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Stressful life events are an important cause of psychopathology. Humans exposed to aversive or stressful experiences show considerable inter-individual heterogeneity in their responses. However, the majority does not develop stress-related psychiatric disorders. The dynamic processes encompassing positive and functional adaptation in the face of significant adversity have been broadly defined as . Traditionally, the assessment of resilience has been confined to self-report measures, both within the general community and putative high-risk populations. Although this approach has value, it is highly susceptible to subjective bias and may not capture the dynamic nature of resilience, as underlying construct. Recognizing the obvious benefits of more objective measures of resilience, research in the field has just started investigating the predictive value of several potential biological markers. This review provides an overview of theoretical views and empirical evidence suggesting that individual differences in heart rate variability (HRV), a surrogate index of resting cardiac vagal outflow, may underlie different levels of resilience toward the development of stress-related psychiatric disorders. Following this line of thought, recent studies describing associations between regional brain morphometric characteristics and resting state vagally-mediated HRV are summarized. Existing studies suggest that the structural morphology of the anterior cingulated cortex (ACC), particularly its cortical thickness, is implicated in the expression of individual differences in HRV. These findings are discussed in light of emerging structural neuroimaging research, linking morphological characteristics of the ACC to psychological traits ascribed to a high-resilient profile and abnormal structural integrity of the ACC to the psychophysiological expression of stress-related mental health consequences. We conclude that a multidisciplinary approach integrating brain structural imaging with HRV monitoring could offer novel perspectives about brain-body pathways in resilience and adaptation to psychological stress.

Background Home treatment in child and adolescent psychiatry offers an alternative to conventional inpatient treatment by involving the patient’s family, school, and peers more directly in therapy. Although several reviews have summarised existing home treatment programmes, evidence of their effectiveness remains limited and data synthesis is lacking. Methods We conducted a meta-analysis on the effectiveness of home treatment compared with inpatient treatment in child and adolescent psychiatry, based on a systematic search of four databases (PubMed, CINAHL, PsychINFO, Embase). Primary outcomes were psychosocial functioning and psychopathology. Additional outcomes included treatment satisfaction, duration, costs, and readmission rates. Group differences were expressed as standardised mean differences (SMD) in change scores. We used three-level random-effects meta-analysis and meta-regression and conducted both superiority and non-inferiority testing. Results We included 30 studies from 13 non-overlapping samples, providing data from 1795 individuals (mean age: 11.95 ± 2.33 years; 42.5% female). We found no significant differences between home and inpatient treatment for postline psychosocial functioning (SMD = 0.05 [− 0.18; 0.30], p  = 0.68, I 2  = 98.0%) and psychopathology (SMD = 0.10 [− 0.17; 0.37], p  = 0.44, I 2  = 98.3%). Similar results were observed from follow-up data and non-inferiority testing. Meta-regression showed better outcomes for patient groups with higher levels of psychopathology at baseline and favoured home treatment over inpatient treatment when only randomised controlled trials were considered. Conclusions This meta-analysis found no evidence that home treatment is less effective than conventional inpatient treatment, highlighting its potential as an effective alternative in child and adolescent psychiatry. The generalisability of these findings is reduced by limitations in the existing literature, and further research is needed to better understand which patients benefit most from home treatment. Trial registration Registered at PROSPERO (CRD42020177558), July 5, 2020.

The present study aimed to investigate the possible mechanisms linking a single-item measure of global self-rated health (SRH) with morbidity by comparing the association strengths between SRH with markers of autonomic nervous system (ANS) function, inflammation, blood glucose and blood lipids. Cross-sectional comprehensive health-check data of 3947 working adults (age 42±11) was used to calculate logistic regressions, partial correlations and compare correlation strength using Olkins Z. Adjusted logistic regression models showed a negative association between SRH (higher values indicating worse health) and measures of heart rate variability (HRV). Glycemic markers were positively associated with poor SRH. No adjusted association was found with inflammatory markers, BP or lipids. In both unadjusted and adjusted linear models Pearson's correlation strength was significantly higher between SRH with HRV measures compared to SRH with other biomarkers. This is the first study investigating the association of ANS function and SRH. We showed that a global measure of SRH is associated with HRV, and that all measures of ANS function were significantly more strongly associated with SRH than any other biomarker. The current study supports the hypothesis that the extent of brain-body communication, as indexed by HRV, is associated with self-rated health.

