COVID-19 Clinical Profile in Latin American Migrants Living in Spain: Does the Geographical Origin Matter?

Alterations in the immune system persist after one year of convalescence in severe COVID-19 patients

Introduction

Severe COVID-19 originates a myriad of alterations in the immune system during active disease, especially in the T and NK cell compartments, but several studies in the last year have unveiled some alterations that persist in convalescence. Although most of the studies follow the participants for a short recovery time, studies following patients up to three or six months still find alterations. We aimed at evaluating changes in the NK, T and B cell compartments after severe COVID-19 in participants with a median recovery time of eleven months.

Methods

Eighteen convalescent of severe COVID-19 (CSC), 14 convalescent of mild COVID-19 (CMC) and nine controls were recruited. NKG2A, NKG2C, NKG2D and the activating receptor NKp44 were evaluated in NK^bright, NK^dim and NKT subpopulations. In addition, CD3 and CD19 were measured and a basic biochemistry with IL-6 levels was obtained.

Results

CSC participants showed lower NK^bright/NK^dim ratio, higher NKp44 expression in NK^bright subpopulations, higher levels of serum IL-6, lower levels of NKG2A⁺ T lymphocytes and a trend to a lower expression of CD19 in B lymphocytes compared to controls. CMC participants showed no significant alterations in the immune system compared to controls.

Conclusions

These results are concordant with previous studies, which find alterations in CSC weeks or months after resolution of the symptoms, and point to the possibility of these alterations lasting one year or more after COVID-19 resolution.

Exposing and Overcoming Limitations of Clinical Laboratory Tests in COVID-19 by Adding Immunological Parameters; A Retrospective Cohort Analysis and Pilot Study

Background

Two years since the onset of the COVID-19 pandemic no predictive algorithm has been generally adopted for clinical management and in most algorithms the contribution of laboratory variables is limited.

Objectives

To measure the predictive performance of currently used clinical laboratory tests alone or combined with clinical variables and explore the predictive power of immunological tests adequate for clinical laboratories. Methods: Data from 2,600 COVID-19 patients of the first wave of the pandemic in the Barcelona area (exploratory cohort of 1,579, validation cohorts of 598 and 423 patients) including clinical parameters and laboratory tests were retrospectively collected. 28-day survival and maximal severity were the main outcomes considered in the multiparametric classical and machine learning statistical analysis. A pilot study was conducted in two subgroups (n=74 and n=41) measuring 17 cytokines and 27 lymphocyte phenotypes respectively.

Findings

1) Despite a strong association of clinical and laboratory variables with the outcomes in classical pairwise analysis, the contribution of laboratory tests to the combined prediction power was limited by redundancy. Laboratory variables reflected only two types of processes: inflammation and organ damage but none reflected the immune response, one major determinant of prognosis. 2) Eight of the thirty variables: age, comorbidity index, oxygen saturation to fraction of inspired oxygen ratio, neutrophil-lymphocyte ratio, C-reactive protein, aspartate aminotransferase/alanine aminotransferase ratio, fibrinogen, and glomerular filtration rate captured most of the combined statistical predictive power. 3) The interpretation of clinical and laboratory variables was moderately improved by grouping them in two categories i.e., inflammation related biomarkers and organ damage related biomarkers; Age and organ damage-related biomarker tests were the best predictors of survival, and inflammatory-related ones were the best predictors of severity. 4) The pilot study identified immunological tests (CXCL10, IL-6, IL-1RA and CCL2), that performed better than most currently used laboratory tests.

Conclusions

Laboratory tests for clinical management of COVID 19 patients are valuable but limited predictors due to redundancy; this limitation could be overcome by adding immunological tests with independent predictive power. Understanding the limitations of tests in use would improve their interpretation and simplify clinical management but a systematic search for better immunological biomarkers is urgent and feasible.