Method for diagnosis and/or prognosis of a septic syndrome
11821038 · 2023-11-21
Assignee
Inventors
Cpc classification
C12Q1/6883
CHEMISTRY; METALLURGY
International classification
Abstract
Disclosed herein is a method for the diagnosis/prognosis of a septic syndrome based on a biological sample from a patient. The method may include extracting biological material the biological sample, contacting the biological material with at least one specific reagent that is selected from specific reagents for the target genes having a nucleic acid sequence of any one of SEQ ID NOs: 1 to 28, and determining the expression of at least one of the target genes.
Claims
1. A method comprising: obtaining a blood sample from a patient having a septic syndrome; and measuring expression levels of one or more target genes in the blood sample using at least one specific reagent, including measuring overexpression of SEQ ID NO: 1 relative to a reference value in the blood sample; wherein no more than 10,000 specific reagents are used to measure the expression levels of the one or more target genes in the blood sample.
2. The method according to claim 1, further comprising extracting biological material from the blood sample.
3. The method according to claim 2, wherein the overexpression is measured by contacting the biological material with a reagent specific for an expression product of SEQ ID NO: 1.
4. The method according to claim 3, further comprising detecting hybridization of the specific reagent to the expression product.
5. The method according to claim 3, wherein the specific reagent comprises a hybridization probe.
6. The method according to claim 5, wherein the hybridization probe is immobilized on a substrate.
7. The method according to claim 2, wherein the biological material comprises nucleic acids.
8. The method according to claim 1, further comprising measuring expression levels of target genes respectively comprising the nucleic acid sequences of SEQ ID NOs: 3, 7, 9-15, and 17-28 in the blood sample.
9. The method according to claim 8, wherein the expression levels of 22 target genes in the blood sample are measured.
10. The method according to claim 1, wherein the expression levels of 28 target genes in the blood sample are measured.
11. The method according to claim 1, further comprising measuring expression levels of target genes respectively comprising the nucleic acid sequences of SEQ ID NOs: 2, 4-8, 11, and 16 in the blood sample.
12. The method according to claim 1, further comprising measuring expression levels of target genes respectively comprising the nucleic acid sequences of SEQ ID NOs: 2-28 in the blood sample.
13. The method according to claim 1, wherein no more than 50 specific reagents are used to measure expression levels of the one or more target genes in the blood sample.
14. The method according to claim 1, further comprising monitoring the expression level of SEQ ID NO: 1 over time.
15. The method according to claim 1, wherein the reference value is a predetermined value indicative of a poor prognosis for septic syndrome.
16. The method according to claim 1, further comprising treating the patient with an antibiotic and/or activated protein C.
17. The method according to claim 1, wherein the overexpression is measured via an amplification method comprising the use of a first primer consisting of SEQ ID NO: 29 and a second primer consisting of SEQ ID NO: 30.
Description
(1) The attached figures are given by way of explanatory example and are in no way limiting in nature. It will make it possible to understand the invention more completely.
(2)
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(5) The following examples are given by way of illustration and are in no way limiting in nature. They will make it possible to understand the invention more fully.
Example 1: Search for an Expression Profile for the Diagnosis/Prognosis of a Septic Syndrome
(6) Characteristics of the biological samples: The study was carried out on patients having developed a septic syndrome, and admitted into the surgical or medical intensive care unit of the Lyon-Sud hospital center. In order to be included in the study, the patients had to present the following criteria: over 18 years of age; presence of a septic shock according to the consensus conference previously described; absence of comorbidity (metastatic cancer, malignant hemopathy, type I diabetes, chronic hepatic pathology, chronic renal insufficiency, AIDS). Since the objective of the study was to study the late mortality induced by a septic shock, the patients who died over the first 48 hours of the syndrome were excluded from the study. The treatment for all the patients included was similar.
