Method for determining the risk of developing a healthcare-associated infection in a patient

Abstract

To provide an in vitro or ex vivo method for determining the risk of developing a healthcare-associated infection in a patient.SOLUTION: The method comprises measuring the expression of CX3CR1 in a biological sample from the subject. The patient is a patient in a hospital, preferably in an emergency unit, resuscitation unit, intensive care unit or continuous care unit, more preferably a sepsis patient, burn patient, trauma patient, or surgery patient, and the biological sample is a blood sample. Expression is measured at the mRNA or protein level.SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates to an in vitro or ex vivo method for determining the risk of developing a healthcare-associated infection in a patient, the method comprising the step of measuring the expression of CX3CR1 in a biological sample from the patient. [Background technology]

[0002] Contracting healthcare-associated infections is a major health care problem, particularly in healthcare settings such as hospitals (more on nosocomial infections below). Nosocomial infections in intensive care units occur in 20–40% of patients and have been documented to be associated with increased morbidity and mortality, longer duration of organ failure requiring supportive care, longer hospital stays, increased healthcare costs, and extensive antibiotic use contributing to antimicrobial resistance. In recent years, the emergence of healthcare-associated infections has been particularly exacerbated by the rise in multidrug-resistant pathogens. The World Health Organization (WHO) estimates that there are approximately 5 million nosocomial infections in European hospitals, resulting in approximately 50,000 deaths and an additional annual cost of 13–24 billion euros. Many factors influence the occurrence and contraction of healthcare-associated infections. These factors include the patient's overall health status, factors related to patient management (e.g., antibiotic administration and / or use of invasive medical devices), factors related to the hospital environment (e.g., nurse-to-patient ratio), and differing use of infection prevention techniques by hospital staff. Recommendations and the establishment of infection control programs have been published and encouraged, particularly by the US Department of Health and Human Services, the European Center for Disease Prevention and Control, the World Health Organization, and national agencies. Prevention and reduction of healthcare-associated infections are a major priority. Healthcare-associated infection control programs have proven effective, particularly in reducing severe infections. However, it has been estimated that up to 65–70% of cases of catheter placement-related blood and urinary tract infections and up to 55% of cases of ventilation-associated pneumonia and surgical site infections could have been avoided. Furthermore, adherence to and application of recommended procedures can be complex in some hospitals, especially in low- and middle-income countries. Early identification of patients at risk of acquiring a healthcare-associated infection would be an important step in preventing that infection and in managing those patients.According to some models, biomarkers that could reduce the time it takes to identify healthcare-associated infections in high-risk populations would reduce mortality in these patients at a cost-effective rate. However, there are currently no clinical in vitro diagnostic tests to identify patients at high risk of contracting healthcare-associated infections.

[0003] On the other hand, it has been surprisingly discovered that measuring the expression of the CX3CR1 gene, which encodes the fractalkine (or CX3CL1) receptor, makes it possible to determine a patient's risk of developing a healthcare-associated infection. Patients at high risk of developing a healthcare-associated infection may benefit from immunostimulatory immunotherapy or personalized management. Literature has already demonstrated that decreased CX3CR1 expression is associated with increased mortality, particularly in patients with sepsis and, more specifically, septic shock (Non-Patent Document 1). However, the usefulness of measuring CX3CR1 expression to predict the development of healthcare-associated infection has not been demonstrated or suggested. [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Pachot et al. (2008), J Immunol 180: 6421-6429 Summary of the Invention [Problem to be solved by the invention]

[0005] Therefore, the object of the present invention is an in vitro or ex vivo method for determining the risk of developing a healthcare-associated infection in a patient, which comprises a step of measuring the expression of CX3CR1 (chromosomal location of the gene according to GRCh38 / hg38: chr3: 39,263,494 to 39,281,735) in a biological sample from the patient. [Means for solving the problem]

