High blood pressure predicts hippocampal atrophy rate in cognitively impaired elders

INTRODUCTION: Understanding relationships among blood pressure (BP), cognition, and brain volume could inform Alzheimer's disease (AD) management. METHODS: We investigated Alzheimer's Disease Neuroimaging Initiative (ADNI) participants: 200 controls, 346 mild cognitive impairment (MCI), and 154 AD. National Alzheimer's Co‐ordinating Center (NACC) participants were separately analyzed: 1098 controls, 2297 MCI, and 4845 AD. Relationships between cognition and BP were assessed in both cohorts and BP and atrophy rates in ADNI. Multivariate mixed linear‐regression models were fitted with joint outcomes of BP (systolic, diastolic, and pulse pressure), cognition (Mini‐Mental State Examination, Logical Memory, and Digit Symbol) and atrophy rate (whole‐brain, hippocampus). RESULTS: ADNI MCI and AD patients with greater baseline systolic BP had higher hippocampal atrophy rates ([r, P value]; 0.2, 0.005 and 0.2, 0.04, respectively). NACC AD patients with lower systolic BP had lower cognitive scores (0.1, 0.0003). DISCUSSION: Higher late‐life BP may be associated with faster decline in cognitively impaired elders

Automated white matter hyperintensity segmentation using Bayesian Model Selection: assessment and correlations with cognitive change

Accurate, automated white matter hyperintensity (WMH) segmentations are needed for large-scale studies to understand contributions of WMH to neurological diseases. We evaluated Bayesian Model Selection (BaMoS), a hierarchical fully-unsupervised model selection framework for WMH segmentation. We compared BaMoS segmentations to semi-automated segmentations, and assessed whether they predicted longitudinal cognitive change in control, early Mild Cognitive Impairment (EMCI), late Mild Cognitive Impairment (LMCI), subjective/significant memory concern (SMC) and Alzheimer’s (AD) participants. Data were downloaded from the Alzheimer’s disease Neuroimaging Initiative (ADNI). Magnetic resonance images from 30 control and 30 AD participants were selected to incorporate multiple scanners, and were semi-automatically segmented by 4 raters and BaMoS. Segmentations were assessed using volume correlation, Dice score, and other spatial metrics. Linear mixed-effect models were fitted to 180 control, 107 SMC, 320 EMCI, 171 LMCI and 151 AD participants separately in each group, with the outcomes being cognitive change (e.g. mini-mental state examination; MMSE), and BaMoS WMH, age, sex, race and education used as predictors. There was a high level of agreement between BaMoS’ WMH segmentation volumes and a consensus of rater segmentations, with a median Dice score of 0.74 and correlation coefficient of 0.96. BaMoS WMH predicted cognitive change in: control, EMCI, and SMC groups using MMSE; LMCI using clinical dementia rating scale; and EMCI using Alzheimer’s disease assessment scale-cognitive subscale (p < 0.05, all tests). BaMoS compares well to semi-automated segmentation, is robust to different WMH loads and scanners, and can generate volumes which predict decline. BaMoS can be applicable to further large-scale studies

Vascular Cognitive Impairment and cognitive decline; a longitudinal study comparing different types of vascular brain injury - The TRACE-VCI study

Background: Little is known about the trajectories of cognitive decline in relation to different types of vascular brain injury in patients presenting at a memory clinic with Vascular Cognitive Impairment (VCI). / Methods: We included 472 memory clinic patients (age 68 (±8.2) years, 44% female, MMSE 25.9 (±2.8), 210 (44.5%) dementia) from the prospective TRACE-VCI cohort study with possible VCI, defined as cognitive complaints and vascular brain injury on MRI and at least 1 follow-up cognitive assessment (follow-up time 2.5 (±1.4) years, n = 1172 assessments). Types of vascular brain injury considered lacune(s) (≥1; n = 108 patients (23%)), non-lacunar infarct(s) (≥1; n = 54 (11%)), white matter hyperintensities (WMH) (none/mild versus moderate/severe (n = 211 patients (45%)) and microbleed(s) (≥1; n = 202 patients (43%)). We assessed cognitive functioning at baseline and follow-up, including the Rey Auditory Verbal Learning Test (RAVLT), Trail Making Test (TMT) A and B, category naming task and MMSE. The association of different types of vascular brain injury with cognitive decline was evaluated with linear mixed models, including one type of vascular brain injury (dichotomized), time and vascular brain injury*time, adjusted for sex, age, dementia status (yes/no), education (Verhage scale) and medial temporal lobe atrophy (MTA) score (dichotomized as ≥ 1.5). / Results: Across the population, performance declined over time on all tests. Linear mixed models showed that lacune(s) were associated with worse baseline TMTA (Beta(SE)) (8.3 (3.8), p = .03) and TMTB (25.6 (10.3), p = .01), albeit with a slower rate of decline on MMSE, RAVLT and category naming. By contrast, patients with non-lacunar infarct(s) showed a steeper rate of decline on TMTB (29.6 (7.7), p = .00), mainly attributable to patients with dementia (62.9 (15.5), p = .00). / Conclusion: Although different types of vascular brain injury have different etiologies and different patterns, they show little differences in cognitive trajectories depending on type of vascular brain injury

