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T. Paranhos

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Open access Aug 2026

EOAD-Signature Atrophy Predicts Dementia in Early-Onset MCI due to Alzheimer Disease

Background and Objectives Early-onset Alzheimer disease (EOAD) is associated with substantial variability in clinical progression, and reliable biomarkers to predict the transition from mild cognitive impairment (MCI) to dementia remain limited. Structural MRI measures have demonstrated prognostic value in late-onset Alzheimer disease, but their utility for predicting progression in EOAD is less well understood. The goal was to examine whether baseline cortical atrophy predicts progression to dementia in patients with MCI because of EOAD. Methods This study included a well-characterized cohort of patients with EOAD enrolled in the large multisite natural history Longitudinal Early-Onset Alzheimer's Disease Study. Participants underwent standardized clinical assessments and structural MRI at baseline. Participants were aged between 40 and 64 years with biomarker-supported sporadic EOAD at the MCI stage. Cortical atrophy was measured within the EOAD-signature, a set of predominantly parieto-temporal regions showing greater atrophy in EOAD than in controls. Clinical severity was measured with the global Clinical Dementia Rating. Cox proportional hazards models estimated the association between baseline EOAD-signature atrophy burden and the hazard of progression to dementia over time. We evaluated whether EOAD-signature atrophy improved prognostic performance beyond baseline clinical severity using likelihood ratio tests, Akaike Information Criterion (AIC), and Harrell concordance index. Results A total of 130 patients with MCI due to EOAD (mean age 59.6 ± 4.1 years; 49% female) and 97 cognitively normal controls (mean age 56.9 ± 6.0 years; 64% female) were included. Greater baseline atrophy within the EOAD-signature predicted faster progression to dementia (hazard ratio [HR] = 1.24 per 1-SD increase in atrophy; 95% CI 1.13–1.37; p < 0.002). Adding EOAD-signature atrophy burden to a model including baseline clinical severity significantly improved model fit (ΔAIC = −4.5; likelihood ratio test p = 0.011). Discussion Baseline cortical atrophy within the EOAD-signature predicts progression from MCI to dementia in EOAD and provides prognostic information beyond baseline clinical severity. These findings support the potential value of EOAD-signature atrophy as an MRI-based biomarker for individualized prognostication and clinical trial stratification.

T. Paranhos, Yuta Katsumi, M. Brickhouse et al. · 0 citations
Aug 2026

Non-invasive brain stimulation increases default mode network functional connectivity in a patient with Posterior Cortical Atrophy

Abstract Repetitive transcranial magnetic stimulation (rTMS) has been explored as an intervention in typical amnestic Alzheimer’s Disease (AD). However, its effects on episodic and associative memory in atypical forms of AD are less known. Posterior cortical atrophy (PCA) is primarily characterized by visuospatial and visuoperceptual symptoms, although significant episodic memory deficits are often observed. To investigate whether intermittent theta burst (iTBS, a form of rTMS), guided by individualized functional imaging, can modulate functional networks and improve associative memory in a patient with PCA presenting with memory impairments. A stimulation target in the left caudal middle frontal gyrus (cMFG) was selected based on peak functional connectivity with the default mode network (DMN). iTBS was administered to this target in a randomized placebo-controlled paradigm. Primary outcomes were changes in functional connectivity of the stimulation target and associative memory performance. Visuospatial working memory and global cognition were secondary outcomes. Consistent with our hypothesis, active iTBS increased connectivity between the cMFG target and distributed DMN regions. Contrary to our hypothesis, associative memory performance did not improve, but we did observe improvements in visuospatial working memory. This case report supports further controlled clinical trials using functional connectivity guided rTMS in PCA.

T. Paranhos, Anna Du, Ryan Eckbo et al. · 1 citation

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