Realtime Diagnosis from Electrocardiogram Artificial Intelligence-Guided Screening for Atrial Fibrillation with Long Follow-Up (REGAL): Rationale and design of a pragmatic, decentralized, randomized controlled trial.

BACKGROUND: Atrial fibrillation (AF) is associated with increased risks of stroke and dementia. Early diagnosis and treatment could reduce the disease burden, but AF is often undiagnosed. An artificial intelligence (AI) algorithm has been shown to identify patients with previously unrecognized AF; however, monitoring these high-risk patients has been challenging. Consumer wearable devices could be an alternative to enable long-term follow-up. OBJECTIVES: To test whether Apple Watch, used as a long-term monitoring device, can enable early diagnosis of AF in patients who were identified as having high risk based on AI-ECG. DESIGN: The Realtime diagnosis from Electrocardiogram (ECG) Artificial Intelligence (AI)-Guided Screening for Atrial Fibrillation (AF) with Long Follow-up (REGAL) study is a pragmatic trial that will accrue up to 2,000 older adults with a high likelihood of unrecognized AF determined by AI-ECG to reach our target of 1,420 completed participants. Participants will be 1:1 randomized to intervention or control and will be followed up for 2 years. Patients in the intervention arm will receive or use their existing Apple Watch and iPhone and record a 30-second ECG using the watch routinely or if an abnormal heart rate notification is prompted. The primary outcome is newly diagnosed AF. Secondary outcomes include changes in cognitive function, stroke, major bleeding, and all-cause mortality. The trial will utilize a pragmatic, digitally-enabled, decentralized design to allow patients to consent and receive follow-up remotely without traveling to the study sites. SUMMARY: The REGAL trial will examine whether a consumer wearable device can serve as a long-term monitoring approach in older adults to detect AF and prevent cognitive function decline. If successful, the approach could have significant implications on how future clinical practice can leverage consumer devices for early diagnosis and disease prevention. CLINICALTRIALS: GOV: : NCT05923359.

Mayo normative studies: regression-based normative data for ages 30-91 years with a focus on the Boston Naming Test, Trail Making Test and Category Fluency.

OBJECTIVE: Normative neuropsychological data are essential for interpretation of test performance in the context of demographic factors. The Mayo Normative Studies (MNS) aim to provide updated normative data for neuropsychological measures administered in the Mayo Clinic Study of Aging (MCSA), a population-based study of aging that randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. We examined demographic effects on neuropsychological measures and validated the regression-based norms in comparison to existing normative data developed in a similar sample. METHOD: The MNS includes cognitively unimpaired adults ≥30 years of age (n = 4,428) participating in the MCSA. Multivariable linear regressions were used to determine demographic effects on test performance. Regression-based normative formulas were developed by first converting raw scores to normalized scaled scores and then regressing on age, age2, sex, and education. Total and sex-stratified base rates of low scores (T < 40) were examined in an older adult validation sample and compared with Mayo's Older Americans Normative Studies (MOANS) norms. RESULTS: Independent linear regressions revealed variable patterns of linear and/or quadratic effects of age (r2 = 6-27% variance explained), sex (0-13%), and education (2-10%) across measures. MNS norms improved base rates of low performance in the older adult validation sample overall and in sex-specific patterns relative to MOANS. CONCLUSIONS: Our results demonstrate the need for updated norms that consider complex demographic associations on test performance and that specifically exclude participants with mild cognitive impairment from the normative sample.

Stricker Learning Span criterion validity: a remote self-administered multi-device compatible digital word list memory measure shows similar ability to differentiate amyloid and tau PET-defined biomarker groups as in-person Auditory Verbal Learning Test.

OBJECTIVE: The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey's Auditory Verbal Learning Test (AVLT). METHOD: Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer's disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A-T-, n = 195). Analyses were repeated among CU participants only. RESULTS: The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p's > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A- vs A+) to large (A-T- vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups. CONCLUSIONS: Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

Plasma biomarkers for prediction of Alzheimer's disease neuropathologic change.

