Normal Cognition Research Articles

Detection of Mild Cognitive Impairment Using Convergent Cross‐Mapping Based on Resting‐State EEG Signals among Community‐Dwelling African American Participants

AbstractBackgroundAccurate and early detection of mild cognitive impairment (MCI) is critical for interventions to promote cognitive resiliency. EEG‐based detection of MCI is attracting considerable attention from the research community due to its accessibility, affordability and increasing accuracy.MethodOur research is based on resting‐state EEG (64‐channel, eye‐closed). The current dataset includes 90 consensus‐diagnosed, community‐dwelling African Americans (ages 60‐90 years, 51 normal cognition, NC; 39 Mild Cognitive Impairment, MCI) recruited through the Wayne State Institute of Gerontology Healthy Black Elders Center and the Michigan Alzheimer’s Disease Research Center, all with subjective cognitive complaints.From an information‐theoretic perspective, causality measures the effective connectivity or directed information transfer from one brain region to another. Convergent cross‐mapping has attracted considerable attention recently since it was proven to be able to detect causal coupling in both deterministic and random settings. In this research, we propose to develop an EEG‐based MCI detection model by exploiting cross‐mapping causality analysis.We first derived the current source density (CSD) from EEG signals and performed cross‐mapping based causality analysis between the CSD signals of all the possible pairs across the selected EEG regions of interest. We then conducted joint time‐frequency‐spatial analysis on the cross‐mapping causation and selected features which are likely to reflect the differences between NC and MCI. The selected features were then fed into a machine‐learning algorithm for discrimination of NC and MCI.ResultBy tuning the observing window size and the number of features used, we obtained a series of different configurations of the discrimination model between NC and MCI, each with its own estimation accuracy. The overall result is a combined output of the model under different configurations, which improve the reliability and sensitivity of the discrimination model. For the 90‐sample dataset we are working with, the leave‐one‐out cross‐validation accuracy of our model is 97.78%.ConclusionOur analysis indicates that, potentially, EEG‐based cross‐mapping causality analysis may serve as a promising assessment tool for early detection of people at risk of MCI and dementia, even when just relying on resting state EEG.Funding: NSF‐2032709/Li; NIH‐1R21AG046637‐01A1/Kavcic and NIH‐1R01AG054484‐01A1/Kavcic; NIH‐ P30AG05376004/Paulson

Direct Electrophysiological Imaging Measure as a Novel Method for Detection of Onset of Medial Temporal Atrophy in Healthy Population

AbstractBackgroundMedial temporal atrophy (MTA) has long been demonstrated as a prognostic measure for transition from normal cognition to MCI and from MCI to Dementia, often but not only due to Alzheimer’s disease (AD). However, brain scans availability and costs do not allow for it to be implemented as common practice, for early detection of MTA in cognitively normal patients.We tested “Delphi”, a non‐invasive measure that probes brain network responses via induction of focused magnetic stimulation over selected brain networks in order to detect MTA.MethodA multicenter study (3 US, 2 OUS), in which one site recruited the derivation cohort (n = 220) which was used for establishing “Delphi” thresholds, and four sites recruited the validation cohort (n = 263, mean age 61.5 (±7.1), 57% females).The study included healthy subjects aged 50‐75 with at least one risk factor for stroke or dementia and no history of neurodegenerative disease.All subjects underwent multiple evaluations including a neurological exam, cognitive tests, MRI scans and “Delphi”. Three experienced neuroradiologists blindly rated the scans for MTA (Schelten’s scale, ‘Normal’‐MTA = 0, ‘Abnormal’‐MTA> = 1) and other findings.Result263 subjects were included in the validation cohort, out of which 23 subjects were rated MTA≥1 (69% MTA = 1, 17% MTA = 2 and 13% MTA = 3) while the rest were MTA = 0 on MRI scanning.Out of the total sample 11% had abnormal result in MMSE (≤27) and 15% had abnormal result in MoCA (≤23) and only 13% had abnormal result in each of MMSE and MoCA in the MTA≥1 subgroup.“Delphi” discriminated subjects with MTA = 0 from MTA≥1 with AUC = 0.81, sensitivity = 82% [95%CI 62.86%:93.02%], specificity = 75% [95% CI 63.62:81.0%].ConclusionBrain network physiology evaluation using the “Delphi” technology may serve to detect early stages of MTA, preceding cognitive impairment with substantial accuracy in the outpatient office setting in a generally healthy population. This could allow the expansion of the physician’s in‐office tools, potentially improving patient management.

