Persistence of amygdala hyperactivity to subliminal negative emotion processing in the long-term course of depression.

Biased emotion processing has been suggested to underlie the etiology and maintenance of depression. Neuroimaging studies have shown mood-congruent alterations in amygdala activity in patients with acute depression, even during early, automatic stages of emotion processing. However, due to a lack of prospective studies over periods longer than 8 weeks, it is unclear whether these neurofunctional abnormalities represent a persistent correlate of depression even in remission. In this prospective case-control study, we aimed to examine brain functional correlates of automatic emotion processing in the long-term course of depression. In a naturalistic design, n = 57 patients with acute major depressive disorder (MDD) and n = 37 healthy controls (HC) were assessed with functional magnetic resonance imaging (fMRI) at baseline and after 2 years. Patients were divided into two subgroups according to their course of illness during the study period (n = 37 relapse, n = 20 no-relapse). During fMRI, participants underwent an affective priming task that assessed emotion processing of subliminally presented sad and happy compared to neutral face stimuli. A group × time × condition (3 × 2 × 2) ANOVA was performed for the amygdala as region-of-interest (ROI). At baseline, there was a significant group × condition interaction, resulting from amygdala hyperactivity to sad primes in patients with MDD compared to HC, whereas no difference between groups emerged for happy primes. In both patient subgroups, amygdala hyperactivity to sad primes persisted after 2 years, regardless of relapse or remission at follow-up. The results suggest that amygdala hyperactivity during automatic processing of negative stimuli persists during remission and represents a trait rather than a state marker of depression. Enduring neurofunctional abnormalities may reflect a consequence of or a vulnerability to depression.

Long-term effects of electroconvulsive therapy on brain structure in major depression.

BACKGROUND: Magnetic resonance imaging (MRI) studies on major depressive disorder (MDD) have predominantly found short-term electroconvulsive therapy (ECT)-related gray matter volume (GMV) increases, but research on the long-term stability of such changes is missing. Our aim was to investigate long-term GMV changes over a 2-year period after ECT administration and their associations with clinical outcome. METHODS: In this nonrandomized longitudinal study, patients with MDD undergoing ECT (n = 17) are assessed three times by structural MRI: Before ECT (t0), after ECT (t1) and 2 years later (t2). A healthy (n = 21) and MDD non-ECT (n = 33) control group are also measured three times within an equivalent time interval. A 3(group) × 3(time) ANOVA on whole-brain level and correlation analyses with clinical outcome variables is performed. RESULTS: Analyses yield a significant group × time interaction (pFWE < 0.001) resulting from significant volume increases from t0 to t1 and decreases from t1 to t2 in the ECT group, e.g., in limbic areas. There are no effects of time in both control groups. Volume increases from t0 to t1 correlate with immediate and delayed symptom increase, while volume decreases from t1 to t2 correlate with long-term depressive outcome (all p ⩽ 0.049). CONCLUSIONS: Volume increases induced by ECT appear to be a transient phenomenon as volume strongly decreased 2 years after ECT. Short-term volume increases are associated with less symptom improvement suggesting that the antidepressant effect of ECT is not due to volume changes. Larger volume decreases are associated with poorer long-term outcome highlighting the interplay between disease progression and structural changes.

Towards a network control theory of electroconvulsive therapy response.

Electroconvulsive Therapy (ECT) is arguably the most effective intervention for treatment-resistant depression. While large interindividual variability exists, a theory capable of explaining individual response to ECT remains elusive. To address this, we posit a quantitative, mechanistic framework of ECT response based on Network Control Theory (NCT). Then, we empirically test our approach and employ it to predict ECT treatment response. To this end, we derive a formal association between Postictal Suppression Index (PSI)-an ECT seizure quality index-and whole-brain modal and average controllability, NCT metrics based on white-matter brain network architecture, respectively. Exploiting the known association of ECT response and PSI, we then hypothesized an association between our controllability metrics and ECT response mediated by PSI. We formally tested this conjecture in N = 50 depressive patients undergoing ECT. We show that whole-brain controllability metrics based on pre-ECT structural connectome data predict ECT response in accordance with our hypotheses. In addition, we show the expected mediation effects via PSI. Importantly, our theoretically motivated metrics are at least on par with extensive machine learning models based on pre-ECT connectome data. In summary, we derived and tested a control-theoretic framework capable of predicting ECT response based on individual brain network architecture. It makes testable, quantitative predictions regarding individual therapeutic response, which are corroborated by strong empirical evidence. Our work might constitute a starting point for a comprehensive, quantitative theory of personalized ECT interventions rooted in control theory.