While plasma biomarkers for Alzheimer's disease (AD) are increasingly being evaluated for clinical diagnosis and prognosis, few population-based autopsy studies have evaluated their utility in the context of predicting neuropathological changes. Our goal was to investigate the utility of clinically available plasma markers in predicting Braak staging, neuritic plaque score, Thal phase, and overall AD neuropathological change (ADNC).We utilized a population-based prospective study of 350 participants with autopsy and antemortem plasma biomarker testing using clinically available antibody assay (Quanterix) consisting of Aß42/40 ratio, p-tau181, GFAP, and NfL. We utilized a variable selection procedure in cross-validated (CV) logistic regression models to identify the best set of plasma predictors along with demographic variables, and a subset of neuropsychological tests comprising the Mayo Clinic Preclinical Alzheimer Cognitive Composite (Mayo-PACC). ADNC was best predicted with plasma GFAP, NfL, p-tau181 biomarkers along with APOE ε4 carrier status and Mayo-PACC cognitive score (CV AUC = 0.798). Braak staging was best predicted using plasma GFAP, p-tau181, and cognitive scores (CV AUC = 0.774). Neuritic plaque score was best predicted using plasma Aß42/40 ratio, p-tau181, GFAP, and NfL biomarkers (CV AUC = 0.770). Thal phase was best predicted using GFAP, NfL, p-tau181, APOE ε4 carrier status and Mayo-PACC cognitive score (CV AUC = 0.754). We found that GFAP and p-tau provided non-overlapping information on both neuritic plaque and Braak stage scores whereas Aß42/40 and NfL were mainly useful for prediction of neuritic plaque scores. Separating participants by cognitive status improved predictive performance, particularly when plasma biomarkers were included. Plasma biomarkers can differentially inform about overall ADNC pathology, Braak staging, and neuritic plaque score when combined with demographics and cognitive variables and have significant utility for earlier detection of AD.

Mayo-PACC: A parsimonious preclinical Alzheimer's disease cognitive composite comprised of public-domain measures to facilitate clinical translation.

INTRODUCTION: We aimed to define a Mayo Preclinical Alzheimer's disease Cognitive Composite (Mayo-PACC) that prioritizes parsimony and use of public domain measures to facilitate clinical translation. METHODS: Cognitively unimpaired participants aged 65 to 85 at baseline with amyloid PET imaging were included, yielding 428 amyloid negative (A-) and 186 amyloid positive (A+) individuals with 7 years mean follow-up. Sensitivity to amyloid-related cognitive decline was examined using slope estimates derived from linear mixed models (difference in annualized change across A+ and A- groups). We compared differences in rates of change between Mayo-PACC and other composites (A+ > A- indicating more significant decline in A+). RESULTS: All composites showed sensitivity to amyloid-related longitudinal cognitive decline (A+ > A- annualized change p < 0.05). Comparisons revealed that Mayo-PACC (AVLT sum of trials 1-5+6+delay, Trails B, animal fluency) showed comparable longitudinal sensitivity to other composites. DISCUSSION: Mayo-PACC performs similarly to other composites and can be directly translated to the clinic.

NIA-AA Alzheimer's Disease Framework: Clinical Characterization of Stages.

BACKGROUND: To operationalize the National Institute on Aging - Alzheimer's Association (NIA-AA) Research Framework for Alzheimer's Disease 6-stage continuum of clinical progression for persons with abnormal amyloid. METHODS: The Mayo Clinic Study of Aging is a population-based longitudinal study of aging and cognitive impairment in Olmsted County, Minnesota. We evaluated persons without dementia having 3 consecutive clinical visits. Measures for cross-sectional categories included objective cognitive impairment (OBJ) and function (FXN). Measures for change included subjective cognitive impairment (SCD), objective cognitive change (ΔOBJ), and new onset of neurobehavioral symptoms (ΔNBS). We calculated frequencies of the stages using different cutoff points and assessed stability of the stages over 15 months. RESULTS: Among 243 abnormal amyloid participants, the frequencies of the stages varied with age: 66 to 90% were classified as stage 1 at age 50 but at age 80, 24 to 36% were stage 1, 32 to 47% were stage 2, 18 to 27% were stage 3, 1 to 3% were stage 4 to 6, and 3 to 9% were indeterminate. Most stage 2 participants were classified as stage 2 because of abnormal ΔOBJ only (44-59%), whereas 11 to 21% had SCD only, and 9 to 13% had ΔNBS only. Short-term stability varied by stage and OBJ cutoff points but the most notable changes were seen in stage 2 with 38 to 63% remaining stable, 4 to 13% worsening, and 24 to 41% improving (moving to stage 1). INTERPRETATION: The frequency of the stages varied by age and the precise membership fluctuated by the parameters used to define the stages. The staging framework may require revisions before it can be adopted for clinical trials. ANN NEUROL 2021;89:1145-1156.

