Lago, Argentina Lario

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.

AbstractBackgroundGiven the rarity of genetic frontotemporal dementia (FTD), researchers across the world have come together to form the FTD Prevention Initiative (FPI) in an effort to improve prevention trials design. As this initiative begins to bring together large‐scale data from worldwide cohort series, including ALLFTD in North America and GENFI in Europe and Canada, it is critical for FPI to quantify the level of relatedness between all participants. Here we provide the most recent update to these ongoing analyses.MethodsGenome‐wide SNP genotyping data from 1,684 ALLFTD and 568 GENFI participants was used to perform lineage analyses using PLINK. Briefly, QC was performed similarly in all datasets to remove individuals with low call rate and filter autosomal SNPs for missingness, frequency, and deviation from Hardy‐Weinberg equilibrium. Genetic ancestry was inferred by projecting genotyped samples into the principal components of the 1000 Genomes reference panel, using R package bigsnpr. Overlapping ALLFTD and GENFI genotyping data was then used, in a two‐stage approach, to calculate pairwise identity‐by‐descent (IBD) estimates and KING coefficients, followed by family‐network identification and pedigree reconstruction using PRIMUS.ResultsFirst, we calculated IBD estimates among all participants by restricting pairs to those with estimates>0.1875 (up to second‐degree relatives). Overall, we identified a total of 292 second‐degree family networks, including 168 ALLFTD and 120 GENFI families, mostly associated with pathogenic variants in the 3 major FTD‐causing genes. We also identified 4 family networks with participants enrolled in both the ALLFTD and GENFI series, as well as several multi‐site families within the ALLFTD consortium. This first, overall approach allowed us to predict close relationships even between individuals with different ancestral backgrounds, including at least 4 confirmed admixed families. More distant relationships were also detected within ALLFTD and GENFI by performing ancestry‐based analysis among participants with estimated European ancestry, using the KING‐robust algorithm.ConclusionsThese lineage analyses allowed us to identify, otherwise unknown, close (and distant) relatives from different study sites, as well as within the ALLFTD and GENFI series. This dataset will be a crucial resource to increase statistical accuracy and power in upcoming collaborative FPI studies.

AbstractBackgroundTMEM106B, a lysosomal trafficking protein, is an important genetic susceptibility risk factor for frontotemporal lobar degeneration (FTLD). In GRN mutation carriers, minor allele homozygosity in the TMEM106B rs1990622 SNP modulates the risk of FTLD. TMEM106B is often the main component of amyloid fibrils in FTLD with TDP43 aggregates. TMEM106B has been quantified in human brain specimens, but its role as a fluid biomarker is unknown. Here, we investigate the clinical value of CSF TMEM106B in FTLD.MethodsCSF TMEM106B was quantified with SOMAmer proteomics (v3.0, SomaLogic®) in an original cohort of C9orf72, GRN and MAPT symptomatic and asymptomatic mutation carriers and family non‐carrier controls, recruited through ALLFTD (n = 182), and a validation cohort of sporadic neuropathology‐confirmed FTLD‐tau and FTLD‐TDP43, clinically‐diagnosed progressive supranuclear palsy – Richardson syndrome (PSP‐RS) and age‐matched controls (n = 96). CSF TMEM106B was correlated with disease severity, measured by the Frontotemporal Lobar Degeneration module global scores (CDR+NACC/FTLD); brain volume, measured with Bayesian linear mixed‐effect modeling, using age, sex and total‐intracranial volume‐corrected permutations with threshold‐free cluster enhancement; and CSF neurofilament light chain (NfL) measured with Simoa. TMEM106B SOMAmer specificity was validated in cell culture overexpression systems and human brain specimens with high TMEM106B burden.ResultsIn both cohorts, there were no differences in CSF TMEM106B by sex, phenotype or neuropathological diagnosis, except for lower levels in PSP‐RS compared to controls (‐0.31 Log2‐fold change, p < 0.001). CSF TMEM106B did not correlate with age. Regardless of disease‐causing mutation, lower CSF TMEM106B was associated with worse disease severity (Figure 1 and 2). CSF TMEM106B was lower in homozygous TMEM106B rs1990622 protective allelein C9orf2 and MAPT, but not in GRN mutation carriers (Figures 3). CSF TMEM106B showed a trend for inverse correlation with NfL in the whole sample (r = ‐0.135, p = 0.052), and correlated positively with left frontal volume in symptomatic FTLD mutation gene carriers (p < 0.05).ConclusionCSF TMEM106B is quantifiable in CSF in vivo. CSF TMEM106B levels are affected by an interaction of disease severity and FTLD and TMEM106B genotypes. Further work is needed to determine its value as a clinical biomarker.

ObjectiveMicrotubule‐associated protein tau (MAPT) mutations cause frontotemporal lobar degeneration, and novel biomarkers are urgently needed for early disease detection. We used task‐free functional magnetic resonance imaging (fMRI) mapping, a promising biomarker, to analyze network connectivity in symptomatic and presymptomatic MAPT mutation carriers.MethodsWe compared cross‐sectional fMRI data between 17 symptomatic and 39 presymptomatic carriers and 81 controls with (1) seed‐based analyses to examine connectivity within networks associated with the 4 most common MAPT‐associated clinical syndromes (ie, salience, corticobasal syndrome, progressive supranuclear palsy syndrome, and default mode networks) and (2) whole‐brain connectivity analyses. We applied K‐means clustering to explore connectivity heterogeneity in presymptomatic carriers at baseline. Neuropsychological measures, plasma neurofilament light chain, and gray matter volume were compared at baseline and longitudinally between the presymptomatic subgroups defined by their baseline whole‐brain connectivity profiles.ResultsSymptomatic and presymptomatic carriers had connectivity disruptions within MAPT‐syndromic networks. Compared to controls, presymptomatic carriers showed regions of connectivity alterations with age. Two presymptomatic subgroups were identified by clustering analysis, exhibiting predominantly either whole‐brain hypoconnectivity or hyperconnectivity at baseline. At baseline, these two presymptomatic subgroups did not differ in neuropsychological measures, although the hypoconnectivity subgroup had greater plasma neurofilament light chain levels than controls. Longitudinally, both subgroups showed visual memory decline (vs controls), yet the subgroup with baseline hypoconnectivity also had worsening verbal memory and neuropsychiatric symptoms, and extensive bilateral mesial temporal gray matter decline.InterpretationNetwork connectivity alterations arise as early as the presymptomatic phase. Future studies will determine whether presymptomatic carriers' baseline connectivity profiles predict symptomatic conversion. ANN NEUROL 2023;94:632–646

