Mini-Mental State Exam Score Research Articles

The association between serum uric acid and cognitive performance in patients with ischemic stroke is modified by estimated glomerular filtration rate

The relationship between serum uric acid (SUA) and poor cognitive performance in patients with ischemic stroke is unclear. We hypothesized that the severity of renal function mediates the association between SUA and cognitive dysfunction.A retrospective analysis of 608 patients with ischemic stroke was conducted between 2016 and 2020. SUA was obtained from inpatient medical records. Global cognitive function via mini-mental state exam (MMSE) and Montreal Cognitive Assessment (MoCA) was determined one month after hospital discharge. The relationship between SUA and cognitive function was assessed by multiple linear and logistic regression analyses. Patients had a mean age of 66.6 years (SD: 4.1 years), and 52% were male. The mean SUA level was 298.6 ± 75.4 μmol/L. SUA increases were significantly positively associated with lower MMSE and MoCA scores and increased risk of moderate-severe cognitive impairment one month after stroke (p < 0.01), even after adjusting for factors including age, gender, BMI, diabetes and hypertension history. Adding a term for estimated glomerular filtration rate (eGFR) attenuated these associations such that SUA was no longer associated with cognitive performance. A fully adjusted stronger negative association between SUA and cognitive performance was found in those who had lower eGFR, with a significant eGFR interaction for MMSE (p-interaction = 0.016) and MoCA (p-interaction = 0.005). In patients with ischemic stroke, SUA showed an inverse association with cognitive function among those who have lower eGFR. The renal function might mediate the association between SUA and cognitive dysfunction.

Clinical Experience with SATURN, a Public Domain Self-administered Cognitive Screening Test (P5-12.002)

<h3>Objective:</h3> Validation via regular clinical use of a free, public domain, automatically scored, and self-administered cognitive screening test. <h3>Background:</h3> Emerging therapies for neurodegenerative disease are directed at patients with little cognitive impairment. How do we efficiently identify these patients? Universal screening with paper-and-pencil tests like the Mini Mental State Exam (MMSE) or the Montreal Cognitive Assessment (MoCA) is cost-prohibitive due to clinician time investment. Self-Administered Tasks Uncovering Risk of Neurodegeneration (SATURN) is a tablet-based cognitive screening test designed to bypass that cost. After a small validation study, SATURN was integrated into regular clinical use alongside paper-and-pencil tests. We hypothesized that SATURN’s psychometric properties continued to compare favorably to paper-and-pencil tests. <h3>Design/Methods:</h3> We will retrospectively analyze data from every patient (n&gt;500) visiting one dementia sub-specialist clinic over a 24-month period. To-date, we have analyzed 66 patients’ records. We documented visit diagnoses and SATURN, MoCA, and MMSE scores. Primary analyses (1) use regression to test whether SATURN is well-correlated with the other tests, and (2) compare test scores to clinical diagnosis using receiver operating characteristic (ROC) curves. <h3>Results:</h3> For this interim analysis, we analyzed patients (n=37) who met prespecified inclusion criteria and also had scores for at least two of the three aforementioned tests. Clinical diagnoses – normal (n=8), mild cognitive impairment (n=16), and dementia (n=13) – were strongly associated with (mean±sd) test scores (SATURN: 27±3, 18±5, 13±6) (MoCA: 25±3, 20±4, 15±4) (MMSE: 30±0, 25±2, 21±6) (each p&lt;0.02; one-way ANOVA). ROC curves were statistically similar for all three tests (p&gt;0.10). SATURN was well-correlated with MoCA (n=24 tested with both: r=0.87, p&lt;0.0001), and MMSE (n=20 with both: r=0.81, p&lt;0.0001). MMSE and MoCA were also correlated (n=17 with both: r=0.69, p=0.002). <h3>Conclusions:</h3> The freely-available SATURN (https://doi.org/10.5061/dryad.02v6wwpzr) is comparable to the MoCA and MMSE in regular clinical practice; a prerequisite for larger-scale efforts to efficiently screen for cognitive impairment. <b>Disclosure:</b> Dr. Florendo has nothing to disclose. Dr. Bissig has received personal compensation in the range of $100,000-$499,999 for serving as a Physician with University of California - Davis.

