EP1799848A1

EP1799848A1 - Method for differentiating between the non-infectious and infectious causes of multiple organ failure

Info

Publication number: EP1799848A1
Application number: EP05775921A
Authority: EP
Inventors: Stefan Russwurm; Konrad Reinhart
Original assignee: SIRS Lab GmbH
Current assignee: SIRS Lab GmbH
Priority date: 2004-10-13
Filing date: 2005-08-18
Publication date: 2007-06-27
Also published as: JP5139804B2; US8476200B2; WO2006042581A1; US20090075831A1; EP2011887A3; EP2218795A1; EP2011887A2; DE102004049897B4; EP2218795B1; DE102004049897A1; JP2008516588A; ES2365978T3; ATE514795T1; EP2011887B1

Abstract

Novel use of a genetic profile expression in vitro drawn from a sample of patient tissue to determine whether a multi-organ failure has an infectious or non-infectious case.

Description

description

Method for distinguishing between non-infectious and infectious causes of multiorverse versa.

The present invention relates to the use of gene expression profiles obtained in vitro from a patient sample for distinguishing between non-infectious and infectious causes of a multiorgan failure according to claim 1, a method for in vitro measurement of such gene expression profiles according to claim 11 and the use of the gene expression profiles and / or of those therefor used probes for switching off and / or activity modification of target genes and / or for determining the gene activity for the screening of drugs against non-infectious / infectious multi-organ failure and / or for the evaluation of the therapeutic effects of drugs against non-infectious / infectious multi-organ failure, according to claim 25.

Furthermore, the present invention relates to new possibilities of distinguishing between non-infectious and infectious causes of multiple organ failure of patients, which can be derived from experimentally verified findings in connection with the occurrence of changes in gene activities (transcription) in patients with multi-organ failure.

Despite advances in pathophysiological understanding and supportive treatment, multiorgan dysfunction syndrome (MODS) or multiple organ failure (MOV) is the leading cause of death in ICU patients and continues to grow worldwide. The consequences of this development are not only significant for the individual patient, but have a huge impact on the costs of healthcare and medical advances in many areas of medicine.

Multi-organ failure refers to the simultaneous or rapid succession of two or more vital failures Organ systems. Multi-organ dysfunction syndrome (MODS) precedes MOV as initial organ failure [1]. One speaks today of multi-organ failure when two or more organs simultaneously or sequentially malfunction, with a chronic persistent organ failure is ruled out [2], the prognosis of MOV is closely related to the number of involved organ systems together. Mortality is 22% in the first 24 hours of an organ failure and 41% after 7 days. In the case of failure of three organ systems mortality increases to 80% on the first day and to 100% after 4 days [3].

For the clinical severity classification of MODS and MOV, the multiple organ failure score (MOF score) of GORIS et al. [4] or, alternatively, the Sepsis-related Organ Failure Assessment (SOFA) score used [5]. The MOF score allows a quick and clinically simple classification of organ function in three levels. A MOF score> 4 is regularly referred to in the clinical literature as MOV [6]. The SOFA score is a point system that evaluates the rapid clinical assessment of function, in four severity levels, in each of the following organ systems: respiratory (lung), coagulation, liver, cardiovascular, central nervous system and kidney.

The MOV runs clinically in three phases [7]:

1. Organ in shock: The triggering pathophysiological mechanism is a perfusion deficit of various genesis. This happens within hours and leaves no lasting damage. 2. Orqandvsfunktion: A persistent perfusion deficit within the next few days leads to the development of a systemic inflammatory response syndrome (SIRS, classified according to [8]) with local edema and cell damage. This phase is called multi-organ dysfunction syndrome (MODS). 3. Qrqanversaαen: The persisting perfusion deficit leads to stasis in the splanchnic area, which leads to the superinfection and translocation of endotoxins from the intestine. This leads to a potentiation of the clinical symptoms and to the full picture of sepsis. The organ dysfunction becomes an organ failure. MODS and MOV are syndromes with a complicated pathophysiology. To date, the exact molecular causes of the genesis and complexity of the immunological-infilatory host response to severe infection and trauma, which can lead to the induction of S (RS) and associated cardiocirculatory effects, are poorly understood [9].

