Cobigo, Yann

AbstractBackgroundClinical trials are underway to treat familial frontotemporal lobar degeneration (f‐FTLD). This is a rare disease, and a limited number of mutation carriers have been identified; thus, efficient trial design is critical. Multimodal, latent disease progression models (DPM) can estimate time to symptom onset and define the temporal ordering of biomarker changes. DPMs can also be leveraged to select endpoints and potentially supplement analyses by integrating historical data. Recent draft FDA guidance for gene therapy trials in neurological disease supports these novel approaches to clinical trials.MethodParticipants included 1,049 members of families affected by f‐FTLD, due to mutations in GRN, MAPT, or C9orf72 genes, who were enrolled in ALLFTD or GENFI. A Bayesian repeated measures model incorporated multimodal data to estimate disease progression, conditional on latent disease age (proximity to symptom onset), in 677 mutations carriers (GRN (n=233), MAPT (n=151) and C9orf72 (n=293)). Family members without pathogenic mutations were used as the reference group. Mean follow‐up was 1.1 (SD=1.1) years. Jointly modeled longitudinal variables included neuropsychological scores, CDR®+NACC‐FTLD Box Score, MRI volumes of brain regions affected by f‐FTLD, and plasma levels of neurofilament light chain (NfL).ResultDisease progression curves were similar across ALLFTD and GENFI cohorts. Plasma NfL elevations occurred earliest, up to 10 years before symptom onset, and NfL was the most powerful endpoint in the asymptomatic stage. MRI abnormalities occurred next, closer to symptom onset. The earliest MRI changes relative to symptom onset were observed in C9orf72+. GRN mutation carriers showed the most rapid acceleration in all biomarkers, and this acceleration occurred in close proximity to symptom onset. Neuropsychological measures and CDR®+NACC‐FTLD Box Score were among the most promising endpoints in the symptomatic stage. Trial simulations indicated that using latent disease age as an enrollment criterion would allow some asymptomatic mutation carriers to be enrolled without sacrificing power.ConclusionSimilarity in disease progression across ALLFTD and GENFI participants suggests these models will apply to international trials. Model‐derived estimates of disease progression curves indicate that endpoint selection should be specific to disease stage and mutation, and DPMs would facilitate greater participant enrollment.

Abstract Introduction Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD‐MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD‐MC and could help predict risk for dementia during trial enrollment. Methods We created a dementia risk score by entering standardized gray‐matter volumes from 231 DIAD‐MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD‐MC followed longitudinally. Results Our risk score separated asymptomatic versus demented DIAD‐MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%–98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD‐MC participants for prevention trials.

AbstractBackgroundMeasuring changes in the earliest phases of familial frontotemporal lobar degeneration (f‐FTLD) and estimating symptom onset has important implications for clinical care. Early stage clinical trials have begun for f‐FTD, but the low prevalence of f‐FTLD mutation carriers and heterogeneous symptomology challenges trial design. Bayesian disease progression models (DPM) incorporate clinical data, neuroimaging metrics, and fluid biomarker concentrations to estimate latent disease age, providing estimates of symptom onset and progression status. Such models may facilitate enrollment in studies (i.e., inclusion of presymptomatic individuals) and provide more powerful analysis methods for trials.MethodA Bayesian latent variable repeated measures model was used to estimate disease progression, conditional on latent disease age (proximity to symptom onset), in 275 participants with mutations in GRN (n=68), MAPT (n=80) and C9orf72 (n=127). Median follow‐up was one year (range: 0‐4). Jointly modeled longitudinal variables included neuropsychological scores, CDR®+NACC‐FTLD box score, 3T MRI frontotemporal brain volumes, and plasma levels of neurofilament light chain (NfL). Sample size estimates for detecting treatment effects were generated by varying thresholds of estimated proximity to symptom onset.ResultThe Bayesian DPM provided a clear picture of clinical and neurological progression within each mutation group. Neuroimaging and NfL captured early progression rates (1 SD from controls) 5‐10 years before symptom onset. After symptom onset, CDR®+NACC‐FTLD box score was the most sensitive measure of disease progression. GRN mutation carriers had the largest annual progression rates (and lowest variability) compared to MAPT and C9orf72. Between 5 years pre‐ and 10 years post‐onset, CDR®+NACC‐FTLD box score progressed by 2 units/year (SD=2.7) in GRN mutation carriers ‐ almost twice the rate of progression in MAPT (M=1.2;SD=2.5) and C9orf72 (M=1.1;SD=2.2) mutation carriers. Compared to a trial enrolling only early symptomatic cases (CDR®+NACC‐FTLD=0.5 or 1), utilizing latent disease age would facilitate enrollment of asymptomatic cases with the same power.ConclusionBased on an estimation of symptom onset, Bayesian DPMs suggest clinical trials in GRN mutation carriers would require the smallest sample sizes. Furthermore, leveraging these DPMs would allow novel, powerful trial designs that may facilitate greater participant enrollment.