Diagnostic Application of Automated Brain MRI Volumetry in Comparing Alzheimer Disease, Behavioral Variant Frontotemporal Dementia and Traumatic Brain Injury (P12-6.005)

<h3>Objective:</h3> To evaluate if application of automated brain MRI volumetry can improve delineation of neurocognitive disorders. <h3>Background:</h3> Assessment of regional structural differences with brain MRI volumetric quantification can improve diagnostic separation of multiple neurodegenerative and non-neurodegenerative disorders. <h3>Design/Methods:</h3> We utilized 136 participants with traumatic brain injury (TBI; n=40), early (EOAD; n=45) and late onset Alzheimer disease (LOAD; n=31) and behavioral variant frontotemporal dementia (bvFTD; n=20). Participants had brain MRI including 3D T1 and analyzed with an FDA cleared software program, Neuroreader. At the time of analysis, Mini-Mental State Exam (MMSE) scores were available on majority of participants (n=125). One-way ANOVA compared mean age, MMSE, and brain volumes across all four groups with Bonferroni correction for multiple comparisons. Volumes were adjusted for total intracranial volume (TIV). Discriminant analysis was done with leave-one-out cross validation on measured brain volumes to determine diagnostic delineation. Automated linear regression identified predictive features. <h3>Results:</h3> LOAD was the oldest compared to other groups (p&lt;.001). There were no statistically significant differences in sex (p=.58) with 54.4% women. EOAD and LOAD had the lowest MMSE scores compared to TBI (p=.04 for EOAD and p=.01 for LOAD). Regional volume difference across groups showed lowest hippocampal volumes in LOAD (p=.005), low white matter volume in TBI (p=.007), lower parietal lobe volumes in EOAD (p&lt;.01), and lower frontal lobe volumes in bvFTD (p&lt;.001). Regional volume differences resulted in a correct classification of 89%, 79.4% after cross validation. Predictive features included caudate, amygdala, frontal, parietal, temporal lobar and total white matter volumes. <h3>Conclusions:</h3> Lower parietal lobe volumes in EOAD and hippocampal volumes in LOAD as well as frontal atrophy of bvFTD reflect known anatomical distribution of pathology in those conditions. White matter volume loss in TBI has been noted with that condition. Brain MRI volumetry may be beneficial in clinical practice. <b>Disclosure:</b> Dr. Meysami has nothing to disclose. Prof. Raji has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Brainreader ApS. Prof. Raji has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Apollo Health . Prof. Raji has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for Neurevolution Medicine. Dr. Porter has nothing to disclose. David Merrill has nothing to disclose. Dr. Mendez has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Medical Education Speakers’ Bureau. Dr. Mendez has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for UpToDate. The institution of Dr. Mendez has received research support from NIH. Dr. Mendez has received publishing royalties from a publication relating to health care.

Cohort Effects in Alzheimer’s Disease Trials: An Empirical Assessment Utilizing Data from the Alzheimer’s Disease Cooperative Study

BackgroundCohort effects in study populations can impact clinical trial conclusions and generalizability, particularly in trials with planned interim analyses. Long recruitment windows may exacerbate these risks in Alzheimer’s disease (AD) trials.ObjectivesTo investigate the presence of cohort effects mild-to-moderate AD trials.DesignRetrospective analysis using pooled participant-level data from nine randomized, placebo-controlled trials conducted by the Alzheimer’s Disease Cooperative Study (ADCS).SettingTrials were multicenter studies conducted by an academic trial network.ParticipantsThe trials enrolled participants with mild, mild-to-moderate, or moderate AD who were over age 50 and had mini mental state exam scores between 12 and 26.Interventions/ExposureWe defined a participant’s site-standardized enrollment time as the number of days between their screening date and the first screening date among randomized participants at their site within their study.Main Outcome(S) and Measure(S)Our primary outcome was the 12-month change in the AD assessment scale — cognitive subscale (ADAS-Cog). Secondary outcomes were participant demographics and time to study discontinuation.ResultsThe pooled sample consisted of N=2,754 at baseline with N=2,191 participants completing a 12-month visit. We found no meaningful differences in the distributions of sex, race and ethnicity, age, years of education or baseline ADAS-Cog score across enrollment time. We found a significant association between enrollment time and 12-month change in ADAS-Cog, with participants enrolling 100 days later tending to experience an increase on the ADAS-Cog of 0.16 points greater (reflecting greater cognitive decline; 95% CI: (0.021, 0.294), p = 0.02), after controlling for potential confounding factors.ConclusionWe found minimal evidence of clinically relevant cohort effects in ADCS trials. Our results reinforce the original findings of these trials.

