Mild Cognitive Impairment Research Articles

Critical analysis of Parkinson’s disease detection using EEG sub-bands and gated recurrent unit

Parkinson’s disease, the second most common neurodegenerative disorder in the world. A progressive disease, which can worsen over time and lead to complications like mild cognitive impairments and dementia. The accurate diagnosis of Parkinson’s Disease (PD) remains a critical challenge in medical engineering. This study explores the potential of brain wave patterns for PD detection in healthy and unhealthy patients. The Power Spectral Density (PSD) and proposed PD detection model based on the Gated Recurrent Unit (GRU) is used to analyze brain activities. It was found that the detection of PD in patients was improved by classifying the RAW EEG in conjunction with the sub-bands using PSD as a feature and GRU as a classifier. The performance matrices including accuracy, precision, recall, and F1-score fall within a range of 90% to 98% for alpha, beta, and gamma sub-bands, while the area under the curve in the case of receiver operating characteristics curve achieved the maximum value of 1.00. To assess the differences between the groups with Parkinson’s disease and the healthy group, a statistical significance test was performed. The power spectral density of the two groups differed statistically significantly, according to the results, indicating that they could be useful as biomarkers for the identification of Parkinson’s disease. The results are compared and validated with the standard performance measures.

Enhancing early detection of cognitive decline in the elderly: a comparative study utilizing large language models in clinical notes

BackgroundLarge language models (LLMs) have shown promising performance in various healthcare domains, but their effectiveness in identifying specific clinical conditions in real medical records is less explored. This study evaluates LLMs for detecting signs of cognitive decline in real electronic health record (EHR) clinical notes, comparing their error profiles with traditional models. The insights gained will inform strategies for performance enhancement. MethodsThis study, conducted at Mass General Brigham in Boston, MA, analysed clinical notes from the four years prior to a 2019 diagnosis of mild cognitive impairment in patients aged 50 and older. We developed prompts for two LLMs, Llama 2 and GPT-4, on Health Insurance Portability and Accountability Act (HIPAA)-compliant cloud-computing platforms using multiple approaches (e.g., hard prompting, retrieval augmented generation, and error analysis-based instructions) to select the optimal LLM-based method. Baseline models included a hierarchical attention-based neural network and XGBoost. Subsequently, we constructed an ensemble of the three models using a majority vote approach. Confusion-matrix-based scores were used for model evaluation. FindingsWe used a randomly annotated sample of 4,949 note sections from 1,969 patients (women: 1,046 [53.1%]; age: mean, 76.0 [SD, 13.3] years), filtered with keywords related to cognitive functions, for model development. For testing, a random annotated sample of 1,996 note sections from 1,161 patients (women: 619 [53.3%]; age: mean, 76.5 [SD, 10.2] years) without keyword filtering was utilised. GPT-4 demonstrated superior accuracy and efficiency compared to Llama 2, but did not outperform traditional models. The ensemble model outperformed the individual models in terms of all evaluation metrics with statistical significance (p<0.01), achieving a precision of 90.2% [95% CI: 81.9%-96.8%], a recall of 94.2% [95% CI: 87.9%-98.7%], and an F1-score of 92.1% [95% CI: 86.8%-96.4%]. Notably, the ensemble model showed a significant improvement in precision, increasing from a range of 70%-79% to above 90%, compared to the best-performing single model. Error analysis revealed that 63 samples were incorrectly predicted by at least one model; however, only 2 cases (3.2%) were mutual errors across all models, indicating diverse error profiles among them. InterpretationLLMs and traditional machine learning models trained using local EHR data exhibited diverse error profiles. The ensemble of these models was found to be complementary, enhancing diagnostic performance. Future research should investigate integrating LLMs with smaller, localised models and incorporating medical data and domain knowledge to enhance performance on specific tasks.

Relationship between MRI brain-age heterogeneity, cognition, genetics and Alzheimer’s disease neuropathology

