Mild Cognitive Impairment Group Research Articles

Disrupted single-subject gray matter networks are associated with cognitive decline and cortical atrophy in Alzheimer’s disease

BackgroundResearch has shown disrupted structural network measures related to cognitive decline and future cortical atrophy during the progression of Alzheimer’s disease (AD). However, evidence regarding the individual variability of gray matter network measures and the associations with concurrent cognitive decline and cortical atrophy related to AD is still sparse.ObjectiveTo investigate whether alterations in single-subject gray matter networks are related to concurrent cognitive decline and cortical gray matter atrophy during AD progression.MethodsWe analyzed structural MRI data from 185 cognitively normal (CN), 150 mild cognitive impairment (MCI), and 153 AD participants, and calculated the global network metrics of gray matter networks for each participant. We examined the alterations of single-subject gray matter networks in patients with MCI and AD, and investigated the associations of network metrics with concurrent cognitive decline and cortical gray matter atrophy.ResultsThe small-world properties including gamma, lambda, and sigma had lower values in the MCI and AD groups than the CN group. AD patients had reduced degree, clustering coefficient, and path length than the CN and MCI groups. We observed significant associations of cognitive ability with degree in the CN group, with gamma and sigma in the MCI group, and with degree, connectivity density, clustering coefficient, and path length in the AD group. There were significant correlation patterns between sigma values and cortical gray matter volume in the CN, MCI, and AD groups.ConclusionThese findings suggest the individual variability of gray matter network metrics may be valuable to track concurrent cognitive decline and cortical atrophy during AD progression. This may contribute to a better understanding of cognitive decline and brain morphological alterations related to AD.

Role of fronto-limbic circuit in neuropsychiatric symptoms of dementia: clinical evidence from an exploratory study

BackgroundNeuropsychiatric symptoms (NPSs) are a distressful aspect of dementia and the knowledge of structural correlates of NPSs is limited. We aimed to identify associations of fronto-limbic circuit with specific NPSs in patients with various types of cognitive impairment.MethodsOf 84 participants, 27 were diagnosed with mild cognitive impairment (MCI), 41 with Alzheimer’s disease (AD) dementia and 16 with non-AD dementia. In all patients we assessed regional brain morphometry using a region of interest (ROI)-based analysis. The mean cortical thickness (CT) of 20 cortical regions and the volume (V) of 4 subcortical areas of the fronto-limbic system were extracted. NPSs were rated with the Neuropsychiatric Inventory (NPI). We used multiple linear regression models adjusted for age and disease duration to identify significant associations between scores of NPI sub-domains and MRI measures of brain morphometry.ResultsAll significant associations found were negative, except those between irritability and the fronto-opercular regions in MCI patients (corresponding to a 40-50% increase in CT) and between delusions and hippocampus and anterior cingulate gyrus (with a 40-60% increase). Apathy showed predominant involvement of the inferior frontal regions in AD group (a 30% decrease in CT) and of the cingulate cortex in non-AD group (a 50-60% decrease in CT). Anxiety correlated in MCI patients with the cingulate gyrus and caudate, with a CT and V decrease of about 40%, while hallucinations were associated with left enthorinal gyrus and right amygdala and temporal pole. Agitation showed associations in the AD group with the frontal regions and the temporal pole, corresponding to a 30-40% decrease in CT. Euphoria, disinhibition and eating abnormalities were associated in the MCI group with the entorhinal, para-hippocampal and fusiform gyri, the temporal pole and the amygdala (with a 40-70% decrease in CT and V). Finally, aberrant motor behavior reported a significant association with frontal and cingulate regions with a 50% decrease in CT.ConclusionOur findings indicate that specific NPSs are associated with the structural involvement of the fronto-limbic circuit across different types of neurocognitive disorders. Factors, such as age and disease duration, can partly account for the variability of the associations observed.

