Citations

Abstract INTRODUCTION Cognitive characterization is increasingly important for Alzheimer’s disease treatment decisions, highlighting the need for scalable cognitive assessment. We evaluated the diagnostic accuracy of a remote self-administered cognitive screening battery, Mayo Test Drive (MTD), across clinically and biologically defined groups. METHODS In this prospectively designed study, 2,131 cognitively unimpaired (CU) and 118 cognitively impaired participants, including 96 with mild cognitive impairment and 22 with mild dementia (MCI/DEM), were recruited from observational cohort studies and completed MTD remotely (mean age=70 years, SD=12; 48% male; mean education=16 years, SD=2). Clinical diagnoses were determined by multidisciplinary consensus independently of MTD. Amyloid- and tau-PET were available for 1,224 participants. Logistic regression estimated associations between MTD and CU versus MCI/DEM, CU A-versus MCI/DEM A+, and A-T-versus A+T+. MTD diagnostic accuracy was compared with person-administered cognitive measures. Sensitivity and specificity across score types and comparison groups were examined. RESULTS MTD showed excellent discrimination of CU versus MCI/DEM (AUC=.89; 95% CI=.87-.92), and discriminability remained high for CU versus MCI (AUC=.88; 95% CI=.85-.92). Discriminability was highest when comparing CU A- and MCI/DEM A+ groups (AUC=.95; 95% CI=.92-.97). MTD outperformed estimated MMSE (p=.02) and was comparable to Mayo-PACC (p=.71) for A-T-versus A+T+ discrimination (AUC=.76; 95% CI=.71-.81). Combining both raw score and normative score cutoffs helped balance sensitivity and specificity relative to use of either cutoff in isolation. A two-stage interpretation framework further improved sensitivity while maintaining clinically useful specificity and informed development of an interpretation guide. DISCUSSION A remote self-administered digital cognitive assessment showed strong diagnostic accuracy for detecting MCI and mild dementia in a large, primarily population-based cohort. The remote, self-administered MTD composite also showed comparable performance to established in-person cognitive composites for differentiating amyloid and tau-defined biomarker groups. Remote self-administered digital cognitive assessment may complement existing cognitive evaluation approaches and support scalable cognitive characterization. Highlights Remote self-administered cognitive assessment showed strong differentiation of cognitively unimpaired and cognitively impaired participants. Diagnostic accuracy improved when amyloid PET biomarker status was incorporated. Remote assessment demonstrated sensitivity to amyloid and tau PET-defined Alzheimer’s disease. Performance was comparable to established in-person composites and better than an in-person mental status screening measure. Digital cognitive screening may support scalable treatment and clinical trial workflows.

Abstract Introduction Remote cognitive assessments offer an accessible, scalable way to support clinical characterization and longitudinal monitoring of cognition. This study evaluates the feasibility of implementing Mayo Test Drive (MTD), a remote, self-administered digital cognitive assessment, within a specialized clinic focused on eligibility assessments for anti-amyloid therapies for Alzheimer’s disease (AD). Method Two-hundred and nine ( N =209) patients (M age =71.2, 53% female) were evaluated through the Mayo Clinic Rochester Alzheimer’s Disease Treatment Clinic (ADTC) and had the opportunity to complete MTD, either as a remote, patient-initiated session through a patient-facing healthcare portal or during an in-clinic neuropsychological evaluation. Results Clinical diagnoses included 55.2% mild cognitive impairment (MCI), 31.0% mild dementia, and 11.6% moderate dementia, in addition to 2.2% cognitively unimpaired (CU), as determined by neurology consensus at a multidisciplinary case conference. Among those who initiated MTD ( n =197/209), 97.5% completed a session (70.6% remotely, 26.9% in clinic). Completion rates were high across diagnostic groups and did not significantly differ by clinical severity ( p =.12): CU (100%), MCI (99.1%), mild dementia (97.0%), and moderate dementia (89.5%). Remote completion rates overall were high (97.9%). Among completers, administration setting (remote vs. in-clinic) did not significantly differ by clinical stage, χ²(3)=2.37, p =.49. Reasons for non-initiation included not receiving or opening portal messages and other/unknown factors. Discussion Remote digital cognitive assessment is feasible within the context of clinic eligibility evaluations for AD therapies. The high completion rates of MTD across clinical impairment levels in this setting support development of paths for broader use in cognitive characterization in AD care.

