Biobanking for COVID-19 research.

BACKGROUND: Biobanks are imperative infrastructures, particularly during outbreaks, when there is an obligation to acquire and share knowledge as quick as possible to allow for implementation of science-based preventive, diagnostic, prognostic, and therapeutic strategies. METHODS: We established a COVID-19 biobank with the aim of collecting high-quality and well-annotated human biospecimens, in the effort to understand the pathogenic mechanisms underlying COVID-19 and identify therapeutic targets (COVID-BioB, NCT04318366). Here we describe our experience and briefly review the characteristics of the biobanks for COVID-19 that have been so far established. RESULTS: A total of 46,677 samples have been collected from 913 participants (63.3% males, median [IQR] age 62.2 [51.2-74.0] years) since the beginning of the program. Most patients (66.9%) had been admitted to hospital for COVID-19, with a median length of stay of 15.0 (9.0-27.0) days. A minority of patients (13.3% of the total) had been admitted for other reasons and subsequently tested positive for SARS-CoV-2. The remainder were managed at home after being seen at the Emergency Department. CONCLUSIONS: Having a solid research infrastructure already in place, along with flexibility and adaptability to new requirements, allowed for the quick building of a COVID-19 biobank that will help expand and share the knowledge of SARS-CoV-2.

Chitinase-3-like protein-1 at hospital admission predicts COVID-19 outcome: a prospective cohort study.

Infectious and inflammatory stimuli elicit the generation of chitinase-3-like protein-1 (CHI3L1), involved in tissue damage, repair and remodeling. We evaluated whether plasma CHI3L1 at disease onset predicts clinical outcome of patients with Coronavirus 2019 (COVID-19) disease. Blood from 191 prospectively followed COVID-19 patients were collected at hospital admission between March 18th and May 5th, 2020. Plasma from 80 survivors was collected one month post-discharge. Forty age- and sex-matched healthy volunteers served as controls. Primary outcome was transfer to intensive care unit (ICU) or death. CHI3L1 was higher in COVID-19 patients than controls (p < 0.0001). Patients with unfavorable outcome (41 patients admitted to ICU, 47 died) had significantly higher CHI3L1 levels than non-ICU survivors (p < 0.0001). CHI3L1 levels abated in survivors one month post-discharge, regardless of initial disease severity (p < 0.0001), although remaining higher than controls (p < 0.05). Cox regression analysis revealed that CHI3L1 levels predict primary outcome independently of age, sex, comorbidities, degree of respiratory insufficiency and systemic inflammation or time from symptom onset to sampling (p < 0.0001). Kaplan-Meier curve analysis confirmed that patients with CHI3L1 levels above the median (361 ng/mL) had a poorer prognosis (log rank test, p < 0.0001). Plasma CHI3L1 is increased in COVID-19 patients and predicts adverse outcome.

Chromogranin A plasma levels predict mortality in COVID-19.

BACKGROUND: Chromogranin A (CgA) and its fragment vasostatin I (VS-I) are secreted in the blood by endocrine/neuroendocrine cells and regulate stress responses. Their involvement in Coronavirus 2019 disease (COVID-19) has not been investigated. METHODS: CgA and VS-I plasma concentrations were measured at hospital admission from March to May 2020 in 190 patients. 40 age- and sex-matched healthy volunteers served as controls. CgA and VS-I levels relationship with demographics, comorbidities and disease severity was assessed through Mann Whitney U test or Spearman correlation test. Cox regression analysis and Kaplan Meier survival curves were performed to investigate the impact of the CgA and VS-I levels on in-hospital mortality. RESULTS: Median CgA and VS-I levels were higher in patients than in healthy controls (CgA: 0.558 nM [interquartile range, IQR 0.358-1.046] vs 0.368 nM [IQR 0.288-0.490] respectively, p = 0.0017; VS-I: 0.357 nM [IQR 0.196-0.465] vs 0.144 nM [0.144-0.156] respectively, p<0.0001). Concentration of CgA, but not of VS-I, significantly increased in patients who died (n = 47) than in survivors (n = 143) (median 0.948 nM [IQR 0.514-1.754] vs 0.507 nM [IQR 0.343-0.785], p = 0.00026). Levels of CgA were independent predictors of in-hospital mortality (hazard ratio 1.28 [95% confidence interval 1.077-1.522], p = 0.005) when adjusted for age, number of comorbidities, respiratory insufficiency degree, C-reactive protein levels and time from symptom onset to sampling. Kaplan Meier curves revealed a significantly increased mortality rate in patients with CgA levels above 0.558 nM (median value, log rank test, p = 0.001). CONCLUSION: Plasma CgA levels increase in COVID-19 patients and represent an early independent predictor of mortality.

Unconventional CD147-dependent platelet activation elicited by SARS-CoV-2 in COVID-19.

