Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

Inflammatory mediators in major depression and bipolar disorder.

Major depressive disorder (MDD) and bipolar disorder (BD) are highly disabling illnesses defined by different psychopathological, neuroimaging, and cognitive profiles. In the last decades, immune dysregulation has received increasing attention as a central factor in the pathophysiology of these disorders. Several aspects of immune dysregulations have been investigated, including, low-grade inflammation cytokines, chemokines, cell populations, gene expression, and markers of both peripheral and central immune activation. Understanding the distinct immune profiles characterizing the two disorders is indeed of crucial importance for differential diagnosis and the implementation of personalized treatment strategies. In this paper, we reviewed the current literature on the dysregulation of the immune response system focusing our attention on studies using inflammatory markers to discriminate between MDD and BD. High heterogeneity characterized the available literature, reflecting the heterogeneity of the disorders. Common alterations in the immune response system include high pro-inflammatory cytokines such as IL-6 and TNF-α. On the contrary, a greater involvement of chemokines and markers associated with innate immunity has been reported in BD together with dynamic changes in T cells with differentiation defects during childhood which normalize in adulthood, whereas classic mediators of immune responses such as IL-4 and IL-10 are present in MDD together with signs of immune-senescence.

Post-COVID Trajectory of Pentraxin 3 Plasma Levels Over 6 Months and Their Association with the Risk of Developing Post-Acute Depression and Anxiety.

BACKGROUND AND OBJECTIVES: Clinical manifestations of coronavirus disease 2019 (COVID-19) often persist after acute disease resolution. Underlying molecular mechanisms are unclear. The objective of this original article was to longitudinally measure plasma levels of markers of the innate immune response to investigate whether they associate with and predict post-COVID symptomatology. METHODS: Adult patients with previous severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection during the first pandemic wave who underwent the 6-month multidisciplinary follow-up were included. Plasma levels of pentraxin 3 (PTX3), the complement components C3a and C5a, and chitinase-3 like-protein-1 (CHI3L1) were measured at hospital admission during acute disease (baseline) and at 1 and 6 months after hospital discharge. Associations with post-COVID-19 sequelae at 6 months were investigated using descriptive statistic and multiple regression models. RESULTS: Ninety-four COVID-19 patients were included. Baseline PTX3, C5a, C3a, and CHI3L1 did not predict post-COVID-19 sequelae. The extent of the reduction of PTX3 over time (delta PTX3) was associated with lower depressive and anxiety symptoms at 6 months (both p < 0.05). When entering sex, age, need for intensive care unit or non-invasive ventilation during hospital stay, psychiatric history, and baseline PTX3 as nuisance covariates into a generalized linear model (GLM), the difference between baseline and 6-month PTX3 levels (delta PTX3) significantly predicted depression (χ2 = 4.66, p = 0.031) and anxiety (χ2 = 4.68, p = 0.031) at 6 months. No differences in PTX3 levels or PTX3 delta were found in patients with or without persistent or new-onset other COVID-19 symptoms or signs at 6 months. Plasma levels of C3a, C5a, and CHI3L1 did not correlate with PTX3 levels at either time point and failed to associate with residual or de novo respiratory or systemic clinical manifestations of the disease at 6 months. CONCLUSIONS: A lower reduction of plasma PTX3 after acute COVID-19 associates with the presence of depression and anxiety, suggesting an involvement of inflammation in post-COVID-19 psychopathology and a potential role of PTX3 as a biomarker.

Higher Seasonal Variation of Systemic Inflammation in Bipolar Disorder.

Seasonal rhythms affect the immune system. Evidence supports the involvement of immuno-inflammatory mechanisms in bipolar disorder (BD), with the neutrophil to lymphocyte ratio (NLR), and the systemic immune-inflammatory index (SII; platelets × neutrophils/lymphocytes) consistently reported to be higher in patients with BD than in HC, but seasonal rhythms of innate and adaptive immunity have never been studied. We retrospectively studied NLR and SII in 824 participants divided into three groups: 321 consecutively admitted inpatients affected by a major depressive episode in course of BD, and 255 consecutively admitted inpatients affected by obsessive-compulsive disorder (OCD; positive psychiatric control), and 248 healthy controls (HC). Patients with BD showed markedly higher markers of systemic inflammation in autumn and winter, but not in spring and summer, in respect to both HC and patients with OCD, thus suggesting a specific effect of season on inflammatory markers in BD, independent of a shared hospital setting and drug treatment. Given that systemic inflammation is emerging as a new marker and as target for treatment in depressive disorders, we suggest that seasonal rhythms should be considered for tailoring antidepressant immuno-modulatory treatments in a precision medicine approach.

The nested hierarchical model of self and its non-relational vs relational posttraumatic manifestation: an fMRI meta-analysis of emotional processing.