Cognitive performance and brain structural connectome alterations in major depressive disorder.

BACKGROUND: Cognitive dysfunction and brain structural connectivity alterations have been observed in major depressive disorder (MDD). However, little is known about their interrelation. The present study follows a network approach to evaluate alterations in cognition-related brain structural networks. METHODS: Cognitive performance of n = 805 healthy and n = 679 acutely depressed or remitted individuals was assessed using 14 cognitive tests aggregated into cognitive factors. The structural connectome was reconstructed from structural and diffusion-weighted magnetic resonance imaging. Associations between global connectivity strength and cognitive factors were established using linear regressions. Network-based statistics were applied to identify subnetworks of connections underlying these global-level associations. In exploratory analyses, effects of depression were assessed by evaluating remission status-related group differences in subnetwork-specific connectivity. Partial correlations were employed to directly test the complete triad of cognitive factors, depressive symptom severity, and subnetwork-specific connectivity strength. RESULTS: All cognitive factors were associated with global connectivity strength. For each cognitive factor, network-based statistics identified a subnetwork of connections, revealing, for example, a subnetwork positively associated with processing speed. Within that subnetwork, acutely depressed patients showed significantly reduced connectivity strength compared to healthy controls. Moreover, connectivity strength in that subnetwork was associated to current depressive symptom severity independent of the previous disease course. CONCLUSIONS: Our study is the first to identify cognition-related structural brain networks in MDD patients, thereby revealing associations between cognitive deficits, depressive symptoms, and reduced structural connectivity. This supports the hypothesis that structural connectome alterations may mediate the association of cognitive deficits and depression severity.

Treatment with the second-generation antipsychotic quetiapine is associated with increased subgenual ACC activation during reward processing in major depressive disorder.

BACKGROUND: The second-generation antipsychotic (SGA) quetiapine is an essential option for antidepressant augmentation therapy in major depressive disorder (MDD), yet neurobiological mechanisms behind its antidepressant properties remain unclear. As SGAs interfere with activity in reward-related brain areas, including the anterior cingulate cortex (ACC) - a key brain region in antidepressant interventions, this study examined whether quetiapine treatment affects ACC activity during reward processing in MDD patients. METHODS: Using the ACC as region of interest, an independent t-test comparing reward-related BOLD response of 51 quetiapine-taking and 51 antipsychotic-free MDD patients was conducted. Monetary reward outcome feedback was measured in a card-guessing paradigm using pseudorandom blocks. Participants were matched for age, sex, and depression severity and analyses were controlled for confounding variables, including total antidepressant medication load, illness chronicity and acute depression severity. Potential dosage effects were examined in a 3 × 1 ANOVA. Differences in ACC-related functional connectivity were assessed in psycho-physiological interaction (PPI) analyses. RESULTS: Left subgenual ACC activity was significantly higher in the quetiapine group compared to antipsychotic-free participants and dependent on high-dose quetiapine intake. Results remained significant after controlling for confounding variables. The PPI analysis did not yield significant group differences in ACC-related functional connectivity. LIMITATIONS: Causal interpretation is limited due to cross-sectional findings. CONCLUSION: Elevated subgenual ACC activity to rewarding stimuli may represent a neurobiological marker and potential key interface of quetiapine's antidepressant effects in MDD. These results underline ACC activity during reward processing as an investigative avenue for future research and therapeutic interventions to improve MDD treatment outcomes.

Shared and Specific Patterns of Structural Brain Connectivity Across Affective and Psychotic Disorders.