Speech markers of depression dimensions across the spectrum of cognitive functions

AbstractBackgroundDepression is a common among patients with cognitive impairment and encompass different dimensions, which may vary in their association with cognitive outcomes and biological substrates. Previous studies have shown a shift toward the use of more negative words in written documents and social media posts of depressed patients with intact cognitive function. To objectively characterize depression dimensions across the spectrum of cognitive functions, we explored their association with the emotion‐based measures of speech in participants of memory clinic.MethodsThis study capitalized on semi‐structured digitized speech data collected at the hospital of University of Pennsylvania. Subjects (n = 302, 40% female, mean age = 67.13±9.59 years, education = 15.82±2.84 years, Mini‐Mental Status Exam (MMSE) = 24.36±5.04) were native English speakers with cognition ranging from normal cognition to mild dementia. Participants were instructed to describe the Cookie Theft scene using complete sentences and their descriptions were digitally recorded. Emotion‐based measures of the content words, including valence (i.e., the pleasantness), arousal (the intensity of emotions), and dominance (the word power), were rated based on published norms. Each emotional measure was averaged per speaker. Depression dimensions were defined based on itemized Geriatric Depression Scale – 15 item (GDS‐15) including Dysphoria, Withdrawal‐Apathy–Vigor (WAV), anxiety, hopelessness and Subjective Memory Complaint. Non‐parametric partial correlations examined associations between speech emotion‐based measures and depression scores adjusting for age, sex, education and MMSE.ResultsOverall depression score (total GDS) did not correlate with the speech measures. However, when examining specific depression dimensions, higher WAV and hopelessness correlated with reduced valence (WAV: r = ‐0.21, P = 0.00, hopelessness: r = ‐ 0.14, P = 0.01) and dominance (WAV: r = ‐ 0.18, P = 0.001, hopelessness: r = ‐ 0.16, P = 0.004). We did not find a significant association between emotional word scores and other depression dimensions.ConclusionPatients with high apathy and hopelessness select words that carry more negative and less powerful emotional valence. Our findings highlight the potential applicability of speech biomarkers in characterization of depression dimensions across spectrum of cognitive and are consistent with previous findings that reported more negative bias and more submissive speech in depressed patients.

Neuroimaging Characteristics of Hearing Loss in the Mayo Clinic Study of Aging.

To investigate the association between standard pure tone and speech audiometry with neuroimaging characteristics reflective of aging and dementia in older adults. Prospective population-based study. Single tertiary care referral center. Participants from the Mayo Clinic Study of aging 60 years old or older with normal cognition or mild cognitive impairment, baseline neuroimaging, and a behavioral audiogram associated with neuroimaging were eligible for study. Imaging modalities included structural MRI (sMRI) and fluid-attenuated inversion recovery MRI (FLAIR-MRI; N = 605), diffusion tensor imaging MRI (DTI-MRI; N = 444), and fluorodeoxyglucose-positron emission tomography (FDG-PET; N = 413). Multivariable logistic and linear regression models were used to evaluate associations with neuroimaging outcomes. Mean (SD) pure tone average (PTA) was 33 (15) dB HL and mean (SD) word recognition score (WRS) was 91% (14). There were no significant associations between audiometric performance and cortical thinning assessed by sMRI. Each 10-dB increase in PTA was associated with increased likelihood of abnormal white-matter hyperintensity (WMH) from FLAIR-MRI (odds ratio 1.26, P = .02). From DTI-MRI, participants with <100% WRSs had significantly lower fractional anisotropy in the genu of the corpus callosum (parameter estimate [PE] -0.012, P = .008) compared to those with perfect WRSs. From FDG-PET, each 10% decrease in WRSs was associated with decreased uptake in the anterior cingulate cortex (PE -0.013, P = .001). Poorer audiometric performance was not significantly associated with cortical thinning but was associated with white matter damage relevant to cerebrovascular disease (increased abnormal WMH, decreased corpus callosum diffusion). These neuroimaging results suggest a pathophysiologic link between hearing loss and cerebrovascular disease.

Periodontitis is associated with altered brain structure and function in normal cognition middle-aged and elderly individuals.

Numerous studies have proposed that periodontitis is a potential risk factor for Alzheimer's disease. However, the association between periodontitis and brain normal cognition in aged and elderly individuals (NCs) is unclear. Such a link could provide clues to Alzheimer's disease development and strategies for early prevention. To explore the associations between periodontal condition and metrics of both brain structure and function among NCs with the help of multimodal magnetic resonance imaging (MRI). High-resolution T1-weighted structural data, resting-state functional-MRI data, and measures of periodontal condition were collected from 40 NCs. Cortical volume, thickness, and area as well as regional homogeneity were calculated with the aid of DPABISurf software. Correlation analyses were then conducted between each imaging metric and periodontal index. Consistent negative correlations were observed between severity of periodontitis (mild, moderate, severe) and cortical volume, area, and thickness, not only in brain regions that took charge of primary function but also in brain regions associated with advanced cognition behavior. Among participants with mild attachment loss (AL) and a shallow periodontal pocket depth (PPD), periodontal index was positively correlated with most measures of brain structure and function, while among participants with severe AL and deep PPD, periodontal index was negatively correlated with measures of brain structure and function (all p < .005 for each hemisphere). Our results demonstrate that periodontitis is associated with widespread changes in brain structure and function among middle-aged and elderly adults without signs of cognitive decline, which might be a potential risk factor for brain damage.

