Clinical, epidemiological, and laboratory prognostic factors in patients with leprosy reactions: A 10-year retrospective cohort study

Introduction

Leprosy reactions, the main cause of neural damage, can occur up to 7 years after starting multidrug therapy. We aimed to approach the prognostic factors that may influence the leprosy reactions over the follow-up time.

Methods

Retrospective cohort study, encompassing 10 years of data collection, composed of 390 patients, divided into 201 affected by reactions and 189 reaction-free individuals. Epidemiological, clinical, and laboratory variables were approached as prognostic factors associated with leprosy reactions. The association among variables was analyzed by a binomial test and survival curves were compared by the Kaplan-Meier and Cox proportional-hazards regression.

Results

51.5% (201/390) of patients were affected by leprosy reactions. These immunological events were associated with lepromatous leprosy (16.2%; 63/390; p < 0.0001) and multibacillary group (43%; 169/390; p < 0.0001). This study showed that survival curves for the prognostic factor anti-PGL-I, comparing positive and negative cases at diagnosis, differed in relation to the follow-up time (Log Rank: p = 0.0760; Breslow: p = 0.0090; Tarone-Ware: p = 0.0110). The median survival times (time at which 50% of patients were affected by leprosy reactions) were 5 and 9 months for those reactional cases with negative (26/51) and positive serology (75/150), respectively. The time-dependent covariates in the cox proportional-hazards regression showed anti-PGL-I as the main prognostic factor to predict leprosy reactions (hazard ratio=1.91; p = 0.0110) throughout the follow-up time.

Conclusions

Finally, these findings demonstrated that anti-PGL-I serology at diagnosis is the most important prognostic factor for leprosy reactions after starting multidrug therapy, thus enabling prediction of this immunological event.

Proteomic Profile of Procoagulant Extracellular Vesicles Reflects Complement System Activation and Platelet Hyperreactivity of Patients with Severe COVID-19

Background

Extracellular vesicles (EVs) are a valuable source of biomarkers and display the pathophysiological status of various diseases. In COVID-19, EVs have been explored in several studies for their ability to reflect molecular changes caused by SARS-CoV-2. Here we provide insights into the roles of EVs in pathological processes associated with the progression and severity of COVID-19.

Methods

In this study, we used a label-free shotgun proteomic approach to identify and quantify alterations in EV protein abundance in severe COVID-19 patients. We isolated plasma extracellular vesicles from healthy donors and patients with severe COVID-19 by size exclusion chromatography (SEC). Then, flow cytometry was performed to assess the origin of EVs and to investigate the presence of circulating procoagulant EVs in COVID-19 patients. A total protein extraction was performed, and samples were analyzed by nLC-MS/MS in a Q-Exactive HF-X. Finally, computational analysis was applied to signify biological processes related to disease pathogenesis.

Results

We report significant changes in the proteome of EVs from patients with severe COVID-19. Flow cytometry experiments indicated an increase in total circulating EVs and with tissue factor (TF) dependent procoagulant activity. Differentially expressed proteins in the disease groups were associated with complement and coagulation cascades, platelet degranulation, and acute inflammatory response.

Conclusions

The proteomic data reinforce the changes in the proteome of extracellular vesicles from patients infected with SARS-CoV-2 and suggest a role for EVs in severe COVID-19.