Limits...
Plasticity of the systemic inflammatory response to acute infection during critical illness: development of the riboleukogram.

McDunn JE, Husain KD, Polpitiya AD, Burykin A, Ruan J, Li Q, Schierding W, Lin N, Dixon D, Zhang W, Coopersmith CM, Dunne WM, Colonna M, Ghosh BK, Cobb JP - PLoS ONE (2008)

Bottom Line: Significant heterogeneity of VAP microarray profiles was observed secondary to patient ethnicity, age, and gender, yet 85 genes were identified with consistent changes in abundance during the seven days bracketing the diagnosis of VAP.Principal components analysis of these 85 genes appeared to differentiate between the responses of subjects who did versus those who did not develop VAP, as defined by a general trajectory (riboleukogram) for the onset and resolution of VAP.Moreover, riboleukograms may help explain variance in the host response due to differences in ethnic background, gender, and pathogen.

View Article: PubMed Central - PubMed

Affiliation: Center for Critical Illness and Health Engineering, Department of Surgery, Washington University in St. Louis, St. Louis, Missouri, USA.

ABSTRACT

Background: Diagnosis of acute infection in the critically ill remains a challenge. We hypothesized that circulating leukocyte transcriptional profiles can be used to monitor the host response to and recovery from infection complicating critical illness.

Methodology/principal findings: A translational research approach was employed. Fifteen mice underwent intratracheal injections of live P. aeruginosa, P. aeruginosa endotoxin, live S. pneumoniae, or normal saline. At 24 hours after injury, GeneChip microarray analysis of circulating buffy coat RNA identified 219 genes that distinguished between the pulmonary insults and differences in 7-day mortality. Similarly, buffy coat microarray expression profiles were generated from 27 mechanically ventilated patients every two days for up to three weeks. Significant heterogeneity of VAP microarray profiles was observed secondary to patient ethnicity, age, and gender, yet 85 genes were identified with consistent changes in abundance during the seven days bracketing the diagnosis of VAP. Principal components analysis of these 85 genes appeared to differentiate between the responses of subjects who did versus those who did not develop VAP, as defined by a general trajectory (riboleukogram) for the onset and resolution of VAP. As patients recovered from critical illness complicated by acute infection, the riboleukograms converged, consistent with an immune attractor.

Conclusions/significance: Here we present the culmination of a mouse pneumonia study, demonstrating for the first time that disease trajectories derived from microarray expression profiles can be used to quantitatively track the clinical course of acute disease and identify a state of immune recovery. These data suggest that the onset of an infection-specific transcriptional program may precede the clinical diagnosis of pneumonia in patients. Moreover, riboleukograms may help explain variance in the host response due to differences in ethnic background, gender, and pathogen. Prospective clinical trials are indicated to validate our results and test the clinical utility of riboleukograms.

Show MeSH

Related in: MedlinePlus

Principal components analysis of 85 leukocyte genes in the training and validation patient cohorts.(A) The solid black curve depicts the aggregate riboleukogram of the first 11 VAP patients (training cohort, same data as in Figure 3C). The other 7 curves are the individual riboleukograms of the patients in the validation cohort. The inset magnifies the trajectories of patients 13–17 (see Table 1) and demonstrates abrupt changes in riboleukogram course typically coincident with an increase in CPIS score (first occurrence of maximal CPIS value is indicated by the arrows). The paths of patients 13, 18 and 19, are atypical (see text for additional details). (B) The aggregate 11 patient VAP riboleukogram (black curve, same as panel A) is compared to the aggregate riboleukogram of all patients aligned by study day (that is, training and validation cohorts, irrespective of VAP day of diagnosis, dotted blue curve). Note that the VAP riboleukogram deviates from the “critical illness” riboleukogram (black arrows) prior to VAP diagnosis (lighting bolt), but after treatment, the VAP riboleukogram converges with the critical illness riboleukogram at the point of recovery. The green and red circles indicate where the patients entered and exited the study, respectively.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2215774&req=5

pone-0001564-g006: Principal components analysis of 85 leukocyte genes in the training and validation patient cohorts.(A) The solid black curve depicts the aggregate riboleukogram of the first 11 VAP patients (training cohort, same data as in Figure 3C). The other 7 curves are the individual riboleukograms of the patients in the validation cohort. The inset magnifies the trajectories of patients 13–17 (see Table 1) and demonstrates abrupt changes in riboleukogram course typically coincident with an increase in CPIS score (first occurrence of maximal CPIS value is indicated by the arrows). The paths of patients 13, 18 and 19, are atypical (see text for additional details). (B) The aggregate 11 patient VAP riboleukogram (black curve, same as panel A) is compared to the aggregate riboleukogram of all patients aligned by study day (that is, training and validation cohorts, irrespective of VAP day of diagnosis, dotted blue curve). Note that the VAP riboleukogram deviates from the “critical illness” riboleukogram (black arrows) prior to VAP diagnosis (lighting bolt), but after treatment, the VAP riboleukogram converges with the critical illness riboleukogram at the point of recovery. The green and red circles indicate where the patients entered and exited the study, respectively.

