Bradley F. Boeve

Early and accurate identification of neurodegenerative disorders has notable implications for treatment and quality of life. Whereas neuroimaging-based biomarkers can accurately identify neurodegenerative subtypes, EEG represents a low-cost alternative that could expand access to dementia care. Here, we investigated whether six data-driven EEG latent factors, derived by nonnegative tensor decomposition of clinical EEGs, differ systematically across FDG-PET-defined neurodegenerative phenotypes. In 455 patients with EEG and FDG-PET acquired within one year of each other, factor expression was compared across 14 diagnostic classes assigned by StateViewer, a validated artificial intelligence framework for FDG-PET interpretation. To separate disease-general severity from phenotype-specific topography, each factor was also regressed on a subject-level slowing index. Finally, we related the factors to regional FDG uptake and to neuropsychological performance (n = 98) and assessed their potential utility for single-subject classification. Four factors reflecting neurophysiological oscillations (posterior alpha, Rolandic beta, frontotemporal delta-theta and posterior theta-slow alpha) varied significantly across phenotypes, with attenuation of faster and augmentation of slower rhythms most pronounced in dementia with Lewy bodies (DLB), dysexecutive Alzheimer disease (AD) and posterior cortical atrophy, whereas factors dominated by eye-movement and muscle artifact showed no robust phenotypic association. Alpha and beta effects were largely attributable to overall slowing, whereas posterior theta-slow alpha became more phenotype-specific after adjustment (eta-squared 0.082 to 0.147), dissociating the Alzheimer disease spectrum from frontotemporal syndromes. The slowing index tracked with an FDG-PET pattern highly associated with DLB across the cohort, irrespective of assigned phenotype (r = 0.51, P < 0.001). Consistent with a model in which dementia phenotypes reflect altered hippocampal-neocortical oscillatory coupling (stochastic latent oscillatory diffusion), frontotemporal delta-theta tracked a limbocortical axis of metabolic pattern expression, rising with neocortical and falling with limbic-predominant involvement, independent of overall slowing and phenotype. Each factor mapped onto a distinct metabolic topography, with frontotemporal delta-theta resembling Alzheimer-type hypometabolism and posterior theta-slow alpha the medial occipital hypometabolism of DLB. In terms of neuropsychological performance, Rolandic beta was associated with executive functions, and frontotemporal delta-theta with memory, visuospatial and global performance. Using these four factors alone, an exploratory logistic regression classifier separated cognitively unimpaired participants from DLB, posterior cortical atrophy, typical AD, and dysexecutive AD (area under the curve > 0.8) but poorly discriminated frontotemporal dementia phenotypes canonically associated with 4-repeat tau. Thus, data-driven decomposition of clinical EEG separates oscillatory activity from artifact into factors that track metabolic phenotype, regional metabolism and cognition, capturing both overall slowing and phenotype-specific patterns. This work informs the further development of scalable, biology-informed EEG-based phenotyping of neurodegenerative disease.

Isolated rapid eye movement sleep behavior disorder represents a prodromal phase of α-synucleinopathy. Diffusion MRI provides in vivo markers of white matter microstructural properties, while white matter hyperintensities reflect cerebrovascular injury. However, their relative contributions to cognitive and clinical dysfunctions in patients with isolated rapid eye movement sleep behavior disorder remain unclear. We analysed 168 polysomnography-confirmed isolated rapid eye movement sleep behavior disorder participants from the North American Prodromal Synucleinopathy Consortium. Multi-shell diffusion MRI was used to derive metrics from diffusion tensor imaging (fractional anisotropy and mean diffusivity) and Neurite Orientation Dispersion and Density Imaging (tissue-weighted neurite density index and orientation dispersion index) across 39 white matter regions using a modified Johns Hopkins University white matter atlas. White matter hyperintensity burden was quantified from fluid-attenuated inversion recovery MRI. Using linear regression adjusted for age and sex, we compared white matter microstructure and hyperintensity burden between clinically impaired and unimpaired participants and examined associations with multiple cognitive and clinical domains, including global cognition, working memory, motor severity, manual dexterity, autonomic dysfunction, olfactory function, prodromal disease severity, and daytime sleepiness. False discovery rate correction was applied to account for multiple comparisons. In our sample (n=168), participants with clinical impairment (n=57) demonstrated higher white matter hyperintensity burden than unimpaired participants (n=111) and showed limited microstructural differences, including lower fractional anisotropy in the superior fronto-occipital fasciculus and inferior occipital white matter and higher orientation dispersion index in inferior occipital white matter. After adjusting for white matter hyperintensity burden, only increased occipital orientation dispersion index remained statistically significant. Diffusion metrics showed widespread associations with digit span forward performance and autonomic dysfunction. In contrast, increased white matter hyperintensity burden demonstrated broader associations with poorer Montreal Cognitive Assessment scores, poorer digit span forward performance, lower Purdue Pegboard performance, and higher Prodromal Synucleinopathy Rating Scale scores, indicating greater prodromal disease severity. Our findings highlight cerebrovascular white matter burden as an important correlate of clinical dysfunction in isolated rapid eye movement sleep behavior disorder and underscore the need to consider cerebrovascular lesions when interpreting diffusion imaging markers in prodromal synucleinopathy.

