Complement as a vital nexus of the pathobiological connectome for acute respiratory distress syndrome: An emerging therapeutic target.

The hallmark of acute respiratory distress syndrome (ARDS) pathobiology is unchecked inflammation-driven diffuse alveolar damage and alveolar-capillary barrier dysfunction. Currently, therapeutic interventions for ARDS remain largely limited to pulmonary-supportive strategies, and there is an unmet demand for pharmacologic therapies targeting the underlying pathology of ARDS in patients suffering from the illness. The complement cascade (ComC) plays an integral role in the regulation of both innate and adaptive immune responses. ComC activation can prime an overzealous cytokine storm and tissue/organ damage. The ARDS and acute lung injury (ALI) have an established relationship with early maladaptive ComC activation. In this review, we have collected evidence from the current studies linking ALI/ARDS with ComC dysregulation, focusing on elucidating the new emerging roles of the extracellular (canonical) and intracellular (non-canonical or complosome), ComC (complementome) in ALI/ARDS pathobiology, and highlighting complementome as a vital nexus of the pathobiological connectome for ALI/ARDS via its crosstalking with other systems of the immunome, DAMPome, PAMPome, coagulome, metabolome, and microbiome. We have also discussed the diagnostic/therapeutic potential and future direction of ALI/ARDS care with the ultimate goal of better defining mechanistic subtypes (endotypes and theratypes) through new methodologies in order to facilitate a more precise and effective complement-targeted therapy for treating these comorbidities. This information leads to support for a therapeutic anti-inflammatory strategy by targeting the ComC, where the arsenal of clinical-stage complement-specific drugs is available, especially for patients with ALI/ARDS due to COVID-19.

Resting-state functional connectome predicts individual differences in depression during COVID-19 pandemic.

Stressful life events are significant risk factors for depression, and increases in depressive symptoms have been observed during the COVID-19 pandemic. The aim of this study is to explore the neural makers for individuals' depression during COVID-19, using connectome-based predictive modeling (CPM). Then we tested whether these neural markers could be used to identify groups at high/low risk for depression with a longitudinal dataset. The results suggested that the high-risk group demonstrated a higher level and increment of depression during the pandemic, as compared to the low-risk group. Furthermore, a support vector machine (SVM) algorithm was used to discriminate major depression disorder patients and healthy controls, using neural features defined by CPM. The results confirmed the CPM's ability for capturing the depression-related patterns with individuals' resting-state functional connectivity signature. The exploration for the anatomy of these functional connectivity features emphasized the role of an emotion-regulation circuit and an interoception circuit in the neuropathology of depression. In summary, the present study augments current understanding of potential pathological mechanisms underlying depression during an acute and unpredictable life-threatening event and suggests that resting-state functional connectivity may provide potential effective neural markers for identifying susceptible populations. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

COVID-19 vicarious traumatization links functional connectome to general distress.

As characterized by repeated exposure of others' trauma, vicarious traumatization is a common negative psychological reaction during the COVID-19 pandemic and plays a crucial role in the development of general mental distress. This study aims to identify functional connectome that encodes individual variations of pandemic-related vicarious traumatization and reveal the underlying brain-vicarious traumatization mechanism in predicting general distress. The eligible subjects were 105 general university students (60 females, aged from 19 to 27 years) undergoing brain MRI scanning and baseline behavioral tests (October 2019 to January 2020), whom were re-contacted for COVID-related vicarious traumatization measurement (February to April 2020) and follow-up general distress evaluation (March to April 2021). We applied a connectome-based predictive modeling (CPM) approach to identify the functional connectome supporting vicarious traumatization based on a 268-region-parcellation assigned to network memberships. The CPM analyses showed that only the negative network model stably predicted individuals' vicarious traumatization scores (q2 = -0.18, MSE = 617, r [predicted, actual] = 0.18, p = 0.024), with the contributing functional connectivity primarily distributed in the fronto-parietal, default mode, medial frontal, salience, and motor network. Furthermore, mediation analysis revealed that vicarious traumatization mediated the influence of brain functional connectome on general distress. Importantly, our results were independent of baseline family socioeconomic status, other stressful life events and general mental health as well as age, sex and head motion. Our study is the first to provide evidence for the functional neural markers of vicarious traumatization and reveal an underlying neuropsychological pathway to predict distress symptoms in which brain functional connectome affects general distress via vicarious traumatization.

Maladaptive changes in delay discounting in males during the COVID-19 pandemic: the predictive role of functional connectome.

The Coronavirus disease of 2019 (COVID-19) and measures to curb it created population-level changes in male-dominant impulsive and risky behaviors such as violent crimes and gambling. One possible explanation for this is that the pandemic has been stressful, and males, more so than females, tend to respond to stress by altering their focus on immediate versus delayed rewards, as reflected in their delay discounting rates. Delay discounting rates from healthy undergraduate students were collected twice during the pandemic. Discounting rates of males (n=190) but not of females (n=493) increased during the pandemic. Using machine learning, we show that prepandemic functional connectome predict increased discounting rates in males (n=88). Moreover, considering that delay discounting is associated with multiple psychiatric disorders, we found the same neural pattern that predicted increased discounting rates in this study, in secondary datasets of patients with major depression and schizophrenia. The findings point to sex-based differences in maladaptive delay discounting under real-world stress events, and to connectome-based neuromarkers of such effects. They can explain why there was a population-level increase in several impulsive and risky behaviors during the pandemic and point to intriguing questions about the shared underlying mechanisms of stress responses, psychiatric disorders and delay discounting.

Functional Connectome Prediction of Anxiety Related to the COVID-19 Pandemic.

OBJECTIVE: Increased anxiety in response to the COVID-19 pandemic has been widely noted. The purpose of this study was to test whether the prepandemic functional connectome predicted individual anxiety induced by the pandemic. METHODS: Anxiety scores from healthy undergraduate students were collected during the severe and remission periods of the pandemic (first survey, February 22-28, 2020, N=589; second survey, April 24 to May 1, 2020, N=486). Brain imaging data and baseline (daily) anxiety ratings were acquired before the pandemic. The predictive performance of the functional connectome on individual anxiety was examined using machine learning and was validated in two external undergraduate student samples (N=149 and N=474). The clinical relevance of the findings was further explored by applying the connectome-based neuromarkers of pandemic-related anxiety to distinguish between individuals with specific mental disorders and matched healthy control subjects (generalized anxiety disorder, N=43; major depression, N=536; schizophrenia, N=72). RESULTS: Anxiety scores increased from the prepandemic baseline to the severe stage of the pandemic and remained high in the remission stage. The prepandemic functional connectome predicted pandemic-related anxiety and generalized to the external sample but showed poor performance for predicting daily anxiety. The connectome-based neuromarkers of pandemic-related anxiety further distinguished between participants with generalized anxiety and healthy control subjects but were not useful for diagnostic classification in major depression and schizophrenia. CONCLUSIONS: These findings demonstrate the feasibility of using the functional connectome to predict individual anxiety induced by major stressful events (e.g., the current global health crisis), which advances our understanding of the neurobiological basis of anxiety susceptibility and may have implications for developing targeted psychological and clinical interventions that promote the reduction of stress and anxiety.