Mentions: A second cohort of 7 patients was analyzed to evaluate the informational value of the 85 genes that were identified in the first 11 patients with VAP. Two of these 7 additional patients were diagnosed with “late” VAP by the attending physician, while another 2 cases were described by the attending as “possible” VAP (Table 1). The individual riboleukograms for these 7 patients demonstrate the existence of immune recovery (basins of attraction) as well as the heterogeneity of the host response. In general, the individual riboleukograms follow a path moving from left to right, that is, from critical illness to recovery (Figure 6, green and red shaded areas, respectively). The development of an infectious complication is typically associated with a change in riboleukogram trajectory. For example, the paths of patients 13, 14, 15, 16, and 17 change directions abruptly coincident with changes in clinical status and concern for VAP or sepsis (see Figure 6A inset). Patient 17 grew Staphylococcus aureus from both urine and tracheal secretions prior to withdrawal of therapy for cure (the only death in the study). In contrast, the riboleukograms of patients 13, 18, and 19 are atypical, in that their paths do not start and/or do not finish with the others. Both patients 18 and 19 had pulmonary contusions secondary to polysystem trauma, maximal CPIS scores of 7 and 9, Gram-positive cocci cultured from airway secretions, and were treated with antibiotics, but had a clinical course labeled by the attending physician as “possible” VAP. Their riboleukograms are in different portions of the graph in Figure 6A, but have a similar shape and slope. Both patients 13 and 18 had intracranial hemorrhage. Patient 13 was not diagnosed with VAP (no infiltrate on CXR) but was treated with antibiotics for a fever of 39.4°C and WBC of 31,300 (day 5), tracheal secretions that subsequently grew out Acinetobacter and Stenotrophomonas (CPIS 6), and concern for catheter-related sepsis.


Plasticity of the systemic inflammatory response to acute infection during critical illness: development of the riboleukogram.

McDunn JE, Husain KD, Polpitiya AD, Burykin A, Ruan J, Li Q, Schierding W, Lin N, Dixon D, Zhang W, Coopersmith CM, Dunne WM, Colonna M, Ghosh BK, Cobb JP - PLoS ONE (2008)

Principal components analysis of 85 leukocyte genes in the training and validation patient cohorts.(A) The solid black curve depicts the aggregate riboleukogram of the first 11 VAP patients (training cohort, same data as in Figure 3C). The other 7 curves are the individual riboleukograms of the patients in the validation cohort. The inset magnifies the trajectories of patients 13–17 (see Table 1) and demonstrates abrupt changes in riboleukogram course typically coincident with an increase in CPIS score (first occurrence of maximal CPIS value is indicated by the arrows). The paths of patients 13, 18 and 19, are atypical (see text for additional details). (B) The aggregate 11 patient VAP riboleukogram (black curve, same as panel A) is compared to the aggregate riboleukogram of all patients aligned by study day (that is, training and validation cohorts, irrespective of VAP day of diagnosis, dotted blue curve). Note that the VAP riboleukogram deviates from the “critical illness” riboleukogram (black arrows) prior to VAP diagnosis (lighting bolt), but after treatment, the VAP riboleukogram converges with the critical illness riboleukogram at the point of recovery. The green and red circles indicate where the patients entered and exited the study, respectively.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2215774&req=5

