Over the past few years, several fluid biomarker candidates have been proposed for frontotemporal dementia (FTD). We have previously identified CSF proteins that could separate individuals with genetic FTD from controls. However, it is unknown whether alterations in these CSF protein levels are associated with neurodegenerative processes. The aim of this study was to explore how these CSF biomarker candidates correlate with symptom severity as well as cortical and subcortical atrophy. The levels of fourteen proteins were measured in CSF from 202 individuals, 131 mutation carriers with mutations in C9orf72, GRN, or MAPT, and 71 controls, in a cross-sectional subset from the GENFI cohort. The association between the levels of these proteins and CDR plus NACC FTLD-NM sum-of-boxes, cortical thickness, and subcortical volumes were estimated in the mutation carriers. Elevated CSF levels of five out of fourteen proteins were associated with an increased CDR score in the mutation carriers. Additionally, elevated levels of three of these proteins, NEFM, PTPRN2 and SERPINA3, were associated with reduced cortical thickness and/or subcortical volume among all mutation carriers. Some mutation-specific associations were also observed, with SPP1 and CTSS being associated with CDR and atrophy only in MAPT mutation carriers, while NPTX2 was specific for GRN mutation carriers. As indicated by the association to brain atrophy, the proposed fluid biomarker candidates continue to show promise and additional studies will further elucidate their relationship to cortical atrophy in genetic FTD, and their potential as biomarkers for diagnosis, prognosis, and disease staging.

Copy-number variants (CNVs) are major contributors to human disease. In Alzheimer disease (AD), APP duplications cause autosomal-dominant forms, but the role of CNVs in non-monogenic AD remains poorly characterized. We analyzed rare CNVs (frequency <1%) from 22,319 exomes (4,150 early-onset AD [EOAD, ≤65 years], 8,519 late-onset AD [LOAD], 9,650 unaffected control subjects) using harmonized calling and quality control. After identifying 17 individuals with a pathogenic CNV, we performed exome-wide and gene-set burden analyses. EOAD-affected individuals showed increased burdens of rare CNVs affecting coding genes, particularly deletions in AD-related genes. Integrated loss-of-function (LoF) analysis gathering short truncating variants with deletions showed that ABCA1 (odds ratio [OR] = 5.77 [95% confidence interval 2.25; 17.06], p = 0.0002) and ABCA7 deletions contribute to this deletion burden (OR = 2.29 [1.44; 3.65], p = 0.0006), while CTSB LoF alleles appear as candidates (OR = 5.03 [1.50; 20.71], p = 0.0089). We then performed exome-wide gene-level dosage analysis and highlighted 18 genes across five loci with a false discovery rate of <10%, including the 22q11.21 central region, where deletions were restricted to EOAD (including one de novo event) and duplications were enriched in control individuals, with intermediate frequencies in LOAD. We narrowed this locus to the SCARF2-KLHL22-MED15 region after integrating short truncating variants. Replication in 33,977 affected individuals and 362,322 control subjects confirmed association for 22q11.21 dosage with exome-wide significance (ORSCARF2 = 0.34 [0.21; 0.53]; mega-p value = 5.52 × 10-7). SCARF2 overexpression significantly increased amyloid-β uptake, congruent with duplication-associated decreased AD risk. We conclude that rare coding CNVs in a proportion of AD-associated genes and 22q11.21 deletions, including some found in DiGeorge syndrome, increase AD risk. Conversely, we identify 22q11.21 duplication as a strong AD-risk-decreasing factor.

