Adaptive response of Italian young adults with autism to the COVID-19 pandemic: A longitudinal study.

The COVID-19 pandemic has represented a hazardous situation for individuals with Autism Spectrum Disorder (ASD) and their families. The difficulties, following the COVID-19-derived lockdown, have involved working from home or loss of employment, and the demands of looking after their children without the daily support of specialists. The aim of this study was to evaluate the adaptive behaviour of young adult participants with ASD after the enforcement of lockdown measures in March 2020 in a specialised centre in central Italy, by administering the Italian form of the Vineland Adaptive Behaviour Scales Second Edition (VABS-II), at baseline as well as 6 months and 1 year after the lockdown. Participants with ASD who were not able to access their normal, in-person care - they were only followed at a distance (i.e. telehealth) - declined dramatically in their adaptive behaviour during the first months after the lockdown for some VABS-II dimensions such as the socialisation and daily living domains. The effects of the lockdown on adaptive behaviour remained after 1 year. Our results emphasise the need for immediate, continuous and personal support for people with ASD during and after the restrictions caused by the COVID-19 pandemic, in order to ensure at least partial recovery of adaptive functioning.

Beneficial effects of a program of Mindfulness by remote during COVID-19 lockdown.

OBJECTIVE: In the emergency context of COVID-19 pandemic and lockdown, mindfulness relaxation techniques can provide a safe and effective strategy to obtain in a reasonably short time some degree of relief from suffering and to guarantee a greater confidence with emotional reactions in the general population. SUBJECTS AND METHODS: The Mindfulness-Based Stress Reduction program for coping with COVID-19 emergency was designed as an 8-week program during the early phase of lockdown consisting in practice meditation exercises at least once a day guided and structured by certified instructors entered on a free online platform. At the end of the program all participants completed a survey. RESULTS: A total of 108 surveys were completed (67.6% male; 32.4% female). Despite the difficult moment of lockdown and the fear linked to the pandemic, 61.9% of interviewed subjects declared a state of general well-being from fair to good linked to the practice of mindfulness. Female subjects (p=0.001), married subjects (p=0.05) and people taking pharmacologic therapy demonstrated (p=0.009) significant improvement in daily management of emotions and practical requests during the early phase of the COVID-19 outbreak. CONCLUSIONS: Mindfulness meditation may be effective in helping people to regulate emotions and to support their mental health during this period of worry and uncertainty.

Magnitude and Dynamics of the T-Cell Response to SARS-CoV-2 Infection and Vaccination

Background. T cells are central to the early identification and clearance of viral infections and support antibody generation by B cells, making them desirable for assessing the immune response to SARS-CoV-2 infection and vaccines. We combined 2 high-throughput immune profiling methods to create a quantitative picture of the SARS-CoV-2 T-cell response that is highly sensitive, durable, diagnostic, and discriminatory between natural infection and vaccination. Methods. We deeply characterized 116 convalescent COVID-19 subjects by experimentally mapping CD8 and CD4 T-cell responses via antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I and 284 class II viral peptides. We also performed T-cell receptor (TCR) repertoire sequencing on 1815 samples from 1521 PCR-confirmed SARS-CoV-2 cases and 3500 controls to identify shared public TCRs from SARS-CoV-2-associated CD8 and CD4 T cells. Combining these approaches with additional samples from vaccinated individuals, we characterized the response to natural infection as well as vaccination by separating responses to spike protein from other viral targets. Results. We find that T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the SARS-CoV-2 T-cell response peaks about 1-2 weeks after infection and is detectable at least several months after recovery. Applying these data, we trained a classifier to diagnose past SARS-CoV-2 infection based solely on TCR sequencing from blood samples and observed, at 99.8% specificity, high sensitivity soon after diagnosis (Day 3-7 = 85.1%;Day 8-14 = 94.8%) that persists after recovery (Day 29+/convalescent = 95.4%). Finally, by evaluating TCRs binding epitopes targeting all non-spike SARS-CoV-2 proteins, we were able to separate natural infection from vaccination with > 99% specificity. Conclusion. TCR repertoire sequencing from whole blood reliably measures the adaptive immune response to SARS-CoV-2 soon after viral antigenic exposure (before antibodies are typically detectable) as well as at later time points, and distinguishes post-infection vs. vaccine immune responses with high specificity. This approach to characterizing the cellular immune response has applications in clinical diagnostics as well as vaccine development and monitoring.