Evaluating the impact of aerobic and resistance green exercises on the fitness, aerobic and intrinsic capacity of older individuals

ObjectiveOur study determined the impact of 12-week aerobic exercise (AE) and aerobic + resistance exercises (AE + RE) within the green exercise concept, on senior fitness, aerobic capacity, and intrinsic capacity (IC). MethodsThe study was a multicenter, randomized controlled study conducted at two senior living facilities with individuals aged 65 and above whose cardiorespiratory and musculoskeletal conditions are suitable for moderate exercise and who have normal cognition levels. Block randomization was applied to 96 participants in a ratio of 1:1:1 to be assigned to AE, AE + RE, and control (C) groups. Intervention groups received exercise sessions led by physiotherapists within the senior living facilitiy gardens, with a frequency of once a week for 50 min, for 12 weeks. Also, they were prescribed additional exercise sessions on two additional days of the week. At the commencement of the study and 12th week, shuttle walking test, senior fitness test (SFT), intrinsic capacity assessment (with Timed Up and Go test, Mini Mental State Examination, Geriatric Depression Scale-15, Mini Nutritional Assessment, handgrip strength test) was conducted of all participants. The primary outcome was the Z score of IC, secondary outcomes were VO2max and SFT subparameters. The study was registered in the Protocol Registry and Results System (Clinicaltrials.gov PRS) with the registration number NCT05958745. Results90 participants successfully completed the study, with 30 individuals in each of the AE, AE + RE, and C groups. By the end of the 12th week, the arm curl score was significantly higher in the AE + RE compared to the C (mean difference: 3.96, 95 % CI= 2.47 to 5.46, p = 0.01). There were significant differences in chair stand, two-minute step, 8-foot up-and-go, chair sit and reach, and back scratch tests in both AE and AE + RE compared to C. AE and AE + RE exhibited significantly higher shuttle test distances and VO2max values compared to the C (p < 0.0001). AE + RE achieved a significantly higher total IC score than the C (mean difference: 0.59, %95 CI= -0.07 to 1.26, p = 0.025). ConclusionIn this study within the green exercise concept, both AE and AE + RE led to similar improvements in strength, flexibility, mobility, endurance, and aerobic capacity. Notably, AE + RE demonstrated an additional benefit by increasing the total IC, while AE alone did not exhibit the same effect.

Cognitive performance and all-cause mortality in community dwellers of Amerindian ancestry living in rural Ecuador: A population-based, longitudinal prospective study

ObjectiveThere is limited information on mortality risk in individuals with cognitive impairment living in rural Latin America. In this study, we assess the association between cognitive impairment and all-cause mortality in adults of Amerindian ancestry living in rural Ecuador. Patients and methodsMiddle-aged and older adults enrolled in the population-based Three Villages Study cohort were followed prospectively in order to estimate mortality risk according to their baseline cognitive performance as determined by the Montreal Cognitive Assessment (MoCA). Results were adjusted for demographics, level of education, traditional cardiovascular risk factors, symptoms of depression, severe tooth loss, and oily fish intake (factors previously associated with mortality in the study population). ResultsAnalysis included 1022 individuals followed for an average of 7.8 ± 3.4 years. Mean MoCA score was 21.2 ± 5.4 points (median: 22 points), with 334 (32.7%) individuals showing cognitive impairment, as evidenced by a MoCA score ≤ 19 points (the cutoff for poor cognitive performance based on previous studies in the same population). A total of 150 (14.7%) individuals died during the follow-up. Crude mortality rate was 2.87 per 100 person-years (95% C.I.: 2.08 – 3.96). For individuals with normal cognition, the mortality rate was 1.21 (95% C.I.: 0.92 – 1.50) while for those with cognitive impairment the rate increased to 3.48 (95% C.I.: 2.73 – 4.23). A multivariate Cox-proportional hazards model, confirmed that individuals with cognitive impairment had a significantly higher mortality risk than those without cognitive impairment (HR: 1.52; 95% C.I.: 1.05 – 2.18). ConclusionsCognitive impairment is associated with mortality in the study population.

Differences in Retinal and Choroidal Microvasculature and Structure in Dementia With Lewy Bodies Compared With Normal Cognition.

Purpose: To evaluate the retinal and choroidal microvasculature and structure in individuals with dementia with Lewy bodies (DLB) compared with controls with normal cognition using optical coherence tomography (OCT) and OCT angiography (OCTA). Methods: An institutional review board-approved cross-sectional comparison of patients with DLB and cognitively normal controls was performed. The Cirrus HD-OCT 5000 with AngioPlex (Carl Zeiss Meditec) was used to obtain OCT and OCTA images. Results: Thirty-four eyes of 18 patients with DLB and 85 eyes of 48 cognitively normal patients were analyzed. The average capillary perfusion density (CPD) was higher in the DLB group than in the control group (P = .005). The average capillary flux index (CFI) and ganglion cell inner-plexiform layer (GC-IPL) thickness were lower in the DLB group than in the control group (P = .016 and P = .040, respectively). Conclusions: Patients with DLB had an increased peripapillary CPD, decreased peripapillary CFI, and attenuated GC-IPL thickness compared with those with normal cognition.

Non-alcoholic fatty liver disease is associated with brain function disruption in type 2 diabetes patients without cognitive impairment.