43 Random Forest Model Approaches to Build Prediction Models of Cognitive Impairment Using the National Alzheimer’s Coordinating Center database

OBJECTIVES/GOALS: Our goal is to explore the complex, the non-linear interplay among chronic conditions collectively contributing to a greater detrimental impact on the progression of Alzheimer’s disease (AD) than a single chronic condition alone in individuals with normal cognition, MCI, and AD. METHODS/STUDY POPULATION: We used longitudinal data from National Alzheimer Coordinating Center (n = 41,437) and focused on individuals with normal cognition (n =16,884, mean age (SD) = 70.72 (9.7)). Random forest models were used to predict newly developed MCI or AD from baseline to the most recent visits. We used self-reported baseline data on 50 chronic conditions and comprehensive clinical and demographic information (e.g., age, sex, APOE status, mini-mental status exam (MMSE) scores, education, BMI, and depressive symptoms). A binomial random forest was used to identify significant interactions (with p-values RESULTS/ANTICIPATED RESULTS: Our model demonstrated an AUC of 0.708 and a classification error rate of 25.4%. Variables of importance for predicting MCI or dementia were age, coronary artery bypass, depression, APOE status, smoking, and depressive symptoms. Two-way interactions, such as age X MMSE score, age X depressive symptoms, and age X BMI, were significant. Three-way interactions, including age X depressive symptoms X MMSE score, or depressive symptoms X BMI X MMSE score, were significant. However, when we explored the random forest model using only the chronic condition data, we found an AUC of 0.602 and an error rate of 27.15%. We found that depression, anxiety, hypercholesterolemia, stroke, and the interaction between BMI and anxiety were significant. DISCUSSION/SIGNIFICANCE: Random Forest models indicate that not only known factors including age, baseline cognitive status, and APOE status, but also chronic conditions like depression, anxiety, hypercholesterolemia, and stroke may predict cognitive impairment.

Convolutional Neural Networks to Classify Alzheimer’s Disease Severity Based on SPECT Images: A Comparative Study

Image recognition and neuroimaging are increasingly being used to understand the progression of Alzheimer's disease (AD). However, image data from single-photon emission computed tomography (SPECT) are limited. Medical image analysis requires large, labeled training datasets. Therefore, studies have focused on overcoming this problem. In this study, the detection performance of five convolutional neural network (CNN) models (MobileNet V2 and NASNetMobile (lightweight models); VGG16, Inception V3, and ResNet (heavier weight models)) on medical images was compared to establish a classification model for epidemiological research. Brain scan image data were collected from 99 subjects, and 4711 images were used. Demographic data were compared using the chi-squared test and one-way analysis of variance with Bonferroni's post hoc test. Accuracy and loss functions were used to evaluate the performance of CNN models. The cognitive abilities screening instrument and mini mental state exam scores of subjects with a clinical dementia rating (CDR) of 2 were considerably lower than those of subjects with a CDR of 1 or 0.5. This study analyzed the classification performance of various CNN models for medical images and proved the effectiveness of transfer learning in identifying the mild cognitive impairment, mild AD, and moderate AD scoring based on SPECT images.

Decrease in Gait Speed Over Time Is Associated With Increase in Number of Depression Symptoms in Older Adults With Type 2 Diabetes.

We examined the cross-sectional and longitudinal relationships of motor functions with depression in older adults with type 2 diabetes (T2D). Participants (n = 984) were from the longitudinal Israel Diabetes and Cognitive Decline (IDCD) study. They were initially cognitively normal and underwent evaluations of motor functions (grip strength and gait speed) and of depression (using the 15-item version of the Geriatric Depression Scale [GDS]) approximately every 18 months. We applied Hierarchical Linear Mixed Models (HLMM) to investigate the associations between motor functions and depression adjusting for sociodemographic, cardiovascular factors, overall cognitive score, and subjective report of exhaustion. Participants' baseline characteristics were 72 (±5) years of age (59.6% males), 13 (±4) years of education, Mini-Mental Status Exam (MMSE) score of 28.01 (±1.78), and a GDS score of (2 ± 2.00), consistent with normal cognitive status and lack of major affective symptomatology. Slower gait speed at baseline was associated with higher GDS scores (p = .001) and with their increase over time (p = .049). A decrease in walking speed from baseline was associated with an increase in GDS scores (p = .015). Lower grip strength at baseline was associated with higher GDS scores (p = .002), but not with trajectories in GDS scores over time. A faster decrease in grip strength from baseline was associated with a faster increase in GDS scores (p = .022). Both gait speed and grip strength are cross-sectionally associated with depression. However, only gait speed and its decrease over time can potentially be used to predict incident depression symptoms, thus facilitating the introduction of depression prevention strategies.

Optical coherence tomography and angiography in Alzheimer's disease and other cognitive disorders.