Abstract INTRODUCTION We describe the reliability of remote self‐administered digital cognitive measures completed via the Mayo Test Drive (MTD) web‐based platform. METHODS A total of 1846 participants (mean age = 70, SD = 12, range 31–101; 48% male; 96% White; 99% non‐Hispanic; 97% cognitively unimpaired) with two to four complete MTD sessions at ∼7.5‐month intervals were included. Test‐retest reliability was assessed using single‐rating, absolute‐agreement, and two‐way mixed intraclass correlation coefficients (ICCs) with 95% confidence intervals. ICCs for in‐person‐administered traditional neuropsychological measures were compared to MTD for a subset of 244 participants. Analyses also compared reliability across demographic, residential, and session context subgroups. RESULTS Reliability was good for the MTD Composite (total ICC = 0.79 [0.77, 0.80]), and moderate‐to‐good for the primary outcome variables for each MTD subtest (total ICCs 0.70–0.83 for Stricker Learning Span and Symbols). The reliability of the remote self‐administered MTD was similar to in‐person‐administered cognitive measures. DISCUSSION MTD showed moderate‐to‐good reliability, supporting its use in longitudinal monitoring.

Abstract INTRODUCTION We examined when Alzheimer's disease biomarkers become informative by identifying age‐related breakpoints with slope‐changing trajectories. METHODS In 2082 Mayo Clinic Study of Aging participants, we modeled plasma amyloid beta (Aβ)42/40, phosphorylated tau (p‐tau)181, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), amyloid/tau positron emission tomography (PET), hippocampal volume (HVa), and global cognition. Generalized additive models described age trends; Davies' test and piecewise linear regression estimated breakpoints. A C2N subsample ( n = 462) provided mass‐spectrometry plasma markers (p‐tau181, p‐tau217, their ratios, Aβ42/40). RESULTS In the full cohort, Aβ42/40, HVa, and cognition declined with age; p‐tau181, NfL, GFAP, and amyloid/tau PET increased. We observed single breakpoints (years, 95% CI): GFAP 68.1 (63.5–71.8), NfL 70.7 (65.9–75.6), p‐tau181 67.2 (60.3–70.3), amyloid PET 62.3 (56.2–69.3), HVa 68.1 (63.1–71.9), cognition 59.8 (55.4–66.0); tau PET showed none. In the mass‐spectrometry subset, p‐tau217 and p‐tau181 broke at 72.6; their ratios and Aβ42/40 showed no breakpoints. DISCUSSION Breakpoints cluster near late midlife, suggesting windows for screening and monitoring.