P.0279 Neural underpinnings of depressive and post-traumatic symptomatology in covid-19 survivors: a voxel-based morphometry study

Background: A high prevalence of depression, anxiety, insomnia and PTSD has been reported in COVID-19 survivors [1]. This is similar to what previously observed in other Coronavirus-related diseases such as SARS and MERS [2]. The pathophysiology of post-infection neuropsychiatric symptoms is likely to be multifactorial, with a role played by inflammatory and immunological factors [3], but it is still largely unknown;we thus investigated COVID-19 survivors via 3T MRI imaging to identify neural underpinnings of post-infection neuropsychiatric symptoms in order to further elucidate their complex pathophysiology. Methods: Covid-19 survivors were recruited during an ongoing prospective cohort study at IRCCS San Raffaele Hospital in Milan;psychopathology was initially measured via several self-report questionnaires (Impact of Events Scale-Revised (IES-R), Zung Self-Rating Depression Scale (ZSDS), 13-item Beck's Depression Inventory (BDI));subsequently patients (n=28) underwent 3T MRI scanning (Philips 3T Ingenia CX scanner with 32-channel sensitivity encoding SENSE head coil). T1 weighted images were processed using Computational Anatomy Toolbox (CAT12) for Statistical Parametric Mapping 12 (SPM12) in Matlab R2016b;segmentation into Gray Matter, White Matter and cerebrospinal fluid, bias regularization, non-linear modulation and normalization to MNI space were performed;measures of Total Intracranial Volume (TIV) were obtained and images were smoothed with an 8-mm full width at half maximum Gaussian filter. Multiple regressions were performed using SPM12 software package: with no a priori regions of interest selected, whole-brain gray matter volumes were used as dependent variables, psychometric scales scores as independent variables, and age, sex and TIV as nuisance covariates. Results: After VBM regression analysis covarying for age, sex and TIV, ZSDS Index scores were inversely correlated with gray matter volume in the Bilateral Anterior Cingulate Cortex (MNI 2, 24, 28, cluster level pFWE = 0.045, k=767);furthermore 3 cluster were identified comprising again the anterior cingulate cortex and the insular cortex bilaterally in which IES-R scores were inversely correlated with gray matter volumes (Cluster 1: MNI -30, 9, 3, cluster level pFWE = 0.005, k=1284;Cluster 2: MNI 36, -3, -3, cluster level pFWE = 0.037, k=773;Cluster 3: MNI 9, 30, 28, cluster level pFWE = 0.038, k=766). No other statistical significant result was found. Conclusions: Our study identified an inverse correlation between anterior cingulate cortex volumes and depressive symptomatology, measured via ZSDS, and between bilateral insulae and anterior cingulate cortex volumes and the degree of distress in response to the traumatic event, measured via the IES-R. Analogous findings have already been reported in patients with Major depression [4] and PTSD [5], and our study confirms the role of volumetric reductions of these brain regions in depressive and post-traumatic symptomatology. Given the nature of our study it is not possible to infer whether the reduction of gray matter volume is a consequence of the Covid-19 infection itself or, as it appears more likely, precede the infection acting as predisposing factor for the subsequent development of depressive and post-traumatic symptomatology. No conflict of interest

P.0691 Mood-congruent cognitive distortion and processing bias in depressed covid-19 survivors: a comparison with major depressive disorder

