METHOD FOR IDENTIFYING A BACTERIAL INFECTION

Abstract

The present application concerns a method for identifying the nature of a bacterial infection from a peritoneal sample, in particular, whether it is a Gram-negative or Gram-positive infection, based upon the determination of one or more cellular and/or humoral markers in a sample.

Claims

1. A method for treating an individual suffering from a peritoneal Gram-positive bacterial infection comprising: (a) obtaining a peritoneal sample from the individual; (b) examining said peritoneal sample in order to determine the amount of CXCL10 and the amount of total CD4.sup.+ T cell numbers; and (c) where the amount of CXCL10 is increased relative to the amount of CXCL10 in a control sample from an individual not having a Gram-positive bacterial infection and the amount of total CD4.sup.+ T cell numbers is increased relative to the amount of CD4.sup.+ T cell numbers in a control sample from an individual not having a Gram-positive bacterial infection, concluding that the individual from whom the peritoneal sample has been taken has a Gram-positive bacterial infection; and (d) administering to the individual to be treated a therapeutic for treating the Gram-positive bacterial infection.

2. The method according to claim 1 wherein said peritoneal sample is fluid from the peritoneal space or from a peritoneal effluent of an individual undergoing peritoneal dialysis treatment or tissue from the peritoneum.

3. The method according to claim 1 wherein at least one additional study is undertaken prior to the step of administering, the at least one additional study comprising: determining the amount of one or more of the following in the peritoneal sample relative to said control: (e) V2.sup.+ T cells within the total T cell population; or (f) IL-22; and where the amount of d) V2.sup.+ T cells within the total T cell population is decreased relative to the amount of same in said control and the amount of IL-22 is increased relative to the amount of same in said control, concluding that the individual from whom the peritoneal sample has been taken has a Gram-positive bacterial infection.

4. The method according to claim 3 wherein said method is performed using steps (a)-(d) and one or more of steps (e)-(f) including any combination thereof.

5. The method according to claim 1 comprising periodically repeating steps (a)-(c) for identifying a Gram-positive infection and, where it is concluded that said individual is still suffering from a Gram-positive bacterial infection continuing to administer to said individual the therapeutic for treating the Gram-positive bacterial infection.

6. The method according to claim 1 wherein said therapeutic is selected from the list comprising: penicillins and beta-lactamase inhibitors, cephalosporins, macrolides and lincosamines, quinolones and fluoroquinolones, carbapenems, monobactams, aminoglycosides, tetracyclines, sulfonamides, rifampin, oxazolidonones, all macrolides, all polymixins, all quinolones, all glycopeptides, all lincosamides, all streptomycin derivatives, and all antibiotics not covered by generic classes including chloramphenicol, rifampicin, fosfomycin, fosmidomycin, nitrofurantoin, metronidazole, daptomycin, quinupristin, linezolid, telavancin, mupirocin, and folate synthesis inhibitors as well as structural analogues and derivates thereof.

Description

BRIEF DESCRIPTION OF THE DRAWING FIGURES

[0055] The disclosed subject matter will now be described in greater detail with reference to the Examples below and to the drawings in which:

[0056] FIG. 1A shows total number and relative frequency (%) of peritoneal neutrophils (CD15.sup.+), monocytes/macrophages (CD14.sup.+) and T cells (CD3.sup.+) in stable and infected PD patients on day 1 of acute peritonitis. Infected patients were grouped according to the microbiological culture results into patients with culture-negative (n/c) or confirmed Gram-positive or Gram-negative infection. Data points represent individual patients, horizontal lines mean values per group.

[0057] FIG. 1B shows total number and proportion of helper T cells (CD4+), cytotoxic T cells (CD8+) and T cells (V2+) within the peritoneal CD3+ T cell population in stable and infected PD patients on day 1 of acute peritonitis. Infected patients were grouped according to the microbiological culture results into patients with culture-negative (n/c) or confirmed Gram-positive or Gram-negative infection. Data points represent individual patients, horizontal lines mean values per group.