To investigate the neural static and dynamic intrinsic activity of intra-/inter-network topology among patients with type 2 diabetes (T2D) with non-alcoholic fatty liver disease (NAFLD) and those without NAFLD (T2NAFLD group and T2noNAFLD group, respectively) and to assess the relationship with metabolism. Fifty-six patients with T2NAFLD, 78 with T2noNAFLD, and 55 healthy controls (HCs) were recruited to the study. Participants had normal cognition and underwent functional magnetic resonance imaging scans, clinical measurements, and global cognition evaluation. Independent component analysis was used to identify frequency spectrum parameters, static functional network connectivity, and temporal properties of dynamic functional network connectivity (P < 0.05, false discovery rate-corrected). Statistical analysis involved one-way analysis of covariance with post hoc, partial correlation and canonical correlation analyses. Our findings showed that: (i) T2NAFLD patients had more disordered glucose and lipid metabolism, had more severe insulin resistance, and were more obese than T2noNAFLD patients; (ii) T2D patients exhibited disrupted brain function, as evidenced by alterations in intra-/inter-network topology, even without clinically measurable cognitive impairment; (iii) T2NAFLD patients had more significant reductions in the frequency spectrum parameters of cognitive executive and visual networks than those with T2noNAFLD; and (iv) altered brain function in T2D patients was correlated with postprandial glucose, high-density lipoprotein cholesterol, and waist-hip ratio. This study may provide novel insights into neuroimaging correlates for underlying pathophysiological processes inducing brain damage in T2NAFLD. Thus, controlling blood glucose levels, lipid levels and abdominal obesity may reduce brain damage risk in such patients.

Longitudinal association of subclinical cardiac function with cognitive function

Abstract Background Cognitive impairment and heart disease frequently co-exist due to shared disease processes and pathological mechanisms. The presence of one may lead to and/or worsen the other. This bidirectional relationship between cognitive impairment and heart disease acts as a vicious cycle that increases the burden of both diseases. Our previous findings have demonstrated that cognitive impairment is a strong predictor of post-discharge readmission or death in heart failure, second only to heart failure severity. However, whether heart failure and cognitive impairment has a causal relationship remains unknown. This study sought to determine the relationship between subclinical cardiac function and cognitive function. Methods This study included 1977 consecutive patients (62% men, aged 73±13 years) with heart failure ranging from stage A to C. These patients were followed up for 36 months. At both baseline and follow-up, subclinical cardiac function was measured by echocardiography, and cognitive function was measured using Montreal Cognitive Assessment (MOCA). Other measurements included blood biochemistry, comorbidities, physical measurements and questionnaires. Results Cognitive function was strongly associated with both readmission and death in patients with heart failure, particularly among those with stage C. Among patients with heart failure stage A or B, left atrial volume index (LAVI) and E/e’ were associated with a reduction of MOCA score and higher risks of newly developed cognitive impairment at 36-month follow-up (OR = 1.04 [95% CI:1.02-1.07] per 1ml/m2 LAVI, and OR = 1.07 [95% CI:1.01-1.15] per 1 unit E/e’). Patients with cognitive impairment have significantly enlarged left atrium, compared with those with normal cognition (p&amp;lt;0.001). While almost all (93%) of patients with consistent cognitive impairment from baseline to follow-up had an enlarged left atrium, 71% of those who became cognitively impaired at follow-up had an enlarged left atrium. Conclusions The longitudinal relationship between diastolic cardiac function and cognitive function suggests a causal pathway between these two. Assessment of cognitive function is recommended in patients with impaired cardiac function.

Alterations via inter-regional connective relationships in Alzheimer's disease.

Disruptions in the inter-regional connective correlation within the brain are believed to contribute to memory impairment. To detect these corresponding correlation networks in Alzheimer's disease (AD), we conducted three types of inter-regional correlation analysis, including structural covariance, functional connectivity and group-level independent component analysis (group-ICA). The analyzed data were obtained from the Alzheimer's Disease Neuroimaging Initiative, comprising 52 cognitively normal (CN) participants without subjective memory concerns, 52 individuals with late mild cognitive impairment (LMCI) and 52 patients with AD. We firstly performed vertex-wise cortical thickness analysis to identify brain regions with cortical thinning in AD and LMCI patients using structural MRI data. These regions served as seeds to construct both structural covariance networks and functional connectivity networks for each subject. Additionally, group-ICA was performed on the functional data to identify intrinsic brain networks at the cohort level. Through a comparison of the structural covariance and functional connectivity networks with ICA networks, we identified several inter-regional correlation networks that consistently exhibited abnormal connectivity patterns among AD and LMCI patients. Our findings suggest that reduced inter-regional connectivity is predominantly observed within a subnetwork of the default mode network, which includes the posterior cingulate and precuneus regions, in both AD and LMCI patients. This disruption of connectivity between key nodes within the default mode network provides evidence supporting the hypothesis that impairments in brain networks may contribute to memory deficits in AD and LMCI.

