White matter hyperintensity patterns: associations with comorbidities, amyloid, and cognition.

White matter hyperintensities (WMHs) are often measured globally, but spatial patterns of WMHs could underlie different risk factors and neuropathological and clinical correlates. We investigated the spatial heterogeneity of WMHs and their association with comorbidities, Alzheimer's disease (AD) risk factors, and cognition. In this cross-sectional study, we studied 171 cognitively unimpaired (CU; median age: 65 years, range: 50 to 89) and 51 mildly cognitively impaired (MCI; median age: 72, range: 53 to 89) individuals with available amyloid (18F-flutementamol) PET and FLAIR-weighted images. Comorbidities were assessed using the Cumulative Illness Rating Scale (CIRS). Each participant's white matter was segmented into 38 parcels, and WMH volume was calculated in each parcel. Correlated principal component analysis was applied to the parceled WMH data to determine patterns of WMH covariation. Adjusted and unadjusted linear regression models were used to investigate associations of component scores with comorbidities and AD-related factors. Using multiple linear regression, we tested whether WMH component scores predicted cognitive performance. Principal component analysis identified four WMH components that broadly describe FLAIR signal hyperintensities in posterior, periventricular, and deep white matter regions, as well as basal ganglia and thalamic structures. In CU individuals, hypertension was associated with all patterns except the periventricular component. MCI individuals showed more diverse associations. The posterior and deep components were associated with renal disorders, the periventricular component was associated with increased amyloid, and the subcortical gray matter structures was associated with sleep disorders, endocrine/metabolic disorders, and increased amyloid. In the combined sample (CU + MCI), the main effects of WMH components were not associated with cognition but predicted poorer episodic memory performance in the presence of increased amyloid. No interaction between hypertension and the number of comorbidities on component scores was observed. Our study underscores the significance of understanding the regional distribution patterns of WMHs and the valuable insights that risk factors can offer regarding their underlying causes. Moreover, patterns of hyperintensities in periventricular regions and deep gray matter structures may have more pronounced cognitive implications, especially when amyloid pathology is also present.

Bachmann D ，von Rickenbach B ，Buchmann A ，Hüllner M ，Zuber I ，Studer S ，Saake A ，Rauen K ，Gruber E ，Nitsch RM ，Hock C ，Treyer V ，Gietl A ... -  《Alzheimers Research & Therapy》

Can white matter hyperintensities based Fazekas visual assessment scales inform about Alzheimer's disease pathology in the population?

Pradeep A ，Raghavan S ，Przybelski SA ，Preboske GM ，Schwarz CG ，Lowe VJ ，Knopman DS ，Petersen RC ，Jack CR Jr ，Graff-Radford J ，Cogswell PM ，Vemuri P ... -  《Alzheimers Research & Therapy》

Association of Data-Driven White Matter Hyperintensity Spatial Signatures With Distinct Cerebral Small Vessel Disease Etiologies.

Topographical distribution of white matter hyperintensities (WMH) are hypothesized to vary by cerebrovascular risk factors. We used an unbiased pattern discovery approach to identify distinct WMH spatial patterns and investigate their association with different WMH etiologies. We performed a cross-sectional study on participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) to identify spatially distinct WMH distribution patterns using voxel-based spectral clustering analysis of aligned WMH probability maps. We included all participants from the ADNI Grand Opportunity/ADNI 2 study with available baseline 2D-FLAIR MRI scans, without history of stroke or presence of infarction on imaging. We evaluated the associations of these WMH spatial patterns with vascular risk factors, amyloid-β PET, and imaging biomarkers of cerebral amyloid angiopathy (CAA), characterizing different forms of cerebral small vessel disease (CSVD) using multivariable regression. We also used linear regression models to investigate whether WMH spatial distribution influenced cognitive impairment. We analyzed MRI scans of 1,046 ADNI participants with mixed vascular and amyloid-related risk factors (mean age 72.9, 47.7% female, 31.4% hypertensive, 48.3% with abnormal amyloid PET). We observed unbiased partitioning of WMH into 5 unique spatial patterns: deep frontal, periventricular, juxtacortical, parietal, and posterior. Juxtacortical WMH were independently associated with probable CAA, deep frontal WMH were associated with risk factors for arteriolosclerosis (hypertension and diabetes), and parietal WMH were associated with brain amyloid accumulation, consistent with an Alzheimer disease (AD) phenotype. Juxtacortical, deep frontal, and parietal WMH spatial patterns were associated with cognitive impairment. Periventricular and posterior WMH spatial patterns were unrelated to any disease phenotype or cognitive decline. Data-driven WMH spatial patterns reflect discrete underlying etiologies including arteriolosclerosis, CAA, AD, and normal aging. Global measures of WMH volume may miss important spatial distinctions. WMH spatial signatures may serve as etiology-specific imaging markers, helping to resolve WMH heterogeneity, identify the dominant underlying pathologic process, and improve prediction of clinical-relevant trajectories that influence cognitive decline.

