Application of machine learning models to identify serological predictors of COVID-19 severity and outcomes

Critically ill people with COVID-19 have greater antibody titers than those with mild to moderate illness, but their association with recovery or death from COVID-19 has not been characterized. In 178 COVID-19 patients, 73 non-hospitalized and 105 hospitalized patients, mucosal swabs and plasma samples were collected at hospital enrollment and up to 3 months post-enrollment (MPE) to measure virus RNA, cytokines/chemokines, binding antibodies, ACE2 binding inhibition, and Fc effector antibody responses against SARS-CoV-2. The association of demographic variables and >20 serological antibody measures with intubation or death due to COVID-19 was determined using machine learning algorithms. Predictive models revealed that IgG binding and ACE2 binding inhibition responses at 1 MPE were positively and C1q complement activity at enrollment was negatively associated with an increased probability of intubation or death from COVID-19 within 3 MPE. Serological antibody measures were more predictive than demographic variables of intubation or death among COVID-19 patients.

Alternative lineage B cells utilizing fatty acid oxidation predict response to third dose COVID vaccination in solid organ transplant recipients

Solid organ transplant recipients (SOTRs) demonstrate reduced seroconversion and increased breakthrough infection rates following standard two dose mRNA vaccination against SARs-CoV-2. However, within a prospective cohort of SOTRs, the majority of patients (72%) developed a positive anti-Spike (S) IgG following a third vaccine dose, compared to only 15% following two doses. Those who failed to respond to vaccination uniformly received mycophenolate mofetil (MMF). To better understand mechanisms underlying divergent vaccine responses, both global and S-specific B cells were evaluated using flow cytometry to assess immunologic and metabolic phenotypes. Prior to the third dose, 76% of SOTRs demonstrated detectable S-specific B cells even though only 15% had positive anti-S IgG titers. However, B cells were skewed towards a non-class switched phenotype in SOTRs compared to healthy controls. Response to a third dose was predicted by expanded populations of germinal center (GC)-like B cells and CD11c+ alternative lineage B cells with upregulation of carnitine palmitoyltransferase 1a (CPT1a), the rate limiting enzyme for fatty acid oxidation (FAO), a preferred energy source of GC B cells. SOTRs receiving high dose MMF demonstrated significantly lower expression of CPT1a compared to healthy controls, indicating an energetic deficit associated with MMF and failure to respond. Further, in vitro treatment of B cells with MMF reduced the ability to oxidize fatty acids and induced an accumulation of intracellular lipid droplets. Together, these data define alternative lineage B cells present in those who respond to a third vaccine dose, outlining FAO as a metabolic pathway that could be targeted to improve vaccine responses.

The Time is Now: A Call for Renewed Support of Infectious Diseases Physician-Scientist Trainees in the Era of Coronavirus Disease 2019

Infectious diseases fellows’ futures have been uniquely imperiled by the pandemic. In this article, we issue a call to action to sustain their careers as the future leaders of infectious diseases inquiry.

Tocilizumab for the Treatment of COVID-19 Among Hospitalized Patients: A Matched Retrospective Cohort Analysis

Background

There is currently no single treatment that mitigates all harms caused by severe acute respiratory syndrome coronavirus 2 infection. Tocilizumab, an interleukin-6 antagonist, may have a role as an adjunctive immune-modulating therapy.

Methods

This was an observational retrospective study of hospitalized adult patients with confirmed coronavirus disease 2019 (COVID-19). The intervention group comprised patients who received tocilizumab; the comparator arm was drawn from patients who did not receive tocilizumab. The primary outcome was all-cause mortality censored at 28 days; secondary outcomes were all-cause mortality at discharge, time to clinical improvement, and rates of secondary infections. Marginal structural Cox models via inverse probability treatment weights were applied to estimate the effect of tocilizumab. A time-dependent propensity score-matching method was used to generate a 1:1 match for tocilizumab recipients; infectious diseases experts then manually reviewed these matched charts to identify secondary infections.

Results

This analysis included 90 tocilizumab recipients and 1669 controls. Under the marginal structural Cox model, tocilizumab was associated with a 62% reduced hazard of death (adjusted hazard ratio [aHR], 0.38; 95% CI, 0.21 to 0.70) and no change in time to clinical improvement (aHR, 1.13; 95% CI, 0.68 to 1.87). The 1:1 matched data set also showed a lower mortality rate (27.8% vs 34.4%) and reduced hazards of death (aHR, 0.47; 95% CI, 0.25 to 0.88). Elevated inflammatory markers were associated with reduced hazards of death among tocilizumab recipients compared with controls. Secondary infection rates were similar between the 2 groups.

Conclusions

Tocilizumab may provide benefit in a subgroup of patients hospitalized with COVID-19 who have elevated biomarkers of hyperinflammation, without increasing the risk of secondary infection.