Topographic patterns of white matter hyperintensities are associated with multimodal neuroimaging biomarkers of Alzheimer’s disease

Abstract

Background White matter hyperintensities (WMH) are frequently found in Alzheimer’s disease (AD). Commonly considered as a marker of cerebrovascular disease, regional WMH may be related to pathological hallmarks of AD, including beta-amyloid (Aβ) plaques and neurodegeneration. The aim of this study was to examine the regional distribution of WMH associated with Aβ burden, glucose hypometabolism, and gray matter volume reduction. Methods In a total of 155 participants (IMAP+ cohort) across the cognitive continuum from normal cognition to AD dementia, FLAIR MRI, AV45-PET, FDG-PET, and T1 MRI were acquired. WMH were automatically segmented from FLAIR images. Mean levels of neocortical Aβ deposition (AV45-PET), temporo-parietal glucose metabolism (FDG-PET), and medial-temporal gray matter volume (GMV) were extracted from processed images using established AD meta-signature templates. Associations between AD brain biomarkers and WMH, as assessed in region-of-interest and voxel-wise, were examined, adjusting for age, sex, education, and systolic blood pressure. Results There were no significant associations between global Aβ burden and region-specific WMH. Voxel-wise WMH in the splenium of the corpus callosum correlated with greater Aβ deposition at a more liberal threshold. Region- and voxel-based WMH in the posterior corpus callosum, along with parietal, occipital, and frontal areas, were associated with lower temporo-parietal glucose metabolism. Similarly, lower medial-temporal GMV correlated with WMH in the posterior corpus callosum in addition to parietal, occipital, and fontal areas. Conclusions This study demonstrates that local white matter damage is correlated with multimodal brain biomarkers of AD. Our results highlight modality-specific topographic patterns of WMH, which converged in the posterior white matter. Overall, these cross-sectional findings corroborate associations of regional WMH with AD-typical Aß deposition and neurodegeneration.

White matter hyperintensity topography in Alzheimer's disease and links to cognition

“…Studies assessing the association between S‐CC WMH and AD pathologies (amyloid or tau) provided mixed results. A link was found between S‐CC WMH and cerebrospinal fluid (CSF) Aβ 1‐42 80 and amyloid‐PET, 81 but not CSF phosphorylated tau, 80 while a recent study found a significant association between global WMH and plasma total tau 82 . Cerebral amyloid angiopathy may at least partially explain the association between WMH and AD as well as the posteroanterior gradient of WMH in AD 83–85 .…”

Intellectual Structure and Emerging Trends of White Matter Hyperintensity Studies: A Bibliometric Analysis From 2012 to 2021

“…White matter degeneration is closely related to cognitive and functional decline and may occur years before the onset of anticipated symptoms of AD ( Ble et al, 2006 ; Lee et al, 2016 ; Zavaliangos-Petropulu et al, 2019 ). White matter degeneration is recognized as a prominent characteristic and potential biomarker of AD ( Sachdev et al, 2013 ; Lee et al, 2016 ) and correlates with neuroimaging biomarkers of AD ( Gaubert et al, 2021 ). Oligodendrocyte lineage cells dysfunction is a crucial mechanism of the white matter changes of AD and may be the potential target ( Nasrabady et al, 2018 ; Lorenzini et al, 2020 ).…”

Vascular Health Is Associated With Functional Connectivity Decline in Higher-Order Networks of Older Adults

“…The present study sample comprised 43 cognitively unimpaired older adults (OA), 18 participants with subjective cognitive decline (SCD) and 34 participates with mild cognitive impairment (MCI). By including participants along the cognitive continuum with normal cognition, SCD, and MCI, we ensured that there was enough variance due to VRF and brain pathology, including of Aβ and WMH, in our sample ( Wirth et al, 2018 ; Gaubert et al, 2021 ) to assess the proposed associations. Other important reasons to include the asymptomatic or preclinical stages (i.e., SCD and MCI) are that these are clinically relevant in terms of early treatment and some mechanisms may specifically appear in stages before the onset of clinical symptoms.…”

“…The WMH volumes were derived using probability maps, which were computed from segmented FLAIR images using the lesion prediction algorithm (LPA), implemented in the Lesion Segmentation Toolbox (LST 2 , version 2) of SPM12. As described in our previous studies ( Garnier-Crussard et al, 2020 , 2021 ; Gaubert et al, 2021 ), processing comprised the co-registration of individual raw FLAIR images to their respective T1-weighted image and the computation of native-space lesion probability maps. To quantify WMH volumes, native-space lesion probability maps were binarized at a threshold at 0.5 and a minimal cluster size of 10 mm 3 .…”

“…We therefore assessed the impact of VRF on RSFC trajectories over time in non-demented older adults using an independent cohort, namely the IMAP+ cohort. This cohort features longitudinal assessments of neurocognitive, neuropsychological, and neuroimaging measures (e.g., Mutlu et al, 2017 ; Gaubert et al, 2021 ) similar to the PREVENT-AD cohort. We evaluated VRF related to systolic and diastolic blood pressure, BMI, and glycated hemoglobin (HbA1c), a long-term marker of glucose metabolism.…”