[0006] With respect to the present invention, The term "patient" refers to an individual (human being) in contact with a medical professional, such as a doctor (e.g., a general practitioner), or with a medical facility or health care institution (e.g., a hospital, and more particularly, an emergency unit, a resuscitation unit, an intensive care unit or a continuing care unit, or a nursing home-type elderly medical facility). A patient may, for example, be an elderly person undergoing a vaccination protocol (particularly in a nursing home or at a general practitioner's office), An infection is considered "healthcare-associated" if it occurs during or after a healthcare professional's treatment of a patient (diagnosis, treatment, palliative, preventive, educational, or surgical) and was not present or latent at the start of treatment. Healthcare-associated infections (HAIs) include infections acquired within a healthcare facility (known as nosocomial infections) as well as infections acquired during care provided outside of this facility. If the infectious status at the start of treatment is not specifically known, a delay of 48 hours or longer than the incubation period is generally accepted in the definition of HAI. For infections occurring at the site of surgery, infections occurring within 30 days of surgery or, if an implant, prosthesis, or prosthetic material has been placed, within one year of surgery are usually considered healthcare-associated. Infections can be bacterial, fungal, or viral in origin. Infections can also be reactivations of potentially pathogenic latent viruses, such as TTV or herpesviruses (e.g., CMV). The term "biological sample" refers to any sample from a patient, which may be of different nature, such as blood or its derivatives, sputum, urine, stool, skin, cerebrospinal fluid, bronchoalveolar lavage fluid, saliva, gastric secretions, semen, seminal fluid, tears, spinal cord, trigeminal ganglion, adipose tissue, lymphoid tissue, placental tissue, gastrointestinal tissue, reproductive tract tissue, central nervous system tissue, etc. In particular, the sample may be a biological fluid, such as a blood sample or a blood-derived sample. In particular, the blood sample or blood-derived sample may be selected from whole blood (blood collected via the intravenous route, i.e., containing white blood cells, red blood cells, platelets, and plasma), plasma, serum, and any type of cell extracted from blood, such as peripheral blood mononuclear cells (i.e., PBMCs, which include lymphocytes (B, T, and NK cells), dendritic cells, and monocytes), subpopulations of B cells, purified monocytes, or neutrophils.

[0007] Preferably, in the above method, The patient is a patient in a medical facility, preferably a hospital, more preferably a patient in an emergency unit, a resuscitation unit, an intensive care unit or a continuing care unit. Particularly preferably, the patient is a patient with a septic condition (more particularly septic shock), a patient suffering from a burn (more particularly severe burn), a patient suffering from a trauma (more particularly severe trauma) or a patient who has undergone surgery (more particularly major surgery); and The method makes it possible to determine the risk of developing a nosocomial infection in the patient.

[0008] In the case of patients in a septic state (who already have a primary infection), the method according to the invention makes it possible to determine the risk of developing a secondary infection.

[0009] A septic patient (or patient with sepsis) refers to a patient with at least one life-threatening organ failure due to an inadequate host response to infection. CK refers to a subtype of sepsis in which hypotension persists despite adequate vascular filling.

[0010] Preferably, the method according to the invention, as described above, in all its embodiments, comprises: within 15 days from the date of the immunoinflammatory attack (i.e., the trauma for a patient with a trauma, the burn for a patient with a burn, the surgery for a patient who has undergone surgery, or the diagnosis of sepsis for a patient with sepsis), i.e., on the 1st, 2nd, 3rd, 4th, 5th, 6th, 7th, 8th, 9th, 10th, 11th, 12th, 13th, 14th or 15th day (wherein the 1st day corresponds to the day on which the immunoinflammatory attack occurred) from the immunoinflammatory attack (the collection of the biological sample may in particular be carried out on the 1st, 2nd, 3rd, 4th, 5th, 6th, 7th, 8th, 9th, 10th, 11th, 12th, 13th, 14th or 15th day from the immunoinflammatory attack, preferably on the 1st, 2nd, 3rd, 4th, 5th, 6th or 7th day from the immunoinflammatory attack, more preferably on the 3rd, 4th, 5th, 6th or 7th day from the immunoinflammatory attack); and / or Within 7 days, 6 days, 5 days, or 4 days after the day on which the biological sample was collected (regardless of the day on which the biological sample was collected), i.e., on the 3rd, 4th, 5th, 6th, or 7th day after the day on which the biological sample was collected (wherein the 1st day corresponds to the day following the day on which the biological sample was collected), It makes it possible to determine the risk of a patient developing a healthcare-associated infection.

[0011] Preferably, in the above methods, in all embodiments thereof, the biological sample is a blood sample, preferably a whole blood sample or a blood-derived sample (e.g., PBMCs, which may be obtained by the Ficoll method well known to those skilled in the art, or purified monocytes).

[0012] Preferably, in all embodiments, the above method further comprises measuring the expression of another gene of interest in a patient biological sample selected from the list consisting of ADGRE3, BTLA, CD3D, CD74, CD274 (also known as PD-L1), CTLA4 (also known as CD152), HP, ICOS, IFNG, IL1RN, IL6, IL7R (also known as CD127), IL10, IL15, MDC1, PDCD1 (also known as PD-1 and CD279), S100A9, TDRD9, and ZAP70. More preferably, the other gene is selected from the list consisting of BTLA, CD3D, CD74, CD274, CTLA4, HP, ICOS, IFNG, IL1RN, IL7R, IL10, IL15, PDCD1, and S100A9.

[0013] [Table 1] Table 1. Chromosomal location of genes. Expression of these genes can be measured in combination with measuring expression of CX3CR1

[0014] Measuring the expression (or expression level) of a gene consists of quantifying at least one expression product of said gene, which in the context of the present invention is any biological molecule resulting from the expression of said gene.