[0058] FIG. 2 relates to humoral indicators. Peritoneal levels (in ng/ml) of IL-1, IL-2, IL-6, sIL 6R, IL-10, IL-12p70, IL-17A, IL-22, CXCL8, CXCL10, IFN-, TNF-, GM-CSF, TGF-1 and MMP-3 in stable and infected PD patients on day 1 of acute peritonitis. Infected patients were grouped according to the microbiological culture results into patients with culture-negative (n/c) or confirmed Gram-positive or Gram-negative infection. Data points represent individual patients, horizontal lines mean values per group.

[0059] FIG. 3A presents examples of immunological biomarkers in patients presenting with a cloudy bag on day 1, depending on the microbiological culture results, showing discrimination between Gram-negative and non-Gram-negative infections. Data points represent individual episodes (white, culture-negative; blue, confirmed Gram-positive infection; red, confirmed Gram-negative infection. Dashed lines indicate calculated cut-off values for positive or negative discrimination.

[0060] FIG. 3B presents examples of immunological biomarkers in patients presenting with a cloudy bag on day 1, depending on the microbiological culture results, showing discrimination between Gram-positive and non-Gram-positive infections. Data points represent individual episodes (white, culture-negative; blue, confirmed Gram-positive infection; red, confirmed Gram-negative infection. Dashed lines indicate calculated cut-off values for positive or negative discrimination.

[0061] FIG. 4. Kaplan-Meier plot showing cumulative technique survival of patients with acute peritonitis, depending on the frequency of V2+ T cells among all peritoneal T cells on day 1. The cut-off value was determined by ROC analysis. AUROC for 30th technique failure prediction: 0.9170.048, 95% confidence interval: 0.823-1.000. Youden Index: 0.85, sensitivity: 100%, specificity: 85%. The statistical difference between the two curves was analysed by log rank test.

[0062] FIG. 5. Flow chart of proposed PD peritonitis treatment as guided by immune fingerprint-based diagnostic tests, depending on the test result.

[0063] Table 1 Immunological biomarkers in stable patients and patients presenting with a cloudy bag on day 1 (meanSEM). n.s., not significant.

[0064] Table 2 Immunological biomarkers in patients presenting with a cloudy bag on day 1, depending on the absence or presence of a confirmed Gram-negative infection (meanSEM). n.s., not significant.

[0065] Table 3. Ability of immunological biomarkers to discriminate between Gram-negative and non-Gram-negative episodes of peritonitis on day 1.

[0066] Table 4. Prediction of Gram-negative infection on the first day of presentation with acute peritonitis.

[0067] Table 5. Immunological biomarkers showing diagnostic significance for prediction of Gram-negative episodes of peritonitis on day 1.

[0068] Table 6 Immunological biomarkers in patients presenting with a cloudy bag on day 1, depending on the absence or presence of a confirmed Gram-positive infection (meanSEM). n.s., not significant.

[0069] Table 7. Ability of immunological biomarkers to discriminate between Gram-positive and non-Gram-positive episodes of peritonitis on day 1.

[0070] Table 8. Prediction of Gram-positive infection on the first day of presentation with acute peritonitis.

[0071] Table 9. Immunological biomarkers showing diagnostic significance for prediction of Gram-positive episodes of peritonitis on day 1.

[0072] Table 10. Biomarkers of potential diagnostic value in patients presenting with a cloudy bag on day 1, depending on the microbiological culture results.

DETAILED DESCRIPTION

Materials and Methods

Patients

[0073] We recruited 52 adult patients who were receiving PD at the University Hospital of Wales, Cardiff, UK, and were admitted on day 1 of acute peritonitis between 1 Sep. 2008 and 31 Jan. 2012. 15 stable patients with no infection in the previous 3 months were included in this study as non-infected controls. Sampling of PD effluent was approved by the South East Wales Local Ethics Committee (04WSE04/27), and conducted according to the principles expressed in the Declaration of Helsinki. All patients provided written informed consent. Diagnosis of acute peritonitis was based on the presence of abdominal pain and cloudy peritoneal effluent with >100 WBC/mm.sup.3. Infections were grouped into culture-negative, Gram-positive and Gram-negative episodes, according to the result of the microbiological analysis of the effluent, which was conducted at the central diagnostic laboratories of the University Hospital of Wales.