A fixel-based analysis of white matter reductions early detects Parkinson disease with mild cognitive impairment

BackgroundWhite matter (WM) tract alterations are early signs of cognitive impairment in Parkinson disease (PD) patients. Fixel-based analysis (FBA) has advantages over traditional diffusion tensor imaging in managing complex and crossing fibers. We used FBA to measure fiber-specific changes in patients with PD mild cognitive impairment (PD-MCI) and PD normal cognition (PD-NC). MethodsSeventy-one patients with PD without dementia were included: 39 PD-MCI and 32 PD-NC. All underwent diffusion-weighted imaging, clinical examinations, and tests to evaluate their cognitive function globally and in five cognitive domains. FBA was used to investigate fiber-tract alterations and compare PD-MCI with PD-NC subjects. Correlations with each cognitive test were analyzed. ResultsPatients with PD-MCI were significantly older (p = 0.044), had a higher male-to-female ratio (P = 0.006) and total Unified Parkinson's Disease Rating Scale score (P = 0.001). All fixel-based metrics were significantly reduced within the body of the corpus callosum and superior corona radiata in PD-MCI patients (family-wise error-corrected P value < 0.05) compared with PD-NC patients. The cingulum, superior longitudinal fasciculi, and thalamocortical circuit exhibited predominantly fiber-bundle cross-section (FC) changes. In regression analysis, reduced FC values in cerebellar circuits were associated with poor motor function in PD-MCI patients and poor picture-naming ability in PD-NC patients. ConclusionsPD-MCI patients have significant WM alterations compared with PD-NC patients. FBA revealed these changes in various bundle tracts, helping us to better understand specific WM changes that are functionally implicated in PD cognitive decline. FBA is potentially useful in detecting early cognitive decline in PD.

Plasma Amyloid-β, Total Tau, and Neurofilament Light Chain Across the Alzheimer's Disease Clinical Spectrum: A Population-Based Study.

Plasma biomarkers have emerged as a promising approach for characterizing pathophysiology in mild cognitive impairment (MCI) and Alzheimer's disease (AD). We aimed to characterize plasma biomarkers for AD and neurodegeneration across the AD clinical continuum, and to assess their ability to differentiate between AD, MCI, and normal cognition. This population-based study engaged 1,446 rural-dwelling older adults (age ≥60 years, 61.0% women) derived from MIND-China; of these, 402 were defined with MCI and 142 with AD. Plasma amyloid-β (Aβ), total tau (t-tau), and neurofilament light chain (NfL) concentrations were analyzed using the Simoa platform. Data were analyzed using linear and logistic regression models, and receiver operating characteristic (ROC) analysis. Across the AD clinical spectrum, plasma Aβ40 and NfL increased, whereas Aβ42/Aβ40 ratio decreased. Plasma t-tau was higher in people with AD dementia than those with MCI or normal cognition. Plasma NfL outperformed other biomarkers in differentiating AD from normal cognition (area under the ROC curve [AUC] = 0.75), but all plasma biomarkers performed poorly to distinguish MCI from normal cognition (AUC <0.60). Plasma NfL in combination with age, sex, education, and APOE genotype yielded the AUC of 0.87 for differentiating between AD and normal cognition, 0.79 between AD and MCI, and 0.64 between MCI and normal cognition. In this Chinese population, AD plasma biomarkers vary by age, sex, and APOE genotype. Plasma Aβ, t-tau, and NfL differ across the AD clinical spectrum, and plasma NfL appears to be superior to plasma Aβ and t-tau for defining the clinical spectrum.

Abstract 13947: Racial Differences in Peripheral Microvasculature's Association With Mild Cognitive Impairment

Introduction: Cardiovascular disease (CVD) and Alzheimer’s Dementia (AD) share numerous risk factors, with vascular dysfunction a common underlying mechanism. Individuals with mild cognitive impairment (MCI) have a high likelihood of developing AD in their lifetime. The link between microvascular dysfunction (MVD) and AD has yet to be fully established. Hypothesis: We examined the contribution of MVD to MCI with the hypothesis that Black Americans, who have a higher prevalence of MVD, will have higher rates of MCI. Methods: Participants &gt;50 years with MCI or with normal cognition (NC) were enrolled for neuropsychological and microvascular function testing using peripheral arterial tonometry. Microvascular function was measured as the reactive hyperemia index (RHI) and calculated as the ratio of the post- to pre-occlusion pulse volume in the fingertip (EndoPAT). Multivariate analyses, adjusting for demographic and CVD risk factors associated with MCI, evaluated the relationship between RHI and MCI in Black and White participants. Causal mediation analysis, using the Monte Carlo approach, was performed to investigate whether the effect of RHI on MCI was mediated through plausible mediators, including risk factors. Results: Of 152 participants (NC=104, MCI=48), 41.4% were Black and 33.6% male. Participants with MCI were more likely to be Black (58.3% vs 33.7%%, p=0.007) and have lower RHI (1.93 vs 2.27, p=0.004) compared to NC. RHI was an independent predictor of MCI with a 96% adjusted greater odds of MCI per unit reduction in RHI. Black race remained an independent predictor of MCI (OR 2.90, 95% CI [1.16, 7.56]). RHI was lower in Black compared to White participants (1.86 vs 2.37, p&lt;0.001). There was no heterogeneity in the impact of RHI on MCI. In a casual mediation analysis, MCI was mediated via RHI more in Black than in White participants (proportion mediated 24.2% vs 18.4%, p=0.034) after multivariate adjustment. Conclusions: Peripheral MVD, measured as RHI, was independently associated with MCI. Furthermore, Black participants exhibited lower RHI levels, a higher prevalence of MCI, and potentially mediated MCI through RHI to a greater extent compared to their White counterparts.

