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

CSF amyloid is a consistent predictor of white matter hyperintensities across the disease course from aging to Alzheimer's disease.

This study investigated the relationship between white matter hyperintensities (WMH) and cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers. Subjects included 180 controls, 107 individuals with a significant memory concern, 320 individuals with early mild cognitive impairment, 171 individuals with late mild cognitive impairment, and 151 individuals with AD, with 3T MRI and CSF Aβ1-42, total tau (t-tau), and phosphorylated tau (p-tau) data. Multiple linear regression models assessed the relationship between WMH and CSF Aβ1-42, t-tau, and p-tau. Directionally, a higher WMH burden was associated with lower CSF Aβ1-42 within each diagnostic group, with no evidence for a difference in the slope of the association across diagnostic groups (p = 0.4). Pooling all participants, this association was statistically significant after adjustment for t-tau, p-tau, age, diagnostic group, and APOE-ε4 status (p < 0.001). Age was the strongest predictor of WMH (partial R2~16%) compared with CSF Aβ1-42 (partial R2~5%). There was no evidence for an association with WMH and either t-tau or p-tau. These data are supportive of a link between amyloid burden and presumed vascular pathology

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

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

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

Functional neuroanatomy of speech signal decoding in primary progressive aphasias

This work was supported by the Alzheimer’s Society (AS-PG-16-007), the National Institute for Health Research University College London Hospitals Biomedical Research Centre (CBRC 161), the UCL Leonard Wolfson Experimental Neurology Centre (PR/ ylr/18575), and the Economic and Social Research Council (ES/ K006711/1). Individual authors were supported by the Medical Research Council (PhD Studentship to CJDH; MRC Clinician Scientist Fellowship to JDR), the Wolfson Foundation (Clinical Research Fellowship to CRM), the National Brain AppealeFrontotemporal Dementia Research Fund (CNC), Alzheimer’s Research UK (ARTSRF2010-3 to SJC), and the Wellcome Trust (091673/Z/10/Z to JDW)

Disentangling the relationship between white matter disease, vascular risk, Alzheimer's disease pathology and brain atrophy: timing of events and location of changes

This thesis is an investigation into vascular risk, vascular brain lesions, and age contributions to brain atrophy and cognitive decline in Alzheimer’s disease (AD). Associations of white matter hyperintensities (WMHs) to longitudinal hippocampal atrophy were explored in control, mild cognitive impairment (MCI) and AD participants enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI1). Also using ADNI1 data, I identified differences in longitudinal brain atrophy patterns in younger vs. older AD patients. Blood pressure (BP), cognition and brain atrophy were jointly modelled to see how changes in each variable are correlated in ADNI1 and National Alzheimer’s Coordinating Centre (NACC) participants. The independent associations of microbleeds (MBs), lacunes and WMHs to longitudinal atrophy were also explored in ADNIGo and ADNI2. Lastly, I developed a new protocol for semi-automated WMH segmentation and generated ‘gold standard’ segmentations with which to assess the performance of an automated WMH segmentation algorithm. WMHs were found to associate with hippocampal atrophy in controls and MCI, which survived correction for CSF biomarkers of amyloid and tau, and concurrent brain atrophy. Secondly, I found that younger AD patients have greater extra- hippocampal atrophy, with a prominent posterior atrophy pattern, and faster atrophy rates compared to older AD patients. Greater hippocampal atrophy rates were found in MCI and AD patients with higher baseline systolic BP. In ADNI2 and ADNIGo subjects MB presence and WMH volume were associated with increased longitudinal brain atrophy rate, whilst presence of a lacune was associated with a reduced atrophy rate. Lastly, I showed that the automated WMH segmentation algorithm compares well to the ‘gold standard’, and automated volumes were able to predict cognitive change across disease types. This work extends existing knowledge about how age, vascular risk and brain lesions with a presumed vascular aetiology, link with brain atrophy and cognitive decline in ageing and AD

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

White matter hyperintensities are associated with disproportionate progressive hippocampal atrophy

This study investigates relationships between white matter hyperintensity (WMH) volume, cerebrospinal fluid (CSF) Alzheimer's disease (AD) pathology markers, and brain and hippocampal volume loss. Subjects included 198 controls, 345 mild cognitive impairment (MCI), and 154 AD subjects with serial volumetric 1.5-T MRI. CSF Aβ42 and total tau were measured (n = 353). Brain and hippocampal loss were quantified from serial MRI using the boundary shift integral (BSI). Multiple linear regression models assessed the relationships between WMHs and hippocampal and brain atrophy rates. Models were refitted adjusting for (a) concurrent brain/hippocampal atrophy rates and (b) CSF Aβ42 and tau in subjects with CSF data. WMH burden was positively associated with hippocampal atrophy rate in controls (P = 0.002) and MCI subjects (P = 0.03), and with brain atrophy rate in controls (P = 0.03). The associations with hippocampal atrophy rate remained following adjustment for concurrent brain atrophy rate in controls and MCIs, and for CSF biomarkers in controls (P = 0.007). These novel results suggest that vascular damage alongside AD pathology is associated with disproportionately greater hippocampal atrophy in nondemented older adults.