Different kinds of traumatic experiences like natural catastrophes vs. relational traumatic experiences (e.g., sex/physical abuse, interpersonal partner violence) are involved in the development of the self and PTSD psychopathological manifestations. Looking at a neuroscience approach, it has been proposed a nested hierarchical model of self, which identifies three neural-mental networks: (i) interoceptive; (ii) exteroceptive; (iii) mental. However, it is still unclear how the self and its related brain networks might be affected by non-relational vs relational traumatic experiences. Departing from this background, the current study aims at conducting a meta-analytic review of task-dependent fMRI studies (i.e., emotional processing task) among patients with PTSD due to non-relational (PTSD-NR) and relational (PTSD-R) traumatic experiences using two approaches: (i) a Bayesian network meta-analysis for a region-of-interest-based approach; (ii) a coordinated-based meta-analysis. Our findings suggested that the PTSD-NR mainly recruited areas ascribed to the mental self to process emotional stimuli. Whereas, the PTSD-R mainly activated regions associated with the intero-exteroceptive self. Accordingly, the PTSD-R compared to the PTSD-NR might not reach a higher symbolic capacity to process stimuli with an emotional valence. These results are also clinically relevant in support of the development of differential treatment approaches for non-relational vs. relational PTSD.

Low-dose interleukin 2 antidepressant potentiation in unipolar and bipolar depression: Safety, efficacy, and immunological biomarkers.

Immune-inflammatory mechanisms are promising targets for antidepressant pharmacology. Immune cell abnormalities have been reported in mood disorders showing a partial T cell defect. Following this line of reasoning we defined an antidepressant potentiation treatment with add-on low-dose interleukin 2 (IL-2). IL-2 is a T-cell growth factor which has proven anti-inflammatory efficacy in autoimmune conditions, increasing thymic production of naïve CD4 + T cells, and possibly correcting the partial T cell defect observed in mood disorders. We performed a single-center, randomised, double-blind, placebo-controlled phase II trial evaluating the safety, clinical efficacy and biological responses of low-dose IL-2 in depressed patients with major depressive (MDD) or bipolar disorder (BD). 36 consecutively recruited inpatients at the Mood Disorder Unit were randomised in a 2:1 ratio to receive either aldesleukin (12 MDD and 12 BD) or placebo (6 MDD and 6 BD). Active treatment significantly potentiated antidepressant response to ongoing SSRI/SNRI treatment in both diagnostic groups, and expanded the population of T regulatory, T helper 2, and percentage of Naive CD4+/CD8 + immune cells. Changes in cell frequences were rapidly induced in the first five days of treatment, and predicted the later improvement of depression severity. No serious adverse effect was observed. This is the first randomised control trial (RCT) evidence supporting the hypothesis that treatment to strengthen the T cell system could be a successful way to correct the immuno-inflammatory abnormalities associated with mood disorders, and potentiate antidepressant response.

Micronized/ultramicronized palmitoylethanolamide improves depression and fatigue in coronavirus disease 2019 (COVID-19) survivors.

Coronavirus disease 2019 (COVID-19) may lead to neuropsychiatric sequelae. Palmitoylethanolamide (PEA) is an anti-inflammatory and neuroprotective amide used in depressive syndromes. Here we investigate whether micronized/ultramicronized (m/um) PEA improves neuropsychiatric sequelae in COVID-19 survivors. Patients evaluated at our post-COVID-19 outpatient clinic between February and August 2021 and presenting neuropsychiatric manifestations (n = 98) were offered treatment with m/umPEA 600 mg twice daily for 3 months. Those accepting m/umPEA therapy (n = 57) were compared with those who did not (n = 41), in terms of depression, fatigue, chronic pain and subjective well-being, through validated scales administered pre- and posttreatment. The two groups did not differ in terms of demographics, comorbidities, psychiatric history, antidepressant therapy, acute COVID-19 severity and baseline neuropsychiatric status. Patients receiving m/umPEA showed a greater improvement in depression and fatigue (both P < 0.05). Conversely, no association was found with changes in chronic pain or subjective well-being. At multivariable logistic regression, m/umPEA predicted neuropsychiatric improvement independently of age, sex and baseline neuropsychiatric status. Worse pretreatment fatigue and subjective well-being identified those who most likely benefited from treatment. In conclusion, despite its retrospective nature, our study suggests that m/umPEA may improve depression and fatigue in COVID-19 survivors, justifying future research in this setting.

White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) "OCD vs. healthy controls" (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) "unmedicated OCD vs. healthy controls" (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) "medicated OCD vs. unmedicated OCD" (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6-79.1 in adults; 35.9-63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research.

Penetrant-induced plasticization in microporous polymer membranes.

