Lowe, Val J.

Stroke is a leading cause of the adult disability epidemic in the United States, with a major contribution from poststroke cognitive impairment and dementia (PSCID), the rates of which are disproportionally high among the health disparity populations. Despite the PSCID’s overwhelming impact on public health, a knowledge gap exists with regard to the complex interaction between the acute stroke event and highly prevalent preexisting brain pathology related to cerebrovascular and Alzheimer disease or related dementia. Understanding the factors that modulate PSCID risk in relation to index stroke event is critically important for developing personalized prognostication of PSCID, targeted interventions to prevent it, and for informing future clinical trial design. The DISCOVERY study (Determinants of Incident Stroke Cognitive Outcomes and Vascular Effects on Recovery), a collaborative network of thirty clinical performance clinical sites with access to acute stroke populations and the expertise and capacity for systematic assessment of PSCID will address this critical challenge. DISCOVERY is a prospective, multicenter, observational, nested-cohort study of 8000 nondemented ischemic and hemorrhagic stroke patients enrolled at the time of index stroke and followed for a minimum of 2 years, with serial cognitive evaluations and assessments of functional outcome, with subsets undergoing research magnetic resonance imaging and positron emission tomography and comprehensive genetic/genomic and fluid biomarker testing. The overall scientific objective of this study is to elucidate mechanisms of brain resilience and susceptibility to PSCID in diverse US populations based on complex interplay between life-course exposure to multiple vascular risk factors, preexisting burden of microvascular and neurodegenerative pathology, the effect of strategic acute stroke lesions, and the mediating effect of genomic and epigenomic variation.

Abstract Introduction Measurement of amyloid beta (Aβ40 and Aβ42) and tau (phosphorylated tau [p‐tau] and total tau [t‐tau]) in cerebrospinal fluid (CSF) can be utilized to differentiate clinical and preclinical Alzheimer's disease dementia (AD) from other neurodegenerative processes. Methods CSF biomarkers were measured in 150 participants from the Mayo Clinic Study of Aging and the Alzheimer's Disease Research Center. P‐tau/Aβ42 (Roche Elecsys, Fujirebio LUMIPULSE) and Aβ42/40 (Fujirebio LUMIPULSE) ratios were compared to one another and to amyloid positron emission tomography (PET) classification. Results Strong correlation was observed between LUMIPULSE p‐tau/Aβ42 and Aβ42/40, as well as Elecsys and LUMIPULSE p‐tau/Aβ42 and Aβ42/40 (Spearman's ρ = –0.827, –0.858, and 0.960, respectively). Concordance between LUMIPULSE p‐tau/Aβ42 and Aβ42/40 was 96% and between Elecsys p‐tau/Aβ42 and both LUMIPULSE ratios was 97%. All ratios had > 94% overall, positive, and negative percent agreement with amyloid PET classification. Discussion These data suggest that p‐tau/Aβ42 and Aβ42/40 ratios provide similar clinical information in the assessment of amyloid pathology.

Background and Purpose: Cerebral microbleeds (CMBs) are represented by small areas of hemosiderin deposition, detected on brain magnetic resonance imaging (MRI), and found in ≈23% of the cognitively normal population over age of 60 years. CMBs predict risk of hemorrhagic and ischemic stroke. They correlate with increased cardiovascular mortality. In this article, we sought to determine in a population-based study whether antithrombotic medications correlate with CMBs and, if present, whether the association was direct or mediated by another variable. Methods: The study consisted of 1253 participants from the population-based Mayo Clinic Study of Aging who underwent T2* gradient-recalled echo magnetic resonance imaging. We tested the relationship between antithrombotic medications and CMB presence and location, using multivariable logistic-regression models. Ordinal logistic models tested the relationship between antithrombotics and CMB frequency. Using structural equation models, we assessed the effect of antithrombotic medications on presence/absence of CMBs and count of CMBs in the CMB-positive group, after considering the effects of age, sex, vascular risk factors, amyloid load by positron emission tomography, and apoE. Results: Two hundred ninety-five participants (26.3%) had CMBs. Among 678 participants taking only antiplatelet medications, 185 (27.3%) had CMBs. Among 95 participants taking only an anticoagulant, 43 (45.3%) had CMBs. Among 44 participants taking an anticoagulant and antiplatelet therapy, 21 (48.8%) had CMBs. Anticoagulants correlated with the presence and frequency of CMBs, whereas antiplatelet agents were not. Structural equation models showed that predictors for presence/absence of CMBs included older age at magnetic resonance imaging, male sex, and anticoagulant use. Predictors of CMB count in the CMB-positive group were male sex and amyloid load. Conclusions: Anticoagulant use correlated with presence of CMBs in the general population. Amyloid positron emission tomography correlated with the count of CMBs in the CMB-positive group.