Prodromal Motoric Cognitive Risk Syndrome and Everyday Function.

Motoric cognitive risk syndrome (MCR), a pre-dementia syndrome characterized by subjective cognitive complaints and slow gait, is associated with disability in instrumental activities of daily living. It is unknown whether these functional limitations occur even before this pre-dementia syndrome is diagnosed. To assess profiles of complex and instrumental activities of daily living in the prodromal stages of MCR. We examined functional profiles in 46 older adults (mean age 79 years, 59% women) living in the community with normal cognition at baseline who developed MCR over follow-up ('pre-MCR') with 264 older adults (mean age 75 years, 57% women) who remained cognitively intact over the follow-up period. Pre-MCR individuals had more limitations on complex everyday function at baseline compared to normal controls in multivariable logistic regression models (odds ratio 1.21). Pre-MCR cases at baseline had limitations in handling finances (odds ratio 3.0) and performing hobbies (odds ratio 5.5) as compared to normal controls. Pre-MCR cases had a greater difference in the number of complex functional limitations from baseline to MCR compared to the difference from baseline to final visit for the controls (1.2±3.0 versus 0.5±2.2, p < 0.001). Limitations in complex everyday tasks arise in the prodromal stages of MCR and can assist in risk prognostication.

Algorithmic Fairness of Machine Learning Models for Alzheimer Disease Progression

Predictive models using machine learning techniques have potential to improve early detection and management of Alzheimer disease (AD). However, these models potentially have biases and may perpetuate or exacerbate existing disparities. To characterize the algorithmic fairness of longitudinal prediction models for AD progression. This prognostic study investigated the algorithmic fairness of logistic regression, support vector machines, and recurrent neural networks for predicting progression to mild cognitive impairment (MCI) and AD using data from participants in the Alzheimer Disease Neuroimaging Initiative evaluated at 57 sites in the US and Canada. Participants aged 54 to 91 years who contributed data on at least 2 visits between September 2005 and May 2017 were included. Data were analyzed in October 2022. Fairness was quantified across sex, ethnicity, and race groups. Neuropsychological test scores, anatomical features from T1 magnetic resonance imaging, measures extracted from positron emission tomography, and cerebrospinal fluid biomarkers were included as predictors. Outcome measures quantified fairness of prediction models (logistic regression [LR], support vector machine [SVM], and recurrent neural network [RNN] models), including equal opportunity, equalized odds, and demographic parity. Specifically, if the model exhibited equal sensitivity for all groups, it aligned with the principle of equal opportunity, indicating fairness in predictive performance. A total of 1730 participants in the cohort (mean [SD] age, 73.81 [6.92] years; 776 females [44.9%]; 69 Hispanic [4.0%] and 1661 non-Hispanic [96.0%]; 29 Asian [1.7%], 77 Black [4.5%], 1599 White [92.4%], and 25 other race [1.4%]) were included. Sensitivity for predicting progression to MCI and AD was lower for Hispanic participants compared with non-Hispanic participants; the difference (SD) in true positive rate ranged from 20.9% (5.5%) for the RNN model to 27.8% (9.8%) for the SVM model in MCI and 24.1% (5.4%) for the RNN model to 48.2% (17.3%) for the LR model in AD. Sensitivity was similarly lower for Black and Asian participants compared with non-Hispanic White participants; for example, the difference (SD) in AD true positive rate was 14.5% (51.6%) in the LR model, 12.3% (35.1%) in the SVM model, and 28.4% (16.8%) in the RNN model for Black vs White participants, and the difference (SD) in MCI true positive rate was 25.6% (13.1%) in the LR model, 24.3% (13.1%) in the SVM model, and 6.8% (18.7%) in the RNN model for Asian vs White participants. Models generally satisfied metrics of fairness with respect to sex, with no significant differences by group, except for cognitively normal (CN)-MCI and MCI-AD transitions (eg, an absolute increase [SD] in the true positive rate of CN-MCI transitions of 10.3% [27.8%] for the LR model). In this study, models were accurate in aggregate but failed to satisfy fairness metrics. These findings suggest that fairness should be considered in the development and use of machine learning models for AD progression.

Association of Adipokines with Alzheimer's Disease in a Chinese Cohort.

