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Brain arteriolosclerosis (B-ASC), characterized by pathologic arteriolar wall thickening, is a common finding at autopsy in aged persons and is associated with cognitive impairment. Hypertension and diabetes are widely recognized as risk factors for B-ASC. Recent research indicates other and more complex risk factors and pathogenetic mechanisms. Here, we describe aspects of the unique architecture of brain arterioles, histomorphologic features of B-ASC, relevant neuroimaging findings, epidemiology and association with aging, established genetic risk factors, and the co-occurrence of B-ASC with other neuropathologic conditions such as Alzheimer's disease and limbic-predominant age-related TDP-43 encephalopathy (LATE). There may also be complex physiologic interactions between metabolic syndrome (e.g., hypertension and inflammation) and brain arteriolar pathology. Although there is no universally applied diagnostic methodology, several classification schemes and neuroimaging techniques are used to diagnose and categorize cerebral small vessel disease pathologies that include B-ASC, microinfarcts, microbleeds, lacunar infarcts, and cerebral amyloid angiopathy (CAA). In clinical-pathologic studies that factored in comorbid diseases, B-ASC was independently associated with impairments of global cognition, episodic memory, working memory, and perceptual speed, and has been linked to autonomic dysfunction and motor symptoms including parkinsonism. We conclude by discussing critical knowledge gaps related to B-ASC and suggest that there are probably subcategories of B-ASC that differ in pathogenesis. Observed in over 80% of autopsied individuals beyond 80 years of age, B-ASC is a complex and under-studied contributor to neurologic disability.

IntroductionThe Frontotemporal Lobar Degeneration Module (FTLD-MOD) includes a neuropsychological battery designed to assess the clinical features of FTLD, although much is unknown about its utility. We investigated FTLD-MOD and Uniform Data Set 3.0 (UDS) language tests for differential diagnosis and disease monitoring.MethodsLinear regressions compared baseline performances in 1655 National Alzheimer's Coordinating Center participants (behavioral variant frontotemporal dementia (bvFTD, n = 612), semantic variant primary progressive aphasia (svPPA, n = 168), non-fluent/agrammatic variant PPA (nfvPPA, n = 168), logopenic variant PPA (lvPPA, n = 109), and controls (n = 581)). Sample sizes to detect treatment effects were estimated using longitudinal data.ResultsAmong PPAs, the FTLD-MOD language tasks and UDS Multilingual Naming Test accurately discriminated svPPA. Number Span Forward best discriminated lvPPA; Phonemic:Semantic Fluency ratio was excellent for nfvPPA classification. UDS fluency and naming measures required the smallest sample size to detect meaningful change.DiscussionThe FTLD-MOD and UDS differentiated among PPA subtypes. UDS 3.0 measures performed best for longitudinal monitoring.

IntroductionFederally funded Alzheimer's Disease Centers in the United States have been using a standardized neuropsychological test battery as part of the National Alzheimer's Coordinating Center Uniform Data Set (UDS) since 2005. Version 3 (V3) of the UDS replaced the previous version (V2) in 2015. We compared V2 and V3 neuropsychological tests with respect to their ability to distinguish among the Clinical Dementia Rating (CDR) global scores of 0, 0.5, and 1.MethodsFirst, we matched participants receiving V2 tests (V2 cohort) and V3 tests (V3 cohort) in their cognitive functions using tests common to both versions. Then, we compared receiver-operating characteristic (ROC) area under the curve in differentiating CDRs for the remaining tests.ResultsSome V3 tests performed better than V2 tests in differentiating between CDR 0.5 and 0, but the improvement was limited to Caucasian participants.DiscussionFurther efforts to improve the ability for early identification of cognitive decline among diverse racial groups are required.

IntroductionParticipant retention is important to maintaining statistical power, minimizing bias, and preventing scientific error in Alzheimer disease and related dementias research.MethodsWe surveyed representative investigators from NIH-funded Alzheimer's Disease Research Centers (ADRC), querying their use of retention tactics across 12 strategies. We compared survey results to data from the National Alzheimer's Coordinating Center for each center. We used a generalized estimating equation with independent working covariance model and empirical standard errors to assess relationships between survey results and rates of retention, controlling for participant characteristics.ResultsTwenty-five (83%) responding ADRCs employed an average 42 (SD=7) retention tactics. In a multivariable model that accounted for participant characteristics, the number of retention tactics used by a center was associated with participant retention (odds ratio=1.68, 95% confidence interval: 1.42, 1.98; P

IntroductionThe neuropsychological battery of the Uniform Data Set (UDSNB) was implemented in 2005 by the National Institute on Aging (NIA) Alzheimer Disease Centers program to measure cognitive performance in dementia and mild cognitive impairment due to Alzheimer Disease. This paper describes a revision, the UDSNB 3.0.MethodsThe Neuropsychology Work Group of the NIA Clinical Task Force recommended revisions through a process of due diligence to address shortcomings of the original battery. The UDSNB 3.0 covers episodic memory, processing speed, executive function, language, and constructional ability. Data from 3602 cognitively normal participants in the National Alzheimer Coordinating Center database were analyzed.ResultsDescriptive statistics are presented. Multivariable linear regression analyses demonstrated score differences by age, sex, and education and were also used to create a normative calculator available online.DiscussionThe UDSNB 3.0 neuropsychological battery provides a valuable non proprietary resource for conducting research on cognitive aging and dementia.