C9orf72 encodes a protein that is important for both typical neurodevelopment and homeostatic processes across the lifespan. Pathogenic C9orf72 repeat expansions constitute the most common genetic cause of frontotemporal lobar degeneration (FTLD). Collectively, preclinical models and clinical neuroimaging studies have observed smaller thalamic volumes in C9orf72 -associated FTLD, including in asymptomatic young adult C9orf72 repeat expansion carriers across 18 to 30 years old, supportive of potential neurodevelopmental origins. However, it is unknown whether asymptomatic young adult C9orf72 expansion carriers demonstrate volume differences in specific thalamic nuclei, as reported in older asymptomatic carriers and symptomatic patients; if so, normative transcriptomic patterns could reveal relevant neurodevelopmental and/or FTLD-related neurodegenerative processes. This study investigated volumetric MRI differences of the thalamic nuclei in asymptomatic young adult C9orf72 expansion carriers compared to non-carriers, and examined spatial associations with normative thalamic transcriptomics from 8 weeks post-conception through middle age. Young adult C9orf72 expansion carriers ( n =72) and non-carriers ( n =48) were enrolled in the Frontotemporal Dementia Prevention Initiative across Europe, Canada, and the USA (ages: 18-30 years; sex: 57% female). Spatial associations between young adult thalamic nuclei volumes and normative transcriptomics from the Allen Human Brain Atlas were examined using complementary data-driven and hypothesis-driven approaches. Spatial expression patterns of transcripts of interest were characterized across prenatal and postnatal neurodevelopment using BrainSpan data. Smaller volumes of the pulvinar, mediodorsal, and lateral nuclei were observed in young adult C9orf72 expansion carriers compared to non-carriers. These nuclei showed higher normative expression of transcripts involved concurrently in neurodevelopmental and C9orf72 -associated FTLD neurodegenerative processes (including lysosomal, autophagic, and small GTPase functions), and lower normative expression of CALB1 , a marker of prenatal human thalamic development. Normative expression of CALB2 (another human thalamic development marker) yielded positive correlations with C9orf72 across prenatal development to adulthood. These findings identify candidate transcripts that may provide insight into the molecular architecture leading to smaller thalamic nuclei volumes in C9orf72 -associated FTLD.

We developed a machine learning framework grounded in a computational model of brain function and FDG-PET imaging to predict Alzheimer’s disease (AD)-type tau across AD and related disorders (ADRD). The model was trained on 1088 research participants spanning normal aging and ADRD with FDG-PET and flortaucipir-PET (FTP-PET). Validation was conducted in: (1) a longitudinal subset of the training cohort ( n = 215), (2) Alzheimer’s Disease Neuroimaging Initiative ( n = 295), and (3) a heretogeneous clinical cohort ( n = 264; n = 28 with FTP-PET). Results showed that the model accurately predicted FTP-PET when applied at the participant-level ( R ² ~ 0.34-0.71). It performed well in clinical scenarios, including classification of low versus high tau stages (79–95% accuracy) and prediction of tau in a heterogeneous clinical cohort without FTP-PET. These findings advance the understanding of the relationship between neurodegeneration and AD-type tau and provide a framework for estimating AD-type tau across ADRD.