Temporal measures, such as time from diagnosis or symptom onset are often used to track disease severity in neurodegenerative diseases. Due to variations in symptom awareness, clinical presentation timing, diagnostic delays, and disease progression rates, these temporal proxies introduce substantial variance and bias, making it very difficult to map progression clearly and accurately, and to severity-match across contrastive patient groups. To address this challenge, we explored a data-driven approach to derive a transdiagnostic severity metric that is independent of time and, instead, treats temporal metrics as observed, dependent data. We analysed data from the Genetic Frontotemporal Dementia Initiative (GENFI 1 and 2). We entered neuropsychological scores for symptomatic individuals including any visits prior to conversion from at-risk to symptomatic (n = 265, 522 visits) in an unrotated principal component analysis to derive a transdiagnostic phenotype-severity model. A single component emerged (Kaiser-Meyer-Olkin = 0.92), explaining 65% of the variance, with all neuropsychological assessments loading highly. This global severity component fitted the data equally well across genetically or clinically defined groups, as well as severity levels. The severity measure’s validity was supported by a clear relationship with the Clinical Dementia Rating scale, and its stability was confirmed when a much broader range of neuropsychological and behavioural measures were included. Additionally, the severity score accounted for a high portion of the total variance in neuropsychological test scores, substantially more than the low proportion accounted for by standard temporal measures. To derive a time-efficient sub-battery, we demonstrated that three neuropsychological assessments (Digit Symbol, Verbal fluency (letters) and Trail Making Test- Part B were able to explain the majority of unique variance in cognitive severity. Finally, by treating time as an observed dependent variable, we showed that the baseline velocity (change in severity measure over time) varied by genetic group, with progranulin mutation carriers being the fastest. This data-driven approach provides an objective, precise measure of disease severity and progression, and it may shed new light on when clinical heterogeneity reflects distinct subtypes rather than differences in disease stage.

Background Brain structural changes in frontotemporal dementia (FTD) can occur decades before symptom onset. Precise characterisation of grey matter changes is necessary for developing models of biomarker progression, while better understanding the trajectory of the pathology is invaluable for prognosis and detecting treatment effects as we enter the era of clinical trials.Methods Cortical and subcortical grey matter volume and thickness from structural MRI were assessed in a large cohort of 892 participants including presymptomatic and symptomatic carriers of mutations within the three main genetic causes of FTD (C9 open reading-frame 72 (C9orf72), progranulin (GRN) and microtubule-associated protein tau (MAPT)) compared with mutation-negative relatives (controls). We compared the distribution of grey matter changes of each metric at different stages of the disease cross sectionally. We aimed to identify grey matter composites for each genetic group which would show the earliest changes and which separated presymptomatic carriers from controls.Results While C9orf72 mutation carriers showed widespread presymptomatic grey matter changes, MAPT and particularly GRN mutation carriers showed changes more proximally to symptom onset. Our composite grey matter signatures, which discriminate asymptomatic/prodromal carriers from controls with high to very high areas under the curve, involved bilateral thalami volumes, precuneus and postcentral thickness in C9orf72; left caudal middle frontal thickness, frontal pole and pars orbitalis volumes in GRN; right temporal pole volume and left insula thickness in MAPT mutation carriers.Conclusion We propose the use of cortical thickness and volume measurements combined from multiple regions into a composite region of interest for each FTD genetic group to identify the earliest changes and track disease progression. Our quasi-longitudinal design illustrates that these regions continue to evolve throughout the symptomatic stages. Investigating how our selected composites progress and validating these in longitudinal samples will be invaluable for future clinical trials.

Frontotemporal dementia (FTD) shows autosomal dominant transmission in up to a third of families, enabling the study of presymptomatic and prodromal phases. Despite self-reported well-being and normal daily cognitive functioning, brain structural changes are evident a decade or more before the expected onset of disease. This divergence between cognitive function and brain structure contrasts with the coupling of structural and functional decline after symptom onset. In healthy ageing, it has been shown that functional connectivity is a better predictor of cognitive function than volumetric structural imaging. We previously proposed that in the presymptomatic phase of genetic FTD, the maintenance of brain functional network integrity enables carriers of pathogenic variants to sustain cognitive performance. However, prior work has focused on a small number of, often predefined, networks. This provides a limited and potentially biased characterisation of the substrates and moderators of brain network integration. Here, we test the hypothesis that brain-wide functional integration in FTD determines resilience to progressive pathology before symptom onset. We assess functional connectome integration in 289 presymptomatic carriers of pathogenic variants associated with FTD using functional magnetic resonance imaging in relation to cognition and contrast with 271 family members without pathogenic variants. Because structural atrophy, functional integration and cognitive profiles are multivariate, we used canonical correlation models, supplemented by multiple linear regression models for each imaging modality. We confirmed progressive atrophy and normal cognitive function in presymptomatic carriers compared to non-carriers. Notably, functional integration was preserved in presymptomatic carriers across age, while it declined in familial non-carriers. The strongest effects were observed in cognitive control networks. The changes in functional integration in presymptomatic carriers were behaviourally relevant and independent of the severity of atrophy, suggesting a resilience mechanism in those at risk of dementia. To generate hypotheses about the genetic and neurometabolic basis of resilience, we assessed the spatial overlap between behaviourally-relevant functional integration maps and gene transcription profiles. These spatial correlations suggested resilience signatures to glial cell composition (astrocytes, microglia, oligodendrocytes), revealing cellular mechanisms inaccessible to standard neuroimaging. Our findings suggest that resilience to atrophy is associated with enhanced functional integration, protecting against clinical conversion for many years in individuals at risk of dementia. This result has implications for the design of presymptomatic disease-modifying therapy trials and gives hope for therapeutic strategies aimed at enhancing resilience and ability to maintain function despite the presence of genetically determined neuropathology.