BACKGROUND: Altered brain structural connectivity has been implicated in the pathophysiology of psychiatric disorders including schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). However, it is unknown which part of these connectivity abnormalities are disorder specific and which are shared across the spectrum of psychotic and affective disorders. We investigated common and distinct brain connectivity alterations in a large sample (N = 1743) of patients with SZ, BD, or MDD and healthy control (HC) subjects. METHODS: This study examined diffusion-weighted imaging-based structural connectome topology in 720 patients with MDD, 112 patients with BD, 69 patients with SZ, and 842 HC subjects (mean age of all subjects: 35.7 years). Graph theory-based network analysis was used to investigate connectome organization. Machine learning algorithms were trained to classify groups based on their structural connectivity matrices. RESULTS: Groups differed significantly in the network metrics global efficiency, clustering, present edges, and global connectivity strength with a converging pattern of alterations between diagnoses (e.g., efficiency: HC > MDD > BD > SZ, false discovery rate-corrected p = .028). Subnetwork analysis revealed a common core of edges that were affected across all 3 disorders, but also revealed differences between disorders. Machine learning algorithms could not discriminate between disorders but could discriminate each diagnosis from HC. Furthermore, dysconnectivity patterns were found most pronounced in patients with an early disease onset irrespective of diagnosis. CONCLUSIONS: We found shared and specific signatures of structural white matter dysconnectivity in SZ, BD, and MDD, leading to commonly reduced network efficiency. These results showed a compromised brain communication across a spectrum of major psychiatric disorders.

Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium.

Identifying brain alterations associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and improving early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth. We performed analyses in three separate stages, in samples ranging from most to least homogeneous in terms of suicide assessment instrument and mental disorder. First, in a sample of 577 young people with mood disorders, in which STBs were assessed with the Columbia Suicide Severity Rating Scale (C-SSRS). Second, in a sample of young people with mood disorders, in which STB were assessed using different instruments, MRI metrics were compared among healthy controls without STBs (HC; N = 519), clinical controls with a mood disorder but without STBs (CC; N = 246) and young people with current suicidal ideation (N = 223). In separate analyses, MRI metrics were compared among HCs (N = 253), CCs (N = 217), and suicide attempters (N = 64). Third, in a larger transdiagnostic sample with various assessment instruments (HC = 606; CC = 419; Ideation = 289; HC = 253; CC = 432; Attempt=91). In the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and a history of actual suicide attempts (N = 163) than those without a lifetime suicide attempt (N = 323; FDR-p = 0.035, Cohen's d = 0.34). No associations with suicidal ideation were found. When examining more heterogeneous samples, we did not observe significant associations. Lower frontal pole surface area may represent a vulnerability for a (non-interrupted and non-aborted) suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk.

Brain structural correlates of recurrence following the first episode in patients with major depressive disorder.

Former prospective studies showed that the occurrence of relapse in Major Depressive Disorder (MDD) is associated with volume loss in the insula, hippocampus and dorsolateral prefrontal cortex (DLPFC). However, these studies were confounded by the patient's lifetime disease history, as the number of previous episodes predict future recurrence. In order to analyze neural correlates of recurrence irrespective of prior disease course, this study prospectively examined changes in brain structure in patients with first-episode depression (FED) over 2 years. N = 63 FED patients and n = 63 healthy controls (HC) underwent structural magnetic resonance imaging at baseline and after 2 years. According to their disease course during the follow-up interval, patients were grouped into n = 21 FED patients with recurrence (FEDrec) during follow-up and n = 42 FED patients with stable remission (FEDrem). Gray matter volume changes were analysed using group by time interaction analyses of covariance for the DLPFC, hippocampus and insula. Significant group by time interactions in the DLPFC and insula emerged. Pairwise comparisons showed that FEDrec had greater volume decline in the DLPFC and insula from baseline to follow-up compared with FEDrem and HC. No group by time interactions in the hippocampus were found. Cross-sectional analyses at baseline and follow-up revealed no differences between groups. This longitudinal study provides evidence for neural alterations in the DLPFC and insula related to a detrimental course in MDD. These effects of recurrence are already detectable at initial stages of MDD and seem to occur without any prior disease history, emphasizing the importance of early interventions preventing depressive recurrence.

Role of Reticulated Platelets in Cardiovascular Disease.