Flow Cytometry

[0074] Peritoneal cells were acquired on an eight-color FACSCanto II (BD Biosciences) and analyzed with FloJo (Tree Star), using monoclonal antibodies against CD3 (UCHT1), CD4 (SK3), CD8 (RPA-T8), CD15 (HI98), CD69 (FN50), CD86 (2331-FUN1), HLA-DR (L234) and TCR-V2 (B6.1) from BD Biosciences; CD14 (61D3) from eBioscience; and TCR-V9 (Immu360) from Beckman Coulter, together with appropriate isotype controls. Leukocyte populations were identified based on their appearance in side scatter and forward scatter area/height, exclusion of live/dead staining (fixable Aqua; Invitrogen), and surface staining: CD15.sup.+ neutrophils, CD14.sup.+ monocytes/macrophages and CD3.sup.+ T cells. T cell subsets were identified as CD4.sup.+ helper T cells, CD8.sup.+ cytotoxic T cells and V2.sup.+ T cells.

ELISA

[0075] Cell-free peritoneal effluents were analyzed for TNF-, GM-CSF, IFN-, IL-1, IL-2, IL-6, IL-10, IL-12p70, CXCL8 and sIL-6R on a SECTOR Imager 6000 (Meso Scale Discovery). IL-17A, IL-22, CXCL10 and MMP-3 (R&D Systems) as well as TGF-1 (eBioscience) were measured in duplicate on a Dynex MRX II reader, using conventional ELISA kits.

Statistical Analysis

[0076] Statistical analyses were performed using SPSS 16.0 and GraphPad Prism 4.0 software. All variables were tested for normal distributions using the Kolmogorov-Smirnov test. Differences between patient groups were analyzed using Student's t-tests for normally distributed data or Mann-Whitney U-tests for non-parametric data. Categorical data were tested using the Chi-square test. Predictive biomarkers were assessed using univariate analysis; statistically significant (p<0.05) variables from the univariate analysis were included in a multivariate analysis. Multiple logistic regression analyses were conducted based on forward and/or backward elimination of data, as indicated in the tables. Discrimination was assessed using AUROC curves and compared using non-parametric approaches; AUROC analyses were also used to calculate cut-off values, sensitivity and specificity. Cumulative survival curves as a function of time were generated using the Kaplan-Meier approach and compared using the log rank test. All statistical tests were two-tailed; differences were considered statistically significant as indicated in the figures and tables: *, p<0.05; **, p<0.01; ***, p<0.001.

Results

[0077] Acute Episodes of Peritonitis are Associated with Severe Peritoneal Inflammation

[0078] Patients presenting with acute peritonitis were characterized by a significant peritoneal influx of immune cells, predominantly CD15.sup.+ neutrophils, CD14.sup.+ monocytes/macrophages and CD3.sup.+ T cells (Table 1). This was true for culture-negative episodes of peritonitis as well as cases of confirmed infection by Gram-negative or Gram-positive bacteria (FIG. 1). While peritoneal leukocytes in stable patients comprised mainly of monocytes/macrophages and T cells, acute peritonitis was dominated by a massive recruitment of neutrophils, at times reaching >95% of all peritoneal cells and >10.sup.11 cells in total. Detailed flow cytometrical analyses of the peritoneal leukocyte population revealed further striking changes in the composition of the local immune cell infiltrate in patients with acute peritonitis. As such, there was a preferential increase in the frequency of V2.sup.+ T cells within the T cell population in acute peritonitis, while the percentages of CD4.sup.+ and CD8.sup.+ T cells remained virtually unchanged (Table 1).

[0079] Soluble mediators significantly increased in acute peritonitis included interleukin-1 (IL-1), IL-6, soluble IL-6 receptor (sIL-6R), IL-10, IL-22, CXCL8, CXCL10, tumour necrosis factor- (TNF-), transforming growth factor- (TGF-) and matrix metalloproteinase-3 (MMP-3); at the same time levels of cytokines such as IL-2, IL-12p70, IL-17 and granulocyte/macrophage colony-stimulating factor (GM-CSF) were not elevated above baseline or, in the case of interferon- (IFN-), not significantly (FIG. 2, Table 1). Taken together, these measurements identify a broad range of humoral and cellular biomarkers that indicate acute inflammatory responses in PD patients, some of which might be of diagnostic value.

