Vemuri, Prashanthi

Abstract Background Hospitalization can impair physical and functional status of older adults, but it is unclear whether these deficits are transient or chronic. This study determined the association between hospitalization of older adults and changes in long-term longitudinal trajectories of 2 measures of physical and functional status: gait speed (GS) and instrumental activities of daily living measured with Functional Activities Questionnaire (FAQ). Method Linear mixed-effects models assessed the association between hospitalization (nonelective vs elective, and surgical vs medical) and outcomes of GS and FAQ score in participants (older than 60 years) enrolled in the Mayo Clinic Study of Aging who had longitudinal assessments. Results Of 4902 participants, 1879 had ≥1 hospital admission. Median GS at enrollment was 1.1 m/s. The slope of the annual decline in GS before hospitalization was −0.015 m/s. The parameter estimate (95% CI) for additional annual change in GS trajectory after hospitalization was −0.009 (−0.011 to −0.006) m/s, p < .001. The accelerated GS decline was greater for medical versus surgical hospitalizations (−0.010 vs −0.003 m/s, p = .005), and nonelective versus elective hospitalizations (−0.011 vs −0.006 m/s, p = .067). The odds of a worsening FAQ score increased on average by 4% per year. Following hospitalization, odds of FAQ score worsening further increased (multiplicative annual increase in odds ratio per year [95% CI] following hospitalization was 1.05 [1.03, 1.07], p < .001). Conclusions Hospitalization of older adults is associated with accelerated long-term decline in GS and functional limitations, especially after nonelective admissions and those for medical indications. However, for most well-functioning participants, these changes have little clinical significance.

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.

Background: An artificial intelligence (AI) algorithm applied to electrocardiography during sinus rhythm has recently been shown to detect concurrent episodic atrial fibrillation (AF). We sought to characterize the value of AI–enabled electrocardiography (AI-ECG) as a predictor of future AF and assess its performance compared with the CHARGE-AF score (Cohorts for Aging and Research in Genomic Epidemiology–AF) in a population-based sample. Methods: We calculated the probability of AF using AI-ECG, among participants in the population-based Mayo Clinic Study of Aging who had no history of AF at the time of the baseline study visit. Cox proportional hazards models were fit to assess the independent prognostic value and interaction between AI-ECG AF model output and CHARGE-AF score. C statistics were calculated for AI-ECG AF model output, CHARGE-AF score, and combined AI-ECG and CHARGE-AF score. Results: A total of 1936 participants with median age 75.8 (interquartile range, 70.4–81.8) years and median CHARGE-AF score 14.0 (IQR, 13.2–14.7) were included in the analysis. Participants with AI-ECG AF model output of >0.5 at the baseline visit had cumulative incidence of AF 21.5% at 2 years and 52.2% at 10 years. When included in the same model, both AI-ECG AF model output (hazard ratio, 1.76 per SD after logit transformation [95% CI, 1.51–2.04]) and CHARGE-AF score (hazard ratio, 1.90 per SD [95% CI, 1.58–2.28]) independently predicted future AF without significant interaction ( P =0.54). C statistics were 0.69 (95% CI, 0.66–0.72) for AI-ECG AF model output, 0.69 (95% CI, 0.66–0.71) for CHARGE-AF, and 0.72 (95% CI, 0.69–0.75) for combined AI-ECG and CHARGE-AF score. Conclusions: In the present study, both the AI-ECG AF model output and CHARGE-AF score independently predicted incident AF. The AI-ECG may offer a means to assess risk with a single test and without requiring manual or automated clinical data abstraction.