[0015] More specifically, the expression product of a gene can be an RNA transcript. "Transcript" refers to the RNA obtained from the transcription of a gene, and in particular, messenger RNA (mRNA). More specifically, a transcript is an RNA generated by post-transcriptional modification of the pre-RNA form after transcribing the gene. In the present invention, the expression level of one or more RNA transcripts of the same gene can be measured. Therefore, preferably, in all embodiments of the above method, the expression of a gene (i.e., the expression of CX3CR1, and optionally the expression of another target gene from the above list) is measured at the RNA or mRNA transcript level. In the case of an mRNA transcript, detection can be carried out by any method known to those skilled in the art that allows determining the presence of the transcript in a sample, or by indirectly detecting the transcript after converting the transcript into DNA, or after amplifying the transcript, or after amplifying the DNA obtained after converting the transcript into DNA. Many methods exist for detecting nucleic acids (see, for example, Kricka et al., Clinical Chemistry, 1999, No. 45(4), pp. 453-458; Relier GH et al., DNA Probes, 2nd Ed., Stockton Press, 1993, sections 5 and 6, pp. 173-249). Gene expression can be detected, in particular, by reverse transcription polymerase chain reaction, i.e., RT-PCR, preferably by quantitative RT-PCR, i.e., RT-qPCR (e.g., using FilmArray® technology), by sequencing ( Preferably, it can be measured by high-throughput sequencing) or by hybridization techniques (for example, using hybridization microchips or by NanoString® nCounter® type techniques).

[0016] The expression product of a gene may also be a protein and / or polypeptide that is a translation product of at least one of the transcription products of the gene. Therefore, in the above method, the expression of a gene may also be measured at the protein level. All of the protein isoforms that are the expression products of the gene may be measured, alone or in combination, as markers for determining the risk of developing a healthcare-associated infection in a patient. The measurement of the expression of a gene at the protein level in a biological sample may be performed according to techniques well known to those skilled in the art for determining the amount or quantity of one or more test subjects in a biological sample. For example, ELISA (Enzyme Linked Immunosorbent Assay) may be used. Examples include analysis by immunoassays such as ELISA (Enzyme Linked Fluorescent Assay), ELFA (Enzyme Linked Fluorescent Assay) and RIA (Radio Immuno Assay), and analysis by mass spectrometry.

[0017] Measuring the expression level of a gene allows for determining the quantity of one or more transcripts (or one or more proteins) present in a biological sample, or for providing a value derived therefrom. The quantity-derived value can be, for example, an absolute concentration calculated by a calibration curve obtained from serial dilutions of an amplicon (or protein or polypeptide) solution of known concentration. The quantity-derived value also corresponds to a standardized and calibrated quantity value, such as CNRQ (Calibrated Normalized Relative Quantity, Hellemans et al. (2007), Genome biology 8(2):R19), which multiplies the values ​​of a reference sample (or calibrator) and one or more housekeeping genes (also called reference genes). Examples of housekeeping genes include DECR1, HPRT1, PPIB, RPLP0, PPIA, GLYR1, RANBP3, 18S, GAPDH, and ACTB genes.

[0018] Therefore, in all embodiments of the above method, the expression of the gene of interest is preferably normalized to the expression of one or more housekeeping genes (or reference genes) known to those skilled in the art, more preferably using one or more of the following housekeeping genes: DECR1 (chromosomal location of the gene in GRCh38 / hg38: chr8: 90,001,352-90,053,633), HPRT1 (chromosomal location of the gene in GRCh38 / hg38: chrX: 134,452,842-134,520,513), and PPIB (chromosomal location of the gene in GRCh38 / hg38: chr15: 64,155,812-64,163,205).

[0019] Preferably, in all embodiments of the above method, the expression (preferably normalized expression) of the gene of interest in a patient's biological sample is compared to a reference value or the expression (preferably normalized expression) of the same gene of interest in a biological reference sample (these data are used to calculate the CNRQ as described above). The reference sample can be, for example, a sample from a volunteer (healthy individual), a sample from a patient, or a mixture of samples from multiple volunteers (one of them) or multiple patients (the other of them). The reference sample can also be a sample taken from a single volunteer (or a mixture of samples taken from multiple volunteers) that has then been treated ex vivo with an immune system stimulant (such as LPS or lipopolysaccharide). The reference sample can also be a mixture of an untreated sample and a sample that has been treated ex vivo with an immune system stimulant. .

