Estelle Peronnet

Marie-Charlotte Delignette, M.D., Muzhda Haem Rahimi, Ph.D., Morgane Gossez, Pharm.D., Teresa Antonini, M.D., Arnaud Riff, M.D., Estelle Peronnet, Ph.D., Franck Berthier, Ph.D., Fabienne Venet, Ph.D., Fanny Lebossé, Pharm.D., Ph.D., and Guillaume Monneret, Pharm.D., Ph.D.. Ann Lab Med -0001;0:. https://doi.org/10.3343/alm.2025.0490

Sepsis induces intense, dynamic and heterogeneous host response modulations. Despite improvement of patient management, the risk of mortality and healthcare-associated infections remains high. Treatments to counterbalance immune response are under evaluation, but effective biomarkers are still lacking to perform patient stratification. The design of the present study was defined to alleviate the limitations of existing literature: we selected patients who survived the initial hyperinflammatory response and are still hospitalized at day 5–7 after ICU admission. Using the Immune Profiling Panel (IPP), a fully automated RT-qPCR multiplex prototype, we optimized a machine learning model combining the IPP gene expression levels for the identification of patients at high risk of worsening, a composite endpoint defined as death or secondary infection, within one week after sampling. This was done on 332 sepsis patients selected from two retrospective studies. The IPP model identified a high-risk group comprising 30% of patients, with a significant increased proportion of worsening events at day 28 compared to the low-risk group (49% vs. 28%, respectively). These preliminary results underline the potential clinical application of IPP for sepsis patient stratification in a personalized medicine perspective, that will be confirmed in a larger prospective multicenter study.

OBJECTIVES: There is a crucial unmet need for biomarker-guided diagnostic and prognostic enrichment in clinical trials evaluating immune modulating therapies in critically ill patients. Low monocyte expression of human leukocyte antigen-DR (mHLA-DR), considered as a reference surrogate to identify immunosuppressed patients, has been proposed for patient stratification in immunostimulation approaches. However, its widespread use in clinic has been somewhat hampered by technical constraints inherent to flow cytometry technology. The objective of the present study was to evaluate the ability of a prototype multiplex polymerase chain reaction tool (immune profiling panel [IPP]) to identify immunosuppressed ICU patients characterized by a low mHLA-DR expression. DESIGN: Retrospective observational cohort study. SETTING: Adult ICU in a University Hospital, Lyon, France. PATIENTS: Critically ill patients with various etiologies enrolled in the REAnimation Low Immune Status Marker study (NCT02638779). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: mHLA-DR and IPP data were obtained from 1,731 blood samples collected from critically ill patients with various etiologies and healthy volunteers. A partial least square regression model combining the expression levels of IPP markers was trained and used for the identification of samples from patients presenting with evidence of immunosuppression, defined here as mHLADR less than 8,000 antibodies bound per cell (AB/C). The IPP gene set had an area under the receiver operating characteristic curve (AUC) of 0.86 (95% CI 0.83–0.89) for the identification of immunosuppressed patients. In addition, when applied to the 123 patients still in the ICU at days 5–7 after admission, IPP similarly enriched the number of patients with ICU-acquired infections in the immunosuppressed group (26%), in comparison with low mHLA-DR (22%). CONCLUSIONS: This study reports on the potential of the IPP gene set to identify ICU patients presenting with mHLA-DR less than 8,000 AB/C. Upon further optimization and validation, this molecular tool may help in the stratification of patients that could benefit from immunostimulation in the context of personalized medicine.

Sepsis is the leading cause of mortality for critically ill patients worldwide. Patients develop T lymphocyte dysfunctions leading to T-cell exhaustion associated with increased risk of death. As interleukin-7 (IL-7) is currently tested in clinical trials to reverse these dysfunctions, it is important to evaluate the expression of its specific CD127 receptor on the T-cell surface of patients with septic shock. Moreover, the CD127lowPD-1high phenotype has been proposed as a T-cell exhaustion marker in chronic viral infections but has never been evaluated in sepsis. The objective of this study was first to evaluate CD127 and CD127lowPD-1high phenotype in septic shock in parallel with functional T-cell alterations. Second, we aimed to reproduce septic shock–induced T-cell alterations in an ex vivo model. CD127 expression was followed at the protein and mRNA levels in patients with septic shock and healthy volunteers. CD127lowPD-1high phenotype was also evaluated in parallel with T-cell functional alterations after ex vivo activation. To reproduce T-cell alterations observed in patients, purified T cells from healthy volunteers were activated ex vivo and their phenotype and function were evaluated. In patients, neither CD127 expression nor its corresponding mRNA transcript level was modified compared with normal values. However, the percentage of CD127lowPD-1high T cells was increased while T cells also presented functional alterations. CD127lowPD-1high T cells co-expressed HLA-DR, an activation marker, suggesting a role for T-cell activation in the development of this phenotype. Indeed, T-cell receptor (TCR) activation of normal T lymphocytes ex vivo reproduced the increase of CD127lowPD-1high T cells and functional alterations following a second stimulation, as observed in patients. Finally, in this model, as observed in patients, IL-7 could improve T-cell proliferation. The proportion of CD127lowPD-1high T cells in patients was increased compared with healthy volunteers, although no global CD127 regulation was observed. Our results suggest that TCR activation participates in the occurrence of this T-cell population and in the development of T-cell alterations in septic shock. Furthermore, we provide an ex vivo model for the investigation of the pathophysiology of sepsis-induced T-cell immunosuppression and the testing of innovative immunostimulant treatments.