The aims of this study were to analyze retinal and choroidal changes on optical coherence tomography (OCT) and OCT-Angiography (OCT-A) in Alzheimer's disease (AD) patients and compare them to other forms of major dementia. We also aimed to analyze the correlation between clinical severity of global cognitive deficiency assessed by the mini-mental state exam (MMSE) score and OCT/OCT-A parameters. Retrospective cross-sectional evaluative study of AD, and age-and gender-matched patients with other dementias. Fundus examination, OCT and OCT-A were compared. Ninety-one eyes of AD patients and 53 eyes of patients with other dementias were included. Retinal deposits were found in 6.59% of AD cases. OCT highlighted the presence of hyperreflective deposits and localized areas of outer retina and ellipsoid zone disruption, respectively in 20.87% and 15.38% of AD cases. Hyperreflective foci were noted within inner retinal layers in 4.39% of AD cases. Quantitative analysis revealed a thicker nasal retinal nerve fiber layer (p = 0.001) and ganglion cell complex in superior (p = 0.011) and temporal quadrants (p = 0.009) in eyes of AD patients, compared to other dementias. OCT-A showed a significantly higher fractal dimension of both superficial and deep capillary plexus (p = 0.005), with lower choriocapillaris density (p = 0.003) in AD patients. Structural OCT could highlight the presence of hyperreflective deposits in AD, probably reflecting beta-amyloid deposits, associated to outer retinal disruptions. Quantitative OCT analysis showed structural differences between AD patients and other dementias, and combined OCT-A could identify microvascular changes in AD patients representing new potential differential diagnosis criteria.

CD34+ progenitor cells as diagnostic and therapeutic targets in Alzheimer's disease.

CD34+ progenitor cells as diagnostic and therapeutic targets in Alzheimer's disease.

S-02-4: BLOOD PRESSURE, ANTIHYPERTENSIVES AND DEMENTIA, AN INDIVIDUAL PATIENT DATA META-ANALYSIS

Background: A large number of observational studies show links between hypertension or higher blood pressure (BP) in mid-life and an increased risk of later dementia. In late life, the evidence is more mixed with some studies indicating higher BP is associated with higher dementia risk and some finding U-shaped associations between BP and incident dementia in older age. The clinical trials of antihypertensives to lower BP have shown largely negative results when examining the relationship between antihypertensive use and incident dementia. However, the trials were designed to examine cardiovascular endpoints and several stopped early for cardiovascular benefit thus limiting their statistical power and ability to accrue dementia outcomes. To overcome some of these limitations a pooled individual patient data meta-analysis of five seminal double-blind placebo-controlled randomised trials was undertaken to better define the effects of BP lowering treatment for the prevention of dementia. Methods: The double-blind placebo-controlled randomised antihypertensive trials; Action in Diabetes and Vascular disease: preterAx and diamicroN-MR Controlled Evaluation (ADVANCE), Hypertension in the Very Elderly Trial (HYVET), Perindopril Protection Against Recurrent Stroke Study (PROGRESS), Systolic Hypertension in the Elderly Program (SHEP), and SYSTolic Hypertension in EURope Trial (SYST-EUR) were merged into a single database. Multilevel logistic regression was used to evaluate the treatment effect on incident dementia. Effect modification was assessed for key population characteristics including age, baseline systolic BP, sex, baseline Mini-Mental State Exam (MMSE) score and presence of prior stroke. Results: All trials were balanced across randomised groups. The combined sample was n = 28,008 recruited from 20 countries. Mean baseline age was 69.1 (Standard Deviation 9.3). Median follow-up 4.3 years. Incident dementia occurred in 2.9% and 3.3% of those in active and placebo groups, respectively. Multilevel logistic regression reported an adjusted odds ratio 0.87 (95% confidence interval 0.75, 0.99) in favour of antihypertensive treatment reducing risk of incident dementia with a mean BP lowering of 10/4mmHg. Further multinomial regression taking account of death as a competing risk found similar results. There was no effect modification by age, sex, baseline systolic BP, baseline MMSE or prior stroke. Discussion: This is the first single-stage individual patient data meta-analysis from double-blind placebo-controlled clinical trials. It provides high-quality evidence to support the benefits of antihypertensive treatment in late-mid and later life to lower the risk of dementia. Questions remain as to the potential benefit from antihypertensive treatment commenced earlier in the life-course to reduce the long-term risk of dementia.

Probability Distributions for Associations Between Cognitive Screening and Pure-tone Thresholds in Older Adults.

Lower general cognitive function is frequently reported in older adults with elevated pure-tone thresholds. Here, we examined reason(s) for this association, including whether this relationship is dependent on the frequency range or extent of hearing loss and cognitive screening performance. Linear regression was used to examine associations between better-ear pure-tone thresholds and Mini-Mental Status Exam (MMSE) performance in a cross-sectional sample of relatively healthy older adults (N = 508; 68% women, 60-89+ years; M age = 72). Quantile regression was also used to identify the ranges of 0.5 and 4.0 kHz thresholds and MMSE scores where these variables exhibited significant associations. MMSE scores and pure-tone thresholds exhibited small but significant associations, particularly for better-ear 0.5 kHz thresholds. This hearing threshold and cognitive screening association was present among participants with better hearing, including the oldest older adults. There was limited evidence for mediating health condition effects on this association. An item analysis of the MMSE revealed that the MMSE and pure-tone threshold associations were largely due to the delayed recall item of the MMSE. Together, the small effect results are consistent with the extant literature and suggest that there are multiple reasons for modest pure-tone threshold and cognitive screening performance associations.