Abstract Associations of Alzheimer’s disease biomarker progression with cognitive decline are important to inform patient prognosis. Of particular interest is how newly available plasma biomarkers evolve relative to cognitive decline. The goals of this work are to measure how much earlier versus later an individual’s progression on plasma and PET Alzheimer’s disease biomarkers is associated with earlier versus later cognitive progression and to estimate the average timeline of progression of these processes in the population. In this cohort study of 2369 Mayo Clinic Study of Aging (MCSA) and 1591 Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants, we fit non-linear mixed-effects models to estimate how much earlier versus later each individual progresses on plasma phosphorylated tau (p-tau)217, amyloid PET, tau PET and auditory verbal learning test (AVLT) sum of trials relative to the population mean (individual adjustment), the associations of these individual adjustments among biomarker pairs and how covariates affect the timing of biomarker progression. The association of individual adjustments implies mechanistic associations and the amount of variability in cognitive decline accounted for by each biomarker. By applying cut-off points, we also estimated the relative timing that these biomarkers become abnormal in the population. Associations of individual adjustments were moderate between all biomarkers and AVLT (R = 0.38–0.47) in the MCSA and stronger (R = 0.74–0.81) in ADNI; plasma p-tau217 accounted for 16% of the variability in timing of AVLT decline in the MCSA and 64% in ADNI. APOE ɛ4 carriership was associated with earlier biomarker progression. AVLT became abnormal after the biomarkers up to age 90, after which AVLT was estimated to become abnormal prior to tau biomarkers. The association of the timing of plasma and PET Alzheimer’s disease biomarker progression with cognitive decline was modest in the MCSA population-based sample and stronger in the Alzheimer’s disease-enriched ADNI cohort. The timing of plasma p-tau217 progression explained a similar degree of variability in AVLT progression as amyloid PET, supporting its utility as a marker of disease progression. The estimated temporal ordering of biomarkers and cognitive abnormality was as anticipated (amyloid, tau, cognition) up to the age of 90, beyond which AVLT was estimated to become abnormal prior to tau biomarkers, likely related to the effects of non-Alzheimer’s disease co-pathologies.

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 Cognitive symptoms are common among cancer patients treated with intracranial radiation but inadequately assessed and suboptimally treated, owing in part to the time-consuming and resource-intensive nature of formal neuropsychological testing. Through remote administration of brief cognitive assessments and symptom-directed interventions, decentralization uniquely addresses this problem. METHODS In this single-site phase 2 fully decentralized clinical trial (NCT06377696), patients treated with radiation therapy (RT) for primary or metastatic brain tumors undergo cognitive evaluations with the application, Mayo Test Drive, and the Short Test of Mental Status (STMS; via telehealth or in person), at baseline and every three months for one year. Participants are provided wearable devices for health promotion. Half the participants are randomized to metformin to evaluate this agent’s efficacy in treating RT-related cognitive symptoms. Target enrollment is 100 participants. RESULTS Seventy-three patients (median age 45.5, 46% female) with brain tumors who received RT were enrolled May 2024 to May 2025. In this unplanned interim analysis, we evaluated the impact of decentralization on study participation. Thirty-six participants (49%) reported a primary residence greater than 150 miles from our institution. Seven patients were consented remotely, the remainder in person. Of 380 study-related visits (201 STMS, 179 treatment toxicity checks) 216 (57%) were completed by telehealth. Thirty-two of 336 (9.5%) study-related lab draws were completed at locations outside our institution. Wearable device data was continuously collected, with median 3022 steps tracked per patient per day on study. 190/250 (76%) quality-of-life surveys sent digitally were completed to date. CONCLUSION Decentralization implemented as part of this clinical trial enabled participation despite significant distance from our institution and facilitated study-related assessments through digital solutions, eliminating the need for travel. Our findings demonstrate the feasibility of conducting a fully decentralized supportive care trial in neuro-oncology, which can increase participation and accelerate evaluation of novel therapeutics.

Abstract Insulin resistance (IR) is a modifiable risk factor for dementia, yet its effects on brain metabolism and function remain unclear. In older adults, greater IR was associated with reduced cerebral glucose uptake (indicating impaired mitochondrial metabolism), atrophy, and weakened connectivity between brain regions critical for cognition. In neuron-specific insulin receptor knockout mice, brain IR produced deficits in hippocampal- and prefrontal-dependent tasks accompanied by reduced brain mitochondrial ATP and elevated reactive oxygen species. To evaluate reversibility of IR-induced brain deficits, forty older adults with IR were randomized to 40-weeks of metformin or placebo. Metformin improved insulin sensitivity, increased brain glucose uptake, strengthened cognitive network connectivity, and preserved whole-brain and regional volumes implicated in decision-making and learning. Metformin also improved processing speed and working memory. Collectively, these findings highlight IR as a driver of brain metabolism and support the concept that insulin sensitization can prevent neurobiological deficits in older people with IR.