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Inter-individual variation in blood pressure is associated with regional white matter integrity in generally healthy older adults.

David H Salat | Victoria J Williams | Elizabeth C Leritz | David M Schnyer | James L Rudolph | Lewis A Lipsitz | Regina E McGlinchey | William P Milberg
NeuroImage | 2012

Prior studies have documented a range of brain changes that occur as a result of healthy aging as well as neural alterations due to profound dysregulation in vascular health such as extreme hypertension, cerebrovascular disease and stroke. In contrast, little information exists about the more transitionary state between the normal and abnormal physiology that contributes to vascular disease and cognitive decline. Specifically, little information exists with regard to the influence of systemic vascular physiology on brain tissue structure in older individuals with low risk for cerebrovascular disease and with no evidence of cognitive impairment. We examined the association between resting blood pressure and diffusion tensor imaging (DTI) indices of white matter microstructure in 128 healthy older adults (43-87 years) spanning the normotensive to moderate-severe hypertensive range. Mean arterial blood pressure (MABP) was related to diffusion measures in several regions of the brain with greatest associations in the anterior corpus callosum and lateral frontal, precentral, superior frontal, lateral parietal and precuneus white matter. Associations between white matter integrity and blood pressure remained when controlling for age, when controlling for white matter lesions, and when limiting the analyses to only normotensive, pharmacologically controlled and pre-hypertensive individuals. Of the diffusion measures examined, associations were strongest between MABP and radial diffusivity which may indicate that blood pressure has an influence on myelin structure. Associations between MABP and white matter integrity followed spatial patterns resembling those often attributed to the effects of chronological age, suggesting that systemic cerebrovascular health may play a role in neural tissue degeneration classically ascribed to aging. These results demonstrate the importance of the consideration of vascular physiology in studies of cognitive and neural aging, and that this significance extends to even the normotensive and medically controlled population. These data additionally suggest that optimal management of blood pressure may require consideration of the more subtle influence of vascular health on neural health in addition to the primary goal of prevention of a major cerebrovascular event.

Pubmed ID: 21820060

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Associated grants

  • Agency: NINDS NIH HHS, United States
    Id: K23 NS062148-02S1
  • Agency: NINDS NIH HHS, United States
    Id: K23NS062148
  • Agency: NIA NIH HHS, United States
    Id: P60AG08812
  • Agency: NIA NIH HHS, United States
    Id: K01AG24898
  • Agency: NINDS NIH HHS, United States
    Id: K23 NS062148
  • Agency: NIA NIH HHS, United States
    Id: P60 AG008812
  • Agency: NINDS NIH HHS, United States
    Id: K23 NS062148-01
  • Agency: NINR NIH HHS, United States
    Id: R01NR010827
  • Agency: NINR NIH HHS, United States
    Id: R01 NR010827-02
  • Agency: NINR NIH HHS, United States
    Id: R01 NR010827
  • Agency: NIA NIH HHS, United States
    Id: K01 AG024898-02
  • Agency: NIA NIH HHS, United States
    Id: K01 AG024898
  • Agency: NINDS NIH HHS, United States
    Id: K23NS062148S1
  • Agency: NIA NIH HHS, United States
    Id: T32 AG023480
  • Agency: NINR NIH HHS, United States
    Id: R01 NR010827-01A1
  • Agency: NIA NIH HHS, United States
    Id: P60 AG008812-15

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FreeSurfer (tool)

RRID:SCR_001847

Open source software suite for processing and analyzing human brain MRI images. Used for reconstruction of brain cortical surface from structural MRI data, and overlay of functional MRI data onto reconstructed surface. Contains automatic structural imaging stream for processing cross sectional and longitudinal data. Provides anatomical analysis tools, including: representation of cortical surface between white and gray matter, representation of the pial surface, segmentation of white matter from rest of brain, skull stripping, B1 bias field correction, nonlinear registration of cortical surface of individual with stereotaxic atlas, labeling of regions of cortical surface, statistical analysis of group morphometry differences, and labeling of subcortical brain structures.Operating System: Linux, macOS.

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