Brain ageing is highly heterogeneous, as it is driven by a variety of normal and neuropathological processes. These processes may differentially affect structural and functional brain ageing across individuals, with more pronounced ageing (older brain age) during midlife being indicative of later development of dementia. Here, we examined whether brain-ageing heterogeneity in unimpaired older adults related to neurodegeneration, different cognitive trajectories, genetic and amyloid-beta (Aβ) profiles, and to predicted progression to Alzheimer's disease (AD). Functional and structural brain age measures were obtained for resting-state functional MRI and structural MRI, respectively, in 3460 cognitively normal individuals across an age range spanning 42-85 years. Participants were categorised into four groups based on the difference between their chronological and predicted age in each modality: advanced age in both (n=291), resilient in both (n=260) or advanced in one/resilient in the other (n=163/153). With the resilient group as the reference, brain-age groups were compared across neuroimaging features of neuropathology (white matter hyperintensity volume, neuronal loss measured with Neurite Orientation Dispersion and Density Imaging, AD-specific atrophy patterns measured with the Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease index, amyloid burden using amyloid positron emission tomography (PET), progression to mild cognitive impairment and baseline and longitudinal cognitive measures (trail making task, mini mental state examination, digit symbol substitution task). Individuals with advanced structural and functional brain-ages had more features indicative of neurodegeneration and they had poor cognition. Individuals with a resilient brain-age in both modalities had a genetic variant that has been shown to be associated with age of onset of AD. Mixed brain-age was associated with selective cognitive deficits. The advanced group displayed evidence of increased atrophy across all neuroimaging features that was not found in either of the mixed groups. This is in line with biomarkers of preclinical AD and cerebrovascular disease. These findings suggest that the variation in structural and functional brain ageing across individuals reflects the degree of underlying neuropathological processes and may indicate the propensity to develop dementia in later life. The National Institute on Aging, the National Institutes of Health, the Swiss National Science Foundation, the Kaiser Foundation Research Institute and the National Heart, Lung, and Blood Institute.

Exploring mitochondrial blood-based and genetic markers in older adults with mild cognitive impairment and remitted major depressive disorder

Mild cognitive impairment (MCI) is a prodromal stage in aging to possible progression to Alzheimer’s disease and related dementia (ADRD), where co-occurrence of major depressive disorder (MDD) accelerates the progression. Metabolic and mitochondrial abnormalities in ADRD and other neurodegenerative disorders have been widely suggested, while possible mitochondrial dysfunction has been associated with etiopathology of both MCI and MDD. Hence, investigation of mitochondrial markers in MCI, MDD, and presence of both conditions is warranted. In total, 332 older adult participants were included: 168 with MCI, 108 with MCI plus remitted MDD (rMDD), and 56 with rMDD but without MCI. We measured plasma circulating mitochondrial DNA (ccf-mtDNA), lactate, and extracted nuclear mitochondrial encoded (NMt) single-nucleotide variants (SNVs) (n = 312). Non-parametric statistical tests on ccf-mtDNA and lactate levels were performed on the diagnosis, clinical and cardiometabolic variables. Binary sequence kernel association test (SKAT-O) and burden test were performed on NMt-SNV, adjusted for age, race, gender, type II diabetes, and APOE genotype. Lower level of lactate was observed in MCI (KW χ2 = 14.8, P = 0.0024), more specifically, significant differences of lower plasma lactate between MCI only and rMDD, but not between MCI+rMDD and MCI were found, suggesting potential roles in MCI driving lactate lower levels. While higher levels of ccf-mtDNA were observed in APOE-ε4 carrier (χ2 = 5.04, P = 0.05). This relationship was present only in MCI (P = 0.043) and MCI+rMDD groups (P = 0.023). No significant nuclear-encoded mitochondrial gene associations were observed with MCI or MDD. The results suggest decreased level of plasma lactate in individuals with MCI and MCI+rMDD, with inverse correlation with ccf-mtDNA, in addition to effect of APOE-ε4 in further increasing ccf-mtDNA specifically in participants with cognitive impairment. These findings contribute to a deeper understanding of the mitochondrial markers in MCI and MDD, warranting further research to explore the precise roles of mitochondrial abnormalities in the development and progression of MCI.

Retrosplenial hypometabolism precedes the conversion from mild cognitive impairment to Alzheimer's disease.

Not all individuals who experience mild cognitive impairment (MCI) transition through progressive stages of cognitive decline at the same rate, if at all. Previous observational studies have identified the retrosplenial cortex (RSC) as an early site of hypometabolism in MCI which seems to be predictive of later transition to Alzheimer's disease (AD). We examined N=399 MCI subjects with baseline 18F-fluorodeoxyglucose positron emission tomography. Subjects were classified based on whether their diagnosis converted from MCI to AD. Whole-brain metabolism was decreased in converters (MCI-AD). This effect was more prominent at the RSC, where MCI-AD subjects showed even greater hypometabolism. Observations of RSC hypometabolism and its utility in predicting transition from MCI-AD withstood statistical analyses in a large retrospective study. These results point to the utility of incorporating RSC hypometabolism into predictive models of AD progression risk and call for further examination of mechanisms underlying this relationship. Not all individuals who develop MCI will progress to AD. Individuals with MCI who progress to AD show early whole-brain hypometabolism. Early hypometabolism is particularly prominent at the RSC.

