Prognostic performance of blood neurofilament light chain protein in hospitalized COVID-19 patients without major central nervous system manifestations: an individual participant data meta-analysis.

BACKGROUND AND AIMS: To investigate the prognostic value of blood neurofilament light chain protein (NfL) levels in the acute phase of coronavirus disease 2019 (COVID-19). METHODS: We conducted an individual participant data (IPD) meta-analysis after screening on MEDLINE and Scopus to May 23rd 2022. We included studies with hospitalized adult COVID-19 patients without major COVID-19-associated central nervous system (CNS) manifestations and with a measurement of blood NfL in the acute phase as well as data regarding at least one clinical outcome including intensive care unit (ICU) admission, need of mechanical ventilation (MV) and death. We derived the age-adjusted measures NfL Z scores and conducted mixed-effects modelling to test associations between NfL Z scores and other variables, encompassing clinical outcomes. Summary receiver operating characteristic curves (SROCs) were used to calculate the area under the curve (AUC) for blood NfL. RESULTS: We identified 382 records, of which 7 studies were included with a total of 669 hospitalized COVID-19 cases (mean age 66.2 ± 15.0 years, 68.1% males). Median NfL Z score at admission was elevated compared to the age-corrected reference population (2.37, IQR: 1.13-3.06, referring to 99th percentile in healthy controls). NfL Z scores were significantly associated with disease duration and severity. Higher NfL Z scores were associated with a higher likelihood of ICU admission, need of MV, and death. SROCs revealed AUCs of 0.74, 0.80 and 0.71 for mortality, need of MV and ICU admission, respectively. CONCLUSIONS: Blood NfL levels were elevated in the acute phase of COVID-19 patients without major CNS manifestations and associated with clinical severity and poor outcome. The marker might ameliorate the performance of prognostic multivariable algorithms in COVID-19.

Anti-SARS-CoV-2 T-stem cell memory persists in ocrelizumab-treated MS patients.

BACKGROUND: Development of long-lasting anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) T-cell responses in persons with multiple sclerosis (pwMS) treated with ocrelizumab is questioned. OBJECTIVE: Investigate antiviral T-cell responses after infection with SARS-CoV-2 in ocrelizumab-treated pwMS. Control groups included ocrelizumab-treated pwMS without SARS-CoV-2 infection, and non-MS individuals with and without SARS-CoV-2 infection. METHODS: Peripheral blood mononuclear cells were stimulated with SARS-CoV-2 peptide pools and T-cell reactivity was assessed by ELISPOT for interferon (IFN)-γ detection, and by multiparametric fluorescence-activated cell sorting (FACS) analyses for assessment and characterization of T-cell activation. RESULTS: ELISPOT assay against the spike and the N protein of SARS-CoV-2 displayed specific T-cell reactivity in 28/29 (96%) pwMS treated with ocrelizumab and infected by SARS-CoV-2, similar to infected persons without MS. This reactivity was present 1 year after infection and independent from the time of ocrelizumab infusion. FACS analysis following stimulation with SARS-CoV-2 peptide pools showed the presence of activation-induced markers (AIMs) in both CD4+ and CD8+ T-cell subsets in 96% and 92% of these individuals, respectively. Within naïve AIM+ CD4+ and CD8+ T-cells, we detected T memory stem cells, suggesting the acquisition of long-term memory. CONCLUSIONS: B-cell depletion using ocrelizumab does not impair the development of long-lasting anti-SARS-CoV-2 T-cell responses.

Vaccination Opportunities in Multiple Sclerosis Patients Treated with Cladribine Tablets.

COVID 19 pandemic and mass vaccination campaigns have revealed the situation of the most vulnerable patients. In this work, we focused our attention to patients who have Multiple Sclerosis (MS), particularly in treatment with cladribine tablets, trying to understand if and when it is possible to administer the vaccine successfully. In light of the novel topic, we studied the existing literature and analysed experiences with previous vaccinations, such as influenza and VZV, as well as data from countries where vaccination campaigns had already begun. Overall, we have taken into account the mechanism of action, the pharmacokinetic/pharmacodynamic of cladribine, and the changes in the immune system after its administration, together with the preliminary data about the humoral response to influenza, VZV, and SARS-CoV-2 vaccinations in cladribine treated patients. In conclusion, data showed that the use of cladribine tablets seems to permit flexibility regarding vaccination timing and we suggest that vaccination in those patients should be safe and effective. The current COVID 19 pandemic has re-ignited the interest in vaccines and vaccination procedures. The importance of including fragile individuals has increased as a result of mass vaccination. Millions of patients with multiple sclerosis (MS) around the world are debating whether they can safely receive their vaccine shot with the same efficacy despite receiving immune-modulating or immune-suppressive treatments. In the absence of conclusive empirical data, we will review and discuss the available evidence and the reasonable conclusions for one specific treatment, namely cladribine tablets (Mavenclad).

