Mild Cognitive Impairment Research Articles

Using ChatGPT as a tool during occupational therapy intervention: A case report in mild cognitive impairment

ABSTRACT This case report examined the impact of computer programmed assistive technology developed, using ChatGPT as a tool when designing an occupational therapy intervention on a client’s independence in activities of daily living. A 66-year-old female client with mild cognitive impairment consulted an occupational therapist due to difficulties with activities of daily living. The occupational therapist developed two activity assistance computer programs using ChatGPT as a resource. The client did not interact directly with ChatGPT; instead, the occupational therapist used the technology to design and implement the intervention. A computer programmed assistive technology-based occupational therapy intervention was completed for eight weeks. The occupational therapist trained the client to use these programs in the clinical setting and at home. As a result of the intervention, the client’s performance and independence in daily activities improved. The results of this study emphasize that ChatGPT may help occupational therapists as a tool to design simple computer programmed assistive technology interventions without requiring additional professional input.

A systematic analysis of neurologic manifestations of Long COVID in Nigeria.

Long COVID, also called post-acute sequelae of SARS-CoV-2 infection (PASC) affects millions of people in the world. The neurologic manifestations of PASC (Neuro-PASC) are among the most debilitating but they are largely unreported in Africa. We sought to compare the demographics, symptoms and cognitive profile of post-hospitalization Neuro-PASC (PNP) and non-hospitalized Neuro-PASC (NNP) patients in Nigeria. In this cross-sectional study performed at the Lagos University Teaching Hospital, 106/2319 (4.6%) SARS-CoV-2 positive individuals contacted via telephone reported Neuro-PASC symptoms with a higher frequency in PNP than in NNP individuals ((23/200 (11.5%) vs. 83/2119 (3.9%), p = < 0.0001). The predominant neurologic symptoms at any time during the disease course were difficulty remembering / brain fog (63/106; 59.4%), fatigue (59/106; 55.7%), sleep problems (34/106; 32%), headache (33/106; 31%), paresthesia (12/106; 11.3%), and myalgia (10/106; 9.4%). Of 66 participants with Neuro-PASC who underwent in-person neurological evaluation and cognitive screening, all had normal scores on the Intervention for Dementia in Elderly Africans cognition screen, while 11/65 (16.9%) that completed the Montreal Cognitive Assessment had results consistent with mild cognitive impairment (3/16 PNP (18.8%) and 8/49 NNP (16.3%); p = 1.0). Finally, 47/66 (71.2%) had digit span test scores consistent with mild cognitive dysfunction (12/16 PNP (75%) and 35/50 (70%) NNP; p = 1.0). Our findings reveal the previously unrecognized occurrence of Neuro-PASC among COVID-19 survivors in Nigeria and highlight the need for improved screening and diagnosis of Neuro-PASC in our population. Development of cognitive support services for persons suffering from Neuro-PASC in Nigeria is warranted.

Asynchronous Functional Brain Network Construction with Spatiotemporal Transformer for MCI Classification.

Construction and analysis of functional brain networks (FBNs) with resting-state functional magnetic resonance imaging (rs-fMRI) is a promising method to diagnose functional brain diseases. Nevertheless, the existing methods suffer from several limitations. First, the functional connectivities (FCs) of the FBN are usually measured by the temporal co-activation level between rs-fMRI time series from regions of interest (ROIs). While enjoying simplicity, the existing approach implicitly assumes simultaneous co-activation of all the ROIs, and models only their synchronous dependencies. However, the FCs are not necessarily always synchronous due to the time lag of information flow and cross-time interactions between ROIs. Therefore, it is desirable to model asynchronous FCs. Second, the traditional methods usually construct FBNs at individual level, leading to large variability and degraded diagnosis accuracy when modeling asynchronous FBN. Third, the FBN construction and analysis are conducted in two independent steps without joint alignment for the target diagnosis task. To address the first limitation, this paper proposes an effective sliding-window-based method to model spatiotemporal FCs in Transformer. Regarding the second limitation, we propose to learn common and individual FBNs adaptively with the common FBN as prior knowledge, thus alleviating the variability and enabling the network to focus on the individual disease-specific asynchronous FCs. To address the third limitation, the common and individual asynchronous FBNs are built and analyzed by an integrated network, enabling end-to-end training and improving the flexibility and discriminativity. The effectiveness of the proposed method is consistently demonstrated on three data sets for mild cognitive impairment (MCI) diagnosis.

