Premium
Cerebral amyloid and white matter hyperintensity volume are independently associated with rates of cerebral atrophy in Insight 46, a sub‐study of the 1946 British birth cohort
Author(s) -
Keuss Sarah E,
Poole Teresa,
Cash David M,
Lane Christopher A,
Parker Thomas D,
Buchanan Sarah M,
Keshavan Ashvini,
Coath William,
Malone Ian B,
Thomas David L,
Sudre Carole H,
Barnes Jo,
Lu Kirsty,
James SarahNaomi,
Wagen Aaron,
Storey Mathew,
MurraySmith Heidi,
Wong Andrew,
Richards Marcus,
Fox Nick C,
Schott Jonathan M
Publication year - 2020
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.044924
Subject(s) - white matter , hyperintensity , atrophy , grey matter , psychology , medicine , brain size , cardiology , magnetic resonance imaging , audiology , pathology , neuroscience , radiology
Background Alzheimer’s (AD) and cerebrovascular disease are common causes of cognitive impairment in later life and often co‐exist. Understanding how AD and vascular pathologies act independently or together to influence neurodegeneration in later life is important for the development of effective treatments and clinical trial design. Method 219 cognitively normal participants underwent cognitive testing, structural MRI and 18F‐florbetapir amyloid‐PET scans at two visits approximately two years apart. Changes in whole brain, ventricular and hippocampal volumes between time‐points were determined using the Boundary Shift Integral (BSI) (doi:10.1016/j.neuroimage.2009.12.059). Baseline white matter hyperintensity volume (WMHV) was generated using BaMoS (doi:10.1109/TMI.2015.2419072). Baseline amyloid SUVRs were derived with eroded subcortical white matter as the reference region and a composite grey matter target region. A cut‐point of 0.6104 was used to define amyloid positivity. Linear regression was used to investigate relationships of amyloid and WMHV with atrophy rates. Specifically, models were fitted with BSI as the outcome, scan interval as the explanatory variable, and interactions between scan interval and i) the explanatory variable of interest and ii) each of the covariates (age at baseline scan, sex and total intracranial volume). Amyloid and WMHV were assessed separately and then together within the same model. An interaction between amyloid, WMHV and scan interval was also tested in a further model. Result 199 cognitively normal participants (mean baseline age 70.1±0.4 years; 47% female) had high‐quality imaging data (Table 1). Positive amyloid status was associated with greater rates of brain and hippocampal atrophy and ventricular expansion, with a positive relationship between SUVR and ventricular expansion and hippocampal atrophy (Table 2). Larger WMHV was associated with higher rates of brain and hippocampal atrophy and ventricular expansion (Table 2). None of these associations were meaningfully altered by including amyloid and WMHV within the same model (Table 3). There was no evidence of an interaction between amyloid and WMHV for any BSI measure (interaction p>0.13, all tests). Conclusion Markers of amyloid and presumed small‐vessel disease were independently associated with atrophy rates, and there was no evidence that either pathological process modified the effect of the other.