[0020] Preferably, in all embodiments, the above-mentioned method for determining the risk of developing a healthcare-associated infection also includes a medical management step to reduce the risk of developing a healthcare-associated infection. Patients identified as being at increased risk of developing a healthcare-associated infection may receive appropriate medical management to reduce the risk of developing a healthcare-associated infection and, for example, to reduce the risk of developing sepsis, septic shock, or death. Examples of medical management include immunomodulatory therapy tailored to the patient or prophylactic antibiotic therapy. The two therapies may be combined and / or applied in a continuous care unit or resuscitation unit to reduce the risk of developing a healthcare-associated infection, for example, to reduce the risk of developing sepsis, septic shock, or death several days after measuring the expression of the biomarker. Preferably, the immunomodulatory therapy is an immunostimulatory therapy if the patient is determined to be in an immunosuppressed state, or an anti-inflammatory therapy if the patient is determined to be in an inflammatory state. Regarding the immunostimulatory treatments that may be selected, for example, interleukins (particularly IL-7, IL-15 or IL-3), growth factors (particularly GM-CSF), interferons (particularly IFN γ ), Toll agonists, antibodies (especially anti-PD1, anti-PDL1, anti-LAG3, anti-TIM3, anti-IL-10, or anti-CTLA4 antibodies), molecules that inhibit transferrin and apoptosis, FLT3L, thymosin alpha 1, and adrenergic blockers. Anti-inflammatory treatments include glucocorticoids, cytostatics, molecules that act on immunophilins and cytokines, molecules that block IL-1 receptors, and anti-TNF treatments. Examples of suitable prophylactic antibiotic treatments to prevent pneumonia are described in particular in Annales Françaises d'Anesthesie et de Reanimation (30; 2011; 168-190). Conversely, patients who do not pose a risk of developing a healthcare-associated infection can be immediately transferred to daytime hospital services (e.g., infectious disease services) rather than remaining in services with unnecessary close observation.

[0021] Another object of the present invention is a kit comprising means for amplifying and / or means for detecting expression (preferably primers and / or probes or antibodies) of CX3CR1 and another gene selected from the list consisting of ADGRE3, BTLA, CD3D, CD74, CD274, CTLA4, HP, ICOS, IFNG, IL1RN, IL6, IL7R, IL10, IL15, MDC1, PDCD1, S100A9, TDRD9 and ZAP70 (preferably said another gene is BTLA, CD3D, CD74, CD274, CTLA4, HP, ICOS, IFNG, IL1RN, IL6, IL7R, IL10, IL15, MDC1, PDCD1, S100A9, TDRD9 and ZAP70). COS, IFNG, IL1RN, IL7R, IL10, IL15, PDCD1 and S100A9, or from the list consisting of ADGRE3, BTLA, CD3D, CD74, CD274, CTLA4, HP, IFNG, IL1RN, IL6, IL7R, IL10, MDC1, PDCD1, S100A9, TDRD9 and ZAP70, more preferably from the list consisting of BTLA, CD3D, CD74, CD274, CTLA4, HP, IFNG, IL1RN, IL7R, IL10, PDCD1 and S100A9). The kit is characterized in that all of the amplification and / or detection means of the kit allow for the detection and / or amplification of a total of no more than 100, preferably no more than 90, preferably no more than 80, preferably no more than 70, preferably no more than 60, preferably no more than 50, preferably no more than 40, preferably no more than 30, preferably no more than 20, preferably no more than 10, preferably no more than 5 biomarkers, preferably no more than 4, preferably no more than 3, preferably no more than 2. "Biomarker" (or "marker") means an objectively measurable biological characteristic that is indicative of a normal or pathological biological process or a pharmacological response to a therapeutic intervention. The biomarker may in particular be detectable at the mRNA or protein level. More particularly, a biomarker may be an endogenous biomarker or locus (such as a gene or HERV / Human Endogenous Retrovirus found in an individual's chromosomal material) or an exogenous biomarker (such as a viral etc.).

[0022] Thus, the kit may also comprise means for amplifying and / or detecting, for example, one or more housekeeping genes (preferably selected from the list consisting of DECR1, HPRT1 and PPIB). The kit may also comprise positive control means making it possible to assess the amount of RNA extraction, any amplification and / or hybridization process.

[0023] A "primer" or "amplification primer" can consist of 5 to 100 nucleotides, preferably 15 to 30 nucleotides, and can be a nucleotide fragment that has specificity for hybridization with a target nucleotide sequence under conditions determined to initiate enzymatic polymerization, for example, in an enzymatic amplification reaction of the target nucleotide sequence. Generally, a "primer pair" consisting of two primers is used. When it is desired to amplify multiple different biomarkers (e.g., genes), multiple different primer pairs are preferably used. Here, each primer pair preferably has the ability to specifically hybridize to a different biomarker.