A short version of the Everyday Cognition scale can predict clinical progression and cognitive decline.

The Everyday Cognition scale (ECog-39) scores are associated with future cognitive decline. We investigated whether the 12-item ECog (ECog-12), which is being collected in Alzheimer's Disease Neuroimaging Initiative (ADNI)4, can predict progression. Baseline self (PT)- and study partner (SP)-ECog-12 data were extracted from the 39-item version collected in the ADNI. Weibull analysis examined the relationship between baseline ECog-12 and future clinical progression (change in Clinical Dementia Rating Sum of Boxes [CDR-SB] scores and diagnostic conversion). Higher PT- and SP-ECog-12 scores were associated with faster CDR-SB worsening, with hazard ratios in cognitively unimpaired (CU) 3.34 and 9.61, mild cognitive impairment (MCI) 1.44 and 2.82, and dementia 0.93 and 1.82. They were associated with conversion from CU to MCI 3.01 and 6.24 and MCI to dementia 1.61 and 3.07. SP-ECog-12 provided a higher prognostic value for predicting clinical progression, so this can help identify and monitor patients at risk in research and health-care settings. The 12-item Everyday Cognition scale (ECog-12) data obtained from both raters increased diagnostic conversion risk from cognitively unimpaired to mild cognitive impairment (MCI) and from MCI to dementia. ECog-12, rated by study partners, was associated with an increased risk of Clinical Dementia Rating Sum of Boxes worsening in all diagnostic groups. Our results provide novel information about the specific scoring outputs and rater types (participant vs. study partner) of ECog-12 that can facilitate screening, prioritization, and longitudinal monitoring of the clinical progression of participants in Alzheimer's Disease Neuroimaging Initiative 4 and other Alzheimer's disease clinical studies, clinical trials, and in health-care settings.

Tracer-Separator: A Deep Learning Model for Brain PET Dual-Tracer (18F-FDG and Amyloid) Separation.

Multiplexed PET imaging revolutionized clinical decision-making by simultaneously capturing various radiotracer data in a single scan, enhancing diagnostic accuracy and patient comfort. Through a transformer-based deep learning, this study underscores the potential of advanced imaging techniques to streamline diagnosis and improve patient outcomes. The research cohort consisted of 120 patients spanning from cognitively unimpaired individuals to those with mild cognitive impairment, dementia, and other mental disorders. Patients underwent various imaging assessments, including 3D T1-weighted MRI, amyloid PET scans using either 18F-florbetapir (FBP) or 18F-flutemetamol (FMM), and 18F-FDG PET. Summed images of FMM/FBP and FDG were used as proxy for simultaneous scanning of 2 different tracers. A SwinUNETR model, a convolution-free transformer architecture, was trained for image translation. The model was trained using mean square error loss function and 5-fold cross-validation. Visual evaluation involved assessing image similarity and amyloid status, comparing synthesized images with actual ones. Statistical analysis was conducted to determine the significance of differences. Visual inspection of synthesized images revealed remarkable similarity to reference images across various clinical statuses. The mean centiloid bias for dementia, mild cognitive impairment, and healthy control subjects and for FBP tracers is 15.70 ± 29.78, 0.35 ± 33.68, and 6.52 ± 25.19, respectively, whereas for FMM, it is -6.85 ± 25.02, 4.23 ± 23.78, and 5.71 ± 21.72, respectively. Clinical evaluation by 2 readers further confirmed the model's efficiency, with 97 FBP/FMM and 63 FDG synthesized images (from 120 subjects) found similar to ground truth diagnoses (rank 3), whereas 3 FBP/FMM and 15 FDG synthesized images were considered nonsimilar (rank 1). Promising sensitivity, specificity, and accuracy were achieved in amyloid status assessment based on synthesized images, with an average sensitivity of 95 ± 2.5, specificity of 72.5 ± 12.5, and accuracy of 87.5 ± 2.5. Error distribution analyses provided valuable insights into error levels across brain regions, with most falling between -0.1 and +0.2 SUV ratio. Correlation analyses demonstrated strong associations between actual and synthesized images, particularly for FMM images (FBP: Y = 0.72X + 20.95, R2 = 0.54; FMM: Y = 0.65X + 22.77, R2 = 0.77). This study demonstrated the potential of a novel convolution-free transformer architecture, SwinUNETR, for synthesizing realistic FDG and FBP/FMM images from summation scans mimicking simultaneous dual-tracer imaging.