Abstract While cerebrovascular disease can be observed in vivo using MRI, the multiplicity and heterogeneity in the mechanisms of cerebrovascular damage impede accounting for these measures in ageing and dementia studies. Our primary goal was to investigate the key sources of variability across MRI markers of cerebrovascular disease and evaluate their impact in comparison to amyloidosis on cognitive decline in a population-based sample. Our secondary goal was to evaluate the prognostic utility of a cerebrovascular summary measure from all markers. We included both visible lesions seen on MRI (white matter hyperintensities, cortical and subcortical infarctions, lobar and deep microbleeds) and early white matter damage due to systemic vascular health using diffusion changes in the genu of the corpus callosum. We identified 1089 individuals aged ≥60 years with concurrent amyloid-PET and MRI scans from the population-based Mayo Clinic Study of Aging. We divided these into discovery and validation datasets. Using the discovery dataset, we conducted principal component analyses and ascertained the main sources of variability in cerebrovascular disease markers. Using linear regression and mixed effect models, we evaluated the utility of these principal components and combinations of these components for the prediction of cognitive performance along with amyloidosis. Our main findings were (i) there were three primary sources of variability among the CVD measures—white matter changes are driven by white matter hyperintensities and diffusion changes; number of microbleeds (lobar and deep); and number of infarctions (cortical and subcortical); (ii) Components of white matter changes and microbleeds but not infarctions significantly predicted cognition trajectories in all domains with greater contributions from white matter; and (iii) The summary vascular score explained 3–5% of variability in baseline global cognition in comparison to 3–6% variability explained by amyloidosis. Across all cognitive domains, the vascular summary score had the least impact on memory performance (∼1%). Though there is mechanistic heterogeneity in the cerebrovascular disease markers measured on MRI, these changes can be grouped into three components and together explain variability in cognitive performance equivalent to the impact of amyloidosis on cognition. White matter changes represent dynamic ongoing damage, predicts future cognitive decline across all domains and diffusion measurements help capture white matter damage due to systemic vascular changes. Therefore, measuring and accounting for white matter changes using diffusion MRI and white matter hyperintensities along with microbleeds will allow us to capture vascular contributions to cognitive impairment and dementia.

AbstractNeurofibrillary tangles, one of the neuropathologic hallmarks of Alzheimer's disease, have a dynamic lifespan of maturity that associates with progressive neuronal dysfunction and cognitive deficits. As neurofibrillary tangles mature, the biology of the neuron undergoes extensive changes that may impact biomarker recognition and therapeutic targeting. Neurofibrillary tangle maturity encompasses three levels: pretangles, mature tangles, and ghost tangles. In this review, we detail distinct and overlapping characteristics observed in the human brain regarding morphologic changes the neuron undergoes, conversion from intracellular to extracellular space, tau immunostaining patterns, and tau isoform expression changes across the lifespan of the neurofibrillary tangle. Post‐translational modifications of tau such as phosphorylation, ubiquitination, conformational events, and truncations are discussed to contextualize tau immunostaining patterns. We summarize accumulated and emerging knowledge of neurofibrillary tangle maturity, discuss the current tools used to interpret the dynamic nature in the postmortem brain, and consider implications for cognitive dysfunction and tau biomarkers.

