A Brain Phenotype for Stressor-Evoked Blood Pressure Reactivity

Abstract

Background: Individuals who exhibit large-magnitude blood pressure (BP) reactions to acute psychological stressors are at risk for hypertension and premature death by cardiovascular disease. This study tested whether a multivariate pattern of stressor-evoked brain activity could reliably predict individual differences in BP reactivity, providing novel evidence for a candidate neurophysiological source of stress-related cardiovascular risk.

Methods and results: Community-dwelling adults (N=310; 30-51 years; 153 women) underwent functional magnetic resonance imaging with concurrent BP monitoring while completing a standardized battery of stressor tasks. Across individuals, the battery evoked an increase systolic and diastolic BP relative to a nonstressor baseline period (M ∆systolic BP/∆diastolic BP=4.3/1.9 mm Hg [95% confidence interval=3.7-5.0/1.4-2.3 mm Hg]). Using cross-validation and machine learning approaches, including dimensionality reduction and linear shrinkage models, a multivariate pattern of stressor-evoked functional magnetic resonance imaging activity was identified in a training subsample (N=206). This multivariate pattern reliably predicted both systolic BP (r=0.32; P<0.005) and diastolic BP (r=0.25; P<0.01) reactivity in an independent subsample used for testing and replication (N=104). Brain areas encompassed by the pattern that were strongly predictive included those implicated in psychological stressor processing and cardiovascular responding through autonomic pathways, including the medial prefrontal cortex, anterior cingulate cortex, and insula.

Conclusions: A novel multivariate pattern of stressor-evoked brain activity may comprise a phenotype that partly accounts for individual differences in BP reactivity, a stress-related cardiovascular risk factor.

Keywords: cardiovascular reactivity; functional magnetic resonance imaging; machine learning; mental stress; psychology and behavior; stress.

© 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Figures

Figure 1

The Stroop task and Multi‐Source Interference Task (MSIT) evoked comparable patterns of cardiovascular reactivity across individuals. A, Comparison of systolic blood pressure (SBP), (B) diastolic blood pressure (DBP), and (C) heart rate (HR) reactivity values across tasks.

Figure 2

The Stroop task and Multi‐Source Interference Task (MSIT) evoked comparable changes in brain activity (voxel‐wise r of blood oxygen level dependent (BOLD) signal change=0.88; P<0.001; Dice coefficient for spatial overlap=0.80). Color‐scaled t‐statistic maps of brain areas exhibiting significant BOLD signal changes (incongruent vs congruent condition changes) are shown for the Stroop task (A) and MSIT (B). Maps in (A) and (B) correspond to statistical parametric t‐statistic maps, shown at a false discovery rate threshold of 0.05 to control for multiple statistical testing. The color‐scaled BOLD signal change map in (C) corresponds to the average of the Stroop and MSIT BOLD signal change maps. Task‐averaged BOLD signal change maps across participants were used to generate a final and whole‐brain multivariate brain pattern to predict task‐averaged stressor‐evoked cardiovascular reactivity.

Figure 3

The final whole‐brain and multivariate predictive model (weight map, β^) is shown in (A). A comparison of predicted vs observed stressor‐evoked systolic blood pressure (SBP) reactivity (ΔSBP) in cross‐validation using the independent test sample of N=104 (not used in training) is shown in (B), r=0.32, P=0.001. C, A receiver operating characteristic curve illustrating the sensitivity and specificity of the whole‐brain multivariate pattern in predicting different cut‐off values (labeled as c) of stressor‐evoked SBP reactivity (ΔSBP in mm Hg) across individuals in the test sample of N=104. For example, c4 corresponds to ΔSBP of 4 mm Hg.

Figure 4

Multivariate pattern (weight map) used to predict stressor‐evoked systolic blood pressure (SBP) reactivity. Here, the map is shown at a threshold of P<0.05, based on 1000 nonparametric permutations, along with an extent threshold of k=50 voxels for illustration and interpretation only (the entire whole‐brain multivariate pattern was used in training and testing; see Figure 3). Warmer colors (orange/yellow) in the medial surface projections in (A) and (B) and regions of the insula shown in (C) reflect a positive predictive association between brain activity and SBP reactivity, whereas cooler colors (blue) reflect a negative association. Labeled in the medial surface projections in (A) and (B) are the ventromedial prefrontal cortex (vmPFC), perigenual anterior cingulate cortex (pgACC), and dorsal anterior cingulate cortex (dACC). Axial views of the left insula and right insula (extending into the operculum) in (C) are shown at Montreal Neurological Institute z coordinates of 0 and 8, respectively. A full listing of areas revealed after random permutation thresholding of the whole‐brain multivariate pattern is in Tables S3 and S4.