RESUMEN
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.
Asunto(s)
Presión Sanguínea , Encéfalo/fisiopatología , Sistema Cardiovascular/fisiopatología , Estrés Psicológico/fisiopatología , Adulto , Encéfalo/diagnóstico por imagen , Mapeo Encefálico/métodos , Análisis Discriminante , Femenino , Humanos , Modelos Lineales , Aprendizaje Automático , Imagen por Resonancia Magnética , Masculino , Persona de Mediana Edad , Análisis Multivariante , Pruebas Neuropsicológicas , Fenotipo , Análisis de Componente Principal , Factores de Riesgo , Estrés Psicológico/diagnóstico por imagen , Estrés Psicológico/psicologíaRESUMEN
Developing prospective models of resilience using the translational and transdiagnostic framework proposed in the target article is a challenging endeavor and will require large-scale data sets with dense intraindividual temporal sampling and innovative analytic methods.