(7) Taking the day of the first administration of catecholamine to be D1 of the septic shock, each patient was monitored for a maximum period of 28 days. On the basis of the mortality observed over this period, a group of 10 patients (PP) and a group of 21 patients (GP) were studied. Subsequently, the gene panel according to the invention was validated blind using two groups of patients recruited on the basis of the same criteria: one group of 3 PP patients and one group of 4 GP patients. The genomic analyses were carried out using samples obtained between D2 and D4. The demographic characteristics of the entire cohort are presented in the following table:
(8) TABLE-US-00002 GP PP Train Test Train Test Total n = 21 (%) n = 4 (%) n = 10 (%) n=3 (%) n = 38 (%) P.sup.a Men 13 (62) 2 (50) 7 (70) 1 (33) 23 (61) 0.930 Women 8 (38) 2 (50) 3 (30) 2 (67) 15 (39) Age (years).sup.b 67 (49-71) 71 (66-75) 68 (57-79) 78 (63-80) 67 (54-78) 0.371 SAPS II at admission.sup.b 48 (40-55) 45 (37-52) 61 (59-73) 61 (60-72) 55 (42-61) <0.001 Duration of hospitalization in ICU..sup.b 12 (10-26) 32 (28-34) 9 (8-14) 4 (4-10) 12 (9-25) 0.013 COPD 1 (5) 2 (50) 3 (30) 1 (33) 7 (18) 0.203 MacCabe and 0 7 (33) 1 (25) 0 0 8 (21) 0.045 Jackson criteria 1 9 (43) 2 (50) 9 (90) 1 (33) 21 (55) 2 5 (24) 1 (25) 0 2 (67) 8 (21) 3 0 0 1 (10) 0 1 (3) Microbiologically documented 15 (71) 4 (100) 7 (70) 3 (100) 29 (76) >0.999 diagnosis In Gram(−) Bacillus 8 (38) 1 (25) 3 (30) 3 (100) 15 (39) 0.950 In Gram(+) Cocci 7 (33) 1 (25) 5 (50) 1 (33) 14 (37) Fungal 6 (29) 1 (25) 3 (30) 1 (33) 11 (29) Type of infection Community- 7 (33) 4 (100) 5 (50) 1 (33) 17 (45) 0.900 acquired 14 (67) 0 (0) 5 (50) 2 (67) 21 (55) Hospital-acquired Site of the Pulmonary 6 (29) 2 (50) 8 (80) 1 (33) 17 (45) 0.061 infection Abdominal 12 (57) 1 (25) 2 (20) 2 (67) 17 (45) Others 3 (14) 1 (25) 0 (0 ) 0 (0 ) 4 (11) .sup.acomparison between the overall population of survivors (n = 25) and non-survivors (n = 13) .sup.bMedian (Q1-Q3) COPD: chronic obstructive pulmonary disease
(9) Extraction of the Biological Material (Total RNA) from the Biological Sample:
(10) The samples were collected directly in PAXGene™ Blood RNA tubes (PreAnalytix, Frankin Lakes, USA). After the step consisting in taking the blood sample and in order to obtain total lysis of the cells, the tubes were left at ambient temperature for 4 h and then stored at −20° C. until the extraction of the biological material. More specifically, in this protocol, the total RNA was extracted using the PAXGene Blood RNA® kits (PreAnalytix) while observing the manufacturer's recommendations. Briefly, the tubes were centrifuged (10 min, 3000 g) in order to obtain a pellet of nucleic acid. This pellet was washed and taken up in a buffer containing proteinase K required for digestion of the proteins (10 min at 55° C.). A further centrifugation (5 min, 19 000 g) was carried out in order to remove the cell debris, and ethanol was added in order to optimize the nucleic acid binding conditions. The total RNA was specifically bound to PAXGene RNA spin columns and, before elution of the latter, a digestion of the contaminating DNA was carried out using the RNAse-free DNAse set (Qiagen Ltd, Crawley, UK). The quality of the total RNA was analyzed with the AGILENT 2100 bioanalyzer (Agilent Technologies, Waldbronn, Germany). The total RNA comprises the transfer RNAs, the messenger RNAs (mRNAs) and the ribosomal RNAs.
