research, it is relevant for diagnosis. OBJECTIVE: To evaluate the ATN scheme performance in real-life cohorts reflecting the inflow of patients with cognitive complaints and different underlying disorders in general neurological centers. METHODS: We included patients (n = 1,128) from six centers with their core cerebrospinal fluid-AD biomarkers analyzed centrally. A was assessed through Aß42/Aß40, T through pTau-181, and N through tTau. Association between demographic features, clinical diagnosis at baseline/follow-up and ATN profiles was assessed. RESULTS: The prevalence of ATN categories was: A-T-N-: 28.3%; AD continuum (A + T-/+N-/+): 47.8%; non-AD (A- plus T or/and N+): 23.9%. ATN profiles prevalence was strongly influenced by age, showing differences according to gender, APOE genotype, and cognitive status. At baseline, 74.6% of patients classified as AD fell in the AD continuum, decreasing to 47.4% in mild cognitive impairment and 42.3% in other neurodegenerative conditions. At follow-up, 41% of patients changed diagnosis, and 92% of patients that changed to AD were classified within the AD continuum. A + was the best individual marker for predicting a final AD diagnosis, and the combinations A + T+ (irrespective of N) and A + T+N+ had the highest overall accuracy (83%). CONCLUSION: The ATN scheme is useful to guide AD diagnosis in real-life neurological centers settings. However, it shows a lack of accuracy for patients with other types of dementia. In such cases, the inclusion of other markers specific for non-AD proteinopathies could be an important aid to the differential diagnosis.

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.

Serum neurofilament light chain as a surrogate of cognitive decline in sporadic and familial frontotemporal dementia.

BACKGROUND AND PURPOSE: Neurofilament light chain (NfL) has recently been proposed as a promising biomarker in frontotemporal dementia (FTD). We investigated the correlation of both cerebrospinal fluid (CSF) and serum NfL with detailed neuropsychological data and cognitive decline in a cohort of sporadic and familial FTD. METHODS: CSF and serum NfL, as well as conventional CSF Alzheimer's disease (AD) biomarkers (Aß42, t-Tau, p-Tau181), were determined in 63 FTD patients (30 sporadic-FTD, 20 with progranulin (GRN) mutations [FTD-GRN], 13 with chromosome 9 open reading frame 72 [C9orf72] expansions [C9orf72-FTD]), 37 AD patients, and 31 neurologic controls. Serum NfL was also quantified in 37 healthy individuals. Correlations between baseline CSF and serum NfL levels, standardized neuropsychological tests, and the rate of cognitive decline in FTD patients were assessed. RESULTS: CSF and serum NfL presented with significantly higher levels in FTD than in AD patients and both control groups. Within FTD subtypes, genetic cases, and particularly FTD-GRN, had higher CSF and serum NfL levels. Significant correlations between NfL levels and overall cognitive function, abstract reasoning (CSF and serum), executive functions, memory, and language (serum) were found. A relationship between increased baseline CSF and serum NfL and a decay in cognitive performance over time was also observed. CONCLUSIONS: Our findings highlight the potential of serum NfL as a useful surrogate end point of disease severity in upcoming targeted treatments.

Clinical validation of the Lumipulse G cerebrospinal fluid assays for routine diagnosis of Alzheimer's disease.

BACKGROUND: Ongoing efforts within the Alzheimer's disease (AD) field have focused on improving the intra- and inter-laboratory variability for cerebrospinal fluid (CSF) biomarkers. Fully automated assays offer the possibility to eliminate sample manipulation steps and are expected to contribute to this improvement. Recently, fully automated chemiluminescence enzyme immunoassays for the quantification of all four AD biomarkers in CSF became available. The aims of this study were to (i) evaluate the analytical performance of the Lumipulse G ß-Amyloid 1-42 (restandardized to Certified Reference Materials), ß-Amyloid 1-40, total Tau, and pTau 181 assays on the fully automated LUMIPULSE G600II; (ii) compare CSF biomarker results of the Lumipulse G assays with the established manual ELISA assays (INNOTEST®) from the same company (Fujirebio); and (iii) establish cut-off values and the clinical performance of the Lumipulse G assays for AD diagnosis. METHODS: Intra- and inter-assay variation was assessed in CSF samples with low, medium, and high concentrations of each parameter. Method comparison and clinical evaluation were performed on 40 neurological controls (NC) and 80 patients with a diagnosis of probable AD supported by a follow-up ≥ 3 years and/or positive amyloid PET imaging. A small validation cohort of 10 NC and 20 AD patients was also included to validate the cut-off values obtained on the training cohort. RESULTS: The maximal observed intra-assay and inter-assay coefficients of variation (CVs) were 3.25% and 5.50%, respectively. Method comparisons revealed correlation coefficients ranging from 0.89 (for Aß40) to 0.98 (for t-Tau), with those for Aß42 (0.93) and p-Tau (0.94) in-between. ROC curve analysis showed area under the curve values consistently above 0.85 for individual biomarkers other than Aß40, and with the Aß42/40, Aß42/t-Tau, and Aß42/p-Tau ratios outperforming Aß42. Validation of the cut-off values in the independent cohort showed a sensitivity ranging from 75 to 95% and a specificity of 100%. The overall percentage of agreement between Lumipulse and INNOTEST was very high (> 87.5%). CONCLUSIONS: The Lumipulse G assays show a very good analytical performance that makes them well-suited for CSF clinical routine measurements. The good clinical concordance between the Lumipulse G and INNOTEST assays facilitates the implementation of the new method in routine practice.