A multiparametric score for assessing the individual risk of severe Covid-19 among patients with Multiple Sclerosis.

BACKGROUND: Many risk factors for the development of severe forms of Covid-19 have been identified, some applying to the general population and others specific to Multiple Sclerosis (MS) patients. However, a score for quantifying the individual risk of severe Covid-19 in patients with MS is not available. The aim of this study was to construct such score and to evaluate its performance. METHODS: Data on patients with MS infected with Covid-19 in Italy, Turkey and South America were extracted from the Musc-19 platform. After imputation of missing values, data were separated into training data set (70%) and validation data set (30%). Univariable logistic regression models were performed in the training dataset to identify the main risk factors to be included in the multivariable logistic regression analyses. To select the most relevant variables we applied three different approaches: (1) multivariable stepwise, (2) Lasso regression, (3) Bayesian model averaging. Three scores were defined as the linear combination of the coefficients estimated in the models multiplied by the corresponding value of the variables and higher scores were associated to higher risk of severe Covid-19 course. The performances of the three scores were compared in the validation dataset based on the area under the ROC curve (AUC) and an optimal cut-off was calculated in the training dataset for the score with the best performance. The probability of showing a severe Covid-19 course was calculated based on the score with the best performance. RESULTS: 3852 patients were included in the study (2696 in the training dataset and 1156 in the validation data set). 17% of the patients required hospitalization and risk factors for severe Covid-19 course were older age, male sex, living in Turkey or South America instead of living in Italy, presence of comorbidities, progressive MS, longer disease duration, higher Expanded Disability Status Scale, Methylprednisolone use and anti-CD20 treatment. The score with the best performance was the one derived using the Lasso selection approach (AUC= 0.72) and it was built with the following variables: age, sex, country, BMI, presence of comorbidities, EDSS, methylprednisolone use, treatment. An excel spreadsheet to calculate the score and the probability of severe Covid-19 is available at the following link: https://osf.io/ac47u/?view_only=691814d57b564a34b3596e4fcdcf8580. CONCLUSIONS: The originality of this study consists in building a useful tool to quantify the individual risk for Covid-19 severity based on patient's characteristics. Due to the modest predictive ability and to the need of external validation, this tool is not ready for being fully used in clinical practice to make important decisions or interventions. However, it can be used as an additional instrument to identify high-risk patients and persuade them to take important measures to prevent Covid-19 infection (i.e. getting vaccinated against Covid-19, adhering to social distancing, and using of personal protection equipment).

Mood-congruent negative thinking styles and cognitive vulnerability in depressed COVID-19 survivors: A comparison with major depressive disorder.

BACKGROUND: COVID-19 is associated with depressive psychopathology in survivors. Negative thinking styles are a core feature of major depression, fostering the experience of negative emotions and affects and hampering recovery. This cognitive vulnerability has been observed in medical conditions associated with depression, but never explored in post-COVID depression. METHODS: We studied 729 participants: 362 COVID-19 survivors, 73 inpatients with Major Depressive Disorder (MDD), and 294 healthy participants (HC). Severity of depression was self-rated on the Zung Self-Rating Depression Scale (ZSDS). Neuropsychological bias toward negative emotional stimuli and the negative outlook on the self were tested in a self-description task, yielding latencies and frequencies of attribution of morally tuned elements. Dimensions of negative thinking and depressive cognitive style in evaluation of hypothetical events were measured on the Cognition Questionnaire (CQ). RESULTS: 22.4% COVID survivors self-rated depression above the clinical threshold. Frequencies and latencies of attribution of morally negative elements, and CQ scores, correlated between themselves and predicted ZSDS scores, with post-COVID depressed patients showing intermediate scores between the more severe MDD patients, and non-depressed post-COVID participants and HC. LIMITATIONS: Recruitment was in a single center, thus raising the possibility of population stratification. CONCLUSIONS: The breadth of self-reproach and depressive cognitive style 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 individual features of negative thinking styles are shared in these conditions, and should be addressed as treatment targets in depressed COVID-19 survivors.