Small vessel disease lesion type and brain atrophy: The role of co‐occurring amyloid

Introduction: It is unknown whether different types of small vessel disease (SVD), differentially relate to brain atrophy and if co‐occurring Alzheimer's disease pathology affects this relation. / Methods: In 725 memory clinic patients with SVD (mean age 67 ± 8 years, 48% female) we compared brain volumes of those with moderate/severe white matter hyperintensities (WMHs; n = 326), lacunes (n = 132) and cerebral microbleeds (n = 321) to a reference group with mild WMHs (n = 197), also considering cerebrospinal fluid (CSF) amyloid status in a subset of patients (n = 488). / Results: WMHs and lacunes, but not cerebral microbleeds, were associated with smaller gray matter (GM) volumes. In analyses stratified by CSF amyloid status, WMHs and lacunes were associated with smaller total brain and GM volumes only in amyloid‐negative patients. SVD‐related atrophy was most evident in frontal (cortical) GM, again predominantly in amyloid‐negative patients. / Discussion: Amyloid status modifies the differential relation between SVD lesion type and brain atrophy in memory clinic patients

Patterns of progressive atrophy vary with age in Alzheimer's disease patients

Age is not only the greatest risk factor for Alzheimer's disease (AD) but also a key modifier of disease presentation and progression. Here, we investigate how longitudinal atrophy patterns vary with age in mild cognitive impairment (MCI) and AD. Data comprised serial longitudinal 1.5-T magnetic resonance imaging scans from 153 AD, 339 MCI, and 191 control subjects. Voxel-wise maps of longitudinal volume change were obtained and aligned across subjects. Local volume change was then modeled in terms of diagnostic group and an interaction between group and age, adjusted for total intracranial volume, white-matter hyperintensity volume, and apolipoprotein E genotype. Results were significant at p < 0.05 with family-wise error correction for multiple comparisons. An age-by-group interaction revealed that younger AD patients had significantly faster atrophy rates in the bilateral precuneus, parietal, and superior temporal lobes. These results suggest younger AD patients have predominantly posterior progressive atrophy, unexplained by white-matter hyperintensity, apolipoprotein E, or total intracranial volume. Clinical trials may benefit from adapting outcome measures for patient groups with lower average ages, to capture progressive atrophy in posterior cortices

Cerebral amyloid burden is associated with white matter hyperintensity location in specific posterior white matter regions

White matter hyperintensities (WMHs) are a common manifestation of cerebral small vessel disease. WMHs are also frequently observed in patients with familial and sporadic Alzheimer's disease, often with a particular posterior predominance. Whether amyloid and tau pathologies are linked to WMH occurrence is still debated. We examined whether cerebral amyloid and tau burden, reflected in cerebrospinal fluid amyloid-beta 1-42 (Aβ-42) and phosphorylated tau (p-tau), are related to WMH location in a cohort of 517 memory clinic patients. Two lesion mapping techniques were performed: voxel-based analyses and region of interest-based linear regression. Voxelwise associations were found between lower Aβ-42 and parieto-occipital periventricular WMHs. Regression analyses demonstrated that lower Aβ-42 correlated with larger WMH volumes in the splenium of the corpus callosum and posterior thalamic radiation, also after controlling for markers of vascular disease. P-tau was not consistently related to WMH occurrence. Our findings indicate that cerebral amyloid burden is associated with WMHs located in specific posterior white matter regions, possibly reflecting region-specific effects of amyloid pathology on the white matter

Assessment of the appropriate use criteria for amyloid PET in an unselected memory clinic cohort: The ABIDE project