There is substantial heterogeneity in clinical presentation of genetic Frontotemporal Dementia (FTD), even within the same family. This suggests that additional heritability may exist and contribute to this variable presentation. We examined whether gene-based aggregate burden of genome-wide rare variants (minor allele frequency [MAF]: ≤1%) contribute to variation in regional cortical and subcortical grey matter volumes, after controlling for effects of causative mutations in GRN , MAPT , and C9orf72 . This study was embedded within the GENetic Frontotemporal dementia Initiative (GENFI), which recruits genetic FTD cases and their asymptomatic at-risk family members, both carriers and non-carriers of FTD mutations. We included 518 participants with genotype (Neurochip; imputed against TOPMed), and T1w-MRI brain volumetric data. Gene-based burden tests that aggregate the number of rare variants by gene were used to examine the association of rare variants (MAF: ≤1%) with regional cortical and subcortical grey matter volumes (70 regions of interest [ROIs]), controlling for age, sex, total intracranial volume, mutation status, scanner site, population stratification, and family membership (kinship matrix) using RVTests. Annotations for loss of function mutations (LOF): start gain, stop loss, start loss, essential splice site, stop gain, normal splice site, and non-synonymous. Multiple testing correction accounted for the number of genes and number of independent grey matter volumes as calculated by matSpD ( p -value threshold: 0.05/(17,053x42) =  6.98 x10 -8 ) . Aggregate burden of LOF mutations ( DNAJB8-AS1, WDR26, RDM1P5, BSND, CNOT2, DDA1, ASAH2B, PPM1A, HOXD13, ALDH1A1, CENATAC, ANKRD45) was associated with significantly lower volumes within the left temporal lobe (ROIs: left temporal and lateral temporal left), and greater volume in the putamen bilaterally ( TSACC) . All genes are protein coding, except the DNAJB8-AS1 (antisense RNA) and RDM1P5 (pseudogene), and are variably expressed in the brain. Molecular functions of significant genes involve regulation of gene expression, transcription, and cell cycle, ion channel function, and chromosomal segregation. WDR26 and CNOT2 genes have been implicated in neurodevelopment and neurological disorders respectively; BSND gene is involved in neurotransmission. Identification of deleterious or protective rare variants contributing to FTD imaging phenotypes may help identify genetic modifiers of familial FTD. Replication in larger cohorts is needed.

Abstract BACKGROUND Genetic frontotemporal dementia (FTD) shows large differences in symptom profiles, brain atrophy patterns, and progression rate, making clinical trials difficult to design and power. There is a need for biomarkers that can model disease progression, identify biologically distinct groups, and support efficient trial enrichment. METHODS We applied contrastive trajectory inference (cTI), a machine-learning method, to structural MRI, white matter hyperintensity, and demographic data from 736 participants in the GENFI cohort, including non-carriers and carriers of C9orf72 , GRN , or MAPT mutations. cTI produced an individual “genetic FTD progression score” (0–1) and grouped mutation carriers into data-driven subtypes. We tested construct validity using correlations between progression score and cognitive/functional measures, examined subtype differences in brain–behavior coupling, plasma neurofilament light (NfL), and longitudinal decline, and compared cTI-based trial enrichment against age, cortical thickness and NfL using analytic and simulation-based power analyses. RESULTS Genetic FTD progression scores correlated strongly with global dementia severity and multiple cognitive domains (all p < 0.001), confirming robust clinical scoring. Two mutation-carrier subtypes emerged: a Progressive Track (Subtype 2) with strong associations between progression score and cognitive/functional impairment, rising NfL, and faster longitudinal decline; and a Dissociated Track (Subtype 3) with comparable levels of structural variation but weak or absent clinical and NfL changes, suggesting relative biological stability. Baseline subtype membership added prognostic value for future decline in processing speed and language beyond baseline severity. Notably, for C9orf72 and GRN , cTI-informed enrichment reduced required recruited sample size per arm by about 61–75% compared with unenriched designs, and outperformed enrichment using age, cortical thickness or NfL in both analytic and simulation-based power analyses. CONCLUSIONS Machine-learning stratification of genetic FTD reveals a progressive and a dissociated disease track and provides individualized progression scores that closely track clinical status. cTI progression scores offer a powerful tool for trial enrichment, enabling smaller, more efficient prevention and early-intervention trials than conventional MRI or NfL markers alone.