AbstractBackgroundFamilial frontotemporal dementia (f‐FTLD) is typically caused by mutations in one of three genes: microtubule‐associated protein tau (MAPT), progranulin (GRN), and a repeat expansion in the chromosome 9 open reading frame 72 (C9orf72) gene. Accurate characterization of the natural history of each mutation is important for clinical prognostication and clinical trial design, and it could shed light on disease biology. Such models have not been thoroughly developed using participants that represent all disease stages, with longitudinal data. We characterized the trajectory of atrophy in each gene by using longitudinal voxel‐wise analyses of gray matter volume, and we assessed whether functional independence declined in tandem.MethodF‐FTLD participants (n=100) with a known mutation (MAPT+ (n=28), GRN+ (n=33), C9orf72+ (n=39)) were grouped according to disease stage (CDR®+NACC FTLD module). We included participants with at least two structural MRIs at a given disease stage: presymptomatic (CDR®+NACC‐FTLD=0, n=57), mild/questionable (CDR®+NACC‐FTLD=0.5, n=15), and symptomatic (CDR®+NACC‐FTLD ≥1, n=28). We fitted longitudinal linear mixed effects models to extract mean atrophy rates in each lobe compared to longitudinal imaging from family members without mutations (n=60). All results presented below were significant at p<.001.ResultUsing the left frontal lobe as an exemplar, in the presymptomatic stage, MAPT mutation carriers showed the greatest rate of atrophy compared to controls (88 mm3/year more volume loss than controls), followed by GRN+ (65 mm3/year) and then C9orf72+ (49 mm3/year). In the mild/questionable stage, MAPT+ showed a greater divergence from controls (374 mm3/year) than did GRN+ (107 mm3/year) or C9orf72+ (223 mm3/year). In the symptomatic stage, MAPT+ again lost volume at the fastest rate (2,099 mm3/year), followed by GRN+ (1,360 mm3/year). C9orf72 expansion carriers showed a much slower rate of volume loss (115 mm3/year). Similar patterns were observed for other brain regions. In contrast to the imaging results, C9orf72+ exhibited similar rates of functional decline compared to GRN+ and MAPT+ at all levels of disease severity.ConclusionThe primary f‐FTLD genes show divergent atrophy trajectories as a function of disease stage, with C9orf72 expansion carriers exhibiting a slow degeneration throughout the disease course, possibly due to unique pathophysiological mechanisms.

AbstractIntroductionThe Advancing Research and Treatment in Frontotemporal Lobar Degeneration and Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects longitudinal studies were designed to describe the natural history of familial‐frontotemporal lobar degeneration due to autosomal dominant mutations.MethodsWe examined cognitive performance, behavioral ratings, and brain volumes from the first time point in 320 MAPT, GRN, and C9orf72 family members, including 102 non–mutation carriers, 103 asymptomatic carriers, 43 mildly/questionably symptomatic carriers, and 72 carriers with dementia.ResultsAsymptomatic carriers showed similar scores on all clinical measures compared with noncarriers but reduced frontal and temporal volumes. Those with mild/questionable impairment showed decreased verbal recall, fluency, and Trail Making Test performance and impaired mood and self‐monitoring. Dementia was associated with impairment in all measures. All MAPT carriers with dementia showed temporal atrophy, but otherwise, there was no single cognitive test or brain region that was abnormal in all subjects.DiscussionImaging changes appear to precede clinical changes in familial‐frontotemporal lobar degeneration, but specific early clinical and imaging changes vary across individuals.

AbstractObjectiveThe prognostic value of cerebrospinal fluid neurofilament light chain, total tau, phosphorylated tau181, and amyloid beta1‐42was examined in frontotemporal dementia subtypes.MethodsWe compared baseline biomarkers between 49 controls, 40 patients with behavioral variant frontotemporal dementia, 24 with semantic variant primary progressive aphasia, and 26 with nonfluent variant primary progressive aphasia. Linear mixed effect models were used to assess the value of baseline biomarkers in predicting clinical and radiographic change in patient cohorts over multiple yearly follow up visits.ResultsNeurofilament light chain concentrations were lowest in controls. Elevated baseline neurofilament light chain predicted faster worsening in clinical severity, frontotemporal volume and frontotemporal fractional anisotropy in patients with behavioral variant frontotemporal dementia and nonfluent variant primary progressive aphasia. High total tau similarly predicted faster progression in nonfluent variant primary progressive aphasia. In behavioral variant frontotemporal dementia, higher phosphorylated tau181predicted faster clinical progression whereas lower amyloid beta1‐42predicted faster volumetric and fractional anisotropy reduction. Neurofilament light chain and phosphorylated tau181were of greater predictive value in patients with tau pathology as compared toTDP‐43 pathology. Baseline neurofilament light chain correlated with baseline clinical severity and frontotemporal volume in behavioral variant frontotemporal dementia. Baseline total tau correlated with baseline clinical severity in semantic variant primary progressive aphasia.InterpretationHigh cerebrospinal fluid neurofilament light chain predicts more aggressive disease in behavioral variant frontotemporal dementia and nonfluent variant primary progressive aphasia. Total tau, phosphorylated tau181, and amyloid beta1‐42also predict some measures of disease aggressiveness in frontotemporal dementia.