The U-shaped association between serum direct bilirubin and incident mild cognitive impairment in hemodialysis patients: a multicenter study

BackgroundPrevious studies have suggested an association between low serum bilirubin concentrations and increased risk of cognitive impairment. This study aimed to explore the association and dose-response relationship between serum direct bilirubin (DBIL) concentrations and mild cognitive impairment (MCI) among hemodialysis patients.MethodsThis is a multicenter cross-sectional study with patients undergoing hemodialysis from 22 dialysis centers in Guizhou Province, China. The outcome was mild cognitive impairment (MCI), measured with a Mini-Mental State Examination. The association and dose-response relationship between serum DBIL and MCI incidence were examined using multivariate logistic regression analysis, restricted cubic spline, and subgroup analysis to explore the association of serum DBIL concentrations with MCI.ResultsOf the 4223 enrolled patients (mean age 55.2 ± 15.3 years, 60.4% males), 1187 (28.1%) had MCI. Serum DBIL of 0.10-1.67umol/L [multivariable-adjusted odds ratios (OR) 1.32, 95% confidence interval (CI): 1.08–1.60, P = 0.005], 2.31-3.20umol/L (OR = 1.22, 95%CI: 1.00-1.49, P = 0.047), and > 3.21umol/L (OR = 1.32, 95%CI: 1.08–1.61, P = 0.006) had increased risk of MCI compared with 1.68-2.30umol/L. The dose-response analysis between serum DBIL and MCI showed a U-shaped relationship (P for non-linearity = 0.009), and the serum DBIL concentrations with the lowest risk of MCI was 2.01umol/L. As the serum DBIL concentrations were lower than the reference, the risk of MCI decreased by 49% per standard deviation (SD) increase in serum DBIL (OR = 0.51, 95%CI: 0.29–0.89, P < 0.001); when the concentration exceeds 2.01umol/L, a rise per SD increased the risk of MCI by 9% (OR = 1.09, 95%CI:1.01–1.17, P < 0.001).ConclusionOur findings suggest a U-shaped association between serum DBIL and MCI among hemodialysis patients.

Adapting a cultural dance program to prevent cognitive decline: insights from experts and educators

Abstract Leveraging activities such as cultural dance shows promise as an effective basis for chronic disease prevention and management with at-risk populations. In fact, recent WHO reports and resolutions advocate utilizing cultural context to achieve health equality. Hula, the Native Hawaiian indigenous dance has been successfully utilized in interventions with statistically significant improvement in medication resistant hypertension management and heart disease prevention. In this study, Alzheimer’s Disease and Related Dementia (ADRD) experts and kumu hula (hula experts and educators) provide insights to developing a hula-based lifestyle program for prevention of cognitive decline. Informant interviews were used to collect information for developing a hula-based program for individuals with mild cognitive impairment from 4 ADRD experts and clinicians, and 4 kumu hula. The 60-90 minute semi-structured interviews were conducted, recorded, then transcribed. Separate thematic analysis allowed distinct themes for each group to emerge. Themes with greatest between group alignment informed the adaptation of an existing hula-based chronic disease intervention. The clinical and cultural experts were unanimous on multiple themes. First, a hula-based program was well positioned to promote social functioning. Second, hula facilitated integrated multi-dimensional benefits including physical, cognitive, social, and cultural. Third, facilitating learning included: repetition done in creative forms; utilization of aids such as dance notation and audio recordings; and educational approaches such as project-based learning. Cultural activities such as dance have been underutilized in health promotion initiatives. A significant challenge in health promotion programs is engagement and retention of participants. Cultural dance programs are popular and can be effective interventions, particularly when both clinical and cultural experts are engaged in program development. Key messages • Inclusion of clinical and cultural experts in health promotion program development leads to unique collaboration and impactful insights. • ADRD clinicians and Hawaiian cultural dance educators identify social, cultural, physical, and cognitive benefits of hula as instrumental for individuals with mild cognitive impairment.

Onset of cognitive impairment, diet quality and adherence to dietary guidelines over 12 years: the Personality and Total Health Cohort Study.

