Corriveau-Lecavalier, Nick

Abstract Introduction Remote cognitive assessments offer an accessible, scalable way to support clinical characterization and longitudinal monitoring of cognition. This study evaluates the feasibility of implementing Mayo Test Drive (MTD), a remote, self-administered digital cognitive assessment, within a specialized clinic focused on eligibility assessments for anti-amyloid therapies for Alzheimer’s disease (AD). Method Two-hundred and nine ( N =209) patients (M age =71.2, 53% female) were evaluated through the Mayo Clinic Rochester Alzheimer’s Disease Treatment Clinic (ADTC) and had the opportunity to complete MTD, either as a remote, patient-initiated session through a patient-facing healthcare portal or during an in-clinic neuropsychological evaluation. Results Clinical diagnoses included 55.2% mild cognitive impairment (MCI), 31.0% mild dementia, and 11.6% moderate dementia, in addition to 2.2% cognitively unimpaired (CU), as determined by neurology consensus at a multidisciplinary case conference. Among those who initiated MTD ( n =197/209), 97.5% completed a session (70.6% remotely, 26.9% in clinic). Completion rates were high across diagnostic groups and did not significantly differ by clinical severity ( p =.12): CU (100%), MCI (99.1%), mild dementia (97.0%), and moderate dementia (89.5%). Remote completion rates overall were high (97.9%). Among completers, administration setting (remote vs. in-clinic) did not significantly differ by clinical stage, χ²(3)=2.37, p =.49. Reasons for non-initiation included not receiving or opening portal messages and other/unknown factors. Discussion Remote digital cognitive assessment is feasible within the context of clinic eligibility evaluations for AD therapies. The high completion rates of MTD across clinical impairment levels in this setting support development of paths for broader use in cognitive characterization in AD care.

Abstract Patients with atypical variants of Alzheimer's disease (AD) often present at a younger age with predominantly non‐amnestic impairments and a more aggressive disease course. Historically, individuals with atypical presentations have not been included in large‐scale clinical trials, which typically focus on late‐onset, sporadic amnestic‐predominant AD. Consequently, treatment options and research efforts specific to atypical AD remain limited. The emergence of amyloid‐targeting therapies that slow disease progression underscores these challenges, as evidence supporting their efficacy in early‐onset amnestic and non‐amnestic AD variants is scarce. This perspective article argues that atypical AD represents an excellent disease model for clinical trials and proposes strategies to address critical gaps in clinical trial design for this population. Key considerations include optimizing participant selection approaches, establishing syndrome‐specific or surrogate biological and clinical endpoints, and fostering advocacy to enhance early and accurate diagnosis, equitable representation, and outcomes for these populations.

Abstract Alzheimer’s disease (AD) emerges from multi-scale interactions between molecular pathology and disruptions in large-scale brain network dynamics. Understanding how these processes co-evolve and relate to disease stages is essential for advancing complex systems models of aging and AD, and for developing system-informed interventions. However, progress has been limited by a lack of large-scale longitudinal data. To address this, we examined the longitudinal relationship between subsystems of the default mode network (DMN) (posterior DMN, ventral DMN, anterior dorsal DMN) using task-free functional MRI (fMRI) and amyloid positron emission tomography (PET) imaging in a large longitudinal cohort spanning the clinico-biological spectrum of AD (n = 1,451; 2,763 time points) using mixed-effect models. We also assessed whether patterns of DMN connectivity predicted conversion to amyloid positivity, mild cognitive impairment (MCI), and dementia using Cox proportional hazards models. Our findings reveal a dynamic interplay between amyloid accumulation and connectivity within and between DMN subsystems, with both hyper- and hypoconnectivity emerging across DMN subsystems in association with increasing amyloid burden. Importantly, survival models showed that DMN connectivity patterns predicted conversion to critical stages of the disease, including not only conversion to MCI and dementia, but also conversion to amyloid positivity in otherwise clinically unimpaired individuals who were amyloid negative at baseline. These associations were independent of age, APOE4 status, sex, education, and in-scanner motion. These results support a model in which breakdowns in tightly regulated feedback loops governing DMN physiology represent a core systems-level pathophysiology of AD. Notably, this functional dyshomeostasis precedes detectable amyloidosis on imaging. Future studies should focus on the development of robust biomarkers of brain function that can be applied at the individual level, which could in turn help support the development of therapeutic approaches targeting system-level pathophysiology.

Objective To determine the clinical features that identify patients with suspected rapidly progressive dementia (RPD) who will develop RPD. Methods Patients with suspected RPD were enrolled and followed at Mayo Clinic (Jacksonville, FL; January 2020 to October 2023) and Washington University (Saint Louis, MO; June 2016 to December 2019). Two dementia specialists independently reviewed clinical data and assigned diagnoses. Patients were diagnosed with RPD if they developed dementia within 1 year or incapacitation within 2 years of symptom onset. The associations between clinical features and causes and outcomes were explored via univariate and multivariate comparisons. Results Of 248 patients with suspected RPD, 185 (74.6%) met criteria for RPD. Patients with RPD were older (62.6 ± 14.5 vs 55.2 ± 18.1 years; p < 0.001), and more frequently diagnosed with Alzheimer's disease or related dementias (OR 3.13, 95% CI 1.40, 7.31) or Creutzfeldt–Jakob disease (OR 4.67, 95% CI 1.38, 15.75). Visual agnosia (15/183; 8.2%), substantial brain atrophy (27/182; 14.8%), and periodic epileptiform discharges (11/151; 7.3%) were exclusively detected in patients with RPD. After controlling for age, intensive care unit admission (OR 4.77, 95% CI 1.61, 14.12), lack of seizures (OR 2.47, 95% CI 1.15, 5.31), abnormal brain magnetic resonance imaging (OR 2.01, 95% CI 0.997, 4.05), and cerebrospinal fluid white blood cell count ≤5 cells/mm 3 (OR 3.30, 95% CI 1.60, 6.82) were also independently associated with RPD. Patients with RPD were more likely to die or develop severe dementia (mean time to outcome, 36.1 months; 95% CI 31.2–41.0). Interpretation Selected clinical features may identify patients with suspected RPD who are likely to continue to decline. Early recognition of these features may improve diagnostic accuracy and inform prognosis. ANN NEUROL 2025;98:764–776