INTRODUCTION: Cognitive characterization is increasingly important for Alzheimer’s disease treatment decisions, highlighting the need for scalable cognitive assessment. We evaluated the diagnostic accuracy of a remote self-administered cognitive screening battery, Mayo Test Drive (MTD), across clinically and biologically defined groups. METHODS: In this prospectively designed study, 2,131 cognitively unimpaired (CU) and 118 cognitively impaired participants, including 96 with mild cognitive impairment and 22 with mild dementia (MCI/DEM), were recruited from observational cohort studies and completed MTD remotely (mean age=70 years, SD=12; 48% male; mean education=16 years, SD=2). Clinical diagnoses were determined by multidisciplinary consensus independently of MTD. Amyloid- and tau-PET were available for 1,224 participants. Logistic regression estimated associations between MTD and CU versus MCI/DEM, CU A-versus MCI/DEM A+, and A-T-versus A+T+. MTD diagnostic accuracy was compared with person-administered cognitive measures. Sensitivity and specificity across score types and comparison groups were examined. RESULTS: MTD showed excellent discrimination of CU versus MCI/DEM (AUC=.89; 95% CI=.87-.92), and discriminability remained high for CU versus MCI (AUC=.88; 95% CI=.85-.92). Discriminability was highest when comparing CU A- and MCI/DEM A+ groups (AUC=.95; 95% CI=.92-.97). MTD outperformed estimated MMSE (p=.02) and was comparable to Mayo-PACC (p=.71) for A-T-versus A+T+ discrimination (AUC=.76; 95% CI=.71-.81). Combining both raw score and normative score cutoffs helped balance sensitivity and specificity relative to use of either cutoff in isolation. A two-stage interpretation framework further improved sensitivity while maintaining clinically useful specificity and informed development of an interpretation guide. DISCUSSION: A remote self-administered digital cognitive assessment showed strong diagnostic accuracy for detecting MCI and mild dementia in a large, primarily population-based cohort. The remote, self-administered MTD composite also showed comparable performance to established in-person cognitive composites for differentiating amyloid and tau-defined biomarker groups. Remote self-administered digital cognitive assessment may complement existing cognitive evaluation approaches and support scalable cognitive characterization. Highlights: Remote self-administered cognitive assessment showed strong differentiation of cognitively unimpaired and cognitively impaired participants. Diagnostic accuracy improved when amyloid PET biomarker status was incorporated. Remote assessment demonstrated sensitivity to amyloid and tau PET-defined Alzheimer’s disease. Performance was comparable to established in-person composites and better than an in-person mental status screening measure. Digital cognitive screening may support scalable treatment and clinical trial workflows.

Recent evidence implicates somatic mutations in disease-associated genes across multiple neurodegenerative disorders, including the identification of two somatic TARDBP variants as a putative cause of frontotemporal lobar degeneration with TDP-43 pathology type C (FTLD-TDP type C). However, these findings remain anecdotal. We performed single-nucleus amplicon sequencing of 39,800 neurons from the superior temporal gyrus of sporadic FTLD-TDP type C patients (34,738 neurons, 52 individuals) and non-demented controls (5,062 neurons, 26 individuals) using the Mission Bio Tapestri platform and investigated somatic variants in TARDBP and other FTLD-TDP-associated genes in a case-control setting. We uncovered an extensive landscape of ultra-low-frequency (TARDBP . Rare somatic occurrences of known ALS/FTD-associated germline TARDBP variants, including p.N267S and p.M337V, were identified exclusively in patients. Among all targeted genes, TARDBP had the highest proportion of neurons harbouring a somatic variant, and this mutational burden was lower in individuals who died at an older age. Strikingly, the C-terminal domain of TDP-43, where most ALS/FTD germline pathogenic variants reside, exhibited a lower neuronal mutational burden than its other domains. This suggests that neurons harbouring damaging mutations may undergo progressive loss prior to autopsy, leaving only rare survivors at frequencies too low to detect by bulk or small-scale single-cell approaches. Together, our findings provide an unprecedented resolution into the somatic mutational landscape of post-mitotic neurons in FTLD-TDP type C and reveal a gene-specific layer of neuronal mosaicism that current single-cell WGS studies fail to detect.