This study explored the impact of a mindfulness-based intervention (MBI) on mental health and emotion regulation mechanisms, particularly focusing on the top-down and bottom-up related processes, such as emotion differentiation and heart rate variability (HRV). Participants underwent an 8-week mindfulness-based stress reduction (MBSR) program or a reading-sharing intervention (READ). Emotion differentiation and HRV were measured at various intervals, alongside mental health measurements (depressive and stress symptomatology, wellbeing, mindfulness, and self-compassion traits). The results showed that the MBSR group exhibited increased emotion differentiation for negative emotions and improvements in various mental health measurements (wellbeing and mindfulness traits) compared to the READ group. However, there were no significant differences in HRV between the two groups, and gains in emotion differentiation did not correlate significantly with changes in mental health outcomes. The findings suggest that MBIs can enhance emotion differentiation as a top-down mechanism and improve mental health outcomes. However, further research is needed to understand the precise psychophysiological mechanisms underlying these effects.

Transcranial magnetic stimulation (TMS) is a non-invasive treatment for adolescent major depressive disorder (MDD). Existing evidence on the efficacy of TMS in adolescent MDD awaits quantitative synthesis. A systematic literature search was conducted, and data from eligible studies were synthesized using random-effects models. Treatment-covariate interactions were examined in exploratory analyses of individual-patient data (IPD). Systematic search of the literature yielded 1264 hits, of which 10 individual studies (2 randomized trials) were included for quantitative synthesis of mainly uncontrolled studies. Individual patient data (IPD) were available from five trials (all uncontrolled studies). Quantitative synthesis of aggregated data revealed a statistically significant negative overall standardized mean change (pooled SMCC = 2.04, 95% CI [1.46; 2.61], SE = 0.29, p < .001), as well as a significant overall treatment response rate (Transformed Proportion = 41.30%, 95% CI [31.03; 51.57], SE = 0.05; p < 0.001), considering data from baseline to post-treatment. Exploratory IPD analyses suggests TMS might be more effective in younger individuals and individuals with more severe depression, and efficacy might be enhanced with certain treatment modality settings, including higher number of TMS sessions, longer treatment durations, and unilateral and not bilateral stimulation. Existing studies exhibit methodological shortcomings, including small-study effects and lack of control group, blinding, and randomization—compromising the credibility of the present results. To date, two randomized controlled trials on TMS in adolescent depression have been published, and the only large-scale randomized trial suggests TMS is not more effective than sham stimulation. Future large-scale, randomized, and sham-controlled trials are warranted. Future trials should ensure appropriate selection of patients for TMS treatment and guide precision medicine approaches for stimulation protocols.

Efficient brain–heart interactions, mediated by the central autonomic network (CAN), are crucial in regulating physiological and psychological stress. The ability of the autonomic nervous system to adapt to stress predicts resilience to cardiovascular, anxiety, and mood disorders. Since the neural dynamics underlying brain–heart interactions remain poorly understood, this study investigated brain activation and heart rate variability (HRV) during stress and relaxation. Functional magnetic resonance imaging (fMRI) and peripheral heart rate assessment were used to assess brain–heart coupling during breathing-induced relaxation, psychosocial stress and stress recovery in 32 healthy participants. We assessed the relation between perceived stress and brain activation, and employed non-linear generalized additive models to forecast changes in HR based on brain activation in the CAN. Both breathing-induced relaxation and stress induction significantly affected HR variation and triggered brain activation in CAN-related regions. HR variation was related to CAN activity during stress induction, and that chronic stress was linked to reduced brain activation during stress recovery. Finally, we demonstrated that brain activation within the CAN predicts changes in HRV. Our results offer novel insights into dynamic brain–heart interactions during stress-related autonomic regulation and emphasize the brain–heart axis’s potential as a target for therapeutic interventions aimed at enhancing stress resilience.

In recent clinical practice, a biomarker of vagal neuroimmunomodulation (NIM), namely the ratio of vagally-mediated heart rate variability (vmHRV) and CRP, was proposed to index the functionality of the cholinergic anti-inflammatory pathway. This study aims to transfer and extend the previous findings to two general population-based samples to explore the hypothesis that NIM-ratio is associated with all-cause mortality. Two large population studies (MIDUS 2: N = 1255 and Whitehall II wave 5: N = 7870) with complete data from a total of N = 3860 participants (36.1% females; average age = 56.3 years; 11.1% deaths, last exit 18.1 years post inclusion) were available. NIM indices were calculated using the vagally-mediated HRV measure RMSSD divided by measures of CRP (NIM CRP ) or IL-6 (NIM IL6 ). The NIM-ratios were quartiled and entered into age, ethnicity and body mass index adjusted Cox proportional hazards models. For NIM IL6 the lowest quartile was 45% more likely to die during the observed period (max. 18 years follow-up) compared to the highest quartile (HR = 0.55 CI 0.41–0.73; p  < .0001). NIM CRP parallel these results. Here we show that an easily computable index of IL-6 inhibition is associated with all-cause mortality in two large general population samples. These results suggest that this index might be useful for risk stratification and warrant further examination.

