Day, Gregory S.

Abstract Background Bedside cognitive screening tools intend to reliably and efficiently detect cognitive impairment in research, clinical, and community settings. Black American (BA) and Hispanic/Latino (H/L) adults obtain lower performance on widely used screeners, largely driven by demographics and structural and social determinants of health (SSDoH). This study characterized the performance of the Montreal Cognitive Assessment (MoCA) performance in a cohort of cognitively normal ethnoracially diverse adults while considering cohort‐specific factors that contributed to misclassification of impairment. Method Cognitively normal BA and H/L participants completed a comprehensive neurological assessment, neuropsychological testing, and MRI and amyloid‐ and tau‐PET imaging as part of a longitudinal study of memory and aging at Mayo Clinic in Florida. Demographically adjusted MoCA cutoffs were applied to BA (MoCA ≤ 22) and WH/L (MoCA ≤ 24) subgroups. Hierarchical binary logistic regression assessed whether amyloid burden (Centiloid value) improved prediction of scoring below demographically adjusted MoCA cutoffs beyond demographic/SSDoH factors, including age, education, and Area Deprivation Index (ADI). Result Participants included 105 (47 WH/L, 58 BA/AA) cognitively normal adults (mean age = 64.71 years, SD = 8.91; 62.9% female) with average of 16.07 years of education (SD=2.35) and mild‐to‐moderate neighborhood disadvantage (mean ADI=47.60, SD=23.77). 40% of H/L participants (MoCA (≤ 24) and 17% of BA participants (MoCa ≤22) scored below demographically adjusted MoCA cut‐offs. For the H/L subgroup, the best fitting model included age, education, ADI, and amyloid burden ( R 2 = 0 .43, χ 2 = 10.98, p = 0.03). Age (OR=1.21, 95% CI: 0.986 – 1.487) and amyloid burden (OR = 0.83, 95% CI: 0.67 – 1.03) approached statistical significance as individual predictors ( p = 0.06, p = 0.09). In the BA/AA subgroup, the best fitting model included age, education and ADI only ( R 2 = 0.47, χ 2 = 9.06, p = 0.02), with education approaching significance as an individual predictor (OR=0.46, 95% CI: 0.21 – 1.01, p = 0.05). Conclusion Sociodemographic factors continued to drive low MoCA performance in cognitively normal individuals despite applying demographically adjusted cut‐off scores by subgroup. These factors differentially impacted performance among BA/AA and WH/L participants. Careful consideration of these factors is warranted to mitigate risk of overdiagnosing impairment based on cognitive screening across clinical and research settings.

Abstract Background African Americans (AA) are twice as likely to develop dementia than non‐Hispanic Whites but remain underrepresented in Alzheimer's Disease (AD) research. Recent studies have identified AA specific risk factors for AD. Therefore, targeted biomarkers and/or therapies may be needed to effectively treat AD in AA. In this study, we aimed to determine if genetic variants that show association with AD‐risk, plasma transcript or protein levels in AA, may serve as accurate and accessible AD biomarkers. Method In 189 clinically diagnosed AA AD cases and 183 AA cognitively unimpaired (CU) controls, we performed targeted DNA sequencing of 10 AD‐associated loci. Genetic variants at these loci were tested for association with corresponding plasma transcripts and total tau protein levels previously measured in this cohort using a custom nanoString panel and Simoa assays, respectively. Utilizing phased haplotypes (SHAPEIT4) from target sequencing, we inferred local ancestry (RFMix v2) using five superpopulations from the 1000 Genomes Project as anchors. Subsequently, we tested the association of each ancestry specific allelic dosages with endophenotypes using Tractor. In receiver operating characteristic (ROC) analyses, the most significant e/pQTLs were added sequentially to a base model that included age and sex to identify e/pQTLs that improved the accuracy to correctly classify AD cases and CU controls. Result Of the 5,112 variants that were tested, 70 were nominally associated with AD‐risk and with plasma transcript or protein levels. Seven of these 70 variants also showed nominally significant associations of AD‐risk and transcript levels with either African or East Asian local ancestry. ROC analysis of age, sex, 33 e/pQTLs in APOE , SORL1 , TLR4 , EPHA1 , ABCA7 , CLU , and CR1 , and plasma levels of APP, ABCA7, AKAP9, CD14, CLU, and APOE ‐ɛ4 dosage achieved 88.2% area under the curve to discriminate AD vs. CU, a 30.4% improvement over the base model that only included age and sex. Conclusion Plasma transcript levels and e/pQTLs are promising diagnostic biomarkers for AD that may improve accessibility and reduce costs for a more accurate diagnosis of AD.