Sleep Disorders in Alzheimer’s Disease

Alzheimer’s disease is the leading cause of dementia worldwide. Patients typically exhibit cognitive impairment, memory loss, diminished social and occupational functioning, as well as language and motor disorders. Alzheimer’s disease is characterized by the abnormal accumulation of amyloid-β (Aβ) and phosphorylated tau in the brain. These pathological changes not only disrupt neuronal function and lead to cognitive deficits, but also interfere with sleep regulation, resulting in sleep disorders. Such disturbances can diminish nighttime sleep quality and contribute to daytime functional impairments, further exacerbating cognitive decline. Therefore, exploring the interplay between cognitive impairment, Alzheimer’s disease, and sleep disorders is crucial for enhancing the quality of life of Alzheimer’s patients. This review summarizes current literature on the interconnections among Alzheimer’s disease, cognitive impairment, and sleep disorders. Sleep disturbances are prevalent in Alzheimer’s patients and can also occur in those with amnestic mild cognitive impairment, which often precedes Alzheimer’s onset. Such sleep disorders may promote and accelerate the accumulation of amyloid-β and tau proteins [1-3]. Furthermore, Alzheimer’s patients may be more vulnerable to sleep disturbances, creating a potential vicious cycle. Further investigation into these relationships may provide valuable insights for the treatment or prevention of Alzheimer’s disease.

The Association Between Mild Cognitive Impairment and Physical Function in Older Japanese Adults Aged 75 Years or Older Living in Independent Senior Housing: A Cross-Sectional Study

Background/Objective: Although there are many reports on the association between cognitive and physical functions in older adults, little information is available on those aged ≥75 years. Therefore, this study aimed to determine whether mild cognitive impairment (MCI) in older adults over 75 years who live in independent senior housing is associated with physical function. Methods: In this study, 271 participants (174 women and 97 men) with a mean age of 85.4 ± 4.7 years were included. Cognitive function was assessed using the Japanese version of the Montreal Cognitive Assessment; a score &lt; 26 confirmed MCI. MCI was an objective variable in univariate and multivariable logistic regression analyses. Physical function was measured using hand grip strength, normal and maximum gait speeds, and the 30 s chair stand test. Physical function was an explanatory variable adjusted for age and divided into tertiles (high, middle, and low) based on sex. The significance level was set at 5%. Results: There were 170 participants (63%) with MCI. Compared to the non-MCI group, the MCI group had significantly higher age and significantly lower normal and maximum gait speeds and 30 s chair stand test values Age-adjusted univariate analyses in women showed higher MCI rates in the low-fitness group than in the high-fitness group for maximum gait speed and 30 s chair stand test values. No variables were associated with MCI in men. Conclusions: MCI may be associated with physical function in women and older adults over 75 years who live in independent senior housing.

Daily high-frequency transcranial random noise stimulation (hf-tRNS) for sleep disturbances and cognitive dysfunction in patients with mild vascular cognitive impairments: A study protocol for a pilot randomized controlled trial.