No Differences in Urine Bisphenol A Concentrations between Subjects Categorized with Normal Cognitive Function and Mild Cognitive Impairment Based on Montreal Cognitive Assessment Scores

A link between bisphenol A (BPA) exposure and cognitive disorders has been suggested. However, the differences in BPA concentrations between subjects with and without cognitive impairment have not been analysed. Therefore, this observational study aimed to compare urine BPA levels in subjects with normal cognitive function (NCF) and mild cognitive impairment (MCI). A total of 89 MCI subjects and 89 well-matched NCF individuals were included in this study. Cognitive functions were assessed using the Montreal Cognitive Assessment (MOCA) scale. Urine BPA concentrations were evaluated by gas chromatography–mass spectrometry and adjusted for creatinine levels. Moreover, anthropometric parameters, body composition, sociodemographic factors, and physical activity were also assessed. Creatinine-adjusted urine BPA levels did not differ between the NCF and MCI groups (1.8 (1.4–2.7) vs. 2.2 (1.4–3.6) µg/g creatinine, p = 0.1528). However, there were significant differences in MOCA results between groups when the study population was divided into tertiles according to BPA concentrations (p = 0.0325). Nevertheless, multivariate logistic regression demonstrated that only education levels were independently associated with MCI. In conclusion, urine BPA levels are not significantly different between subjects with MCI and NCF, but these findings need to be confirmed in further studies.

EEG biomarkers analysis in different cognitive impairment after stroke: an exploration study

EEG biomarkers analysis in different cognitive impairment after stroke: an exploration study

Moderating effect of education on glymphatic function and cognitive performance in mild cognitive impairment

ObjectiveThis research aims to investigate putative mechanisms between glymphatic activity and cognition in mild cognitive impairment (MCI) and analyzes whether the relationship between cognitive reserve (CR) and cognition was mediated by glymphatic activity.Methods54 MCI patients and 31 NCs were enrolled to evaluate the bilateral diffusivity along the perivascular spaces and to acquire an index for diffusivity along the perivascular space (ALPS-index) on diffusion tensor imaging (DTI). The year of education was used as a proxy for CR. The ALPS-index was compared between two groups and correlation analyses among the ALPS-index, cognitive function, and CR were conducted. Mediation analyses were applied to investigate the correlations among CR, glymphatic activity and cognition.ResultsMCI group had a significantly lower right ALPS-index and whole brain ALPS-index, but higher bilateral diffusivity along the y-axis in projection fiber area (Dyproj) than NCs. In MCI group, the left Dyproj was negatively related to cognitive test scores and CR, the whole brain ALPS-index was positively correlated with cognitive test scores and CR. Mediation analysis demonstrated that glymphatic activity partially mediated the correlations between CR and cognitive function.ConclusionMCI exhibited decreased glymphatic activity compared to NCs. CR has a protective effect against cognitive decline in MCI, and this effect may be partially mediated by changes in glymphatic activity.

Directed Functional Connectivity Changes of Triple Networks for Stable and Progressive Mild Cognitive Impairment

Mild cognitive impairment includes two distinct subtypes, namely progressive mild cognitive impairment and stable mild cognitive impairment. While alterations in extensive functional connectivity have been observed in both subtypes, limited attention has been given to directed functional connectivity. A triple network, composed of the central executive network, default mode network, and salience network, is considered to be the core cognitive network. We evaluated the alterations in directed functional connectivity within and between the triple network in progressive and stable mild cognitive impairment groups and investigated its role in predicting disease conversion. Resting-state functional magnetic resonance imaging was used to analyze directed functional connectivity within the triple networks. A correlation analysis was performed to investigate potential associations between altered directed functional connectivity within the triple networks and the neurocognitive performance of the participants. Our study revealed significant differences in directed functional connectivity within and between the triple network in the progressive and stable mild cognitive impairment groups. Altered directed functional connectivity within the triple network was involved in episodic memory and executive function. Thus, the directed functional connectivity of the triple network may be used as an imaging marker of mild cognitive impairment.

Network Structure of Depressive Symptomatology in Elderly with Cognitive Impairment

