Identification of a sub-group of critically ill patients with high risk of intensive care unit-acquired infections and poor clinical course using a transcriptomic score
Abstract Background The development of stratification tools based on the assessment of circulating mRNA of genes involved in the immune response is constrained by the heterogeneity of septic patients. The aim of this study is to develop a transcriptomic score based on a pragmatic combination of immu...
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| Format: | Article |
| Language: | English |
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BMC
2023-04-01
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| Series: | Critical Care |
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| Online Access: | https://doi.org/10.1186/s13054-023-04436-3 |
| _version_ | 1797841039415836672 |
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| author | Maxime Bodinier Guillaume Monneret Marie Casimir Aurore Fleurie Filippo Conti Fabienne Venet Marie-Angélique Cazalis Elisabeth Cerrato Estelle Peronnet Thomas Rimmelé Anne-Claire Lukaszewicz Karen Brengel-Pesce Jean-François Llitjos |
| author_facet | Maxime Bodinier Guillaume Monneret Marie Casimir Aurore Fleurie Filippo Conti Fabienne Venet Marie-Angélique Cazalis Elisabeth Cerrato Estelle Peronnet Thomas Rimmelé Anne-Claire Lukaszewicz Karen Brengel-Pesce Jean-François Llitjos |
| author_sort | Maxime Bodinier |
| collection | DOAJ |
| description | Abstract Background The development of stratification tools based on the assessment of circulating mRNA of genes involved in the immune response is constrained by the heterogeneity of septic patients. The aim of this study is to develop a transcriptomic score based on a pragmatic combination of immune-related genes detected with a prototype multiplex PCR tool. Methods As training cohort, we used the gene expression dataset obtained from 176 critically ill patients enrolled in the REALISM study (NCT02638779) with various etiologies and still hospitalized in intensive care unit (ICU) at day 5–7. Based on the performances of each gene taken independently to identify patients developing ICU-acquired infections (ICU-AI) after day 5–7, we built an unweighted score assuming the independence of each gene. We then determined the performances of this score to identify a subgroup of patients at high risk to develop ICU-AI, and both longer ICU length of stay and mortality of this high-risk group were assessed. Finally, we validated the effectiveness of this score in a retrospective cohort of 257 septic patients. Results This transcriptomic score (TScore) enabled the identification of a high-risk group of patients (49%) with an increased rate of ICU-AI when compared to the low-risk group (49% vs. 4%, respectively), with longer ICU length of stay (13 days [95% CI 8–30] vs. 7 days [95% CI 6–9], p < 0.001) and higher ICU mortality (15% vs. 2%). High-risk patients exhibited biological features of immune suppression with low monocytic HLA-DR levels, higher immature neutrophils rates and higher IL10 concentrations. Using the TScore, we identified 160 high-risk patients (62%) in the validation cohort, with 30% of ICU-AI (vs. 18% in the low-risk group, p = 0.06), and significantly higher mortality and longer ICU length of stay. Conclusions The transcriptomic score provides a useful and reliable companion diagnostic tool to further develop immune modulating drugs in sepsis in the context of personalized medicine. |
| first_indexed | 2024-04-09T16:24:28Z |
| format | Article |
| id | doaj.art-da79f8118eff430eb3627a8e0a39d2af |
| institution | Directory Open Access Journal |
| issn | 1364-8535 |
| language | English |
| last_indexed | 2024-04-09T16:24:28Z |
| publishDate | 2023-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Critical Care |
| spelling | doaj.art-da79f8118eff430eb3627a8e0a39d2af2023-04-23T11:18:49ZengBMCCritical Care1364-85352023-04-0127111410.1186/s13054-023-04436-3Identification of a sub-group of critically ill patients with high risk of intensive care unit-acquired infections and poor clinical course using a transcriptomic scoreMaxime Bodinier0Guillaume Monneret1Marie Casimir2Aurore Fleurie3Filippo Conti4Fabienne Venet5Marie-Angélique Cazalis6Elisabeth Cerrato7Estelle Peronnet8Thomas Rimmelé9Anne-Claire Lukaszewicz10Karen Brengel-Pesce11Jean-François Llitjos12Joint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Joint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Joint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Joint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Joint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Immunology