Abstract Background Plasma biomarkers offer improved accessibility compared to established diagnostic modalities for Alzheimer's disease (AD). However, current plasma biomarker candidates have not been tested comprehensively in diverse populations, and represent only a fraction of pathways dysregulated in AD. This study seeks to address these knowledge gaps through untargeted plasma biomarker discovery in African Americans (AA), an underrepresented group in AD research despite having a higher risk of developing dementia compared to non‐Hispanic Whites (NHW). Method Untargeted proteomics were generated using the SomaScan 7k platform on plasma samples from AA study participants clinically diagnosed as AD dementia ( n = 181) or cognitively unimpaired (CU; n = 142). Machine learning was implemented to identify a set of plasma proteins to distinguish between AD dementia and CU. Predictive models were constructed by elastic net regression optimized with nested cross‐validation on 6,853 proteins and evaluated by receiver operating characteristic analysis. The generalizability of plasma protein predictors was evaluated in an external Alzheimer's Disease Research Center cohort of 369 NHW and AA study participants diagnosed as AD dementia or CU. Result Thirty‐six proteins were selected as predictors. Proteins selected by machine learning were enriched for processes previously associated with AD including synaptic dysfunction, inflammation, vascular dysfunction, and amyloid processing. The 36 plasma proteins alone achieved an area under the curve (AUC) of 0.94 to classify AD dementia in the discovery cohort, representing a 22% improvement over a model including age and sex. The 36 proteins were validated in an external cohort also achieving AUC=0.94, a 35% improvement over age and sex. Conclusion Biomarker discovery combining untargeted proteomics and machine learning identified a set of plasma proteins that could serve as a novel and highly accurate diagnostic plasma biomarker panel for AD. Work is underway to assess the association of the predictive panel with p ‐tau217, medical comorbidities, and social/structural determinants of health.

Abstract Background Self‐administered and remote digital cognitive assessments provide a scalable method for screening and longitudinal cognitive monitoring. Mayo Test Drive (MTD) is one such assessment with previously demonstrated usability, reliability, validity and multi‐device compatibility. MTD includes a computer‐adaptive word list memory test (Stricker Learning Span) and a measure of processing speed/executive functioning (Symbols Test) that combine to provide an MTD Composite. This study aimed to develop a conditional normative model predicting longitudinal cognitive change for MTD, and to validate the model in two independent samples of cognitively unimpaired (CU) and mild cognitive impairment (MCI)/dementia (DEM) participants. Method 1355 CU participants at initial MTD assessment with 2‐4 consecutive MTD assessments every 7.5 months comprised the development dataset. Linear mixed effects models were used to construct a conditional normative model for MTD assessments 2‐4. The baseline model was chosen a priori , consisting of age, sex, education, baseline score, number of assessments, and time. Device type, race, and baseline score by time interactions were also considered. Variables were only added if a >1% increment in r‐squared was observed. The models were externally validated in 113 CU and 51 MCI/DEM patients. Following model development, the data were updated and additional follow‐up MTD assessments were added for many participants, including the addition of additional CU validation data at test 3 ( N = 126) and 4 ( N = 279). T‐tests compared observed and predicted differences and residual z‐scores between development and validation at each follow‐up assessment. Result Table 1 presents demographic variables. No additional variables increased the r‐squared by >1%. The final models are presented in Table 2. Age, baseline score, sex, and education were significant. Residual z‐scores were not significantly different between CU development and CU validation cohorts, indicating observed scores were in line with model predicted scores. Residual z‐scores were significantly worse among MCI/DEM compared to CU development in 11/12 comparisons (Figure 1), indicating observed scores were below model predicted expectations and implying sensitivity to longitudinal cognitive decline. Conclusion These longitudinal normative models can be used to identify individuals with follow‐up scores outside of expected predicted ranges, signifying abnormal longitudinal cognitive decline.