MODS and MOV can be both infectiological and non-infectiological. MODS and MOV are regularly a clinically important complication in patients with sepsis after traumatic shock

Patients after surgery using the heart-lung machine, after

Organ transplants u.v.m. on (Figure 1). An important

The pathomechanism for the development of MODS and MOV is the development of a systemic inflammatory syndrome (SIRS, [8]). The as part of a

SIRS initiated pathophysiological processes not only involve all

Components of the nrrnrrmnsystems, but affect the cardio-circulatory system at all levels and are not limited to myocardial depression and vasodilation. The cardiocirculatory changes, especially at the level of the microcirculation form the final common pathway and result in a tissue hypoxia, which ^a) applies s important cofactor in the pathogenesis of multiple organ failure.

Figure 1 exemplifies the most important mechanisms of the formation of MODS and MOV [1O] from today's point of view: an overactive

Immune system seems to play a central role in the development of multi-organ failure. The endothelium secretes by secretion

Cytokines and by mediating leukocyte adhesion a central

Key role. In the endothelial cells, signal transduction cascades are activated, which ultimately lead to the expression and activation of

Lead to transcription factors.

The still incomplete knowledge about the processes in the early phase of the MODS and MOV is the reason why it is still not sensitive / specific Diagnosis, which can discriminate between infectious and non-infectious causes, exists. Novel biomarkers and diagnostics, now also at the gene expression level, can provide the diagnostic information essential for the early detection of multiorgan failure as well as the distinction between infectious and non-infectious causes of MODS and MOV and, moreover, make an important contribution to the elucidation of the pathophysiological mechanisms of systemic inflammation.

The clinically commonly used early symptoms such as fever, leukocytosis, tachycardia, and tachypnoea are completely nonspecific in the diagnosis of MODS or MOV, as well as in distinguishing between infectious and non-infectious causes of MODS and MOV. Parameters that detect early microcirculation disorders, such as changes in the pH of Drammukosa [11] and lactate levels in the capillary bed [12,13], the occurrence of respiratory failure, the cause is not in the lungs [2], the increase in leukocyte etastasis [14,15], the level of neopterin levels [16], the activation of polymorphonuclear leukocytes, and the level of IL-6 [17] are conditional as early parameters for the later development of MODS and MOV, but can not contribute to distinguish between infectious and non-infectious causes of a MODS and MOV. Thus, there is an urgent need for new diagnostic methods which are intended to improve the ability of those skilled in the art to early distinguish non-infectious from infectious MODS or MOV, and to deduce responses to specific treatment responses.

Exactly the distinction between infectious and non-infectious causes of a MOD and MOV is of highest medical importance, since by means of such a distinction, for example, antibiotics can be used more specifically, which in addition to avoiding side effects due to the non-specific use of antibiotics also contributes to a significant cost savings. Similarly, the patient can be very stressful as well as time and personnel-intensive diagnostic measures (eg transport to CT / MRI) to identify the respective site of infection, The implementation of extensive microbiological methods (eg the examination of blood cultures, which are also associated with the decrease of large amounts of blood) but also the risky replacement of all connected with the patient plastic materials such as venous catheters etc. in the presence of a non-infectious MODS or MOV are avoided. Vice versa, the rapid identification of infectious causes of a MODS or MOV can ensure the timely initiation of such measures and thus the reduction of mortality.

Technological advances, particularly the development of microarray technology, now enable the skilled artisan to simultaneously compare 10,000 or more genes and their gene products. The application of such microarray technologies can now provide information on the status of health, regulatory mechanisms, biochemical interactions and signal transmission networks. Improving understanding of how an organism responds to infections should facilitate the development of enhanced detection, diagnosis and treatment modalities for sepsis disorders.

Microarrays are derived from "Southern blotting" [19], which is the first approach to immobilize DNA molecules in a spatially responsive manner on a solid matrix.The first microarrays consisted of DNA fragments, often of unknown sequence, and were spiked onto a porous membrane (usually nylon). Routine use was made of cDNA, genomic DNA or plasmid libraries, and the hybridized material was labeled with a radioactive group [20-22].