Bipolar disorder (BD) shows different clinical manifestations according to illness onset (early vs late onset). Its etiology is multifaceted and no reliable biomarkers are available. However, clinical manifestations of BD may stem from disruption in white matter (WM) integrity within brain networks or selective epigenetic alterations, including plasma neural derived extracellular vesicles (NDEVs). In this context, this study further explores the existence of similar epigenetic expression patterns in NDVEs, such as micro-ribonucleic acid (miRNA), and seeks to correlate them with biological markers obtained through Diffusion Tensor Imaging and with clinical data. 23 early onset BD (35% males) (EOBD), 15 late-onset BD (47% males) (LOBD), and 18 healthy controls (44% males) (HC) were recruited. Fractional anisotropy (FA) was investigated through Tract-Based Spatial Statistics. NDEVs were isolated from plasma, and their miRNA content was profiled using real-time polymerase chain reaction. Compared to HC, miR-20a and miR-299-5p were upregulated in EOBD, while miR-323-3p expression was reduced in both EOBD and LOBD patients relative to HC. Moreover, compared to HC, EOBD and LOBD showed decreased FA in the left posterior thalamic radiation and the left anterior corona radiata, respectively. Finally, after Bonferroni correction, EOBD patients showed a negative correlation between miR-323-3p and FA in the left tapetum. Our results shed light on a possible interaction between miRNA expression and WM modifications in BD. However, further research is needed to better characterize the role of miRNA by FA interaction in BD pathophysiology.

Fluid biomarkers to diagnose frontotemporal lobar degeneration (FTLD) are currently lacking. In this study, we aimed to identify proteomic changes in cerebrospinal fluid (CSF) associated with FTLD pathogenesis, focusing on signatures unique to different genetic groups. Additionally, we sought proteins distinguishing FTLD-spectrum disorders from controls. To this end, we measured a comprehensive library of over 2900 proteins in CSF using proximity extension assay technology in two well-characterized FTLD cohorts. The discovery cohort, selected from the GENFI cohort, included 47 symptomatic pathogenic variant carriers (22 C9orf72, 14 GRN, 10 MAPT and 1 TARDBP), 124 presymptomatic pathogenic variant carriers (55 C9orf72, 44 GRN, 24 MAPT and 1 TARDBP) and 57 healthy non-carriers. The validation cohort comprised individuals clinically diagnosed with an FTLD-spectrum disorder (n = 132) and cognitively intact controls (n = 32). We assessed differentially abundant proteins using linear regression, adjusting for age and sex. Overrepresentation analysis was conducted for the three genetic groups using Gene Ontology Biological Processes as ontology source. To develop diagnostic tools, we applied a LASSO regression, establishing two types of panels: one to distinguish individuals with an FTLD-spectrum disorder from controls (FTLD panel) and another to differentiate individuals with underlying TDP pathology from controls (TDP panel). We observed 23 dysregulated proteins in symptomatic carriers. Of these, four were also significantly dysregulated (NEFL, TPM3, MSLN and DNM3) in the validation cohort. When focusing on genetic subgroups, 63 upregulated proteins were observed in symptomatic MAPT carriers, with enriched biological pathways linked to immune function. In symptomatic C9orf72 carriers, four proteins – related to energy metabolism – were upregulated. When limiting symptomatic carriers to GRN, six proteins were dysregulated, with enriched pathways involved in neuronal development and projection. Notably, NEFL and TPM3 were consistently significant in all comparisons across both cohorts. We developed two diagnostic panels: one for FTLD and one for FTLD-TDP. The FTLD panel consisted of six proteins (NEFL, RBFOX3, NPTX1, TFF1, ENTPD5, and CNP). The TDP panel was made up of seven proteins (NEFL, RBFOX3, CBLN4, ENTPD5, CCL25, CNP, and MMP1). Both panels were successfully replicated in the validation cohort (AUC of 0.94 and 0.96 respectively). This study highlights distinct proteomic signatures across FTLD genetic subgroups and their associated pathologies using a targeted proteomic approach. Additionally, we present two diagnostic panels—comprising both established and novel proteins—that effectively differentiate individuals with FTLD-spectrum disorders from healthy controls, offering promising avenues for improved clinical diagnosis.