Abstract Background Population aging is expected to increase the burden of Alzheimer's disease (AD) and related dementias (ADRD), yet up to 45% of ADRD risk may be modified. Disparities in ADRD burden among Hispanic/Latino and Black/African Americans suggests that socioeconomic deprivation and medical comorbidities may influence AD risk. The relationship between these factors, symptomatic age of onset, and neuropathologic findings in AD remains unclear. This study aims to investigate these associations in an ethnoracially diverse, neuropathologically diagnosed AD case series. Understanding these risk factors may help develop more effective AD risk reduction strategies. Method We queried the Florida Autopsied Multi‐Ethnic (FLAME) cohort database for neuropathologically‐diagnosed AD cases with available age onset of cognitive symptoms, who self‐identified as Hispanic/Latino ( n = 75) or Black/African American ( n = 22). Cases were matched to non‐Hispanic White decedents ( n = 101) by sex and year of birth. Medical records at the time of brain donation were retrospectively reviewed, assessing completeness for demographics, clinical characteristics, and medical comorbidities (Table 1). Result The table shows a comparative analysis stratified by young‐onset AD (YOAD, onset <65 years) and late‐onset AD (LOAD, onset ≥65 years). YOAD cases had a significantly higher level of education compared to LOAD ( p = 0.003). No differences were observed in sex , APOE ε4 carriership, or Area Deprivation Index between YOAD and LOAD. However, YOAD cases had a longer disease duration and were more likely to present with atypical clinical features compared to LOAD (both p <0.001). YOAD cases also showed a faster rate of decline on MMSE compared to LOAD ( p = 0.002), higher frequency of depression ( p = 0.018), and lower frequency of stroke/TIA ( p = 0.025). YOAD cases also had lower brain weight ( p = 0.041), less cerebrovascular disease burden ( p = 0.003) and higher neurofibrillary tangle density in association cortices ( p <0.001) compared to LOAD cases. Conclusion Socioeconomic deprivation and most medical comorbidities were not associated with AD symptomatic onset. Despite having higher education levels and lower cerebrovascular burden, YOAD decedents experienced faster cognitive decline but a longer disease course, with more frequent atypical clinical presentations and depression compared to LOAD. Further discussion will address the topographic distribution of tangle and plaque pathology.

