Skip to main content
Download PDF

Science review: Searching for gene candidates in acute lung injury

Critical Care volume 8, Article number: 440 (2004) Cite this article

Abstract

Acute lung injury (ALI) is a complex and devastating illness, often occurring within the setting of sepsis, and carries an annual mortality rate of 30–50%. Although the genetic basis of ALI has not been fully established, an increasing body of evidence suggests that genetic predisposition contributes to disease susceptibility and severity. Significant difficulty exists, however, in defining the exact nature of these genetic factors, including large phenotypic variance, incomplete penetrance, complex gene–environment interactions, and strong potential for locus heterogeneity. We utilized the candidate gene approach and an ortholog gene database to provide relevant gene ontologies and insights into the genetic basis of ALI. We employed a Medline search of selected basic and clinical studies in the English literature and studies sponsored by the HopGene National Institutes of Health sponsored Program in Genomic Applications. Extensive gene expression profiling studies in animal models of ALI (rat, murine, canine), as well as in humans, were performed to identify potential candidate genes http://www.hopkins-genomics.org/. We identified a number of candidate genes for ALI, with blood coagulation and inflammation gene ontologies being the most highly represented. The candidate gene approach coupled with extensive gene profiling and novel bioinformatics approaches is a valuable way to identify genes that are involved in ALI.

Introduction

Acute lung injury (ALI) is a common and devastating illness that most often occurs in the setting of sepsis [1]. Despite impressive technologic advances in our ability to monitor this critically ill population, ALI continues to carry an annual mortality rate of 30–50%. Recently, advances in the management of patients with ALI with low tidal volume ventilation offered hope that combined mechanistic and physiologically sound approaches to ALI may further reduce mortality from this illness [2]. Our understanding of the pathogenesis of sepsis and ALI recently improved with the appreciation that inflammation is a fundamental component of the pathophysiology and is exacerbated by conventional or high tidal volume ventilation [3]. Unfortunately, these insights have not fully been translated into novel and effective strategies designed to increase survival. Furthermore, our improved understanding of ALI at both the molecular and population levels has not provided an explanation for the heterogeneity in patient susceptibility and outcome. Clearly, both genetic and environmental factors must be involved. Although the genetic basis of ALI has not been fully established, an increasing body of evidence suggests that genetic predisposition contributes to disease susceptibility and severity [4–7]. Why do some patients with Gram-negative sepsis develop ALI whereas others do not? Why is low tidal ventilation of great benefit in some patients and not in others? What are the genetic determinants that convey risk for progression to multiorgan failure in patients with ALI? A complete understanding of the genetic basis of ALI susceptibility and disease severity would address these important questions.

Because ALI is a complex illness, alterations in specific illness genes will probably not explain the physiologic derangements fully. Large phenotypic variance, incomplete penetrance, complex gene–environment interactions, and potential locus heterogeneity all make genetic evaluation of ALI difficult. Moreover, the sporadic nature of ALI makes a conventional genomic approach such as linkage mapping (or 'positional cloning') impossible. Briefly, linkage mapping involves scanning entire genomes of families affected by an illness using known regularly spaced variable DNA segments, thus identifying those genetic variants (alleles) that are shared by affected family members more frequently than would be expected based on chance [8]. These regions can then be isolated and cloned, and further evaluated as disease genes. One advantage of linkage mapping is that investigators need no prior knowledge of the biology underlying an illness; this is especially important in complex disorders such as sepsis and ALI. However, this approach has the disadvantage of requiring large families with both affected and unaffected individuals. This is a major limitation to the use of linkage mapping in the evaluation of ALI, given the sporadic nature, low incidence, and lack of affected families associated with this illness.

The candidate gene approach refers to a strategy for investigating the genetic basis of complex illnesses such as ALI, which can be performed using unrelated cases and controls. In the candidate gene approach, investigators study the association between variants (polymorphisms) in a certain gene, or allele and a specific disease by studying the frequency of the target variant allele in a population of affected patients and comparing this with the frequency in controls. Unlike linkage mapping, this approach requires an element of prior knowledge of disease pathogenesis so that candidate genes can be identified. Of particular interest in the candidate gene approach are publicly available databases of single nucleotide polymorphisms (SNPs; http://www.ncbi.nlm.nih.gov/SNP). Studying an association between one or more SNPs and a disease can help researchers to focus on certain areas of DNA and potentially identify candidate genes.

In the absence of significant insights into disease pathogenesis, comprehensive gene array analysis of tissues derived from animal models of disease is also often helpful in identifying candidate genes. However, this presents a difficult challenge in determining how best to analyze the unprecedented quantities of data generated by these approaches. In September 2000, the US National Heart, Lung, and Blood Institute launched the Programs for Genomic Applications (PGAs), funding 11 centers to generate novel data and resources for the research community at large in order to advance functional genomic research related to heart, lung, blood, and sleep disorders. These resources include state of the art software programs for array analysis and normalization, SNP analysis, phenotyping of animal models of disease, and a rich array of analytical tools (summarized and updated on the PGA homepage: http://www.nhlbi.nih.gov/resources/pga). Several PGAs are working to discover and model the associations between single nucleotide sequence differences in the genes and pathways that underlie interindividual variation in inflammatory responses and their relationship to disease risk, outcome, and treatments in common human lung disorders, including ALI. For example, the HopGene PGA website http://www.hopkins-genomics.org/ contains extensive array data for rat, murine, and canine models of ALI, ALI candidate genes with preliminary evaluation for relevant SNPs, and preliminary genotyping of these genes in controls and patients with sepsis and ALI. In this review we explain how the candidate gene approach has provided a menu of gene ontologies that may help to unravel the genetics and pathogenesis of ALI and, most importantly, to identify novel targets for therapy.

