Aakre, Jeremiah

AbstractBackgroundThe NIA Health Disparities Research (NIA‐HD) Framework organizes factors in four domains (i.e., environmental, sociocultural, behavioral, and biological), which work together over the lifetime to influence health and health disparities.MethodIn previous work, we employed a 2‐stage approach using factor and principal component (PC) analyses to identify patterns of factors in the domains of the NIA‐HD Framework. We found three PCs that identified related groupings from more than one NIA‐HD domain. PC1: retirement status, residence type, multivitamin use, heart disease, Charlson comorbidity index, walking/balance difficulties, and Beck Depression Inventory (BDI)‐II questions – mainly from the somatic dimension; PC2: physical activity/exercise, social and group activities, education, occupation, cardiometabolic risk factors, and self‐rated health; PC3: national and state area deprivation index ranking and BDI‐II questions – mainly in the cognitive dimension. Age and sex‐adjusted linear regression models were used to assess the cross‐sectional association of each PC with AD‐plasma biomarkers measured using the Quanterix Simoa platform in the Mayo Clinic Study of Aging (MCSA) participants. AD‐plasma biomarkers included Aβ 42/40, phosphorylated‐tau 181 (p‐tau181), plasma glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). All analyses were considered statistically significant at a p <0.05.ResultThere were 1300 cognitively unimpaired participants, 50 years old or older, with available plasma biomarkers (mean age (SD) 68.6 (9.5) years; 49.1% were female) at the current study baseline. PC1 and PC3 were associated with higher NfL and p‐tau 181 values (p<0.05). PC1 and PC2 were associated with higher GFAP values (p<0.05). No PCs were associated with the Aβ 42/40 ratio. Findings were mostly similar after additionally adjusting for global cognitive performance and chronic kidney disease.ConclusionWe found that patterns in a wide range of environmental, sociocultural, behavioral, and biological factors were associated with AD plasma biomarkers. Longitudinal studies are warranted to validate findings and support multi‐faceted approaches to address health disparities and achieve disease delay and prevention.

AbstractBackgroundNeocortical tau can be present in over half of patients with Lewy body disease at autopsy, and may influence the timing of when a diagnosis of Dementia with Lewy bodies (DLB) can be made. We examined whether the core features, onset age and latency of probable DLB diagnosis differ by pathological subgroups.MethodAll patients (n=176) met clinical criteria for probable DLB, underwent autopsy and were classified as transitional or diffuse Lewy body disease (TLBD, DLBD). The TLBD and DLBD groups were further subdivided based on the absence of neocortical tangles represented by a low (L) Braak NFT stage of 0‐III or by the presence of neocortical tangles represented by a high (H) Braak NFT stage of IV‐VI. Onset age and latency from cognitive symptom onset to probable DLB were compared for TLBD‐L (n=30), DLBD‐L (n=47), DLBD‐H (n=78) and TLBD‐H (n=21).ResultThe TLBD‐H group met criteria for DLB at an older age (median 76 years) compared to TLBD‐L, DLBD‐L or DLBD‐H groups (median age 70 years, p<0.001). The latency to probable DLB from cognitive onset was shortest for TLBD‐L and DLBD‐L (median < 1 year), which was shorter than DLBD‐H (median 2 years; p=0.016), each of which were shorter than TLBD‐H (median 7.3 years; p<0.001). RBD was more common in men (79% men vs. 40% women, p<0.001) and in patients without neocortical tangles (86% vs. 57%, p<0.001). Patients with RBD met criteria for probable DLB at a younger age than those without a history of RBD (median 69 years vs. 76 years, p<0.001). Men had a shorter latency to probable DLB than women (median 1.0 year vs. 2.8 years, p<0.01), but this was related to RBD status that was more common in men.ConclusionPresence of RBD in both sexes led to a younger onset age and shorter latency to diagnosis of probable DLB. Patients with more widespread tau relative to α‐synuclein pathology (TLBD‐H) were older when probable DLB was diagnosed compared to those with so‐called pure Lewy body disease (TLBD‐L, DLBD‐L) or those with diffuse α‐synuclein and tau pathology (DLBD‐H).