BACKGROUND:What drives the heterogeneity of survival estimates in genetic frontotemporal dementia is unknown. We sought to understand the natural history and predictors of disease trajectory, which are crucial not only for effective care but also for the design of therapeutic clinical trials and efficacy evaluation. METHODS:In this international, cohort study, we used the Kaplan-Meier method to retrospectively assess survival estimates in patients enrolled in the GENFI cohort, which included 32 research sites located in Belgium, Canada, Finland, France, Germany, Italy, the Netherlands, Portugal, Spain, Sweden, and the UK, and comprised participants carrying a causal C9orf72 expansion or a causal mutation in GRN or MAPT genes. Survival was calculated as the time from symptom onset to time of death or censoring date; median survival estimate for all patients was the primary endpoint. Cox proportional hazards models were used to identify predictors of survival, which were subsequently externally validated in an independent cohort. We further designed a structural equation model to assess the relationships between predictors, applying a least absolute shrinkage and selection operator method. FINDINGS:Of 278 participants of the GENFI cohort included in this study, 160 (58%) were men and 118 (42%) were women. 162 died during follow-up (58%) and 116 were still alive (42%) on June 1, 2024, the chosen censoring date. 138 participants carried a C9orf72 expansion, 94 carried a GRN mutation, and 46 a MAPT mutation. 179 participants were diagnosed with behavioural variant frontotemporal dementia, 46 with primary progressive aphasia, and 31 with frontotemporal dementia-amyotrophic lateral sclerosis. 22 participants had other diagnoses. The median survival estimate for all patients with genetic frontotemporal dementia was 6·94 years (95% CI 6·59-7·80) from symptom onset. The median survival estimate for patients with GRN mutations was 6·63 years (6·08-7·98), for patients with a C9orf72 expansion was 7·04 years (6·45-8·77), and for patients with MAPT mutations was 8·56 years (7·06-13·50). Older age at onset, shorter disease duration from onset to enrolment in the GENFI study, clinical presentation (ie, frontotemporal dementia-amyotrophic lateral sclerosis), domain of first symptom (ie, motor or language onset), and geographical area of residency (ie, central and southern Europe) were associated with poorer prognosis. Genetic group did not directly affect survival estimates; rather its effect was mediated by age at onset and clinical phenotype. We computed a genetic frontotemporal dementia survival risk index, which can be used at an individual patient level. INTERPRETATION:Our results highlight that motor impairment in addition to cognitive and behavioural symptoms should be considered when estimating prognosis in genetic frontotemporal dementia. Individual risk scores might be of help for patient stratification in future therapeutic trials, although refinement and prospective validation are now needed. FUNDING:Italian Ministry of Health (Ricerca Corrente), Fondation Philippe Chatrier, and Fondation Vaincre Alzheimer.