Poor sleep quality is increasingly considered to be an underlying cause of cerebrovascular diseases. This is a slowly progressing condition that gradually leads to vascular cognitive impairment and stroke during ageing. At present, randomized clinical trials examining the non-pharmacological therapies in the management of this comorbidity are very limited. Transcranial current stimulation (tCS) is a non-invasive technology for promoting cognitive function and treating brain disorders. As advanced modalities of tCS, transcranial random noise stimulation (tRNS) and transcranial alternating current stimulation (tACS), could deliver frequency-specific waveforms of currents that can modulate brain activities in a more specific manner. Chinese individuals between the ages of 60 and 90 years, who are right-handed and have mild vascular cognitive impairment (VCI) with sleep disturbances, will participate in a randomized study. They will undergo a 2-week intervention period where they will be randomly assigned to one of three groups: high-frequency (hf)-tRNS, 40 Hz tACS, or sham tCS. Each group will consist of 15 participants. Before the intervention, high-resolution magnetic resonance imaging (MRI) data will be used to create a computational head model for each participant. This will help identify the treatment target of left inferior parietal lobe (IPL). Throughout the study, comprehensive assessments will be conducted at multiple time points, including baseline, 2nd week, 6th week, and 12th week. These assessments will evaluate various factors such as sleep quality, domain-specific cognitive performance, and actigraphic records. In addition, the participants' adherence to the program and any potential adverse effects will be closely monitored throughout the duration of the intervention. The primary objective of this study is to examine the safety, feasibility, and effectiveness of hf-tRNS and 40 Hz tACS interventions targeting left IPL in individuals with mild vascular cognitive impairment (VCI) who experience sleep disturbances and cognitive dysfunction. Additionally, the study seeks to evaluate the program's adherence, tolerability, and any potential adverse effects associated with frequency-specific transcranial current stimulation (tCS). The findings from this research will contribute to a deeper understanding of the intricate relationship between oscillation, sleep, and cognition. Furthermore, the results will provide valuable insights to guide future investigations in the field of sleep medicine and neurodegenerative diseases. ClinicalTrials.gov Identifier: NCT06169254.

Enrichment for clinical trials of early AD: Combining genetic risk factors and plasma p-tau as screening instruments.

Identifying low-cost, minimally-invasive screening instruments for Alzheimer's disease (AD) trial enrichment will improve the efficiency of AD trials. A total of 685 cognitively normal (CN) individuals and individuals with mild cognitive impairment (MCI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were grouped according to cutoffs of genetic risk factor (G) polygenic hazard score (PHS) and tau pathology (T) plasma phosphorylated tau-181 (p-tau181) into four groups: G+T+, G-T-, G+T-, and G-T+. We assessed the associations between group level and longitudinal cognitive decline and AD conversion. Power analyses compared the estimated sample size required to detect differences in cognitive decline. The G+T+ group was associated with faster cognitive decline and higher AD risk. Clinical trials enrolling G+T+ participants would benefit from significantly reduced sample sizes compared with similar trials using only single makers as an inclusion criterion. The combination of two low-cost, minimally-invasive measures-genetics and plasma biomarkers-would be a promising screening procedure for clinical trial enrollment. Participants with unimpaired or mildly impaired cognition were grouped based on cutoffs on genetic risk factors (G: polygenic hazardous score [PHS]) and Alzheimer's pathology (T: baseline plasma phosphorylated tau-181 [p-tau181]). Participants with high PHSs and plasma p-tau181 levels (G+T+) were at risk of faster cognitive decline and AD progression. The combination of PHS and plasma p-tau181 could enhance clinical trial enrichment more effectively than using single biomarkers.

Long-term cognitive training enhances fluid cognition and brain connectivity in individuals with MCI

