Acute and chronic stress are important factors in the development of mental disorders. Reliable measurement of stress reactivity is therefore pivotal. Critically, experimental induction of stress ...often involves multiple “hits” and it is an open question whether individual differences in responses to an earlier stressor lead to habituation, sensitization, or simple additive effects on following events. Here, we investigated the effect of the individual cortisol response to intravenous catheter placement (IVP) on subsequent neural, psychological, endocrine, and autonomous stress reactivity. We used an established psychosocial stress paradigm to measure the acute stress response (Stress) and recovery (PostStress) in 65 participants. Higher IVP‐induced cortisol responses were associated with lower pulse rate increases during stress recovery (b = −4.8 bpm, p = .0008) and lower increases in negative affect after the task (b = −4.2, p = .040). While the cortisol response to IVP was not associated with subsequent specific stress‐induced neural activation patterns, the similarity of brain responses Pre‐ and PostStress was higher IVP‐cortisol responders (t64 = 2.35, p = .022) indicating faster recovery. In conclusion, preparatory stress induced by IVP reduced reactivity in a subsequent stress task by modulating the latency of stress recovery. Thus, an individually stronger preceding release of cortisol may attenuate a second physiological response and perceived stress suggesting that relative changes, not absolute levels are crucial for stress attribution. Our study highlights that considering the entire trajectory of stress induction during an experiment is important to develop reliable individual biomarkers.
Stress often involves multiple “hits” and it is an open question whether individual differences in responses to an earlier stressor lead to habituation, sensitization, or additive effects. Here, we show that a cortisol response to the placement of an intravenous catheter attenuated reactivity to a subsequent psychosocial stress task on the neural, endocrine, autonomous, and subjective level.
Summary Homeostasis of the human stress response system is critically maintained by a hierarchical system of neural and endocrine elements for which intact negative feedback is important to prevent ...maladaptation towards stress. Such feedback is efficiently probed by the established combined dexamethasone-suppression/corticotropin-releasing hormone stimulation (dex/CRH) test. Here we investigate which suprahypothalamic networks might modulate the response assessed by this neuroendocrine test. Combined resting state fMRI (rs-fMRI)/EEG was acquired in 20 healthy male volunteers along with dex/CRH profiles obtained on a different day outside the scanner. Seed-based network analysis and inter-seed cross correlation analysis for selected atlas-based limbic, paralimbic and medial prefrontal cortex seeds were correlated with stimulated cortisol and adrenocorticotropin hormone (ACTH) concentrations. Lower connectivity between a left hippocampus-based network and the right hippocampus significantly predicted stimulated cortisol concentration ( R2 = 0.70, corrected pcluster = 0.001). Six further significantly negative correlations were detected mainly in the left anterior cingulate cortex (ACC) and the medial prefrontal cortex (mPFC). The strongest positive correlation with stimulated hormone concentration was detected for the left subcallosal ACC (ACTH, R2 = 0.57, corrected pcluster = 0.009). Inter-seed connectivity mainly pointed to hippocampal/amygdala interactions as correlates of the dex/CRH response. In conclusion, resting state functional connectivity patterns of limbic, particularly hippocampal, as well as cingulate and medial prefrontal areas can explain some of the variance of the dex/CRH test in healthy subjects. Functional connectivity analysis can be considered useful to study supra-hypothalamic control systems of the HPA axis.
We investigated human hippocampal functional connectivity in wakefulness and throughout non-rapid eye movement sleep. Young healthy subjects underwent simultaneous EEG and functional magnetic ...resonance imaging (fMRI) measurements at 1.5 T under resting conditions in the descent to deep sleep. Continuous 5 min epochs representing a unique sleep stage (i.e., wakefulness, sleep stages 1 and 2, or slow-wave sleep) were extracted. fMRI time series of subregions of the hippocampal formation (HF) (cornu ammonis, dentate gyrus, and subiculum) were extracted based on cytoarchitectonical probability maps. We observed sleep stage-dependent changes in HF functional coupling. The HF was integrated to variable strength in the default mode network (DMN) in wakefulness and light sleep stages but not in slow-wave sleep. The strongest functional connectivity between the HF and neocortex was observed in sleep stage 2 (compared with both slow-wave sleep and wakefulness). We observed a strong interaction of sleep spindle occurrence and HF functional connectivity in sleep stage 2, with increased HF/neocortical connectivity during spindles. Moreover, the cornu ammonis exhibited strongest functional connectivity with the DMN during wakefulness, while the subiculum dominated hippocampal functional connectivity to frontal brain regions during sleep stage 2. Increased connectivity between HF and neocortical regions in sleep stage 2 suggests an increased capacity for possible global information transfer, while connectivity in slow-wave sleep is reflecting a functional system optimal for segregated information reprocessing. Our data may be relevant to differentiating sleep stage-specific contributions to neural plasticity as proposed in sleep-dependent memory consolidation.
