Citations

Background: Cardiovascular health may be used for prevention of cerebral vascular disease; however, data on the association of cardiovascular health across midlife and late-life with late-life cerebral vascular disease are lacking. Our aim was to examine whether midlife or late-life cardiovascular health as well as changes of cardiovascular health within midlife and between midlife and late-life were associated with prevalence of magnetic resonance imaging markers of cerebral vascular disease at late-life. Methods: Prospective cohort study including 1638 participants from the Atherosclerosis Risk in Communities Study who took part in 2 visits at midlife (mean ages, 53 and 59 years), and a late-life visit (mean age, 76 years). A cardiovascular health Life’s Simple 7 score (range, 0–12/0–14, depending on diet availability) including 6 out of 7 items was calculated at each visit, with weight assigned to each item as poor (0), intermediate (1), or ideal (2). Participants underwent 3T brain magnetic resonance imaging scans in late-life visit. Outcomes were white matter hyperintensity volume, microbleeds, and lacunar, subcortical, and cortical infarcts at late-life. Linear and logistic regression models were used to assess the associations of cardiovascular health in midlife and late-life, and improvement of cardiovascular health within midlife, and from midlife to late-life with magnetic resonance imaging markers of cerebral vascular disease, adjusting for potential confounders. Results: A higher cardiovascular health in midlife, improvement of cardiovascular health within midlife, higher cardiovascular health at late-life, and improvement of cardiovascular health from midlife to late-life were associated with a lower prevalence of cerebral vascular disease markers. For example, improvement in cardiovascular health (per point) from midlife to late-life was associated with smaller white matter hyperintensity volume (β, −0.07 [95% CI, −0.10 to −0.04]) and lower odds of microbleeds (odds ratio, 0.93 [0.90–0.97]), lacunar (odds ratio, 0.93 [0.89–0.97]), subcortical (odds ratio, 0.93 [0.89–0.97]), and cortical infarcts (odds ratio, 0.92 [0.87–0.97]). Conclusions: Improving cardiovascular health within midlife and from midlife to late-life may prevent development of cerebral vascular disease.

AbstractBackgroundRecent evidence indicates that abnormal P‐wave parameters (PWPs)—ECG markers of atrial myopathy—are associated with incident dementia, independent of atrial fibrillation (AF) and clinical ischemic stroke. However, the mechanisms remain unclear and may include subclinical vascular brain injury. Hence, we evaluated the association of abnormal PWPs with brain MRI correlates of vascular brain injury in the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC‐NCS).MethodsARIC‐NCS participants who underwent 3T brain MRI scans in 2011–2013 were included. PWPs were measured from standard 12‐lead ECGs. Brain MRI outcomes included cortical infarcts, lacunar infarcts, cerebral microhemorrhages, brain volumes, and white matter disease (WMD) volume. We used weighted multivariable logistic and linear regression to evaluate the associations of abnormal PWPs with brain MRI outcomes.ResultsAmong 1715 participants (mean age, 76.1 years; 61% women; 29% Black), 797 (46%) had ≥1 abnormal PWP. After multivariable adjustment, including adjusting for prevalent AF, abnormal P‐wave terminal force in lead V1 (aPTFV1) and prolonged P‐wave duration (PPWD) were associated with increased odds of both cortical (OR 1.41; 95% CI, 1.14 to 1.74 and OR 1.30; 95% CI, 1.04 to 1.63, respectively) and lacunar infarcts (OR 1.36; 95% CI, 1.15 to 1.63 and OR 1.37; 95% CI, 1.15 to 1.65, respectively). Advanced interatrial block (aIAB) was associated with higher odds of subcortical microhemorrhage (OR 2.04; 95% CI, 1.36 to 3.06). Other than a significant association between aPTFV1 with lower parietal lobe volume, there were no other significant associations with brain or WMD volume.ConclusionIn this exploratory analysis of a US community‐based cohort, ECG surrogates of atrial myopathy are associated with a higher prevalence of brain infarcts and microhemorrhage, suggesting subclinical vascular brain injury as a possible mechanism underlying the association of atrial myopathy with dementia.

AbstractFrom a complex systems perspective, clinical syndromes emerging from neurodegenerative diseases are thought to result from multiscale interactions between aggregates of misfolded proteins and the disequilibrium of large-scale networks coordinating functional operations underpinning cognitive phenomena. Across all syndromic presentations of Alzheimer’s disease, age-related disruption of the default mode network is accelerated by amyloid deposition. Conversely, syndromic variability may reflect selective neurodegeneration of modular networks supporting specific cognitive abilities. In this study, we leveraged the breadth of the Human Connectome Project-Aging cohort of non-demented individuals (N = 724) as a normative cohort to assess the robustness of a biomarker of default mode network dysfunction in Alzheimer’s disease, the network failure quotient, across the aging spectrum. We then examined the capacity of the network failure quotient and focal markers of neurodegeneration to discriminate patients with amnestic (N = 8) or dysexecutive (N = 10) Alzheimer’s disease from the normative cohort at the patient level, as well as between Alzheimer’s disease phenotypes. Importantly, all participants and patients were scanned using the Human Connectome Project-Aging protocol, allowing for the acquisition of high-resolution structural imaging and longer resting-state connectivity acquisition time. Using a regression framework, we found that the network failure quotient related to age, global and focal cortical thickness, hippocampal volume, and cognition in the normative Human Connectome Project-Aging cohort, replicating previous results from the Mayo Clinic Study of Aging that used a different scanning protocol. Then, we used quantile curves and group-wise comparisons to show that the network failure quotient commonly distinguished both dysexecutive and amnestic Alzheimer’s disease patients from the normative cohort. In contrast, focal neurodegeneration markers were more phenotype-specific, where the neurodegeneration of parieto-frontal areas associated with dysexecutive Alzheimer’s disease, while the neurodegeneration of hippocampal and temporal areas associated with amnestic Alzheimer’s disease. Capitalizing on a large normative cohort and optimized imaging acquisition protocols, we highlight a biomarker of default mode network failure reflecting shared system-level pathophysiological mechanisms across aging and dysexecutive and amnestic Alzheimer’s disease and biomarkers of focal neurodegeneration reflecting distinct pathognomonic processes across the amnestic and dysexecutive Alzheimer’s disease phenotypes. These findings provide evidence that variability in inter-individual cognitive impairment in Alzheimer’s disease may relate to both modular network degeneration and default mode network disruption. These results provide important information to advance complex systems approaches to cognitive aging and degeneration, expand the armamentarium of biomarkers available to aid diagnosis, monitor progression and inform clinical trials.