Use of Immune Profiling Panel to assess the immune response of septic patients for prediction of worsening as a composite endpoint.

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.

Persistent NLRP3 inflammasome activation is associated with delayed immunosuppression in septic patients.

Sepsis triggers a complex response marked by the simultaneous presence of proinflammatory and immunosuppressive elements, disrupting the mechanisms intended to maintain homeostasis. While the NLRP3 inflammasome has been demonstrated to contribute to the inflammatory side, its connection with delayed sepsis-induced immunosuppression remains unexplored. The present objective was to concomitantly and prospectively assess NLRP3 activation (IL-1ß, IL-18, and soluble receptors) and features of immune failure (IL-10, mHLA-DR, myeloid-derived suppressor cells) in septic patients. To validate our findings, we conducted a transcriptomic analysis of mRNA of NLRP3-related genes (IL-18R1, IL-1R2) on an additional cohort of 107 patients. Two distinct endotypes were identified. One cluster displayed moderate inflammation rapidly returning to normal values, while the other exhibited a higher inflammatory response persisting until day 28, which was associated with persistent marked immunosuppression and higher 28-d mortality. Identifying endotypes with different pro/anti-inflammatory trajectories could hold important clinical implications for the management of sepsis.

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.

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.

Distinct Immune Reconstitution Profiles Captured by Immune Functional Assays at 6 Months Post Allogeneic Hematopoietic Stem Cell Transplantation.

Immune reconstitution after allogeneic-hematopoietic-stem-cell transplantation (allo-HSCT) is a complex and individual process. In this cross-sectional study, whole-blood (WB) immune functional assay (IFA) was used to characterize immune function by assessing immune-related gene/pathway alterations. The usefulness of this tool in the context of infection, 6 months after transplantation, was evaluated. Sixty allo-HSCT recipients at 6 months after transplantation and 10 healthy volunteers (HV) were included. WB was stimulated in standardized TruCulture tubes using lipopolysaccharides and Staphylococcal enterotoxin B. Gene expression was quantified using a custom 144-gene panel using NanoString nCounter technology and analyzed using Ingenuity Pathway Analysis. The relationships between immune function and clinical characteristics, immune cell counts, and post-transplantation infections were assessed. Allo-HSCT recipients were able to activate similar networks of the innate and adaptive immune response compared to HV, with, nevertheless, a lower intensity. A reduced number and a lower expression of genes associated with immunoregulatory and inflammatory processes were observed in allo-HSCT recipients. The use of immunosuppressive treatments was associated with a protracted immune reconstitution revealed by transcriptomic immunoprofiling. No difference in immune cell counts was observed among patients receiving or not receiving immunosuppressive treatments using a large immunophenotyping panel. Moreover, the expression of a set of genes, including CCL3/CCL4, was significantly lower in patients with Herpesviridae reactivation (32%, 19/60), which once again was not identified using classical immune cell counts. Transcriptional IFA revealed the heterogeneity among allo-HSCT recipients with a reduced immune function, a result that could not be captured by circulating immune cell counts. This highlights the potential added value of this tool for the personalized care of immunocompromised patients.

A 9-mRNA signature measured from whole blood by a prototype PCR panel predicts 28-day mortality upon admission of critically ill COVID-19 patients.

Immune responses affiliated with COVID-19 severity have been characterized and associated with deleterious outcomes. These approaches were mainly based on research tools not usable in routine clinical practice at the bedside. We observed that a multiplex transcriptomic panel prototype termed Immune Profiling Panel (IPP) could capture the dysregulation of immune responses of ICU COVID-19 patients at admission. Nine transcripts were associated with mortality in univariate analysis and this 9-mRNA signature remained significantly associated with mortality in a multivariate analysis that included age, SOFA and Charlson scores. Using a machine learning model with these 9 mRNA, we could predict the 28-day survival status with an Area Under the Receiver Operating Curve (AUROC) of 0.764. Interestingly, adding patients' age to the model resulted in increased performance to predict the 28-day mortality (AUROC reaching 0.839). This prototype IPP demonstrated that such a tool, upon clinical/analytical validation and clearance by regulatory agencies could be used in clinical routine settings to quickly identify patients with higher risk of death requiring thus early aggressive intensive care.

Mortality Prediction in Sepsis With an Immune-Related Transcriptomics Signature: A Multi-Cohort Analysis.