Human platelets differ considerably with regard to their size, RNA content and thrombogenicity. Reticulated platelets (RPs) are young, hyper-reactive platelets that are newly released from the bone marrow. They are larger and contain more RNA compared to older platelets. In comparison to more mature platelets, they exhibit a significantly higher thrombogenicity and are known to be elevated in patients with an increased platelet turnover such as, diabetics and after acute myocardial infarction. Several studies have shown that RPs correlate with an insufficient antiplatelet response to aspirin and specific P2Y12 receptor inhibitors. In addition, RPs are promising novel biomarkers for the prediction of adverse cardiovascular events in cardiovascular disease. However, the reason for RPs intrinsic hyper-reactivity and their association with ischemic events is not completely understood and the biology of RPs is still under investigation. We here present a structured review of preclinical and clinical findings concerning the role of RPs in cardiovascular disease.

Brain functional correlates of emotional face processing in body dysmorphic disorder.

Previous neuroimaging studies in body dysmorphic disorder (BDD) have focused on discordances in visual processing systems. However, little is known about brain functional aberrations in individuals with BDD during emotional face processing. An fMRI paradigm with negative emotional faces was employed in 20 individuals with BDD and 43 mentally healthy controls (HC). We compared functional activity and whole-brain connectivity patterns of the amygdala and the fusiform gyrus (FFG) between both groups. Regression analyses were performed for associations of body dysmorphic symptoms with brain activity and connectivity. Individuals with BDD exhibited higher activity in the left amygdala compared to HC (pFWE = .04) as well as increased functional connectivity of the left amygdala with a network including frontostriatal and temporal regions (pFWE < .05). The FFG revealed increased functional connectivity in individuals with BDD, mapping to brain areas such as the cingulate cortex and temporo-limbic regions (pFWE < .05). In HC, higher levels of body dysmorphic symptoms were associated with higher functional amygdala and FFG activity (pFWE < .05). Individuals with BDD show aberrant functional activity and connectivity patterns within the amygdala and the FFG for negative emotional face processing. Body dysmorphic symptoms in HC are associated with a mild pattern of brain functional alterations, which could emphasize the relevance of a dimensional approach in addition to diagnosis. Treatments for BDD could benefit from targeting visual misperception and evaluation processes upon confrontation with emotional information.

Changes in brain function during negative emotion processing in the long-term course of depression.

BACKGROUND: Relapses in major depression are frequent and are associated with a high burden of disease. Although short-term studies suggest a normalisation of depression-associated brain functional alterations directly after treatment, long-term investigations are sparse. AIMS: To examine brain function during negative emotion processing in association with course of illness over a 2-year span. METHOD: In this prospective case-control study, 72 in-patients with current depression and 42 healthy controls were investigated during a negative emotional face processing paradigm, at baseline and after 2 years. According to their course of illness during the study interval, patients were divided into subgroups (n = 25 no-relapse, n = 47 relapse). The differential changes in brain activity were investigated by a group × time analysis of covariance for the amygdala, hippocampus, insula and at whole-brain level. RESULTS: A significant relapse × time interaction emerged within the amygdala (PTFCE-FWE = 0.011), insula (PTFCE-FWE = 0.001) and at the whole-brain level mainly in the temporal and prefrontal cortex (PTFCE-FWE = 0.027), resulting from activity increases within the no-relapse group, whereas in the relapse group, activity decreased during the study interval. At baseline, the no-relapse group showed amygdala, hippocampus and insula hypoactivity compared with healthy controls and the relapse group. CONCLUSIONS: This study reveals course of illness-associated activity changes in emotion processing areas. Patients in full remission show a normalisation of their baseline hypo-responsiveness to the activation level of healthy controls after 2 years. Brain function during emotion processing could further serve as a potential predictive marker for future relapse.

The Course of Disease in Major Depressive Disorder Is Associated With Altered Activity of the Limbic System During Negative Emotion Processing.