The correlation between plasma adipose factor levels and Alzheimer's patients is not entirely clear. We aimed to investigate associations between AD and plasma levels of three adipokines including plasma adiponectin, leptin, and resistin. A single-center, cross-sectional study recruited AD patients (n = 148) and cognitively normal (CN) controls (n = 110). The multivariate logistic regression analysis was applied to determine associations of adiponectin, leptin, and resistin with the presence of AD. The receiver operating characteristic (ROC) analysis was employed to determine the diagnostic power of adiponectin, leptin and resistin for AD. After adjusted for the conventional risk factors, plasma levels of leptin (OR = 0.417, 95% CI: 0.272-0.638, p < 0.0001) and adiponectin (OR = 1.249, 95% CI: 1.151-1.354, p < 0.0001) were associated with the presence of AD. In total participants, the plasma adiponectin level was negatively correlated with MMSE scores (p < 0.0001) and was positively with CDR scores (p < 0.0001) and age (p < 0.0001). The plasma level of leptin was negatively correlated with CDR scores (p < 0.0001) and positively correlated with MMSE scores (p < 0.0001). Both adiponectin (p < 0. 0001) and leptin (p < 0. 0001) featured higher AUC than the random chance. Plasma adiponectin and leptin were associated with the presence, symptomatic severity, and diagnostic power of AD, suggesting a potential role of adipokines in the pathogenesis of AD.

97 Exploring Urban-Rural Disparities in Alzheimer’s disease: Clinical characterization of a southern Nevada cohort

Objective:As the US population ages, the prevalence of Alzheimer’s disease and related dementias (AD/RD) is on the rise. This is especially true in rural America, where mortality rates due to AD/RD are rising faster than in metropolitan areas. To date, however, people living in rural communities are severely underrepresented in aging research. The Nevada Exploratory Alzheimer’s Disease Research Center (NVeADRC) seeks to address this gap. Here, we present preliminary cognitive data from our rural-dwelling cohort, as well as relevant demographic and clinical characteristics.Participants and Methods:Individuals with normal cognition (NC), mild cognitive impairment (MCI), and dementia due to Alzheimer’s disease (AD) living in rural communities, defined as a rural-urban commuting area (RUCA) code of 4 or higher, were enrolled through either clinic or community outreach. Eligibility for the observational cohort required: age &gt;55 years, primarily English-speaking, primary residence in a rural community, and availability of a study partner. Measures included the Uniform Data Set (v3), blood-based biomarkers, structural brain MRI, and portions of the PhenX Social Determinants of Health toolkit. Participants are seen at baseline and followed annually, with interim remote visits every 6 months. A multidisciplinary consensus diagnosis is rendered after each visit. Where feasible, a harmonized urban cohort followed by the Nevada Center for Neurodegeneration and Translational Neuroscience (CNTN) was used for comparison.Results:Fifty-six rural-dwelling (age=70.4±7.1 years; edu=15.2±2.6 years; 61% female) and 148 urban-dwelling (age=72.9±6.8 years; edu=15.8±2.7 years; 46% female) older adults were included; age significantly differed between cohorts but education did not. The rural cohort was 46% NC (MoCA=26.8±2.3; CDRsob=0.3±0.6), 32% MCI (MoCA=22.8±3.1; CDRsob=1.2±1.0), and 22% AD (MoCA=16.9±5.5; CDRsob=5.2±3.0). The urban cohort was 39% NC (MoCA=26.4±2.6; CDRsob=0.3±0.8), 44% MCI (MoCA=22.3±3.1; CDRsob=2.0±1.5) and 17% AD (MoCA=18.6±3.9; CDRsob=4.7±2.3). Rural communities were significantly more disadvantaged, as measured by the Area Deprivation Index (ADI), than urban communities (rural ADI=6.3±2.6; urban ADI=3.4±2.3; p&lt;.001). Fifty-percent of the rural cohort lives in a moderate to severely disadvantaged neighborhood (ADI Decile&gt;7) compared to 12% of the urban cohort, and 11% of individuals in the rural cohort reported living more than 30 miles from the nearest medical facility. Across the combined cohort, education was significantly correlated with ADI deciles (r=-.30, p&lt;.001), with people in the areas of highest disadvantage having the lowest education. Verbal memory was also inversely associated with ADI. There were no differences in clinical diagnosis as a function of ADI rank.Conclusions:Living in a rural community conveys a multifaceted array of risks and benefits, some of which differ from urban settings. The literature to date suggests that older adults living in rural communities are at significantly increased risk for morbidity and mortality due to AD/RD, though it is unclear why. Preliminary data from the NVeADRC show that increasing levels of neighborhood disadvantage were associated with lower levels of education and worse verbal memory in this convenience sample. The combined effect of low education and increased disadvantage account for some of the urban-rural differences in mortality that have been reported, though additional research on representative samples in this underrepresented population is critical.