Amnestic mild cognitive impairment (aMCI) is a risk factor for Alzheimer’s disease (AD). Multi-domain cognitive training (CT) may slow cognitive decline and delay AD onset. However, most work involves short interventions, targeting single cognitive domains or lacking active controls. We conducted a single-blind randomized controlled trial to investigate the effect of a 6-month, multi-domain CT on Fluid Cognition, functional connectivity in memory and executive functioning networks (primary outcomes), and white matter microstructural properties (secondary outcome) in aMCI. Sixty participants were randomly assigned to either a multi-domain CT or crossword training (CW) group, and thirty-four participants completed the intervention. We found a significant group-by-time interaction in Fluid Cognition (p = 0.007, F (1,28) = 8.26, Cohen’s d = 0.38, 95% confidence interval [CI]: 2.45–14.4), with 90% of CT patients showing post-intervention improvements (p < 0.01, Cohen’sd = 0.7). The CT group also showed better post-intervention Fluid Cognition than healthy controls (HCs, N = 45, p = 0.045). Functional connectivity analyses showed a significant group-by-time interaction (Cohen’s d ≥ 0.8) in the dorsolateral prefrontal cortex (DLPFC) and inferior parietal cortex (IPC) networks. Specifically, CT displayed post-intervention increases whereas CW displayed decreases in functional connectivity. Moreover, increased connectivity strength between the left DLPFC and medial PFC was associated with improved Fluid Cognition. At a microstructural level, we observed a decline in fiber density (FD) for both groups, but the CT group declined less steeply (1.3 vs. 2%). The slower decline in FD for the CT group in several tracts, including the cingulum-hippocampus tract, was associated with better working memory. Finally, we identified regions in cognitive control and memory networks for which baseline functional connectivity and microstructural properties were associated with changes in Fluid Cognition. Long-term, multi-domain CT improves cognitive functioning and functional connectivity and delays structural brain decline in aMCI (ClinicalTrials.gov number: NCT03883308).

Unveiling the hippocampal subfield changes across the Alzheimer's disease continuum: a systematic review of neuroimaging studies.

Studies exploring the hippocampal subfield atrophy in Alzheimer's disease (AD) have shown contradictory results. This review aims to disentangle such heterogeneity by investigating the dynamic changes of hippocampal subfields across the AD continuum. We systematically searched the PubMed and EMBASE databases for case-control studies. Selected studies included investigations of biomarker-based amyloid status and reported data on hippocampal subfield atrophy using advanced MRI techniques. Twelve studies were included. Despite high heterogeneity, a distinguishable pattern of vulnerability of hippocampal subfields can be recognized from the cognitively unimpaired phase to the dementia stage, shedding light on hippocampal changes with disease progression. Consistent findings revealed atrophy in the subiculum and presubiculum, along with a potential increase in volume in the cornu ammonis (CA) among the cognitively unimpaired group, a feature not observed in patients experiencing subjective cognitive decline. Atrophy in the subiculum, presubiculum, CA 1-4, and the dentate gyrus characterized the mild cognitive impairment stage, with a more pronounced severity in the progression to dementia.

Blood-derived mitochondrial DNA copy number is associated with Alzheimer disease, Alzheimer-related biomarkers and serum metabolites

BackgroundBlood-derived mitochondrial DNA copy number (mtDNA-CN) is a proxy measurement of mitochondrial function in the peripheral and central systems. Abnormal mtDNA-CN not only indicates impaired mtDNA replication and transcription machinery but also dysregulated biological processes such as energy and lipid metabolism. However, the relationship between mtDNA-CN and Alzheimer disease (AD) is unclear.MethodsWe performed two-sample Mendelian randomization (MR) using publicly available summary statistics from GWAS for mtDNA-CN and AD to investigate the causal relationship between mtDNA-CN and AD. We estimated mtDNA-CN using whole-genome sequence data from blood and brain samples of 13,799 individuals from the Alzheimer’s Disease Sequencing Project. Linear and Cox proportional hazards models adjusting for age, sex, and study phase were used to assess the association of mtDNA-CN with AD. The association of AD biomarkers and serum metabolites with mtDNA-CN in blood was evaluated in Alzheimer’s Disease Neuroimaging Initiative using linear regression. We conducted a causal mediation analysis to test the natural indirect effects of mtDNA-CN change on AD risk through the significantly associated biomarkers and metabolites.ResultsMR analysis suggested a causal relationship between decreased blood-derived mtDNA-CN and increased risk of AD (OR = 0.68; P = 0.013). Survival analysis showed that decreased mtDNA-CN was significantly associated with higher risk of conversion from mild cognitive impairment to AD (HR = 0.80; P = 0.002). We also identified significant associations of mtDNA-CN with brain FDG-PET (β = 0.103; P = 0.022), amyloid-PET (β = 0.117; P = 0.034), CSF amyloid-β (Aβ) 42/40 (β=-0.124; P = 0.017), CSF t-Tau (β = 0.128; P = 0.015), p-Tau (β = 0.140; P = 0.008), and plasma NFL (β=-0.124; P = 0.004) in females. Several lipid species, amino acids, biogenic amines in serum were also significantly associated with mtDNA-CN. Causal mediation analyses showed that about a third of the effect of mtDNA-CN on AD risk was mediated by plasma NFL (P = 0.009), and this effect was more significant in females (P < 0.005).ConclusionsOur study indicates that mtDNA-CN measured in blood is predictive of AD and is associated with AD biomarkers including plasma NFL particularly in females. Further, we illustrate that decreased mtDNA-CN possibly increases AD risk through dysregulation of mitochondrial lipid metabolism and inflammation.