Mayo Normative Studies: Regression-Based Normative Data for the Auditory Verbal Learning Test for Ages 30-91 Years and the Importance of Adjusting for Sex.

OBJECTIVE: Rey's Auditory Verbal Learning Test (AVLT) is a widely used word list memory test. We update normative data to include adjustment for verbal memory performance differences between men and women and illustrate the effect of this sex adjustment and the importance of excluding participants with mild cognitive impairment (MCI) from normative samples. METHOD: This study advances the Mayo's Older Americans Normative Studies (MOANS) by using a new population-based sample through the Mayo Clinic Study of Aging, which randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. Regression-based normative T-score formulas were derived from 4428 cognitively unimpaired adults aged 30-91 years. Fully adjusted T-scores correct for age, sex, and education. We also derived T-scores that correct for (1) age or (2) age and sex. Test-retest reliability data are provided. RESULTS: From raw score analyses, sex explained a significant amount of variance in performance above and beyond age (8-10%). Applying original age-adjusted MOANS norms to the current sample resulted in significantly fewer-than-expected participants with low delayed recall performance, particularly in women. After application of new T-scores adjusted only for age, even in normative data derived from this sample, these age-adjusted T-scores showed scores <40 T occurred more frequently among men and less frequently among women relative to T-scores that also adjusted for sex. CONCLUSIONS: Our findings highlight the importance of using normative data that adjust for sex with measures of verbal memory and provide new normative data that allow for this adjustment for the AVLT.

Diagnostic accuracy of the Cogstate Brief Battery for prevalent MCI and prodromal AD (MCI A+ T+ ) in a population-based sample.

INTRODUCTION: This study evaluated the diagnostic accuracy of the Cogstate Brief Battery (CBB) for mild cognitive impairment (MCI) and prodromal Alzheimer's disease (AD) in a population-based sample. METHODS: Participants included adults ages 50+ classified as cognitively unimpaired (CU, n = 2866) or MCI (n = 226), and a subset with amyloid (A) and tau (T) positron emission tomography who were AD biomarker negative (A-T-) or had prodromal AD (A+T+). RESULTS: Diagnostic accuracy of the Learning/Working Memory Composite (Lrn/WM) for discriminating all CU and MCI was moderate (area under the curve [AUC] = 0.75), but improved when discriminating CU A-T- and MCI A+T+ (AUC = 0.93) and when differentiating MCI participants without AD biomarkers from those with prodromal AD (AUC = 0.86). Conventional cut-offs yielded lower than expected sensitivity for both MCI (38%) and prodromal AD (73%). DISCUSSION: Clinical utility of the CBB for detecting MCI in a population-based sample is lower than expected. Caution is needed when using currently available CBB normative data for clinical interpretation.

Detectable Neuropsychological Differences in Early Preclinical Alzheimer's Disease: A Meta-Analysis.

The development of methods for in vivo detection of cerebral beta amyloid retention and tau accumulation have been increasingly useful in characterizing preclinical Alzheimer's disease (AD). While the association between these biomarkers and eventual AD has been demonstrated among cognitively intact older adults, the link between biomarkers and neurocognitive ability remains unclear. We conducted a meta-analysis to test the hypothesis that cognitively intact older adults would show statistically discernable differences in neuropsychological performance by amyloid status (amyloid negative = A-, amyloid positive = A+). We secondarily hypothesized a third group characterized by either CSF tau pathology or neurodegeneration, in addition to amyloidosis (A+/N+ or Stage 2), would show lower neuropsychology scores than the amyloid positive group (A+/N- or Stage 1) when compared to the amyloid negative group. Pubmed, PsychINFO, and other sources were searched for relevant articles, yielding 775 total sources. After review for inclusion/exclusion criteria, duplicates, and risk of bias, 61 studies were utilized in the final meta-analysis. Results showed A+ was associated with poorer performance in the domains of global cognitive function, memory, language, visuospatial ability, processing speed, and attention/working memory/executive functions when compared to A-. A+/N+ showed lower performances on memory measures when compared to A+/N- in secondary analyses based on a smaller subset of studies. Results support the notion that neuropsychological measures are sensitive to different stages of preclinical AD among cognitively intact older adults. Further research is needed to determine what constitutes meaningful differences in neuropsychological performance among cognitively intact older adults.