Around 55 million people worldwide live with dementia, and more are expected due to population ageing. We aimed to investigate associations between healthy diet and mild cognitive impairment and dementia in 1753 older adults aged 60-64 from the PATH (Personality and Total Health Through Life Cohort) study. Healthy diet was defined by the Mediterranean-DASH diet Intervention for Neurological Delay (MIND) and two dietary guideline quality scores (Dietary Guideline Index (DGI) and Index Diet Quality (IDQ)), which were calculated from baseline FFQ. Higher dietary scores indicated higher diet quality. Incidence of Alzheimer's disease/vascular dementia (National Institute of Neurological Disorders criteria) and mild cognitive impairment (Winbald criteria) was assessed after 12 years of follow-up using validated questionnaires with nominated proxies. Logistic regression explored associations between dietary scores and cognitive function, adjusting for demographics, lifestyle factors and medical preconditions. Adjusted logistic regression comparing the per unit linear increase in diet scores showed MIND (OR = 0·82, 95 % CI = 0·68, 0·99), but not DGI (0·99 (0·97, 1·00)) or IDQ (1·12 (0·95, 1·32)), was significantly associated with lower odds of developing cognitive impairment. In conclusion, a healthier neuroprotective dietary pattern is associated with better cognitive function over time, whereas dietary patterns generated from general dietary guidelines did not show a significant association. Further research and well-designed clinical studies are needed to determine the effects of the MIND diet on cognitive impairment in older adults without a family history of dementia.

Outdoor artificial light at night and risk of conversion from mild cognitive impairment to dementia

Abstract Background A few studies have suggested that exposure to lighting during night hours, i.e. light at night (LAN), may increase the risk of dementia. In this study, we aimed to evaluate the association between exposure to outdoor artificial LAN and risk of conversion to dementia in an Italian cohort of subjects with mild cognitive impairment (MCI). Methods We recruited subjects with a diagnosis of MCI at the Cognitive Neurology Clinic of Modena Hospital in the period 2008-2014, and we followed these subjects up to 2021 for conversion to dementia. We collected their residential history and we assessed LAN exposure at subjects’ residences using satellite imagery data available from the Visible Infrared Imaging Radiometer Suite (VIIRS) for the period 2014-2022. Using a Cox-proportional hazards model adjusted for relevant confounders, we computed the hazard ratio (HR) of dementia with 95% confidence interval (CI) according to increasing LAN exposure through linear, categorical, and non-linear restricted-cubic spline models. Results Out of 53 recruited subjects, 34 converted to dementia of any type including 26 Alzheimer’s dementia. In linear regression analysis, LAN exposure was positively associated with dementia conversion (HR 1.03, 95% CI 1.00-1.06 for 1-unit increase). Using as reference the lowest tertile, subjects at both intermediate and highest tertiles of LAN exposure showed increased risk of dementia conversion (HRs 2.26, 95% CI 0.88-5.85, and 2.89, 95% CI 1.10-7.58). In spline regression analysis, the risk linearly increased up to a LAN exposure of 30 nW/cm2/sr, above which a plateau seemed to be reached. Results were almost confirmed when limited to conversion to Alzheimer’s dementia, except for an almost linear relation. Conclusions Our findings suggest that exposure to outdoor artificial LAN may increase conversion from MCI to any type of dementia, especially above 30 nW/cm2/sr, while such relation appears to be almost linear for Alzheimer’s dementia. Key messages • Light at night exposure above 30 nW/cm2/sr was associated with risk of conversion to dementia. • Light at night showed almost linear association with risk of conversion to Alzheimer’s dementia.

Peripheral biomarkers of Parkinson’s disease and its correlation with clinical symptoms: a case-control study

BackgroundInflammation significantly impacts Parkinson’s disease (PD), yet the intricate relationship between inflammatory markers and PD remains elusive.ObjectiveTo identify the peripheral biomarkers of PD and its correlation with the motor and non-motor symptoms of PD.Methods79 PD patients and 65 controls were included in this study. Clinical information and the serum levels of IL-8, IL-27, IL-33, β-NGF, AgRP, and TRAILR2 in the participants were collected. Appropriate scales were used to assess the symptoms of PD. For the factors with significant differences in the two groups, multivariable logistic regression was used to determine its relationship with PD. Moreover, spearman correlation was conducted to explore the correlation between the factors and PD related symptoms. The IL-27 level was compared between the cognitively healthy PD group and the mild cognitive impairment in PD (PD-MCI). The serum level of TRAILR2 was positively correlated with age and was not associated with other clinical characteristics related to PD.ResultsCompared to controls, the serum levels of IL-27(P = 0.013) were increased whereas the levels of TRAILR2(P = 0.008) were decreased in PD patients. IL-8, IL-33, β-NGF, and AgRP showed no significant differences between the two groups. After controlling for the other variables, IL-27 was considered as an independent risk factor for PD in the multivariable logistic regression model. The receiver operating characteristic (ROC) curve for diagnosing PD with IL-27 yielded an area under the curve (AUC) of 0.621. Additionally, IL-27 level in PD patients was positively correlated with age, the disease duration, LEDD and negatively correlated with the MoCA scores. However, no significant difference was found in IL-27 levels between cognitively healthy PD and PD-MCI groups.ConclusionElevated serum IL-27 was a risk factor for PD and positively correlated with the cognitive decline in PD.