Objective and objectives: Patients with cognitive disorders such as Alzheimer’s disease (AD) and mild cognitive impairment (MCI) frequently exhibit depressive symptoms. Depressive symptoms can be evaluated with various measures and questionnaires. The geriatric depression scale (GDS) is a scale that can be used to measure symptoms in geriatric age. Many questionnaires sum up symptom scales. However, core symptoms of depression in these patients and connections between these symptoms have not been fully explored yet. Thus, the objectives of this study were (1) to determine core symptoms of two cognitive disorders, Alzheimer’s disease and mild cognitive impairment, and (2) to investigate the network structure of depressive symptomatology in individuals with cognitive impairment in comparison with those with Alzheimer’s disease. Materials and Methods: This study encompassed 5354 patients with cognitive impairments such as Alzheimer’s disease (n = 1889) and mild cognitive impairment (n = 3464). The geriatric depression scale, a self-administered questionnaire, was employed to assess depressive symptomatology. Using exploratory graph analysis (EGA), a network analysis was conducted, and the network structure was evaluated through regularized partial correlation models. To determine the centrality of depressive symptoms within each cohort, network parameters such as strength, betweenness, and closeness were examined. Additionally, to explore differences in the network structure between Alzheimer’s disease and mild cognitive impairment groups, a network comparison test was performed. Results: In the analysis of centrality indices, “worthlessness” was identified as the most central symptom in the geriatric depression scale among patients with Alzheimer’s disease, whereas “emptiness” was found to be the most central symptom in patients with mild cognitive impairment. Despite these differences in central symptoms, the comparative analysis showed no statistical difference in the overall network structure between Alzheimer’s disease and mild cognitive impairment groups. Conclusions: Findings of this study could contribute to a better understanding of the manifestation of depressive symptoms in patients with cognitive impairment. These results are expected to aid in identifying and prioritizing core symptoms in these patients. Further research should be conducted to explore potential interventions tailored to these core symptoms in patients with Alzheimer’s disease and mild cognitive impairment. Establishing core symptoms in those groups might have clinical importance in that appropriate treatment for neuropsychiatric symptoms in patients with cognitive impairment could help preclude progression to further impairment.

Serum neurofilament light chain and inflammatory cytokines as biomarkers for early detection of mild cognitive impairment

To investigate the association between serum neurofilament light chain (NfL) levels, inflammatory cytokines, and cognitive function to assess their utility in the early detection of mild cognitive impairment (MCI). We conducted a cross-sectional study involving 157 community-dwelling individuals aged 55 years and above, categorized into healthy controls, MCI, and probable Alzheimer's disease (AD). Serum levels of NfL, inflammatory cytokines, and AD pathology markers were measured using enzyme-linked immunosorbent assay (ELISA). Correlations between these biomarkers and cognitive function were analyzed, and the diagnostic performance of the cognitive assessment scales and serum biomarker concentrations was evaluated using receiver operating characteristic (ROC) curve analysis. Serum NfL levels were significantly elevated in MCI and probable AD groups compared to healthy controls. Positive correlations were found between serum NfL and inflammatory cytokines IL-1β, IL-6, and Aβ40. Combining serum NfL with p-tau217 and the Boston Naming Test significantly enhanced the predictive accuracy for MCI. However, combining serum NfL with inflammatory markers did not improve MCI prediction accuracy. Elevated serum NfL is associated with cognitive impairment and inflammatory markers, suggesting its potential as a peripheral serum biomarker for MCI detection. The combination of serum NfL with p-tau217 and cognitive tests could offer a more accurate prediction of MCI, providing new insights for AD treatment strategies.

Neuropsychiatric symptoms and white matter hyperintensities in older adults without dementia.

We aimed to examine associations between neuropsychiatric symptoms (NPS) and white matter hyperintensities (WMH) status in older adults without dementia under the hypothesis that WMH increased the odds of having NPS. Longitudinal analysis of data acquired from the National Alzheimer's Coordinating Center Uniform Data Set. Data were derived from 46 National Institute on Aging - funded Alzheimer's Disease Research Centers. NACC participants aged ≥50 years with available data on WMH severity with a diagnosis of mild cognitive impairment (MCI) or who were cognitively unimpaired (CU) were studied. Among 4617 CU participants, 376 had moderate and 54 extensive WMH. Among 3170 participants with MCI, 471 had moderate and 88 had extensive WMH. Using Cardiovascular Health Study (CHS) scores, WMH were coded as no to mild (CHS score: 0-4), moderate (score: 5-6) or extensive (score: 7-8). NPS were quantified on the Neuropsychiatric Inventory Questionnaire. Binary logistic regression models estimated the odds of reporting each of 12 NPS by WMH status separately for individuals with MCI or who were CU. Compared to CU individuals with no to mild WMH, the odds of having elation [9.87, (2.63-37.10)], disinhibition [4.42, (1.28-15.32)], agitation [3.51, (1.29-9.54)] or anxiety [2.74, (1.28-5.88)] were higher for the extensive WMH group, whereas the odds of having disinhibition were higher for the moderate WMH group [1.94, (1.05-3.61)]. In the MCI group, he odds of NPS did not vary by WMH status. Extensive WMH were associated with higher odds of NPS in CU older adults but not in those with MCI.