INCLUSION OF ETHNICALLY DIVERSE POPULATIONS IN CLINICAL TRIALS OF HEALTHSPAN: IMPLICATIONS FROM THE SALSA STUDY

Abstract Background Geroscience-guided clinical trials focused on healthspan may seek to enroll older adults initially free of chronic diseases and disability. Here we examine healthspan in the San Antonio Longitudinal Study of Aging (SALSA), a cohort of 749 community-dwelling older (65+ years) Mexican Americans (MA) and European Americans (EA), and describe prevalence and characteristics associated with poor healthspan. Methods Poor healthspan was defined at the SALSA baseline exam as presence of any one of: 1) chronic disease (diabetes, myocardial infarction, congestive heart failure, stroke, chronic obstructive pulmonary disease, or cancer); 2) dependence in basic or instrumental activities of daily living; or 3) mini mental state exam score &amp;lt; 18. Frailty was defined by Fried phenotype criteria. The association of poor healthspan with age, sex, ethnic group, socioeconomic status (SES), and frailty was assessed using chi-square or t-tests. Results 544 (72.6%) participants met criteria for poor healthspan, which was associated with older age (69.6 ±3.4 vs. 69.3 ±3.4, p&amp;lt; 0.05), male sex (77.3% vs. 69.2%, p&amp;lt; 0.05), MA ethnicity (77.4% vs. 67.3%, p&amp;lt; 0.05), lower income (11.3 ±3.1 vs. 12.2 ±2.9, p&amp;lt; 0.001 and education (10.4 ±4.6 vs. 12.7 ±3.2, &amp;lt; 0.0001), and frailty (95.5% vs. 4.6%, p&amp;lt; 0.001). Conclusion Poor healthspan was highly prevalent (&amp;gt;70%) in SALSA and associated with MA ethnicity, low SES, and frailty. Geroscience-guided clinical trials of potential interventions to improve healthspan by preventing chronic diseases and disability may under-represent individuals of ethnic minority background and lower SES and, thereby, jeopardize generalizability of the findings to the broader population.

WORSENING OF DEPRESSIVE SYMPTOMATOLOGY SINCE BEFORE COVID-19 AMONG CAREGIVERS OF PERSONS LIVING WITH DEMENTIA

Abstract This study examines factors associated with self-reported worsening of depressive symptomatology since before the COVID-19 pandemic among caregivers of persons living with dementia (PLWD). Cross-sectional baseline survey data were analyzed from 76 paid and unpaid caregivers of PLWD participating in a larger NIH-funded study assessing the feasibility of using a novel in-situ sensor system. Using the PHQ-2, caregivers were asked to report their depressive symptomatology twice: (1) retrospectively before the COVID-19 pandemic started; and (2) since the COVID-19 pandemic. A change score was calculated, and whether or not caregivers’ depressive symptomatology worsened since before the pandemic served as the dependent variable. A logistic regression model was fitted, controlling for contextual items related to the caregiver, care recipient, and caregiving logistics. On average, caregivers were age 58.09(±16.92) and the majority was female (84.2%). Thirty percent of caregivers reported worse depressive symptomatology since the COVID-19 pandemic than before the COVID-19 pandemic started. Caregivers who were female (OR=25.86, P=0.028), not paid for caregiving (OR=14.59, P=0.047), had lower annual household incomes (OR=0.50, P=0.032), and whose care recipients had higher Mini-Mental State Exam scores (OR=1.78, P=0.005) were more likely to report worse depressive symptomatology since the COVID-19 pandemic. Results suggest that the COVID-19 pandemic intensified depressive symptomatology for many caregivers, and unpaid, female caregivers with fewer financial resources have been especially impacted. As the pandemic continues, support for caregivers of PLWD should be tailored to specifically meet their needs and circumstances.