Distinct Immune Fingerprints in Patients with Gram-Negative Infections have Diagnostic Potential on Day 1

[0080] We next tested whether pathogen-specific immune fingerprints exist that could predict infections by certain groups of bacteria. Given the importance of Gram-negative bacteria in the clinic and their association with worse outcomes we initially concentrated on the prediction of Gram-negative infections. Amongst all patients presenting with a cloudy bag on day 1, patients with confirmed Gram-negative infections displayed larger numbers of infiltrating neutrophils and consequently lower proportions of monocytes/macrophages and T cells than the rest of the patients, i.e. individuals with culture-negative or Gram-positive infections (Table 2). Within the T cell population, V2.sup.+ T cells were significantly increased and expressed higher levels of the activation marker HLA-DR in Gram-negative infections. In turn, peritoneal monocytes/macrophages expressed lower levels of CD86 in Gram-negative infections, compared to the rest of the patients. Inflammatory markers significantly increased in Gram-negative infections included IL-1, IL-10 and TNF- (FIG. 3A; Table 2). AUROC calculations identified the combination of V2.sup.+ T cell frequencies and peritoneal levels of IL-10 as excellent discriminator to predict Gram-negative infections (Table 3). This combination also had the highest overall correctness, with 100% sensitivity and 93% specificity for the correct prediction of Gram-negative peritonitis (Table 4). The prognostic value of the proportion of monocytes/macrophages amongst all cells (10.7%) and their expression of CD86 (67.9%), the frequency of V2.sup.+ T cells with the T cell population (6.3%) and their expression of HLA-DR (16.1%), and peritoneal IL-10 levels (110.1 pg/ml) were all confirmed by univariate analyses. Multivariate analysis of these parameters identified the V2.sup.+ T cell frequency as independent prognostic biomarker for the prediction of Gram-negative peritonitis in all patients presenting with a cloudy bag on day 1 (Table 5). As Gram-negative infections are associated with higher rates of technique failure and mortality, we finally tested whether the peritoneal V2.sup.+ T cell frequency has any indirect predictive power as to clinical outcome from episodes of acute peritonitis. As shown in FIG. 4, there was a clear difference between patients with a relatively low and a relatively high proportion of peritoneal V2.sup.+ T cells on the day of presentation. While patients with V2.sup.+ T cell levels below the cut-off value of 4.3% had very low rates of technique failure over the following 3 months, patients with V2.sup.+ T cell levels higher than 4.3% had a significantly elevated risk of technique failure, confirming V2.sup.+ T cells as having both diagnostic and prognostic value in PD patients with acute peritonitis.

Distinct Immune Fingerprints in Patients with Gram-Positive Infections have Diagnostic Potential on Day 1

[0081] In an analogous way, we next attempted to identify predictors of Gram-positive infections. Amongst all patients presenting with a cloudy bag on day 1, patients with confirmed Gram-positive infections displayed larger numbers of infiltrating CD4.sup.+ and CD8.sup.+ T cells than the rest of the patients, i.e. individuals with culture-negative or Gram-negative infections (Table 6), while the proportion of V2.sup.+ T cells within the T cell population was significantly lower in Gram-positive infections. Inflammatory markers significantly increased in Gram-positive infections included IL-22 and CXCL10 (FIG. 3B; Table 6). AUROC calculations identified the combination of CXCL10 (301.2 pg/ml) and IL-22 levels (54.3 pg/ml) and V2.sup.+ T cell frequencies (2.7%) as excellent discriminator to predict Gram-positive infections (Table 7). This combination also had the highest overall correctness, with 89% sensitivity and 67% specificity for the correct prediction of Gram-positive peritonitis. In turn, CXCL10 levels (301.2 pg/ml) combined with total CD4.sup.+ T cell counts (15.2.Math.10.sup.6) had a sensitivity of only 53% yet at a specificity of 95% for the prediction of Gram-positive peritonitis (Table 8). CD4.sup.+ T cell counts as well as V2.sup.+ T cell frequencies and CXCL10 levels had prognostic value as confirmed by univariate analyses. Multivariate analysis of these parameters alone and in combination identified the combination of CD4.sup.+ T cell counts and CXCL10 levels as independent biomarker for the prediction of Gram-positive peritonitis in all patients presenting with a cloudy bag on day 1 (Table 9).