Cognitive and behavioural dysfunction in frontotemporal dementia (FTD) evolves along a clinical continuum from a clinically silent stage of disease, through a prodromal period, often referred to as mild cognitive impairment (MCI) and/or mild behavioural impairment (MBI), and into a clinically manifest stage recognized by the syndromes of behavioural variant FTD and primary progressive aphasia (PPA). Similar cognitive and behavioural manifestations of varying severity are also encountered in individuals with amyotrophic lateral sclerosis (ALS). Notwithstanding this phenotypic overlap as well as a degree of shared genetic risk and underlying pathology, the approach to phenotypic characterization and description meaningfully differs between the ALS and FTD communities. The problem is particularly evident within the ALS community when describing impairment in the prodromal versus clinically manifest disease stages. Pertinent considerations include the nature of cognitive and behavioural assessments, the nosology used to describe symptoms identified, including those encompassed by the terms ‘behavioural’ and ‘neuropsychiatric’, the operationalized criteria that define prodromal syndromes and clinically manifest disease, and the extent to which these criteria rely on longitudinal (versus cross-sectional) data. A multi-stakeholder workshop, held in London, Ontario (12–14 May 2025), brought together neurologists, psychiatrists, neuropsychologists, neuropathologists, neuroscientists and neurogeneticists studying ALS and FTD, to promote interdisciplinary dialogue and to define a research agenda that might be jointly tackled to address these critical issues. A new nosology for classifying frontotemporal-related behavioural and neuropsychiatric dysfunction, which could be used to support empirical evidence collection, is proposed alongside a list of cognitive, language, behavioural and neuropsychiatric symptoms to be considered in the evaluation of individuals with ALS. Research priorities for each of the ALS and FTD communities, as well as initiatives that should be undertaken jointly, are highlighted. The long-term goal is to harmonize approaches to phenotypic characterization, the nosology used to describe symptoms and the criteria used to define landmark stages along the clinical continua of the motor neuron and frontotemporal axes, irrespective of clinical stage.

Determining the optimal timing of disease-modifying therapies for neurodegenerative disorders will necessitate identification of when the underlying pathobiological process becomes active, well in advance of the point at which clinical manifestations appear. Phenoconversion, the emergence of clinically manifest syndromes, may be preceded by years to decades of silent pathobiological activity that can only be mapped by an array of biomarkers. Amyotrophic lateral sclerosis (ALS) and frontotemporal dementias (FTD), traditionally identified as distinct clinical syndromes, are increasingly recognized to exist along a spectrum of clinical syndromes with shared genetic risk and underlying pathology. This clinicopathological spectrum is underpinned by cytoplasmic aggregation of TAR DNA-binding protein 43 (TDP-43) as the common neuropathological hallmark. In contrast, the majority of neuropathologically-defined frontotemporal lobar degeneration (FTLD) is associated with alterations in either TDP-43 metabolism (FTLD-TDP) or of the microtubule associated protein tau (FTLD-tau), with a smaller percentage associated with either autosomal dominant genetic mutations or impairments in the ubiquitin proteasome system. As the field of neurodegenerative disorders increasingly shifts towards the frameworks of a pathobiological definition of disease, there is a growing imperative to develop biomarkers that reflect the varied pathobiologies that underly these disorders, and to determine the sensitivity of such biomarkers to detect the presence of these pathobiologies before phenoconversion. To that end, an international workshop was convened in London, Canada in 2025 to review the evidence for existing or evolving biomarkers suitable for (i) the detection of either ALS or FTD pathobiology prior to phenoconversion and/or (ii) predict phenoconversion in at-risk individuals. Such biomarkers might be conceptualized as ‘biotypic biomarkers’, capturing their ability to describe an underlying pathophysiology whilst being agnostic to the emergent clinical manifestations. While currently no single biotypic marker can predict the emergence of ALS, FTD or their intersection, a multimodal approach to developing a biotypic biomarker profile holds promise for the detection of relevant pathobiological processes. The strength of such an approach would be augmented by also addressing issues of resiliency/susceptibility both in terms of genetic risk susceptibility profiles and developing sensitive biomarkers of genomic and cellular ageing. By including such non-traditional markers of disease, a more robust picture of not only the degenerative process but also of those factors that might potentially mitigate or drive a heightened probability of disease can be derived.

Background and ObjectivesPlasma growth differentiation factor 15 (GDF15), a TGFbeta family cytokine, has been robustly identified from proteomics discovery work as linked to adverse brain aging; im...