(11) Synthesis of cDNA, obtaining of cRNAs, labeling of cRNAs and quantification: In order to analyze the expression of the target genes according to the invention, the complementary DNAs (cDNAs) of the mRNAs contained in the total RNA as purified above were obtained from 5 μg of total RNA, using 400 units of the SuperScriptII reverse transcription enzyme (Invitrogen) and 100 pmol of poly-T primer containing the T7 promoter (T7-oligo(dT)24-primer, Proligo, Paris, France). The cDNAs thus obtained were then extracted with phenol/chloroform and precipitated with ammonium acetate and ethanol and redissolved in 24 μl of DEPC water. A 20 μl volume of this purified solution of cDNA was subsequently subjected to in vitro transcription using a T7 RNA polymerase which specifically recognizes the promoter of the T7 polymerase as mentioned above. This transcription makes it possible to obtain the cRNA of the cDNA. This transcription was carried out using a Bioarray High Yield RNA Transcript Labeling Kit (Enzo Diagnostics, Farmingdale, NY), which not only makes it possible to obtain the cRNA, but also allows the incorporation of biotinylated cytidine and uridine bases during the synthesis of the cRNA.
(12) The purified cRNAs were subsequently quantified by spectrophotometry, and the cRNA solution was adjusted to a concentration of 1 μg/μl of cRNA. The step consisting of cleavage of these cRNAs was subsequently carried out at 94° C. for 35 min, using a fragmentation buffer (40 mM of tris acetate, pH 8.1, 100 mM of potassium acetate, 30 mM of magnesium acetate) in order to bring about the hydrolysis of the cRNAs and to obtain fragments of 35 to 200 bp. The success of such a fragmentation was verified by 1.5% agarose gel electrophoresis.
(13) Demonstration of a differential expression profile between the PP and GP patients: For this, 20 μg of fragmented cRNAs derived from each sample were added to a hybridization buffer (Affymetrix) and 200 μl of this solution were brought into contact for 16 h at 45° C. on an expression chip (Human Genome U133A GeneChip® (Affymetrix)), which comprises 22 283 groups of probes representing approximately 14 500 genes according to the Affymetrix protocol as described on the Affymetrix internet site. In order to record the best hybridization and washing performance levels, RNAs described as “control” RNAs, that were biotinylated (bioB, bioC, bioD and cre), and oligonucleotides (oligo B2) were also included in the hybridization buffer. After the hybridization step, the solution of cRNA biotinylated and hybridized on the chip was visualized using a solution of streptavidin-phycoerythrin and the signal was amplified using an anti-streptavidin antibody. The hybridization was carried out in a “GeneChip hybridization oven” (Affymetrix), and the Euk GE-WS2V4 protocol of the Affymetrix protocol was followed. The washing and visualization steps were carried out on a “Fluidics Station 450” (Affymetrix). Each U133A chip was subsequently analyzed on an Agilent G2500A GeneArray Scanner at a resolution of 3 microns in order to pinpoint the areas hybridized on the chip. This scanner makes it possible to detect the signal emitted by the fluorescent molecules after excitation with an argon laser using the epifluorescence microscope technique. A signal proportional to the amount of cRNAs bound is thus obtained for each position. The signal was subsequently analyzed using the Microarray Suite 5.0 software (MAS5.0, Affymetrix). In order to prevent the variations obtained by using various chips, an overall normalization approach was carried out using the MAS5.0 software (Affymetrix), which, by virtue of a statistical algorithm, makes it possible to define whether or not a gene was expressed. In order to be able to compare the chips with one another, the raw data (“.CELL” file) were processed by means of a quantile normalization step using the “Affy” package of the “R” software (Gautier, L. et al., Bioinformatics (2004), p. 30′7-315). Each gene represented on the U133A chip was covered by 11 pairs of probes of oligonucleotides. The term “pair of probes” is intended to mean a first probe which hybridized perfectly (reference is then made to PM or perfect match probes) with one of the cRNAs derived from a target gene, and a second probe, identical to the first probe with the exception of a mismatch (reference is then made to MM or mismatched probe) at the center of the probe. Each MM probe was used to estimate the background noise corresponding to a hybridization between two nucleotide fragments of non-complementary sequence (Affymetrix technical note “Statistical Algorithms Reference Guide”; Lipshutz, et al (1999) Nat. Genet. 1 Suppl., 20-24). The 38 samples of the study showed an average of 38.1±4.2% of expressed genes.
