Jack, Clifford R

Background: Although inflammation has been implicated in the pathogenesis of Alzheimer’s disease, the effects of systemic inflammation on brain amyloid deposition remain unclear. Objective: We examined the association of midlife and late-life systemic inflammation with late-life brain amyloid levels in a community sample of non-demented older adults from the Atherosclerosis Risk in Communities (ARIC) – PET Study. Methods: 339 non-demented participants (age: 75 [SD 5]) were recruited from the ARIC Study to undergo florbetapir PET (amyloid) imaging. Blood levels of high sensitivity C-reactive protein (CRP), a marker of systemic inflammation, were measured 22 years (Visit 2), 16 years (Visit 4), and up to 2 years before PET imaging (Visit 5). Elevated brain amyloid deposition (standardized uptake value ratio >1.2) was the primary outcome. Results: Our primary analyses found no association of midlife and late-life CRP with late-life brain amyloid levels. However, in secondary stratified analyses, we found that higher midlife (Visit 2) CRP was associated with elevated amyloid among males (OR 1.65, 95% CI: 1.13–2.42), and among white (OR 1.33, 95% CI: 1.02–1.75), but not African American, participants ( p-interactions<0.05). Among male participants, those who maintained high CRP levels (≥3 mg/L) throughout mid- and late-life were most likely to have elevated brain amyloid (OR, 8.81; 95% CI: 1.23, 62.91). Conclusions: Although our primary analysis does not support an association between systemic inflammation and brain amyloid deposition, we found evidence for sex- and race-dependent associations. However, findings from subgroup analyses should be interpreted with caution.

Background: Neuropsychological assessment can add essential information to the characterization of individuals presenting with the logopenic variant of primary progressive aphasia (lvPPA). Objective: This study examined the neuropsychological characteristics of lvPPA patients. We also examined differences in regional and whole brain atrophy based on neuropsychological profiles. Methods: We conducted a hierarchical cluster analysis on memory, executive functioning, and visuospatial neuropsychological test data for 56 individuals with lvPPA. We then compared resultant clusters to left middle temporal, inferior parietal, and superior parietal regions-of-interest using multivariate analysis of covariance. We also performed voxel-level analyses. Results: We identified three clusters characterized as lvPPA with no neurocognitive impairment ( n = 5), lvPPA with mild neurocognitive deficits ( n = 23), and lvPPA with marked cognitive deficits ( n = 28). WAB-AQ was associated with left middle temporal volume. Superior parietal volumes were smaller for the lvPPA group with marked cognitive symptoms compared to the less severe groups. Voxel-level analyses showed greater atrophy in temporal, parietal, lateral occipital, and frontal regions, left worse than right. Age, disease duration, gender, WAB-AQ, and PiB-PET did not account for differences between groups. Conclusions: LvPPA patients without cognitive deficits in other domains were relatively uncommon while 50% of our sample exhibited pronounced neurocognitive deficits outside the language domain. Pronounced cognitive deficits in lvPPA are associated with widespread atrophy, left worse than right. Our study underscores the importance of examining neuropsychological function in addition to language in patients with lvPPA.

Abstract Introduction We sought to establish the relationships between standard postmortem measures of AD neuropathology and antemortem [ 11 C]PIB–positron emission tomography ([ 11 C]PIB‐PET) analyzed with the Centiloid (CL) method, a standardized scale for Aβ‐PET quantification. Methods Four centers contributed 179 participants encompassing a broad range of clinical diagnoses, PET data, and autopsy findings. Results CL values increased with each CERAD neuritic plaque score increment (median −3 CL for no plaques and 92 CL for frequent plaques) and nonlinearly with Thal Aβ phases (increases were detected starting at phase 2) with overlap between scores/phases. PET‐pathology associations were comparable across sites and unchanged when restricting the analyses to the 56 patients who died within 2 years of PET. A threshold of 12.2 CL detected CERAD moderate‐to‐frequent neuritic plaques (area under the curve = 0.910, sensitivity = 89.2%, specificity = 86.4%), whereas 24.4 CL identified intermediate‐to‐high AD neuropathological changes (area under the curve = 0.894, sensitivity = 84.1%, specificity = 87.9%). Discussion Our study demonstrated the robustness of a multisite Centiloid [ 11 C]PIB‐PET study and established a range of pathology‐based CL thresholds.

Abstract Introduction The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late‐onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials. Methods We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news‐publications/publications/ ). Results (1) Data‐driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β‐Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a “typical AD” subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies. Discussion ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.