IMPORTANCE Hospitalizations are associated with cognitive decline in older adults. OBJECTIVE To determine the association between hospitalization characteristics and the trajectory of cognitive function in older adults. DESIGN Population‐based longitudinal study of cognitive aging. SETTING Olmsted Medical Center and Mayo Clinic, the only centers in Olmsted County, Minnesota, with hospitalization capacity. PARTICIPANTS Individuals without dementia at baseline, with consecutive cognitive assessments from 2004 through 2017, and at least one visit after the age of 60. MEASUREMENTS The primary outcome was longitudinal changes in global cognitive z ‐score. Secondary outcomes were changes in four cognitive domains: memory, attention/executive function, language, and visuospatial skills. Hospitalization characteristics analyzed included elective versus nonelective, medical versus surgical, critical care versus no critical care admission, and long versus short duration admissions. RESULTS Of 4,587 participants, 1,622 had 1 and more hospital admission. Before hospitalization, the average slope of the global z ‐score was −0.031 units/year. After hospitalization, the rate of annual global z ‐score accelerated by −0.051 (95% CI = −0.057, −0.045) units, P < .001, resulting in an estimated annual slope after the first hospitalization of −0.082. The accelerated decline was found in all four cognitive domains (memory, visuospatial, language, and executive, all P < .001). The acceleration of the decline in global z ‐score following hospitalization was greater for medical compared to surgical hospitalizations (slope change following hospitalization = −0.064 vs −0.034 for medical vs surgical, P < .001), and nonelective compared to elective admissions (slope change following hospitalization = −0.075 vs −0.037 for nonelective vs elective, P < .001). The acceleration of cognitive decline was not different for hospitalization with intensive care unit admission versus not. CONCLUSIONS Hospitalization of older adults is associated with accelerated decline of global and domain‐specific cognitive domains, with the rate of decline dependent upon type of admission. The clinical impact of this accelerated decline will depend on the individual's baseline cognitive reserve and expected longevity.

AbstractTau deposition is a key biological feature of Alzheimer’s disease that is closely related to cognitive impairment. However, it remains poorly understood why certain individuals may be more susceptible to tau deposition while others are more resistant. The recent availability of in vivo assessment of tau burden through positron emission tomography provides an opportunity to test the hypothesis that common genetic variants may influence tau deposition. We performed a genome-wide association study of tau-positron emission tomography on a sample of 754 individuals over age 50 (mean age 72.4 years, 54.6% men, 87.6% cognitively unimpaired) from the population-based Mayo Clinic Study of Aging. Linear regression was performed to test nucleotide polymorphism associations with AV-1451 (18F-flortaucipir) tau-positron emission tomography burden in an Alzheimer’s-signature composite region of interest, using an additive genetic model and covarying for age, sex and genetic principal components. Genome-wide significant associations with higher tau were identified for rs76752255 (P = 9.91 × 10−9, β = 0.20) in the tau phosphorylation regulatory gene PPP2R2B (protein phosphatase 2 regulatory subunit B) and for rs117402302 (P = 4.00 × 10−8, β = 0.19) near IGF2BP3 (insulin-like growth factor 2 mRNA-binding protein 3). The PPP2R2B association remained genome-wide significant after additionally covarying for global amyloid burden and cerebrovascular disease risk, while the IGF2BP3 association was partially attenuated after accounting for amyloid load. In addition to these discoveries, three single nucleotide polymorphisms within MAPT (microtubule-associated protein tau) displayed nominal associations with tau-positron emission tomography burden, and the association of the APOE (apolipoprotein E) ɛ4 allele with tau-positron emission tomography was marginally nonsignificant (P = 0.06, β = 0.07). No associations with tau-positron emission tomography burden were identified for other single nucleotide polymorphisms associated with Alzheimer’s disease clinical diagnosis in prior large case–control studies. Our findings nominate PPP2R2B and IGF2BP3 as novel potential influences on tau pathology which warrant further functional characterization. Our data are also supportive of previous literature on the associations of MAPT genetic variation with tau, and more broadly supports the inference that tau accumulation may have a genetic architecture distinct from known Alzheimer’s susceptibility genes, which may have implications for improved risk stratification and therapeutic targeting.