Phuah CL ，Chen Y ，Strain JF ，Yechoor N ，Laurido-Soto OJ ，Ances BM ，Lee JM ，Alzheimer's Disease Neuroimaging Initiative ... -  《-》

White matter hyperintensities are higher among early-onset Alzheimer's disease participants than their cognitively normal and early-onset nonAD peers: Longitudinal Early-onset Alzheimer's Disease Study (LEADS).

We compared white matter hyperintensities (WMHs) in early-onset Alzheimer's disease (EOAD) with cognitively normal (CN) and early-onset amyloid-negative cognitively impaired (EOnonAD) groups in the Longitudinal Early-Onset Alzheimer's Disease Study. We investigated the role of increased WMH in cognition and amyloid and tau burden. We compared WMH burden of 205 EOAD, 68 EOnonAD, and 89 CN participants in lobar regions using t-tests and analyses of covariance. Linear regression analyses were used to investigate the association between WMH and cognitive impairment and that between amyloid and tau burden. EOAD showed greater WMHs compared with CN and EOnonAD participants across all regions with no significant differences between CN and EOnonAD groups. Greater WMHs were associated with worse cognition. Tau burden was positively associated with WMH burden in the EOAD group. EOAD consistently showed higher WMH volumes. Overall, greater WMHs were associated with worse cognition and higher tau burden in EOAD. This study represents a comprehensive characterization of WMHs in sporadic EOAD. WMH volumes are associated with tau burden from positron emission tomography (PET) in EOAD, suggesting WMHs are correlated with increasing burden of AD. Greater WMH volumes are associated with worse performance on global cognitive tests. EOAD participants have higher WMH volumes compared with CN and early-onset amyloid-negative cognitively impaired (EOnonAD) groups across all brain regions.

Eloyan A ，Thangarajah M ，An N ，Borowski BJ ，Reddy AL ，Aisen P ，Dage JL ，Foroud T ，Ghetti B ，Griffin P ，Hammers D ，Iaccarino L ，Jack CR Jr ，Kirby K ，Kramer J ，Koeppe R ，Kukull WA ，La Joie R ，Mundada NS ，Murray ME ，Nudelman K ，Rumbaugh M ，Soleimani-Meigooni DN ，Toga A ，Touroutoglou A ，Atri A ，Day GS ，Duara R ，Graff-Radford NR ，Honig LS ，Jones DT ，Masdeu J ，Mendez MF ，Musiek E ，Onyike CU ，Rogalski E ，Salloway S ，Sha S ，Turner RS ，Wingo TS ，Wolk DA ，Womack K ，Beckett L ，Gao S ，Carrillo MC ，Rabinovici G ，Apostolova LG ，Dickerson B ，Vemuri P ，LEADS Consortium ... -  《-》

Topographical differences in white matter hyperintensity burden and cognition in aging, MCI, and AD.

White matter hyperintensities (WMHs) are pathological changes that occur with increased age and are associated with cognitive decline. Most WMH research has not examined regional differences and focuses on a whole-brain approach. This study examined regional WMHs between normal controls (NCs), people with mild cognitive impairment (MCI), and Alzheimer's disease (AD). We also examined whether WMHs were associated with cognitive decline. Participants from the Alzheimer's Disease Neuroimaging Initiative were included if they had at least one WMH measurement and cognitive scores examining global cognition, executive functioning, and memory. Only amyloid-positive MCI and AD participants were included. A total of 1573 participants with 7381 timepoints over a maximum period of 13 years were included. Linear mixed-effects models examined group differences in WMH burden and associations between WMH burden and cognition. People with MCI and AD had increased total and regional WMHs compared to NCs. An association between WMHs and cognition was observed for global cognition, executive functioning, and memory in NCs in all regions. A steeper decline (stronger association between WMH and cognition) was observed in MCI compared to NCs for all cognitive domains in all regions. A steeper decline was observed in AD compared to NCs for global cognition in only the temporal region. A strong association is observed between all cognitive domains of interest and WMH burden in healthy aging and MCI, while those with AD only had a few associations between WMH and global cognition. These findings suggest that the WMH burden is associated with changes in cognition in healthy aging and early cognitive decline.

Kamal F ，Morrison C ，Maranzano J ，Zeighami Y ，Dadar M ... -  《-》