Background: Novel biomarkers are needed to progress toward individualized patient care in sepsis. The immune profiling panel (IPP) prototype has been designed as a fully-automated multiplex tool measuring expression levels of 26 genes in sepsis patients to explore immune functions, determine sepsis endotypes and guide personalized clinical management. The performance of the IPP gene set to predict 30-day mortality has not been extensively characterized in heterogeneous cohorts of sepsis patients. Methods: Publicly available microarray data of sepsis patients with widely variable demographics, clinical characteristics and ethnical background were co-normalized, and the performance of the IPP gene set to predict 30-day mortality was assessed using a combination of machine learning algorithms. Results: We collected data from 1,801 arrays sampled on sepsis patients and 598 sampled on controls in 17 studies. When gene expression was assayed at day 1 following admission (1,437 arrays sampled on sepsis patients, of whom 1,161 were alive and 276 (19.2%) were dead at day 30), the IPP gene set showed good performance to predict 30-day mortality, with an area under the receiving operating characteristics curve (AUROC) of 0.710 (CI 0.652-0.768). Importantly, there was no statistically significant improvement in predictive performance when training the same models with all genes common to the 17 microarray studies (n = 7,122 genes), with an AUROC = 0.755 (CI 0.697-0.813, p = 0.286). In patients with gene expression data sampled at day 3 following admission or later, the IPP gene set had higher performance, with an AUROC = 0.804 (CI 0.643-0.964), while the total gene pool had an AUROC = 0.787 (CI 0.610-0.965, p = 0.811). Conclusion: Using pooled publicly-available gene expression data from multiple cohorts, we showed that the IPP gene set, an immune-related transcriptomics signature conveys relevant information to predict 30-day mortality when sampled at day 1 following admission. Our data also suggests that higher predictive performance could be obtained when assaying gene expression at later time points during the course of sepsis. Prospective studies are needed to confirm these findings using the IPP gene set on its dedicated measurement platform.

T cell response against SARS-CoV-2 persists after one year in patients surviving severe COVID-19.

BACKGROUND: In critically ill COVID-19 patients, the initial response to SARS-CoV-2 infection is characterized by major immune dysfunctions. The capacity of these severe patients to mount a robust and persistent SARS-CoV-2 specific T cell response despite the presence of severe immune alterations during the ICU stay is unknown. METHODS: Critically ill COVID-19 patients were sampled five times during the ICU stay and 9 and 13 months afterwards. Immune monitoring included counts of lymphocyte subpopulations, HLA-DR expression on monocytes, plasma IL-6 and IL-10 concentrations, anti-SARS-CoV-2 IgG levels and T cell proliferation in response to three SARS-CoV-2 antigens. FINDINGS: Despite the presence of major lymphopenia and decreased monocyte HLA-DR expression during the ICU stay, convalescent critically ill COVID-19 patients consistently generated adaptive and humoral immune responses against SARS-CoV-2 maintained for more than one year after hospital discharge. Patients with long hospital stays presented with stronger anti-SARS-CoV-2 specific T cell response but no difference in anti-SARS-CoV2 IgG levels. INTERPRETATION: Convalescent critically ill COVID-19 patients consistently generated a memory immune response against SARS-CoV-2 maintained for more than one year after hospital discharge. In recovered individuals, the intensity of SARS-CoV-2 specific T cell response was dependent on length of hospital stay. FUNDING: This observational study was supported by funds from the Hospices Civils de Lyon, Fondation HCL, Claude Bernard Lyon 1 University and Région Auvergne Rhône-Alpes and by partial funding by REACTing (Research and ACTion targeting emerging infectious diseases) INSERM, France and a donation from Fondation AnBer (http://fondationanber.fr/).

Immune Profiling Demonstrates a Common Immune Signature of Delayed Acquired Immunodeficiency in Patients With Various Etiologies of Severe Injury.

OBJECTIVES: The host response plays a central role in the pathophysiology of sepsis and severe injuries. So far, no study has comprehensively described the overtime changes of the injury-induced immune profile in a large cohort of critically ill patients with different etiologies. DESIGN: Prospective observational cohort study. SETTING: Adult ICU in a University Hospital in Lyon, France. PATIENTS: Three hundred fifty-three septic, trauma, and surgical patients and 175 healthy volunteers were included in the REAnimation Low Immune Status Marker study. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Extensive immune profiling was performed by assessing cellular phenotypes and functions, protein, and messenger RNA levels at days 1-2, 3-4, and 5-7 after inclusion using a panel of 30 standardized immune markers. Using this immunomonitoring panel, no specificity in the immune profile was observed among septic, trauma, and surgical patients. This common injury-induced immune response was characterized by an initial adaptive (i.e., physiologic) response engaging all constituents of the immune system (pro- and anti-inflammatory cytokine releases, and innate and adaptive immune responses) but not associated with increased risk of secondary infections. In contrary, the persistence in a subgroup of patients of profound immune alterations at the end of the first week after admission was associated with increased risk of secondary infections independently of exposure to invasive devices. The combined monitoring of markers of pro-/anti-inflammatory, innate, and adaptive immune responses allowed a better enrichment of patients with risk of secondary infections in the selected population. CONCLUSIONS: Using REAnimation Low Immune Status Marker immunomonitoring panel, we detected delayed injury-acquired immunodeficiency in a subgroup of severely injured patients independently of primary disease. Critically ill patients' immune status could be captured through the combined monitoring of a common panel of complementary markers of pro-/anti-inflammatory, innate, and adaptive immune responses. Such immune monitoring needs to be incorporated in larger study cohorts with more extensive immune surveillance to develop specific hypothesis allowing for identification of biological systems affecting altered immune function related to late infection in the setting of acute systemic injury.

