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

Genes informational in distinguishing clinical phenotypes of interest, including host gender, age, and ethnic background, with the caveats that all African-Americans and all middle-aged individuals were female (Table 1).Note that the largest number of probe sets were associated with differences in ethnic background (African-American compared to Caucasian). Of note, as opposed to the mouse response, there we no genes that differentiated between the human response to bacterial cell wall products (Gram negative versus Gram-positive bacteria), suggesting that signal variance due to ethnic background, gender, and age is greater than that due to infecting organism.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2215774&req=5

pone-0001564-g004: Genes informational in distinguishing clinical phenotypes of interest, including host gender, age, and ethnic background, with the caveats that all African-Americans and all middle-aged individuals were female (Table 1).Note that the largest number of probe sets were associated with differences in ethnic background (African-American compared to Caucasian). Of note, as opposed to the mouse response, there we no genes that differentiated between the human response to bacterial cell wall products (Gram negative versus Gram-positive bacteria), suggesting that signal variance due to ethnic background, gender, and age is greater than that due to infecting organism.

Mentions: Three patients exhibited contrary gene expression profiles within two of these four clusters (Figure 3A). Patients 1, 7 and 11 showed decreased expression of genes in cluster 2 and patients 7 and 11 showed increased expression of genes in clusters 3 and 4. Based on patient demographics (Table 1 and data not shown), the only clear difference between patients 7 and 11 and the other patients in the study is that these two patients developed VAP later in their ICU course (study day 18 and 14 respectively) whereas the remaining patients developed VAP between study days 3 and 6. This was also evident in PCA analysis of the 11 individual trajectories (data not shown). The changes in transcript abundance of selected genes were validated by quantitative RT-PCR (Figure S1). Finally, we tested whether host ethnicity, host gender, host age, or the cell wall phenotype of the infectious agent had an effect on the number of informational genes. The most informational of these demographic variables was host ethnicity (Figure 4).


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)

Genes informational in distinguishing clinical phenotypes of interest, including host gender, age, and ethnic background, with the caveats that all African-Americans and all middle-aged individuals were female (Table 1).Note that the largest number of probe sets were associated with differences in ethnic background (African-American compared to Caucasian). Of note, as opposed to the mouse response, there we no genes that differentiated between the human response to bacterial cell wall products (Gram negative versus Gram-positive bacteria), suggesting that signal variance due to ethnic background, gender, and age is greater than that due to infecting organism.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0001564-g004: Genes informational in distinguishing clinical phenotypes of interest, including host gender, age, and ethnic background, with the caveats that all African-Americans and all middle-aged individuals were female (Table 1).Note that the largest number of probe sets were associated with differences in ethnic background (African-American compared to Caucasian). Of note, as opposed to the mouse response, there we no genes that differentiated between the human response to bacterial cell wall products (Gram negative versus Gram-positive bacteria), suggesting that signal variance due to ethnic background, gender, and age is greater than that due to infecting organism.
Mentions: Three patients exhibited contrary gene expression profiles within two of these four clusters (Figure 3A). Patients 1, 7 and 11 showed decreased expression of genes in cluster 2 and patients 7 and 11 showed increased expression of genes in clusters 3 and 4. Based on patient demographics (Table 1 and data not shown), the only clear difference between patients 7 and 11 and the other patients in the study is that these two patients developed VAP later in their ICU course (study day 18 and 14 respectively) whereas the remaining patients developed VAP between study days 3 and 6. This was also evident in PCA analysis of the 11 individual trajectories (data not shown). The changes in transcript abundance of selected genes were validated by quantitative RT-PCR (Figure S1). Finally, we tested whether host ethnicity, host gender, host age, or the cell wall phenotype of the infectious agent had an effect on the number of informational genes. The most informational of these demographic variables was host ethnicity (Figure 4).

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