AbstractIntroductionPractical algorithms predicting the probability of amyloid pathology among patients with subjective cognitive decline or mild cognitive impairment may help clinical decisions regarding confirmatory biomarker testing for Alzheimer's disease.MethodsAlgorithm feature selection was conducted with Alzheimer's Disease Neuroimaging Initiative and Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing data. Probability algorithms were developed in Alzheimer's Disease Neuroimaging Initiative using nested cross‐validation accompanied by stratified subsampling to obtain 1000 internally validated decision trees. Semi‐independent validation was conducted using Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing. Independent external validation was conducted in the population‐based Mayo Clinic Study of Aging.ResultsTwo algorithms were developed using age and normalized immediate recall z‐scores, with or without apolipoprotein E ε4 carrier status. Both algorithms had robust performance across data sets and when substituting different recall memory tests.DiscussionThe statistical framework resulted in robust probability estimation. Application of these algorithms may assist in clinical decision‐making for further testing to diagnose amyloid pathology.

There has been no comparison of excessive daytime sleepiness (EDS) in patients with Alzheimer’s disease dementia (AD), dementia with Lewy bodies (DLB), and behavioral variant frontotemporal dementia (bvFTD). We identified patients with mild dementia who met criteria for these disorders who also had the Epworth Sleepiness Scale (ESS) completed. The sample included 17 bvFTD, 111 AD, and 31 DLB. An ESS score ≥10 was considered abnormal and consistent with EDS. Analyses with age and sex as covariates revealed higher mean ESS scores for DLB compared to the other groups (DLB 13.9 [5], bvFTD 9.6 [8], AD 8.8 [5], P < .05). An ESS score ≥10 was significantly more likely to occur in DLB compared to bvFTD or AD (DLB 81% vs bvFTD 47% vs AD 45%, P < .01). In patients with mild dementia, EDS is greatest in DLB and comparably lower in bvFTD and AD.

Background and Purpose— Superficial siderosis (SS) is characterized by hemosiderin deposition in the superficial layers of the central nervous system and can be seen during postmortem examination or with iron-sensitive magnetic resonance imaging techniques. The distribution of SS may predict the probable underlying cause. This study aimed to report the prevalence and natural history of SS in a population-based study. Methods— Brain magnetic resonance imaging scans from the MCSA (Mayo Clinic Study of Aging), a population-based study of residents 50 to 89 years of age in Olmsted County, Minnesota, were reviewed. Participants with imaging consistent with SS were identified from 2011 through 2016. An inverse probability weighting approach was used to convert our observed frequencies to population prevalence of SS. Additional data abstracted included amyloid positron emission tomography, Apolipoprotein E genotype, coexisting cerebral microbleeds, and extent of SS. Results— A total of 1412 participants had eligible magnetic resonance imaging scans. Two participants had infratentorial SS, restricted to the posterior fossa. Thirteen participants had cortical SS involving the cerebral convexities (7 focal and 6 disseminated). Only 3 of the participants with cortical SS (23%) also had cerebral microbleeds. The population prevalence of SS was 0.21% (95% confidence interval, 0–0.45) in those 50 to 69 years old and 1.43% (confidence interval, 0.53–2.34) in those over 69 years old. Apolipoprotein E ε2 allele was more common in those with SS (57.1% versus 15.0%; P <0.001). Compared with participants without SS, those with SS were also more likely to have a positive amyloid positron emission tomographic scan (76.9% versus 29.8%; P <0.001). Conclusions— SS may be encountered in the general elderly population. The association with increased amyloid burden and Apolipoprotein E ε2 genotype supports cerebral amyloid angiopathy as the most common mechanism. Longitudinal follow-up is needed to evaluate the risk of subsequent hemorrhage in cases of incidentally discovered SS.