Longitudinal accelerated brain age in mild cognitive impairment and Alzheimer’s disease

IntroductionBrain age is a machine learning-derived estimate that captures lower brain volume. Previous studies have found that brain age is significantly higher in mild cognitive impairment and Alzheimer’s disease (AD) compared to healthy controls. Few studies have investigated changes in brain age longitudinally in MCI and AD. We hypothesized that individuals with MCI and AD would show heightened brain age over time and across the lifespan. We also hypothesized that both MCI and AD would show faster rates of brain aging (higher slopes) over time compared to healthy controls.MethodsWe utilized data from an archival dataset, mainly Alzheimer’s disease Neuroimaging Initiative (ADNI) 1 with 3Tesla (3 T) data which totaled 677 scans from 183 participants. This constitutes a secondary data analysis on existing data. We included control participants (healthy controls or HC), individuals with MCI, and individuals with AD. We predicted brain age using a pre-trained model and tested for accuracy. We investigated cross-sectional differences in brain age by group [healthy controls or HC, mild cognitive impairment (MCI), and AD]. We conducted longitudinal modeling of age and brain age by group using time from baseline in one model and chronological age in another model.ResultsWe predicted brain age with a mean absolute error (MAE) &amp;lt; 5 years. Brain age was associated with age across the study and individuals with MCI and AD had greater brain age on average. We found that the MCI group had significantly higher rates of change in brain age over time compared to the HC group regardless of individual chronologic age, while the AD group did not differ in rate of brain age change.DiscussionWe replicated past studies that showed that MCI and AD had greater brain age than HC. We additionally found that this was true over time, both groups showed higher brain age longitudinally. Contrary to our hypothesis, we found that the MCI, but not the AD group, showed faster rates of brain aging. We essentially found that while the MCI group was actively experiencing faster rates of brain aging, the AD group may have already experienced this acceleration (as they show higher brain age). Individuals with MCI may experience higher rates of brain aging than AD and controls. AD may represent a homeostatic endpoint after significant neurodegeneration. Future work may focus on individuals with MCI as one potential therapeutic option is to alter rates of brain aging, which ultimately may slow cognitive decline in the long-term.

Prevalence of Unrecognized Cognitive Impairment in Federally Qualified Health Centers

There is a need for early and equitable detection of cognitive impairment among older adults. To examine the prevalence of unrecognized cognitive impairment among older adults receiving primary care from federally qualified health centers (FQHCs). This cross-sectional study was conducted at 5 FQHCs providing primary care in Indianapolis, Indiana, between 2021 and 2023. Participants were adults aged 65 years and older, without a diagnosis of mild cognitive impairment (MCI), dementia, or severe mental illness. Data analysis was performed from September 2023 to April 2024. The primary outcome was a diagnosis of dementia or MCI, as determined by an interdisciplinary clinical team using data from structured patient and study partner interviews, medical record reviews, and a detailed cognitive assessment, including neuropsychological testing. Differences between participants determined to have normal cognition, MCI, and dementia were assessed statistically using analysis of variance for continuous variables, χ2 or Fisher exact tests for categorical variables, or Fisher exact test alone when expected cell counts were 5 or less. A total of 844 eligible individuals were consecutively approached, 294 consented to participate, and 204 completed the study (mean [SD] age, 70.0 [5.1] years; 127 women [62.3%]). One hundred eight participants (52.9%) were African American, 5 (2.5%) were Hispanic, 199 (97.5%) were not Hispanic, and 90 (44.1%) were White. The mean (SD) duration of education was 13.1 (2.6) years, and the mean (SD) Area Deprivation Index score was 78.3 (19.9), indicating a high level of neighborhood disadvantage. In total, 127 patients (62.3%) met the diagnostic criteria for MCI, 25 (12.3%) had dementia, and 52 (25.5%) had no cognitive impairment. Compared with non-Hispanic White individuals and after adjusting for age, sex, and education level, African American individuals were more than twice as likely to have MCI or dementia (odds ratio, 2.73; 95% CI, 1.38-5.53; P = .02). This cross-sectional study found that unrecognized cognitive impairment is ubiquitous among older adults from underrepresented, minoritized racial and ethnic groups and those who are socially vulnerable receiving primary care from FQHCs. To overcome the disparity in early detection of cognitive impairment, timely, equitable, scalable, and sustainable detection approaches need to be developed.

