School of Medicine

Machine learning enables scalable quantification of neuropathology, offering deeper phenotyping of Alzheimer's disease (AD). In this validation study, we quantified amyloid-beta (Aβ) deposits, evaluating multiple brain regions across institutions, and evaluated associations with clinical, demographic, and genetic factors in persons pathologically diagnosed with AD. All linear models were adjusted for sex, age of death, ethnicity, and center. We analyzed densities (#/mm2) of cored plaques, diffuse plaques, and cerebral amyloid angiopathy (CAA) in 273 individuals from 3 Alzheimer's Disease Research Centers. Formalin-fixed paraffin-embedded sections of frontal, temporal, and parietal cortices were immunostained and digitized, generating 799 whole-slide images (WSIs). Following log transformation, mixed-effects modeling revealed the parietal cortex had the highest cored plaque densities (P < .001); the temporal cortex had the highest diffuse plaque (P < .001); CAA showed no regional differences. Wilcoxon rank-sum test, and covariates adjusted linear models showed ApoE ε4- status was associated with higher cored plaque densities in the temporal lobe (P = .04). ApoE ε4+ status was associated with diffuse plaques in the temporal lobe (P = .001), and CAA in the frontal lobe (P = .004). These findings provide further validation and provide exploratory associations advancing deeper phenotyping of AD.

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.

Objective

Method

Results

Conclusions

BACKGROUND: Progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) are 4-repeat tauopathies (4RT) presenting with overlapping syndromes. Imperfect clinicopathological associations increase sample-size demands in clinical trials. We test whether MRI can enrich trials for PSP/CBD and provide sensitive MRI-based outcome measures. METHODS: Longitudinal cohort analysis including participants from the 4 Repeat Tauopathy Neuroimaging Initiative (4RTNI) and phase 2/3 Davunetide trial (DAV). An MRI model trained on autopsy-confirmed cases predicted PSP (MRI-PSP) or CBD (MRI-CBD); corticobasal syndrome (CBS) with positive Alzheimer's biomarkers was reclassified. Clinical scales and MRI-derived thickness/volume were analyzed with linear mixed-effects models. We derived data-driven MRI-signatures (optimal regional combinations) to minimize required trial sample sizes. RESULTS: 206 participants from 4RTNI (n = 106 with Richardson's syndrome [RS], CBS, or nonfluent/agrammatic primary progressive aphasia [nfvPPA]) and DAV (n = 100 with RS). In 4RTNI, 49 participants were predicted MRI-PSP and 43 MRI-CBD. 76% of MRI-PSP had RS, 24% had CBS/nfvPPA; 66% of MRI-CBD had CBS. PSP and CBD signatures shared midbrain/pontine atrophy but differed in cortical involvement. PSP signature correlated strongly with 12-month change on the PSP Rating Scale (β = -0.59, p < 0.001). MRI-based signatures reduced the estimated sample sizes required to detect 30% reduction in progression over 12-months by 50% for MRI-PSP and 87% for MRI-CBD, compared with clinical outcomes. In DAV, feasibility was replicated. CONCLUSION: MRI-derived models can identify PSP or CBD with high accuracy, and MRI-based signatures track progression more sensitively than established clinical outcomes. Incorporating these tools into therapeutic trial design could reduce sample sizes and enable more inclusive disease-modifying trials for 4RT.

Axons are unique structural and functional features of nerve cells, which play a critical role in regulating neuronal homeostasis. Dysfunction and degeneration of axons (axonopathy) has been established as an early and prominent contributing mechanism to the pathogenesis of neurodegenerative diseases including Alzheimers disease, Parkinsons disease, Huntingtons disease, and amyotrophic lateral sclerosis. In this review, we briefly summarize the structure and function of axons, and highlight recent advances in the understanding of the role of axons in health and disease. We argue that axons are a potential target for developing novel therapies for neurodegenerative diseases.