(14) The analysis of the expression data was carried out using the Microsoft Excel software, the Spotfire decision site for functional genomics V7.1 software (Spotfire AB, Gothenburg, Sweden), and a statistical algorithm: the genetic algorithm (Gautier, L. et al., Bioinformatics (2004), p. 30′7-315; Ooi, C. H. and Tan, P. Bioinformatics (2003), p. 3′7-44). Based on the 22 283 groups of probes, representing approximately 14 500 genes, of the chip, the inventors duly selected the relevant genes that made it possible to differentiate between the PP patients and the GP patients.
(15) For this, a first step consisted in excluding the genes exhibiting a level of expression comparable between all the groups of patients. Four steps were carried out: the genes not expressed in all the patients were excluded (MAS5.0 software). the genes for which the fluorescence median was less than 30 in the two groups were excluded; the genes that were not expressed in at least 30% of the patients in one of the two groups were excluded; the genes for which the ratio of the expression medians between the GP and PP patients was between 0.77 and 1.3 were excluded.
Subsequent to the application of these filters, a group of 2216 groups of probes was selected and was used as a working base for a multiparametric analysis with the Genetic Algorithm.
(16) Results obtained: a list of 28 genes was identified. The increase or the decrease in expression of each of these genes, observed in the PP patients compared with the BP patients, is indicated in table 2.
(17) TABLE-US-00003 TABLE 2 List of 28 genes differentially expressed in PP and GP patients Abbreviated Expression in SEQ ID N° Gene name name PP versus GP 1 chemokine (C-X3-C motif) receptor 1 CX3CR1 Increased* 2 T cell receptor delta diversity 3 TRDD3 Increased.sup.£ 3 KIAA0882 protein KIAA0882 Increased 4 T-cell lymphoma invasion and metastasis 1 TIAM1 Increased.sup.£ 5 Interleukin 1, beta IL1B Increased* 6 Carbonyl reductase 1 CBR1 Increased.sup.£ 7 TIR domain containing molecule 1 TRIF Increased* 8 FYN tyrosine kinase protooncogene FYN Increased.sup.£ 9 Heparanase HPSE Increased 10 SRY (Sex determining region Y) box 4 SOX4 Increased.sup.£ 11 Interleukin 2 receptor, beta IL2RB Increased* 12 Raft-linking protein RAFTLIN Increased 13 CGI-40 protein Homo sapiens SID1 transmembrane CGI-40 SIDT2 Increased family, member 2 14 glucose-6-phosphatase catalytic subunit 3 G6PC3 Increased 15 Mannosidase alpha, class 1A member 2 MAN1A2 Increased 16 Myeloid differentiation primary response gene (88) MYD88 Increased* 17 Ribosomal protein L6 RPL6 Increased 18 Ribosomal protein L10a RPL10a Increased 19 sin3-associated polypeptide, 30kDa SAP30 Decreased 20 Mitogen activated protein kinase-activated MAPKAPK2 Decreased protein kinase 2 21 Presenlin enhancer 2 PEN2 Decreased 22 Hypothetical protein LOC55924 LOC55924 Decreased 23 Solute carrier family 39 (zinc transporter member 7) SLC39A7 Decreased.sup.£ 24 Glutathione peroxidase 3 (plasma) GPX3 Decreased.sup.£ 25 Hemochromatosis HFE Decreased 26 Transcriptional activator of the cfos promoter CROC4 Decreased 27 peroxisomal biogenesis factor 6 PEX6 Decreased 28 Huntingtin interacting protein Decreased
(18) The indication of an * and £ indicate respectively a statistically different difference between the two groups according to a T test with Bonferroni or Benjamini and Hochberg correction, respectively. This indicates that these genes taken in isolation are very relevant in the diagnosis/prognosis of a septic syndrome.