pone-0001564-g006: Principal components analysis of 85 leukocyte genes in the training and validation patient cohorts.(A) The solid black curve depicts the aggregate riboleukogram of the first 11 VAP patients (training cohort, same data as in Figure 3C). The other 7 curves are the individual riboleukograms of the patients in the validation cohort. The inset magnifies the trajectories of patients 13–17 (see Table 1) and demonstrates abrupt changes in riboleukogram course typically coincident with an increase in CPIS score (first occurrence of maximal CPIS value is indicated by the arrows). The paths of patients 13, 18 and 19, are atypical (see text for additional details). (B) The aggregate 11 patient VAP riboleukogram (black curve, same as panel A) is compared to the aggregate riboleukogram of all patients aligned by study day (that is, training and validation cohorts, irrespective of VAP day of diagnosis, dotted blue curve). Note that the VAP riboleukogram deviates from the “critical illness” riboleukogram (black arrows) prior to VAP diagnosis (lighting bolt), but after treatment, the VAP riboleukogram converges with the critical illness riboleukogram at the point of recovery. The green and red circles indicate where the patients entered and exited the study, respectively.
Mentions: A second cohort of 7 patients was analyzed to evaluate the informational value of the 85 genes that were identified in the first 11 patients with VAP. Two of these 7 additional patients were diagnosed with “late” VAP by the attending physician, while another 2 cases were described by the attending as “possible” VAP (Table 1). The individual riboleukograms for these 7 patients demonstrate the existence of immune recovery (basins of attraction) as well as the heterogeneity of the host response. In general, the individual riboleukograms follow a path moving from left to right, that is, from critical illness to recovery (Figure 6, green and red shaded areas, respectively). The development of an infectious complication is typically associated with a change in riboleukogram trajectory. For example, the paths of patients 13, 14, 15, 16, and 17 change directions abruptly coincident with changes in clinical status and concern for VAP or sepsis (see Figure 6A inset). Patient 17 grew Staphylococcus aureus from both urine and tracheal secretions prior to withdrawal of therapy for cure (the only death in the study). In contrast, the riboleukograms of patients 13, 18, and 19 are atypical, in that their paths do not start and/or do not finish with the others. Both patients 18 and 19 had pulmonary contusions secondary to polysystem trauma, maximal CPIS scores of 7 and 9, Gram-positive cocci cultured from airway secretions, and were treated with antibiotics, but had a clinical course labeled by the attending physician as “possible” VAP. Their riboleukograms are in different portions of the graph in Figure 6A, but have a similar shape and slope. Both patients 13 and 18 had intracranial hemorrhage. Patient 13 was not diagnosed with VAP (no infiltrate on CXR) but was treated with antibiotics for a fever of 39.4°C and WBC of 31,300 (day 5), tracheal secretions that subsequently grew out Acinetobacter and Stenotrophomonas (CPIS 6), and concern for catheter-related sepsis.

Bottom Line: Significant heterogeneity of VAP microarray profiles was observed secondary to patient ethnicity, age, and gender, yet 85 genes were identified with consistent changes in abundance during the seven days bracketing the diagnosis of VAP.Principal components analysis of these 85 genes appeared to differentiate between the responses of subjects who did versus those who did not develop VAP, as defined by a general trajectory (riboleukogram) for the onset and resolution of VAP.Moreover, riboleukograms may help explain variance in the host response due to differences in ethnic background, gender, and pathogen.

View Article: PubMed Central - PubMed

Affiliation: Center for Critical Illness and Health Engineering, Department of Surgery, Washington University in St. Louis, St. Louis, Missouri, USA.

ABSTRACT

Background: Diagnosis of acute infection in the critically ill remains a challenge. We hypothesized that circulating leukocyte transcriptional profiles can be used to monitor the host response to and recovery from infection complicating critical illness.

Methodology/principal findings: A translational research approach was employed. Fifteen mice underwent intratracheal injections of live P. aeruginosa, P. aeruginosa endotoxin, live S. pneumoniae, or normal saline. At 24 hours after injury, GeneChip microarray analysis of circulating buffy coat RNA identified 219 genes that distinguished between the pulmonary insults and differences in 7-day mortality. Similarly, buffy coat microarray expression profiles were generated from 27 mechanically ventilated patients every two days for up to three weeks. Significant heterogeneity of VAP microarray profiles was observed secondary to patient ethnicity, age, and gender, yet 85 genes were identified with consistent changes in abundance during the seven days bracketing the diagnosis of VAP. Principal components analysis of these 85 genes appeared to differentiate between the responses of subjects who did versus those who did not develop VAP, as defined by a general trajectory (riboleukogram) for the onset and resolution of VAP. As patients recovered from critical illness complicated by acute infection, the riboleukograms converged, consistent with an immune attractor.

Conclusions/significance: Here we present the culmination of a mouse pneumonia study, demonstrating for the first time that disease trajectories derived from microarray expression profiles can be used to quantitatively track the clinical course of acute disease and identify a state of immune recovery. These data suggest that the onset of an infection-specific transcriptional program may precede the clinical diagnosis of pneumonia in patients. Moreover, riboleukograms may help explain variance in the host response due to differences in ethnic background, gender, and pathogen. Prospective clinical trials are indicated to validate our results and test the clinical utility of riboleukograms.

Show MeSH
Related in: MedlinePlus