Brain correlates of depression, post-traumatic distress, and inflammatory biomarkers in COVID-19 survivors: A multimodal magnetic resonance imaging study.

Psychiatric sequelae substantially contribute to the post-acute burden of disease associated with COVID-19, persisting months after clearance of the virus. Brain imaging shows white matter (WM) hypodensities/hyperintensities, and the involvement of grey matter (GM) in prefrontal, anterior cingulate (ACC) and insular cortex after COVID, but little is known about brain correlates of persistent psychopathology. With a multimodal approach, we studied whole brain voxel-based morphometry, diffusion-tensor imaging, and resting-state connectivity, to correlate MRI measures with depression and post-traumatic distress (PTSD) in 42 COVID-19 survivors without brain lesions, at 90.59 â€‹± â€‹54.66 days after COVID. Systemic immune-inflammation index (SII) measured in the emergency department, which reflects the immune response and systemic inflammation based on peripheral lymphocyte, neutrophil, and platelet counts, predicted worse self-rated depression and PTSD, widespread lower diffusivity along the main axis of WM tracts, and abnormal functional connectivity (FC) among resting state networks. Self-rated depression and PTSD inversely correlated with GM volumes in ACC and insula, axial diffusivity, and associated with FC. We observed overlapping associations between severity of inflammation during acute COVID-19, brain structure and function, and severity of depression and post-traumatic distress in survivors, thus warranting interest for further study of brain correlates of the post-acute COVID-19 syndrome. Beyond COVID-19, these findings support the hypothesis that regional GM, WM microstructure, and FC could mediate the relationship between a medical illness and its psychopathological sequelae, and are in agreement with current perspectives on the brain structural and functional underpinnings of depressive psychopathology.

One-year mental health outcomes in a cohort of COVID-19 survivors.

COVID-19 survivors are at increased risk of persistent psychopathology after the infection. Despite long-term sequelae are an increasing concern, long-term neuropsychiatric consequences remain largely unclear. This cohort study aimed at investigating the psychopathological impact of COVID-19 in Italy one year after infection, outlining the trajectory of symptomatology at one, six-, and twelve-months follow-up. We evaluated 402, 216, and 192 COVID-19 survivors respectively at one, six, and 12 months. A subgroup of 95 patients was evaluated longitudinally both at one, six, and 12 months. Validated self-report questionnaires were administered to assess depression, fatigue, anxiety, and post-traumatic distress. Socio-demographics and setting of care information were gathered for each participant. At six and twelve months, respectively 94 (44%) and 86 (45%) patients self-rated in the clinical range in at least one psychopathological dimension. Pathological fatigue at twelve months was detected in 63 patients (33%). Considering the longitudinal cohort an interaction effect of sex and time was observed for depression (F = 8.63, p < 0.001) and anxiety (F = 5.42, p = 0.005) with males showing a significant increasing trend of symptoms, whereas an opposite course was observed in females. High prevalence of psychiatric sequelae six and 12 months after COVID-19 was reported for the first time. These findings confirm the need to provide integrated multidisciplinary services to properly address long-lasting mental health sequelae of COVID-19 and to treat them with the aim of reducing the disease burden and related years of life lived with disability.

Long-term consequences of COVID-19 on cognitive functioning up to 6 months after discharge: role of depression and impact on quality of life.