BackgroundTo operationalize the National Institute on Aging – Alzheimer's Association (NIA‐AA) Research Framework for Alzheimer's Disease 6‐stage continuum of clinical progression for persons with abnormal amyloid.MethodsThe Mayo Clinic Study of Aging is a population‐based longitudinal study of aging and cognitive impairment in Olmsted County, Minnesota. We evaluated persons without dementia having 3 consecutive clinical visits. Measures for cross‐sectional categories included objective cognitive impairment (OBJ) and function (FXN). Measures for change included subjective cognitive impairment (SCD), objective cognitive change (ΔOBJ), and new onset of neurobehavioral symptoms (ΔNBS). We calculated frequencies of the stages using different cutoff points and assessed stability of the stages over 15 months.ResultsAmong 243 abnormal amyloid participants, the frequencies of the stages varied with age: 66 to 90% were classified as stage 1 at age 50 but at age 80, 24 to 36% were stage 1, 32 to 47% were stage 2, 18 to 27% were stage 3, 1 to 3% were stage 4 to 6, and 3 to 9% were indeterminate. Most stage 2 participants were classified as stage 2 because of abnormal ΔOBJ only (44–59%), whereas 11 to 21% had SCD only, and 9 to 13% had ΔNBS only. Short‐term stability varied by stage and OBJ cutoff points but the most notable changes were seen in stage 2 with 38 to 63% remaining stable, 4 to 13% worsening, and 24 to 41% improving (moving to stage 1).InterpretationThe frequency of the stages varied by age and the precise membership fluctuated by the parameters used to define the stages. The staging framework may require revisions before it can be adopted for clinical trials. ANN NEUROL 2021;89:1145–1156

Background: The identification of blood-borne biomarkers for the diagnosis and prognosis of Alzheimer’s disease and related dementias is more feasible at the population level than obtaining cerebrospinal fluid or neuroimaging markers. Objective: This study determined the association of blood microvesicles, derived from cells of the neurovascular unit, with brain amyloid-β deposition in menopausal women. Methods: A subset of women from the Kronos Early Estrogen Prevention Study underwent brain amyloid-β positron emission tomography three years following cessation of study treatment with placebo (PL, n = 29), transdermal 17β-estradiol (tE2; n = 21), or oral conjugated equine estrogen (oCEE; n = 17). Isolated peripheral venous blood microvesicles were analyzed by digital flow cytometry using fluorophore conjugated antibodies directed toward total tau, amyloid-β 1–42 (Aβ1–42), neuron specific class III β-tubulin (Tuj1), microglia ionized calcium -binding adaptor molecule 1(Iba1), glial fibrillary acid protein (GFAP), and low density lipoprotein receptor-related protein1 (LRP1). Principal components analysis reduced the dimensionality of these selected six markers to two principal components (PCs). Proportional odds ordinal logistic regression analysis was used with amyloid-β deposition regressed on these PCs. Results: Only the number of microvesicles positive for Aβ1–42 differed statistically among prior treatment groups (median [IQR]: 6.06 [2.11, 12.55] in PL; 2.49 [0.73, 3.59] in tE2; and 4.96 [0.83, 10.31] in oCEE; p = 0.032). The joint association between the 2 PCs and brain amyloid-β deposition was significant (p = 0.045). Conclusion: Six selected markers expressing peripheral blood microvesicles derived from cells of the neurovascular unit, when summarized into two principal components, were associated with brain amyloid-β deposition.

Abstract Deterioration in white-matter health plays a role in cognitive ageing. Our goal was to discern heterogeneity of white-matter tract vulnerability in ageing using longitudinal imaging data (two to five imaging and cognitive assessments per participant) from a population-based sample of 553 elderly participants (age ≥60 years). We found that different clusters (healthy white matter, fast white-matter decliners and intermediate white-matter group) were heterogeneous in the spatial distribution of white-matter integrity, systemic health and cognitive trajectories. White-matter health of specific tracts (genu of corpus callosum, posterior corona radiata and anterior internal capsule) informed about cluster assignments. Not surprisingly, brain amyloidosis was not significantly different between clusters. Clusters had differential white-matter tract vulnerability to ageing (commissural fibres > association/brainstem fibres). Identification of vulnerable white-matter tracts is a valuable approach to assessing risk for cognitive decline.