(19) Validation by Quantitative RT-PCR
(20) In order to confirm these results by means of another molecular biology technique, certain genes were assayed by quantitative RT-PCR. Briefly, a reverse transcription (RT) reaction was carried out in a final volume of 20 μl. The total RNA (1 μg) was mixed with 1 μl of polyT at 50 μM and 1 μl of dNTP mix (ThermoScript™ RT-PCR system, Invitrogen), and then incubated for 5 min at 65° C. After cooling in ice, the solution was mixed with 4 μl of 5×cDNA synthesis buffer, 1 μl of RNAse out (40 U/μ1), 1 μl of DEPC-treated water and 1 μl of Thermoscript RT (15 U/μ1), all these products being derived from the ThermoScript™ RT-PCR system (Invitrogen). The reverse transcription was carried out for 1 h at 50° C. and then stopped by incubation at 85° C. for 5 min. To finish, each cDNA solution was diluted to 1/10 in DEPC water. For each of the genes of interest, a standard was prepared by means of a PCR (polymerase chain reaction) amplification carried out until saturation. The amplicons obtained were purified (PCR purification kit, Qiagen Ltd) and the presence of a unique amplicon was verified by agarose gel electrophoresis and ethidium bromide staining. The standard consisting of the peptidylpropyl isomerase B (PPIB) «housekeeping» gene encoding cycophilin B was obtained from Search-LC (Heidelberg, Germany).
(21) Analysis of mRNA Expression by Real Time PCR
(22) The mRNAs of the target genes of SEQ ID Nos 1, 5, 11 and 16 were quantified by real time quantitative PCR using the LightCycler™ (Roche). The PCR reactions were carried out using the Fast-Start™ DNA Master SYBR Green I real-time PCR kit (Roche Molecular Biochemicals). Each PCR was carried out in a final volume of 20 μl containing 1 μl of LC-Fast Start Reaction Mix SYBR Green I, 1 μl of LC-Fast Start DNA Master SYBR Green I/Enzyme (including the Taq DNA polymerase, the reaction buffer and a deoxynucleotide triphosphate mix), MgCl.sub.2 (final concentration of 3 mM), the sense and antisense primers (final concentration of 0.5 μM), and 10 μl of cDNA solution. After a denaturation step of 10 min at 95° C., the amplification was carried out by means of 40 cycles of a “touch-down” PCR protocol (10 s at 95° C., 10 s of hybridization at 68-58° C., followed by an extension of 16 s at 72° C.). At the end of each cycle, the fluorescence emitted by the SYBR Green was measured.
(23) In order to confirm the specificity of the amplification, the PCR products were systematically subjected to a melting curve analysis (LightCycler™—Roche). For this, the PCR products were treated with an increase in temperature of from 58 to 98° C., with an increase of 0.1° C./s. For each PCR product, a single peak was obtained in the analysis of the curve, characterized by a specific melting point.
(24) The combinations of primers required for the quantification of the PPIB housekeeping gene and IL-1β gene (SEQ ID No. 5) were obtained from Search-LC (Heidelberg, Germany). For PPIB, the Genbank accession no. was M60857 and the 105-338 region was amplified. For IL-113, the Genbank accession no. was M15330 and the 438-642 region was amplified. The pairs of primers used to quantitatively determine the target genes of SEQ ID Nos 1, 11 and 16, the Genbank sequence used as reference and the position of the amplicons are described in the table below.
(25) TABLE-US-00004 TARGET GENE OF SEQ ID No. ′ amplicon 1 Sense primer 5′-->3′ SEQ ID No. 29 TGACTGGCAGATCCAGAGGTT 164 bases Antisense primer 5′-->3 SEQ ID No. 30 GTAGAATATGGACAGGAACAC 11 Sense primer 5′-->3′ SEQ ID No. 31 CCTGAAGTGTAACACCCCAGA 162 bases Antisense primer 5′-->3 SEQ ID No. 32 TCCCTCTCCAGCACTTCTAGT 16 Sense primer 5′-->3′ SEQ ID No. 33 TGCTGGAGCTGGGACCCAGCATTGAGGAGGA 280 bases Antisense primer 5′-->3 SEQ ID No. 34 TCAGACACACACAACTTCAGTCGATAG
(26) The amount of target mRNA relative to the amount of mRNA of the PPIB housekeeping gene was analyzed by the relative quantification technique with the LightCycler Relative Quantification Software (Roche Molecular Biochemicals). The “Second Derivative Maximum Method” of the LightCycler™ (Roche) was used to automatically determine the crossing point (Cp) for each sample. The value of the Cp was defined as the number of cycles for which the fluorescence was significantly different than the background noise.