Increasing age is tightly linked to decreased thickness of the human neocortex. The biological mechanisms that mediate this effect are hitherto unknown. The DNA methylome, as part of the epigenome, ...contributes significantly to age-related phenotypic changes. Here, we identify an epigenetic signature that is associated with cortical thickness (P=3.86 × 10
) and memory performance in 533 healthy young adults. The epigenetic effect on cortical thickness was replicated in a sample comprising 596 participants with major depressive disorder and healthy controls. The epigenetic signature mediates partially the effect of age on cortical thickness (P<0.001). A multilocus genetic score reflecting genetic variability of this signature is associated with memory performance (P=0.0003) in 3,346 young and elderly healthy adults. The genomic location of the contributing methylation sites points to the involvement of specific immune system genes. The decomposition of blood methylome-wide patterns bears considerable potential for the study of brain-related traits.
Alterations in regional subcortical brain volumes have been investigated as part of the efforts of an international consortium, ENIGMA, to identify reliable neural correlates of major depressive ...disorder (MDD). Given that subcortical structures are comprised of distinct subfields, we sought to build significantly from prior work by precisely mapping localized MDD‐related differences in subcortical regions using shape analysis. In this meta‐analysis of subcortical shape from the ENIGMA‐MDD working group, we compared 1,781 patients with MDD and 2,953 healthy controls (CTL) on individual measures of shape metrics (thickness and surface area) on the surface of seven bilateral subcortical structures: nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Harmonized data processing and statistical analyses were conducted locally at each site, and findings were aggregated by meta‐analysis. Relative to CTL, patients with adolescent‐onset MDD (≤ 21 years) had lower thickness and surface area of the subiculum, cornu ammonis (CA) 1 of the hippocampus and basolateral amygdala (Cohen's d = −0.164 to −0.180). Relative to first‐episode MDD, recurrent MDD patients had lower thickness and surface area in the CA1 of the hippocampus and the basolateral amygdala (Cohen's d = −0.173 to −0.184). Our results suggest that previously reported MDD‐associated volumetric differences may be localized to specific subfields of these structures that have been shown to be sensitive to the effects of stress, with important implications for mapping treatments to patients based on specific neural targets and key clinical features.
Major depressive disorder (MDD) is associated with abnormal neural circuitry. It can be measured by assessing functional connectivity (FC) at resting-state functional MRI, that may help identifying ...neural markers of MDD and provide further efficient diagnosis and monitor treatment outcomes. The main aim of the present study is to investigate, in an unbiased way, functional alterations in patients with MDD using a large multi-center dataset from the PsyMRI consortium including 1546 participants from 19 centers ( www.psymri.com ). After applying strict exclusion criteria, the final sample consisted of 606 MDD patients (age: 35.8 ± 11.9 y.o.; females: 60.7%) and 476 healthy participants (age: 33.3 ± 11.0 y.o.; females: 56.7%). We found significant relative hypoconnectivity within somatosensory motor (SMN), salience (SN) networks and between SMN, SN, dorsal attention (DAN), and visual (VN) networks in MDD patients. No significant differences were detected within the default mode (DMN) and frontoparietal networks (FPN). In addition, alterations in network organization were observed in terms of significantly lower network segregation of SMN in MDD patients. Although medicated patients showed significantly lower FC within DMN, FPN, and SN than unmedicated patients, there were no differences between medicated and unmedicated groups in terms of network organization in SMN. We conclude that the network organization of cortical networks, involved in processing of sensory information, might be a more stable neuroimaging marker for MDD than previously assumed alterations in higher-order neural networks like DMN and FPN.
