Associations between arterial stiffening and brain structure, perfusion, and cognition in the Whitehall II Imaging Sub-study: A retrospective cohort study

Abstract

Background: Aortic stiffness is closely linked with cardiovascular diseases (CVDs), but recent studies suggest that it is also a risk factor for cognitive decline and dementia. However, the brain changes underlying this risk are unclear. We examined whether aortic stiffening during a 4-year follow-up in mid-to-late life was associated with brain structure and cognition in the Whitehall II Imaging Sub-study.

Methods and findings: The Whitehall II Imaging cohort is a randomly selected subset of the ongoing Whitehall II Study, for which participants have received clinical follow-ups for 30 years, across 12 phases. Aortic pulse wave velocity (PWV) was measured in 2007-2009 (Phase 9) and at a 4-year follow-up in 2012-2013 (Phase 11). Between 2012 and 2016 (Imaging Phase), participants received a multimodal 3T brain magnetic resonance imaging (MRI) scan and cognitive tests. Participants were selected if they had no clinical diagnosis of dementia and no gross brain structural abnormalities. Voxel-based analyses were used to assess grey matter (GM) volume, white matter (WM) microstructure (fractional anisotropy (FA) and diffusivity), white matter lesions (WMLs), and cerebral blood flow (CBF). Cognitive outcomes were performance on verbal memory, semantic fluency, working memory, and executive function tests. Of 542 participants, 444 (81.9%) were men. The mean (SD) age was 63.9 (5.2) years at the baseline Phase 9 examination, 68.0 (5.2) at Phase 11, and 69.8 (5.2) at the Imaging Phase. Voxel-based analysis revealed that faster rates of aortic stiffening in mid-to-late life were associated with poor WM microstructure, viz. lower FA, higher mean, and radial diffusivity (RD) in 23.9%, 11.8%, and 22.2% of WM tracts, respectively, including the corpus callosum, corona radiata, superior longitudinal fasciculus, and corticospinal tracts. Similar voxel-wise associations were also observed with follow-up aortic stiffness. Moreover, lower mean global FA was associated with faster rates of aortic stiffening (B = -5.65, 95% CI -9.75, -1.54, Bonferroni-corrected p < 0.0125) and higher follow-up aortic stiffness (B = -1.12, 95% CI -1.95, -0.29, Bonferroni-corrected p < 0.0125). In a subset of 112 participants who received arterial spin labelling scans, faster aortic stiffening was also related to lower cerebral perfusion in 18.4% of GM, with associations surviving Bonferroni corrections in the frontal (B = -10.85, 95% CI -17.91, -3.79, p < 0.0125) and parietal lobes (B = -12.75, 95% CI -21.58, -3.91, p < 0.0125). No associations with GM volume or WMLs were observed. Further, higher baseline aortic stiffness was associated with poor semantic fluency (B = -0.47, 95% CI -0.76 to -0.18, Bonferroni-corrected p < 0.007) and verbal learning outcomes (B = -0.36, 95% CI -0.60 to -0.12, Bonferroni-corrected p < 0.007). As with all observational studies, it was not possible to infer causal associations. The generalisability of the findings may be limited by the gender imbalance, high educational attainment, survival bias, and lack of ethnic and socioeconomic diversity in this cohort.

Conclusions: Our findings indicate that faster rates of aortic stiffening in mid-to-late life were associated with poor brain WM microstructural integrity and reduced cerebral perfusion, likely due to increased transmission of pulsatile energy to the delicate cerebral microvasculature. Strategies to prevent arterial stiffening prior to this point may be required to offer cognitive benefit in older age.

Trial registration: ClinicalTrials.gov NCT03335696.

Fig 1. Association of aortic stiffening with WM microstructure and CBF.

Higher aortic stiffening was associated with (A) higher RD, (B) higher AD, (C) lower FA, (D) higher MD, and (E) lower CBF. Associations with Phase 9 PWV, Phase 11 PWV, and ΔPWV are presented in pink, blue, and red yellow, respectively. Five horizontal slices are displayed with MNI152 coordinates ranging from Z = 65 to Z = 105 for WM and Z = 56 to Z = 104 for CBF. The WM clusters are overlaid on the study-specific mean FA skeleton (green) and the standard FMRIB58 FA image, and the CBF clusters are overlaid on the standard MNI152 brain. All results are thresholded at p < 0.05 (TFCE and FWE-corrected p-values) and are presented with a colour gradient for 1 p-values. AD, axial diffusivity; CBF, cerebral blood flow; FA, fractional anisotropy; FWE, family-wise error; L, left; MD, mean diffusivity; PWV, pulse wave velocity; R, right; RD, radial diffusivity; TFCE, threshold-free cluster enhancement; WM, white matter.

Fig 2. Partial regression plots showing the associations of PWV with brain and cognitive outcomes which survived Bonferroni correction for multiple comparisons.

Plots present estimated marginal means for (A, B) Predicted global FA, (C) Predicted CBF from frontal (green) and parietal (orange) lobes, and (D) Predicted memory performance on semantic fluency (green) and verbal learning (orange) tests, plotted against (A,C) Rate of change of PWV, (B) PWV at Phase 11, and (D) PWV at Phase 9. Estimated marginal means are derived from linear regression models adjusted for age, MAP, BMI, and antihypertensive treatment measured at the respective phase (9 or 11), number of years from the respective phase (9 or 11) to the MRI scan, and sex, education, socioeconomic status, and MRI scanner model. BMI, body mass index; CBF, cerebral blood flow; FA, fractional anisotropy; MAP, mean arterial pressure; MRI, magnetic resonance imaging; PWV, pulse wave velocity.