AbstractBackgroundThe ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) research consortium is actively enrolling participants across 23 North American centers to characterize sporadic and familial frontotemporal dementia (FTD) and prepare for disease‐modifying clinical trials. The ability to identify, otherwise unknown, relatives among these participants is critical to rigorously build family structures for downstream clinical and genetic research studies.MethodsGenome‐wide SNP genotyping data from ALLFTD participants was used to perform lineage analyses using PLINK. Briefly, QC was performed to remove individuals with low call rate and filter autosomal SNPs for missingness, allele frequency, and deviation from Hardy‐Weinberg equilibrium, before pruning SNPs for linkage disequilibrium. Identity‐by‐descent (IBD) estimates were then calculated for determining relatedness, followed by family‐network identification and pedigree reconstruction using PRIMUS.ResultsAbout 46% of ALLFTD participants that were genotyped and passed QC (n = 1,453) had reported a family history, while 50% (n = 721) did not and were considered sporadic. We identified a total of 460 participants that had at least one relative who was second degree or closer (PI_HAT>0.1875) based on IBD sharing, resulting in 150 family networks. This included 9 participants who self‐identified as sporadic, demonstrating the utility of direct genetic characterization to determine familiality in FTD. Most of the predicted families were associated with disease causing variants in the 3 major FTD‐causing genes: 66 families with known C9orf72 repeat expansion carriers, 35 with MAPT (including 11 families with the variant historically known as p.P301L) and 30 with GRN pathogenic variant carriers, as well as 2 families with carriers of both a C9orf72 expansion and a GRN pathogenic variant. We also identified 5 families with carriers of pathogenic variants in other familial dementia genes (2 TARDBP, 2 VCP and 1 PSEN1), as well as 12 families with yet unknown genetic etiology.ConclusionsThis dataset sets up a crucial resource to increase statistical accuracy and power in downstream association studies using the clinical, neuropsychological, neuroimaging and biomarker data currently being generated by the ALLFTD consortium. It will also facilitate genetic studies aimed at novel gene discovery, and identification of haplotypes and genetic modifiers associated with the 3 major FTD causal genes.

ImportancePhysical activity is associated with cognitive health, even in autosomal dominant forms of dementia. Higher physical activity is associated with slowed cognitive and functional declines over time in adults carrying autosomal dominant variants for frontotemporal lobar degeneration (FTLD), but whether axonal degeneration is a potential neuroprotective target of physical activity in individuals with FTLD is unknown.ObjectiveTo examine the association between physical activity and longitudinal neurofilament light chain (NfL) trajectories in individuals with autosomal dominant forms of FTLD.Design, Setting, and ParticipantsThis cohort study included individuals from the ALLFTD Consortium, which recruited patients from sites in the US and Canada. Symptomatic and asymptomatic adults with pathogenic variants in one of 3 common genes associated with FTLD (GRN, C9orf72, or MAPT) who reported baseline physical activity levels and completed annual blood draws were assessed annually for up to 4 years. Genotype, clinical measures, and blood draws were collected between December 2014 and June 2019; data were analyzed from August 2021 to January 2022. Associations between reported baseline physical activity and longitudinal plasma NfL changes were assessed using generalized linear mixed-effects models adjusting for baseline age, sex, education, functional severity, and motor symptoms.ExposuresBaseline physical activity levels reported via the Physical Activity Scale for the Elderly. To estimate effect sizes, marginal means were calculated at 3 levels of physical activity: 1 SD above the mean represented high physical activity, 0 SD represented average physical activity, and 1 SD below the mean represented low physical activity.Main Outcomes and MeasuresAnnual plasma NfL concentrations were measured with single-molecule array technology.ResultsOf 160 included FTLD variant carriers, 84 (52.5%) were female, and the mean (SD) age was 50.7 (14.7) years. A total of 51 (31.8%) were symptomatic, and 77 carried the C9orf72 variant; 39, GRN variant; and 44, MAPT variant. Higher baseline physical activity was associated with slower NfL trajectories over time. On average, NfL increased 45.8% (95% CI, 22.5 to 73.7) over 4 years in variant carriers. Variant carriers with high physical activity demonstrated 14.0% (95% CI, −22.7 to −4.3) slower NfL increases compared with those with average physical activity and 30% (95% CI, −52.2 to −8.8) slower NfL increases compared with those with low physical activity. Within genotype, C9orf72 and MAPT carriers with high physical activity evidenced 18% to 21% (95% CI, −43.4 to −7.2) attenuation in NfL, while the association between physical activity and NfL trajectory was not statistically significant in GRN carriers. Activities associated with higher cardiorespiratory and cognitive demands (sports, housework, and yardwork) were most strongly correlated with slower NfL trajectories (vs walking and strength training).Conclusions and RelevanceIn this study, higher reported physical activity was associated with slower progression of an axonal degeneration marker in individuals with autosomal dominant FTLD. Physical activity may serve as a primary prevention target in FTLD.