Gorno‐Tempini, Maria‐Luisa

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

Abstract INTRODUCTION Risk factors associated with sporadic non‐amnestic and early‐onset Alzheimer's disease (AD) remain underexamined. METHODS We investigated a large, clinically heterogeneous, AD cohort for frequencies of established risk factors (hypertension, hypercholesterolemia, diabetes mellitus) alongside novel factors (non–right‐handedness, learning disability, seizures, autoimmune disease). RESULTS Early‐onset AD possessed lower frequencies of established risk factors (hypertension, hypercholesterolemia, diabetes mellitus, all p < 0.001) and higher frequencies of novel factors (non–right‐handedness, learning disability, active seizure, all p < 0.001; remote seizure, p = 0.002; and autoimmune disease, p = 0.007). An age at onset < 70 maximally distinguished novel from typical factors. Principal component analysis loaded novel factors into two components, non–right‐handedness and learning disability versus seizure and autoimmune disease, which combined, resulted in an exponential decrease in age at onset from one factor alone. DISCUSSION Identifying novel factors enriched in early‐onset and non‐amnestic AD introduces new theories of AD susceptibility and phenotypic heterogeneity, with significant implications for disease prediction and treatment. Highlights We identified a suite of novel factors overrepresented in early‐onset and non‐amnestic AD. These factors can be broadly conceptualized as neurodevelopmental (non–right‐handedness and learning disability) and neural environmental (seizure and autoimmunity). The combination of these factors produced exponential decreases in AD age at onset, compared to each alone, supporting a new theoretical framework for understanding AD risk with implications for disease prediction, prevention, and therapeutic intervention.

ABSTRACT Objective Autosomal dominant progranulin ( GRN ) pathogenic variants are a genetic cause of frontotemporal lobar degeneration. Though clinical trials for GRN ‐related therapies are underway, there is an unmet need for biomarkers that can predict symptom onset and track disease progression. We previously showed that asymptomatic GRN variant carriers exhibit thalamocortical hyperconnectivity that increases with age, presumably as they are approaching symptom onset. Whether hyperconnectivity arises concomitantly with markers of neurodegeneration remains unclear. Methods Utilizing T1 and task‐free functional magnetic resonance imaging from 49 asymptomatic and 26 symptomatic GRN variant carriers, we determined the relationships between functional connectivity, as measured by voxelwise whole‐brain degree, and GRN ‐relevant markers of disease progression, including plasma neurofilament light chain concentrations, cerebrospinal fluid complement C1q and C3b protein levels, obsessive‐compulsive disorder symptom severity, and gray matter volume. Results Neurofilament light chain concentrations were associated with frontotemporoparietal and thalamic hyperconnectivity in asymptomatic GRN variant carriers and extensive regions of atrophy in symptomatic carriers. Complement levels were associated with regions of hyperconnectivity, but not gray matter volume, in symptomatic carriers. Obsessive‐compulsive disorder symptom severity was associated with hypoconnectivity across all GRN carriers. Asymptomatic carriers with thalamic hyperconnectivity tended to have lower gray matter volume in the bilateral insula and left lateral parietal cortex, early regions of atrophy in GRN ‐frontotemporal dementia. Interpretation In asymptomatic carriers, the co‐occurrence of hyperconnectivity, high neurofilament light chain, and low gray matter volume suggests that functional hyperconnectivity may portend the onset of clinical decline. These findings point toward hyperconnectivity as an indicator of approaching symptomatic onset.

Abstract INTRODUCTION Although frontotemporal dementia (FTD) with right anterior temporal lobe (RATL) predominance has been recognized, a uniform description of the syndrome is still missing. This multicenter study aims to establish a cohesive clinical phenotype. METHODS Retrospective clinical data from 18 centers across 12 countries yielded 360 FTD patients with predominant RATL atrophy through initial neuroimaging assessments. RESULTS Common symptoms included mental rigidity/preoccupations (78%), disinhibition/socially inappropriate behavior (74%), naming/word‐finding difficulties (70%), memory deficits (67%), apathy (65%), loss of empathy (65%), and face‐recognition deficits (60%). Real‐life examples unveiled impairments regarding landmarks, smells, sounds, tastes, and bodily sensations (74%). Cognitive test scores indicated deficits in emotion, people, social interactions, and visual semantics however, lacked objective assessments for mental rigidity and preoccupations. DISCUSSION This study cumulates the largest RATL cohort unveiling unique RATL symptoms subdued in prior diagnostic guidelines. Our novel approach, combining real‐life examples with cognitive tests, offers clinicians a comprehensive toolkit for managing these patients. Highlights This project is the first international collaboration and largest reported cohort. Further efforts are warranted for precise nomenclature reflecting neural mechanisms. Our results will serve as a clinical guideline for early and accurate diagnoses.