34 Association Between Subjective Cognitive Decline and Mental Wellbeing in Normal Cognition and MCI Older Adults

Objective:Subjective cognitive decline (SCD, i.e., perceived cognitive decline without neuropsychological deficits) is associated with Alzheimer’s disease pathology and increased risk for cognitive impairment but is heterogenous in etiology and has been linked to other factors including personality and depression. Mental wellbeing (i.e., the perception and functioning of social, emotional, and health-related aspects of one’s life) has been associated with subjective memory complaints, but its relationship with other subjective cognitive domains is poorly understood. Further characterizing the relationship between mental wellbeing and SCD could refine understanding of SCD and inform development of interventions that prevent progression to objective cognitive decline. This study aimed to describe the relationship between mental wellbeing and subjective decline in multiple cognitive domains and examine whether this relationship differs between older adults with normal cognition and those with mild cognitive impairment (MCI).Participants and Methods:Community-dwelling older adults (normal: n = 58, Mage = 73.7±5.6; MCI: n = 43, Mage = 75.9±6.1) completed the Everyday Cognition scale, a validated self-report measure of SCD, and the RAND-36 Health Survey, a validated self-report measure of health-related quality of life which includes a mental wellbeing subscale. Spearman’s rank correlations were conducted between self-reported mental wellbeing and each self-reported cognitive domain (i.e., memory, language, visuospatial, and executive function) for the Normal Cognition and MCI groups.Results:Worse mental wellbeing was associated with worse subjective language and executive function in the normal group, rs(56) = -.42, p =.001; rs(56) = -.37, p =.005, but not for the MCI group, rs(41) = -.23, p =.15; rs(41) = -.12, p =.46. Worse mental wellbeing was associated with worse subjective visuospatial function in the MCI group, rs(41) = -.39, p =.009, but not in the normal group, rs(56) = -.11, p =.39. For both groups, worse mental wellbeing was associated with worse subjective memory, rs(56) = -.45, p &lt; .001; rs(41) = -.37, p =.02. While this correlation was greater in the normal group, the difference was not significant (z = 0.38, p =.71).Conclusions:These results suggest that perceptions of mental wellbeing are related to perceptions of cognitive decline in multiple domains, and that the specific domains involved differ between normal and MCI groups. The differential associations may mean perception of specific cognitive domains more strongly affect mental wellbeing, or mental wellbeing more acutely influences perception of those domains. The overall observed relationship between SCD and mental wellbeing may have several explanations: the impact of broader health perceptions may extend to cognitive perception, behavioral changes associated with poor wellbeing may reduce subjective cognitive function, or worse subjective cognitive function may lead to negative experiences of wellbeing. Future longitudinal investigation could inform causal inferences. The more limited associations between mental wellbeing and SCD among MCI individuals may point to the role of decreased self-awareness (due to cognitive impairment) precluding detection of subtle changes in cognition or wellbeing. This study highlights the importance of better understanding mental wellbeing in experiences of SCD in both normal and MCI older adults to improve cognitive and mental health outcomes.

4 Evaluating Plasma GFAP for the Detection of Alzheimer’s Disease Dementia

Objective:Blood-based biomarkers represent a scalable and accessible approach for the detection and monitoring of Alzheimer’s disease (AD). Plasma phosphorylated tau (p-tau) and neurofilament light (NfL) are validated biomarkers for the detection of tau and neurodegenerative brain changes in AD, respectively. There is now emphasis to expand beyond these markers to detect and provide insight into the pathophysiological processes of AD. To this end, a reactive astrocytic marker, namely plasma glial fibrillary acidic protein (GFAP), has been of interest. Yet, little is known about the relationship between plasma GFAP and AD. Here, we examined the association between plasma GFAP, diagnostic status, and neuropsychological test performance. Diagnostic accuracy of plasma GFAP was compared with plasma measures of p-tau181 and NfL.Participants and Methods:This sample included 567 participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC) Longitudinal Clinical Core Registry, including individuals with normal cognition (n=234), mild cognitive impairment (MCI) (n=180), and AD dementia (n=153). The sample included all participants who had a blood draw. Participants completed a comprehensive neuropsychological battery (sample sizes across tests varied due to missingness). Diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using the Simoa platform. Binary logistic regression analyses tested the association between GFAP levels and diagnostic status (i.e., cognitively impaired due to AD versus unimpaired), controlling for age, sex, race, education, and APOE e4 status. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate diagnostic groups compared with plasma p-tau181 and NfL. Linear regression models tested the association between plasma GFAP and neuropsychological test performance, accounting for the above covariates.Results:The mean (SD) age of the sample was 74.34 (7.54), 319 (56.3%) were female, 75 (13.2%) were Black, and 223 (39.3%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having cognitive impairment (GFAP z-score transformed: OR=2.233, 95% CI [1.609, 3.099], p&lt;0.001; non-z-transformed: OR=1.004, 95% CI [1.002, 1.006], p&lt;0.001). ROC analyses, comprising of GFAP and the above covariates, showed plasma GFAP discriminated the cognitively impaired from unimpaired (AUC=0.75) and was similar, but slightly superior, to plasma p-tau181 (AUC=0.74) and plasma NfL (AUC=0.74). A joint panel of the plasma markers had greatest discrimination accuracy (AUC=0.76). Linear regression analyses showed that higher GFAP levels were associated with worse performance on neuropsychological tests assessing global cognition, attention, executive functioning, episodic memory, and language abilities (ps&lt;0.001) as well as higher CDR Sum of Boxes (p&lt;0.001).Conclusions:Higher plasma GFAP levels differentiated participants with cognitive impairment from those with normal cognition and were associated with worse performance on all neuropsychological tests assessed. GFAP had similar accuracy in detecting those with cognitive impairment compared with p-tau181 and NfL, however, a panel of all three biomarkers was optimal. These results support the utility of plasma GFAP in AD detection and suggest the pathological processes it represents might play an integral role in the pathogenesis of AD.