[0082] Taken together, our findings indicate that immune fingerprint-based diagnostic tests are able to guide treatment of patients with acute infections (FIG. 5). Depending on the test result, patients might be diagnosed as having a culture-negative episode (i.e. no bacterial infection present) of peritonitis that is associated with relatively benign outcome. Such patients might benefit from shorter course treatments as outpatients (and might not need any antibiotics at all if the episode is of non-infectious origin). Patients diagnosed with Gram-positive or Gram-negative infections might benefit from better targeted therapy, and especially in the case of Gram-negative infections that are associated with high rates of technique failure and mortality, from close monitoring and improved management. In the case of unknown bacterial infection, patients might receive the conventional treatment with broad-spectrum antibiotics.

SUMMARY

[0083] Our research highlights the importance of combining humoral and cellular parameters to establish accurate immune fingerprints. Particularly promising humoral and cellular parameters in the definition of disease-specific immune fingerprints include local levels of IL-1, IL-10, IL-22, TNF- and CXCL10, as well as the relative proportion of neutrophils and monocytes/macrophages among total peritoneal cells and the frequency of T cells within the peritoneal T cell population (Table 10).

[0084] Consequently, it has therefore been shown that immune fingerprints of bacterial infections exist, and that characteristic immunological biomarkers have the potential to distinguish and predict early bacterial infection and so direct appropriate modes of treatment.

REFERENCES

[0085] 1. Fahim M, Hawley C M, McDonald S P, Brown F G, Rosman J B, Wiggins K J, Bannister K M, Johnson D W: Culture-negative peritonitis in peritoneal dialysis patients in Australia: predictors, treatment, and outcomes in 435 cases. Am J Kidney Dis 55: 690-697, 2010 [0086] 2. Mohan R, Mach K E, Bercovici M, Pan Y, Dhulipala L, Wong P K, Liao J C: Clinical validation of integrated nucleic acid and protein detection on an electrochemical biosensor array for urinary tract infection diagnosis. PLoS One 6(10): e26846, 2011 [0087] 3. Podsiadly E, Fracka B, Szmigielska A, Tylewska-Wierzbanowska S: Seroepidemiological studies of Chlamydia pneumoniae infections in 1-36 months old children with respiratory tract infections and other diseases in Poland. Pol J Microbiol. 54(3):215-9, 2005.

TABLE-US-00001 TABLE 1 Immunological biomarkers in stable patients and patients presenting with a cloudy bag on day 1 (mean SEM). Stable PD Cloudy bag p Gender (male/female) 9/6 32/20 n.s. Age (years) 60.4 4.9 65.5 2.0 n.s. Days on PD (days) 1,058 219.2 1,142 131.1 n.s. Neutrophils (.Math.10.sup.6) 0.6 0.3 7,048 1,384 *** Monocytes (.Math.10.sup.6) 2.8 1.5 753.9 166.0 *** CD4.sup.+ T cells (.Math.10.sup.6) 0.3 0.2 32.3 15.7 *** CD8.sup.+ T cells (.Math.10.sup.6) 0.3 0.2 24.5 12.0 *** V2.sup.+ T cells (.Math.10.sup.6) 0.01 0.003 1.1 0.4 *** Neutrophils (% of total) 9.0 4.2 80.3 2.2 *** Monocytes (% of total) 28.9 9.4 12.9 1.9 n.s. T cells (% of total) 17.5 6.8 1.0 0.3 *** CD4.sup.+ (% of T cells) 52.2 3.3 50.6 2.1 n.s. CD8.sup.+ (% of T cells) 40.0 3.8 37.6 2.1 n.s. V2.sup.+ (% of T cells) 1.3 0.3 2.9 0.4 * IL-1 (pg/ml) 3.7 1.6 45.1 12.6 *** IL-2 (pg/ml) 6.2 2.2 11.4 2.1 n.s. IL-6 (pg/ml) 37.1 7.3 3,249 623.6 *** sIL-6R (pg/ml) 360.1 50.8 639.6 50.3 ** IL-10 (pg/ml) 10.9 3.8 85.6 19.4 *** IL-12p70 (pg/ml) 4.2 1.5 4.5 1.0 n.s. IL-17 (pg/ml) 1.5 1.0 6.7 2.7 n.s. IL-22 (pg/ml) 13.9 7.7 121.8 36.5 ** CXCL8 (pg/ml) 18.1 3.2 699.3 191.7 *** CXCL10 (pg/ml) 43.2 22.5 514.1 82.7 *** IFN- (pg/ml) 52.7 16.6 123.0 39.7 n.s. TNF- (pg/ml) 21.8 8.4 86.8 18.8 * GM-CSF (pg/ml) 11.3 4.4 15.5 3.8 n.s. MMP-3 (pg/ml) 1,540 184.9 3,029 427.3 ** n.s., not significant.