Catheter ablation increases cerebral blood flow and cognitive function in elderly patients with atrial fibrillation

Abstract Background Atrial fibrillation (AF) has been considered to have an increased risk for cognitive impairment independent of a stroke and a silent micro-infarction. The mechanism of this interaction is unclear. One of the potential explanations is brain hypoperfusion due to a reduced cardiac output. To date, there are no reports focusing on the cerebral blood flow and cognitive impairment in patients undergoing AF ablation. Purpose The purpose of this study was to investigate whether catheter ablation of AF would increase cerebral blood flow and restore cognitive impairment. Methods AF patients aged 75 years or older with mild or more cognitive impairment were selected. The assessment of cognitive function using Mini-Mental State Examination (MMSE) and Hasegawa's Dementia Scale-Revised (HDS-R), and measurement of cerebral blood flow using 99mTc-ECD SPECT imaging were examined before and 3 months after ablation. Results A total of 25 elderly patients (mean age 83, 14 males and 11 females) were included in this study. Of them, 23 patients had persistent AF. Twenty-three patients (92%) maintained sinus rhythm after ablation. There was a significant improvement in MMSE score (from 24.6±4.5 to 25.9±4.0, p&amp;lt;0.05) and HDS-R (from 23.2±5.5 to 24.8±5.1, p&amp;lt;0.05) after ablation. Cerebral blood flow also significantly increased after ablation (right lobe: from 34.4±4.6 to 38.5±4.4 ml/100g/min, p&amp;lt;0.01, left lobe: from 35.3±9.7 to 38.8±3.7 ml/100g/min, p&amp;lt;0.01). Overall average cerebral blood flow increased by 10.1±9.4% after ablation. There was a positive correlation between the changes in MMSE score and the changes in cerebral blood flow (r=0.65, p&amp;lt;0.05). Conclusion AF ablation in elderly patients increased cerebral blood flow and cognitive function. AF ablation would be one of the therapeutic options to improve cognitive function in elderly patients with cognitive impairment.

Cognitive and physical fatigue: the experience and consequences of brain fog after spontaneous coronary artery dissection, a qualitative study

Abstract Background Mild cognitive impairment (often subjectively referred to as "brain fog") and cognitive fatigue are common sequelae after acute coronary syndrome. However, little is known about the nature and impact of these experiences in spontaneous coronary artery dissection (SCAD) survivors. Purpose To understand if and how brain fog and cognitive fatigue are experienced following SCAD. Methods Participants were recruited from a larger SCAD genetics study database and were considered eligible if they had experienced SCAD within 12 months. Seven semi-structured online focus groups, with the primary aim of exploring psychosocial impacts of SCAD, were conducted between December 2021 and January 2022. Each focus group lasted for 1 hour 30 minutes and were led by investigators extensively experienced in qualitative research and cardiac rehabilitation. Interviews were digitally recorded, transcribed verbatim, and thematically analysed using Braun and Clark’s reflexive approach. Results Participants (n=30) had a mean age of 52.2±9.5 years and mostly female (n=27, 90%), partnered (n=27, 90%) and employed (n=27, 90%). Four main themes were identified: experiences of brain fog, perceived causes of brain fog, impacts of brain fog and coping with brain fog. Experiences of brain fog included memory lapses, difficulty concentrating and impaired judgement. Perceived causes of brain fog included medication, sleep deprivation and tiredness, and menopause and hormonal changes. The impacts of brain fog included rumination, changes in self-perception, disruption to hobbies and pastimes, and limitations at work. Coping mechanisms used for these challenges included reminders, setting expectations, being one's own advocate, making lifestyle adjustments, and support from peers. Conclusion Brain fog is commonly experienced by SCAD survivors and present challenges to normal life after SCAD. The impacts on daily life are varied, including those relating to self-perception and capacity to work. SCAD survivors reported difficulty understanding causes and found their own path to coping. Clinicians should be aware of these experiences as they are ideally placed to assist patients with these challenges.

Challenges for Family Caregivers of Persons With Mild Cognitive Impairment: A Qualitative Longitudinal Study.