Neurologic and psychiatric symptoms have been reported in the months following the infection with COVID-19. A low-grade inflammation has been associated both with depression and cognitive symptoms, suggesting a link between these disorders. The aim of the study is to investigate cognitive functioning 6 months following hospital discharge for COVID-19, the impact of depression, and the consequences on quality of life. Ninety-two COVID-19 survivors evaluated at 1-month follow-up, 122 evaluated at 3 months and 98 evaluated at 6 months performed neuropsychological and psychiatric evaluations and were compared with a healthy comparison group (HC) of 165 subjects and 165 patients with major depression (MDD). Cognitive performances were adjusted for age, sex, and education. Seventy-nine percent of COVID-19 survivors at 1 month and 75% at 3- and 6-month follow-up showed cognitive impairment in at least one cognitive function. No significant difference in cognitive performances was observed between 1-, 3-, and 6-months follow-up. COVID-19 patients performed worse than HC but better than MDD in psychomotor coordination and speed of information processing. No difference between COVID-19 survivors and MDD was observed for verbal fluency, and executive functions, which were lower than in HC. Finally, COVID-19 survivors performed the same as HC in working memory and verbal memory. The factor that most affected cognitive performance was depressive psychopathology which, in turn, interact with cognitive functions in determining quality of life. Our results confirm that COVID-19 sequelae include signs of cognitive impairment which persist up to 6 months after hospital discharge and affect quality of life.

CXCL10 levels at hospital admission predict COVID-19 outcome: hierarchical assessment of 53 putative inflammatory biomarkers in an observational study.

BACKGROUND: Host inflammation contributes to determine whether SARS-CoV-2 infection causes mild or life-threatening disease. Tools are needed for early risk assessment. METHODS: We studied in 111 COVID-19 patients prospectively followed at a single reference Hospital fifty-three potential biomarkers including alarmins, cytokines, adipocytokines and growth factors, humoral innate immune and neuroendocrine molecules and regulators of iron metabolism. Biomarkers at hospital admission together with age, degree of hypoxia, neutrophil to lymphocyte ratio (NLR), lactate dehydrogenase (LDH), C-reactive protein (CRP) and creatinine were analysed within a data-driven approach to classify patients with respect to survival and ICU outcomes. Classification and regression tree (CART) models were used to identify prognostic biomarkers. RESULTS: Among the fifty-three potential biomarkers, the classification tree analysis selected CXCL10 at hospital admission, in combination with NLR and time from onset, as the best predictor of ICU transfer (AUC [95% CI] = 0.8374 [0.6233-0.8435]), while it was selected alone to predict death (AUC [95% CI] = 0.7334 [0.7547-0.9201]). CXCL10 concentration abated in COVID-19 survivors after healing and discharge from the hospital. CONCLUSIONS: CXCL10 results from a data-driven analysis, that accounts for presence of confounding factors, as the most robust predictive biomarker of patient outcome in COVID-19.

SARS-CoV-2 serology after COVID-19 in multiple sclerosis: An international cohort study.

BACKGROUND: The MuSC-19 project is an Italian cohort study open to international partners that collects data on multiple sclerosis (MS) patients with COVID-19. During the second wave of the pandemic, serological tests became routinely available. OBJECTIVE: To evaluate the seroprevalence of anti-SARS-CoV-2 antibodies according to the use of disease-modifying therapy (DMT) in a subset of patients included in the MuSC-19 data set who had undergone a serological test. METHODS: We evaluated the association between positive serological test results and time elapsed since infection onset, age, sex, Expanded Disability Status Scale score, comorbidities and DMT exposure using a multivariable logistic model. RESULTS: Data were collected from 423 patients (345 from Italy, 61 from Turkey and 17 from Brazil) with a serological test performed during follow-up. Overall, 325 out of 423 tested patients (76.8%) had a positive serological test. At multivariate analysis, therapy with anti-CD20 was significantly associated with a reduced probability of developing antibodies after COVID-19 (odds ratio (OR) = 0.20, p = 0.002). CONCLUSION: Patients with MS maintain the capacity to develop humoral immune response against SARS-COV-2, although to a lesser extent when treated with anti-CD20 drugs. Overall, our results are reassuring with respect to the possibility to achieve sufficient immunization with vaccination.

Blood neurofilament light chain and total tau levels at admission predict death in COVID-19 patients.

BACKGROUND AND AIMS: Patients infected with SARS-CoV-2 range from asymptomatic, to mild, moderate or severe disease evolution including fatal outcome. Thus, early predictors of clinical outcome are highly needed. We investigated markers of neural tissue damage as a possible early sign of multisystem involvement to assess their clinical prognostic value on survival or transfer to intensive care unit (ICU). METHODS: We collected blood from 104 patients infected with SARS-CoV-2 the day of admission to the emergency room and measured blood neurofilament light chair (NfL), glial fibrillary acidic protein (GFAP), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and total tau protein levels. RESULTS: We found that NfL, GFAP, and tau were significantly increased in patients with fatal outcome, while NfL and UCH-L1 in those needing ICU transfer. ROC and Kaplan-Meier curves indicated that total tau levels at admission accurately predict mortality. CONCLUSIONS: Blood neural markers may provide additional prognostic value to conventional biomarkers used to predict COVID-19 outcome.

