scholarly journals Plasma contact factors as novel biomarkers for diagnosing Alzheimer’s disease

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Jung Eun Park ◽  
Do Sung Lim ◽  
Yeong Hee Cho ◽  
Kyu Yeong Choi ◽  
Jang Jae Lee ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Stage ◽  
Clinical Stage ◽  
Area Under The Curve ◽  
Contact System ◽  
Plasma Diagnostic ◽  
Vascular Abnormalities ◽  
Prodromal Ad ◽  
Novel Biomarkers

Abstract Background Alzheimer’s disease (AD) is the most common cause of dementia and most of AD patients suffer from vascular abnormalities and neuroinflammation. There is an urgent need to develop novel blood biomarkers capable of diagnosing Alzheimer’s disease (AD) at very early stage. This study was performed to find out new accurate plasma diagnostic biomarkers for AD by investigating a direct relationship between plasma contact system and AD. Methods A total 101 of human CSF and plasma samples from normal and AD patients were analyzed. The contact factor activities in plasma were measured with the corresponding specific peptide substrates. Results The activities of contact factors (FXIIa, FXIa, plasma kallikrein) and FXa clearly increased and statistically correlated as AD progresses. We present here, for the first time, the FXIIa cut-off scores to as: > 26.3 U/ml for prodromal AD [area under the curve (AUC) = 0.783, p < 0.001] and > 27.2 U/ml for AD dementia (AUC = 0.906, p < 0.001). We also describe the cut-off scores from the ratios of CSF Aβ1–42 versus the contact factors. Of these, the representative ratio cut-off scores of Aβ1–42/FXIIa were to be: < 33.8 for prodromal AD (AUC = 0.965, p < 0.001) and < 27.44 for AD dementia (AUC = 1.0, p < 0.001). Conclusion The activation of plasma contact system is closely associated with clinical stage of AD, and FXIIa activity as well as the cut-off scores of CSF Aβ1–42/FXIIa can be used as novel accurate diagnostic AD biomarkers.

scholarly journals Detection of mild cognitive impairment and early stage dementia with an audio-recorded cognitive scale

2013 ◽  
Vol 25 (8) ◽  
pp. 1325-1333 ◽  
Author(s):  
Margaret C. Sewell ◽  
Xiaodong Luo ◽  
Judith Neugroschl ◽  
Mary Sano
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Verbal Memory ◽  
Early Stage ◽  
Neuropsychological Testing ◽  
Area Under The Curve ◽  
Cognitive Domain ◽  
Screening Measures

ABSTRACTBackground: Physicians often miss diagnosis of mild cognitive impairment (MCI) or early dementia and screening measures can be insensitive to very mild impairments. Other cognitive assessments may take too much time or be frustrating to seniors. This study examined the ability of an audio-recorded scale, developed in Australia, to detect MCI or mild Alzheimer's disease (AD) and compared cognitive domain-specific performance on the audio-recorded scale to in-person battery and common cognitive screens.Method: Seventy-six patients from the Mount Sinai Alzheimer's Disease Research Center were recruited. Patients were aged 75 years or older, with clinical diagnosis of AD or MCI (n = 51) or normal control (n = 25). Participants underwent in-person neuropsychological testing followed by testing with the audio-recorded cognitive screen (ARCS).Results: ARCS provided better discrimination between normal and impaired elderly individuals than either the Mini-Mental State Examination or the clock drawing test. The in-person battery and ARCS analogous variables were significantly correlated, most in the 0.4 to 0.7 range, including verbal memory, executive function/attention, naming, and verbal fluency. The area under the curve generated from the receiver operating characteristic curves indicated high and equivalent discrimination for ARCS and the in-person battery (0.972 vs. 0.988; p = 0.23).Conclusion: The ARCS demonstrated better discrimination between normal controls and those with mild deficits than typical screening measures. Performance on cognitive domains within the ARCS was well correlated with the in-person battery. Completion of the ARCS was accomplished despite mild difficulty hearing the instructions even in very elderly participants, indicating that it may be a useful measure in primary care settings.

Performance of Validated MicroRNA Biomarkers for Alzheimer’s Disease in Mild Cognitive Impairment

2020 ◽  
Vol 78 (1) ◽  
pp. 245-263
Author(s):  
Ursula S. Sandau ◽  
Jack T. Wiedrick ◽  
Sierra J. Smith ◽  
Trevor J. McFarland ◽  
Theresa A. Lusardi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Early Stage ◽  
Linear Trend ◽  
Area Under The Curve ◽  
Classification Performance ◽  
T Tau ◽  
Median Expression