Widowhood Shock, Family Reconstruction, and Mild Cognitive Impairment Among Older Adults: A Prospective Cohort Study.

Mild cognitive impairment (MCI), especially among widowed older adults, is increasingly urging public concern. This study aimed to investigate the association of widowhood, remarriage, and widowed life characteristics with the MCI risk among Chinese older adults. With an average age of 86.49 ± 10.20, a sample of 5377 participants aged between 65 and 116 was collected from four waves of the Chinese Longitudinal Healthy Longevity Survey between 2008 and 2018. Cox proportional hazards models and restricted cubic spline models were employed to estimate and plot the associations. Results showed that widowhood is associated with an increasing MCI risk, which could not be alleviated by remarriage. This negative impact was pronounced among women and those at older age. The association of living alone duration after widowhood and MCI onset displayed an inverse U-shape, with a peak risk at the 10th year. These findings have practical implications for pointing out the most vulnerable groups to MCI.

Physical Activity and Acute Care Utilization Among Older Adults With Mild Cognitive Impairment and Dementia.

People living with dementia have high rates of hospitalizations. Identifying factors that influence hospitalization is important. This study examines the influence of physical activity levels on risk of hospitalization and emergency department (ED) use among older people living with mild cognitive impairment (MCI) or dementia followed in our primary care practice in Rochester, Minnesota, United States. We included those age 55 years and older, who had a clinic visit between June 1, 2019 and June 30, 2021 and completed a social determinants of health questionnaire about physical activity levels (n = 3090). Physical activity was classified as sufficiently active, insufficiently active, or physically inactive. Risk of hospitalization and ED visits by physical activity levels were examined. People who were physically inactive were at higher risk of hospitalization and ED visits (p < .001) compared with those who were sufficiently active. This highlights an area for health promotion in people living with MCI and dementia.

Multi-stage semi-supervised learning enhances white matter hyperintensity segmentation

IntroductionWhite matter hyperintensities (WMHs) are frequently observed on magnetic resonance (MR) images in older adults, commonly appearing as areas of high signal intensity on fluid-attenuated inversion recovery (FLAIR) MR scans. Elevated WMH volumes are associated with a greater risk of dementia and stroke, even after accounting for vascular risk factors. Manual segmentation, while considered the ground truth, is both labor-intensive and time-consuming, limiting the generation of annotated WMH datasets. Un-annotated data are relatively available; however, the requirement of annotated data poses a challenge for developing supervised machine learning models.MethodsTo address this challenge, we implemented a multi-stage semi-supervised learning (M3SL) approach that first uses un-annotated data segmented by traditional processing methods (“bronze” and “silver” quality data) and then uses a smaller number of “gold”-standard annotations for model refinement. The M3SL approach enabled fine-tuning of the model weights with the gold-standard annotations. This approach was integrated into the training of a U-Net model for WMH segmentation. We used data from three scanner vendors (over more than five scanners) and from both cognitively normal (CN) adult and patients cohorts [with mild cognitive impairment and Alzheimer's disease (AD)].ResultsAn analysis of WMH segmentation performance across both scanner and clinical stage (CN, MCI, AD) factors was conducted. We compared our results to both conventional and transfer-learning deep learning methods and observed better generalization with M3SL across different datasets. We evaluated several metrics (F-measure, IoU, and Hausdorff distance) and found significant improvements with our method compared to conventional (p &amp;lt; 0.001) and transfer-learning (p &amp;lt; 0.001).DiscussionThese findings suggest that automated, non-machine learning, tools have a role in a multi-stage learning framework and can reduce the impact of limited annotated data and, thus, enhance model performance.