Abstract Limbic predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC) is highly prevalent in late life and a common co‐pathology with Alzheimer's disease neuropathologic change (ADNC). LATE‐NC is a slowly progressive, amnestic clinical syndrome. Alternatively, when present with ADNC, LATE‐NC is associated with a more rapid course. With the emergence of anti‐amyloid therapeutics, discrimination of LATE‐NC from ADNC is critical and will lead to greater clinical recognition of amnestic patients without ADNC. Furthermore, co‐pathology with LATE‐NC may influence outcomes of these therapeutics. Thus there is a need to identify patients during life with likely LATE‐NC. We propose criteria for clinical diagnosis of LATE as an initial framework for further validation. In the context of progressive memory loss and substantial hippocampal atrophy, criteria are laid out for probable (amyloid negative) or possible LATE (amyloid biomarkers are unavailable or when amyloid is present, but hippocampal neurodegeneration is out of proportion to expected pure ADNC). Highlights Limbic‐predominant age‐related TDP‐43 encephalopathy (LATE) is a highly prevalent driver of neuropathologic memory loss in late life. LATE neuropathologic change (LATE‐NC) is a common co‐pathology with Alzheimer's disease neuropathologic change (ADNC) and may influence outcomes with emerging disease‐modifying medicines. We provide initial clinical criteria for diagnosing LATE during life either when LATE‐NC is the likely primary driver of symptoms or when observed in conjunction with AD. Definitions of possible and probable LATE are provided.

AbstractObjectivePrion disease classically presents with rapidly progressive dementia, leading to death within months of diagnosis. Advances in diagnostic testing have improved recognition of patients with atypical presentations and protracted disease courses, raising key questions surrounding the relationship between patterns of neurodegeneration and survival. We assessed the contribution of fluorodeoxyglucose (FDG‐PET) imaging for this purpose.MethodsFDG‐PET were performed in 40 clinic patients with prion disease. FDG‐PET images were projected onto latent factors generated in an external dataset to yield patient‐specific eigenvalues. Eigenvalues were input into a clustering algorithm to generate data‐driven clusters, which were compared by survival time.ResultsMedian age at FDG‐PET was 65.3 years (range 23–85). Median time from FDG‐PET to death was 3.7 months (range 0.3–19.0). Four data‐driven clusters were generated, termed “Neocortical” (n = 7), “Transitional” (n = 12), “Temporo‐parietal” (n = 13), and “Deep nuclei” (n = 6). Deep nuclei and transitional clusters had a shorter survival time than the neocortical cluster. Subsequent analyses suggested that this difference was driven by greater hypometabolism of deep nuclei relative to neocortical areas. FDG‐PET‐patterns were not associated with demographic (age and sex) or clinical (CSF total‐tau, 14‐3‐3) variables.InterpretationGreater hypometabolism within deep nuclei relative to neocortical areas associated with more rapid decline in patients with prion disease and vice versa. FDG‐PET informs large‐scale network physiology and may inform the relationship between spreading pathology and survival in patients with prion disease. Future studies should consider whether FDG‐PET may enrich multimodal prion disease prognostication models.

Abstract Neuronal dysfunction in specific brain regions or across distributed brain networks is a known feature of Alzheimer’s disease. An often reported finding in the early stage of the disease is the presence of increased functional MRI (fMRI) blood oxygenation level-dependent signal under task conditions relative to cognitively normal controls, a phenomenon known as ‘hyperactivation’. However, research in the past decades yielded complex, sometimes conflicting results. The magnitude and topology of fMRI hyperactivation patterns have been found to vary across the preclinical and clinical spectrum of Alzheimer’s disease, including concomitant ‘hypoactivation’ in some cases. These incongruences are likely due to a range of factors, including the disease stage at which the cohort is examined, the brain areas or networks studied and the fMRI paradigm utilized to evoke these functional abnormalities. Additionally, a perennial question pertains to the nature of hyperactivation in the context of Alzheimer’s disease. Some propose it reflects compensatory mechanisms to sustain cognitive performance, while others suggest it is linked to the pathological disruption of a highly regulated homeostatic cycle that contributes to, or even drives, disease progression. Providing a coherent narrative for these empirical and conceptual discrepancies is paramount to develop disease models, understand the synergy between hyperactivation and the Alzheimer’s disease pathological cascade and tailor effective interventions. We first provide a comprehensive overview of functional brain changes spanning the course from normal ageing to the clinical spectrum of Alzheimer’s disease. We then highlight evidence supporting a close relationship between fMRI hyperactivation and in vivo markers of Alzheimer’s pathology. We primarily focus on task-based fMRI studies in humans, but also consider studies using different functional imaging techniques and animal models. We then discuss the potential mechanisms underlying hyperactivation in the context of Alzheimer’s disease and provide a testable framework bridging hyperactivation, ageing, cognition and the Alzheimer’s disease pathological cascade. We conclude with a discussion of future challenges and opportunities to advance our understanding of the fundamental disease mechanisms of Alzheimer’s disease, and the promising development of therapeutic interventions incorporating or aimed at hyperactivation and large-scale functional systems.