Introduction. COVID-19 survivors often experience psychiatric sequelae, with depressive psychopathology as the leading cause for needing psychiatric intervention [1]. Depressive cognitive distortion is a core feature of major depression, fostering the experience of negative emotions and hampering recovery [2]. Moreover, cognitive biases are well-documented in patients with inflammatory diseases and associated depressive symptomatology [3]. Considering both the high prevalence of clinical depression among COVID-19 survivors and the critical role of cognitive distortions in depression, we consider of crucial importance to investigate cognitive processing biases in COVID-19 survivors. Methods. We studied 729 participants, divided in three groups: (1) 362 COVID-19 survivors;(2) 73 inpatients with Major Depressive Disorder (MDD);(3) 294 healthy participants (HC). Severity of depression was self-rated on the Zung Self-Rating Depression Scale (ZSDS). Neuropsychological bias toward emotional stimuli and the general negative outlook on the self were tested in a self-description task [4], during which subjects were asked to self-attribute or refuse positive and negative morally tuned adjectives, and latencies and frequencies of attribution were recorded. Depressive dysfunctional attitudes in causal attribution and interpretation of hypothetical events were measured on the Cognition Questionnaire (CQ). We performed homogeneity of slope or separate slopes analysis when appropriate in the context of Generalized linear model (GLMZ), with an identity link function. Likelihood ratio test was computed as a measure of significance for tested effects and Akaike Information Criterion (AIC) was obtained as goodness of fit measure [5]. Results. 22.4% COVID survivors self-rated their depressive symptoms above the clinical threshold. Bias in speed of information processing significantly predicts self-description in all groups (COVID depressed: Wald W2=19.81;COVID non depressed: W2=15.48;MD: W2=13.65;HC: W2=33.54;all p<0.001). Information processing bias and frequencies of attribution of morally negative elements strongly predicted the severity of self-rated depressive psychopathology (ZSDS scores) (Processing bias: LR χ2=40.99, p<0.0001;Frequencies: LR χ2=127.89, p<0.0001). Additionally, the cognitive distortion in causal attribution and interpretation of hypothetical events (CQ scores) in depressed post-COVID patients showed intermediate levels of severity in all dimensions between non-depressed post-COVID patients, and MDD (post-hoc Fisher's least significance test: p<0.05 at all comparisons). Moreover, the CQ total score significantly influenced the ZSDS scores (χ2=84.60, p<0.0001). Interestingly, homogeneity of slope analysis revealed regression slopes were parallel in COVID-depressed and hospitalized MD patient groups in all models, yielding no significant group interaction. Finally, bias in information processing and negative self-description both predicted CQ scores (Latencies ratio: χ2=3.91, p=0.0479;Frequencies: χ2=42.96, p<0.0001). Conclusions. The breadth of moral self-reproach and the severity of cognitive distortion in evaluating events showed the same association with severity of depression in MDD and in post-COVID depressed patients, distributing along a gradient of severity, thus suggesting that these individual features of depressive cognitive distortion are shared in these conditions and should be addressed as treatment targets in depressed COVID-19 survivors. No conflict of interest

P.0404 Rapid antidepressant response to first-line selective serotonin reuptake inhibitors in post-COVID-19 depression