Object
In humans, even a single night of partial sleep deprivation (PSD) can have a negative impact on cognition and affective processing, suggesting that sleep pressure represents a basic ...physiological constraint of brain function. Among the spontaneously fluctuating resting state networks, the default mode network (DMN) and its anticorrelated network (ACN) hold key functions in segregating internally and externally directed awareness. Task fMRI after sleep deprivation has revealed altered activation patterns in both networks. We hypothesized that effects of PSD in these intrinsically coupled networks can be detected by resting state fMRI.
Methods
We obtained 6-minute echoplanar imaging time series (1.5 Tesla) during eyes-closed, wakeful-resting experiments from 16 healthy volunteers after normal sleep and after PSD. We used independent component and cross-correlation analysis to study functional connectivity (fc), focusing on the DMN and ACN.
Results
After PSD, focal reductions of auto-correlation strength were detected in the posterior and anterior midline node of the DMN and in the lateral parietal and insular nodes of the ACN. Cross-correlation analysis confirmed reduced cortico-cortical connectivity within and between the DMN and ACN.
Conclusions
Increased sleep pressure is reflected in reduced fc of main DMN and ACN nodes during rest. Results have implications for understanding perceptual and cognitive changes after sleep deprivation and are relevant to clinical studies on conditions in which increased sleep propensity is present.
Abstract Dysfunctional limbic, paralimbic and prefrontal brain circuits represent neural substrates of major depression that are targeted by pharmacotherapy. In a high resolution structural magnetic ...resonance imaging (MRI) study we investigated the potential of variability of the cortex volume to predict the response to antidepressant treatment among patients with major depression. We enrolled 167 patients participating in the Munich Antidepressant Response Signature (MARS) study and employed voxel based morphometry to investigate covariation of gray matter (GM) maps with changes of depression severity over 5 weeks. Larger left hippocampal and bilateral posterior cingulate GM volumes and lower right temporolateral GM volumes were associated with beneficial treatment response. Subcallosal/orbitofrontal GM volumes were associated with treatment response mainly through gender-by-region interactions. A hippocampal/temporolateral composite marker proved robust in both first episode and recurrent unipolar patients and in bipolar patients. Compared with 92 healthy controls, abnormally low volumes were only detected in the left hippocampal area, particularly in recurrent unipolar patients. These findings indicate that variability of the cortex volume of specific brain areas is associated with different response to antidepressants. In addition, hippocampal findings recursively link together unfavorable treatment response and progressive hippocampal structural changes in recurrent depression.
The identification of generalizable treatment response classes (TRCs) in major depressive disorder (MDD) would facilitate comparisons across studies and the development of treatment prediction ...algorithms. Here, we investigated whether such stable TRCs can be identified and predicted by clinical baseline items. We analyzed data from an observational MDD cohort (Munich Antidepressant Response Signature MARS study, N = 1017), treated individually by psychopharmacological and psychotherapeutic means, and a multicenter, partially randomized clinical/pharmacogenomic study (Genome-based Therapeutic Drugs for Depression GENDEP, N = 809). Symptoms were evaluated up to week 16 (or discharge) in MARS and week 12 in GENDEP. Clustering was performed on 809 MARS patients (discovery sample) using a mixed model with the integrated completed likelihood criterion for the assessment of cluster stability, and validated through a distinct MARS validation sample and GENDEP. A random forest algorithm was used to identify prediction patterns based on 50 clinical baseline items. From the clustering of the MARS discovery sample, seven TRCs emerged ranging from fast and complete response (average 4.9 weeks until discharge, 94% remitted patients) to slow and incomplete response (10% remitted patients at week 16). These proved stable representations of treatment response dynamics in both the MARS and the GENDEP validation sample. TRCs were strongly associated with established response markers, particularly the rate of remitted patients at discharge. TRCs were predictable from clinical items, particularly personality items, life events, episode duration, and specific psychopathological features. Prediction accuracy improved significantly when cluster-derived slopes were modelled instead of individual slopes. In conclusion, model-based clustering identified distinct and clinically meaningful treatment response classes in MDD that proved robust with regard to capturing response profiles of differently designed studies. Response classes were predictable from clinical baseline characteristics. Conceptually, model-based clustering is translatable to any outcome measure and could advance the large-scale integration of studies on treatment efficacy or the neurobiology of treatment response.
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