Family caregivers of persons with mild cognitive impairment attempt to understand the behavioural and functional changes exhibited by their relative. However, how caregivers respond to initial changes and changes over time has not been explored. The purpose of this qualitative study was to explore the experience of family caregivers responding to changes in their relative's memory, behaviours, and physical functions over 2 years. Eleven family caregivers of a relative with mild cognitive impairment were purposively recruited from neurological clinics in Taiwan. Face-to-face semi-structured interviews were conducted within 6-months of referral; three follow-ups were conducted at 6-month intervals. Content analysis of 41 transcribed audio-recorded interviews revealed the longitudinal changes in their relative with cognitive impairment was made caregiving challenging. Three themes described the challenges: (1) Changes related to their relative's cognitive impairment, which included increases in mood fluctuations, erratic behaviours, and reductions in physical abilities; (2) changes in their relative's comorbidities, which included adapting to new symptoms and treatments for a chronic disease, monitoring medication adherence and drug interactions; and (3) changes in caregiver burden, which increased levels of stress, uncertainty, and anxiety resulting in greater role strain. Caregiving became more challenging with time, especially caregivers whose relative developed dementia during the study period. These findings offer insight into the trajectory of the experience of family caregivers attempting to understand changes in cognition, behaviours, and physical functions for their relative with mild cognitive impairment over 2 years, which could help mental healthcare providers develop support services to reduce caregiver role strain.

Association of modifiable risk factors with progression to dementia in relation to amyloid and tau pathology

BackgroundDementia preventive interventions targeting multiple modifiable risk factors are a promising approach. However, the impact of modifiable risk factors in the presence of beta-amyloid or phosphorylated-tau (p-tau) pathology is unclear.MethodsThe objective of the study was to examine the role of modifiable risk factors (vascular factors, depression, and smoking) in the progression to mild cognitive impairment (MCI) or dementia among 434 cognitively unimpaired (CU) and 611 individuals with MCI from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Vascular risk factors were summarized with the Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) score, dichotomized into higher versus lower risk. Depression and smoking (yes/no) were categorised according to medical history or current symptoms. Analyses were stratified by beta-amyloid negative (A-) and positive (A +), p-tau negative (T-) and positive (T +), or beta-amyloid and p-tau negative (A-T-) and positive (A + T +) biomarker status. Cox proportional hazard models were adjusted for age, sex, education, baseline MMSE score, baseline hippocampal volume and ApoE4 carrier status.ResultsHigher CAIDE score was associated with increased risk of progression to all-cause dementia in most MCI subgroups: adjusted hazard ratios (aHR) [95% CI] were 3.1 [1.43; 6.53] in the A- subgroup, 1.7 [1.20–2.27] in T + , 2.6 [1.06–6.59] in A-T-, and 1.6 [1.15–2.22] in the A + T + subgroup. Smoking (yes/no) was associated with increased dementia aHR in the A + MCI subgroup: 1.6 [1.07–2.34]. Depression increased dementia aHR in the T + MCI subgroup: 1.5 [1.06–2.02]. No significant associations were found in the CU biomarker subgroups.ConclusionAddressing modifiable risk factors carries an important potential for reducing the risk of dementia even after the onset of Alzheimer's pathology. Knowledge of biomarker status can further optimize prevention strategies.

Inflammatory Cytokines and Cognition in Alzheimer's Disease and Its Prodrome.

The aim of this study was to investigate the association between blood levels of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) and cognitive impairments among elderly individuals. Peripheral concentration of TNF-α and IL-6 were measured in all subjects. To assess individual cognitive function, the Consortium to Establish a Registry for Alzheimer's Disease Neuropsychological Assessment Battery (CERAD-NP) was used, and standardized scores (z-scores) were calculated for each test. Cytokine levels were compared between the diagnostic groups, and correlations between blood inflammatory factor levels and z-scores were analyzed. The 37 participants included 8 patients with Alzheimer's disease (AD), 15 subjects with mild cognitive impairment (MCI), and 14 cognitively healthy controls. TNF-α and IL-6 levels were higher in patients with AD than in healthy controls. TNF-α levels were higher in the AD group than in the MCI group. However, after adjusting for age, the associations between diagnosis and TNF-α and IL-6 were not significant. The higher the plasma IL-6 level, the lower the z-scores on the Boston Naming Test, Word List Learning, Word List Recognition, and Constructional Recall. The higher the serum TNF-α level, the lower the z-scores on the Word List Learning and Constructional Recall. Negative correlation between serum TNF-α level and the z-score on Word List Learning remained significant when age was adjusted. The difference in the blood levels of TNF-α and IL-6 between the diagnostic groups may be associated with aging. However, elevated TNF-α levels were associated with worse immediate memory performance, even after adjusting for age.