Introduction: Depression was reported in 30–40% of patients at one, three, and six months following COVID-19 [1]. The host immune response to SARS-CoV-2 infection and related severe systemic inflammation seems to be the main mechanism contributing to the development of post-COVID depression. Emerging literature suggests anti-inflammatory and antiviral properties of antidepressants in the treatment of SARS-CoV-2 infection [2]. We hypothesized that post-COVID depression, triggered by infection and sustained by systemic inflammation, could particularly benefit from antidepressants. Thus, the present study aims to investigate the efficacy of SSRI in treating post-COVID depression. Methods: We included 58 adults patients who showed depressive episodes in the six months following COVID-19. We excluded patients if they showed: other psychiatric comorbidities, ongoing treatment with antidepressants or neuroleptics, somatic disease and medications known to affect mood. The severity of depression was rated at baseline and after for four weeks from the start of the treatment on the Hamilton Depression Rating Scale (HDRS) and response was considered when the patients achieved a 50% HDRS reduction after treatment. Statistical analyses to compare group means and frequencies (Student's t-test, Pearson χ2 test) were performed. To investigate changes in HDRS scores over time, repeated measures ANOVAs (according to sex, mood disorder history, and antidepressant molecule) were performed. Results: We found that 53 (91%) patients showed a clinical response to antidepressant treatment. Age, sex, mood disorder history, and hospitalization for COVID did not affect the response rate. Patients were treated with sertraline (n=26), citalopram (n=18), paroxetine (n=8), fluvoxamine (n=4), and fluoxetine (n=2). From baseline to follow-up, patients showed a significant decrease over time of HDRS score (F=618.90, p<0.001), irrespectively of sex (0.28, p=0.599), mood disorder history (F=0.04, p=0.834), and drug used (F=1.47, p=0.239). Discussion: Common knowledge highlights that among antidepressant-treated patients, response rates are moderate (40–60%). On the contrary, we observed a rapid response to the first-line antidepressants in more than 90% of patients irrespectively of clinical variables, thus suggesting a higher antidepressant response rate in post-COVID depression. The pathophysiology of post-COVID neuropsychiatric sequelae mainly entails severe systemic inflammation and subsequent neuroinflammation. In this context, we have previously found that one and three months after COVID-19, the severity of depression was predicted by the baseline systemic immune-inflammation index (SII) [3,4]. Furthermore, we found a protective effect of the IL-1β and IL-6 receptor antagonist against post-COVID depression possibly associated with their effect in dampening SII [5]. Mounting evidence suggests that antidepressants may a) decrease markers of inflammation;b) may inhibit acid sphingomyelinase preventing the infection of epithelial cells with SARS-CoV-2;c) may prevent the COVID-19 related cytokine storm by stimulating the σ-1 receptor;d) may exert antiviral effects via lysosomotropic properties;e) may inhibit platelets activation [2]. In conclusion, we hypothesized that post-COVID depression could particularly benefit from antidepressants since this molecules have anti-inflammatory and antiviral properties, pass the BBB and accumulate in the CNS, thus preventing the neuro-inflammation triggered by SARS-CoV-2 and associated with post-COVID depression. No conflict of interest

P.0086 Clinical and psychopathological predictors of fatigue in COVID-19 survivors: a machine learning study

Introduction: The COVID-19 pandemic has led to profound mental health consequences observed during acute infection and at short, medium, and long-term follow-up [1–3]. When considering long-term sequelae, a prevalent proportion of patients infected by SARS-CoV-2 experience a “Post-COVID-19 Syndrome” characterized by fatigue, depressive symptoms, sleep disturbances, and myalgia. In this context, fatigue is recognized as one of the leading complaints in COVID-19 survivors [4]. Long-term health consequences following COVID-19 and their impact on daily quality of life are largely unknown and need further investigation. Thus, questions about possible effects of mental health on fatigue, and of COVID-19 clinical severity on both, remained unanswered. We aim to predict long-term fatigue symptoms basing on clinical and psychopathological predictors through a machine learning approach. Methods: We evaluated the fatigue syndrome and the psychopathological status of 122 adult COVID-19 survivors (80 male, mean age 59.8±12.9) six months after hospital discharge for COVID-19. Clinical and psychopathological predictors were collected for the entire sample. Fatigue at six months was assessed using the Fatigue Severity Scale (FSS). Descriptive statistical analyses to compare means and frequencies were performed. To better disentangle the relationship between somatic and psychopathological predictors and the development of fatigue, we explored the effect of each predictor in affecting fatigue by implementing 5000 non-parametric bootstraps enhanced elastic net penalized logistic regression. The model's accuracy was estimated by 5-folds stratified nested cross-validations in the outer loop to define balance accuracy value (BA), class accuracies, and area under the receiver operator curve (AUC) (for a complete description of the method see [5]). Results: Six months after hospital discharge, 28%, 29%, and 24% of the total sample showed respectively depression (according to Zung Self-Rating Depression Scale), anxiety (according to State-Trait Anxiety Inventory form Y), and sleep disturbances (according to Women's Health Initiative Insomnia Rating Scale). Fatigue was present in 19% of the patients. When entering demographical, clinical, and psychopathological predictors in the elastic net penalized logistic regression, only depressive symptomatology significantly predicted the presence of fatigue at six months (Log Odds Ratio: 2.33;Standard deviation: 1.58;Lower and Upper 95% CI: -0.78 - 5.43;Variable Inclusion Probability: 96.7%). The 10-folds cross-validated elastic net model predicted fatigue with a BA of 65%, an AUC of 77%, and a specificity for the absence of fatigue of 74%, and a sensitivity for the presence of fatigue of 55%, showing good performances in excluding fatigue syndrome. Discussion: Besides confirming a high rate of long-term neuropsychiatric sequelae, our main finding is the strict association between fatigue and depression. We fear that, rather independent of pneumonia severity, major depression after COVID-19 is associated with persistent fatigue, thus worsening the burden of a non-communicable condition triggered by infection and by infection-related systemic inflammation, but then persisting on its own. Post-COVID syndrome, mainly characterized by fatigue, depression, and sleep disturbances, will affect COVID-19 survivors' daily functioning and place additional burden on the healthcare system. Clarifying the mechanisms and risk factors underlying such long-term symptomatology is essential to identify target population and to tailor specific treatment and rehabilitation interventions to foster recovery. No conflict of interest