CAREGIVING BURDENS OF TASK TIME AND TASK DIFFICULTY AMONG PAID AND UNPAID CAREGIVERS OF PERSONS LIVING WITH DEMENTIA

Abstract Demands of caregivers of persons living with dementia (PLWD) are often influenced by the context of their caregiving situation. This study examines factors associated with caregiving burden in terms of task time and task difficulty among paid and unpaid caregivers of PLWD. Cross-sectional baseline survey data were analyzed from 110 paid and unpaid caregivers of PLWD participating in a larger NIH-funded study assessing the feasibility of using a novel in-situ sensor system. Oberst Caregiving Burden Scale constructs of task time and task difficulty served as dependent variables. Two least squares regression models were fitted, controlling for contextual items related to the caregiver, care recipient, and caregiving logistics. Caregivers whose care recipients were female (B=-0.29, P=0.006), had more chronic conditions (B=0.31, P=0.011), and had lower Mini-Mental State Exam scores (B=-0.20, P=0.015) reported higher task time burdens. Caregivers whose care recipients had other paid caregivers (B=0.30, P=0.031) and spent more months/years caring for their care recipients (B=0.28, P=0.004) reported higher task time burdens. Caregivers’ task time burden was positively associated with their emotional stress level (B=0.30, P=0.020). Caregivers’ task difficulty burden was positively associated with their emotional stress (B=0.30, P=0.029) and depressive symptomatology (B=0.32, P=0.002). Results reinforce the relationship between caregiver burden and mental health. While the care recipient’s disease profile and needs were drivers of task time burden, which may also require coordination with other paid caregivers, task difficulty was emotionally driven. Findings highlight the importance of caregiver support services and programming for mental health.

Differences between Weekly Physical Activity among People with Alzheimer’s Disease in Greece

Objective: Dementia is one social challenge with global prevalence. Creating personalized programs that enhance physical activity (PA) is an efficient approach for patients suffering from Alzheimer’s disease (AD), and a distinction between sexes to organize such programs is needed. Therefore, the present study focuses on differences in PA between male and female patients with AD and compared the number of performed steps in these patients during week and weekend days. Methods: In total, 21 patients with AD, who attended the daily center for dementia of the Psychogeriatric Association for Alzheimer in Athens and met the established criteria based on information obtained from neuropsychiatric examinations, were included in this study. The Mini-Mental State Examination Test was conducted, and data concerning the daily performed steps were obtained by using a portable pedometer, which the participants wore for 7 days. Results: The cognitive status and physical activity among male and female individuals were found to be similar. The results were similar for both week and weekend days. However, there was a significant correlation between the Mini-Mental State Exam scores and daily steps. Our findings suggest that PA is independently associated with sexes and weekdays in patients with mild to severe dementia. Conclusion: PA is an important factor in everyday life. Our findings suggest that there are no differences between the sexes regarding their physical activity. However, there was a significant link between the cognitive status and PA. Because of the small number of included participants, additional research is required to generalize our findings

Cerebrospinal Fluid Biomarkers of Synaptic Dysfunction are Altered in Parkinson's Disease and Related Disorders.

Synaptic dysfunction and degeneration are central contributors to the pathogenesis and progression of parkinsonian disorders. Therefore, identification and validation of biomarkers reflecting pathological synaptic alterations are greatly needed and could be used in prognostic assessment and to monitor treatment effects. To explore candidate biomarkers of synaptic dysfunction in Parkinson's disease (PD) and related disorders. Mass spectrometry was used to quantify 15 synaptic proteins in two clinical cerebrospinal fluid (CSF) cohorts, including PD (n1 =51, n2 =101), corticobasal degeneration (CBD) (n1 =11, n2 =3), progressive supranuclear palsy (PSP) (n1 =22, n2 =21), multiple system atrophy (MSA) (n1 =31, n2 =26), and healthy control (HC) (n1 =48, n2 =30) participants, as well as Alzheimer's disease (AD) (n2 =23) patients in the second cohort. Across both cohorts, lower levels of the neuronal pentraxins (NPTX; 1, 2, and receptor) were found in PD, MSA, and PSP, compared with HC. In MSA and PSP, lower neurogranin, AP2B1, and complexin-2 levels compared with HC were observed. In AD, levels of 14-3-3 zeta/delta, beta- and gamma-synuclein were higher compared with the parkinsonian disorders. Lower pentraxin levels in PD correlated with Mini-Mental State Exam scores and specific cognitive deficits (NPTX2; rho=0.25-0.32, P < 0.05) and reduced dopaminergic pre-synaptic integrity as measured by DaTSCAN (NPTX2; rho=0.29, P=0.023). Additionally, lower levels were associated with the progression of postural imbalance and gait difficulty symptoms (All NPTX; β-estimate=-0.025 to -0.038, P < 0.05) and cognitive decline (NPTX2; β-estimate=0.32, P=0.021). These novel findings show different alterations of synaptic proteins in parkinsonian disorders compared with AD and HC. The neuronal pentraxins may serve as prognostic CSF biomarkers for both cognitive and motor symptom progression in PD. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Higher CSF Ab38 levels protect against cognitive decline in high‐functioning individuals

