No association between cardiometabolic risk and neural reactivity to acute psychosocial stress

Perceived stress modulates the activity between the amygdala and the cortex

The significant link between stress and psychiatric disorders has prompted research on stress's impact on the brain. Interestingly, previous studies on healthy subjects have demonstrated an association between perceived stress and amygdala volume, although the mechanisms by which perceived stress can affect brain function remain unknown. To better understand what this association entails at a functional level, herein, we explore the association of perceived stress, measured by the PSS10 questionnaire, with disseminated functional connectivity between brain areas. Using resting-state fMRI from 252 healthy subjects spanning a broad age range, we performed both a seed-based amygdala connectivity analysis (static connectivity, with spatial resolution but no temporal definition) and a whole-brain data-driven approach to detect altered patterns of phase interactions between brain areas (dynamic connectivity with spatiotemporal information). Results show that increased perceived stress is directly associated with increased amygdala connectivity with frontal cortical regions, which is driven by a reduced occurrence of an activity pattern where the signals in the amygdala and the hippocampus evolve in opposite directions with respect to the rest of the brain. Overall, these results not only reinforce the pathological effect of in-phase synchronicity between subcortical and cortical brain areas but also demonstrate the protective effect of counterbalanced (i.e., phase-shifted) activity between brain subsystems, which are otherwise missed with correlation-based functional connectivity analysis.

Association of amygdala size with stress perception: Findings of a transversal study across the lifespan

Daily routines are getting increasingly stressful. Interestingly, associations between stress perception and amygdala volume, a brain region implicated in emotional behaviour, have been observed in both younger and older adults. Life stress, on the other hand, has become pervasive and is no longer restricted to a specific age group or life stage. As a result, it is vital to consider stress as a continuum across the lifespan. In this study, we investigated the relationship between perceived stress and amygdala size in 272 healthy participants with a broad age range. Participants were submitted to a structural magnetic resonance imaging (MRI) to extract amygdala volume, and the Perceived Stress Scale (PSS) scores were used as the independent variable in volumetric regressions. We found that perceived stress is positively associated with the right amygdala volume throughout life.

Spatiotemporal Dynamics of Stress-Induced Network Reconfigurations Reflect Negative Affectivity

BACKGROUND

Maladaptive stress responses are important risk factors in the etiology of mood and anxiety disorders, but exact pathomechanisms remain to be understood. Mapping individual differences of acute stress-induced neurophysiological changes, especially on the level of neural activation and functional connectivity (FC), could provide important insights in how variation in the individual stress response is linked to disease risk.

METHODS

Using an established psychosocial stress task flanked by two resting states, we measured subjective, physiological, and brain responses to acute stress and recovery in 217 participants with and without mood and anxiety disorders. To estimate blockwise changes in stress-induced activation and FC, we used hierarchical mixed-effects models based on denoised time series within predefined stress-related regions. We predicted inter- and intraindividual differences in stress phases (anticipation vs. stress vs. recovery) and transdiagnostic dimensions of stress reactivity using elastic net and support vector machines.

RESULTS

We identified four subnetworks showing distinct changes in FC over time. FC but not activation trajectories predicted the stress phase (accuracy = 70%, p_perm < .001) and increases in heart rate (R² = 0.075, p_perm < .001). Critically, individual spatiotemporal trajectories of changes across networks also predicted negative affectivity (ΔR² = 0.075, p_perm = .030) but not the presence or absence of a mood and anxiety disorder.

CONCLUSIONS

Spatiotemporal dynamics of brain network reconfiguration induced by stress reflect individual differences in the psychopathology dimension of negative affectivity. These results support the idea that vulnerability for mood and anxiety disorders can be conceptualized best at the level of network dynamics, which may pave the way for improved prediction of individual risk.

Integrating multiple brain imaging modalities does not boost prediction of subclinical atherosclerosis in midlife adults

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Brain measures from MRI do not improve Framingham Risk Score prediction of CA-IMT.

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Prediction stacking is a flexible approach to determine added predictive utility.

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Multimodal stacking can be applied to individual difference factors.

Background

Human neuroimaging evidence suggests that cardiovascular disease (CVD) risk may relate to functional and structural features of the brain. The present study tested whether combining functional and structural (multimodal) brain measures, derived from magnetic resonance imaging (MRI), would yield a multivariate brain biomarker that reliably predicts a subclinical marker of CVD risk, carotid-artery intima-media thickness (CA-IMT).

Methods

Neuroimaging, cardiovascular, and demographic data were assessed in 324 midlife and otherwise healthy adults who were free of (a) clinical CVD and (b) use of medications for chronic illnesses (aged 30–51 years, 49% female). We implemented a prediction stacking algorithm that combined multimodal brain imaging measures and Framingham Risk Scores (FRS) to predict CA-IMT. We included imaging measures that could be easily obtained in clinical settings: resting state functional connectivity and structural morphology measures from T1-weighted images.

