4.7 Article

Structural network alterations and neurological dysfunction in cerebral amyloid angiopathy

Journal

BRAIN
Volume 138, Issue -, Pages 179-188

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/brain/awu316

Keywords

small vessel disease; mild cognitive impairment; stroke: imaging; amyloid imaging; executive function; tractography

Funding

  1. National Institutes of Health [R01 AG26484, R01 NS070834, K23 NS083711, R01NR010827]
  2. American Heart Association [14POST20010031]
  3. Netherlands Organization for Scientific Research (NWO) [VIDI] [639.072.411]
  4. NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R56NS042861, K23NS083711, R01NS070834] Funding Source: NIH RePORTER
  5. NATIONAL INSTITUTE OF NURSING RESEARCH [R01NR010827] Funding Source: NIH RePORTER
  6. NATIONAL INSTITUTE ON AGING [R01AG026484, R01AG047975, P50AG005134] Funding Source: NIH RePORTER

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Cerebral amyloid angiopathy is an important risk factor for cognitive impairment. Reijmer et al. use multimodal MRI and amyloid PET imaging to report changes in the brain network structure, which may represent a key step between small vessel brain disease and cognitive and gait impairment.Cerebral amyloid angiopathy is a common form of small-vessel disease and an important risk factor for cognitive impairment. The mechanisms linking small-vessel disease to cognitive impairment are not well understood. We hypothesized that in patients with cerebral amyloid angiopathy, multiple small spatially distributed lesions affect cognition through disruption of brain connectivity. We therefore compared the structural brain network in patients with cerebral amyloid angiopathy to healthy control subjects and examined the relationship between markers of cerebral amyloid angiopathy-related brain injury, network efficiency, and potential clinical consequences. Structural brain networks were reconstructed from diffusion-weighted magnetic resonance imaging in 38 non-demented patients with probable cerebral amyloid angiopathy (69 +/- 10 years) and 29 similar aged control participants. The efficiency of the brain network was characterized using graph theory and brain amyloid deposition was quantified by Pittsburgh compound B retention on positron emission tomography imaging. Global efficiency of the brain network was reduced in patients compared to controls (0.187 +/- 0.018 and 0.201 +/- 0.015, respectively, P < 0.001). Network disturbances were most pronounced in the occipital, parietal, and posterior temporal lobes. Among patients, lower global network efficiency was related to higher cortical amyloid load (r = -0.52; P = 0.004), and to magnetic resonance imaging markers of small-vessel disease including increased white matter hyperintensity volume (P < 0.001), lower total brain volume (P = 0.02), and number of microbleeds (trend P = 0.06). Lower global network efficiency was also related to worse performance on tests of processing speed (r = 0.58, P < 0.001), executive functioning (r = 0.54, P = 0.001), gait velocity (r = 0.41, P = 0.02), but not memory. Correlations with cognition were independent of age, sex, education level, and other magnetic resonance imaging markers of small-vessel disease. These findings suggest that reduced structural brain network efficiency might mediate the relationship between advanced cerebral amyloid angiopathy and neurologic dysfunction and that such large-scale brain network measures may represent useful outcome markers for tracking disease progression.

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