Recently, it has allowed the use of glass as a substrate and fluorescence for detection along with the development of new technologies for synthesis and application of the nucleic acids at very high densities, miniaturizing the nucleic acid arrays while increasing experimental throughput and information content [23]. 25]. Furthermore, it is known from WO 03/002763 that the measurement of gene expression by means of microarrays can in principle be used for the diagnosis of sepsis and sepsis-like conditions.

A rationale for the applicability of microarray technology was first provided by clinical research in the field of cancer research. Here, expression profiles have shown their usefulness in identifying activities of individual genes or gene groups that correlate with particular clinical phenotypes [26]. By analyzing many samples from individuals with or without acute leukemia or diffuse B cell lymphomas, gene expression markers (RNA) were found and subsequently applied to the clinically relevant classification of these cancers [26, 27]. Golub et al. have found that reliable predictions can not be made on the basis of any single gene, but that predictions based on altering the transcription of 53 genes (selected from over 6,000 genes represented on the arrays) are very accurate [26 ].

Alisadeh et al. [27] investigated large B-cell lymphomas (DLBCL). The authors developed expression profiles with a "lymphochip", a microarray, the

18,000 clones of complementary DNA were carried and developed to monitor genes involved in normal and abnormal lymphocyte development. Using cluster analysis, they were able to

Divide DLBCL into two categories that showed significant differences in patient survival rates. The gene expression profiles of these subgroups corresponded to two significant stages of

Cell differentiation.

The general applicability of gene expression profiles which can be obtained for example by means of the microarray technique for the diagnosis of SIRS, generalized inflammatory inflammations, sepsis and severe sepsis is described in the unpublished German patent applications of the present applicant DE 103 40 395.7, DE 103 36 511.7, DE 103 150 31.5 and 10 2004 009 952.9, to which reference is hereby made in its entirety.

By Feezor et al. [28] it is known that the gene activities of patients, who due to their surgical treatment a SIRS with multi-organ

Dysfunction Syndrome (MODS), compared to patients who developed SIRS without MODS under the same operative conditions. However, these investigations can not be said about the

To distinguish non-infectious MOV against infectious MOV, as no infection was detected in the patients.

The use of gene expression profiles to distinguish between non-infectious MOV and infectious MOV has not been described.

The starting point for the invention disclosed in the present patent application is the recognition that the gene activities of patients with non-infectious MOV differ from gene activities of patients with infectious MOV. These differences in gene activity let it therefore differ based on the gene expression between non-infectious and infectious MOV to _^. This distinction is not possible with the clinical parameters used to date for diagnosis, but is very significant for the initiation of specialized intensive care therapy.

The present invention is therefore based on the object of distinguishing between a non-infectious MOV and an infectious MOV by the use of gene activity markers.

This object is solved by the features of claims 1, 11 and 25.

In particular, the present invention relates to the use of gene expression profiles obtained in vitro from a patient sample to distinguish between non-infectious and infectious causes of multi-organ failure. Furthermore, the present invention provides the therapy-accompanying course assessment of patients who are suffering from non-infectious and infectious causes of multi-organ failure.

The present invention is also useful as an inclusion or exclusion criterion of patients suffering from non-infectious or infectious causes of multi-organ failure in Phase 2-4 clinical trials.

A preferred embodiment of the invention lies in the generation of gene activity data for the electronic further processing and for the production of software for the description of the individual prognosis of a sepsis patient, for diagnostic purposes and / or patient data management systems.

The present invention may also be used to prepare "in silico" expert systems and / or for "in silico" modeling of more cellular signal transduction pathways.

To create the gene expression profile according to the present invention, a plurality of specific genes and / or gene fragments ^"are used, which are selected from the group consisting of SEQ ID No. 1 to SEQ ID No. 1 297, as well as gene fragments thereof with at least 5- 2000 , preferably 20-200, more preferably 20-80 nucleotides.