Correction to: Detectable Neuropsychological Differences in Early Preclinical Alzheimer's Disease: a Meta-Analysis.

Errors were discovered in the reporting of processing speed data that do not impact the interpretation of findings.

Diagnostic Accuracy of Memory Measures in Alzheimer's Dementia and Mild Cognitive Impairment: a Systematic Review and Meta-Analysis.

With an increasing focus on biomarkers in dementia research, illustrating the role of neuropsychological assessment in detecting mild cognitive impairment (MCI) and Alzheimer's dementia (AD) is important. This systematic review and meta-analysis, conducted in accordance with PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) standards, summarizes the sensitivity and specificity of memory measures in individuals with MCI and AD. Both meta-analytic and qualitative examination of AD versus healthy control (HC) studies (n = 47) revealed generally high sensitivity and specificity (≥ 80% for AD comparisons) for measures of immediate (sensitivity = 87%, specificity = 88%) and delayed memory (sensitivity = 89%, specificity = 89%), especially those involving word-list recall. Examination of MCI versus HC studies (n = 38) revealed generally lower diagnostic accuracy for both immediate (sensitivity = 72%, specificity = 81%) and delayed memory (sensitivity = 75%, specificity = 81%). Measures that differentiated AD from other conditions (n = 10 studies) yielded mixed results, with generally high sensitivity in the context of low or variable specificity. Results confirm that memory measures have high diagnostic accuracy for identification of AD, are promising but require further refinement for identification of MCI, and provide support for ongoing investigation of neuropsychological assessment as a cognitive biomarker of preclinical AD. Emphasizing diagnostic test accuracy statistics over null hypothesis testing in future studies will promote the ongoing use of neuropsychological tests as Alzheimer's disease research and clinical criteria increasingly rely upon cerebrospinal fluid (CSF) and neuroimaging biomarkers.

The neurocognitive performance of female veterans with posttraumatic stress disorder.

Neurocognitive problems are common with posttraumatic stress disorder (PTSD) and are important to understand because of their association with the success of PTSD treatment and its potential neural correlates. To our knowledge, this is the first neurocognitive study in an all-female U.S. veteran sample, some of whom had PTSD. We examined neurocognitive performance and assessed whether learning deficits, common in PTSD, were associated with executive functioning. Veterans with PTSD (n = 56) and without (n = 53) were evaluated for psychiatric and neurocognitive status. The PTSD group had a lower estimated IQ (d = 0.53) and performed more poorly on all neurocognitive domains (d range = 0.57-0.88), except verbal retention (d = 0.04). A subset of the 2 groups that were matched on IQ and demographics similarly demonstrated poorer performance for the PTSD group on all neurocognitive domains (d range = 0.52-0.79), except verbal retention (d = 0.15). Within the PTSD group, executive functioning accounted for significant variance in verbal learning over and above IQ and processing speed (ΔR(2) = .06), as well as depression (ΔR(2) = .07) and PTSD severity (ΔR(2) = .06). This study demonstrated that female veterans with PTSD performed more poorly than females without PTSD on several neurocognitive domains, including verbal learning, processing speed, and executive functioning. Replication of these results using a control group of veterans with more similar trauma exposure, history of mild traumatic brain injury, and psychiatric comorbidities would solidify these findings.

APOE interacts with age to modify rate of decline in cognitive and brain changes in Alzheimer's disease.

OBJECTIVE: To determine (1) whether age-standardized cognitive declines and brain morphometric change differ between Young-Old patients with Alzheimer's disease (YOAD) and Very-Old patients with Alzheimer's disease (VOAD), and (2) whether the apolipoprotein E (APOE) genotype modifies these neuropsychological and morphometric changes. METHODS: Baseline and 12-month follow-up neuropsychological and morphometric measures were examined for healthy control subjects and patients with AD. The two AD groups were divided further into subgroups on the basis of the presence of at least one APOE ε4 allele. RESULTS: The YOAD group showed more severe deficits and steeper declines in cognition than the VOAD group. Moreover, the presence of an APOE ε4 allele had a more deleterious effect on the YOAD group than the VOAD group on cognition and brain structure both cross-sectionally and longitudinally. CONCLUSIONS: Results underscore the importance of integrating an individual's age and genetic susceptibility--and their interaction--when examining neuropsychological and neuroimaging changes in the early stages of Alzheimer's disease.

Mayo Normative Studies: Amyloid and Neurodegeneration Negative Normative Data for the Auditory Verbal Learning Test and Sex-Specific Sensitivity to Mild Cognitive Impairment/Dementia.

