Jack, Clifford R.

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.

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).

Abstract BACKGROUND Understanding long-term sequelae of cancer care is critical. Cognitive impairment is a common and disabling survivorship issue. Because sex influences tumor biology, therapy exposure, and dementia risk, we examined whether cancer care for a prior malignancy alters late-life cognitive outcomes differently in males and females. METHODS We assessed adults ≥50 years, cognitively normal at study entry, from a longitudinal, population-based cohort (Mayo Clinic Study of Aging). Participants were linked to our institutional cancer registry (excluding non-melanoma skin cancers). Mild cognitive impairment (MCI) and dementia were adjudicated by consensus. We fitted multivariable Cox proportional-hazards models to estimate how prevalent cancer diagnosis influenced the risk of developing MCI/dementia. Sex-specific effects were determined by incorporating a cancer×sex interaction term and by generating separate hazard ratios. Analyses were controlled for age, APOE4 status, education, and presence of vascular/metabolic conditions. RESULTS 5793 MCSA participants (female: 49.4%, APOE4 positive: 27.5%) were included in the study, with a mean age of 73 years at study entry. Incident MCI was recorded in 866 participants, and 737 were diagnosed with incident dementia. About 20% (n=1176) of the cohort had a cancer diagnosis, most commonly prostate (n=423) and breast (n=277). There was no independent relationship between history of cancer and risk for MCI or dementia. We found that males with cancer had an increased risk for MCI (HR 1.28, 95% CI 1.04-1.57, p=0.003) and dementia (HR 1.29, 95% CI 1.04-1.6, p=0.053). Conversely, females with cancer had a lower risk for MCI (HR 0.79, 95% CI 0.61-1.01, p=0.063), although this was not statistically significant. CONCLUSIONS Our data suggests male cancer survivors may be more susceptible to cognitive impairment, independent of age, APOE4 status, education, and vascular/metabolic burden. Elucidating the hormonal, treatment-related, and systemic pathways driving this should be a priority for future mechanistic studies.

Objective Lewy body disease (LBD) is a complex neurodegenerative disorder characterized by the accumulation of misfolded α‐synuclein in the brain. Neuroinflammation has long been implicated in LBD pathogenesis, and recent genetic studies in Parkinson's disease (a clinical manifestation of LBD) have shown consistent association with the human leukocyte antigen (HLA) gene complex. Here, we assessed whether variation in HLA alleles influences neuropathological burden in a neuropathologically‐defined series of LBD cases. Methods We conducted a comprehensive analysis of HLA allelic variants in a cohort of 539 LBD cases of European descent from the Mayo Clinic brain bank. High‐resolution whole‐genome sequencing was used, and the HLA alleles of each sample were called using the HLA*LA tool and assessed for association with neuropathological outcomes. Results Our analysis identified 1 significant ( P < 3.43 × 10 −5 ) and 4 suggestive ( P < 0.001) associations between certain HLA alleles and specific neuropathological outcomes in LBD, suggesting a potential role for HLA‐mediated immune mechanisms in disease progression and subtype differentiation. Specifically, HLA‐DPB1*06:01 was significantly associated with lower Lewy body counts in the parahippocampal gyrus ( P = 3.30 × 10 −5 ), with weaker and suggestive associations observed in the middle frontal ( P = 1.80 × 10 −4 ) and inferior parietal gyrus ( P = 6.33 × 10 −4 ). Additionally, although only suggestive, HLA‐DRB1*11:01 correlated with a lower Thal amyloid phase ( P = 1.56 x 10 −4 ), and HLA‐B*15:01 correlated with an increased risk of diffuse LBD ( P = 7.58 x 10 −4 ). Interpretation This study provides a detailed evaluation of the relationship between HLA alleles and LBD pathology, highlighting the importance of immune‐related genetic factors in the etiology of LBD. ANN NEUROL 2026;99:492–501

Decades of research on biomarker identification and integration in Alzheimer’s disease (AD) have helped to advance biologically driven disease models, disease subtypes, and disease-modifying treatments. Key lessons learned from AD biomarker development include the need for integration of new biological insights, investment in large cross-sectional and longitudinal studies, a multicomponent biomarker approach, and recruitment of clinical trial cohorts and biosamples that are representative of the target population. We describe how these lessons are being applied in Parkinson’s disease, Huntington’s disease, multiple sclerosis, and psychotic disorders as use cases to inform biomarker-based approaches across central nervous system disorders.

Abstract INTRODUCTION M0 images were missing in Siemens ASL data in Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, prohibiting cerebral blood flow (CBF) quantification. METHODS A conditional latent diffusion model was trained and evaluated on in‐house datasets, then applied to the Siemens data in ADNI‐3. Regional CBF differences by Alzheimer's disease (AD) stages, their accuracy for AD classification, and CBF trajectory slopes were compared between generated data (Siemens) and acquired data (General Electric). RESULTS The diffusion model generated M0 images with high fidelity (SSIM = 0.918 ± 0.023, PSNR = 31.361 ± 2.537) and minimal CBF bias (mean difference is 0.21 ± 1.58 mL/100 g/min). Both generated and acquired CBF showed similar spatial patterns and decreasing trends with AD progression in specific AD‐related regions. Generated CBF also improved accuracy in classifying AD stages compared to qualitative perfusion images. CONCLUSION This study shows the potential of diffusion models for imputing missing modalities in large‐scale studies exploring the use of ASL as a biomarker of AD. Highlights Using latent diffusion model, we can generate M0 image from control image in arterial spin labeling (ASL) with high fidelity. The generated M0 can be used for cerebral blood flow (CBF) quantification in Alzheimer's Disease Neuroimaging Initiative dataset. The performance of classification between Alzheimer's disease (AD) patients and cognitive normal people is better when using generated CBF maps than using non‐quantitative perfusion images. ASL CBF decreases with AD progression in key AD‐related brain regions.

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.