IntroductionCerebrovascular damage is increasingly recognized as an early event in the dementia continuum, occurring before typical Alzheimer’s disease (AD) pathological changes. Hypoxia-inducible factor 1 (HIF-1) is a transcription factor composed of HIF-1α and HIF-1β subunits which, under hypoxic conditions, dimerize and activate hypoxia response element (HRE)-containing genes. HIF-1α has been reported to be implicated in neuroinflammation, a key feature of AD.MethodsThis study evaluated HIF1A and its negative regulator HIF1AN gene expression in peripheral blood mononuclear cells (PBMCs) from 308 cognitively healthy older individuals (controls) and 83 AD patients, and their associations with gene expression of HRE-containing inflammatory genes in PBMCs and corresponding protein concentrations in plasma.ResultsPeripheral blood mononuclear cells from AD patients showed lower gene expression of both HIF1A and HIF1AN compared with controls, and this reduction was associated with higher odds of AD. In the overall cohort, after adjustment for age, sex, Apolipoprotein E ε4 status, and diagnosis, HIF1A gene expression was positively associated with interleukin (IL)-6, IL-10, tumor necrosis factor-α (TNF-α), IL-1B, and triggering receptor expressed on myeloid cells-1 (TREM-1) gene expression, whereas HIF1AN gene expression was negatively associated with IL-6, IL-1B, and TREM-1 gene expression. Furthermore, HIF1A gene expression was positively associated with plasma IL-1β and soluble TREM-1 concentrations, while HIF1AN gene expression was negatively associated with IL-10 concentrations.DiscussionOverall, these findings support the use of peripheral cells to investigate HIF-1 pathway dysregulation in AD and suggest that altered HIF-1α signaling may reflect impaired cellular responsiveness linked to neuroinflammatory processes.

Sporadic behavioral variant frontotemporal dementia (bvFTD) is often misdiagnosed as late-onset primary psychiatric disorder (PPD) due to overlapping symptoms and lack of disease-specific biomarkers. This multicenter pilot study aimed to identify brain atrophy patterns using visual rating scales (VRS) that distinguish between groups, and to compare VRS performance with standard clinical assessment. Magnetic resonance images from bvFTD and PPD patients across five centers were retrospectively reviewed. One rater, blinded for the clinical diagnosis, applied eight VRS. Group differences were assessed, the most predictive scales were identified and combined into a composite score, and the predictivity compared. 297 bvFTD and 92 PPD patients were analysed. All VRS yielded higher atrophy in bvFTD than in PPD patients. The Orbitofrontal, the Anterior-Temporal, and the Fronto-Insula scales were the strongest discriminators, and their composite score outperformed any individual scale. VRS may provide useful diagnostic support for distinguishing bvFTD from PPD.

ABSTRACT Frontotemporal lobar degeneration (FTLD) is a common cause of early-onset dementias marked by progressive declines in behavior, cognition, and/or movement. FTLD neuropathologies, including TDP-43 proteinopathies and primary tauopathies, do not have reliable fluid biomarkers for in-vivo diagnosis nor biomarkers that directly correspond to FTLD clinical features. Fluid biomarkers that forecast and track FTLD clinical progression, irrespective of pathology or clinical syndrome, are urgently needed to improve clinical trial designs. We previously identified the ratio between two cerebrospinal fluid (CSF) synaptic proteins, YWHAG and NPTX2, as a prognostic biomarker of cognitive decline in Alzheimer’s disease (AD), independent of core AD pathologies, amyloid and tau. Here, we evaluate its utility in sporadic and familial FTLD compared to other neurodegenerative diseases. Using CSF assays from four independent cohorts (UCSF-MAC, ALLFTD, GENFI, PDBP), we find CSF YWHAG:NPTX2 is substantially elevated across all sporadic and familial FTLD syndromes, AD, and dementia with Lewy bodies. CSF YWHAG:NPTX2 robustly correlates with clinical severity across sporadic and familial FTLD ( C9orf72 , GRN , or MAPT mutations), independent of current gold-standard neurodegeneration biomarker neurofilament light (NfL). In presymptomatic familial FTLD, CSF YWHAG:NPTX2 is estimated to rise roughly a decade before symptom onset and improves prediction of imminent symptomatic conversion by 1.7-fold compared to plasma NfL alone, more than halving the estimated sample size required for an FTLD prevention clinical trial. These findings underscore CSF YWHAG:NPTX2 as a cross-dementia synaptic biomarker of cognitive decline and a promising biomarker for disease staging and prognosis across the clinico-pathological continuum of FTLD.