AbstractBackgroundThe amyloid cascade hypothesis proposes that Alzheimer’s disease (AD) pathology starts with accumulation of b‐amyloid (Ab) peptides, leading to plaque deposition. In this context, the spotlight has been pointed firmly onto Ab42, but evidence suggests that shorter isoforms may also play an important role in modulating AD pathophysiology. A recent report with individuals with mild cognitive impairment or subjective cognitive decline (Cullen et al., 2021) has shown that higher cerebrospinal fluid (CSF) levels of Ab38 were associated with less decline on the mini‐mental state exam (MMSE) score and reduced risk of conversion to AD. The aim of this study was to test whether CSF Ab38 levels also predicted change in MMSE scores in cognitively intact individuals.MethodData were obtained from 40 individuals (age = 67.3, 6.3), who had taken part in a study on late‐life major depressive disorder at the Nathan Kline Institute and New York University. Data were available for baseline examination as well as three‐year follow up. Twenty‐three individuals were depressed at baseline, and 17 were controls; all had an MMSE score of 28 or higher at baseline. To test our hypothesis, we carried out a Bayesian linear regression analysis with change in MMSE score from baseline to follow‐up as outcome; CSF Ab38, CSF Ab42, and CSF phosphorylated (p) tau as predictors; and controlling for age, sex, APOE e4‐status and depression diagnosis (null model).ResultThe results showed that the model combining CSF Ab38 and CSF p tau was the strongest, with moderate evidence (BFm = 4), carrying nearly double the odds of the model with all predictors (BF10 = 0.539), and 4.6 times the odds of the null model (BF10 = 0.219): higher baseline levels of CSF Ab38 were associated with less decline in MMSE score, while higher p tau levels were linked to more decline. When isolating depressed individuals, the pattern of results was unchanged, while the null model was strongest with controls.ConclusionThese findings confirm the importance of examining shorter Ab isoforms also in individuals with no cognitive impairment or subjective cognitive decline.

A novel machine learning technique using resting‐state EEG to assess and monitor cognitive impairment

AbstractBackgroundMonitoring changes in cognitive impairment is an important aspect of care for aging patients. Traditionally, this is done with pen‐and‐paper assessments such as the Mini‐Mental State Exam (MMSE). EEG is a low‐cost and widely available neurophysiology tool that provides a data‐rich measure of brain health, but signal complexity has limited its impact. Advances in machine learning bring new possibilities to decode those complex signals and leverage EEG in patient care. Here, we engineer novel EEG features for assessing brain health with the [Banded Fractal Variability] (BFV) technique. We use [BFV] and other EEG metrics to assess patients’ cognitive function via a continuous score (a [Cognitive Impairment Index], or [CII]). We validate the diagnostic value of the EEG features by comparing our model against reduced models lacking the EEG features.MethodThe patient sample (N=97, mean (sd) age = 69.1 (11.0), 52.6% female) was collected at the Pacific Brain Health Center. Diagnostic categories included subjective cognitive impairment (n=44), mild cognitive impairment (n=26), and dementia (n=27). Mixed disease (AD, DLB, FTD, vascular, diabetes) was common in the impaired sample, and 39.6% were diagnosed with AD. We developed a continuous [CII] model trained on patients’ MMSE scores (range = 11 to 30, mean = 26.6) using a gradient boosting model with [Banded Fractal Variability] and other EEG features computed from clinical wake EEGs. Model development and testing took place within a rigorous nested cross‐validation (NCV) procedure to prevent overfitting. Performance was compared to reduced (no‐EEG features) models using the non‐parametric Wilcoxon sign‐rank test.ResultThe approach showed a Mean Absolute Error of 1.98 (sd = 0.28) across 5 test folds in the NCV outer loops, significantly outperforming both the baseline intercept‐only model (p = 0.031) and the demographics (age and years of education) model (p = 0.031).ConclusionThese preliminary results suggest that our [CII] derived from machine‐learning and quantitative EEG using [BFV] is a viable approach to assess and track patients’ cognitive impairment regardless of disease status across all impairment levels, raising the possibility that a brief EEG scan could shed light on patient health normally accessible only through extensive cognitive and neuropsychological testing.