TABLE-US-00002 TABLE 2 Immunological biomarkers in patients presenting with a cloudy bag on day 1, depending on the absence or presence of a confirmed Gram-negative infection (mean SEM). Other Gram-negative p Gender (male/female) 25/15 7/5 n.s. Age (years) 64.1 2.4 70.1 2.9 n.s. Days on PD (days) 1,234 156.2 899.3 248.3 n.s. Neutrophils (.Math.10.sup.6) 5,875 1,580 10,779 2,686 * Monocytes (.Math.10.sup.6) 754.7 206.1 751.1 242.9 n.s. CD4.sup.+ T cells (.Math.10.sup.6) 39.3 20.5 9.9 3.4 n.s. CD8.sup.+ T cells (.Math.10.sup.6) 29.5 15.6 8.6 2.8 n.s. V2.sup.+ T cells (.Math.10.sup.6) 1.1 0.4 1.1 0.4 n.s. Neutrophils (% of total) 78.1 2.7 87.7 2.3 n.s. Monocytes (% of total) 15.1 2.3 5.8 1.0 * T cells (% of total) 1.3 0.3 0.2 0.03 * CD4.sup.+ (% of T cells) 52.7 2.3 43.7 4.6 n.s. CD8.sup.+ (% of T cells) 37.8 2.4 36.6 5.0 n.s. V2.sup.+ (% of T cells) 2.0 0.2 5.0 1.4 * HLA-DR.sup.+ (% of T cells) 10.8 1.8 22.5 4.7 * CD86.sup.+ (% of monocytes) 72.6 3.6 53.1 7.2 * IL-1 (pg/ml) 35.0 12.5 79.5 34.7 * IL-2 (pg/ml) 12.2 2.6 8.8 1.9 n.s. IL-6 (pg/ml) 2,561 538.8 5,586 1,942 n.s. sIL-6R (pg/ml) 606.3 57.6 751.4 100.9 n.s. IL-10 (pg/ml) 49.4 10.6 208.6 65.5 ** IL-12p70 (pg/ml) 4.6 1.3 4.1 1.4 n.s. IL-17 (pg/ml) 8.4 3.7 2.4 1.3 n.s. IL-22 (pg/ml) 139.8 45.9 56.8 22.9 n.s. CXCL8 (pg/ml) 742.6 237.5 552.3 257.8 n.s. CXCL10 (pg/ml) 570.1 97.7 306.9 130.2 n.s. IFN- (pg/ml) 144.5 50.9 50.0 11.6 n.s. TNF- (pg/ml) 65.3 17.9 159.7 51.8 * GM-CSF (pg/ml) 16.6 4.8 12.1 3.6 n.s. MMP-3 (pg/ml) 2,804 359.2 3,765 1,429 n.s. n.s., not significant.

TABLE-US-00003 TABLE 3 Ability of immunological biomarkers to discriminate between Gram-negative and non-Gram-negative episodes of peritonitis on day 1. AUROC SEM 95% CI p For Gram-negative prediction Monocytes (% of total) 0.745 0.075 0.597-0.893 * V2.sup.+ (% of T cells) 0.710 0.106 0.501-0.918 * HLA-DR.sup.+ (% of T cells) 0.720 0.097 0.530-0.911 * CD86.sup.+ (% of monocytes) 0.740 0.083 0.578-0.903 * IL-10 (pg/ml) 0.803 0.092 0.622-0.984 ** IL-1 (pg/ml) 0.738 0.086 0.569-0.907 * TNF- (pg/ml) 0.735 0.091 0.557-0.914 * IL-10 + V2.sup.+ 0.976 0.022 0.934-1.000 *** IL-10 + V2.sup.+ + HLA-DR.sup.+ 0.959 0.031 0.899-1.000 *** IL-1 + IL-10 + TNF- 0.844 0.077 0.693-0.995 **