Alzheimer's disease (AD) is increasingly recognized as a neurodegenerative disorder associated with chronic low-grade inflammation and age-related immune dysregulation. Microglial-derived extracellular vesicles (MDEVs) are emerging as important mediators of neuroimmune communication and potential biomarkers reflecting pathological processes occurring within the central nervous system (CNS). However, how EV-associated inflammatory signalling changes across different stages of AD remains poorly understood. In this study, we characterized the inflammatory molecular profile of serum-derived MDEVs in 22 AD patients, 19 prodromal AD subjects, and 23 healthy controls (HC). Cytokine concentrations were also evaluated in paired serum and cerebrospinal fluid (CSF) samples to compare vesicle-associated and soluble inflammatory signals across biological compartments. MDEVs were isolated by size exclusion chromatography followed by TMEM119-based immunoenrichment. Cytokine quantification was performed using the Ella Simple Plex automated immunoassay platform. MDEVs from AD patients showed a generalized reduction in both pro- and anti-inflammatory cytokines compared to HC, including IL-1β, TNF-α, IL-2, IFN-γ, IL-6, IL-12p70, IL-10, and IL-4. Notably, several alterations were already detectable at the prodromal stage. In contrast, soluble cytokines in serum and CSF displayed a predominantly pro-inflammatory profile in AD patients, with increased levels of IL-1β, TNF-α, and IL-12p70. No significant correlations were observed between cytokine levels measured in MDEVs and those detected in serum or CSF. Overall, these findings support the presence of a compartment-specific reorganization of inflammatory signalling during AD progression. Early alterations in MDEV inflammatory cargo may reflect disrupted EV-mediated neuroimmune communication and highlight the potential of MDEVs as accessible peripheral biomarkers of neuroinflammatory processes in AD.

Frontotemporal dementia (FTD) is a neurodegenerative disease characterized by significant clinical and genetic heterogeneity, with approximately 40

Background and Objectives:Converging evidence hints at neurodevelopmental effects in genetic frontotemporal degeneration (FTD). In cross-sectional studies, for some genes, young adult FTD variant carriers show differences in brain volumes and cognition compared to familial non-carriers. However, longitudinal trajectories may more sensitively capture FTD-related neurodevelopmental vs. neurodegenerative changes than cross-sectional approaches. This study examined longitudinal trajectories of brain volumes, executive function, and plasma biomarkers in young adult carriers compared to familial non-carriers, as measures of neurodevelopmental and neurodegenerative outcomes of FTD-causing variants. Methods:This longitudinal cohort study comprised participants, aged 18-30 years, from the FTD Prevention Initiative across Europe, Canada, and the USA. Genetic groups included C9orf72 (47%), MAPT (30%), and GRN (23%). Linear mixed-effects models were computed to assess longitudinal outcomes across age between groups, controlling for sex, scanner (for brain volumes), and education (for executive function); random effects accounted for between-subject variability nested within family membership. Results:Variant carriers ( n =147) and familial non-carriers ( n =113) did not differ in age (mean±SD, 25.9±3.2 years), sex (53% female), or number of visits (2.1±1.7). Young adult C9orf72 repeat expansion carriers exhibited smaller thalamic volumes than non-carriers at the reference age of 26 years ( b =-982.8mm 3 , SE=317.0, p= 0.0046, f 2 =0.32), with relatively stable trajectories across ages 18-30 (i.e., no change over time). Trajectories of rostral anterior cingulate volumes differed in C9orf72 carriers and non-carriers across age, where carriers showed relatively stable trajectories and non-carriers showed age-appropriate declines ( b =64.4mm 3 , SE=29.9, p= 0.035, f 2 =0.07). For MAPT and GRN , there were little to no differences in total brain, cortical, or subcortical volumes between groups and over time. No longitudinal differences were observed between carriers and non-carriers in executive function, or plasma NfL or GFAP for any genetic group. Discussion:C9orf72 repeat expansions were linked to smaller average thalamic volumes and stable trajectories between ages 18 to 30, supporting potential neurodevelopmental origins. The modest evidence supporting an absence of difference in neurodegenerative biomarkers and executive function suggests minimal early neurodegeneration and functional preservation in young adulthood.

