Serum Amyloid Biomarkers, Tau Protein and YKL-40 Utility in Detection, Differential Diagnosing, and Monitoring of Dementia

Introduction: The diagnosis and treatment of dementia is one of the greatest challenges in contemporary health care. The widespread use of dementia biomarkers would improve the quality of life of patients and reduce the economic costs of the disease. The aim of the study was to evaluate the usefulness of proteins related to the Alzheimer's disease pathogenesis—amyloid beta isoform (Aβ) and total tau protein (t-tau), as well as the quite recently discovered marker YKL-40 in the most common types of dementia.Methods: 60 dementia (AD—Alzheimer's disease, VaD—vascular dementia, MxD—mixed dementia) and 20 cognitively normal subjects over 60 years old were examined. Subjects with dementia of etiology different than AD or VaD and with neoplastic or chronic inflammatory diseases were excluded. Concentrations of Aβ40, Aβ42, t-tau, and YKL-40 were measured in serum using ELISA kits on admission and after 4 weeks of inpatient treatment. ANOVA and Tukey's test or Dunn's test were used to perform comparison tests between groups. Correlations were measured using Pearson's coefficient. Biomarker diagnostic utility was assessed with ROC analysis.Results: YKL-40 differentiates between cognitively normal and mild dementia patients with 85% sensitivity and specificity and t-tau with 72% sensitivity and 70% specificity. YKL-40 and t-tau concentrations correlate with each other and with the severity of clinically observed cognitive decline.Conclusions: YKL-40 is a sensitive and specific biomarker of early dementia and, to a lesser extent, of dementia progression, however, many comorbidities may influence its levels. In such conditions, less specific but still reliable t-tau may serve as an alternative marker. Obtained results did not confirm the diagnostic utility of amyloid biomarkers.

Hyperconnectivity of Self-Referential Network as a Predictive Biomarker of the Progression of Alzheimer’s Disease

Background: Self-referential processing is associated with the progression of Alzheimer’s disease (AD), and cerebrospinal fluid (CSF) proteins have become accepted biomarkers of AD. Objective: Our objective in this study was to focus on the relationships between the self-referential network (SRN) and CSF pathology in AD-spectrum patients. Methods: A total of 80 participants, including 20 cognitively normal, 20 early mild cognitive impairment (EMCI), 20 late MCI (LMCI), and 20 AD, were recruited for this study. Independent component analysis was used to explore the topological SRN patterns, and the abnormalities of this network were identified at different stages of AD. Finally, CSF pathological characteristics (i.e., CSF Aβ, t-tau, and p-tau) that affected the abnormalities of the SRN were further determined during the progression of AD. Results: Compared to cognitively normal subjects, AD-spectrum patients (i.e., EMCI, LMCI, and AD) showed a reversing trend toward an association between CSF pathological markers and the abnormal SRN occurring during the progression of AD. However, a certain disease state (i.e., the present LMCI) with a low concentration of CSF tau could evoke more hyperconnectivity of the SRN than other patients with progressively increasing concentrations of CSF tau (i.e., EMCI and AD), and this fluctuation of CSF tau was more sensitive to the hyperconnectivity of the SRN than the dynamic changes of CSF Aβ. Conclusion: The integrity of the SRN was closely associated with CSF pathological characteristics, and these findings support the view that the hyperconnectivity of the SRN will play an important role in monitoring the progression of the pre-dementia state to AD.

Blinded Clinical Evaluation for Dementia of Alzheimer’s Type Classification Using FDG-PET: A Comparison Between Feature-Engineered and Non-Feature-Engineered Machine Learning Methods

Background: Advanced machine learning methods can aid in the identification of dementia risk using neuroimaging-derived features including FDG-PET. However, to enable the translation of these methods and test their usefulness in clinical practice, it is crucial to conduct independent validation on real clinical samples, which has yet to be properly delineated in the current literature. Objective: In this paper, we present our efforts to enable such clinical translational through the evaluation and comparison of two machine-learning methods for discrimination between dementia of Alzheimer’s type (DAT) and Non-DAT controls. Methods: FDG-PET-based dementia scores were generated on an independent clinical sample whose clinical diagnosis was blinded to the algorithm designers. A feature-engineered approach (multi-kernel probability classifier) and a non-feature-engineered approach (3D convolutional neural network) were analyzed. Both classifiers were pre-trained on cognitively normal subjects as well as subjects with DAT. These two methods provided a probabilistic dementia score for this previously unseen clinical data. Performance of the algorithms were compared against ground-truth dementia rating assessed by experienced nuclear physicians. Results: Blinded clinical evaluation on both classifiers showed good separation between the cognitively normal subjects and the patients diagnosed with DAT. The non-feature-engineered dementia score showed higher sensitivity among subjects whose diagnosis was in agreement between the machine-learning models, while the feature-engineered approach showed higher specificity in non-consensus cases. Conclusion: In this study, we demonstrated blinded evaluation using data from an independent clinical sample for assessing the performance in DAT classification models in a clinical setting. Our results showed good generalizability for two machine-learning approaches, marking an important step for the translation of pre-trained machine-learning models into clinical practice.