BACKGROUND: Brain functional alterations during emotion processing in patients with major depressive disorder (MDD) compared with healthy control subjects (HCs) are frequently reported. However, evidence for functional correlates of emotion processing with regard to MDD trajectories is scarce. This study investigates the role of lifetime disease course for limbic brain activation during negative emotional face processing in patients with MDD. METHODS: In a large sample of patients with MDD (n = 333; 58.55% female) and HCs (n = 333; 60.06% female), brain activation was investigated during a negative emotional face-processing task within a cross-sectional design. Differences between HC and MDD groups were analyzed. Previous disease course, characterized by 2 components, namely hospitalization and duration of illness, was regressed on brain activation of the amygdala, (para-)hippocampus, and insula in patients with MDD. RESULTS: Patients with MDD showed increased activation in the amygdala, insula, and hippocampus compared with HCs (all p values corrected for familywise error [pFWE] < .045). The hospitalization component showed negative associations with brain activation in the bilateral insula (right: pFWE = .026, left: pFWE = .019) and (para-)hippocampus (right: pFWE = .038, left: pFWE = .031). No significant association was found for the duration of illness component (all pFWE > .057). CONCLUSIONS: This study investigated negative emotion processing in a large sample of patients with MDD and HCs. Our results confirm limbic hyperactivation in patients with MDD during negative emotion processing; however, this hyperactivation may resolve with a more severe lifetime disease course in the insula and (para-)hippocampus-brain regions involved in emotion processing and regulation. These findings need further replication in longitudinal studies.

Platelet Surface Protein Expression and Reactivity upon TRAP Stimulation after BNT162b2 Vaccination.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection induces a coagulopathy characterized by platelet activation and a hypercoagulable state with an increased incidence of cardiovascular events. The viral spike protein S has been reported to enhance thrombosis formation, stimulate platelets to release procoagulant factors, and promote the formation of platelet-leukocyte aggregates even in absence of the virus. Although SARS-CoV-2 vaccines induce spike protein overexpression to trigger SARS-CoV-2-specific immune protection, thrombocyte activity has not been investigated in this context. Here, we provide the first phenotypic platelet characterization of healthy human subjects undergoing BNT162b2 vaccination. Using mass cytometry, we analyzed the expression of constitutive transmembrane receptors, adhesion proteins, and platelet activation markers in 12 healthy donors before and at five different time points within 4 weeks after the first BNT162b2 administration. We measured platelet reactivity by stimulating thrombocyte activation with thrombin receptor-activating peptide. Activation marker expression (P-selectin, LAMP-3, LAMP-1, CD40L, and PAC-1) did not change after vaccination. All investigated constitutive transmembrane proteins showed similar expressions over time. Platelet reactivity was not altered after BNT162b2 administration. Activation marker expression was significantly lower compared with an independent cohort of mild symptomatic COVID-19 patients analyzed with the same platform. This study reveals that BNT162b2 administration does not alter platelet protein expression and reactivity.

Mass cytometry of platelet-rich plasma: a new approach to analyze platelet surface expression and reactivity.

Mass cytometry (CyTOF) is a new technology that allows the investigation of protein expression at single cell level with high resolution. While several protocols are available to investigate leukocyte expression, platelet staining and analysis with CyTOF have been described only from whole blood. Moreover, available protocols do not allow sample storage but require fresh samples to be obtained, processed, and measured immediately. We provide a structured and reproducible method to stain platelets from platelet-rich plasma to study thrombocyte protein expression and reactivity using mass cytometry. With our method, it is possible to acquire a large number of events allowing deep bioinformatic investigation of platelet expression heterogeneity. Integrated in our protocol is also a previously established freezing protocol that allows the storage of stained samples and to delay their measurement. Finally, we provide a structured workflow using different platelet stimulators and a freely available bioinformatic pipeline to analyze platelet expression. Our protocol unlocks the potential of CyTOF analysis for studying platelet biology in health and disease.

A systematic comparison of novel and existing differential analysis methods for CyTOF data.

Cytometry techniques are widely used to discover cellular characteristics at single-cell resolution. Many data analysis methods for cytometry data focus solely on identifying subpopulations via clustering and testing for differential cell abundance. For differential expression analysis of markers between conditions, only few tools exist. These tools either reduce the data distribution to medians, discarding valuable information, or have underlying assumptions that may not hold for all expression patterns. Here, we systematically evaluated existing and novel approaches for differential expression analysis on real and simulated CyTOF data. We found that methods using median marker expressions compute fast and reliable results when the data are not strongly zero-inflated. Methods using all data detect changes in strongly zero-inflated markers, but partially suffer from overprediction or cannot handle big datasets. We present a new method, CyEMD, based on calculating the earth mover's distance between expression distributions that can handle strong zero-inflation without being too sensitive. Additionally, we developed CYANUS - CYtometry ANalysis Using Shiny - a user-friendly R Shiny App allowing the user to analyze cytometry data with state-of-the-art tools, including well-performing methods from our comparison. A public web interface is available at https://exbio.wzw.tum.de/cyanus/.

Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study.

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

Functional enrichment of alternative splicing events with NEASE reveals insights into tissue identity and diseases.

Alternative splicing (AS) is an important aspect of gene regulation. Nevertheless, its role in molecular processes and pathobiology is far from understood. A roadblock is that tools for the functional analysis of AS-set events are lacking. To mitigate this, we developed NEASE, a tool integrating pathways with structural annotations of protein-protein interactions to functionally characterize AS events. We show in four application cases how NEASE can identify pathways contributing to tissue identity and cell type development, and how it highlights splicing-related biomarkers. With a unique view on AS, NEASE generates unique and meaningful biological insights complementary to classical pathways analysis.

Interaction of developmental factors and ordinary stressful life events on brain structure in adults.

An interplay of early environmental and genetic risk factors with recent stressful life events (SLEs) in adulthood increases the risk for adverse mental health outcomes. The interaction of early risk and current SLEs on brain structure has hardly been investigated. Whole brain voxel-based morphometry analysis was performed in N = 786 (64.6% female, mean age = 33.39) healthy subjects to identify correlations of brain clusters with commonplace recent SLEs. Genetic and early environmental risk factors, operationalized as those for severe psychopathology (i.e., polygenic scores for neuroticism, childhood maltreatment, urban upbringing and paternal age) were assessed as modulators of the impact of SLEs on the brain. SLEs were negatively correlated with grey matter volume in the left medial orbitofrontal cortex (mOFC, FWE p = 0.003). This association was present for both, positive and negative, life events. Cognitive-emotional variables, i.e., neuroticism, perceived stress, trait anxiety, intelligence, and current depressive symptoms did not account for the SLE-mOFC association. Further, genetic and environmental risk factors were not correlated with grey matter volume in the left mOFC cluster and did not affect the association between SLEs and left mOFC grey matter volume. The orbitofrontal cortex has been implicated in stress-related psychopathology, particularly major depression in previous studies. We find that SLEs are associated with this area. Important early life risk factors do not interact with current SLEs on brain morphology in healthy subjects.

SARS-CoV-2 infection is associated with a pro-thrombotic platelet phenotype.

Novel coronavirus disease 2019 (COVID-19) is associated with a hypercoagulable state, characterized by abnormal coagulation parameters and by increased incidence of cardiovascular complications. With this study, we aimed to investigate the activation state and the expression of transmembrane proteins in platelets of hospitalized COVID-19 patients. We investigated transmembrane proteins expression with a customized mass cytometry panel of 21 antibodies. Platelets of 8 hospitalized COVID-19 patients not requiring intensive care support and without pre-existing conditions were compared to platelets of healthy controls (11 donors) with and without in vitro stimulation with thrombin receptor-activating peptide (TRAP). Mass cytometry of non-stimulated platelets detected an increased surface expression of activation markers P-Selectin (0.67 vs. 1.87 median signal intensity for controls vs. patients, p = 0.0015) and LAMP-3 (CD63, 0.37 vs. 0.81, p = 0.0004), the GPIIb/IIIa complex (4.58 vs. 5.03, p < 0.0001) and other adhesion molecules involved in platelet activation and platelet-leukocyte interactions. Upon TRAP stimulation, mass cytometry detected a higher expression of P-selectin in COVID-19 samples compared to controls (p < 0.0001). However, we observed a significantly reduced capacity of COVID-19 platelets to increase the expression of activation markers LAMP-3 and P-Selectin upon stimulation with TRAP. We detected a hyperactivated phenotype in platelets during SARS-CoV-2 infection, consisting of highly expressed platelet activation markers, which might contribute to the hypercoagulopathy observed in COVID-19. In addition, several transmembrane proteins were more highly expressed compared to healthy controls. These findings support research projects investigating antithrombotic and antiplatelet treatment regimes in COVID-19 patients, and provide new insights on the phenotypical platelet expression during SARS-CoV-2 infection.