Combining Deep Phenotyping of Serum Proteomics and Clinical Data via Machine Learning for COVID-19 Biomarker Discovery.

The persistence of long-term coronavirus-induced disease 2019 (COVID-19) sequelae demands better insights into its natural history. Therefore, it is crucial to discover the biomarkers of disease outcome to improve clinical practice. In this study, 160 COVID-19 patients were enrolled, of whom 80 had a "non-severe" and 80 had a "severe" outcome. Sera were analyzed by proximity extension assay (PEA) to assess 274 unique proteins associated with inflammation, cardiometabolic, and neurologic diseases. The main clinical and hematochemical data associated with disease outcome were grouped with serological data to form a dataset for the supervised machine learning techniques. We identified nine proteins (i.e., CD200R1, MCP1, MCP3, IL6, LTBP2, MATN3, TRANCE, α2-MRAP, and KIT) that contributed to the correct classification of COVID-19 disease severity when combined with relative neutrophil and lymphocyte counts. By analyzing PEA, clinical and hematochemical data with statistical methods that were able to handle many variables in the presence of a relatively small sample size, we identified nine potential serum biomarkers of a "severe" outcome. Most of these were confirmed by literature data. Importantly, we found three biomarkers associated with central nervous system pathologies and protective factors, which were downregulated in the most severe cases.

Cytokines from Bench to Bedside: A Retrospective Study Identifies a Definite Panel of Biomarkers to Early Assess the Risk of Negative Outcome in COVID-19 Patients.

The main aim of this study was to identify the most relevant cytokines which, when assessed in the earliest stages from hospital admission, may help to select COVID-19 patients with worse prognosis. A retrospective observational study was conducted in 415 COVID-19 patients (272 males; mean age 68 ± 14 years) hospitalized between May 2020 and March 2021. Within the first 72 h from hospital admission, patients were tested for a large panel of biomarkers, including C-reactive protein (CRP), Mid-regional proadrenomedullin (MR-proADM), Interferon-γ, interleukin 6 (IL-6), IL-1ß, IL-8, IL-10, soluble IL2-receptor-α (sIL2Rα), IP10 and TNFα. Extensive statistical analyses were performed (correlations, t-tests, ranking tests and tree modeling). The mortality rate was 65/415 (15.7%) and a negative outcome (death and/or orotracheal intubation) affected 98/415 (23.6%) of cases. Univariate tests showed the majority of biomarkers increased in severe patients, but ranking tests helped to select the best variables to put on decisional tree modeling which identified IL-6 as the first dichotomic marker with a cut-off of 114 pg/mL. Then, a good synergy was found between IL-10, MR-proADM, sIL2Rα, IP10 and CRP in increasing the predictive value in classifying patients at risk or not for a negative outcome. In conclusion, beside IL-6, a panel of other cytokines representing the degree of immunoparalysis and the anti-inflammatory response (IP10, sIL2Rα and IL-10) showed synergic role when combined to biomarkers of systemic inflammation and endothelial dysfunction (CRP, MR-proADM) and may also better explain disease pathogenesis and suggests targeted intervention.

High T-cell response rate after COVID-19 vaccination in belimumab and rituximab recipients.

OBJECTIVE: To evaluate B-cell- and T-cell-mediated immune response to SARS-CoV-2 mRNA vaccination in patients with complex or rare systemic autoimmune diseases previously been treated with or under continuous treatment with B-cell-targeted therapies including rituximab (RTX) and belimumab (BEL). MATERIALS AND METHODS: Twenty-eight consecutive patients receiving RTX (n = 11) or BEL (n = 17) treatment and 13 age-/sex-matched controls (non-rheumatic healthcare personnel) were recruited. None of the patients had detectable anti-SARS-CoV-2 antibodies caused by prior exposure to the virus. All the patients and controls received mRNA vaccines and were tested three to four weeks after completion of vaccination. In all the RTX patients, vaccination was started within 5 months from the last infusion, and B-cell depletion was confirmed in all but one of them. Total anti-SARS-CoV-2 RBD antibodies were analyzed using a diagnostic assay, while T-cell response was evaluated using the interferon-gamma release assay (IGRA). Further, SARS-CoV-2 pseudoviruses were employed to verify the strain-specific neutralizing capacity of the antibodies. RESULTS: Detectable anti-SARS-CoV-2 antibodies were documented in 1 out of the 11 RTX patients and 16 of the 17 BEL patients. The median concentration in the RTX and BEL patients was significantly lower than that in the controls (39.6 AU/ml vs. 1133 AU/ml, p = 0.002). The result of IGRA was positive in 8 of the 11 (72.7%) RTX patients and 16 of the 17 (94.1%) BEL patients, and interferon release in both the RTX and BEL patients was comparable to that in the control participants. CONCLUSION: B-cell-targeted therapies do not preclude SARS-CoV-2 vaccination, since virus-specific cellular immunity can be induced even in the absence of circulating B cells. An important finding was that lupus patients treated with BEL developed immune responses to SARS-CoV-2; this indicates retention of the immunogenicity of the COVID-19 vaccine.