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A. Boxer

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Clinical trial Open access Oct 2026

Phase 3 randomized trial of latozinemab in frontotemporal dementia due to GRN mutations

Abstract INTRODUCTION Heterozygous progranulin gene mutations causing frontotemporal dementia (FTD‐GRN) are associated with deficiency in progranulin (PGRN). Latozinemab is a human monoclonal immunoglobulin G1 (IgG1) antibody designed to elevate PGRN levels in people with heterozygous loss‐of‐function (LOF) GRN mutatio...

Adam Simmons, B. Boeve, I. Le Ber et al. · 0 citations
Open access Oct 2026

Large-scale cerebrospinal fluid proteomics identifies diagnostic biomarker candidates across the clinico-pathological continuum of frontotemporal lobar degeneration

Frontotemporal lobar degeneration (FTLD), predominantly comprised of tau and TDP-43 proteinopathies, is a common cause of early-onset dementia. Biomarkers that reliably classify FTLD subtypes are limited, thereby hindering in-vivo diagnosis and clinical trial stratification. We conducted large-scale, multi-platform cer...

R. Saloner, L. Cornelis, Joshua Downer et al. · 0 citations
Open access Sep 2026

Smartphone Passive Digital Phenotyping in Frontotemporal Lobar Degeneration

Introduction: Frontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. Remote monitoring via low-burden digital health tools may overcome these barriers. We evaluated clinical utility...

E. Paolillo, Sreya Dhanam, J. Taylor et al. · 0 citations
Review Aug 2026

TDP-43-Associated Neurodegenerative Disease Conceptualization and Integrated Staging: A Review.

A pathobiological definition of disease is proposed to provide a road map for developing biomarkers that accurately reflect the underlying pathobiology of disease and for advancing therapeutic candidates that effectively target fundamental disease mechanisms.

M. Benatar, SJ Barmada, Gregory A. Jicha et al. · 1 citation
#machine learning Open access Dec 2024

Enhancing brain age estimation with structural MRI and synthesized cerebral blood volume maps

Abstract Brain age gap estimation (BrainAGE) is a promising imaging-derived biomarker of neurobiological ageing and disease risk, yet current approaches rely predominantly on T1-weighted structural MRI, overlooking functional vascular changes that may precede tissue damage and cognitive decline. Deep learning-derived c...

Jordan Jomsky, Zongyu Li, K. Igwe et al. · 1 citation

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