[0024] The term "probe" or "hybridization probe" refers to a nucleotide fragment typically consisting of 5 to 100 nucleotides, preferably 15 to 90 nucleotides, and even more preferably 15 to 35 nucleotides, that has hybridization specificity under conditions determined to form a hybridization complex with a target nucleotide sequence. The probe also contains a reporter (such as a fluorophore, enzyme, or any other detection system) that enables detection of the target nucleotide sequence. In the present invention, the target nucleotide sequence may be a nucleotide sequence contained in messenger RNA (mRNA) or a nucleotide sequence contained in complementary DNA (cDNA) obtained by reverse transcription of the mRNA. When targeting multiple different biomarkers (e.g., genes), multiple different probes are preferably used. Here, each probe preferably has the ability to specifically hybridize to a different biomarker.

[0025] "Hybridization" refers to the process by which, under appropriate conditions, two nucleotide fragments with sufficiently complementary sequences, such as a hybridization probe and a target nucleotide fragment, can form a duplex with stable and specific hydrogen bonds. A nucleotide fragment "hybridizable" with a polynucleotide is a fragment capable of hybridizing with the polynucleotide under hybridization conditions, which can be determined in a known manner in each case. Hybridization conditions are determined by the stringency, i.e., rigor, of the operating conditions. The higher the stringency, the more specific the hybridization. Stringency is defined, in particular, according to the base composition of the probe / target duplex and the degree of mismatch between the two nucleic acids. Stringency can also be a function of reaction parameters such as the concentration and type of ionic species present in the hybridization solution, the nature and concentration of denaturing agents, and / or the hybridization temperature. The stringency of the conditions under which the hybridization reaction is carried out depends primarily on the hybridization probe used. All of these data are well known, and appropriate conditions can be determined by those skilled in the art. Generally, the temperature for the hybridization reaction is about 20 to 70°C, particularly 35 to 65°C, when the concentration of the hybridization probe is about 0.5 to 1 M in physiological saline solution, depending on the length of the hybridization probe used. Next, a step of detecting the hybridization reaction is carried out.

[0026] "Enzymatic amplification reaction" means a process that produces multiple copies of a target nucleotide fragment by the action of at least one enzyme. Such amplification reactions are well known to those skilled in the art. Examples of enzymatic amplification methods include PCR (polymerase chain reaction), LCR (ligase chain reaction), RCR (repair chain reaction), 3SR (self-sustained sequence replication), which has patent application WO-A-90 / 06995, NASBA (nucleic acid sequence-based amplification), TMA (transcription-mediated amplification), which has patent US-A-5,399,491, and LAMP (loop-mediated isothermal amplification), which has patent US-A-6,410,278. When the enzymatic amplification reaction is PCR, and more particularly when the amplification step is preceded by a step of reverse transcribing messenger RNA (mRNA) into complementary DNA (cDNA), the term RT-PCR (RT stands for "reverse transcription") is used, and when the PCR is quantitative, the term qPCR or RT-qPCR is used.

[0027] Another object of the present invention is to provide means for amplifying and / or means for detecting expression (preferably primers and / or probes, or antibodies) of CX3CR1, and optionally also of another gene selected from the list consisting of ADGRE3, BTLA, CD3D, CD74, CD274, CTLA4, HP, ICOS, IFNG, IL1RN, IL6, IL7R, IL10, IL15, MDC1, PDCD1, S100A9, TDRD9 and ZAP70 (preferably the other gene is selected from the list consisting of BTLA, CD3D, CD74, CD274, CTLA4, HP, ICOS, IFNG, IL1RN, IL6, IL7R, IL10, IL15, MDC1, PDCD1, S100A9, TDRD9 and ZAP70); G, IL1RN, IL7R, IL10, IL15, PDCD1 and S100A9, or from the list consisting of ADGRE3, BTLA, CD3D, CD74, CD274, CTLA4, HP, IFNG, IL1RN, IL6, IL7R, IL10, MDC1, PDCD1, S100A9, TDRD9 and ZAP70, more preferably from the list consisting of BTLA, CD3D, CD74, CD274, CTLA4, HP, IFNG, IL1RN, IL7R, IL10, PDCD1 and S100A9), or A kit comprising such amplification and / or detection means, preferably wherein all of the amplification and / or detection means of the kit allow the detection and / or amplification of a total of no more than 100, preferably no more than 90, preferably no more than 80, preferably no more than 70, preferably no more than 60, preferably no more than 50, preferably no more than 40, preferably no more than 30, preferably no more than 20, preferably no more than 10, preferably no more than 5 biomarkers, preferably no more than 4, preferably no more than 3, preferably no more than 2 biomarkers, and optionally the kit comprises means for amplifying and / or detecting the expression of one or more housekeeping genes (preferably selected from the list consisting of DECR1, HPRT1 and PPIB). Using The present invention relates to determining the risk of developing a healthcare-associated infection, preferably a nosocomial infection, in a patient, wherein the patient is preferably a patient in a healthcare facility, more preferably a patient in a hospital, preferably an emergency unit, a resuscitation unit, an intensive care unit or a continuing care unit. Particularly preferably, the patient is a patient in a septic state (more particularly, septic shock), a patient suffering from a burn (more particularly, severe burn), a patient suffering from a trauma (more particularly, severe trauma), or a patient who has undergone surgery (more particularly, major surgery). DETAILED DESCRIPTION OF THE INVENTION

[0028] The following examples illustrate the present invention without, however, limiting it.