Prefrontal intra-individual ERP variability and its asymmetry: exploring its biomarker potential in mild cognitive impairment

BackgroundThe worldwide trend of demographic aging highlights the progress made in healthcare, albeit with health challenges like Alzheimer’s Disease (AD), prevalent in individuals aged 65 and above. Its early detection at the mild cognitive impairment (MCI) stage is crucial. Event-related potentials (ERPs) obtained by averaging EEG segments responded to repeated events are vital for cognitive impairment research. Consequently, examining intra-trial ERP variability is vital for comprehending fluctuations within psychophysiological processes of interest. This study aimed to investigate cognitive deficiencies and instability in MCI using ERP variability and its asymmetry from a prefrontal two-channel EEG device.MethodsIn this study, ERP variability for both target and non-target responses was examined using the response variance curve (RVC) in a sample comprising 481 participants with MCI and 1,043 age-matched healthy individuals. The participants engaged in auditory selective attention tasks. Cognitive decline was assessed using the Seoul Neuropsychological Screening Battery (SNSB) and the Mini-Mental State Examination (MMSE). The research employed various statistical methods, including independent t-tests, and univariate and multiple logistic regression analyses. These analyses were conducted to investigate group differences and explore the relationships between neuropsychological test results, ERP variability and its asymmetry measures, and the prevalence of MCI.ResultsOur results showed that patients with MCI exhibited unstable cognitive processing, characterized by increased ERP variability compared to cognitively normal (CN) adults. Multiple logistic regression analyses confirmed the association between ERP variability in the target and non-target responses with MCI prevalence, independent of demographic and neuropsychological factors.DiscussionThe unstable cognitive processing in the MCI group compared to the CN individuals implies abnormal neurological changes and reduced and (or) unstable attentional maintenance during cognitive processing. Consequently, utilizing ERP variability measures from a portable EEG device could serve as a valuable addition to the conventional ERP measures of latency and amplitude. This approach holds significant promise for identifying mild cognitive deficits and neural alterations in individuals with MCI.

Plasma ADAM10 Levels and their Association with Alzheimer's Disease Diagnosis in Older Adults with Fewer Years of Formal Education.

Low educational attainment is a potential risk factor for Alzheimer's disease (AD) development. Alpha-secretase ADAM10 plays a central role in AD pathology, attenuating the formation of beta-amyloid peptides and, therefore, their aggregation into senile plaques. This study seeks to investigate ADAM10 as a blood-based biomarker in mild cognitive impairment (MCI) and AD in a diverse group of community-dwelling older adults, focusing on those with limited educational attainment. Participants were recruited from public health services. Cognition was evaluated using MMSE and ACE-R batteries. Blood samples were collected to analyze plasma ADAM10 levels. A logistic regression was conducted to verify the influence of plasma ADAM10 on the AD diagnosis. Significant differences in age, years of education, prescribed medications, and cognitive test scores were found between the MCI and AD groups. Regarding cognitive performance, both ACE-R and MMSE scores displayed significant differences between groups, with post-hoc analyses highlighting these distinctions, particularly between AD and cognitively healthy individuals. Elevated plasma ADAM10 levels were associated with a 4.5-fold increase in the likelihood of a diagnosis of MCI and a 5.9-fold increase in the likelihood of a diagnosis of AD. These findings suggest that ADAM10 levels in plasma serve as a valuable biomarker for assessing cognitive status in older individuals with low education attainment. This study underscores the potential utility of plasma ADAM10 levels as a blood-based biomarker for cognitive status, especially in individuals with low educational backgrounds, shedding light on their relevance in AD development and diagnosis.

The Hippocampal Subfield Volume Reduction and Plasma Biomarker Changes in Mild Cognitive Impairment and Alzheimer's Disease.