Abstract Background Disparities in structural and social determinants of health in Latino and Black communities may increase the burden of Alzheimer disease and related dementias (ADRD). Identifying dementia risk factors, which may account for up to 45% of ADRD risk, is crucial to implement effective risk‐reduction strategies. This study aimed to assess ADRD risk factors in community‐dwelling, cognitively normal, Latino and Black Americans by measuring the frequency of modifiable dementia risk factors through subjective and objective measures. Method Community‐dwelling, cognitively normal, Latino and Black adults (≥45‐years‐old) were enrolled in a longitudinal study of memory and aging at Mayo Clinic in Jacksonville, Florida. Baseline assessments conducted between Mach 2022 and November 2024 included demographics, self‐reported race/ethnicity, and history of dementia risk factors. Socioeconomic deprivation [Area Deprivation Index (ADI) State scores] and modifiable dementia risk factors were reported by participants and directly measured, including hypertension (BP >130/80 mmHg), obesity (BMI≥30), hyperlipidemia (LDL>100 mg/dL), hyperglycemia (HbA1C >5.6%), low vitamin B12 (B12<350 pg/mL), hearing loss (bedside assessment), vision loss (bedside assessment), and depression (Geriatric Depression Scale ≥5). Result 105 participants (47 Latino, 55 Black), 64.7 (±8.8) years‐old, female 66 (63%), with 16 (±2.3) years of education were assessed. Black participants experienced higher socioeconomic deprivation than Latino participants (median ADI 7 vs 3; p <0.001). Dementia risk factors were common in Latino and Black participants. These included, hypertension (55.3%, 70.3%; p = 0.291), hyperlipidemia (58.7%, 55.8%; p = 0.908), obesity (29.8%, 45.5%; p = 0.263), hyperglycemia (51.1%, 49.1%; p = 0.834), low vitamin B12 (23.9%, 28.0%; p = 0.270), hearing loss (19.1%, 7.3%; p = 0.111), vision loss (85.1%, 85.2%; p = 0.771), and depression (6.4%, 5.5%; p = 0.168). Objective measures revealed a higher frequency of risk factors compared with participant‐provided history, highlighting a substantial proportion of unrecognized or inadequately treated risk factors: hypertension (62.3%, 45.1%; p = 0.067), hyperlipidemia (57.6%, 47.5%; p = 0.004), hyperglycemia (49%, 20%; p = <0.001), vitamin B12 deficiency (27.8%, 9.3%; p = 0.170), and depression (6.9%, 11.9%; p = 0.009). Conclusion Modifiable dementia risk factors were detected in most cognitively normal Latino and Black adults engaged in a longitudinal study of memory and aging. Objective measures highlighted unrecognized and undertreated risk factors. Active surveillance programs are needed to detect and treat modifiable ADRD risk factors in underrepresented populations.

Abstract Background Dementia with Lewy Bodies (DLB) has been overlooked or misdiagnosed as Alzheimer’s disease (AD) dementia due to its frequent concomitant AD pathology with Lewy Body Disease (LBD) pathology. Although autopsy confirmation has been the gold standard for the precise diagnosis of DLB, time‐course 123 I‐FP‐CIT SPECT (DaT‐SPECT) findings in autopsy‐confirmed DLB are not well characterized. We previously reported that the DaTQUANT z‐score of the more affected side of the putamen has the best discriminatory power in detecting LBD pathology and nigrostriatal degeneration in dementia patients and demonstrated z‐score of −1 as the cutoff value. We sought to examine how DaT‐SPECT findings change over time in autopsy confirmed LBD patients in preparation for its use in LBD targeted clinical trials. Method Eight autopsy confirmed neocortical or limbic LBD patients who underwent two or more DaT‐SPECT were included. Nigrostriatal dopamine transporter (DaT) binding and age‐adjusted z‐scores were analyzed using the DaTQUANT 2.0 software (GE Healthcare). Result Six patients (75%) were male. The patients had 2.5±0.7 longitudinal DaT‐SPECT scans. Clinical diagnosis at initial scan was: DLB (75%), mild cognitive impairment (MCI) with REM sleep behavior disorder (RBD) (13%), and isolated RBD (iRBD) (13%). Clinical diagnosis at last scan was: DLB (88%) and iRBD (12%). All patients developed dementia during life. Mean age at initial scan/last scan/autopsy were 71.1±7.0/73.4±6.9/75.1±7.3 years old. Time from initial and last scan to autopsy were 4.0±1.9 and 1.8±1.9 years respectively. Seven patients (88%) had neocortical LBD and one (12%) had limbic LBD. Concomitant AD pathology was observed in four patients (two males (33%), two females (100%)). All patients had DaTQUANT putamen z‐score <‐1.0 at their initial scan including in MCI+RBD (‐1.76) and iRBD (‐1.53) patients. In the DLB patients at their initial scans, five (83%) had DaTQUANT putamen z‐score <‐2.0 and one (17%) had z‐score of ‐1.55. All patients (100%) showed DaTQUANT putamen z‐score <‐2.0 at their last scans. Conclusion DaTQUANT using cut‐off putamen z‐score of ‐1 was associated with underlying LBD pathology including at their iRBD and MCI stages. Nigrostriatal DaT binding tends to decline over time with DaTQUANT z‐score <‐2 at their last scans.