[0029] Example 1: Measurement of CX3CR1 expression makes it possible to predict the risk of developing healthcare-associated infections in patients

[0030] material and method A prospective, longitudinal, monocentric observational clinical study was conducted at Edouard Herriot Hospital (Lyon, France). The design of this clinical study was based on the same method as Rol et al. (20 17), BMJ Open 7(6): e015734. This clinical study was approved by the National Agency for the Safety of Medicines and Health Products (ANSM) in November 2015 and approved by the South-East II The protocol was approved by the Personal Protection Committee. The protocol was revised in June 2016 and again in January 2017. Briefly, a total of 377 patients were included between December 2015 and March 2018. These patients were septic (n = 35) or in septic shock (n = 72), had severe burns (n ​​= 24), severe trauma (n = 137), or were admitted to a resuscitation or intensive care unit after major surgery (n = 109), and 175 healthy volunteers.

[0031] Patients with septic conditions / septic shock: According to the initial clinical protocol, only patients with septic shock were included based on suspicion of the site of infection. Treatment with catecholamines was initiated within 48 hours after admission to the intensive care unit, and treatment with catecholamines (norepinephrine) at a dose of > 0.25 μg / kg / min for more than 2 hours was started. Subsequently, the eligibility criteria were revised in August 2016 after the publication of the new definition of septic shock, Sepsis 3 (Singer et al. (2016), JAMA 315(8):801 - 810). Therefore, patients with septic shock were included based on suspicion of the site of infection, treatment with catecholamines was initiated within 48 hours after admission to the intensive care unit, and vasopressor treatment was started to maintain blood pressure at ≥ 65 mmHg and lactate concentration at > 2 mmol / L (18 mg / dL) despite correction of hypovolemia. In 2017, patients with sepsis (according to the definition of Sepsis 3), that is, suspicion of the site of infection within 48 hours after admission to the intensive care unit and an increase in the SOFA score of ≥ 2 points compared to the baseline SOFA, were added. For this group, day 1 corresponds to the day when sepsis or septic shock was diagnosed.

[0032] Severe trauma : In the initial protocol, only patients with severe trauma were included (Injury Severity Score (ISS) ≥ 25). In August 2016, the possibility of including less severe trauma was added (16 < ISS < 24). For this group, day 1 corresponds to the day of admission to the intensive care unit or the intensive care unit (approximately the day of trauma).

[0033] major surgery : In the initial protocol, only esophagogastrectomy, Bricker type cystectomy, pancreaticoduodenectomy, and abdominal aortic surgery by laparotomy were considered. In January 2017, other types of surgeries with a high risk of complications were added. (Total or distal) pancreatectomy, neuroendocrine tumor, hepatectomy (right), extended colectomy (laparotomy), abdominoperineal resection of the rectum, nephrectomy (laparotomy, PKD), iliofemoral bypass (Scarpa). For this group, day 1 corresponds to the day of surgery.

[0034] Severe burns Patients were selected based on having a burn injury of more than 30% of the total surface area. For this population, day 1 corresponded to the day of admission to the resuscitation or intensive care unit (approximately the day of the burn).

[0035] Exclusion criteria mainly related to factors that could affect immune status and bias the results (e.g., severe neutropenia, corticosteroid treatment, oncological hematopathology, etc.). Three physicians not involved in patient recruitment independently investigated each suspected HCAI incident occurring in the hospital before day 30. Twenty-six percent of patients had at least one HCAI before day 30 or before discharge.

[0036] Blood samples were placed in PAXgene® tubes (product number 762165, PreA Blood samples were collected on the same day (approximately D14, D28, and D60) from patients. Healthy volunteers were sampled once. Patients were sampled multiple times: 3-4 times during the first week (days 1 or 2: D1 / 2, 3 or 4: D3 / 4, and 5, 6, or 7: D5 / 7), and then 3 times thereafter (approximately D14, D28, and D60).

[0037] The expression levels of CX3CR1 in these samples were measured by RT-qPCR. RNA was extracted from whole blood samples using the Maxwell HT Simply RNA Kit (product number AX2420, Promega) and the EVO automated platform (TECAN) according to the kit supplier's instructions. Ten nanograms of total RNA was then reverse transcribed into complementary DNA (cDNA) using Fluidigm Reverse Transcription Master Mix (product number PN100-6472 A1, Fluidigm) according to the supplier's instructions. CX3CR1 expression was then quantified by qPCR using Fluidigm's Biomark HD Real-Time PCR System.