Validation of a functional human AD model with four AD therapeutics utilizing patterned ipsc-derived cortical neurons integrated with microelectrode arrays

Preclinical methods are needed for screening potential Alzheimer’s disease (AD) therapeutics that recapitulate phenotypes found in the Mild Cognitive Impairment (MCI) stage or even before this stage of the disease. This would require a phenotypic system that reproduces cognitive deficits without significant neuronal cell death to mimic the clinical manifestations of AD during these stages. Long-term potentiation (LTP), which is a correlate of learning and memory, was induced in mature human iPSC-derived cortical neurons cultured on microelectrode arrays utilizing circuit patterns connecting two adjacent electrodes. We demonstrated an LTP system that modeled the MCI and pre-MCI stages of Alzheimer’s and validated this functional system utilizing four AD therapeutics, which was also verified utilizing patch-clamp electrophysiology. LTP was induced by tetanic electrical stimulation, and LTP maintenance was significantly reduced in the presence of Amyloid-Beta 42 (Aβ42) oligomers compared to the controls, however, co-treatment with AD therapeutics (Donepezil, Memantine, Rolipram and Saracatinib) corrected Aβ42-induced LTP impairment. The results illustrate the utility of the system as a validated platform to model MCI AD pathology, and potentially for the pre-MCI phase before significant neuronal death. This system also has the potential to become an ideal platform for high-content therapeutic screening for other neurodegenerative diseases.

Association of Neurogranin and BACE1 With Clinical Cognitive Decline in Individuals With Subjective Cognitive Decline.

CSF biomarkers have immense diagnostic and prognostic potential for Alzheimer disease (AD). However, AD is still diagnosed relatively late in the disease process, sometimes even years after the initial manifestation of cognitive symptoms. Thus, further identification of biomarkers is required to detect related pathology in the preclinical stage and predict cognitive decline. Our study aimed to assess the association of neurogranin and β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) with cognitive decline in individuals with subjective cognitive decline (SCD). We enrolled participants with available neurogranin and BACE1 measurements in CSF from the DELCODE (DZNE-Longitudinal Cognitive Impairment and Dementia, Germany) cohort. The longitudinal change of Preclinical Alzheimer's Cognitive Composite score was assessed as the primary outcome in participants with SCD and controls. The secondary outcome was defined as conversion of SCD to mild cognitive impairment (MCI) during follow-up. Levels of neurogranin, BACE1, and neurogranin/BACE1 ratio across groups were compared by analysis of covariance after adjustment for demographics. The linear mixed-effects model and Cox regression analysis were applied to evaluate their association with cognitive decline and progression of SCD to MCI, respectively. A total of 530 participants (mean age: 70.76 ± 6.01 years, 48.7% female) were analyzed in the study. The rate of cognitive decline was faster in individuals with SCD with higher neurogranin and neurogranin/BACE1 ratio (β = -0.138, SE = 0.065, p = 0.037, and β = -0.293, SE = 0.115, p = 0.013). Higher baseline neurogranin and neurogranin/BACE1 ratio were associated with an increased rate of conversion from SCD to MCI (hazard ratio [HR] 1.35 per SD, 95% CI 1.03-1.77, p = 0.028, and HR 1.53 per SD, 95% CI 1.13-2.07, p = 0.007). In addition, the impact of higher neurogranin levels on accelerating the rate of cognitive decline was more pronounced in the SCD group than in cognitively unimpaired controls (β = -0.077, SE = 0.033, p = 0.020). Our findings suggest that CSF neurogranin and BACE1 begin to change in the preclinical stage of AD and they are associated with clinical progression in individuals with SCD.