Background: Conventional normative samples include individuals with undetected Alzheimer's disease neuropathology, lowering test sensitivity for cognitive impairment. Objective: We developed Mayo Normative Studies (MNS) norms limited to individuals without elevated amyloid or neurodegeneration (A-N-) for Rey's Auditory Verbal Learning Test (AVLT). We compared these MNS A-N- norms in female, male, and total samples to conventional MNS norms with varying levels of demographic adjustments. Methods: The A-N- sample included 1,059 Mayo Clinic Study of Aging cognitively unimpaired (CU) participants living in Olmsted County, MN, who are predominantly non-Hispanic White. Using a regression-based approach correcting for age, sex, and education, we derived fully-adjusted T-score formulas for AVLT variables. We validated these A-N- norms in two independent samples of CU (n = 261) and mild cognitive impairment (MCI)/dementia participants (n = 392) > 55 years of age. Results: Variability associated with age decreased by almost half in the A-N- norm sample relative to the conventional norm sample. Fully-adjusted MNS A-N- norms showed approximately 7- 9% higher sensitivity to MCI/dementia compared to fully-adjusted MNS conventional norms for trials 1- 5 total and sum of trials. Among women, sensitivity to MCI/dementia increased with each normative data refinement. In contrast, age-adjusted conventional MNS norms showed greatest sensitivity to MCI/dementia in men. Conclusions: A-N- norms show some benefits over conventional normative approaches to MCI/dementia sensitivity, especially for women. We recommend using these MNS A-N- norms alongside MNS conventional norms. Future work is needed to determine if normative samples that are not well characterized clinically show greater benefit from biomarker-refined approaches.

Mayo Normative Studies: regression-based normative data for remote self-administration of the Stricker Learning Span, Symbols Test and Mayo Test Drive Screening Battery Composite and validation in individuals with Mild Cognitive Impairment and dementia.

Objective: Few normative data for unsupervised, remotely-administered computerized cognitive measures are available. We examined variables to include in normative models for Mayo Test Drive (a multi-device remote cognitive assessment platform) measures, developed normative data, and validated the norms. Method: 1240 Cognitively Unimpaired (CU) adults ages 32-100-years (96% white) from the Mayo Clinic Study of Aging and Mayo Alzheimer's Disease Research Center with Clinical Dementia Rating® of 0 were included. We converted raw scores to normalized scaled scores and derived regression-based normative data adjusting for age, age2, sex and education (base model); alternative norms are also provided (age+age2+sex; age+age2). We assessed additional terms using an a priori cut-off of 1% variance improvement above the base model. We examined low test performance rates (<-1 standard deviation) in independent validation samples (n=167 CU, n=64 mild cognitive impairment (MCI), n=14 dementia). Rates were significantly different when 95% confidence intervals (CI) did not include the expected 14.7% base rate. Results: No model terms met the a priori cut-off beyond the base model, including device type, response input source (e.g., mouse, etc.) or session interference. Norms showed expected low performance rates in CU and greater rates of low performance in MCI and dementia in independent validation samples. Conclusion: Typical normative models appear appropriate for remote self-administered MTD measures and are sensitive to cognitive impairment. Device type and response input source did not explain enough variance for inclusion in normative models but are important for individual-level interpretation. Future work will increase inclusion of individuals from under-represented groups.

Clinical criteria for a limbic-predominant amnestic neurodegenerative syndrome.