Penetrant-induced plasticization has prevented the industrial deployment of many polymers for membrane-based gas separations. With the advent of microporous polymers, new structural design features and unprecedented property sets are now accessible under controlled laboratory conditions, but property sets can often deteriorate due to plasticization. Therefore, a critical understanding of the origins of plasticization in microporous polymers and the development of strategies to mitigate this effect are needed to advance this area of research. Herein, an integrative discussion is provided on seminal plasticization theory and gas transport models, and these theories and models are compared to an exhaustive database of plasticization characteristics of microporous polymers. Correlations between specific polymer properties and plasticization behavior are presented, including analyses of plasticization pressures from pure-gas permeation tests and mixed-gas permeation tests for pure polymers and composite films. Finally, an evaluation of common and current state-of-the-art strategies to mitigate plasticization is provided along with suggestions for future directions of fundamental and applied research on the topic.

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures.

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.

A Microporous Poly(Arylene Ether) Platform for Membrane-Based Gas Separation.

Membrane-based gas separations are crucial for an energy-efficient future. However, it is difficult to develop membrane materials that are high-performing, scalable, and processable. Microporous organic polymers (MOPs) combine benefits for gas sieving and solution processability. Herein, we report membrane performance for a new family of microporous poly(arylene ether)s (PAEs) synthesized via Pd-catalyzed C-O coupling reactions. The scaffold of these microporous polymers consists of rigid three-dimensional triptycene and stereocontorted spirobifluorene, endowing these polymers with micropore dimensions attractive for gas separations. This robust PAE synthesis method allows for the facile incorporation of functionalities and branched linkers for control of permeation and mechanical properties. A solution-processable branched polymer was formed into a submicron film and characterized for permeance and selectivity, revealing lab data that rivals property sets of commercially available membranes already optimized for much thinner configurations. Moreover, the branching motif endows these materials with outstanding plasticization resistance, and their microporous structure and stability enables benefits from competitive sorption, increasing CO2 /CH4 and (H2 S+CO2 )/CH4 selectivity in mixture tests as predicted by the dual-mode sorption model. The structural tunability, stability, and ease-of-processing suggest that this new platform of microporous polymers provides generalizable design strategies to form MOPs at scale for demanding gas separations in industry.

Choroid plexus volume is increased in mood disorders and associates with circulating inflammatory cytokines.

Depressed patients exhibit altered levels of immune-inflammatory markers both in the peripheral blood and in the cerebrospinal fluid (CSF) and inflammatory processes have been widely implicated in the pathophysiology of mood disorders. The Choroid Plexus (ChP), located at the base of each of the four brain ventricles, regulates the exchange of substances between the blood and CSF and several evidence supported a key role for ChP as a neuro-immunological interface between the brain and circulating immune cells. Given the role of ChP as a regulatory gate between periphery, CSF spaces and the brain, we compared ChP volumes in patients with bipolar disorder (BP) or major depressive disorder (MDD) and healthy controls, exploring their association with history of illness and levels of circulating cytokines. Plasma levels of inflammatory markers and MRI scans were acquired for 73 MDD, 79 BD and 72 age- and sex-matched healthy controls (HC). Patients with either BD or MDD had higher ChP volumes than HC. With increasing age, the bilateral ChP volume was larger in patients, an effect driven by the duration of illness; while only minor effects were observed in HC. Right ChP volumes were proportional to higher levels of circulating cytokines in the clinical groups, including IFN-γ, IL-13 and IL-17. Specific effects in the two diagnostic groups were observed when considering the left ChP, with positive association with IL-1ra, IL-13, IL-17, and CCL3 in BD, and negative associations with IL-2, IL-4, IL-1ra, and IFN-γ in MDD. These results suggest that ChP could represent a reliable and easy-to-assess biomarker to evaluate the brain effects of inflammatory status in mood disorders, contributing to personalized diagnosis and tailored treatment strategies.

Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers.

BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.

Circulating cytotoxic immune cell composition, activation status and toxins expression associate with white matter microstructure in bipolar disorder.

Patients with bipolar disorder (BD) show higher immuno-inflammatory setpoints, with in vivo alterations in white matter (WM) microstructure and post-mortem infiltration of T cells in the brain. Cytotoxic CD8+ T cells can enter and damage the brain in inflammatory disorders, but little is known in BD. Our study aimed to investigate the relationship between cytotoxic T cells and WM alterations in BD. In a sample of 83 inpatients with BD in an active phase of illness (68 depressive, 15 manic), we performed flow cytometry immunophenotyping to investigate frequencies, activation status, and expression of cytotoxic markers in CD8+ and tested for their association with diffusion tensor imaging (DTI) measures of WM microstructure. Frequencies of naïve and activated CD8+ cell populations expressing Perforin, or both Perforin and Granzyme, negatively associated with WM microstructure. CD8+ Naïve cells negative for Granzyme and Perforin positively associates with indexes of WM integrity, while the frequency of CD8+ memory cells negatively associates with index of WM microstructure, irrespective of toxins expression. The resulting associations involve measures representative of orientational coherence and myelination of the fibers (FA and RD), suggesting disrupted oligodendrocyte-mediated myelination. These findings seems to support the hypothesis that immunosenescence (less naïve, more memory T cells) can detrimentally influence WM microstructure in BD and that peripheral CD8+ T cells may participate in inducing an immune-related WM damage in BD mediated by killer proteins.