Exploring Longitudinal Physiological Monitoring: Insights From Utilizing a Commercial Wearable Device Among Older Adults With Mild Cognitive Impairment

Commercial wearable technologies are becoming increasingly prevalent and offer the potential for monitoring physiological changes over time, particularly in older adults with Mild Cognitive Impairment (MCI). While literature suggests the utility of such devices, little evidence exists of their successful deployment among people with MCI. This feasibility study aimed to establish research guidelines, optimize participant training, and identify data collection challenges when collecting longitudinal physiological data using the Oura Ring. Our results indicated that adequate researcher support was crucial for study success and participant engagement. This involves including care partners of participants with MCI and providing appropriate technological training to participants. Care partner support reduced device troubleshooting instances and emotionally encouraged participants with MCI. Lastly, maintaining regular researcher-participant communication fostered rapport and ensured ongoing participant consent and data quality. This research lays the groundwork for future health monitoring studies by emphasizing the importance of tailored support, communication, and researcher involvement.

Joint association of serum sodium and frailty with mild cognitive impairment among hospitalized older adults with chronic diseases: a cross-sectional study

BackgroundTo examine the associations of serum sodium and frailty with the risk of mild cognitive impairment (MCI) among hospitalized older adults with chronic diseases.MethodsA cross-sectional study was conducted in 403 hospitalized older adults with chronic diseases. Serum sodium concentration was assessed by the ion-selective electrode method, frailty status was evaluated by the FRAIL scale, and MCI was determined by the Montreal Cognitive Assessment (MoCA). Multiple logistic regression models were used to estimate the associations of serum sodium and frailty with MCI.ResultsParticipants with the lowest tertile of serum sodium had a higher risk of MCI than those in the middle tertile group (OR = 1.75, 95% CI: 1.01–3.04). Below 143 mmol/L, the risk of MCI was 1.38 (95% CI: 1.03–1.84) for per 1 SD decrease in serum sodium. Compared with the robust group, frailty was significantly associated with an increased risk of MCI (OR = 3.94, 95% CI: 1.92–8.10). Moreover, in comparison with participants with the middle tertile of serum sodium and who were robust/prefrail, those with frailty and either the lowest (OR = 5.53, 95% CI: 2.08–14.67) or the highest tertile of serum sodium (OR = 3.48, 95% CI: 1.20–10.05) had higher risks of MCI.ConclusionBoth lower and higher serum sodium impose a significantly higher risk for MCI in older adults with frailty. This could inform the design of clinical trials and the development of guidelines and recommendations for correcting serum sodium and frailty in hospitalized older adults with chronic diseases.

Supplementation and Mitigating Cognitive Decline in Older Adults With or Without Mild Cognitive Impairment or Dementia: A Systematic Review.

This systematic literature review aims to answer the question of how micronutrients might influence the development and progression of dementia. In the present work, we focused on an overview of an updated review of relevant literature published in the last two decades. This review aims to delineate the relationship between micronutrient supplementation and cognitive decline in older subjects. In carrying out this review, we followed PRISMA, and our literature search was performed on PubMed. This systematic review includes only primary studies that have investigated the efficacy of nutritional interventions for the prevention of dementia and improvement of cognitive function in subjects aged 65 years or older with normal cognition, mild cognitive impairment (MCI), or Alzheimer's disease (AD). A gross heterogeneity of studies forbids the possibility of a direct comparison of the results. A review of the inclusion criteria and restrictions has been conducted to check the validity and reliability of the results. In this review, thirty-three primary studies were included. Results have shown that supplementation with vitamin D, probiotics, and PUFAs would most likely reduce cognitive decline, dementia, or AD compared with vitamins A, B, C, and E, which were seen to be relatively ineffective. Of note, when considering vitamin B supplementation, positive effects were only observed in non-aspirin users having high ω-3 fatty acid (ω-3 FA) plasma levels. In some cases, however, there were genotypic differences in subjects in response to vitamin B supplementation.