These sequences having the sequence ID: 1 to the sequence ID: 1297 are encompassed within the scope of the present invention and are disclosed in detail in the attached, 1297 sequences, sequence listing, which is thus part of the description of the present invention, and thus is also part of the disclosure of the invention. This sequence protocol also includes an assignment of the individual sequences with the sequence ID: 1 to the sequence ID: 1297 to their GenBank Accession No. (Internet access via http://www.ncbi.nlm.nih.gov/). Moreover, the present invention relates to the use of gene expression profiles obtained in vitro from a patient sample and / or of the probes used therefor, which are selected from the group consisting of SEQ ID no. 1 to SEQ ID NO. 1297 and gene fragments thereof with at least 5-2000, preferably 20-200, more preferably 20-80 nucleotides, for switching off and / or for changing the activity of target genes and / or for determining the gene activity for the screening of drugs against non-infectious / infectious multi-organ failure and / or to evaluate the effect against non-infectious / infectious multi-organ failure.

For this purpose, hybridizable synthetic analogs of the listed probes can also be used.

Further, in patients suffering from non-infectious or infectious causes of multiple organ failure, in clinical studies of phases 2-4 one can determine the gene activities in a biological fluid and from their "value" conclusions about disease progression, probability of survival, course of therapy or Include or exclude these patients for clinical trials.

A further embodiment of the invention is characterized in that a specific gene and / or gene fragment is selected from the group consisting of SEQ ID NO. 1 to SEQ ID NO. 1297 and gene fragments thereof having at least 5-2000, preferably 20-200, more preferably 20-80 nucleotides.

A further embodiment of the invention is characterized in that at least 2 to 100 different genes and / or gene fragments are used.

Another embodiment of the invention is characterized in that at least 200 different genes and / or gene fragments are used. Another embodiment of the invention is characterized in that at least 200 to 500 different genes and / or gene fragments are used.

Another embodiment of the invention is characterized in that at least 500 to 1000 different genes and / or gene fragments are used.

Another embodiment of the invention is characterized in that at least 1000 to 2000 different genes and / or gene fragments are used.

A further embodiment of the invention is characterized in that the genes or gene fragments listed in claim 9 and / or sequences derived from their RNA are replaced by synthetic analogs, aptamers and peptidonucleic acids.

Another embodiment of the invention is characterized in that the synthetic analogs of the genes comprise 5-100, in particular about 70 base pairs.

A further embodiment of the invention is characterized in that the gene activities are determined by means of hybridization methods.

A further embodiment of the invention is characterized in that the gene activity is determined by means of microarrays.

A further embodiment of the invention is characterized in that the gene activity is determined by hybridization-independent methods, in particular enzymatic and / or chemical hydrolysis and / or amplification methods, preferably PCR, subsequent quantification of the nucleic acids and / or derivatives and / or fragments thereof ,

Another embodiment of the invention is characterized in that the sample is selected from: body fluids, in particular blood, cerebrospinal fluid, urine, ascites fluid, seminal fluid, saliva, punctate; Cell contents or a mixture thereof. Another embodiment of the invention is characterized in that cell samples are optionally subjected to a lytic treatment to release their cell contents.

It is clear to the person skilled in the art that the individual features of the invention set out in the claims can be combined with one another without restriction.

Marker genes within the meaning of the invention are understood to mean all derived DNA sequences, partial sequences and synthetic analogs (for example peptido-nucleic acids, PNA). The description of the invention related to gene expression determination at the RNA level is not a limitation but only an exemplary application.

The blood-related description of the invention represents only an exemplary application of the invention. As biological fluids in the sense of the invention, all body fluids of humans are understood.

Further advantages and features of the present invention will become apparent from the description of an embodiment and from the drawing.

Fig. 1 shows the pathological course of multi-organ failure, starting from different medical conditions.

embodiment

Differential gene expression studies to distinguish between non-infectious and infectious causes of multiple organ failure.

For the measurement of differential gene expression to differentiate between noninfectious and infectious causes of multiple organ failure, whole blood samples were taken from a total of 57 patients treated in surgical intensive care units.

Whole blood samples were taken from 31 patients who underwent infective MOV [then referred to as severe sepsis or septic shock and classified after 8] as part of their intensive care.

In addition, whole blood samples were taken from 26 patients who developed a noninfectious MOV [classified after 8] as part of their intensive care.