Background: Cerebrospinal fluid (CSF) microRNA (miRNA) biomarkers of Alzheimer’s disease (AD) have been identified, but have not been evaluated in prodromal AD, including mild cognitive impairment (MCI). Objective: To assess whether a set of validated AD miRNA biomarkers in CSF are also sensitive to early-stage pathology as exemplified by MCI diagnosis. Methods: We measured the expression of 17 miRNA biomarkers for AD in CSF samples from AD, MCI, and cognitively normal controls (NC). We then examined classification performance of the miRNAs individually and in combination. For each miRNA, we assessed median expression in each diagnostic group and classified markers as trending linearly, nonlinearly, or lacking any trend across the three groups. For trending miRNAs, we assessed multimarker classification performance alone and in combination with apolipoprotein E ɛ4 allele (APOE ɛ4) genotype and amyloid-β42 to total tau ratio (Aβ42:T-Tau). We identified predicted targets of trending miRNAs using pathway analysis. Results: Five miRNAs showed a linear trend of decreasing median expression across the ordered diagnoses (control to MCI to AD). The trending miRNAs jointly predicted AD with area under the curve (AUC) of 0.770, and MCI with AUC of 0.705. Aβ42:T-Tau alone predicted MCI with AUC of 0.758 and the AUC improved to 0.813 (p = 0.051) after adding the trending miRNAs. Multivariate correlation of the five trending miRNAs with Aβ42:T-Tau was weak. Conclusion: Selected miRNAs combined with Aβ42:T-Tau improved classification performance (relative to protein biomarkers alone) for MCI, despite a weak correlation with Aβ42:T-Tau. Together these data suggest that that these miRNAs carry novel information relevant to AD, even at the MCI stage. Preliminary target prediction analysis suggests novel roles for these biomarkers.

scholarly journals Speech- and Language-Based Classification of Alzheimer’s Disease: A Systematic Review

2022 ◽  
Vol 9 (1) ◽  
pp. 27
Author(s):  
Inês Vigo ◽  
Luis Coelho ◽  
Sara Reis
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Best Practices ◽  
Early Stage ◽  
Low Cost ◽  
Clinical Stage ◽  
Invasive Procedure ◽  
The Impact

Background: Alzheimer’s disease (AD) has paramount importance due to its rising prevalence, the impact on the patient and society, and the related healthcare costs. However, current diagnostic techniques are not designed for frequent mass screening, delaying therapeutic intervention and worsening prognoses. To be able to detect AD at an early stage, ideally at a pre-clinical stage, speech analysis emerges as a simple low-cost non-invasive procedure. Objectives: In this work it is our objective to do a systematic review about speech-based detection and classification of Alzheimer’s Disease with the purpose of identifying the most effective algorithms and best practices. Methods: A systematic literature search was performed from Jan 2015 up to May 2020 using ScienceDirect, PubMed and DBLP. Articles were screened by title, abstract and full text as needed. A manual complementary search among the references of the included papers was also performed. Inclusion criteria and search strategies were defined a priori. Results: We were able: to identify the main resources that can support the development of decision support systems for AD, to list speech features that are correlated with the linguistic and acoustic footprint of the disease, to recognize the data models that can provide robust results and to observe the performance indicators that were reported. Discussion: A computational system with the adequate elements combination, based on the identified best-practices, can point to a whole new diagnostic approach, leading to better insights about AD symptoms and its disease patterns, creating conditions to promote a longer life span as well as an improvement in patient quality of life. The clinically relevant results that were identified can be used to establish a reference system and help to define research guidelines for future developments.

scholarly journals Sleep-Based Interventions in Alzheimer’s Disease: Promising Approaches from Prevention to Treatment along the Disease Trajectory

2021 ◽  
Vol 14 (4) ◽  
pp. 383
Author(s):  
Susanna Cordone ◽  
Serena Scarpelli ◽  
Valentina Alfonsi ◽  
Luigi De De Gennaro ◽  
Maurizio Gorgoni
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Sleep Disorders ◽  
Sleep Disturbances ◽  
Early Stage ◽  
Clinical Stage ◽  
Nrem Sleep ◽  
Behavioral Strategies ◽  
Healthy Elderly ◽  
Obstructive Sleep

The multifactorial nature of Alzheimer’s disease (AD) has led scientific researchers to focus on the modifiable and treatable risk factors of AD. Sleep fits into this context, given the bidirectional relationship with AD confirmed by several studies over the last years. Sleep disorders appear at an early stage of AD and continue throughout the entire course of the pathology. Specifically, sleep abnormalities, such as more fragmented sleep, increase in time of awakenings, worsening of sleep quality and primary sleep disorders raise with the severity and progression of AD. Intervening on sleep, therefore, means acting both with prevention strategies in the pre-clinical phase and with treatments during the course of the disease. This review explores sleep disturbances in the different stages of AD, starting from the pre-clinical stage. Particular attention is given to the empirical evidence investigating obstructive sleep apnea (OSA) disorder and the mechanisms overlapping and sharing with AD. Next, we discuss sleep-based intervention strategies in the healthy elderly population, mild cognitive impairment (MCI) and AD patients. We mention interventions related to behavioral strategies, combination therapies, and bright light therapy, leaving extensive space for new and raising evidence on continuous positive air pressure (CPAP) treatment effectiveness. Finally, we clarify the role of NREM sleep across the AD trajectory and consider the most recent studies based on the promising results of NREM sleep enhancement, which use innovative experimental designs and techniques.

