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

Abstract

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.

Keywords: Alzheimer’s; biomarkers; cerebrovascular disease; microbleeds; white matter hyperintensities.

Graphical Abstract

Figure 1

Small vessel disease markers. Axial views of A white matter hyperintensity (outlined in red) on a FLAIR image; B Cerebral microbleeds unlabelled with labelling shown underneath (yellow crosses) on a T₂* image; C a lacune with labelling shown underneath (yellow cross) on a FLAIR image.

Figure 2

Flowchart depicting subject selection for analysis. Definitions: white matter hyperintensity (WMH); statistical parametric mapping (SPM); total intracranial volume (TIV).

Figure 3

Results from disease progression modelling analyses. Subject numbers for each group are: Group 1 (223); Group 2 (108); Group 3 (76); Group 4 (43). Only continuous complete-case biomarker variables were used. No time scale is imposed on the event position (x-axis); events may be close together or distant in time. Positioning for all biomarkers of interest (y-axis) in all groups is presented. Each entry of each positional variance diagram corresponds to the probability each biomarker (y-axis) will become abnormal at each position in the sequence (x-axis) estimated by the SuStaIn EBM algorithm, ranging from 0 in white to 1 in black. Definitions: cerebrospinal fluid (CSF); amyloid beta 1–42 (Aβ); total tau (tau); phosphorylated tau 181 (p-tau); brain boundary shift integral atrophy rate over 12 months (BBSI); hippocampal boundary shift integral atrophy rate over 12 months (HBSI); Mini Mental State Examination (MMSE); logical memory immediate recall (LIMM).