(27) Five serial 10-fold dilutions were carried out in quadruplicate with each standard in order to generate a standard curve expressing the Cp as a function of the logarithm of the number of copies. The standard dilutions were optimized so that the standard curve covered the expected level of expression for the target gene and the housekeeping gene. The relative standard curves describing the PCR efficiency for the target gene and the housekeeping gene were generated and used to perform a quantification with the LightCycler Relative Quantification Software (Roche Molecular Biochemicals).
(28) The results obtained for the quantitative determination of the mRNAs of the target genes of SEQ ID Nos 1, 5, 11 and 16 by quantitative RT-PCR are given in table 3 below. The results correspond to 25 samples (8 PP and 17 GP). The correlation of the results obtained, firstly, with the biochip and, secondly, with the quantitative RT-PCR technique was established by means of Spearman's correlation test.
(29) TABLE-US-00005 TABLE 3 Comparison of the levels of expression of 4 genes between Affymetrix and quantitative RT-PCR Spearman Spearman Abbreviated median median median median correlation test degree of gene Affymetrix Affymetrix RT-PCR RT-PCR coefficient: significance: name GP PP GP PP r p CX3CR1 582.965 92.995 0.04295 0.00663 0.94 <0.001 IL-1B 227.64 113.4 0.329 0.18 0.83 <0.001 IL-2RB 204.86 131.965 0.00075 0.00024 0.76 <0.001 MyD88 2644.03 1986.315 0.0351 0.0294 0.56 <0.01
(30) For the 4 genes analyzed, a significant correlation was observed between the Affymetrix results and the quantitative RT-PCR results, confirming the relevance of the genes according to the invention.
(31) By following the same protocol as that described in the above paragraphs, the CX3CR1 mRNAs were quantified from blood samples taken from 50 patients in septic shock (19 PP and 21 GP). A blood sample was obtained during the first 72 hours after the beginning of the shock, and then a second sample was obtained later on in the course of the syndrome. The level of expression of CX3CR1 was normalized to that of the PPIB housekeeping gene. The results are given in
(32) The level of expression of the CX3CR1 mRNA showed a significant decrease over time in the PP patients. The results are given in
(33) It is therefore particularly advantageous to follow the expression of the CX3CR1 mRNA over time in order to confirm this poor prognosis.
(34) Analysis of the Expression of a Panel of Genes
(35) The inventors also demonstrated that the simultaneous analysis of the expression of several genes was very relevant for discriminating between GP and PP patients.
(36) The inventors thus demonstrated that the simultaneous analysis of the expression of the 28 genes described above was very relevant for discriminating between the two GP and PP groups.
(37) The results are given in
(38) In addition, the inventors demonstrated that the simultaneous analysis of the expression of the genes of SEQ ID Nos 1, 3, 7, 9-15 and 17-28, among the 28 described above, was also particularly relevant for discriminating between the two GP and PP groups. The results are given in
(39) Among the 28 genes described above, each of the 9 genes of SEQ ID Nos 1, 2, 4-8, 11 and 16 makes it possible to discriminate between the two groups of patients. Table 4 represents the p value calculated using the T tet with Bonferroni or Benjamini and Hochberg correction. All these genes were overexpressed in the GP compared with the PP.
(40) TABLE-US-00006 TABLE 4 Genes for discriminating between the two groups of patients. Gene Bonferroni BHFDR Fold Gene name Symbol correction correction change Chemokine (C-X3-C motif) receptor 1 CX3CR1 6.3E−05 6.3E−05 8.33 T cell receptor delta diversity 3 TRDD3 >0.05 4.4E−02 4.00 T-cell lymphoma invasion and metastasis 1 TIAM1 >0.05 2.7E−02 2.08 Interleukin 1, beta IL1B 4.9E−02 9.7E−03 2.08 Carbonyl reductase 1 CBR1 >0.05 2.8E−02 1.89 TIR domain containing adaptor TRIF 5.3E−04 2.6E−04 1.72 inducing interferon-beta FYN tyrosine kinase protooncogene FYN >0.05 2.7E−02 1.67 Interleukin 2 receptor, beta IL2RB 4.3E−02 9.7E−03 1.52 Myeloid differentiation primary MYD88 3.5E−02 9.7E−03 1.37 response gene (88)