Predominant limbic degeneration has been associated with various underlying aetiologies and an older age, predominant impairment of episodic memory and slow clinical progression. However, the neurological syndrome associated with predominant limbic degeneration is not defined. This endeavour is critical to distinguish such a syndrome from those originating from neocortical degeneration, which may differ in underlying aetiology, disease course and therapeutic needs. We propose a set of clinical criteria for a limbic-predominant amnestic neurodegenerative syndrome that is highly associated with limbic-predominant age-related TDP-43 encephalopathy but also other pathologic entities. The criteria incorporate core, standard and advanced features, including older age at evaluation, mild clinical syndrome, disproportionate hippocampal atrophy, impaired semantic memory, limbic hypometabolism, absence of neocortical degeneration and low likelihood of neocortical tau, with degrees of certainty (highest, high, moderate and low). We operationalized this set of criteria using clinical, imaging and biomarker data to validate its associations with clinical and pathologic outcomes. We screened autopsied patients from Mayo Clinic and Alzheimer's Disease Neuroimaging Initiative cohorts and applied the criteria to those with an antemortem predominant amnestic syndrome (Mayo, n = 165; Alzheimer's Disease Neuroimaging Initiative, n = 53) and who had Alzheimer's disease neuropathological change, limbic-predominant age-related TDP-43 encephalopathy or both pathologies at autopsy. These neuropathology-defined groups accounted for 35, 37 and 4% of cases in the Mayo cohort, respectively, and 30, 22 and 9% of cases in the Alzheimer's Disease Neuroimaging Initiative cohort, respectively. The criteria effectively categorized these cases, with Alzheimer's disease having the lowest likelihoods, limbic-predominant age-related TDP-43 encephalopathy patients having the highest likelihoods and patients with both pathologies having intermediate likelihoods. A logistic regression using the criteria features as predictors of TDP-43 achieved a balanced accuracy of 74.6% in the Mayo cohort, and out-of-sample predictions in an external cohort achieved a balanced accuracy of 73.3%. Patients with high likelihoods had a milder and slower clinical course and more severe temporo-limbic degeneration compared to those with low likelihoods. Stratifying patients with both Alzheimer's disease neuropathological change and limbic-predominant age-related TDP-43 encephalopathy from the Mayo cohort according to their likelihoods revealed that those with higher likelihoods had more temporo-limbic degeneration and a slower rate of decline and those with lower likelihoods had more lateral temporo-parietal degeneration and a faster rate of decline. The implementation of criteria for a limbic-predominant amnestic neurodegenerative syndrome has implications to disambiguate the different aetiologies of progressive amnestic presentations in older age and guide diagnosis, prognosis, treatment and clinical trials.

Decreased white matter integrity in neuropsychologically defined mild cognitive impairment is independent of cortical thinning.

Improved understanding of the pattern of white matter changes in early and prodromal Alzheimer's disease (AD) states such as mild cognitive impairment (MCI) is necessary to support earlier preclinical detection of AD, and debate remains whether white matter changes in MCI are secondary to gray matter changes. We applied neuropsychologically based MCI criteria to a sample of normally aging older adults; 32 participants met criteria for MCI and 81 participants were classified as normal control (NC) subjects. Whole-head high resolution T1 and diffusion tensor imaging scans were completed. Tract-Based Spatial Statistics was applied and a priori selected regions of interest were extracted. Hippocampal volume and cortical thickness averaged across regions with known vulnerability to AD were derived. Controlling for corticalthic kness, the MCI group showed decreased average fractional anisotropy (FA) and decreased FA in parietal white matter and in white matter underlying the entorhinal and posterior cingulate cortices relative to the NC group. Statistically controlling for cortical thickness, medial temporal FA was related to memory and parietal FA was related to executive functioning. These results provide further support for the potential role of white matter integrity as an early biomarker for individuals at risk for AD and highlight that changes in white matter may be independent of gray matter changes.

Neural network process simulations support a distributed memory system and aid design of a novel computer adaptive digital memory test for preclinical and prodromal Alzheimer's disease.

OBJECTIVE: Growing evidence supports the importance of learning as a central deficit in preclinical/prodromal Alzheimer's disease. The aims of this study were to conduct a series of neural network simulations to develop a functional understanding of a distributed, nonmodular memory system that can learn efficiently without interference. This understanding is applied to the development of a novel digital memory test. METHOD: Simulations using traditional feed forward neural network architectures to learn simple logic problems are presented. The simulations demonstrate three limitations: (a) inefficiency, (b) an inability to learn problems consistently, and (c) catastrophic interference when given multiple problems. A new mirrored cascaded architecture is introduced to address these limitations, with support provided by a series of simulations. RESULTS: The mirrored cascaded architecture demonstrates efficient and consistent learning relative to feed forward networks but also suffers from catastrophic interference. Addition of context values to add the capability of distinguishing features as part of learning eliminates the problem of interference in the mirrored cascaded, but not the feed forward, architectures. CONCLUSIONS: A mirrored cascaded architecture addresses the limitations of traditional feed forward neural networks, provides support for a distributed memory system, and emphasizes the importance of context to avoid interference. These process models contributed to the design of a digital computer-adaptive word list learning test that places maximum stress on the capability to distinguish specific episodes of learning. Process simulations provide a useful method of testing models of brain function and contribute to new approaches to neuropsychological assessment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Risk of dementia and psychiatric or sleep disorders after diagnosis of adrenal adenomas: a population-based cohort study.