Monocyte Trajectories Endotypes Are Associated With Worsening in Septic Patients.

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. The immune system plays a key role in sepsis onset and remains dysregulated over time in a heterogeneous manner. Here, we decipher the heterogeneity of the first week evolution of the monocyte HLA-DR (mHLA-DR) surface protein expression in septic patients, a key molecule for adaptive immunity onset. We found and verified four distinctive trajectories endotypes in a discovery (n = 276) and a verification cohort (n = 102). We highlight that 59% of septic patients exhibit low or decreasing mHLA-DR expression while in others mHLA-DR expression increased. This study depicts the first week behavior of mHLA-DR over time after sepsis onset and shows that initial and third day mHLA-DR expression measurements is sufficient for an early risk stratification of sepsis patients. These patients might benefit from immunomodulatory treatment to improve outcomes. Going further, our study introduces a way of deciphering heterogeneity of immune system after sepsis onset which is a first step to reach a more comprehensive landscape of sepsis.

Concomitant Assessment of Monocyte HLA-DR Expression and Ex Vivo TNF-α Release as Markers of Adverse Outcome after Various Injuries-Insights from the REALISM Study.

Intensive care unit (ICU) patients develop an altered host immune response after severe injuries. This response may evolve towards a state of persistent immunosuppression that is associated with adverse clinical outcomes. The expression of human leukocyte antigen DR on circulating monocytes (mHLA-DR) and ex vivo release of tumor necrosis factor α (TNF-α) by lipopolysaccharide-stimulated whole blood are two related biomarkers offered to characterize this phenomenon. The purpose of this study was to concomitantly evaluate the association between mHLA-DR and TNF-α release and adverse clinical outcome (i.e., death or secondary infection) after severe trauma, sepsis or surgery in a cohort of 353 ICU patients. mHLA-DR and TNF-α release was similarly and significantly reduced in patients whatever the type of injury. Persistent decreases in both markers at days 5-7 (post-admission) were significantly associated with adverse outcomes. Overall, mHLA-DR (measured by flow cytometry) appears to be a more robust and standardized parameter. Each marker can be used individually as a surrogate of immunosuppression, depending on center facilities. Combining these two parameters could be of interest to identify the most immunosuppressed patients presenting with a high risk of worsening. This last aspect deserves further exploration.

RNA-Seq Transcriptome Analysis Reveals Long Terminal Repeat Retrotransposon Modulation in Human Peripheral Blood Mononuclear Cells after In Vivo Lipopolysaccharide Injection.

Human endogenous retroviruses (HERVs) and mammalian apparent long terminal repeat (LTR) retrotransposons (MaLRs) are retroviral sequences that integrated into germ line cells millions of years ago. Transcripts of these LTR retrotransposons are present in several tissues, and their expression is modulated in pathological conditions, although their function remains often far from being understood. Here, we focused on the HERV/MaLR expression and modulation in a scenario of immune system activation. We used a public data set of human peripheral blood mononuclear cells (PBMCs) RNA-Seq from 15 healthy participants to a clinical trial before and after exposure to lipopolysaccharide (LPS), for which we established an RNA-Seq workflow for the identification of expressed and modulated cellular genes and LTR retrotransposon elements.IMPORTANCE We described the HERV and MaLR transcriptome in PBMCs, finding that about 8.4% of the LTR retrotransposon loci were expressed and identifying the betaretrovirus-like HERVs as those with the highest percentage of expressed loci. We found 4,607 HERV and MaLR loci that were modulated as a result of in vivo stimulation with LPS. The HERV-H group showed the highest number of differentially expressed most intact proviruses. We characterized the HERV and MaLR loci as differentially expressed, checking their genomic context of insertion and observing a general colocalization with genes that are involved and modulated in the immune response, as a consequence of LPS stimulation. The analyses of HERV and MaLR expression and modulation show that these LTR retrotransposons are expressed in PBMCs and regulated in inflammatory settings. The similar regulation of HERVs/MaLRs and genes after LPS stimulation suggests possible interactions of LTR retrotransposons and the immune host response.