scholarly journals Cats and Apples: Semantic Fluency Performance for Living Things Identifies Patients with Very Early Alzheimer’s Disease

2020 ◽  
Author(s):  
Sabine Krumm ◽  
Manfred Berres ◽  
Sasa L Kivisaari ◽  
Andreas U Monsch ◽  
Julia Reinhardt ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Stage ◽  
Memory Performance ◽  
Area Under The Curve ◽  
Disease Status ◽  
Semantic Fluency ◽  
Operating Characteristics ◽  
Living Things ◽  
Early Alzheimer’S Disease

Abstract Objective: Reduced semantic memory performance is a known neuropsychological marker of very early Alzheimer’s disease (AD), but the task format that best predicts disease status is an open question. The present study aimed to identify the semantic fluency task and measure that best discriminates early-stage AD patients (PATs) from cognitively healthy controls. Method: Semantic fluency performance for animals, fruits, tools, and vehicles was assessed in 70 early-stage AD PATs and 67 cognitively healthy participants. Logistic regressions and receiver operating characteristics were calculated for five total score semantic fluency measures. Results: Compared with all other measures, living things (i.e., total correct animals + total correct fruits) achieved highest z-statistics, highest area under the curve and smallest difference between the upper and lower 95% confidence intervals. Conclusion: Living things total correct is a powerful tool to detect the earliest signs of incipient AD.

scholarly journals Phosphorylated tau181 in plasma as a potential biomarker for Alzheimer’s disease in adults with Down syndrome

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Alberto Lleó ◽  
Henrik Zetterberg ◽  
Jordi Pegueroles ◽  
Thomas K. Karikari ◽  
María Carmona-Iragui ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Down Syndrome ◽  
Single Molecule ◽  
Area Under The Curve ◽  
Imaging Biomarkers ◽  
Potential Biomarker ◽  
Prodromal Ad ◽  
Asymptomatic Individuals ◽  
The Relationship

AbstractPlasma tau phosphorylated at threonine 181 (p-tau181) predicts Alzheimer’s disease (AD) pathology with high accuracy in the general population. In this study, we investigated plasma p-tau181 as a biomarker of AD in individuals with Down syndrome (DS). We included 366 adults with DS (240 asymptomatic, 43 prodromal AD, 83 AD dementia) and 44 euploid cognitively normal controls. We measured plasma p-tau181 with a Single molecule array (Simoa) assay. We examined the diagnostic performance of p-tau181 for the detection of AD and the relationship with other fluid and imaging biomarkers. Plasma p-tau181 concentration showed an area under the curve of 0.80 [95% CI 0.73–0.87] and 0.92 [95% CI 0.89–0.95] for the discrimination between asymptomatic individuals versus those in the prodromal and dementia groups, respectively. Plasma p-tau181 correlated with atrophy and hypometabolism in temporoparietal regions. Our findings indicate that plasma p-tau181 concentration can be useful to detect AD in DS.

Fluoxetine Protects against Dendritic Spine Loss in Middle-aged APPswe/PSEN1dE9 Double Transgenic Alzheimer’s Disease Mice

2020 ◽  
Vol 17 (1) ◽  
pp. 93-103 ◽  
Author(s):  
Jing Ma ◽  
Yuan Gao ◽  
Wei Tang ◽  
Wei Huang ◽  
Yong Tang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dendritic Spines ◽  
Dendritic Spine ◽  
Early Stage ◽  
Learning Ability ◽  
Middle Aged ◽  
Protein Levels ◽  
Spine Pathology ◽  
The Impact

Background: Studies have suggested that cognitive impairment in Alzheimer’s disease (AD) is associated with dendritic spine loss, especially in the hippocampus. Fluoxetine (FLX) has been shown to improve cognition in the early stage of AD and to be associated with diminishing synapse degeneration in the hippocampus. However, little is known about whether FLX affects the pathogenesis of AD in the middle-tolate stage and whether its effects are correlated with the amelioration of hippocampal dendritic dysfunction. Previously, it has been observed that FLX improves the spatial learning ability of middleaged APP/PS1 mice. Objective: In the present study, we further characterized the impact of FLX on dendritic spines in the hippocampus of middle-aged APP/PS1 mice. Results: It has been found that the numbers of dendritic spines in dentate gyrus (DG), CA1 and CA2/3 of hippocampus were significantly increased by FLX. Meanwhile, FLX effectively attenuated hyperphosphorylation of tau at Ser396 and elevated protein levels of postsynaptic density 95 (PSD-95) and synapsin-1 (SYN-1) in the hippocampus. Conclusion: These results indicated that the enhanced learning ability observed in FLX-treated middle-aged APP/PS1 mice might be associated with remarkable mitigation of hippocampal dendritic spine pathology by FLX and suggested that FLX might be explored as a new strategy for therapy of AD in the middle-to-late stage.

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