TABLE-US-00004 TABLE 4 Prediction of Gram-negative infection on the first day of presentation with acute peritonitis. Cut-off Youden Sensitivity Specificity Point Index (%) (%) For Gram-negative prediction Monocytes (% of total) 10.7 0.50 50 100 V2.sup.+ (% of T cells) 6.3 0.46 46 100 HLA-DR.sup.+ (% of T cells) 16.1 0.48 64 84 CD86.sup.+ (% of monocytes) 67.9 0.47 74 73 IL-10 (pg/ml) 110.1 0.61 70 91 IL-1 (pg/ml) 14.0 0.55 90 65 TNF- (pg/ml) 32.8 0.45 80 65 IL-10 + V2.sup.+ 0.5 0.93 100 93 IL-10 + V2.sup.+ + HLA-DR.sup.+ 0.5 0.78 100 78 IL-1 + IL-10 + TNF- 2.5 0.61 70 91

TABLE-US-00005 TABLE 5 Immunological biomarkers showing diagnostic significance for prediction of Gram-negative episodes of peritonitis on day 1. Standard Odds ratio Coefficient error (95% CI) p Univariate logistic regression Monocytes (% of total) 0.189 0.093 0.828 (0.690-0.994) * V2.sup.+ (% of T cells) 0.385 0.159 1.469 (1.075-2.008) * HLA-DR.sup.+ (% of T cells) 0.072 0.029 1.075 (1.014-1.139) * CD86.sup.+ (% of monocytes) 0.037 0.016 0.964 (0.934-0.995) * IL-10 0.012 0.005 1.012 (1.003-1.022) * Multivariate logistic regression (backward) V2.sup.+ (% of T cells) 0.571 0.246 1.770 (1.093-2.866) * Constant 4.591 1.376 0.010

TABLE-US-00006 TABLE 6 Immunological biomarkers in patients presenting with a cloudy bag on day 1, depending on the absence or presence of a confirmed Gram-positive infection (mean SEM). Other Gram-positive p Gender (male/female) 17/10 15/10 n.s. Age (years) 68.2 2.4 62.4 3.1 n.s. Days on PD (days) 1,058 167.9 1,266 213.9 n.s. Neutrophils (.Math.10.sup.6) 5,604 1,610 8,623 2,293 n.s. Monocytes (.Math.10.sup.6) 477.2 128.0 1,056 309.1 n.s. CD4.sup.+ T cells (.Math.10.sup.6) 6.8 1.9 60.2 32.2 ** CD8.sup.+ T cells (.Math.10.sup.6) 4.9 1.5 46.1 24.5 * V2.sup.+ T cells (.Math.10.sup.6) 0.6 0.2 1.6 0.7 n.s. Neutrophils (% of total) 77.2 3.8 83.7 2.1 n.s. Monocytes (% of total) 15.4 3.3 10.3 1.5 n.s. T cells (% of total) 0.9 0.4 1.1 0.3 n.s. CD4.sup.+ (% of T cells) 49.3 3.2 51.9 2.9 n.s. CD8.sup.+ (% of T cells) 36.6 3.0 38.6 3.1 n.s. V2.sup.+ (% of T cells) 3.6 0.7 1.8 0.3 * HLA-DR.sup.+ (% of T cells) 17.2 3.0 10.3 2.1 n.s. CD86.sup.+ (% of monocytes) 62.9 5.3 73.0 4.1 n.s. IL-1 (pg/ml) 37.3 16.0 54.5 20.1 n.s. IL-2 (pg/ml) 7.6 1.4 16.0 4.0 n.s. IL-6 (pg/ml) 3,204 970.8 3,303 753.0 n.s. sIL-6R (pg/ml) 607.2 60.0 674.8 83.2 n.s. IL-10 (pg/ml) 96.5 33.1 72.5 16.0 n.s. IL-12p70 (pg/ml) 3.1 0.7 6.2 2.0 n.s. IL-17 (pg/ml) 3.7 1.9 12.1 6.5 n.s. IL-22 (pg/ml) 55.8 16.8 193.8 71.8 ** CXCL8 (pg/ml) 504.3 199.9 933.3 346.0 n.s. CXCL10 (pg/ml) 316.6 88.8 738.4 131.4 ** IFN- (pg/ml) 55.5 12.7 204.0 83.6 n.s. TNF- (pg/ml) 76.0 25.8 99.7 28.0 n.s. GM-CSF (pg/ml) 10.1 2.2 22.0 7.8 n.s. MMP-3 (pg/ml) 2,760 658.1 3,336 532.7 n.s. n.s., not significant.