Diagnostic Utility of Brain MRI Volumetry in Comparing Traumatic Brain Injury, Alzheimer Disease and Behavioral Variant Frontotemporal Dementia

AbstractBackgroundApplication of brain MRI with volumetric quantification can improve delineation of various neurocognitive disorders.MethodWe utilized 136 participants from previously defined cohorts of traumatic brain injury (TBI; n=40) [1], early (EOAD; n=45) and late onset Alzheimer disease (LOAD; n=31) [2] as well as of behavioral variant frontotemporal dementia (bvFTD; n=20). Participants had brain MRI including 3D T1 sequences amendable to volumetric quantification. Scans were analyzed with an FDA cleared software program, Neuroreader[3] to measure regional brain volumes. At the time of analysis, Mini‐Mental State Exam (MMSE) scores were available on majority of participants (n=125). One‐way ANOVA compared mean age, MMSE, and brain volumes across all four groups with Bonferroni correction for multiple comparisons. All brain volumes were corrected for total intracranial volume (TIV). Discriminant analysis was done with leave‐one‐out cross validation on measured brain volumes to determine diagnostic delineation across groups. Automated linear regression identified predictive features from these quantified structures.ResultParticipant demographics and MMSE scores are shown in Table 1. With respect to age, LOAD was the oldest compared to other groups (p&lt;.001). There were no statistically significant differences in sex (p=.58) with women comprising 54.4% of the entire sample. EOAD and LOAD had the lowest MMSE scores compared to TBI (p=.04 for EOAD and p=.01 for LOAD). Regional volume difference across groups showed lowest hippocampal volumes in LOAD (p=.005), low white matter volume in TBI (p=.007), lower parietal lobe volumes in EOAD (p&lt;.01), and lower frontal lobe volumes in bvFTD (p&lt;.001). Regional volume differences resulted in a correct classification of 89%, 79.4% after cross validation. Predictive features included caudate, amygdala, frontal, parietal, temporal lobar and total white matter volumes.ConclusionWe identified the diagnostic utility of regional volumetric differences across multiple neurodegenerative and non‐neurodegenerative disorders. The lower parietal lobe volumes in EOAD and lower hippocampal volumes in LOAD and well as frontal atrophy of bvFTD reflect the known anatomical distribution of pathology in those conditions[4]. The white matter volume loss in TBI is a previously demonstrated feature of that condition[5]. Brain MRI volumetry may therefore be beneficial in clinical practice.

Working Memory Performance for Semantically Related Objects Distinguishes Cognitively‐Unimpaired Mutation Carriers from Non‐Carriers in a Colombian kindred with Autosomal Dominant Alzheimer’s Disease

AbstractBackgroundThe identification of cognitive tests sensitive to subtle changes in the preclinical stage of Alzheimer’s disease (AD) is of upmost importance to early detection of the disease, and to optimizing AD clinical trial recruitment. We used a delayed matching‐to‐sample (DMS) paradigm to study working memory for semantic relatedness in young adult carriers and non‐carriers of an autosomal dominant AD (ADAD) mutation from the Colombian kindred.Methods35 cognitively‐unimpaired Presenilin1 (PSEN1) E280A mutation carriers and 26 non‐carrier family members took the “Memory for Semantically‐Related Objects” test (MESERO), a computerized DMS working memory test for semantically‐related (and unrelated objects) developed by our group. The MESERO shows an equal number of either 4 or 6 objects that are semantically‐related or unrelated and records accuracy out of 80 points total (40 semantically‐related trials; 40 unrelated trials), as well as reaction time in milliseconds. Participants also completed the Mini‐Mental State Exam (MMSE). MESERO behavioral responses between groups were evaluated with the Mann‐Whitney test; age, MMSE scores, and education were compared with independent samples t‐tests.ResultsNon‐carriers were significantly older (M = 36.7 years, SD = 6.5) and had slightly, but significantly higher MMSE scores (M = 28.8, SD = 6.5) than the carriers (age: M = 30.5, SD = 5.3; t = 3.92, p&lt;.001; MMSE: M = 28.1, SD = 1.2; p&lt;.001). The groups did not differ on education (∼mean of 11 years for both; t = 0.29, p = .39). On the MESERO total score, mutation carriers had significantly lower performance (mean = 70.8, SD = 6.5) relative to non‐carriers (mean = 73.5, SD = 5.7; U = 312, p = .04). The PSEN1 E280A carriers, in particular, performed worse on the semantically‐related trials (mean = 33.9, SD = 4.2) relative to non‐carriers (mean = 35.8, SD = 2.9; U = 312.5, p = .04), but not on unrelated trials (U = 357, p = .19). The carriers performed worse than non‐carriers on trials with 4‐items (mean = 35.5, SD = 4.2 vs. mean = 37.3, SD = 3.2) (U = 300.5, p = .02), but not with 6‐items in the study phase (U = 366.5, p = .19).ConclusionA brief computerized working memory task for semantically‐related objects was able to distinguish cognitively unimpaired mutation carriers from non‐carriers from a Colombian kindred with autosomal dominant Alzheimer’s disease, approximately 14 years before the median age of mild cognitive impairment onset in this cohort. Working memory for semantic relatedness warrants further study as a potential marker of preclinical AD.