The hippocampus consists of histologically and functionally distinct subfields, which shows differential vulnerabilities to Alzheimer's disease (AD)-associated pathological changes. To investigate the atrophy patterns of the main hippocampal subfields in patients with mild cognitive impairment (MCI) and AD and the relationships among the hippocampal subfield volumes, plasma biomarkers and cognitive performance. This cross-sectional study included 119 patients stratified into three categories: normal cognition (CN; N = 40), MCI (N = 39), and AD (N = 40). AD-related plasma biomarkers were measured, including amyloid-β (Aβ)42, Aβ40, Aβ42/Aβ40 ratio, p-tau181, and p-tau217, and the hippocampal subfield volumes were calculated using automated segmentation and volumetric procedures implemented in FreeSurfer. The subiculum body, cornu ammonis (CA) 1-head, CA1-body, CA4-body, molecular_layer_HP-head, molecular_layer_HP-body, and GC-ML-DG-body volumes were smaller in the MCI group than in the CN group. The subiculum body and CA1-body volumes accurately distinguished MCI from CN (area under the curve [AUC] = 0.647-0.657). The subiculum-body, GC-ML-DG-body, CA4-body, and molecular_layer_HP-body volumes accurately distinguished AD from MCI (AUC = 0.822-0.833) and AD from CN (AUC = 0.903-0.905). The p-tau 217 level served as the best plasma indicator of AD and correlated with broader hippocampal subfield volumes. Moreover, mediation analysis demonstrated that the subiculum-body volume mediated the associations between the p-tau217 and p-tau181 levels, and the Montreal Cognitive Assessment and Auditory Verbal Learning Test recognition scores. Hippocampal subfields with distinctive atrophy patterns may mediate the effects of tau pathology on cognitive function. The subiculum-body may be the most clinically meaningful hippocampal subfield, which could be an effective target region for assessing disease progression.

Connectome-based prediction of decreased trust propensity in older adults with mild cognitive impairment: A resting-state functional magnetic resonance imaging study

Trust propensity (TP) relies more on social than economic rationality to transform the perceived probability of betrayal into positive reciprocity expectations in older adults with normal cognition. While deficits in social rationality have been observed in older adults with mild cognitive impairment (MCI), there is limited research on TP and its associated resting-state functional connectivity (RSFC) mechanisms in this population. To measure TP and related psychological functions (affect, motivation, executive cognition, and social cognition), MCI (n=42) and normal healthy control (NHC, n=115) groups completed a one-shot trust game and additional assessments of related psychological functions. RSFC associated with TP was analyzed using connectome-based predictive modeling (CPM) and lesion simulations. Our behavioral results showed that the MCI group trusted less (i.e., had lower TP) than the NHC group, with lower TP associated with higher sensitivity to the probability of betrayal in the MCI group. In the MCI group, only negative CPM models (RSFC negatively correlated with TP) significantly predicted TP, with a high salience network (SN) contribution. In contrast, in the NHC group, positive CPM models (RSFC positively correlated with TP) significantly predicted TP, with a high contribution from the default mode network (DMN). In addition, the total network strength of the NHC-specific positive network was lower in the MCI group than in the NHC group. Our findings demonstrated a decrease in TP in the MCI group compared to the NHC group, which is associated with deficits in social rationality (social cognition, associated with DMN) and increased sensitivity to betrayal (affect, associated with SN) in a trust dilemma. In conclusion, our study contributes to understanding MCI-related alterations in trust and their underlying neural mechanisms.

Spontaneous brain activity in the hippocampal regions could characterize cognitive impairment in patients with Parkinson's disease.

This study aimed to investigate whether spontaneous brain activity can be used as a prospective indicator to identify cognitive impairment in patients with Parkinson's disease (PD). Resting-state functional magnetic resonance imaging (RS-fMRI) was performed on PD patients. The cognitive level of patients was assessed by the Montreal Cognitive Assessment (MoCA) scale. The fractional amplitude of low-frequency fluctuation (fALFF) was applied to measure the strength of spontaneous brain activity. Correlation analysis and between-group comparisons of fMRI data were conducted using Rest 1.8. By overlaying cognitively characterized brain regions and defining regions of interest (ROIs) based on their spatial distribution for subsequent cognitive stratification studies. A total of 58 PD patients were enrolled in this study. They were divided into three groups: normal cognition (NC) group (27 patients, average MoCA was 27.96), mild cognitive impairment (MCI) group (21 patients, average MoCA was 23.52), and severe cognitive impairment (SCI) group (10 patients, average MoCA was 17.3). It is noteworthy to mention that those within the SCI group exhibited the most advanced chronological age, with an average of 74.4 years, whereas the MCI group displayed a higher prevalence of male participants at 85.7%. It was found hippocampal regions were a stable representative brain region of cognition according to the correlation analysis between the fALFF of the whole brain and cognition, and the comparison of fALFF between different cognitive groups. The parahippocampal gyrus was the only region with statistically significant differences in fALFF among the three cognitive groups, and it was also the only brain region to identify MCI from NC, with an AUC of 0.673. The paracentral lobule, postcentral gyrus was the region that identified SCI from NC, with an AUC of 0.941. The midbrain, hippocampus, and parahippocampa gyrus was the region that identified SCI from MCI, with an AUC of 0.926. The parahippocampal gyrus was the potential brain region for recognizing cognitive impairment in PD, specifically for identifying MCI. Thus, the fALFF of parahippocampal gyrus is expected to contribute to future study as a multimodal fingerprint for early warning.