TABLE-US-00007 TABLE 7 Ability of immunological biomarkers to discriminate between Gram-positive and non-Gram-positive episodes of peritonitis on day 1. AUROC SEM 95% CI p For Gram-positive prediction CD4.sup.+ T cells (.Math.10.sup.6) 0.741 0.079 0.587-0.895 ** CD8.sup.+ T cells (.Math.10.sup.6) 0.723 0.083 0.561-0.885 * V2.sup.+ (% of T cells) 0.699 0.079 0.543-0.854 * CXCL10 (pg/ml) 0.744 0.075 0.596-0.891 ** IL-22 (pg/ml) 0.736 0.074 0.591-0.881 ** CXCL10 + V2.sup.+ 0.821 0.066 0.691-0.951 *** CXCL10 + IL-22 + V2.sup.+ 0.816 0.069 0.681-0.951 ** CXCL10 + CD4.sup.+ 0.797 0.073 0.653-0.941 ** CXCL10 + IL-22 0.794 0.068 0.661-0.926 **

TABLE-US-00008 TABLE 8 Prediction of Gram-positive infection on the first day of presentation with acute peritonitis. Cut-off Youden Sensitivity Specificity Point Index (%) (%) For Gram-positive prediction CD4.sup.+ T cells (.Math.10.sup.6) 15.2 0.46 55 91 CD8.sup.+ T cells (.Math.10.sup.6) 7.8 0.46 60 86 CXCL10 (pg/ml) 301.2 0.49 77 72 IL-22 (pg/ml) 54.3 0.39 73 67 CXCL10 + IL-22 + V2.sup.+ 1.5 0.561 89 67 CXCL10 + V2.sup.+ 0.5 0.524 100 52 CXCL10 + CD4.sup.+ 1.5 0.48 53 95 CXCL10 + IL-22 0.5 0.49 91 55 For non-Gram-positive prediction V2.sup.+ (% of T cells) 2.7 0.375 57 81

TABLE-US-00009 TABLE 9 Immunological biomarkers showing diagnostic significance for prediction of Gram-positive episodes of peritonitis on day 1. Standard Odds ratio Coefficient error (95% CI) p Univariate logistic regression CD4.sup.+ T cells (.Math.10.sup.6) 0.062 0.026 1.064 (1.011-1.119) * CD8.sup.+ T cells (.Math.10.sup.6) 0.077 0.035 1.080 (1.008-1.156) * V2.sup.+ (% of T cells) 0.388 0.185 0.679 (0.472-0.976) * CXCL10 (pg/ml) 0.002 0.001 1.002 (1.000-1.003) * Multivariate logistic regression (forward) CXCL10 + CD4.sup.+ 1.972 0.597 7.186 (2.229-23.170) ** Constant 1.543 0.581 0.214

TABLE-US-00010 TABLE 10 Biomarkers of potential diagnostic value in patients presenting with a cloudy bag on day 1, depending on the microbiological culture results. Culture- Culture- Gram- Gram- negative positive positive negative Monocytes (% of total) 19.1 <19.1 <10.7 CD4.sup.+ T cells (.Math.10.sup.6) 15.2 V2.sup.+ (% of T cells) 2.7 6.3 HLA-DR.sup.+ (% of T cells) 16.1 CD86.sup.+ (% of monocytes) <67.9 IL-1 (pg/ml) <4.1 4.1 14.0 IL-10 (pg/ml) <23.3 23.3 110.1 IL-22 (pg/ml) 54.3 CXCL10 (pg/ml) 301.2 TNF- (pg/ml) <19.5 19.5 32.8