Citations

AbstractIntroductionWe examined the temporal sequence of the core features in probable dementia with Lewy bodies (DLB).MethodsIn 488 patients with probable DLB, the onset of each core feature and time to diagnosis was determined for men and women, and a pathologic subgroup (n = 209).ResultsREM sleep behavior disorder (RBD) developed before the other core features in men and women. Men were more likely to have RBD and were diagnosed with probable DLB earlier than women. Visual hallucinations developed after the other core features in men, but in women, they appeared earlier and concurrently with fluctuations and parkinsonism. Women were older and more cognitively impaired at first visit, were less likely to have RBD, more likely to be diagnosed with probable DLB later than men, and more likely to have neocortical tangles.DiscussionAn earlier latency to probable DLB was associated with men, RBD, and Lewy body disease without neocortical tangles.

We present the case of a cognitively unimpaired 77-year-old man with elevated, asymmetric, and longitudinally increasing Flortaucipir tau PET despite normal (visually negative) amyloid PET. His atypical tau PET signal persisted and globally increased in a follow-up scan five years later. Across eight years of observations, temporoparietal atrophy was observed consistent with tau PET patterns, but he retained the cognitively unimpaired classification. Altogether, his atypical tau PET signal is not explained by any known risk factors or alternative pathologies, and other imaging findings were not remarkable. He remains enrolled for further observation.

Longitudinal observational cohort studies are being conducted worldwide to understand cognition, biomarkers, and the health of the aging population better. Cross-cohort comparisons and networks of registries in Alzheimer’s disease (AD) foster scientific exchange, generate insights, and contribute to the evolving clinical science in AD. A scientific working group was convened with invited investigators from established cohort studies in AD, in order to form a research collaboration network as a resource to address important research questions. The Connecting Cohorts to Diminish Alzheimer’s Disease (CONCORD-AD) collaboration network was created to bring together global resources and expertise, to generate insights and improve understanding of the natural history of AD, to inform design of clinical trials in all disease stages, and to plan for optimal patient access to disease-modifying therapies once they become available. The network brings together expertise and data insights from 7 cohorts across Australia, Europe, and North America. Notably, the network includes populations recruited through memory clinics as well as population-based cohorts, representing observations from individuals across the AD spectrum. This report aims to introduce the CONCORD-AD network, providing an overview of the cohorts involved, reporting the common assessments used, and describing the key characteristics of the cohort populations. Cohort study designs and baseline population characteristics are compared, and available cognitive, functional, and neuropsychiatric symptom data, as well as the frequency of biomarker assessments, are summarized. Finally, the challenges and opportunities of cross-cohort studies in AD are discussed.

