Vascular risk factor burden correlates with cerebrovascular reactivity but not resting state coactivation in the default mode network

White matter hyperintensities (WMH) are common in older adults and linked to cognitive decline, stroke, and dementia. Vascular risk factors (VRFs) such as high blood pressure contribute to WMH, but their effect on gray matter function is unclear. In 29 participants with suspected WMH, those with more VRFs showed lower cerebrovascular reactivity (CVR) in the default-mode network (DMN), measured using a dual-regression analysis of BOLD imaging during hypercapnia. CVR in the DMN also correlated with resting-state coactivation. No differences were found in sensory-motor or medial-visual networks. The findings suggest that multiple VRFs may impair blood flow regulation in key brain networks.

Study at a glance

Abstract

PURPOSE: White matter hyperintensities (WMH) are prevalent among older adults and are often associated with cognitive decline and increased risk of stroke and dementia. Vascular risk factors (VRFs) are linked to WMH, yet the impact of multiple VRFs on gray matter function is still unclear. The goal of this study was to test for associations between the number of VRFs and cerebrovascular reactivity (CVR) and resting state (RS) coactivation among individuals with WMH. MATERIALS AND METHODS: Twenty-nine participants with suspected WMH were grouped based on the number of VRFs (subgroups: 0, 1, or ≥2). CVR and RS coactivation were measured with blood oxygenation level-dependent (BOLD) imaging on a 3T magnetic resonance imaging (MRI) system during hypercapnia and rest, respectively. Default-mode (DMN), sensory-motor, and medial-visual networks, generated using independent component analysis of RS-BOLD, were selected as networks of interest (NOIs). CVR-BOLD was analyzed using two methods: 1) a model-based approach using CO2 traces, and 2) a dual-regression (DR) approach using NOIs as spatial inputs. Average CVR and RS coactivations within NOIs were compared between VRF subgroups. A secondary analysis investigated the correlation between CVR and RS coactivation. RESULTS: VRF subgroup differences were detected using DR-based CVR in the DMN (F20,2 = 5.17, P = 0.015) but not the model-based CVR nor RS coactivation. DR-based CVR was correlated with RS coactivation in the DMN (r(2) = 0.28, P = 0.006) but not the sensory-motor nor medial-visual NOIs. CONCLUSION: In individuals with WMH, CVR in the DMN was inversely associated with the number of VRFs and correlated with RS coactivation.