Objective: High plasma ceramide levels and ratios are associated with poor outcomes in individuals with cardiovascular disease; less is known about their relation to cerebral small vessel disease. We examined whether high plasma ceramide levels or ratios were associated with cerebral microbleeds (CMBs) and lacunes and whether associations differ by sex. Approach and Results: We included 548 participants enrolled in the MCSA (Mayo Clinic Study of Aging) with concurrent plasma ceramide assays and magnetic resonance imaging. CMBs were quantified on T2* magnetic resonance imaging and lacunes on T2 fluid-attenuated inversion recovery magnetic resonance imaging. Fasting plasma ceramides were assayed using liquid chromatography-electrospray ionization tandem mass spectrometry. We used logistic regression models adjusting for age, sex, hypertension, and diabetes mellitus to examine the relationship between ceramides and presence of a lacune; hurdle models were used for presence and number of CMBs. Each SD increase in the log ceramide C16:0/24:0 ratio was associated with greater odds of a CMB (odds ratio, 1.28 [95% CI, 1.01–1.64]). There was an interaction between sex and the ceramide C16:0/24:0 ratio ( P =0.049). The association between this ratio and presence of a CMB was stronger for women (odds ratio, 1.87 [95% CI, 1.20–3.00]) than men (odds ratio, 1.09 [95% CI, 0.80–1.46]). Several ceramides and all ceramide ratios were associated with number of CMBs. We did not find associations between plasma ceramides and lacunes. Conclusions: In a population-based sample, the plasma ceramide C16:0/24:0 ratio was associated with CMBs and was stronger for women. Plasma ceramides are differentially associated with cerebral small vessel pathologies.

Abstract Clinical trials with anti-tau drugs will need to target individuals at risk of accumulating tau. Our objective was to identify variables available in a research setting that predict future rates of tau PET accumulation separately among individuals who were either cognitively unimpaired or cognitively impaired. All 337 participants had: a baseline study visit with MRI, amyloid PET, and tau PET exams, at least one follow-up tau PET exam; and met clinical criteria for membership in one of two clinical diagnostic groups: cognitively unimpaired (n = 203); or cognitively impaired (n = 134, a combined group of participants with either mild cognitive impairment or dementia with Alzheimer’s clinical syndrome). Our primary analyses were in these two clinical groups; however, we also evaluated subgroups dividing the unimpaired group by normal/abnormal amyloid PET and the impaired group by clinical phenotype (mild cognitive impairment, amnestic dementia, and non-amnestic dementia). Linear mixed effects models were used to estimate associations between age, sex, education, APOE genotype, amyloid and tau PET standardized uptake value ratio (SUVR), cognitive performance, cortical thickness, and white matter hyperintensity volume at baseline, and the rate of subsequent tau PET accumulation. Log-transformed tau PET SUVR was used as the response and rates were summarized as annual per cent change. A temporal lobe tau PET meta-region of interest was used. In the cognitively unimpaired group, only higher baseline amyloid PET was a significant independent predictor of higher tau accumulation rates (P &lt; 0.001). Higher rates of tau accumulation were associated with faster rates of cognitive decline in the cognitively unimpaired subgroup with abnormal amyloid PET (P = 0.03), but among the subgroup with normal amyloid PET. In the cognitively impaired group, younger age (P = 0.02), higher baseline amyloid PET (P = 0.05), APOE ε4 (P = 0.05), and better cognitive performance (P = 0.05) were significant independent predictors of higher tau accumulation rates. Among impaired individuals, faster cognitive decline was associated with faster rates of tau accumulation (P = 0.01). While we examined many possible predictor variables, our results indicate that screening of unimpaired individuals for potential inclusion in anti-tau trials may be straightforward because the only independent predictor of high tau rates was amyloidosis. In cognitively impaired individuals, imaging and clinical variables consistent with early onset Alzheimer’s disease phenotype were associated with higher rates of tau PET accumulation suggesting this may be a highly advantageous group in which to conduct proof-of-concept clinical trials that target tau-related mechanisms. The nature of the dementia phenotype (amnestic versus non-amnestic) did not affect this conclusion.