ObjectiveRecent availability of amyloid and tau positron emission tomography (PET) has provided us with a unique opportunity to measure the association of systemic vascular health with brain health after accounting for the impact of Alzheimer disease (AD) pathologies. We wanted to quantify early cerebrovascular health–related magnetic resonance imaging brain measures (structure, perfusion, microstructural integrity) and evaluate their utility as a biomarker for cerebrovascular health.MethodsWe used 2 independent samples (discovery, n = 390; validation, n = 1,035) of individuals, aged ≥ 60 years, along the cognitive continuum with imaging from the population‐based sample of Mayo Clinic Study of Aging. We ascertained vascular health by summing up recently existing cardiovascular and metabolic conditions (CMC) from health care records (hypertension, hyperlipidemia, cardiac arrhythmias, coronary artery disease, congestive heart failure, diabetes mellitus, and stroke). Using multiple regression models, we quantified associations between CMC and brain health after accounting for age, sex, education/occupation, and AD burden (from amyloid and tau PET).ResultsSystemic vascular health was associated with medial temporal lobe thinning, widespread cerebral hypoperfusion, and loss of microstructural integrity in several white matter tracts including the corpus callosum and fornix. Further investigations suggested that microstructural integrity of the genu of the corpus callosum was suitable for assessing prodromal cerebrovascular health, had similar distributions in the discovery and independent validation datasets, and predicted cognitive performance above and beyond amyloid deposition.InterpretationSystemic vascular health has significant impact on brain structure and function. Quantifying prodromal cerebrovascular health–related brain measures that are independent of AD pathology–related changes has great utility for cognitive aging. Ann Neurol 2018;84:713–724

2067 Background: An estimated 2% of the general population has a meningioma (Vernooij et al. 2007), which accounts for about 36% of all primary intracranial tumors (Ostrom et al. 2015). The most established risk factors are older age and female gender. One small study identified gender but no other risk factors with meningioma (Krampla et al 2004). A larger study using the Iowa Women’s Health study data found lower levels of physical activity, greater body mass index (BMI), greater height and uterine fibroids were associated with meningioma (Johnson et al. 2011). We sought to replicate these findings and to identify additional risk factors related to meningioma in a large population-based sample. Methods: Study participants were enrolled in the Mayo Clinic Study of Aging (MCSA), a population-based sample of Olmsted County, Minnesota residents used to study prevalence, incidence, and risk-factors for Mild Cognitive Impairment and dementia and includes a variety of medical factors. Using a text search of radiologists’ notes of 2,402 MCSA individuals, mean age 77±8 years and scanned between 2004-2014.We identified 52 subjects who had at least one meningioma. We estimated the association of selected potential risk factors with presence of meningioma using odds ratios and 95% confidence intervals from logistic regression models adjusted for age and gender, which informed the multivariable models. Results: In the initial models, significant risk factors identified included BMI (as a continuous variable) (OR = 1.06 95%CI 1.01 to 1.12), taking NSAIDS (OR = 2.11, 95%CI 1.13 to 3.95), aspirin (OR = 1.90, 95%CI 1.04 to 3.46), and blood pressure lowering medication (OR = 2.06, 95%CI 1.07 to 3.99). Protective factors included male gender (OR = 0.51, 95%CI 0.29 to 0.90), coronary artery disease (CAD; OR = 0.46, 95%CI 0.22 to 0.97) and higher Beck Anxiety Inventory (BAI) total score (OR = 0.88, 95%CI 0.78 to 0.98). Simultaneous adjustment for these factors in a multivariable model did not attenuate these associations. Conclusions: Findings reveal gender and BMI as risk factors for meningioma. Additionally, certain medications such as NSAIDS and BP lowering medications warrant follow up as potential factors related to development of meningioma.

Background: Statins have been proposed to reduce the risk of Alzheimer’s disease (AD). Objective: Assess whether long-term statin use was associated with neuroimaging biomarkers of aging and dementia. Methods: Methods: We analyzed neuroimaging biomarkers in 1,160 individuals aged 65+ from the Mayo Clinic Study of Aging, a population-based prospective longitudinal study of cognitive aging. Results: Statin-treated (5+ years of therapy) individuals had greater burden of mid-and late-life cardiovascular disease ( p < 0.001) than statin-untreated (≤3 months) individuals. Lower fractional anisotropy in the genu of the corpus callosum, an early marker of cerebrovascular disease, was associated with long-term statin exposure ( p < 0.035). No significant associations were identified between long-term statin exposure and cerebral amyloid or tau burden, AD pattern neurodegeneration, or white matter hyperintensity burden. Conclusions: Long-term statin therapy was not associated with differences in AD biomarkers. Individuals with long-term statin exposure had worse white matter integrity in the genu of the corpus callosum, consistent with the coexistence of higher cerebrovascular risk factor burden in this group.