Frontiers in immunology · 2026
Exploring the timeline and network interplay of immune mediators in COVID-19 patients according to disease outcome.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод в очереди
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Guimarães Gabriel Macedo Costa, Costa-Pereira Christiane, Faustino Renan da Silva, Alves Lilian Santos, Carvalho Fabiana Rabe, Medeiros Thalia, Brito-de-Sousa Joaquim Pedro, Amaral Laurence Rodrigues, Peruhype-Magalhães Vanessa, Campi-Azevedo Ana Carolina, Teixeira-Carvalho Andréa, Silva Andrea Alice, Martins-Filho Olindo Assis
Аннотация
INTRODUCTION: The present study is an observational descriptive follow-up investigation designed to characterize the profile of serum immune mediators in COVID-19 patients further categorized according to disease outcome.
METHODS: A total of 92 COVID-19 patients were enrolled in a timeline kinetics, starting at hospital admission (Day 0) throughout consecutive timepoint intervals (Day 3-7, Day 8-14 and Day 15-40). Immune mediators (chemokines, cytokines and growth factors) were quantified by a high-throughput multiplex assay and compared with a pre-pandemic healthy control group (HC).
RESULTS: Data demonstrated that COVID-19 exhibited a classical immune mediator storm, with prominent increase of chemokines and pro-inflammatory cytokines. Longitudinal follow-up revealed that the "death" outcome was associated with a persistent increase of immune mediators across all timepoints, with higher imbalance at Day 8-14. Conversely, the "discharge" outcome evolved with a balanced temporal profile with progressive waning of pro-inflammatory cytokines. Integrative network architectures uncovered that the "death" outcome exhibited a selective high-density chemokine cluster, contrasting with the balanced pattern described for "discharge" subgroups. A set of serum immune mediators (CXCL8, CCL2, CXCL10, IL-6, and IFN-γ) emerged as relevant predictors of disease outcome (AUC ≥ 0.8). Decision tree stepwise algorithms pointed out the hierarchical power (accuracy = 83%) of IL-6, CCL2, and CXCL8 to sort out patients according to disease outcome.
CONCLUSIONS: Overall, these findings support clinical applicability of measuring serum immune mediators as complementary prognostic biomarkers for early classification and prediction of disease outcome in COVID-19 patients.
METHODS: A total of 92 COVID-19 patients were enrolled in a timeline kinetics, starting at hospital admission (Day 0) throughout consecutive timepoint intervals (Day 3-7, Day 8-14 and Day 15-40). Immune mediators (chemokines, cytokines and growth factors) were quantified by a high-throughput multiplex assay and compared with a pre-pandemic healthy control group (HC).
RESULTS: Data demonstrated that COVID-19 exhibited a classical immune mediator storm, with prominent increase of chemokines and pro-inflammatory cytokines. Longitudinal follow-up revealed that the "death" outcome was associated with a persistent increase of immune mediators across all timepoints, with higher imbalance at Day 8-14. Conversely, the "discharge" outcome evolved with a balanced temporal profile with progressive waning of pro-inflammatory cytokines. Integrative network architectures uncovered that the "death" outcome exhibited a selective high-density chemokine cluster, contrasting with the balanced pattern described for "discharge" subgroups. A set of serum immune mediators (CXCL8, CCL2, CXCL10, IL-6, and IFN-γ) emerged as relevant predictors of disease outcome (AUC ≥ 0.8). Decision tree stepwise algorithms pointed out the hierarchical power (accuracy = 83%) of IL-6, CCL2, and CXCL8 to sort out patients according to disease outcome.
CONCLUSIONS: Overall, these findings support clinical applicability of measuring serum immune mediators as complementary prognostic biomarkers for early classification and prediction of disease outcome in COVID-19 patients.