The reference samples were the total RNA from cell lines SIG-M5.

Selected characteristics of the two patient groups are shown in Table 1. Data on age, gender, and the SOFA score are used as a measure of the function of the organ systems. It also reports the plasma protein levels of procalcitonin (PCT) and CRP, the number of leucocytes, and the patient's most common Center of Disease Control (CDC) criteria.

All patient samples were co-hybridized with the reference sample on a microarray. Table "!: Data of patient groups

^r median (intraquartile distance)

Experimental description:

After collection of the whole blood, the total RNA of the samples was isolated using the PAXGene Blood RNA Kit according to the manufacturer's instructions (Qiagen). ^:

cell culture

For cell cultivation (control samples), 19 cryocell cultures (SIGM5) (frozen in liquid nitrogen) were used. The cells were each inoculated with 2 ml of Iscove's medium (Biochrom AG) supplemented with 20% fetal calf serum (FCS). The cell cultures were then incubated for 24 hours at 37 ° C under 5% CO2 in 12-well plates. Afterwards, the contents of 18 wells were divided into 2 parts, each with the same volume, so that finally 3 plates of the same format (in total 36 wells) were available. The cultivation was then continued for 24 hours under the same conditions. Subsequently, the resulting cultures of 11 wells of each plate were combined and centrifuged (1000 xg, 5 min, room temperature). The supernatant was discarded and the cell pellet in 40 ml solved the above medium. These 40 ml dissolved cells were divided equally into two 250 ml flasks and incubated again after 48 hours of incubation and addition of 5 ml of the above-mentioned medium. Of the remaining 2 ml of the two remaining plates, 80 μl were added to empty wells of the same plates previously prepared with 1 ml of the above medium. After 48 hours of incubation, only one of the 12 well plates was processed as follows: 500 μl were withdrawn from each well and pooled. The resulting 6 ml was added to a 250 ml flask containing approximately 10 ml of fresh medium. This mixture was centrifuged at 1000 xg for 5 minutes at room temperature and dissolved in 10 ml of the above medium. The subsequent cell count gave the following result: 1.5 × 10 7 cells per ml, 10 ml total volume, total number of cells: 1, 5 × 108. Since the cell number was not sufficient, 2.5 ml of the above cell suspension in 30 ml of medium in a 250 ml (75 cm ² ) flask (total of 4 pistons). After 72 hours of incubation, 20 ml each of fresh medium was added to the flasks. After the following 24-hour incubation, the count was as described above, giving a total cell number of 3.8 x 10 ° cells. In order to reach the desired cell number of 2 × 10 6 cells, the cells were resuspended in 47.5 ml of the above medium in 4 flasks. After an incubation period of 24 hours, the cells were centrifuged and washed twice with phosphate buffer without Ca ²⁺ and Mg ²⁺ (Biochrom AG).

The isolation of the total RNA is carried out by means of the NucleoSpin RNA L kit (Machery & Nagel) according to the manufacturer's instructions. The procedure described above was repeated until the required number of cells was reached. This was required to achieve the required amount of 6 mg total RNA, which corresponds approximately to an efficiency of 600 μg RNA per 10 8 cells.

Reverse transcription / labeling / hybridization

After collection of the whole blood, the total RNA of the samples was isolated and tested for quality using the PAXGene Blood RNA Kit (PreAnalytiX) according to the manufacturer's instructions. From every sample 10 μg of total RNA were aliquoted and together with 10 μg total RNA from SIGM5 cells as reference RNA to complementary DNA (cDNA) with the reverse transcriptase Superscript II (Invitrogen) rewritten and the RNA then removed by alkaline hydrolysis from the batch. In the reaction mixture, a portion of the dTTP was replaced by aminoallyl-dUTP (AA-dUTP), to allow later the coupling of the fluorescent dye to the cDNA.

After purification of the reaction mixture, the cDNA of the samples and controls were labeled with the fluorescence dyes Afexa 647 and Alexa 555 kovaJent and hybridized on a microarray from SIRS-Lab.

On the microarray used are 5308 immobilized

55-70 base pair polynucleotides each representing a human gene and quality assurance control spots. A microarray is divided into 28 subarrays with a grid of 15x15 spots.

