Snyder, Allison

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

AbstractINTRODUCTIONCardiovascular health is important for brain aging, yet its role in the clinical manifestation of autosomal dominant or atypical forms of dementia has not been fully elucidated. We examined relationships between Life's Simple 7 (LS7) and clinical trajectories in individuals with autosomal dominant frontotemporal lobar degeneration (FTLD).METHODSTwo hundred forty‐seven adults carrying FTLD pathogenic genetic variants (53% asymptomatic) and 189 non‐carrier controls completed baseline LS7, and longitudinal neuroimaging and neuropsychological testing.RESULTSAmong variant carriers, higher baseline LS7 is associated with slower accumulation of frontal white matter hyperintensities (WMHs), as well as slower memory and language declines. Higher baseline LS7 associated with larger baseline frontotemporal volume, but not frontotemporal volume trajectories.DISCUSSIONBetter baseline cardiovascular health related to slower cognitive decline and accumulation of frontal WMHs in autosomal dominant FTLD. Optimizing cardiovascular health may be an important modifiable approach to bolster cognitive health and brain integrity in FTLD.Highlights Better cardiovascular health associates with slower cognitive decline in frontotemporal lobar degeneration (FTLD). Lifestyle relates to the accumulation of frontal white matter hyperintensities in FTLD. More optimal cardiovascular health associates with greater baseline frontotemporal lobe volume. Optimized cardiovascular health relates to more favorable outcomes in genetic dementia.

Abstract The pathophysiological mechanisms driving disease progression of frontotemporal lobar degeneration (FTLD) and corresponding biomarkers are not fully understood. We leveraged aptamer-based proteomics (> 4,000 proteins) to identify dysregulated communities of co-expressed cerebrospinal fluid proteins in 116 adults carrying autosomal dominant FTLD mutations (C9orf72, GRN, MAPT) compared to 39 noncarrier controls. Network analysis identified 31 protein co-expression modules. Proteomic signatures of genetic FTLD clinical severity included increased abundance of RNA splicing (particularly in C9orf72 and GRN) and extracellular matrix (particularly in MAPT) modules, as well as decreased abundance of synaptic/neuronal and autophagy modules. The generalizability of genetic FTLD proteomic signatures was tested and confirmed in independent cohorts of 1) sporadic progressive supranuclear palsy-Richardson syndrome and 2) frontotemporal dementia spectrum syndromes. Network-based proteomics hold promise for identifying replicable molecular pathways in adults living with FTLD. ‘Hub’ proteins driving co-expression of affected modules warrant further attention as candidate biomarkers and therapeutic targets.