News event memory in amnestic and non-amnestic MCI, heritable risk for dementia, and subjective memory complaints

Robust and sensitive clinical measures are needed for more accurate and earlier detection of Alzheimer’s disease (AD), for staging preclinical AD, and for gauging the efficacy of treatments. Mild impairment on episodic memory tests is thought to indicate a cognitive risk of developing AD and mild cognitive impairment (MCI), considered to be a transitional stage between normal aging and AD. Novel tests of semantic memory, such as memory for news events, are also impaired early on but have received little clinical attention even though they may provide a novel way to assess cognitive risk for AD. We examined memory for news events in older individuals with normal cognition (NC, N=34), amnestic MCI (aMCI, N=27), and non-aMCI (N=10) using the novel Retrograde Memory News Events Test (RM-NET). We asked if news event memory was sensitive to 1) aMCI and also non-aMCI, which has rarely been examined, 2) genetic risk for dementia (positive family history of dementia, presence of an APOE-4 allele, or polygenic risk for AD), and 3) subjective memory functioning judgments about the past. We found that both MCI subgroups exhibited impaired RM-NET Lifespan accuracy scores together with temporally-limited retrograde amnesia. For the aMCI group amnesia extended back 45 years prior to testing, but not beyond that time frame. The extent of retrograde amnesia could not be reliably estimated in the small non-aMCI group. The effect sizes for MCI on the RM-NET were medium for the non-aMCI group and large for the aMCI group, whereas the effect sizes of participant characteristics on RM-NET accuracy scores were small. For the combined MCI group (N=37), news event memory was significantly related to positive family history of dementia but was not related to the more specific genetic markers of AD risk. For the NC group, news event memory was not related to any measure of genetic risk. Objective measures of past memory from the RM-NET were not related to subjective memory judgements about the present or the recent past in either group. By contrast, when individuals subjectively compared their present versus past memory abilities, there was a significant association between this judgment and objective measures of the past from the RM-NET (direct association for the NC group and inverse for the MCI group). The RM-NET holds significant promise for early identification of those with cognitive and genetic risk factors for AD and non-AD dementias.

Cholinergic hyperintensity pathways are associated with cognitive performance in patients with asymptomatic carotid artery stenosis

ObjectivesWe aimed to determine whether asymptomatic carotid artery stenosis (ACS) induced cognitive impairments were related to the cholinergic hyperintensity pathway. MethodsThis cross-sectional study included patients with moderate-to-severe ACS, who were categorized into mild cognitive impairment (MCI) and normal cognition groups on the basis of Montreal Cognitive Assessment (MoCA) scores. The cholinergic pathway hyperintensity scale (CHIPS), Fazekas, and medial temporal atrophy (MTA) scores were assessed. SPSS software was used for statistical analyses. ResultsA total of 117 ACS patients (70.89 ± 8.81 years) and 105 controls (67.87 ± 9.49 years) were evaluated (t = 2.46, p = 0.015). The ACS group showed a worse median Mini-Mental Status Examination (MMSE) score (z = -2.41, p = 0.016) and MoCA score (z = -3.51, p < 0.001), and a significantly higher median total CHIPS score (z = 4.88, p < 0.001) and mean Fazekas score (t = 2.39, p = 0.018). In the correlation analysis, the MoCA score showed a significant negative correlation with the CHIPS score (ρ = -0.41, p < 0.001) and Fazekas score (ρ = -0.31, p < 0.001) in ACS group. Logistic regression analyses suggested that CHIPS scores were risk factors for MCI in patients with ACS (odds ratio [OR] = 1.07, 95% Confidence Interval [CI]1.01 - 1.13 and controls (OR = 1.09, 95%CI 1.01 - 1.17), while the MTA and Fazekas scores showed no predictive power. The receiver operating characteristic curve showed that the area under the curve of the CHIPS score for predicting MCI was 0.71 in ACS group, but was only 0.57 in controls. ConclusionsPatients with ACS showed poorer cognitive performance and higher CHIPS and Fazekas scores. CHIPS, but not Fazekas, scores were risk factors for cognitive impairment and were a valuable factor to predict MCI in patients with ACS.

