BACKGROUNDPeanut allergy, for which there are no approved treatment options, affects patients who are at risk for unpredictable and occasionally life-threatening allergic reactions. METHODS Randomization and BlindingEligible participants were randomly assigned, in a 3:1 ratio, to receive either AR101, a peanut-derived pharmaceutical product that was manufactured

Managing patients with severe asthma during the coronavirus pandemic and COVID-19 is a challenge. Authorities and physicians are still learning how COVID-19 affects people with underlying diseases, and severe asthma is not an exception. Unless relevant data emerge that change our understanding of the relative safety of medications indicated in patients with asthma during this pandemic, clinicians must follow the recommendations of current evidence-based guidelines for preventing loss of control and exacerbations. Also, with the absence of data that would indicate any potential harm, current advice is to continue the administration of biological therapies during the COVID-19 pandemic in patients with asthma for whom such therapies are clearly indicated and have been effective. For patients with severe asthma infected by SARS-CoV-2, the decision to maintain or postpone biological therapy until the patient recovers should be a case-by-case based decision supported by a multidisciplinary team. A registry of cases of COVID-19 in patients with severe asthma, including those treated with biologics, will help to address a clinical challenge in which we have more questions than answers.

There is an urgent need to identify cellular/molecular mechanisms responsible for severe COVID-19 progressing to mortality. We initially performed untargeted/targeted lipidomics and focused biochemistry on 127 plasma samples and found elevated metabolites associated with secreted phospholipase A2 (sPLA2) activity and mitochondrial dysfunction in severe COVID-19 patients.Deceased COVID-19 patients had higher levels of circulating, catalytically active sPLA2 Group IIA (sPLA2-IIA), with a median value 9.6-fold higher than mild patients and 5.0-fold higher than severe COVID-19 survivors. Elevated sPLA2-IIA levels paralleled several indices of COVID-19 disease severity (e.g., kidney dysfunction, hypoxia, multiple organ dysfunction). A decision tree generated by machine learning identified sPLA2-IIA levels as a central node in stratifying patients that succumbed to COVID-19. Random forest analysis and LASSO-based regression analysis additionally identified sPLA2-IIA and blood urea nitrogen (BUN) as the key variables among 80 clinical indices in predicting COVID-19 mortality. The combined PLA-BUN index performed significantly better than either alone. An independent cohort (n=154) confirmed higher plasma sPLA2-IIA levels in deceased patients vs. severe or mild COVID-19, with the PLA-BUN indexbased decision tree satisfactorily stratifying mild, severe, and deceased COVID-19 patients. With clinically tested inhibitors available, this study supports sPLA2-IIA as a therapeutic target to reduce COVID-19 mortality.

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