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. 2009 Oct;67(4):792-801.
doi: 10.1097/TA.0b013e31819d9c04.

Hemorrhage and subsequent allogenic red blood cell transfusion are associated with characteristic monocyte messenger RNA expression patterns in patients after multiple injury-a genome wide view

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Hemorrhage and subsequent allogenic red blood cell transfusion are associated with characteristic monocyte messenger RNA expression patterns in patients after multiple injury-a genome wide view

Viktoria Bogner et al. J Trauma. 2009 Oct.

Abstract

Introduction: As outcome to severe trauma is frequently affected by massive blood loss and consecutive hemorrhagic shock, replacement of red blood cell (RBC) units remains indispensable. Administration of RBC units is an independent risk factor for adverse outcome in patients with trauma. The impact of massive blood transfusion or uncrossmatched blood transfusion on the patients' immune response in the early posttraumatic period remains unclear.

Material: Thirteen patients presenting with blunt multiple injuries (Injury Severity Score >16) were studied. Monocytes were obtained on admission and at 6, 12, 24, 48, and 72 hours after trauma. Biotinylated complementary RNA targets were hybridized to Affymetrix HG U 133A microarrays. The data were analyzed by a supervised analysis based on whether the patients received massive blood transfusions, and then subsequently, by hierarchical clustering, and by Ingenuity pathway analysis.

Results: Supervised analysis identified 224 probe sets to be differentially expressed (p < 0.001) in patients who received massive blood transfusion, when compared with those who did not. In addition, 331 probe sets were found differentially expressed (p < 0.001) in patients who received uncrossmatched RBC units in comparison with those who exclusively gained crossmatched ones. Functional pathway analysis of the respectively identified gene expression profiles suggests a contributory role by the AKT/PI3Kinase pathway, the mitogen-activated protein-kinase pathway, the Ubiquitin pathway, and the diverse inflammatory networks.

Conclusion: We exhibited for the first time a serial, sequential screening analysis of monocyte messenger RNA expression patterns in patients with multiple trauma indicating a strongly significant association between the patients' genomic response in blood monocytes and massive or uncrossmatched RBC substitution.

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Figures

Figure 1
Figure 1
Supervised analysis of massive RBC transfusion: This graph depicts the hierarchical cluster analysis of the 224 probe sets, which are differentially expressed (p < 0.001) in the subjects depending on the amount of administered RBC units. The arrays clustering on the left hand side of the figure belong to patients having received less than 10 RBC units (3,000 mL erythrocyte concentrate, n = 9) during the first 24-hour posttrauma, whereas the cluster on the right hand side consists of arrays from patients who underwent massive blood transfusion (more than 10 RBC units, n = 4).
Figure 2
Figure 2
Supervised analysis of UORBC transfusion. The hierarchical cluster analysis of the 331 probe sets, which are differentially expressed (p < 0.001) in the patients who were supplied with UORBC units, when compared with those who exclusively gained crossmatched RBC units. The arrays clustering on the left hand side of the graph belong to patients having received UORBC units (n = 7) during the first 72-hour posttrauma, whereas the cluster on the right hand side consists of arrays from patients who were resuscitated with crossmatched RBC units only (n = 6).
Figure 3
Figure 3
Pathway analysis of the massive transfusion gene set. A functional network of the pathway analysis of the 224 identified probe sets concerning the criterion “moderate versus massive RBC transfusion.” Interestingly, this network connects elements of the PI3K/AKT pathway and the MAP-Kinase pathway. Red colored gene symbols show an upregulation of gene expression in the patient collective who underwent massive transfusion, and gene symbols in green stand for downregulation in this patient collective. For patients with moderate RBC transfusion, the coloring counts vice versa. The color intensity additionally correlates with the extent of the gene expression change between the two clinical groups. The probability to generate this network by chance alone is 10−21.
Figure 4
Figure 4
Pathway analysis of the UORBC transfusion gene set, network 1: the first functional network of the pathway analysis of the 331 identified probe sets concerning the criterion “transfusion of crossmatched versus uncrossmatched RBC units.” The main field of duty of these differentially expressed gene products consists in pro- and antiinflammatory immune system regulation. Red colored gene symbols show an upregulation of gene expression in the patient collective with UORBC unit application, beyond that, color encoding is equally managed as in the precedent analysis. The probability to generate this network by chance alone is 10−59.

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References

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