Objectives: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.Methods: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 prior 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.Results: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 five 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’s 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.Discussion: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 pathological process, and improve prediction of clinical-relevant trajectories that influence cognitive decline.

Despite the persistently high prevalence of neurocognitive impairment in HIV-positive patients, routine HIV care in many resource-limited settings does not include neuropsychological assessment. The objective of this study was to examine the utility of a brief computerized battery for identifying neurocognitive impairment in a busy HIV clinic in Uganda. Specifically, we compared performance on a gold standard neuropsychological exam to that on the CogState Brief Battery. In this cross-sectional study, 181 HIV-positive patients completed both assessment batteries in a randomized order. The primary outcome measures were neurocognitive impairment on the standard exam defined by the global deficit score and cumulative performance on the CogState Brief Battery. Sixty-nine participants (38%) were classified as impaired on the standard neuropsychological exam, and participants who were classified as impaired performed significantly worse on CogState compared to those who were unimpaired (p<0.001). CogState had adequate specificity but low sensitivity, suggesting that it may not be a clinically useful screening tool to identify patients who likely have neurocognitive impairment in Uganda. This study supports the feasibility of using a computerized battery for assessing neurocognitive impairment in HIV-positive patients in resource-limited settings, but additional research is needed to identify screening tools with higher sensitivity for use in HIV clinics.