The hybridization and the subsequent washing or drying was carried out in the hybridization station HS 400 (Tecan) according to the manufacturer for 10.5 hours at 42 ⁰ C. The hybridization solution used consists of the respective labeled cDNA samples, 3.5 × SSC (1x SSC contains 150 mM sodium chloride and 15 mM sodium citrate), 0.3% sodium dodecyl sulfate (v / v) 25% formamide (v / v) and 0 each , 8 μg μl-1 cot-1 DNA, yeast t-RNA and polyA RNA. The subsequent washing of the microarrays was carried out with the following program at room temperature: rinse for 90 seconds with washing buffer 1 (2 × SSC, 0.03% sodium dodecylsuifate), with washing buffer 2 (1 × SSC) and finally with washing buffer 3 (0.2 × SSC) , Thereafter, the microarrays were dried under a stream of nitrogen at a pressure of 2.5 bar at 30 ⁰ C for 150 seconds.

After hybridization, the hybridization signals of the microarrays were read with a GenePix 4000B scanner (Axon) and the expression ratios of the differentially expressed genes were determined using the GenePix Pro 4.0 software (Axon). Evaluation:

For the evaluation, the mean intensity of a spot was determined as the median value of the associated spot pixels.

Correction of systematic error:

The correction of systematic errors was carried out according to the approach of Huber et al. (2002). Here, the additive and the multipUcative Blas were estimated within a microarray of 70% of the existing gene samples. For all further calculations, the signals were transformed by means of hyperbolic arc sinus.

For analysis, the normalized and transformed relative ratios of the signals of the patient samples versus the general control were calculated. That for the jth gene of the nth patient, the calculation gave the value Gj, n = arcsinh (Scy5 (j, n)) - arcsinh (Scy3 (j, n)), where [SCy3 (j, π), SCy5 (j, n)] denotes the associated signal pair. If a spot was not evaluable for a patient (e.g., a spot on the scanned image), the associated value was marked as missing ('missing value').

Statistical comparison:

For comparison, the two-sided two-sample Student's test was used per gene. Both samples contained patient group values of non-infectious MOV and infectious MOV, respectively. The associated p-value was evaluated for the selection of the differentially expressed genes. For the group of selected genes, the associated p-value was less than 0.05.

The level of expression of each gene was the criterion for sorting the genes under study. Of interest were the genes that were most overexpressed or under-expressed between patients afflicted with a non-infectious MOV versus infectious MOV patients.

From Table 2, it can be seen that 721 genes were found in the patient sample present in the patient with infectious MOV compared to the patients with non-infective MOV were significantly overexpressed. Further, it can be seen from Table 3 that 576 genes of infectious MOV patients were significantly under-expressed in patients with non-infective MOV. From the results, it is clear that the gene activities listed in Table 2 and Table 3 distinguish between the non-infectious causes of multiple organ failure and the infectious causes of multi-organ failure (Thus, the listed gene activities are markers for distinguishing non-infectious and infectious causes of multi-organ failure.

Table 2: Significantly increased gene activities in samples of patients with infectious MOV ₁ in the liver for the gene activities of patients with non-infectious MOV

Table 3: Significantly reduced gene activities in samples from patients with infectious MODS / MOV compared to the gene activities of patients with non-infectious MODS / MOV

These characteristic changes in Table 2 and 3 are exploitable for the inventive use according to claim 1.

The GenBank accession numbers listed in Tables 2 and 3 (Internet access via http://www.ticbi.nim.nih.gov/) of the individual sequences are described in detail in the sequence protocol attached to this application in each case of a sequence ID (Sequence ID : 1 to sequence ID: 1297).

references

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Claims

claims

1. Use of in vitro gene expression profiles obtained from a patient sample for distinguishing between non-infectious and infectious causes of multi-organ failure.

2. Use according to claim 1 for the therapy-accompanying course assessment in non-infectious and infectious

Multiple organ failure.

3. Use according to claim 1 for the classification of patients with non-infectious or infectious causes of multi-organ failure.