Difference of Cerebrospinal Fluid Biomarkers and Neuropsychiatric Symptoms Profiles among Normal Cognition, Mild Cognitive Impairment, and Dementia Patient.

The delineation of biomarkers and neuropsychiatric symptoms across normal cognition, mild cognitive impairment (MCI), and dementia stages holds significant promise for early diagnosis and intervention strategies. This research investigates the association of neuropsychiatric symptoms, evaluated via the Neuropsychiatric Inventory (NPI), with cerebrospinal fluid (CSF) biomarkers (Amyloid-β42, P-tau, T-tau) across a spectrum of cognitive states to enhance diagnostic accuracy and treatment approaches. Drawing from the National Alzheimer's Coordinating Center's Uniform Data Set Version 3, comprising 977 individuals with normal cognition, 270 with MCI, and 649 with dementia. To assess neuropsychiatric symptoms, we employed the NPI to understand the behavioral and psychological symptoms associated with each cognitive category. For the analysis of CSF biomarkers, we measured levels of Amyloid-β42, P-tau, and T-tau using the enzyme-linked immunosorbent assay (ELISA) and Luminex multiplex xMAP assay protocols. These biomarkers are critical in understanding the pathophysiological underpinnings of Alzheimer's disease and its progression, with specific patterns indicative of disease stage and severity. This study cohort consists of 1896 participants, which is composed of 977 individuals with normal cognition, 270 with MCI, and 649 with dementia. Dementia is characterized by significantly higher NPI scores, which are largely reflective of mood-related symptoms (p < 0.001). In terms of biomarkers, normal cognition shows median Amyloid-β at 656.0 pg/mL, MCI at 300.6 pg/mL, and dementia at 298.8 pg/mL (p < 0.001). Median P-tau levels are 36.00 pg/mL in normal cognition, 49.12 pg/mL in MCI, and 58.29 pg/mL in dementia (p < 0.001). Median T-tau levels are 241.0 pg/mL in normal cognition, 140.6 pg/mL in MCI, and 298.3 pg/mL in dementia (p < 0.001). Furthermore, the T-tau/Aβ-42 ratio increases progressively from 0.058 in the normal cognition group to 0.144 in the MCI group, and to 0.209 in the dementia group (p < 0.001). Similarly, the P-tau/Aβ-42 ratio also escalates from 0.305 in individuals with normal cognition to 0.560 in MCI, and to 0.941 in dementia (p < 0.001). The notable disparities in NPI and CSF biomarkers among normal, MCI and Alzheimer's patients underscore their diagnostic potential. Their combined assessment could greatly improve early detection and precise diagnosis of MCI and dementia, facilitating more effective and timely treatment strategies.

Alterations in Gut Microbiota and Their Correlation with Brain Beta-Amyloid Burden Measured by 18F-Florbetaben PET in Mild Cognitive Impairment Due to Alzheimer's Disease.

(1) Background: This study investigated changes in the gut microbial composition of individuals with mild cognitive impairment (MCI) due to Alzheimer's disease (AD) and their relationship with positron emission tomography (PET) amyloid accumulation. (2) Methods: In total, 17 cognitively normal individuals without amyloid-beta (Aβ) accumulation (Aβ-NC) and 24 with Aβ-positive mild cognitive impairment (Aβ+MCI) who underwent 18F-florbetaben PET and fecal bacterial 16S ribosomal RNA gene sequencing were enrolled. The taxonomic compositions of the Aβ-NC and Aβ+MCI groups were compared. The abundance of taxa was correlated with the standardized uptake value ratio (SUVR), using generalized linear models. (3) Results: There were significant differences in microbiome richness (ACE, p = 0.034 and Chao1, p = 0.024), alpha diversity (Shannon, p = 0.039), and beta diversity (Bray-Curtis, p = 0.018 and Generalized UniFrac, p = 0.034) between the Aβ-NC and Aβ+MCI groups. The global SUVR was positively correlated with the genus Intestinibacter (q = 0.006) and negatively correlated with the genera Roseburia (q = 0.008) and Agathobaculum (q = 0.029). (4) Conclusions: In this study, we identified significant changes in the gut microbiota composition that occur in individuals with MCI due to AD. In particular, the correlation analysis results between PET amyloid burden and gut microbial abundance showed that amyloid deposition is associated with a reduction in specific taxa involved in butyrate production.