Results

Our models reliably predicted CA-IMT using FRS, as well as for several individual MRI measures; however, none of the individual MRI measures outperformed FRS. Moreover, stacking functional and structural brain measures with FRS did not boost prediction accuracy above that of FRS alone.

Conclusions

Combining multimodal functional and structural brain measures through a stacking algorithm does not appear to yield a reliable brain biomarker of subclinical CVD, as reflected by CA-IMT.

Affective brain patterns as multivariate neural correlates of cardiovascular disease risk

This study tested whether brain activity patterns evoked by affective stimuli relate to individual differences in an indicator of pre-clinical atherosclerosis: carotid artery intima-media thickness (CA-IMT). Adults (aged 30-54 years) completed functional magnetic resonance imaging (fMRI) tasks that involved viewing three sets of affective stimuli. Two sets included facial expressions of emotion, and one set included neutral and unpleasant images from the International Affective Picture System (IAPS). Cross-validated, multivariate and machine learning models showed that individual differences in CA-IMT were partially predicted by brain activity patterns evoked by unpleasant IAPS images, even after accounting for age, sex and known cardiovascular disease risk factors. CA-IMT was also predicted by brain activity patterns evoked by angry and fearful faces from one of the two stimulus sets of facial expressions, but this predictive association did not persist after accounting for known cardiovascular risk factors. The reliability (internal consistency) of brain activity patterns evoked by affective stimuli may have constrained their prediction of CA-IMT. Distributed brain activity patterns could comprise affective neural correlates of pre-clinical atherosclerosis; however, the interpretation of such correlates may depend on their psychometric properties, as well as the influence of other cardiovascular risk factors and specific affective cues.

Stress Reactivity as a Contributor to Racial and Socioeconomic Disparities: Rationale and Baseline Results From the Richmond Stress and Sugar Study

OBJECTIVE

There are pronounced racial and socioeconomic disparities in type 2 diabetes. Although "stress" as a general phenomenon is hypothesized to contribute to these disparities, few studies have objective measures of stress reactivity in diverse samples to test hypotheses about purported mechanisms. This study describes the rationale and baseline characteristics of a cohort designed to address the question: how does stress contribute to disparities in diabetes risk?

METHODS

The Richmond Stress and Sugar Study recruited 125 adults at elevated risk of type 2 diabetes using a two-by-two sampling frame wherein non-Hispanic whites and African Americans (AAs) were each recruited from neighborhoods of higher and lower socioeconomic status (SES). Stress reactivity was assessed using the Trier Social Stress Test (TSST) and salivary cortisol. Analyses of variance and multilevel modeling were used to examine how stress reactivity varied both within and across race and neighborhood SES.

RESULTS

The mean (SD) age was 57.4 (7.3) years, 49% were female, 54% were AA or another racial/ethnic minority, and mean hemoglobin A1c level was in the prediabetes range (5.8%; range, 5.50%-5.93%). Living in a lower-SES neighborhood was associated with 16% (95% confidence interval [CI] = -0.04 to 34) higher pre-TSST cortisol, 8.4% (95% CI = -14 to -3) shallower increase in response to the TSST, and 1% (95% CI = 0.3 to 1.7) steeper decline post-TSST than living in the higher neighborhood SES. Post-TSST cortisol decline was 3% greater among AA compared with non-Hispanic whites. Race-by-SES interaction terms were generally small and nonsignificant.

CONCLUSIONS

SES is associated with stress reactivity among adults at high risk of diabetes.

Frontostriatal Brain Activation Is Associated With the Longitudinal Progression of Cardiometabolic Risk

OBJECTIVE

Cardiometabolic risk refers to a set of interconnected factors of vascular and metabolic origin associated with both cardiovascular disease and various brain disorders. Although midlife cardiometabolic risk is associated with future brain dysfunction, emerging evidence suggests that alterations in autonomic and central nervous system function may precede increases in cardiometabolic risk.

METHODS

The present study tested whether patterns of cerebral blood flow in brain areas associated with autonomic regulation were associated with increases in overall cardiometabolic risk. A community sample of 109 adults with resting systolic blood pressure between 120 and 139 mm Hg, diastolic blood pressure between 80 and 89 mm Hg, or both underwent pseudocontinuous arterial spin labeling to quantify cerebral blood flow responses to cognitively challenging tasks. Cardiometabolic risk and cerebral blood flow measurements were collected at baseline and at a 2-year follow-up.

RESULTS

Regression analyses showed that greater frontostriatal cerebral blood flow responses to cognitive challenge were associated with higher cardiometabolic risk at follow-up (β = 0.26 [95% confidence interval = 0.07 to 0.44], t = 2.81, p = .006, ΔR = 0.04). These findings were specific to frontostriatal brain regions, as frontoparietal, insular-subcortical, and total cerebral blood flow were not associated with progression of cardiometabolic risk. Moreover, cardiometabolic risk was not associated with frontostriatal cerebral blood flow responses 2 years later.

CONCLUSIONS

Frontostriatal brain function may precede and possibly forecast the progression of cardiometabolic risk.