OBJECTIVE: Adrenal adenomas are commonly encountered in clinical practice. To date, population-based data on their impact on cognition, mental health, and sleep are lacking. We aimed to study possible associations between adrenal adenomas and dementia, psychiatric or sleep disorders. DESIGN: Population-based cohort study, Olmsted County, MN, 1995-2017. METHODS: Patients with adrenal adenoma and absent overt hormone excess were age- and sex-matched 1:1 to a referent person without adrenal adenoma. Outcomes were baseline and incident diagnoses of dementia, psychiatric or sleep disorders, assessed using ICD codes. RESULTS: Of 1004 patients with adrenal adenomas, 582 (58%) were women, and median age at diagnosis was 63 years. At baseline, and after adjusting for age, sex, education, BMI, and tobacco use, patients with adenoma had higher odds of depression (adjusted odds ratio, aOR: 1.3, 95% CI, 1.1-1.6), anxiety (aOR: 1.4, 95% CI, 1.1-1.8), and substance abuse (aOR: 2.4, 95% CI, 1.7-3.4) compared to referents. During a median follow-up of 6.8 years, and after adjusting for age, sex, socioeconomic status, BMI, tobacco, and substance abuse, patients demonstrated a higher risk of psychiatric and sleep disorders [adjusted hazard ratio (95% CI)]: depression [1.7 (1.3-2.2)], anxiety [1.4, CI (1.1-1.7)], insomnia [1.4 (1.0-1.9)], sleep-related breathing disorders [1.5 (1.1-1.9)], hypersomnias [2.1 (1.0-4.2)], parasomnias [2.1 (1.0-4.2)], and sleep-related movement disorders [1.5 (1.0-2.1)], but not dementia. CONCLUSIONS: Patients with adenomas demonstrate a higher incidence of psychiatric and sleep disorders, possibly due to the underlying subtle increase in cortisol secretion.

Evaluation of the Electronic Clinical Dementia Rating for Dementia Screening.

Importance: The Clinical Dementia Rating (CDR) is a well-validated instrument widely used to detect and stage dementia due to Alzheimer disease. The digital Electronic Clinical Dementia Rating (eCDR) can be remotely self-administered and automatically scored, with potential to facilitate efficient dementia screening and staging. Objective: To evaluate the association of the eCDR with the CDR and other in-clinic assessments for screening older adults for cognitive impairment. Design, Setting, and Participants: This multisite, cross-sectional study used baseline data from a longitudinal, observational study from 2020 to 2023, including up to 3 years of follow-up. Participants were enrolled from 3 Alzheimer Disease Research Centers and the Brain Health Registry. Participants (aged ≥55 years, with a study partner, and no acute or unstable major medical conditions) were recruited during in-clinic visits or by automated emails. Exposures: Participants completed the Uniform Data Set Version 3 (UDS; including the CDR) in supervised clinical research settings, and then completed the eCDR remotely, online and unsupervised, using their own device. Main Outcomes and Measures: The primary outcomes were eCDR scores (item; categorical box and global; continuous box and global), CDR scores (item; categorical box and global), and UDS assessment scores. Associations were evaluated using linear and logistic regressions. Results: A total of 3565 participants were contacted, and 288 were enrolled. Among 173 participants with item-level data (mean [SD] age, 70.84 [7.65] years; 76 women [43.9%]), eCDR to CDR concordance was 90% or higher for 33 items (63%) and 70% to 89% for 13 items (25%). Box (domain) level concordance ranged from 80% (memory) to 99% (personal care). The global score concordance rate was 81%. κ statistics were fair to moderate. Among 206 participants with box and global scores (mean [SD] age, 71.34 [7.68] years; 95 women [46.1%]), eCDR continuous global score was associated with CDR global (categorical) score with an area under the receiver operating characteristic curve of 0.79 (95% CI, 0.70-0.87). Correlations between eCDR and in-clinic UDS assessments were similar to those between CDR sum of box scores and the same in-clinic assessments. Conclusions and Relevance: These findings suggest that the eCDR is valid and has potential use for screening and assessment of older adults for cognitive and functional decline related to Alzheimer disease. Instrument optimization and validation in diverse cohorts in remote settings are crucial for evaluating scalability and eCDR utility in clinical research, trials, and health care settings.