Abstract Significant progress has been made in understanding the pre-symptomatic phase of amyotrophic lateral sclerosis. While much is still unknown, advances in other neurodegenerative diseases offer valuable insights. Indeed, it is increasingly clear that the well-recognized clinical syndromes of Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, spinal muscular atrophy and frontotemporal dementia are also each preceded by a pre-symptomatic or prodromal period of varying duration, during which the underlying disease process unfolds, with associated compensatory changes and loss of inherent system redundancy. Key insights from these diseases highlight opportunities for discovery in amyotrophic lateral sclerosis. The development of biomarkers reflecting amyloid and tau has led to a shift in defining Alzheimer’s disease based on inferred underlying histopathology. Parkinson’s disease is unique among neurodegenerative diseases in the number and diversity of non-genetic biomarkers of pre-symptomatic disease, most notably REM sleep behaviour disorder. Huntington’s disease benefits from an ability to predict the likely timing of clinically manifest disease based on age and CAG-repeat length alongside reliable neuroimaging markers of atrophy. Spinal muscular atrophy clinical trials have highlighted the transformational value of early therapeutic intervention, and studies in frontotemporal dementia illustrate the differential role of biomarkers based on genotype. Similar advances in amyotrophic lateral sclerosis would transform our understanding of key events in pathogenesis, thereby dramatically accelerating progress towards disease prevention. Deciphering the biology of pre-symptomatic amyotrophic lateral sclerosis relies on a clear conceptual framework for defining the earliest stages of disease. Clinically manifest amyotrophic lateral sclerosis may emerge abruptly, especially among those who harbour genetic mutations associated with rapidly progressive amyotrophic lateral sclerosis. However, the disease may also evolve more gradually, revealing a prodromal period of mild motor impairment preceding phenoconversion to clinically manifest disease. Similarly, cognitive and behavioural impairment, when present, may emerge gradually, evolving through a prodromal period of mild cognitive impairment or mild behavioural impairment before progression to amyotrophic lateral sclerosis. Biomarkers are critically important to studying pre-symptomatic amyotrophic lateral sclerosis and essential to efforts to intervene therapeutically before clinically manifest disease emerges. The use of non-genetic biomarkers, however, presents challenges related to counselling, informed consent, communication of results and limited protections afforded by existing legislation. Experiences from pre-symptomatic genetic testing and counselling, and the legal protections against discrimination based on genetic data, may serve as a guide. Building on what we have learned—more broadly from other pre-symptomatic neurodegenerative diseases and specifically from amyotrophic lateral sclerosis gene mutation carriers—we present a road map to early intervention, and perhaps even disease prevention, for all forms of amyotrophic lateral sclerosis.

Abstract Introduction Amyloid beta (Aβ), tau, and neurodegeneration jointly with the Alzheimer's disease (AD) risk factors affect the severity of clinical symptoms and disease progression. Methods Within 248 Aβ‐positive elderly with and without cognitive impairment and dementia, partial least squares structural equation pathway modeling was used to assess the direct and indirect effects of imaging biomarkers (global Aβ‐positron emission tomography [PET] uptake, regional tau‐PET uptake, and regional magnetic resonance imaging–based atrophy) and risk‐factors (age, sex, education, apolipoprotein E [ APOE ], and white‐matter lesions) on cross‐sectional cognitive impairment and longitudinal cognitive decline. Results Sixteen percent of variance in cross‐sectional cognitive impairment was accounted for by Aβ, 46% to 47% by tau, and 25% to 29% by atrophy, although 53% to 58% of total variance in cognitive impairment was explained by incorporating mediated and direct effects of AD risk factors. The Aβ–tau–atrophy pathway accounted for 50% to 56% of variance in longitudinal cognitive decline while Aβ, tau, and atrophy independently explained 16%, 46% to 47%, and 25% to 29% of the variance, respectively. Discussion These findings emphasize that treatments that remove Aβ and completely stop downstream effects on tau and neurodegeneration would only be partially effective in slowing of cognitive decline or reversing cognitive impairment.

A rare APOE variant APOE3 -Jac reduces self-aggregation and promotes healthy brain aging.

AbstractIntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020.MethodsWe identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion.ResultsDisease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity.DiscussionADNI has had a profound impact in improving clinical trials for AD.

AbstractIntroductionBlood‐based biomarkers of amyloid pathology and neurodegeneration are entering clinical use. It is critical to understand what factors affect the levels of these markers.MethodsPlasma markers (Aβ42, Aβ40, NfL, T‐tau, Aβ42/40 ratio) were measured on the Quanterix Simoa HD‐1 analyzer for 996 Mayo Clinic Study of Aging (MCSA) participants, aged 51 to 95 years. All other data were collected during in‐person MCSA visits or abstracted from the medical record.ResultsAmong cognitively unimpaired (CU) participants, all plasma markers correlated with age. Linear regression models revealed multiple relationships. For example, higher Charlson Comorbidity Index and chronic kidney disease were associated with higher levels of all biomarkers. Some relationships differed between mild cognitive impairment and dementia participants.DiscussionMultiple variables affect plasma biomarkers of amyloid pathology and neurodegeneration among CU in the general population. Incorporating this information is critical for accurate interpretation of the biomarker levels and for the development of reference ranges.