Objectives: Septic shock is the primary cause of death in ICUs. A better comprehension of its pathophysiology, in particular, the immune alteration mechanisms, opened new therapeutic perspectives such as the recombinant interleukin-7. The use of biomarkers could improve the identification of eligible patients for this therapy. The soluble form of the interleukin-7 appears as a promising candidate in this regard since an association between its high plasmatic level and mortality in critically ill patients has been demonstrated. Because there are no data available on the transcriptional regulation of the interleukin-7 receptor in such patients, this study aimed to explore the expression level of different interleukin-7 receptor transcripts after septic shock and evaluate their association with mortality. Design: Retrospective discovery cohort (30 patients) and validation cohort (177 patients). Setting: Two French ICUs (discovery study) and six French ICUs (validation study). Patients: Adult septic shock patients. Interventions: None. Measurements and Main Results: The quantification of several interleukin-7 receptor transcripts using specific reverse transcription quantitative polymerase chain reaction designs allowed for global evaluation of interleukin-7 receptor gene expression in whole blood. In the discovery cohort, all interleukin-7 receptor transcripts studied were expressed at lower levels in septic shock patients than in healthy volunteers. Interleukin-7 receptor gene expression at day 3 after septic shock diagnosis was associated with day 28 mortality. Patients at a lower risk of death showed higher expression levels. These results were confirmed in the independent validation cohort. Interestingly, using a threshold obtained on the discovery cohort, we observed in the validation cohort a high negative predictive value for day 28 mortality for the transcript encoding the membrane form of interleukin-7 receptor (0.86; 95% CI, 0.79–0.93). Conclusions: Interleukin-7 receptor transcripts appear as biomarkers of impaired adaptive immune response in septic shock patients and as a promising tool for patient stratification in clinical trials evaluating immunoadjuvant therapies.

Purpose Intensive care unit (ICU)-acquired infections (IAI) result in increased hospital and ICU stay, costs and mortality. To date, no biomarker has shown sufficient evidence and ease of application in clinical routine for the identification of patients at risk of IAI. We evaluated the association of the systemic mRNA expression of two host response biomarkers, CD74 and IL10, with IAI occurrence in a large cohort of ICU patients. Methods ICU patients were prospectively enrolled in a multicenter cohort study. Whole blood was collected on the day of admission (D1) and on day 3 (D3) and day 6 (D6) after admission. Patients were screened daily for IAI occurrence and data were censored after IAI diagnosis. mRNA expression levels of biomarkers were measured using RT-qPCR. Fine and Gray competing risk models were used to assess the association between gene expression and IAI occurrence. Results A total of 725 patients were analyzed. At least one IAI episode occurred in 137 patients (19%). After adjustment for shock and sepsis status at admission, CD74 and IL10 levels were found to be significantly associated with IAI occurrence [subdistribution hazard ratio (95% confidence interval) 0.67 (0.46–0.97) for CD74 D3/D1 expression ratio and 2.21 (1.63–3.00) for IL10 at D3]. IAI cumulative incidence was significantly different between groups stratified according to CD74 or IL10 expression (Gray tests p < 0.001). Conclusion Our results suggest that two immune biomarkers, CD74 and IL10, could be relevant tools for the identification of IAI risk in ICU patients.

Hospital-acquired infections (HAI) are associated with significant mortality and morbidity and prolongation of hospital stay, adding strain on limited hospital resources. Despite stringent infection control practices some children remain at high risk of developing HAI. The development of biomarkers which could identify these patients would be useful. In this study our objective was to evaluate mRNA candidate biomarkers for HAI prediction in a pediatric intensive care unit. Serial blood samples were collected from patients admitted to pediatric intensive care unit between March and June 2012. Candidate gene expression (IL1B, TNF, IL10, CD3D, BCL2, BID) was quantified using RT-qPCR. Comparisons of relative gene expression between those that did not develop HAI versus those that did were performed using Mann Whitney U-test. Exclusion criteria were: age pIL1B and IL10) was observed in patients who developed HAI, as well as a pro-apoptosis pattern (higher expression of BID and lower expression of BCL2). CD3D, a key TCR co-factor was also significantly down-modulated in patients who developed HAI. To our knowledge, this is the first study of mRNA biomarkers of HAI in the paediatric population. Increased mRNA expressions of anti-inflammatory cytokine and modulation of apoptotic genes suggest the development of immunosuppression in critically ill children. Immune monitoring using a panel of genes may offer a novel stratification tool to identify HAI risk.