P.0267 Persistent psychopathology in covid-19 survivors at one-year follow-up

Introduction: The effects of COVID-19 are highly variable, with potential involvement of almost all organs and systems. While the acute and sub-acute symptoms have been well described, the possible long-term sequelae of COVID-19 have become an increasing concern [1]. One, three, and six-months follow-up studies have reported highly prevalent post COVID neuropsychiatric sequelae [2,3,4,5]. The aim of the present study is to investigate the psychopathological impact of COVID-19 in survivors at one-year follow-up, also considering the effect of possible risk factors. Methods: We prospectively evaluated the psychopathological status of 160 COVID-19 survivors one year after hospital discharge during an ongoing prospective cohort study. To keep a naturalistic study design, exclusion criteria were limited to patients under 18 years. Sociodemographic and clinical data were collected. Current psychopathology was measured using the following self-report questionnaire: Zung Self-Rating Depression Scale (ZSDS), Impact of Events Scale-Revised (IES-R), State-Trait Anxiety Inventory form Y (STAI-Y), and Fatigue Severity Score (FSS). Need of antidepressant or anxiolytic treatment in the last year was collected. Statistical analyses to compare group means and frequencies (Student's t-test, Pearson χ2 test) exploring effects of sex, psychiatric history, and hospitalization for COVID-19 were performed. Results: Overall, 77 patients (48%) scored in the clinical range in at least one psychopathological dimension among depression, anxiety, and PTSD. Females and patients with a positive previous psychiatric diagnosis showed an increased score on most measures (Table). Hospitalization for COVID-19 did not affect psychopathology. During the year after COVID-19, 25 (16%) and 23 (14%) patients started an antidepressant or anxiolytic treatment respectively.Discussion: This is the first study that investigates psychopathology in a sample of COVID-19 survivors at one-year follow-up after hospital treatment. We reported high rates of persistent psychopathology consistently with previous coronavirus outbreaks. Psychiatric consequences to SARS-CoV-2 infection can be caused by the immune-inflammatory response to the virus itself or by psychological stressors such as social isolation, concerns about infecting others, and stigma. Considering that neuropsychiatric sequelae associates with a markedly increased risk of all-cause mortality, and given the alarming prevalence of post-COVID psychopathology, we now suggest to routinely asses psychopathology of COVID-19 survivors in order to promptly diagnose emergent disorders and to treat them to reduce the disease burden and related years of life lived with disability. No conflict of interest

Health for All: a health literate, culturally competent and participative approach