Decorin is an early CSF biomarker of Alzheimer’s Aβ amyloidosis

Alzheimer’s disease (AD) is characterized by impaired protein homeostasis leading to amyloid-beta (Aβ) amyloidosis. Here, we show that autophagy is similarly inhibited in AD brains and App knock-in AD mouse models. To determine how pathologies translate to cerebrospinal fluid (CSF), label-free mass spectrometry of mouse CSF was used. This identified autophagy-related extracellular matrix (ECM) protein decorin as significantly and similarly increased in App knock-in mice and cognitively normal human subjects with abnormal CSF-amyloid. Notably, a switch from negative to positive correlation of CSF-decorin and CSF-amyloid occurs in cognitively normal subjects when CSF-amyloid becomes abnormal, indicating an early change in CSF-decorin induced by Aβ amyloidosis. In App knock-in mice increased CSF-decorin correlated with accentuated decorin expression in choroid plexus and decreased interneuronal decorin. Furthermore, decorin activates neuronal autophagy-lysosomal system by enhancing lysosomal degradation. Therefore, decorin is a potential CSF biomarker that reflects ECM and autophagy alterations in early AD Aβ amyloidosis.

Association of cerebral blood flow with myelin content in cognitively unimpaired adults

BackgroundMyelin loss and cerebral blood flow (CBF) decline are central features of several neurodegenerative diseases. Myelin maintenance through oligodendrocyte metabolism is an energy-demanding process, so that myelin homeostasis is particularly sensitive to hypoxia, hypoperfusion or ischaemia. However, in spite of its central importance, little is known about the association between blood supply and myelin integrity.ObjectiveTo assess associations between cortical and subcortical CBF, and subcortical myelin content, in critical brain white matter regions.Materials and methodsMRI was performed on a cohort of 67 cognitively unimpaired adults. Using advanced MRI methodology, we measured whole-brain longitudinal and transverse relaxation rates (R1 and R2), sensitive but non-specific markers of myelin content, and myelin water fraction (MWF), a direct surrogate of myelin content, as well as regional CBF, from each of these participants.ResultsAll quantitative relaxometry metrics were positively associated with CBF in all brain regions evaluated. These associations between MWF or R1 and CBF, and, to a lesser extent, between R2 and CBF, were statistically significant in most brain regions examined, indicating that lower regional cortical or subcortical CBF corresponds to a decrease in local subcortical myelin content. Finally, all relaxometry metrics exhibited a quadratic, inverted U-shaped, association with age; this is attributed to the development of myelination from young to middle age, followed by progressive loss of myelin in later years.ConclusionsIn this first study examining the association between local blood supply and myelin integrity, we found that myelin content declines with CBF across a wide age range of cognitively normal subjects.

Validation of the Argentine version of the Montreal Cognitive Assessment Test (MOCA): A screening tool for Mild Cognitive Impairment and Mild Dementia in Elderly

ABSTRACT. The MoCA is a brief useful test to diagnose mild cognitive impairment (MCI) and mild dementia (MD). To date, no Argentine cross-cultural adapted validations of the Spanish version have been reported. Objective: To validate the MoCA in the elderly and study its usefulness in MCI and MD. Methods: This study included 399 individuals over 60 years old evaluated in the Cognitive-Behavioral Department (2017-2018). Patients with<3 years of education, sensory disturbances, psychiatric disorders, or moderate-severe dementia were excluded. The control group comprised cognitively normal subjects. Participants were classified according to neuropsychological assessment and clinical standard criteria into Control, MCI or MD groups. A locally adapted MoCA (MOCA-A) was administered to the patients and controls. Results: Mean educational level was 10.34 years (SD 3.5 years). MoCA-A score differed significantly among groups (p<0.0001). MoCA-A performance correlated with educational level (r: 0.406 p<0.00001). Adopting a cut-off score ≥25 (YI=0.55), the sensitivity for MCI was 84.8% and for MD 100%, with specificity of 69.7%. When adding a single point to the score in patients with ≤12 years of education, the specificity of the test reached 81%. Conclusion: The MoCA-A is an accurate reliable screening test for MCI and MD in Argentina.

Elevated neurofilament light chain in plasma is associated with reduced right hippocampal and amygdala volume in Alzheimer's patients

Background Plasma neurofilament light (NfL) levels have been considered as an especially promising biomarker for dementia, however, the mechanism of NfL regulating cognition is not very clear. Methods 43 amnesic mild cognitive impairment(aMCI), 35 Alzheimer’s disease (AD) and 30 cognitively normal subjects were recruited. Plasma NfL levels were examined by the Single Molecule array (Simoa) technique; the volumes of the hippocampus and amygdala were calculated and compared by T1-weighted MRI; and cognitive function was assessed by the Beijing version of the Montreal Cognitive Assessment (MoCA) Results Our results showed significantly increased plasma NfL levels in AD group (29.42 pg/ml) compared to aMCI(15.92 pg/ml) group and normal (12.85 pg/ml) group (both p < 0.001), while there was no statistical difference (p>0.05) between aMCI group and normal group. And the results of partial correlation analysis showed that plasma NfL levels were negatively correlated (p<0.05)with MoCA total score (r=-0.415, p=0.013), right hippocampal volume(r=-0.335,p=0.036) and right amygdala volume(r=-0.337, p=0.048). Conclusions NfL in plasma of AD patients is significantly increased, and the protein is related to atrophy of right hippocampus and right amygdala.