BACKGROUND: Platelet activation and thrombotic events characterizes COVID-19. OBJECTIVES: To characterize platelet activation and determine if SARS-CoV-2 induces platelet activation. PATIENTS/METHODS: We investigated platelet activation in 119 COVID-19 patients at admission in a university hospital in Milan, Italy, between March 18 and May 5, 2020. Sixty-nine subjects (36 healthy donors, 26 patients with coronary artery disease, coronary artery disease, and seven patients with sepsis) served as controls. RESULTS: COVID-19 patients had activated platelets, as assessed by the expression and distribution of HMGB1 and von Willebrand factor, and by the accumulation of platelet-derived (plt) extracellular vesicles (EVs) and HMGB1+ plt-EVs in the plasma. P-selectin upregulation was not detectable on the platelet surface in a fraction of patients (55%) and the concentration of soluble P-selectin in the plasma was conversely increased. The plasma concentration of HMGB1+ plt-EVs of patients at hospital admission remained in a multivariate analysis an independent predictor of the clinical outcome, as assessed using a 6-point ordinal scale (from 1 = discharged to 6 = death). Platelets interacting in vitro with SARS-CoV-2 underwent activation, which was replicated using SARS-CoV-2 pseudo-viral particles and purified recombinant SARS-CoV-2 spike protein S1 subunits. Human platelets express CD147, a putative coreceptor for SARS-CoV-2, and Spike-dependent platelet activation, aggregation and granule release, release of soluble P-selectin and HMGB1+ plt-EVs abated in the presence of anti-CD147 antibodies. CONCLUSIONS: Hence, an early and intense platelet activation, which is reproduced by stimulating platelets in vitro with SARS-CoV-2, characterizes COVID-19 and could contribute to the inflammatory and hemostatic manifestations of the disease.

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.

Adiponectin to leptin ratio reflects inflammatory burden and survival in COVID-19.

AIM: Obesity is a risk factor for COVID-19, but the underlying mechanisms are unclear. We investigated the role of adiponectin (an anti-inflammatory adipokine), leptin (a pro-inflammatory adipokine) and their ratio (Adpn/Lep) in this context. DESIGN: Single-centre, prospective observational study. METHODS: Adiponectin and leptin were measured in 60 COVID-19 patients with mild (not hospitalised, n=11), moderate (hospitalised but not requiring intensive care, n=25) and severe (admission to the intensive care unit [ICU] or death, n=24) disease. RESULTS: Adiponectin and leptin levels were similar across severity groups, but patients with moderate severity had the highest Adpn/Lep ratio (1.2 [0.5; 2.0], 5.0 [1.6; 11.2], 2.1 [1.0; 3.6] in mild, moderate and severe disease; P = 0.019). Adpn/Lep, but not adiponectin or leptin alone, correlated with systemic inflammation (C reactive protein, CRP: Spearman's rho 0.293, P = 0.023). When dividing patients into Adpn/Lep tertiles, adiponectin was highest, whereas leptin was lowest in the third (highest) tertile. Patients in the highest Adpn/Lep tertile had numerically lower rates of obesity, diabetes and hypertension, and lower rates of death or admission to ICU versus other tertiles. At linear regression in the whole cohort, CRP significantly predicted Adpn/Lep (ß 0.291, P = 0.022), while female gender (ß -0.289, P = 0.016), diabetes (ß -0.257, P = 0.028), and hypertension (ß -239, P = 0.043) were negative predictors. CONCLUSIONS: We speculate that the rise in Adpn/Lep, due to increased adiponectin and reduced leptin, is a compensatory response to systemic inflammation. In patients with worse cardiometabolic health (e.g. diabetes, hypertension) this mechanism might be blunted, possibly contributing to higher mortality.

COVID-19: Pharmacology and kinetics of viral clearance.

Coronavirus Disease 2019 (COVID-19) is a pandemic disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The clinical spectrum of COVID-19 is broad and varies from mild to severe forms complicated by acute respiratory distress and death. This heterogeneity might reflect the ability of the host immune system to interact with SARS-CoV2 or the characteristics of the virus itself in terms of loads or persistence. Information on this issue might derive from interventional studies. However, results from high-quality trials are scarce. Here we evaluate the level of evidence of available published interventional studies, with a focus on randomised controlled trials and the efficacy of therapies on clinical outcomes. Moreover, we present data on a large cohort of well-characterized patients hospitalized at a single University Hospital in Milano (Italy), correlating viral clearance with clinical and biochemical features of patients.

Patients with COVID-19: in the dark-NETs of neutrophils.

SARS-CoV-2 infection poses a major threat to the lungs and multiple other organs, occasionally causing death. Until effective vaccines are developed to curb the pandemic, it is paramount to define the mechanisms and develop protective therapies to prevent organ dysfunction in patients with COVID-19. Individuals that develop severe manifestations have signs of dysregulated innate and adaptive immune responses. Emerging evidence implicates neutrophils and the disbalance between neutrophil extracellular trap (NET) formation and degradation plays a central role in the pathophysiology of inflammation, coagulopathy, organ damage, and immunothrombosis that characterize severe cases of COVID-19. Here, we discuss the evidence supporting a role for NETs in COVID-19 manifestations and present putative mechanisms, by which NETs promote tissue injury and immunothrombosis. We present therapeutic strategies, which have been successful in the treatment of immunο-inflammatory disorders and which target dysregulated NET formation or degradation, as potential approaches that may benefit patients with severe COVID-19.

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.