The relationship between micronutrients and cognitive ability in an elderly population with mild cognitive impairment and Alzheimer’s disease: a cross-sectional study

BackgroundMild cognitive impairment (MCI) and Alzheimer’s disease (AD) are significant neurodegenerative disorders with increasing prevalence worldwide. Lifestyle and dietary factors, including micronutrients, have been suggested as modifiable risk factors for disease development. This study aims to investigate the association between micronutrients and cognitive ability in these diseases.MethodsA cross-sectional study involving 105 participants with MCI and AD was conducted. Dietary assessments were performed using a validated food frequency questionnaire (FFQ), and micronutrient intake was calculated based on nutrient content. Disease severity was evaluated using the Functional Assessment Staging Tool (FAST). Statistical analyses, including correlation coefficients and multiple regression models, were employed to examine the association between micronutrients and disease progression.ResultsThe results revealed significant correlations between disease severity and several micronutrients, including omega-3 fatty acids (B = -0.2, P = 0.01), carotenoids (B = -0.19, P = 0.02), dietary antioxidant compounds, including vitamins A, C, D, E (B = -0.19, P = 0.02), selenium (B = -0.17, P = 0.03), alpha-carotene (B = -0.16, P = 0.04), beta-carotene (B = -0.17, P = 0.03), and lycopene (B = -0.16, P = 0.04). Multivariate regression analysis showed that higher intake of omega-3 fatty acids was associated with slower disease progression. Furthermore, the levels of these micronutrients declined in advanced stages of the disease.ConclusionOmega-3 fatty acids and carotenoids may affect the cognitive ability and disease progression. Further longitudinal studies are warranted to establish causality and explore the therapeutic implications of these findings for the prevention and management of MCI and AD.

Mitochondrial Dysfunction in Parkinson’s Disease: A Contribution to Cognitive Impairment?

Among the non-motor symptoms associated with Parkinson’s disease (PD), cognitive impairment is one of the most common and disabling. It can occur either early or late during the disease, and it is heterogeneous in terms of its clinical manifestations, such as Subjective Cognitive Dysfunction (SCD), Mild Cognitive Impairment (MCI), and Parkinson’s Disease Dementia (PDD). The aim of the present review is to delve deeper into the molecular mechanisms underlying cognitive decline in PD. This is extremely important to delineate the guidelines for the differential diagnosis and prognosis of the dysfunction, to identify the molecular and neuronal mechanisms involved, and to plan therapeutic strategies that can halt cognitive impairment progression. Specifically, the present review will discuss the pathogenetic mechanisms involved in the progression of cognitive impairment in PD, with attention to mitochondria and their contribution to synaptic dysfunction and neuronal deterioration in the brain regions responsible for non-motor manifestations of the disease.

EEG biomarkers in Alzheimer’s and prodromal Alzheimer’s: a comprehensive analysis of spectral and connectivity features

BackgroundBiomarkers of Alzheimer’s disease (AD) and mild cognitive impairment (MCI, or prodromal AD) are highly significant for early diagnosis, clinical trials and treatment outcome evaluations. Electroencephalography (EEG), being noninvasive and easily accessible, has recently been the center of focus. However, a comprehensive understanding of EEG in dementia is still needed. A primary objective of this study is to investigate which of the many EEG characteristics could effectively differentiate between individuals with AD or prodromal AD and healthy individuals.MethodsWe collected resting state EEG data from individuals with AD, prodromal AD, and normal cognition. Two distinct preprocessing pipelines were employed to study the reliability of the extracted measures across different datasets. We extracted 41 different EEG features. We have also developed a stand-alone software application package, Feature Analyzer, as a comprehensive toolbox for EEG analysis. This tool allows users to extract 41 EEG features spanning various domains, including complexity measures, wavelet features, spectral power ratios, and entropy measures. We performed statistical tests to investigate the differences in AD or prodromal AD from age-matched cognitively normal individuals based on the extracted EEG features, power spectral density (PSD), and EEG functional connectivity.ResultsSpectral power ratio measures such as theta/alpha and theta/beta power ratios showed significant differences between cognitively normal and AD individuals. Theta power was higher in AD, suggesting a slowing of oscillations in AD; however, the functional connectivity of the theta band was decreased in AD individuals. In contrast, we observed increased gamma/alpha power ratio, gamma power, and gamma functional connectivity in prodromal AD. Entropy and complexity measures after correcting for multiple electrode comparisons did not show differences in AD or prodromal AD groups. We thus catalogued AD and prodromal AD-specific EEG features.ConclusionsOur findings reveal that the changes in power and connectivity in certain frequency bands of EEG differ in prodromal AD and AD. The spectral power, power ratios, and the functional connectivity of theta and gamma could be biomarkers for diagnosis of AD and prodromal AD, measure the treatment outcome, and possibly a target for brain stimulation.