Laboratory, Edouard Herriot Hospital – Hospices Civils de LyonJoint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Joint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Joint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Joint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Joint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Joint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Joint Research Unit HCL-bioMérieux, EA 7426 “Pathophysiology of Injury-Induced Immunosuppression” (Université Claude Bernard Lyon 1 – Hospices Civils de Lyon, bioMérieux)Abstract Background The development of stratification tools based on the assessment of circulating mRNA of genes involved in the immune response is constrained by the heterogeneity of septic patients. The aim of this study is to develop a transcriptomic score based on a pragmatic combination of immune-related genes detected with a prototype multiplex PCR tool. Methods As training cohort, we used the gene expression dataset obtained from 176 critically ill patients enrolled in the REALISM study (NCT02638779) with various etiologies and still hospitalized in intensive care unit (ICU) at day 5–7. Based on the performances of each gene taken independently to identify patients developing ICU-acquired infections (ICU-AI) after day 5–7, we built an unweighted score assuming the independence of each gene. We then determined the performances of this score to identify a subgroup of patients at high risk to develop ICU-AI, and both longer ICU length of stay and mortality of this high-risk group were assessed. Finally, we validated the effectiveness of this score in a retrospective cohort of 257 septic patients. Results This transcriptomic score (TScore) enabled the identification of a high-risk group of patients (49%) with an increased rate of ICU-AI when compared to the low-risk group (49% vs. 4%, respectively), with longer ICU length of stay (13 days [95% CI 8–30] vs. 7 days [95% CI 6–9], p < 0.001) and higher ICU mortality (15% vs. 2%). High-risk patients exhibited biological features of immune suppression with low monocytic HLA-DR levels, higher immature neutrophils rates and higher IL10 concentrations. Using the TScore, we identified 160 high-risk patients (62%) in the validation cohort, with 30% of ICU-AI (vs. 18% in the low-risk group, p = 0.06), and significantly higher mortality and longer ICU length of stay. Conclusions The transcriptomic score provides a useful and reliable companion diagnostic tool to further develop immune modulating drugs in sepsis in the context of personalized medicine.https://doi.org/10.1186/s13054-023-04436-3SepsisTranscriptomicIntensive care unitAcquired infectionsPersonalized medicine |
| spellingShingle | Maxime Bodinier Guillaume Monneret Marie Casimir Aurore Fleurie Filippo Conti Fabienne Venet Marie-Angélique Cazalis Elisabeth Cerrato Estelle Peronnet Thomas Rimmelé Anne-Claire Lukaszewicz Karen Brengel-Pesce Jean-François Llitjos Identification of a sub-group of critically ill patients with high risk of intensive care unit-acquired infections and poor clinical course using a transcriptomic score Critical Care Sepsis Transcriptomic Intensive care unit Acquired infections Personalized medicine |
| title | Identification of a sub-group of critically ill patients with high risk of intensive care unit-acquired infections and poor clinical course using a transcriptomic score |
| title_full | Identification of a sub-group of critically ill patients with high risk of intensive care unit-acquired infections and poor clinical course using a transcriptomic score |
| title_fullStr | Identification of a sub-group of critically ill patients with high risk of intensive care unit-acquired infections and poor clinical course using a transcriptomic score |
| title_full_unstemmed | Identification of a sub-group of critically ill patients with high risk of intensive care unit-acquired infections and poor clinical course using a transcriptomic score |
| title_short | Identification of a sub-group of critically ill patients with high risk of intensive care unit-acquired infections and poor clinical course using a transcriptomic score |
| title_sort | identification of a sub group of critically ill patients with high risk of intensive care unit acquired infections and poor clinical course using a transcriptomic score |
| topic | Sepsis Transcriptomic Intensive care unit Acquired infections Personalized medicine |
| url | https://doi.org/10.1186/s13054-023-04436-3 |
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