Mild Mild Cognitive Impairment Research Articles

Verbal fluency discrepancies as a marker of the prehippocampal stages of Alzheimer's disease.

Prior to evidence of episodic memory decline, a lengthy preclinical phase of Alzheimer's disease (AD) exists characterized by the build-up of tau pathology within extrahippocampal structures. Semantic memory, also impaired in AD, has been linked to degradation within these earliest affected areas. This study aimed to assess the utility of performance discrepancies between letter and category verbal fluency tasks to detect neuronal loss in brain regions affected very early by AD. Whole-brain voxel-based morphometry was used to assess the neural correlates of semantic processing in three patient groups: two groups of mild cognitive impairment (MCI) patients split into mildly (n = 58) and moderately (n = 53) affected and a mild AD dementia group (n = 71). Discrepancies between the level of impairment on the semantic category fluency test and nonsemantic letter fluency test were calculated for each participant and included in regression models measuring the relationship between semantic memory and whole-brain gray matter volume. Patients at all disease stages demonstrated a loss of the normal semantic advantage in fluency tests, showing significantly greater impairments in category relative to letter fluency. Discrepancy scores in mild MCI correlated strongly with the structural integrity of the anterior medial temporal lobes. Correlations in more severely affected groups were weaker and more widespread. Semantic memory appears a useful indicator of even the earliest stages of medial temporal damage in AD. With advancing disease severity, the discrepancy index loses its focal anatomical association, reinforcing its value as an early marker of incipient decline. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Nilotinib: from animal-based studies to clinical investigation in Alzheimer's disease patients.

Nilotinib: from animal-based studies to clinical investigation in Alzheimer's disease patients.

Single-Domain Amnestic Mild Cognitive Impairment Identified by Cluster Analysis Predicts Alzheimer's Disease in the European Prospective DESCRIPA Study

Background/Aims: To identify prodromal Alzheimer's disease (AD) subjects using a data-driven approach to determine cognitive profiles in mild cognitive impairment (MCI). Methods: A total of 881 MCI subjects were recruited from 20 memory clinics and followed for up to 5 years. Outcome measures included cognitive variables, conversion to AD, and biomarkers (e.g. CSF, and MRI markers). Two hierarchical cluster analyses (HCA) were performed to identify clusters of subjects with distinct cognitive profiles. The first HCA included all subjects with complete cognitive data, whereas the second one selected subjects with very mild MCI (MMSE ≥28). ANOVAs and ANCOVAs were computed to examine whether the clusters differed with regard to conversion to AD, and to AD-specific biomarkers. Results: The HCAs identified 4-cluster solutions that best reflected the sample structure. One cluster (aMCIsingle) had a significantly higher conversion rate (19%), compared to subjective cognitive impairment (SCI, p < 0.0001), and non-amnestic MCI (naMCI, p = 0.012). This cluster was the only one showing a significantly different biomarker profile (Aβ₄₂, t-tau, APOE ε4, and medial temporal atrophy), compared to SCI or naMCI. Conclusion: In subjects with mild MCI, the single-domain amnestic MCI profile was associated with the highest risk of conversion, even if memory impairment did not necessarily cross specific cut-off points. A cognitive profile characterized by isolated memory deficits may be sufficient to warrant applying prevention strategies in MCI, whether or not memory performance lies below specific z-scores. This is supported by our preliminary biomarker analyses. However, further analyses with bigger samples are needed to corroborate these findings.

Progression from Mild to Pronounced MCI Is Not Associated with Cerebrospinal Fluid Biomarker Deviations

Background/Aim: Detection of cerebrospinal fluid (CSF) biomarker deviations improve prediction of progression from mild cognitive impairment (MCI) to dementia. However, it is not settled whether the same pattern exists in patients progressing from very mild to more pronounced MCI. Given that neurodegenerative processes occur very early in the disease course, we also expected to find biomarker deviations in these patients. Methods: A total of 246 memory clinic patients with non-progressive (n = 161), progressive (n = 19), or converting (n = 66) MCI, 67 with stable dementia, and 80 controls were followed for 24 months. At baseline, CSF total tau (T-tau), β-amyloid 1–42 (Aβ42) and the light subunit of neurofilament protein (NFL) were determined. Results: Patients with converting MCI and stable dementia had lower CSF Aβ42 concentrations and higher T-tau concentrations and NFL in comparison with controls and non-progressive/progressive MCI (p < 0.0005). No differences were found between progressive and non-progressive MCI. Conclusion: As expected, biomarker deviations predicted progression from MCI to dementia. Contrary to our hypothesis, progression from very mild MCI to more pronounced MCI was not reflected by biomarker deviations. The results suggest that the measured biomarkers are not early disease markers, or alternatively Alzheimer or vascular pathology is not the underlying cause in this patient group.

Subjective complaints in mild cognitive impairment make a difference

Subjective complaints in mild cognitive impairment make a difference

Poster 34: Evidence-Based Practice for Early Cognitive Impairment Detection on Older Individuals with Metabolic Syndrome

Background: Alzheimer's disease (AD) is the most common form of dementia, and it has been associated to diabetes and metabolic syndrome. Due to the high prevalence of diabetes and metabolic syndrome in the older population, it is important to detect cognitive decline at early stages to allow prompt initiation of therapy and counseling of the patients and family. Objective: The objective of this study is twofold: 1) to systematically analyze the literature to investigate the clinical significance of FDG-PET in the early diagnosis of mild cognitive impairment (MCI), and 2) based on the systematic review, we examine by a case study design the patterns of hypometabolism found in 2 older female subjects with metabolic syndrome and subjective memory complaints. Systematic Review Methods: An extensive review of literature has been conducted, using PubMed as the primary search engine. A set of predefined inclusion criteria was used to determine inclusion and analysis of the papers. Systematic Review Results: A total of 6 studies were included in the review. Cognitive decline was predicted with sensitivities ranging from 38% to 93%, specificities ranging from 62.5% to 97% and accuracies from 81.8 to 90% (N=6). Case Study Methods: Two older female patients (P1& P2) were evaluated by a comprehensive battery of neurological, memory, and laboratory tests. Case Study Results: Both patients had insulin resistance and MS. The neuropsychological evaluation indicated that both patients suffer from mild MCI. Conclusions: The results of the review of literature show that due to the high values for specificity, sensitivity, and accuracy, as well as due to the consistent patterns of hypometabolism detected, FDG-PET is a good diagnostic tool and shows great promise as a clinical tool in the early detection of MCI. As for the case study, the FDG-PET scans of P1 and P2 showed different patterns of hypometabolism, suggesting the patients have two different types of MCI. Even though most of the neuropsychological tests were close to normal ranges, the PET scan was able to detect patterns of hypometabolism—and thus reduced function, consistent with the subjective memory complaints of the patients. The objective assessment performed with FDG-PET was more reliable in predicting early MCI than the neuropsychological tests, as suggested by previous studies.