4. Use according to claim 3 as an inclusion or exclusion criterion of patients with non-infectious or infectious causes of multi-organ failure in clinical studies of phases 2-4.

5. Use according to one of claims 1 to 4 for generating gene activity data for electronic processing.

6. Use according to claim 5, wherein the obtained gene activity data for the production of software for the description of the individual prognosis of a patient, for diagnostic purposes and / or

Patient data management systems, to be used.

7. Use according to claim 5, wherein the gene activity data are used to produce expert clinical systems and / or to model more cellular signal transduction pathways.

8. Use according to one of claims 1 to 7, wherein a specific gene and / or gene fragment is used to generate the Genexpressionsprofiles, which is selected from the group consisting of SEQ ID NO. 1 to SEQ ID NO. 1326 as well as gene fragments thereof with at least 5-2000.

9. Use according to claim 8, wherein the gene fragments comprise 20-200, preferably 20-80 nucleotides.

10. Use according to one of claims 1 to 9, characterized in that the gene expression profiles are determined by means of hybridization methods, in particular those on microarrays.

11. A method for in vitro measurement of gene expression profiles for use according to at least one of claims 1-9, characterized in that one determines in patients the gene activity of a plurality of specific, related to the non-infectious and infectious causes of multi-organ failure genes in a patient sample, wherein the genes and / or gene fragments specific for the differentiation of non-infectious and infectious causes of a multiorgan failure are selected from the group consisting of: SEQ ID NO. 1 to SEQ ID NO. 1326 and gene fragments thereof with at least 5-2000 nucleotides.

12. The method according to claim 11, characterized in that the gene fragments comprise 20-200, preferably 20-80 nucleotides.

13. The method according to claim 11 or 12, characterized in that at least 2 to 100 different genes and / or gene fragments are used.

14. The method according to any one of claims 11 or 12, characterized in that at least 200 different genes and / or gene fragments are used.

15. The method according to any one of claims 11 or 12, characterized in that at least 200 to 500 different genes and / or gene fragments are used.

16. The method according to any one of claims 11 or 12, characterized in that at least 500 to 1000 different genes and / or gene fragments are used.

17. The method according to any one of claims 11 or 12, characterized in that at least 1000 to 2000 different genes and / or gene fragments are used.

18. The method according to any one of claims 11 to 17, characterized in that the listed in claim 11 genes or gene fragments and / or derived from their RNA sequences are replaced by synthetic analogues, aptamers, spiegelmers and Peptido- and

Morpholinonucleic.

19. The method according to claim 18, characterized in that the synthetic analogues of the genes and / or gene fragments include 5-100, in particular about 70 base pairs.

20. The method according to claim 11 to 19, characterized in that the gene activities is determined by hybridization method.

21. The method according to claim 20, characterized in that the gene activity is determined by means of microarrays.

22. The method according to any one of claims 11 to 21, characterized in that the gene activity by hybridization-independent methods, in particular enzymatic and / or chemical hydrolysis and / or amplification methods, preferably PCR, subsequent quantification of the nucleic acids and / or derivatives and / or Fragments thereof, is determined.

23. The method according to any one of claims 11 to 22, characterized in that the sample is selected from: body fluids, in particular blood, cerebrospinal fluid, urine, ascites fluid, seminal fluid, saliva, punctate; Cell contents or a mixture thereof.

24. The method according to any one of claims 11 to 23, characterized in that cell samples are optionally subjected to a lytic treatment to release their cell contents.

25. Use of gene expression profiles obtained in vitro from a patient sample and / or of the probes used therefor, which are selected from the group consisting of SEQ ID no. 1 to SEQ ID NO. 1326 and gene fragments thereof having at least 5-2000 nucleotides, for switching off and / or activity modification of target genes and / or for determining the gene activity or derived protein products for the screening of drugs against non-infectious and / or infectious causes of multi-organ failure and / or for evaluation the effect against non-infectious and / or infectious causes of a multi-organ failure.

26. Use according to claim 25, characterized in that hybridizable synthetic analogs of the probes listed in claim 25 are used.

27. Use according to one of claims 25 or 26, characterized in that the genes and / or gene fragments comprise 20-200, preferably 20-80 nucleotides.