Non-suicidal self-injury (NSSI) is a highly prevalent phenomenon in adolescence, often associated with prior traumatic experiences. The development and maintenance of NSSI is associated with dysregulation of the stress response, and evidence suggests that the hypothalamic-pituitary-adrenal (HPA) axis plays an important role. The endocannabinoid system is a neuromodulatory system in close functional interaction with the HPA axis. Several studies have reported alterations of the endocannabinoid system in adult patients with post-traumatic stress disorder. However, the role of the endocannabinoid system in children and adolescents with NSSI is less clear, and previously no study examined endocannabinoids in youth with experiences of maltreatment. N-arachidonyl ethanolamide (AEA) and 2-arachidonyl glycerol (2-AG) were quantified alongside sociodemographic and clinical characteristics in n  = 148 adolescents (12–17 years of age). Analyses addressed group differences comparing healthy controls (HC, n  = 38), patients with NSSI without (NSSI − CMT, n  = 42) and with a history of childhood maltreatment (NSSI + CMT, n  = 68). We show that AEA is reduced in adolescents with NSSI independent of childhood maltreatment. Further, we present first evidence for a negative association between AEA and NSSI frequency as well as AEA and the severity of childhood maltreatment. This is the first study providing evidence for alterations in the endocannabinoid system in children and adolescents engaging in repetitive NSSI. Findings from the study support current endocannabinoid-hypotheses on the neurobiology of trauma and adversity, extending existing findings of altered endocannabinoid signaling following exposure to traumatic events to a well-powered sample of children and adolescents.

Non-suicidal self-injury (NSSI) is a transdiagnostic psychiatric symptom with high prevalence and relevance in child and adolescent psychiatry. Therefore, it is of great interest to identify a biological phenotype associated with NSSI. The aim of the present study was to cross-sectionally investigate patterns of biological markers underlying NSSI and associated psychopathology in a sample of female patients and healthy controls. Comprehensive clinical data, saliva and blood samples, heart rate variability and pain sensitivity, were collected in n  = 149 patients with NSSI and n = 40 healthy participants. Using machine-based learning, we tested the extent to which oxytocin, dehydroepiandrosterone (DHEA), beta-endorphin, free triiodothyronine (fT3), leukocytes, heart rate variability and pain sensitivity were able to classify participants regarding their clinical outcomes in NSSI, depression and borderline personality disorder symptomatology. We evaluated the predictive performance of several models (linear and logistic regression, elastic net regression, random forests, gradient boosted trees) using repeated cross-validation. With NSSI as an outcome variable, both logistic regression and machine learning models showed moderate predictive performance (Area under the Receiver Operating Characteristic Curve between 0.67 and 0.69). Predictors with the highest predictive power were low oxytocin (OR = 0.55; p  = 0.002), low pain sensitivity (OR = 1.15; p  = 0.021), and high leukocytes (OR = 1.67; p  = 0.015). For the psychopathological outcome variables, i.e., depression and borderline personality disorder symptomatology, models including the biological variables performed not better than the null model. A combination of hormonal and inflammatory markers, as well as pain sensitivity, were able to discriminate between participants with and without NSSI disorder. Based on this dataset, however, complex machine learning models were not able to detect non-linear patterns of associations between the biological markers. These findings need replication and future research will reveal the extent to which the respective biomarkers are useful for longitudinal prediction of clinical outcomes or treatment response.

Previous research has shown associations between brain structure and resting state high-frequency heart rate variability (HF HRV). Age affects both brain structure and HF HRV. Therefore, we sought to examine the relationship between brain structure and HF HRV as a function of age. Data from two independent studies were used for the present analysis. Study 1 included 19 older adults (10 males, age range 62–78 years) and 19 younger adults (12 males, age range 19–37). Study 2 included 23 older adults (12 males; age range 55–75) and 27 younger adults (17 males; age range 18–34). The root-mean-square of successive R–R-interval differences (RMSSD) from ECG recordings was used as time-domain measure of HF HRV. MRI scans were performed on a 3.0-T Siemens Magnetom Trio scanner. Cortical reconstruction and volumetric segmentation were performed with the Freesurfer image analysis suite, including 12 regions as regions of interests (ROI). Zero-order and partial correlations were used to assess the correlation of RMSSD with cortical thickness in selected ROIs. Lateral orbitofrontal cortex (OFC) cortical thickness was significantly associated with RMSSD. Further, both studies, in line with previous research, showed correlations between RMSSD and anterior cingulate cortex (ACC) cortical thickness. Meta-analysis on adjusted correlation coefficients from individual studies confirmed an association of RMSSD with the left rostral ACC and the left lateral OFC. Future longitudinal studies are necessary to trace individual trajectories in the association of HRV and brain structure across aging.