Background Three micro projects, planned by the multidisciplinary team in a Primary Care setting targeting refugees and asylum seekers, aim at migrants' health, building strategies together with the private and social sectors involved, for a culturally competent and Health Literate approach, within the ICARE Project activities. Three different areas of work were identified: detecting barriers to migrants' management of prevention and care of Covid-19;preventing domestic accidents in children;improving the participation to screening programs among refugees and women victims of human trafficking. Objectives The main objective is to improve migrants' engagement in health care and health promotion activities in a new context of living strongly influenced by the pandemic waves of Covid-19. The second objective is to enable a participative approach to migrants' health among intercultural mediators, nurses, paediatrician, infectious diseases specialist, psychologist, social workers and representatives of No Profit Organizations (NPOs) that support refugees and women victims of human trafficking within the “Oltre la Strada” Regional project. Results A closed questionnaire assessing knowledge about prevention and management of Covid-19 has been carried out among 100 refugees and asylum seekers. A video on prevention of domestic accidents was made and translated in eleven languages as a result of a cooperation with intercultural mediators, to encourage questions during the educational meetings. Finally, a focus group was performed with NPOs in order to identify common areas of work, enabling a participative approach to improve migrants' engagement. Conclusions The preliminary results reveal the need to approach migrants' health focusing on their participation through a multidimensional, person-centred, Health Literate and culturally competent cooperation. The outcomes from data analysis of the ongoing activities within the ICARE Project will be presented at the conference. Key messages A multidimensional approach to migrants’ health enables all stakeholders to learn from each others, improving the awareness about the relationship between health literacy and health outcomes. The cooperation between health, social and private sectors could be strategic for an organizational change towards a person-centred approach.

Emotions, moods and hyperreality: social media and the stock market during the first phase of COVID-19 pandemic

Purpose: This paper aims to expand the emerging literature on COVID-19 and the financial markets by searching for a relationship between the uncertainty of the first phase of the COVID-19 pandemic experienced through social media and the extreme volatility of the Italian stock market. Design/methodology/approach: The authors analyze the relationship between social media and stock market trends during the first phase of the COVID-19 pandemic through the lens of social theory and Baudrillard's simulacra and hyperreality theory. The authors conducted the data analysis in two phases: the emotional and Granger correlation analysis by using the KPI6 software to analyze 3,275,588 tweets for the predominant emotion on each day and observe its relationship with the stock market. Findings: The research results show a significant Granger causality relation between tweets on a particular day and the closing price of the FTSE MIB during the first phase of the COVID-19 epidemic. The results highlight a strong relationship between social media hyperreality and the real world. The study confirms the role of social media in predicting stock market volatility. Research limitations/implications: The findings have theoretical and practical implications as they reveal the relevance of social media in our society and its relationship with businesses and economies. In an emergency, social media, as an expression of users' feelings and emotions, can generate a state of hyperreality that is strong correlated with reality. Since social media allows users to publish and share messages without any filter and mediation, the hyperreality generated is affected by highly subjective elements. Originality/value: This research is different from the previous ones on the same topic because unlike previous studies, conducted under normal or simulated scenarios, this study is focused on the first phase of an unpredictable and unforeseen emergency event: the COVID-19 pandemic. This research adopts a multidisciplinary approach and integrates previous studies on the economic and financial effects generated by social media by applying well-known theories to a new and unexplored context. The study reveals the significant impact generated by social media on stock markets during a global pandemic. © 2021, Arianna Lazzini, Simone Lazzini, Federica Balluchi and Marco Mazza.

What about heart and mind in the COVID-19 era?

From the time of Hippocratic medicine, heart-brain interactions have been recognized and contributed to both mental and physical health. Heart-brain interactions are complex and multifaceted and appear to be bidirectional. Exposure to chronic and daily stressors such as quarantine, or severe psychological trauma like a significant person in danger of life can affect the cardiovascular system and the emotional experience of the individual, leading to an increased risk of developing a cardiovascular disease or mental illness. Subjects with comorbidities between mental disorders and heart diseases are obviously more susceptible to be influenced by emotional burden due to the spread of COVID-19, with emotional responses characterized by fear, panic, anger, frustration. Psychological services and crisis interventions are needed at an early stage to reduce anxiety, depression and post-traumatic stress disorder in such a stressful period, with a special attention to special groups of patients, such as women, children, or the elderly.