Glycation is a class of modifications arising from non-enzymatic reactions of reducing sugars with proteins, lipids, and/or DNA, generating advanced glycation end-products (AGEs). AGEs are linked to many age-related comorbidities. In response to HIV-1 infection, activated T-cells and macrophages shift their predominate metabolism from oxidative phosphorylation to glycolysis. Increased glycolytic flux enhances AGE formation, which may increase age-related comorbidities. In this prospective, multicenter cohort study of antiretroviral therapy treated people with HIV, we explored predictive associations by baseline plasma AGE concentrations and their corresponding detoxification metabolites, with incident comorbidities and mortality. AGEs included dicarbonyl sugars: 3-deoxyglucosone, glyoxal, and methylglyoxal. Methylglyoxal-derived metabolites included carboxyethyl-arginine, carboxyethyl-lysine, and methylglyoxal hydroimidazolone-1. Detoxification metabolites included reduced and oxidized glutathione, and the glyoxalase cycle products lactoyl-glutathione and lactoyl-Lysine modified proteins. Plasma was collected at study entry, in the fasting state, and assayed by liquid chromatography-mass spectroscopy. Incident clinical outcomes included diabetes, chronic kidney disease, hypertension, neurocognitive impairment, peripheral neuropathy, frailty, fractures, recurrent falls, and all-cause mortality. Among 376 participants, higher baseline plasma concentrations of methylglyoxal derived AGEs predicted increased risks of diabetes, chronic kidney disease, and recurrent falls, while higher 3-deoxyglucosone predicted an increased risk of peripheral neuropathy. By contrast, higher baseline concentrations of reduced or oxidized glutathione, lactoyl-glutathione, and/or lactoyl-Lysine modified proteins predicted lower risks of diabetes, neurocognitive impairment, frailty, fractures, recurrent falls, and all-cause mortality. These findings support growing experimental evidence of the potential to mitigate age-related declines by interventions that reduce glycation or increase glutathione.

Neurogenic orthostatic hypotension (nOH), a common non-motor feature of Parkinson’s disease (PD), is defined as a sustained drop in blood pressure (BP) upon standing due to autonomic dysfunction. Although prior studies support an association between nOH and cognitive impairment, its longitudinal impact on cognitive decline in PD remains insufficiently explored. We aimed to determine to what extent baseline nOH is associated with an accelerated decline in global and exploratory domain-specific cognitive functions. A retrospective longitudinal cohort study was conducted using clinical data from patients with PD evaluated at the University of California San Diego movement disorders clinics between 2012 and 2024. Participants were classified as having nOH (nOH+) or without nOH (nOH−) based on initial orthostatic BP measurements (≥20 mmHg systolic BP and/or ≥10 mmHg diastolic BP reduction within 3 minutes of standing, with a blunted heart rate response [ΔHR/ΔSBP] < 0.5 bpm/mmHg). Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA), including total scores and domain-specific subscores. Longitudinal changes in cognitive function were modeled using linear mixed-effects models, adjusting for time, nOH status, age, sex, and their interaction. Motor and non-motor symptom progression was evaluated using the MDS-UPDRS Parts I–III. Patients with nOH at the first visit showed faster decline in total MoCA scores (Interaction β = −0.57, SE = 0.15, p < 0.001), reflecting declines in abstraction (Interaction β = −0.15, SE = 0.05, p < 0.01), attention (Interaction β = −0.13, SE = 0.04, p < 0.01), delayed recall (Interaction β = −0.18, SE = 0.06, p < 0.001), executive function (Interaction β = −0.16, SE = 0.05, p < 0.001), language (Interaction β = −0.14, SE = 0.05, p < 0.001), and orientation (Interaction β = −0.17, SE = 0.06, p < 0.001) subscores. No significant time × nOH interaction was observed for MDS-UPDRS Parts I-III (all p > 0.6), indicating comparable rates of motor and nonmotor symptom progression between nOH+ and nOH− groups. In this single-center, real-world retrospective cohort, the presence of baseline nOH was associated with a more rapid decline in cognitive function. These findings highlight the potential importance of early autonomic assessment in PD and warrant further investigation in larger, multi-center studies to determine generalizability and to better understand the underlying mechanisms contributing to cognitive deterioration.

Oral cannabidiol (CBD) treatment has been suggested to alleviate severe symptoms of autism spectrum disorder (ASD). While many CBD preparations have been studied in clinical trials involving ASD, none has used purified CBD preparations or preparations approved by the U.S. Food and Drug Administration, nor have they focused on children with ASD with higher support needs. Previous studies have identified several candidate electrophysiological biomarkers of cognitive and behavioral disabilities in ASD, with emerging biomarkers including periodic (oscillatory) and aperiodic measures of neural activity. We analyzed electroencephalography (EEG) recordings from 24 boys with ASD and higher support needs (aged 7–14 years) from a prior double-blind, placebo-controlled, crossover Phase II Clinical Trial (NCT04517799) that investigated whether 8 weeks of daily CBD treatment (up to 20 mg/kg/day) improved severe behavioral problems, measured at baseline, post-CBD, post-placebo, and post-washout. Using linear mixed effect models, we found that aperiodic EEG measures varied with CBD metabolite levels in blood, as evidenced by a larger aperiodic offset across the scalp and a decreased aperiodic exponent across occipital electrodes. Furthermore, CBD metabolite levels in blood had a positive association with receptive vocabulary, nonverbal intelligence and visuomotor coordination. Our data suggest that this daily CBD preparation and administration schedule produced mixed effects, with some children showing improvements in cognitive and behavioral abilities while others demonstrated limited changes. Our findings support the inclusion of aperiodic EEG measures alongside traditional oscillatory EEG measures as candidate biomarkers for tracking the variable clinical impact of purified CBD treatment in children with ASD.