Association Between Years of Education and Amyloid Burden in Patients With Subjective Cognitive Decline, MCI, and Alzheimer Disease.

Higher-educated patients with Alzheimer disease (AD) can harbor greater neuropathologic burden than those with less education despite similar symptom severity. In this study, we assessed whether this observation is also present in potential preclinical AD stages, namely in individuals with subjective cognitive decline and clinical features increasing AD likelihood (SCD+). Amyloid-PET information ([18F]Flutemetamol or [18F]Florbetaben) of individuals with SCD+, mild cognitive impairment (MCI), and AD were retrieved from the AMYPAD-DPMS cohort, a multicenter randomized controlled study. Group classification was based on the recommendations by the SCD-I and NIA-AA working groups. Amyloid PET images were acquired within 8 months after initial screening and processed with AMYPYPE. Amyloid load was based on global Centiloid (CL) values. Educational level was indexed by formal schooling and subsequent higher education in years. Using linear regression analysis, the main effect of education on CL values was tested across the entire cohort, followed by the assessment of an education-by-diagnostic-group interaction (covariates: age, sex, and recruiting memory clinic). To account for influences of non-AD pathology and comorbidities concerning the tested amyloid-education association, we compared white matter hyperintensity (WMH) severity, cardiovascular events, depression, and anxiety history between lower-educated and higher-educated groups within each diagnostic category using the Fisher exact test or χ2 test. Education groups were defined using a median split on education (Md = 13 years) in a subsample of the initial cohort, for whom this information was available. Across the cohort of 212 individuals with SCD+ (M(Age) = 69.17 years, F 42.45%), 258 individuals with MCI (M(Age) = 72.93, F 43.80%), and 195 individuals with dementia (M(Age) = 74.07, F 48.72%), no main effect of education (ß = 0.52, 95% CI -0.30 to 1.58), but a significant education-by-group interaction on CL values, was found (p = 0.024) using linear regression modeling. This interaction was driven by a negative association of education and CL values in the SCD+ group (ß = -0.11, 95% CI -4.85 to -0.21) and a positive association in the MCI group (ß = 0.15, 95% CI 0.79-5.22). No education-dependent differences in terms of WMH severity and comorbidities were found in the subsample (100 cases with SCD+, 97 cases with MCI, 72 cases with dementia). Education may represent a factor oppositely modulating subjective awareness in preclinical stages and objective severity of ongoing neuropathologic processes in clinical stages.

Classification of Mild Cognitive Impairment Using Functional Near-Infrared Spectroscopy-Derived Biomarkers With Convolutional Neural Networks.

To date, early detection of mild cognitive impairment (MCI) has mainly depended on paper-based neuropsychological assessments. Recently, biomarkers for MCI detection have gained a lot of attention because of the low sensitivity of neuropsychological assessments. This study proposed the functional near-infrared spectroscopy (fNIRS)-derived data with convolutional neural networks (CNNs) to identify MCI. Eighty-two subjects with MCI and 148 healthy controls (HC) performed the 2-back task, and their oxygenated hemoglobin (HbO2) changes in the prefrontal cortex (PFC) were recorded during the task. The CNN model based on fNIRS-derived spatial features with HbO2 slope within time windows was trained to classify MCI. Thereafter, the 5-fold cross-validation approach was used to evaluate the performance of the CNN model. Significant differences in averaged HbO2 values between MCI and HC groups were found, and the CNN model could better discriminate MCI with over 89.57% accuracy than the Korean version of the Montreal Cognitive Assessment (MoCA) (89.57%). Specifically, the CNN model based on HbO2 slope within the time window of 20-60 seconds from the left PFC (96.09%) achieved the highest accuracy. These findings suggest that the fNIRS-derived spatial features with CNNs could be a promising way for early detection of MCI as a surrogate for a conventional screening tool and demonstrate the superiority of the fNIRS-derived spatial features with CNNs to the MoCA.