The self and our perception of its synchrony - Beyond internal and external cognition.

The self is the core of our mental life which connects one's inner mental life with the external perception. Since synchrony is a key feature of the biological world and its various species, what role does it play for humans? We conducted a large-scale psychological study (n = 1072) combining newly developed visual analogue scales (VAS) for the perception of synchrony and internal and external cognition complemented by several psychological questionnaires. Overall, our findings showed close connection of the perception of synchrony of the self with both internal (i.e., body and cognition) and external (i.e., others, environment/nature) synchrony being associated positively with adaptive and negatively with maladaptive traits of self. Moreover, we have demonstrated how external (i.e., life events like the COVID-19 pandemic) variables modulate the perception of the self's internal-external synchrony. These findings suggest how synchrony with self plays a central role during times of uncertainty.

Association between NTRK2 Polymorphisms, Hippocampal Volumes and Treatment Resistance in Major Depressive Disorder.

Despite the increasing availability of antidepressant drugs, a high rate of patients with major depression (MDD) does not respond to pharmacological treatments. Brain-derived neurotrophic factor (BDNF)-tyrosine receptor kinase B (TrkB) signaling is thought to influence antidepressant efficacy and hippocampal volumes, robust predictors of treatment resistance. We therefore hypothesized the possible role of BDNF and neurotrophic receptor tyrosine kinase 2 (NTRK2)-related polymorphisms in affecting both hippocampal volumes and treatment resistance in MDD. A total of 121 MDD inpatients underwent 3T structural MRI scanning and blood sampling to obtain genotype information. General linear models and binary logistic regressions were employed to test the effect of genetic variations related to BDNF and NTRK2 on bilateral hippocampal volumes and treatment resistance, respectively. Finally, the possible mediating role of hippocampal volumes on the relationship between genetic markers and treatment response was investigated. A significant association between one NTRK2 polymorphism with hippocampal volumes and antidepressant response was found, with significant indirect effects. Our results highlight a possible mechanistic explanation of antidepressant action, possibly contributing to the understanding of MDD pathophysiology.

Melatonin secretion patterns are associated with cognitive vulnerability and brain structure in bipolar depression.

Circadian rhythm disruption is a core symptom of bipolar disorder (BD), also reflected in altered patterns of melatonin release. Reductions of grey matter (GM) volumes are well documented in BD. We hypothesized that levels and timing of melatonin secretion in bipolar depression could be associated with depressive psychopathology and brain GM integrity. The onset of melatonin secretion under dim light conditions (DLMO) and the amount of time between DLMO and midsleep (i.e. phase angle difference; PAD) were used as circadian rhythm markers. To study the time course of melatonin secretion, an exponential curve fitting the melatonin values was calculated, and the slope coefficients (SLP) were obtained for each participant. Significant differences were found between HC and BD in PAD measures and melatonin profiles. Correlations between PAD and depressive psychopathology were identified. Melatonin secretion patterns were found to be associated with GM volumes in the Striatum and Supramarginal Gyrus in BD. Our findings emphasized the role of melatonin secretion role as a biological marker of circadian synchronization in bipolar depression and provided a novel insight for a link between melatonin release and brain structure.

In Between the Psychological and Physiological Self - The Impact of Covid-19 Pandemic on the Neuro-Socio-Ecological and Inflammatory Mind-Body-Brain System.

The COVID-19 pandemic has had a profound impact on individuals' sense of self perturbating the sense of connectedness with the others, touching upon deep existential fears and deep intersubjective and cultural layers, emphasizing the importance of a neuro-socio-ecological alignment for the sense of security of psychological self. We can still observe after years how social distancing measures, quarantines, and lockdowns have disrupted social connections and routines, leading to feelings of isolation, anxiety and depressive symptomatology. Furthermore, from a physiological perspective, some people continue to experience health problems long after having COVID-19, and these ongoing health problems are sometimes called post-COVID-19 syndrome or post-COVID conditions (PASC). In this complex scenario, through the operationalization of the sense of self and its psychological and physiological baseline, our aim is to try to shed some new light on elements of resilience vs. vulnerability. Here we intend the self and its baseline as the crossroads between psychology and physiology and we show how COVID-19 pandemic, especially in post-COVID-19 syndrome (PACS), left traces in the mind-body-brain system at a neuro-socio-ecological and inflammatory level.