Persistent psychopathology and neurocognitive impairment in COVID-19 survivors: Effect of inflammatory biomarkers at three-month follow-up.

COVID-19 outbreak is associated with mental health implications during viral infection and at short-term follow-up. Data on psychiatric and cognitive sequelae at medium-term follow-up are still lacking. During an ongoing prospective cohort study, the psychopathological and cognitive status of 226 COVID-19 pneumonia survivors (149 male, mean age 58) were prospectively evaluated one and three months after hospital discharge. Psychiatric clinical interview, self-report questionnaires, and neuropsychological profiling of verbal memory, working memory, psychomotor coordination, executive functions, attention and information processing, and verbal fluency were performed. Three months after discharge from the hospital, 35.8% still self-rated symptoms in the clinical range in at least one psychopathological dimension. We observed persistent depressive symptomatology, while PTSD, anxiety, and insomnia decreased during follow-up. Sex, previous psychiatric history, and the presence of depression at one month affected the depressive symptomatology at three months. Regardless of clinical physical severity, 78% of the sample showed poor performances in at least one cognitive domain, with executive functions and psychomotor coordination being impaired in 50% and 57% of the sample. Baseline systemic immune-inflammation index (SII), which reflects the immune response and systemic inflammation based on peripheral lymphocyte, neutrophil, and platelet counts, predicted self-rated depressive symptomatology and cognitive impairment at three-months follow-up; and changes of SII predicted changes of depression during follow-up. Neurocognitive impairments associated with severity of depressive psychopathology, and processing speed, verbal memory and fluency, and psychomotor coordination were predicted by baseline SII. We hypothesize that COVID-19 could result in prolonged systemic inflammation that predisposes patients to persistent depression and associated neurocognitive dysfunction. The linkage between inflammation, depression, and neurocognition in patients with COVID-19 should be investigated in long-term longitudinal studies, to better personalize treatment options for COVID-19 survivors.

Anxiety and depression in COVID-19 survivors: Role of inflammatory and clinical predictors.

Infection-triggered perturbation of the immune system could induce psychopathology, and psychiatric sequelae were observed after previous coronavirus outbreaks. The spreading of the Severe Acute Respiratory Syndrome Coronavirus (COVID-19) pandemic could be associated with psychiatric implications. We investigated the psychopathological impact of COVID-19 in survivors, also considering the effect of clinical and inflammatory predictors. We screened for psychiatric symptoms 402 adults surviving COVID-19 (265 male, mean age 58), at one month follow-up after hospital treatment. A clinical interview and a battery of self-report questionnaires were used to investigate post-traumatic stress disorder (PTSD), depression, anxiety, insomnia, and obsessive-compulsive (OC) symptomatology. We collected sociodemographic information, clinical data, baseline inflammatory markers and follow-up oxygen saturation levels. A significant proportion of patients self-rated in the psychopathological range: 28% for PTSD, 31% for depression, 42% for anxiety, 20% for OC symptoms, and 40% for insomnia. Overall, 56% scored in the pathological range in at least one clinical dimension. Despite significantly lower levels of baseline inflammatory markers, females suffered more for both anxiety and depression. Patients with a positive previous psychiatric diagnosis showed increased scores on most psychopathological measures, with similar baseline inflammation. Baseline systemic immune-inflammation index (SII), which reflects the immune response and systemic inflammation based on peripheral lymphocyte, neutrophil, and platelet counts, positively associated with scores of depression and anxiety at follow-up. PTSD, major depression, and anxiety, are all high-burden non-communicable conditions associated with years of life lived with disability. Considering the alarming impact of COVID-19 infection on mental health, the current insights on inflammation in psychiatry, and the present observation of worse inflammation leading to worse depression, we recommend to assess psychopathology of COVID-19 survivors and to deepen research on inflammatory biomarkers, in order to diagnose and treat emergent psychiatric conditions.