Introduction The objective of this study was to assess the usefulness of the appropriate use criteria (AUC) for amyloid imaging in an unselected cohort. Methods We calculated sensitivity and specificity of appropriate use (increased confidence and management change), as defined by Amyloid Imaging Taskforce in the AUC, and other clinical utility outcomes. Furthermore, we compared differences in post–positron emission tomography diagnosis and management change between “AUC-consistent” and “AUC-inconsistent” patients. Results Almost half (250/507) of patients were AUC-consistent. In both AUC-consistent and AUC-inconsistent patients, post–positron emission tomography diagnosis (28%–21%) and management (32%–17%) change was substantial. The Amyloid Imaging Taskforce's definition of appropriate use occurred in 55/507 (13%) patients, detected by the AUC with a sensitivity of 93%, and a specificity of 56%. Diagnostic changes occurred independently of AUC status (sensitivity: 57%, specificity: 53%). Discussion The current AUC are not sufficiently able to discriminate between patients who will benefit from amyloid positron emission tomography and those who will not

Presumed small vessel disease, imaging and cognition markers in the Alzheimer's Disease Neuroimaging Initiative

MRI-derived features of presumed cerebral small vessel disease are frequently found in Alzheimer’s disease. Influences of such markers on disease-progression measures are poorly understood. We measured markers of presumed small vessel disease (white matter hyperintensity volumes; cerebral microbleeds) on baseline images of newly enrolled individuals in the Alzheimer’s Disease Neuroimaging Initiative cohort (GO and 2) and used linear mixed models to relate these to subsequent atrophy and neuropsychological score change. We also assessed heterogeneity in white matter hyperintensity positioning within biomarker abnormality sequences, driven by the data, using the Subtype and Stage Inference algorithm. This study recruited both sexes and included: controls: [n = 159, mean(SD) age = 74(6) years]; early and late mild cognitive impairment [ns = 265 and 139, respectively, mean(SD) ages =71(7) and 72(8) years, respectively]; Alzheimer’s disease [n = 103, mean(SD) age = 75(8)] and significant memory concern [n = 72, mean(SD) age = 72(6) years]. Baseline demographic and vascular risk-factor data, and longitudinal cognitive scores (Mini-Mental State Examination; logical memory; and Trails A and B) were collected. Whole-brain and hippocampal volume change metrics were calculated. White matter hyperintensity volumes were associated with greater whole-brain and hippocampal volume changes independently of cerebral microbleeds (a doubling of baseline white matter hyperintensity was associated with an increase in atrophy rate of 0.3 ml/year for brain and 0.013 ml/year for hippocampus). Cerebral microbleeds were found in 15% of individuals and the presence of a microbleed, as opposed to none, was associated with increases in atrophy rate of 1.4 ml/year for whole brain and 0.021 ml/year for hippocampus. White matter hyperintensities were predictive of greater decline in all neuropsychological scores, while cerebral microbleeds were predictive of decline in logical memory (immediate recall) and Mini-Mental State Examination scores. We identified distinct groups with specific sequences of biomarker abnormality using continuous baseline measures and brain volume change. Four clusters were found; Group 1 showed early Alzheimer’s pathology; Group 2 showed early neurodegeneration; Group 3 had early mixed Alzheimer’s and cerebrovascular pathology; Group 4 had early neuropsychological score abnormalities. White matter hyperintensity volumes becoming abnormal was a late event for Groups 1 and 4 and an early event for 2 and 3. In summary, white matter hyperintensities and microbleeds were independently associated with progressive neurodegeneration (brain atrophy rates) and cognitive decline (change in neuropsychological scores). Mechanisms involving white matter hyperintensities and progression and microbleeds and progression may be partially separate. Distinct sequences of biomarker progression were found. White matter hyperintensity development was an early event in two sequences

Prediction of poor clinical outcome in vascular cognitive impairment: TRACE-VCI study

INTRODUCTION: Prognostication in memory clinic patients with vascular brain injury (eg possible vascular cognitive impairment [VCI]) is often uncertain. We created a risk score to predict poor clinical outcome. METHODS: Using data from two longitudinal cohorts of memory clinic patients with vascular brain injury without advanced dementia, we created (n = 707) and validated (n = 235) the risk score. Poor clinical outcome was defined as substantial cognitive decline (change of Clinical Dementia Rating ≥1 or institutionalization) or major vascular events or death. Twenty‐four candidate predictors were evaluated using Cox proportional hazard models. RESULTS: Age, clinical syndrome diagnosis, Disability Assessment for Dementia, Neuropsychiatric Inventory, and medial temporal lobe atrophy most strongly predicted poor outcome and constituted the risk score (C‐statistic 0.71; validation cohort 0.78). Of note, none of the vascular predictors were retained in this model. The 2‐year risk of poor outcome was 6.5% for the lowest (0‐5) and 55.4% for the highest sum scores (10‐13). DISCUSSION: This is the first, validated, prediction score for 2‐year clinical outcome of patients with possible VCI