[0038] First, a cDNA preamplification step was performed using PreAmp master mix (product number PN100-5876 B1, Fluidigm) according to the supplier's instructions. The preamplified cDNA was then diluted 5-fold and subjected to qPCR on a Fluidic Integrated Circuit 192.24 (product number PN100-6170 C1) according to the supplier's recommendations. The part numbers of the probes and primers used for qPCR are listed in Table 2.

[0039] The threshold cycle (or Ct) was then determined. CX3CR1 expression was normalized to CNRQ (Calibrated Normalized Relative Quantity). This was performed using the geometric mean Ct of three housekeeping genes (DECR1, HPRT1, PPIB) and a calibrator (corresponding to a mixture of ex vivo samples (50%) treated with LPS (an immune system stimulant) and untreated ex vivo samples (50%) from healthy volunteers / patients) for each fluidic integrated circuit 192.24, as described in Hellemans et al. (2007), Genome biology 8(2):R19.

[0040] [Table 2] Table 2. Probes and primers used for qPCR

[0041] For data analysis, the association between CX3CR1 expression measured at different time points in week 1 and the occurrence of healthcare-associated infections before day 30 after enrollment was evaluated. Results were calculated in the form of hazard ratios (HR IQR) expressed as interquartile ranges and associated 95% confidence intervals. Univariate logistic regression was then performed to predict the risk of developing healthcare-associated infections before day 15. The power of the logistic regression prediction to distinguish between those with and without healthcare-associated infections was quantified by the area under the curve (AUC) of the ROC (Receiver Operating Characteristic) curve, and the 95% confidence interval was estimated.

[0042] The association between CX3CR1 expression and the occurrence of healthcare-associated infection was then evaluated for different time intervals from the onset of infection (i.e., the period between sample collection and the first occurrence of infection). The different periods of interest were healthcare-associated infections within 4 days and 7 days after sample collection, regardless of when the sample was collected. For each patient with healthcare-associated infection, the sample of interest corresponds to the sample collection closest to the occurrence of the first episode of healthcare-associated infection.

[0043] For patients who did not suffer from a healthcare-associated infection (i.e., control patients), a matching method was used to select control patients with the same sample collection date and similar SOFA and Charlson scores for each case. Finally, a unique control was selected for each unique case. Univariate logistic regression was performed. The magnitude of the predicted value by logistic regression for distinguishing between those with and without a healthcare-associated infection was quantified by the area under the receiver operating characteristic curve (AUC), and the 95% confidence interval was estimated.

[0044] result In the overall patient population, decreased expression of CX3CR1 mRNA levels measured on days 3 / 4 or 5 / 7 after cohort inclusion was associated with a higher risk of developing a healthcare-associated infection before day 30 (D3 / 4: HR IQR = 0.54 [0.39-0.74], p = 0.0001; D5 / 7: HR IQR = 0.57 [0.42-0.79], p = 0.0006). This association remained significant after adjustment for the SOFA and Charlson scores for both CX3CR1 expression measurements (D3 / 4: HR IQR = 0.54 [0.39-0.74], p = 0.0001; D5 / 7: HR IQR = 0.57 [0.42-0.79], p = 0.0006). IQR=0.61[0.44~0.85], p=0.003;D5 / 7:HR IQR=0.65[0.46~0.91], p=0.01).

[0045] Furthermore, the predictive model showed that the expression of CX3CR1 at the mRNA level measured on D3 / 4 or D5 / 7 after cohort inclusion allowed the prediction of the occurrence of healthcare-associated infection before day 15 after cohort inclusion (Table 3).

[0046] [Table 3] Table 3. Performance of measurements of CX3CR1 expression measured on D3 / 4 or D5 / 7 after cohort inclusion for predicting the occurrence of healthcare-associated infection before day 15 after cohort inclusion (AUC and 95% confidence interval, CI)

[0047] The predictive model also showed that the expression of CX3CR1 at the mRNA level measured on D3 / 4 or D5 / 7 made it possible to predict the occurrence of healthcare-associated infection within 4 or 7 days after sample collection (Table 4).

[0048] [Table 4] Table 4. Performance of measurements of CX3CR1 expression to predict the occurrence of healthcare-associated infection within 4 or 7 days after sample collection (AUC and 95% confidence interval, CI)

[0049] Thus, the results obtained above indicate that by measuring the expression of CX3CR1 alone, it is possible to predict the occurrence of healthcare-associated infection within 15 days of an immune inflammatory challenge, within 4 days after sample collection, or within 7 days after sample collection.

