An exploratory analysis of associations of genetic variation with the efficacy of tocilizumab in severe COVID-19 patients. A pharmacogenetic study based on next-generation sequencing

Background In the context of the cytokine storm the takes place in severe COVID-19 patients, the Interleukin 6 ( IL6 ) pathway emerges as one of the key pathways involved in the pathogenesis of this hyperinflammatory state. The strategy of blocking the inflammatory storm by targeting the IL6 is a promising therapy to mitigate mortality. The use of Tocilizumab was recommended by the World Health Organization (WHO) to treat severe COVID-19 patients. However, the efficacy of Tocilizumab is variable. We hypothesize that the genetic background could be behind the efficacy of Tocilizumab in terms of mortality. Methods We performed a targeted-next generation sequencing of 287 genes, of which 264 belong to a community panel of ThermoFisher for the study of genetic causes of primary immunodeficiency disorders, and 23 additional genes mostly related to inflammation, not included in the original community panel. This panel was sequenced in an initial cohort of 425 COVID-19 patients, of which 232 were treated with Tocilizumab and standard therapy, and 193 with standard therapy only. Selected genetic variants were genotyped by single base extension in additional 245 patients (95 treated with Tocilizumab and 150 non-treated with Tocilizumab). Appropriate statistical analyses and internal validation, including logistic regression models, with the interaction between Tocilizumab and genetic variants, were applied to assess the impact of these genetic variants in the efficacy of Tocilizumab in terms of mortality. Results Age ( p < 0.001) and cardiovascular disease ( p < 0.001) are risk factors for mortality in COVID-19 patients. The presence of GG and TT genotypes at IL10Rβ (rs2834167) and IL1β (rs1143633) genes significantly associates with a reduced risk of mortality in patients treated with Tocilizumab (OR = 0.111; 95%CI = 0.015–0.829; p = 0.010 and OR = 0.378; 95%CI = 0.154–0.924; p = 0.028 respectively). The presence of CC genotype at IL1RN (rs2234679) significantly associates with an increased risk of mortality, but only in patients not treated with Tocilizumab (OR = 3.200; 95%CI = 1.512–6.771; p = 0.002). Exhaustive internal validation using a bootstrap method (B = 500 replicates) validated the accuracy of the predictive models. Conclusion We developed a series of predictive models based on three genotypes in genes with a strong implication in the etiopathogenesis of COVID-19 disease capable of predicting the risk of mortality in patients treated with Tocilizumab.

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Journal
Frontiers in Pharmacology
Published
2024-09-13
DOI
https://doi.org/10.3389/fphar.2024.1426826
Primary Topic
COVID-19 Clinical Research Studies
Type
article
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article

An exploratory analysis of associations of genetic variation with the efficacy of tocilizumab in severe COVID-19 patients. A pharmacogenetic study based on next-generation sequencing

Vanesa Balboa‐Barreiro, Francisco Javier Blanco, Juan Fernández‐Tajes, Ignacio Rego‐Pérez et al.
Frontiers in Pharmacology
COVID-19 Clinical Research Studies
article

An exploratory analysis of associations of genetic variation with the efficacy of tocilizumab in severe COVID-19 patients. A pharmacogenetic study based on next-generation sequencing

Vanesa Balboa‐Barreiro, Francisco Javier Blanco, Juan Fernández‐Tajes, Ignacio Rego‐Pérez, Jorge Vázquez-García, Alejandro Durán‐Sotuela, S. Relaño-Fernández
article en

Abstract

Background In the context of the cytokine storm the takes place in severe COVID-19 patients, the Interleukin 6 ( IL6 ) pathway emerges as one of the key pathways involved in the pathogenesis of this hyperinflammatory state. The strategy of blocking the inflammatory storm by targeting the IL6 is a promising therapy to mitigate mortality. The use of Tocilizumab was recommended by the World Health Organization (WHO) to treat severe COVID-19 patients. However, the efficacy of Tocilizumab is variable. We hypothesize that the genetic background could be behind the efficacy of Tocilizumab in terms of mortality. Methods We performed a targeted-next generation sequencing of 287 genes, of which 264 belong to a community panel of ThermoFisher for the study of genetic causes of primary immunodeficiency disorders, and 23 additional genes mostly related to inflammation, not included in the original community panel. This panel was sequenced in an initial cohort of 425 COVID-19 patients, of which 232 were treated with Tocilizumab and standard therapy, and 193 with standard therapy only. Selected genetic variants were genotyped by single base extension in additional 245 patients (95 treated with Tocilizumab and 150 non-treated with Tocilizumab). Appropriate statistical analyses and internal validation, including logistic regression models, with the interaction between Tocilizumab and genetic variants, were applied to assess the impact of these genetic variants in the efficacy of Tocilizumab in terms of mortality. Results Age ( p < 0.001) and cardiovascular disease ( p < 0.001) are risk factors for mortality in COVID-19 patients. The presence of GG and TT genotypes at IL10Rβ (rs2834167) and IL1β (rs1143633) genes significantly associates with a reduced risk of mortality in patients treated with Tocilizumab (OR = 0.111; 95%CI = 0.015–0.829; p = 0.010 and OR = 0.378; 95%CI = 0.154–0.924; p = 0.028 respectively). The presence of CC genotype at IL1RN (rs2234679) significantly associates with an increased risk of mortality, but only in patients not treated with Tocilizumab (OR = 3.200; 95%CI = 1.512–6.771; p = 0.002). Exhaustive internal validation using a bootstrap method (B = 500 replicates) validated the accuracy of the predictive models. Conclusion We developed a series of predictive models based on three genotypes in genes with a strong implication in the etiopathogenesis of COVID-19 disease capable of predicting the risk of mortality in patients treated with Tocilizumab.

Frontiers in PharmacologyVol. 15
Universidade da Coruña (ES), Instituto de Investigación Biomédica de A Coruña (ES)
Xunta de Galicia, Instituto de Salud Carlos III, Servicio Gallego de Salud
Openalex Percentile: Top 81%
COVID-19 Clinical Research Studies
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