Individuals with autosomal dominant frontotemporal dementia (FTD) exhibit considerable variability in disease onset and progression. Both modifiable and non-modifiable factors-such as sex, educational attainment or geographic region of residence-may contribute to this heterogeneity, potentially through their influence on cognitive reserve. The aim of the present study was to investigate the role of cognitive reserve modulators within the Genetic Frontotemporal dementia Initiative (GENFI) cohort. To this end, we used functional MRI (i.e. spatial chronnectome measures) and neurodegenerative markers (i.e. plasma neurofilament light chains levels) to determine disease stage using a Discriminative Event-Based Model (DEBM). We then examined how potential modulators influence the relationship between disease stage and cognitive performance. We analysed a total of 711 participants, including 106 patients with genetic FTD, 325 presymptomatic mutation carriers and 280 non-carriers healthy controls. Female participants showed a weaker association between disease stage and cognitive performance compared to males (P < 0.001), with difference becoming progressively more pronounced across symptomatic stages. Educational attainment exhibited a similar effect: individuals with higher education demonstrated an attenuated association compared to those with secondary or primary schooling (P < 0.001), with differences already detectable at prodromal disease stages. The effect of geographical region of residence was associated with education levels, but appeared to have an indirect and less strong influence. In summary, sex and educational attainment significantly affect the development and maintenance of cognitive reserve in individuals with genetic FTD. These findings underscore the importance of identifying disease-modifying interventions since the presymptomatic stages of the disease.

Recent proteomic studies have identified both established and novel proteins in genetic frontotemporal lobar degeneration (FTLD). However, it remains unclear at what point in the disease these proteins deviate from normal levels and how their trajectories relate to one another. Defining the temporal sequence of protein abnormalities could not only improve disease staging but also help identify biomarkers most sensitive to early disease activity in pathogenic variant carriers. We aimed to apply discriminative event-based modelling (DEBM) to characterize the progression profiles of proteins identified in a previous cross-sectional proteomic analysis. Building on our prior cross-sectional CSF proteomic analysis of genetic FTLD using a proximity extension assay, we selected the top ten significant proteins for each genetic group (C9orf72, GRN, MAPT). We then applied DEBM to characterize temporal dynamics of these proteins separately in each genetic group and evaluated their potential as early disease markers. To validate model performance, each individual was assigned a disease stage according to their position along the estimated disease timeline, based on protein levels and independent of clinical labels. Next, we assessed how well these stages discriminated symptomatic from presymptomatic carriers and non-carriers. Across all genetic groups, NfL consistently became abnormal before TPM3, although the earliest abnormal proteins differed between groups. In C9orf72, ELAVL4 is the first protein to become abnormal; in GRN SEMA3G and GRN, and in MAPT MMP-10. Estimated individual-level disease stage effectively distinguished symptomatic carriers from presymptomatic carriers and non-carriers, demonstrating high diagnostic accuracy (range AUC 0.74–0.98). Our data-driven findings provide a temporal ordering of multiple CSF proteins, highlighting potential early biomarkers and disease dynamics in different forms of genetic FTLD. In addition, the model’s accurate estimation of disease stages underscores the value of DEBM for patient stratification, offering a promising tool to support clinical trial design.

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.

Sporadic behavioural variant frontotemporal dementia (bvFTD) is often misdiagnosed as late-onset primary psychiatric disorder (PPD) due to overlapping symptoms and lack of biomarkers. We aimed to identify clinical features that distinguish sporadic bvFTD from PPD. Multi-centre baseline data were retrospectively retrieved and categorized into neuropsychological domains. Logistic regression models and receiver operating characteristic curves were conducted to determine discriminators. Data from 508 sporadic bvFTD and 152 PPD cases were included. Higher scores in cognitive screening [odds ratio (OR): 1.23], facial emotion processing (OR: 1.69), episodic memory (OR: 1.09), animal fluency (OR: 1.17), working memory (OR: 1.18), letter fluency (OR: 1.17) and depressive symptoms (OR: 7.41) were significantly associated with PPD (all Ps ≤ 0.010). Within a combined model, higher scores of letter fluency (OR: 1.47), cognitive screening (OR: 1.72) and lower attention (OR: 0.77) were significantly (all Ps ≤ 0.05) associated with PPD (area under the curve = 0.771). Neuropsychological measurements-letter fluency, cognitive screening and attention-can help distinguish sporadic bvFTD from late-onset PPD. Depressive symptoms and facial emotion processing emerged as potential discriminators, warranting further exploration.