Reliability of remote self‐administered Web‐based digital cognitive measures and comparison to in‐person neuropsychological tests: Stricker Learning Span, Symbols Test, and the Mayo Test Drive Screening Battery Composite
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.
Individualized Atrophy‐Based Prediction of Dementia Progression in Familial Frontotemporal Lobar Degeneration With Bayesian Linear Mixed‐Effects Modeling
Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD. We used a Bayesian linear mixed‐effect (BLME) prediction method for identifying accelerated brain volume loss to predict conversion to dementia. Methods Participants included 234 asymptomatic or prodromal carriers of C9orf72 , GRN , or MAPT mutations (including 21 dementia converters) with ≥3 longitudinal magnetic resonance imaging (MRI) T1‐weighted scans. The BLME models established individual voxel‐wise gray matter trajectories using the first 2 scans. Person‐specific clusters of accelerated volume loss were estimated in subsequent scans and tested as predictors of dementia conversion compared with other approaches in time‐varying Cox proportional hazard models covarying for age. Receiver‐operating characteristic (ROC) curves estimated utility of cluster volume in discriminating which participants converted to dementia within 24 months. Results The BLME cluster volume predicted conversion to dementia in f‐FTLD mutation carriers overall and separately in C9orf72 , GRN , and MAPT , with comparable hazard ratios observed for atrophy W‐maps and regional volumes. Within a 24‐month timeframe, BLME cluster volume discriminated dementia converters from non‐converters with larger areas under the curve (AUCs) than other approaches. Interpretation Bayesian‐modeled individualized atrophy scores predict dementia progression among asymptomatic f‐FTLD mutation carriers and may have increased utility compared with other structural imaging methods when studying individuals over shorter timeframes that align with clinical trial design. ANN NEUROL 20269999:n/a–n/a
A Longitudinal Investigation of Prediabetes, Diabetes,
HbA1c
and Cognitive Trajectories Among Cognitively Unimpaired Individuals
ABSTRACT Background Previous studies on the relationship between prediabetes, HbA1c and cognitive trajectories show mixed results. Therefore, we investigated the association of prediabetes, diabetes and HbA1c with change in global and domain‐specific cognitive scores in cognitively unimpaired (CU) adults, as well as the potential effect modification by sex or age. Methods This longitudinal study included 4236 CU persons aged ≥ 50 years from the population‐based Mayo Clinic Study of Aging. We ran linear mixed‐effect models with baseline prediabetes, diabetes and HbA1c predicting longitudinal global and domain‐specific (i.e., memory, language, attention/executive function, and visuospatial skills) cognitive z‐scores and raw scores. Models were adjusted for age, sex, education, medical comorbidity, repeated cognitive testing, and ApoEɛ4. We additionally ran models with sex and age interactions. Results Compared to normoglycemic individuals, individuals with prediabetes and diabetes showed poorer performance on cognitive tests, i.e., TMT‐B, category fluency, and block design subtest over time. Additionally, the presence of prediabetes, diabetes, longer diabetes duration and higher HbA1c were associated with faster global and domain‐specific cognitive decline over a median follow‐up of 6.4 years (range 1–19). Three‐way interactions showed that the effect of diabetes on decline in global cognition, attention and visuospatial domains was more pronounced in women than in men. Age did not modify the effect of diabetes or higher HbA1c on cognition. Conclusions The results suggest that prediabetes and diabetes significantly shorten the timeframe before a potentially clinically noticeable change in global and domain‐specific cognition is reached. Thus, lifestyle modification to reverse prediabetes and prevent diabetes could potentially reduce the rate of cognitive decline in aging populations. The findings differed by sex (i.e., the effect of diabetes on decline in global cognition, attention and visuospatial domains was more pronounced in women than men).