[0050] Example 2: Measurement of the expression of CX3CR1 and other genes allows for improved prediction of the risk of developing healthcare-associated infections

[0051] material and method The materials and methods were the same as in Example 1, with the following exceptions: 1) For the genes of interest (BTLA and IL15, as well as the reference genes measured using two references), a cDNA preamplification step was performed using a separate PreAmp master mix reference (product number PN100-5875 C1, Fluidigm), followed by a further processing step using Exonuclease I (product number PN100-5875 C1, Fluidigm), and in addition to these genes, an amplification step was performed using another type of fluidic integrated circuit 192.24 (product number PN100-7222 C1) as recommended by the supplier. 2) Here, a multivariate logistic regression (combined measurements of the expression of CX3CR1 and another gene selected from the list consisting of BTLA, CD3D, CD74, CD274, CTLA4, HP, ICOS, IFNG, IL1RN, IL7R, IL10, IL15, PDCD1, and S100A9) was performed.

[0052] Therefore, expression of the genes of interest (except BTLA and IL15) was measured using TaqMan Chemistry, where normalization was performed using the expression of the reference genes, also measured using TaqMan Chemistry (ThermoFisher reference, containing two primers and one probe). Expression of the BTLA and IL15 genes was measured using SYBR Green Chemistry, where normalization was performed using the expression of the reference genes, also measured using SYBR Green Chemistry (Integrated DNA Technologies reference, containing two primers). In addition to the probes and primers already shown in Table 2 (for CX3CR1 and reference genes in TaqMan Chemistry), additional probes and primers (for the other genes of interest and reference genes in SYBR Green Chemistry) used in this example are shown in Table 5.

[0053] [Table 5] Table 5. Additional probes and primers used for qPCR

[0054] result In addition to measuring the expression of CX3CR1, measuring the expression of one of these other genes of interest can improve the predictive performance of the risk of developing a healthcare-associated infection, either before day 15 after cohort inclusion (Table 6) or within 4 or 7 days after sample collection (Table 7).

[0055] [Table 6] Table 6. Performance (AUC and 95% confidence interval, CI) of measuring CX3CR1 expression combined with another biomarker (multivariate analysis), measured at D3 / 4 or D5 / 7 after cohort inclusion, for predicting the occurrence of healthcare-associated infection before day 15 after cohort inclusion

[0056] [Table 7] Table 7. Performance (AUC and 95% confidence interval, CI) of measuring CX3CR1 expression in combination with another biomarker (multivariate analysis) for predicting the occurrence of healthcare-associated infection within 4 or 7 days after sample collection

Claims

1. An in vitro or ex vivo method for determining the risk of developing a healthcare-associated infection in a patient, comprising measuring the expression of CX3CR1 in a biological sample from the patient.

2. 10. The method of claim 1, wherein the patient is a patient in a medical facility and the method makes it possible to determine the risk of developing a nosocomial infection in the patient.

3. 3. The method according to claim 1 or 2, wherein the patient is a patient in a hospital, preferably an emergency unit, a resuscitation unit, an intensive care unit or a continuing care unit, more preferably a sepsis patient, a burn patient, a trauma patient or a surgery patient.

4. 4. The method according to any one of claims 1 to 3, characterized in that the method makes it possible to determine the risk of developing a healthcare-associated infection in the patient within 15 days of an immunoinflammatory challenge and / or within 7 days after the date of collection of the biological sample.

5. 5. The method according to claim 1, wherein the biological sample is a blood sample.

6. The method according to any one of claims 1 to 5, wherein the biological sample is a whole blood sample.

7. 7. The method of any one of claims 1 to 6, further comprising measuring the expression of another gene in the biological sample from the patient selected from the list consisting of ADGRE3, BTLA, CD3D, CD74, CD274, CTLA4, HP, ICOS, IFNG, IL1RN, IL6, IL7R, IL10, IL15, MDC1, PDCD1, S100A9, TDRD9 and ZAP70.

8. The method according to any one of claims 1 to 7, wherein the expression is measured at the mRNA or protein level.

9. The method according to any one of claims 1 to 8, wherein the expression is measured at the mRNA level.

10. The method according to any one of claims 1 to 9, characterized in that the expression is measured by RT-PCR, preferably RT-qPCR.

11. 10. The method of any one of claims 1 to 9, wherein the expression is measured by sequencing.

12. 10. The method of any one of claims 1 to 9, wherein the expression is measured by hybridization.

13. The method of any one of claims 9 to 12, wherein the expression is normalized to the expression of one or more housekeeping genes.

14. CX3CR1, and another selected from the list consisting of ADGRE3, BTLA, CD3D, CD74, CD274, CTLA4, HP, IFNG, IL1RN, IL6, IL7R, IL10, MDC1, PDCD1, S100A9, TDRD9 and ZAP70. A kit comprising gene amplification means and / or expression detection means, characterized in that all of the amplification and / or detection means of the kit enable the detection and / or amplification of a total of 100 or less biomarkers.

15. CX3CR1 amplification means and / or expression detection means, or of a kit comprising such amplification means and / or detection means, Use to determine the risk of developing a healthcare-associated infection in a patient.

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