Abstract The cortical asymmetry index evaluates the cortical thickness asymmetry between hemispheres. We investigated cortical asymmetry index in asymptomatic and symptomatic mutation carriers of autosomal dominant Alzheimer’s disease to explore the brain asymmetry within the Alzheimer’s disease continuum. Sixty baseline T1-weighted MRI scans were obtained from the Clinic Barcelona cohort. Baseline and longitudinal MRI data from 564 participants within the dominantly inherited Alzheimer network observational study were used as an independent, confirmatory cohort. Cerebrospinal fluid and plasma neurofilament light chain levels were included when available. Cortical thickness was calculated using Freesurfer and cortical asymmetry index was calculated via an open-source pipeline. Cross-sectional analyses examined cortical asymmetry index differences based on clinical classification and APOE ε4 status, adjusting for age, sex and estimated years from onset, while correlations were assessed with age, estimated years from onset, mini-mental state examination scores, and neurofilament light. Longitudinal cortical asymmetry index evolution was modelled using generalized additive models in the dominantly inherited Alzheimer network observational study cohort, incorporating age, sex, and the interaction between group and estimated years from onset. The cortical asymmetry index successfully distinguished asymptomatic mutation carrier and symptomatic mutation carriers from healthy controls in the Clinic Barcelona cohort and symptomatic mutation carriers from controls in dominantly inherited Alzheimer network observational study. Higher cortical asymmetry index in mutation carriers (asymptomatic mutation carrier and symptomatic mutation carriers combined) and in symptomatic mutation carriers were associated with higher plasma neurofilament light levels, a closer proximity to symptom onset, and lower mini-mental state examination in the Clinic Barcelona cohort. In the dominantly inherited Alzheimer network observational study cohort, mutation carriers exhibited increased cortical asymmetry index compared to controls and correlated with elevated neurofilament light (plasma and Cerebrospinal fluid), lower mini-mental state examination, and a closer proximity to symptom onset. APOE3/3 carriers showed greater asymmetry than other APOE genotypes and significant cortical asymmetry index differences between asymptomatic mutation carrier and symptomatic mutation carriers. Longitudinally, cortical asymmetry index increased over time significantly in symptomatic mutation carriers. These findings underscore brain asymmetry as a potential biomarker for early Alzheimer’s disease progression in autosomal dominant Alzheimer’s disease, with implications for detection and monitoring tracking disease-related neuroanatomical changes.

Abstract INTRODUCTION Brief digital cognitive measures may be a valuable and scalable alternative to traditional tests for improving early detection and disease monitoring in patients with early‐onset Alzheimer's disease (EOAD). METHODS We examined the convergent, diagnostic, and neuroanatomical validity of Tablet‐based Cognitive Assessment Tool (TabCAT) tests in the multisite Longitudinal Early‐Onset Alzheimer's Disease Study. Four hundred seventy‐five participants from 16 sites (83 cognitively unimpaired participants, 146 individuals diagnosed with mild cognitive impairment [MCI], and 246 with mild dementia) underwent TabCAT testing, including two executive/attentional tasks (Match and Flanker) and two visuospatial tasks (Line Length and Line Orientation). RESULTS TabCAT tests showed good convergent validity with traditional pen‐and‐paper tests. Match was the most accurate TabCAT test in differentiating among clinical groups (controls vs. MCI vs. dementia) and predicting amyloid positron emission tomography (PET) positivity in clinically impaired participants. TabCAT tests were associated with regional tau PET patterns. DISCUSSION TabCAT digital measures have promise for frontline identification of patients with EOAD. Highlights Four hundred seventy‐five participants from 16 US sites underwent tablet‐based cognitive assessment. Digital tests assessed executive function and visuospatial abilities. Digital tests correlated with traditional pen‐and‐paper cognitive tests. Match (test of executive function) differentiated clinical groups. Digital tests were associated with amyloid positron emission tomography (PET) status and regional tau PET patterns.