Physical and Cognitive Activities and Trajectories of AD Neuroimaging Biomarkers
Background The literature on dyslipidemia and cognitive trajectories among cognitively unimpaired (CU) persons remains inconclusive. Objective To investigate the association between baseline dyslipidemia and change in global and domain specific (i.e., memory, language, attention/executive function, and visuospatial skills) cognition in a population-based setting and whether the association differs by sex, age, or APOE ɛ4 carrier status. Methods We conducted a longitudinal study derived from the Mayo Clinic Study of Aging, involving 4236 CU persons aged ≥ 50 years. We ran linear mixed-effect models to examine baseline dyslipidemia in predicting longitudinal cognitive global and domain-specific z-scores adjusted for age, sex, education, medical comorbidity, repeated cognitive testing, and APOE ɛ4. We examined interactions among dyslipidemia, years since baseline, and separately by sex, age, and APOE ɛ4 carrier status. Results Over a median follow-up period of 6.4 years, CU individuals with dyslipidemia showed faster decline in z-scores of all domains, i.e., memory, language, attention/executive function, visuospatial and global cognition relative to CU individuals without dyslipidemia. Three-way interactions showed that dyslipidemia's effect on decline in z-scores of global cognition, attention and visuospatial skills was less pronounced in males than females. Higher age increased dyslipidemia's effect on decline in z-scores of attention but not global cognition or any other domain. APOE ɛ4 carrier status did not modify the effect of dyslipidemia on cognitive z-scores. Conclusions Dyslipidemia was associated with faster global and domain-specific cognitive decline over time in older community-dwelling individuals who were cognitively unimpaired at baseline. The effect of dyslipidemia on cognitive trajectories may be sex-influenced.
Predictive Value of Plasma Biomarkers in Tau‐
PET
Transitions
Objective The objective of this study was to determine the predictive value of amyloid‐positron emission tomography (PET) versus the plasma ratio of phosphorylated tau at threonine 217 (p‐tau217) to non‐phosphorylated tau217 (%p‐tau217) for tau‐PET transitions (T− to T+). The added value of combining plasma amyloid‐β 42 and amyloid‐β 40 (Aβ42/40) and %p‐tau217 into an amyloid probability score (APS2) was also assessed. Methods Mayo Clinic Study of Aging (MCSA) participants had plasma markers measured at via mass spectrometry (MS), an amyloid‐PET scan, and a tau‐PET (meta‐temporal region of interest [ROI]) negative scan (standardized uptake value ratio [SUVR] <1.29) at the index (baseline) date, along with one or more follow‐up tau‐PET scans. The BioFINDER‐2 cohort was used for validation. Cox proportional hazards models adjusted for age, sex, and apolipoprotein ( APOE ) ε4 were used to assess predictors, with scaling to the interquartile range (IQR) for comparability of hazard ratios (HR). Results Among 255 tau‐PET negative MCSA participants (median age: 71.9 years), 37 converted to tau‐PET positive (median follow‐up time: 3.81 years). Higher %p‐tau217 (HR: 1.52 [95% CI: 1.28–1.80]), amyloid‐PET centiloid (HR: 1.47 [95% CI: 1.20–1.79]), and APS2 (HR: 1.62 [95% CI: 1.22–2.16]) predicted tau‐PET conversion. However, Aβ42/40 (HR: 0.94 [95% CI: 0.54–1.66]) was not associated with tau‐PET conversion. In the BioFINDER‐2 cohort (605 tau‐negative, median age: 70.2), 33 converted to tau‐positive (median follow‐up time: 2 years), with higher %p‐tau217 (HR: 1.80 [95% CI: 1.50–2.17]), amyloid‐PET centiloid (HR: 2.29 [95% CI: 1.77–2.97]), and lower Aβ42/40 (HR: 2.38 [95% CI: 1.17–4.83]) predicting conversion. Interpretation In two cohorts, %p‐tau217 was associated with tau‐PET conversion, comparable to amyloid‐PET. APS2 also predicted conversion in the MCSA cohort, whereas Aβ42/40 predicted conversion in the BioFINDER‐2 cohort, which had more individuals with cognitive impairment. ANN NEUROL 2025;98:1249–1260
Depression and Cognitive Outcomes: Linking the Mayo Clinic Study of Aging and Rochester Epidemiology Project