One approach to the identification of genes relevant to ALI susceptibility and severity is to examine general trends in the expression of common groups of genes in response to ALI in diverse species. This commonality might relate to unsuspected evolutionarily conserved responses to lung injury. At the same time, known biologic pathways and genes, either activated or suppressed in ALI, can be used as a validation of novel candidate genes that are implicated in the same pathway [9]. Figure 1 illustrates the HopGene approach to searching for candidate genes involved in ALI expression, as defined as the response to increased mechanical stress delivered by increased tidal volume ventilation or to cyclic stretching of human endothelium in vitro. Gene expression alterations in response to mechanical ventilation alone, in the absence of additional inflammatory stimuli, are easily detected by microarray techniques, and they may therefore provide a powerful framework on which to characterize normal lung responses to mechano-transduction stresses. Responses of four different biological systems (rat, mouse, dog, and human endothelial cell culture) to levels of mechanical stretch relevant to ALI were investigated (Fig. 1). The control and ventilated lung samples were collected at the time point at which the defining feature of ALI (i.e. vascular leakage) was detected in each animal model [9]. The total mRNA extracted from obtained tissues was hybridized to corresponding species-specific Affymetrix GeneChip (Santa Clara, CA, USA). Generated gene expression profiles from different species-specific platforms were linked using RESOURCERER – the PGA developed ortholog linking tool [10].

Figure 1
figure 1

The approach to identify mechanical stress induced candidate genes using schematic representation of cross-species ortholog database and gene ontology processes. Total RNA from rat, mouse, and canine ventilator-injured lung tissues and human endothelial cell cultures exposed to injurious mechanical stretch was extracted, and gene expression data were generated by hybridization of corresponding total mRNAs to HG-U34A, HG-U74A, HG-U133A, and HG-U95A Affymetrix arrays, respectively. These steps were performed at the PGA-HopGene center. Gene expression profiles were analyzed by the HopGene PGA center using in silico multispecies cross-platform database applying the RESOURCERER tool designed by the TIGR PGA center. Gene ontology assignment and analysis was conducted by HopGene PGA center using the MAPPFinder tool designed by the BayGenomics PGA center. The acute lung injury (ALI)-related ontologic groups were selected using filtering conditions described in Table 1. The contribution of each bioprocess to ALI is represented as the percentage of values calculated by MAPPFinder and shown in the percentage changed genes column. The literature search was done by the HopGene PGA center using PubMatrix tool designed by PGA collaborators at the National Institute on Aging, National Institutes of Health.

Full size image

Gene ontologies generated by the Gene Ontology™ Consortium http://www.geneontology.org were assigned to corresponding genes using PGA developed tools GenMAPP and MAPPFinder [11, 12]. Genes with change in expression of 20% or higher and a false discovery rate of less than 10% were selected from the microarray data derived from the four mechanical stress-challenged species. This relaxed filtering approach was introduced by Munson and other speakers at the Symposium on the Functional Genomics of Critical Illness and Injury [13] and was successfully applied for selection of candidate genes [14]. This approach is especially suited to identification of genes with elevated basal expression levels, upregulation of which will not produce a high fold change ratio, meaning that these genes will be missed by more stringent conditions. The slight increase in false discovery rate will be applied equally throughout all gene ontologies and will not affect individual ontology selection.

Selected using this approach, stretch-affected genes were dynamically linked to an expansive menu of known gene ontologies using MAPPFinder tool developed by the PGA-BayGenomics Center (Fig. 1). The MAPPFinder analyzed total of 1329 bioprocesses and selected 32 related to ALI (Z > 2.0). Further filtering for bioprocesses that had five or more involved genes (number of changed genes column Table 1) and exclusion of broadly defined terms such 'signal transduction' revealed five prominent mechanical stretch-related ALI biological processes with different degrees of contribution to this injury (Table 1; the unfiltered MAPPFinder output is provided in Additional file 1). A total of 49 genes were involved in these bioprocesses (Table 1, number of changed genes), of which 10 genes were involved in two bioprocesses and three genes in three bioprocesses simultaneously (Table 2). Thus, the actual candidate list comprised 33 individual genes.

Table 1 Biological processes identified by MAPPFinder based on gene expression
Full size table
Table 2 Candidate genes in acute lung injury
Full size table

Negative regulation of cell proliferation ontology

IL-1ß and IL-6 were the most commonly upregulated ALI-related genes that were cited as lung injury related in 287 and 173 references, respectively (Table 2). IL-6 is differentiation factor cytokine with activity toward a wide variety of biologic systems [15–17] and IL-1ß is involved regulating multiple biological pathways, including inflammatory and immune responses and immune cell differentiation [18]. Clinical studies showed that IL-1ß and IL-6 concentrations in bronchoalveolar lavage fluid from patients with established severe ALI (acute respiratory distress syndrome) were higher than in bronchoalveolar lavage fluid from normal volunteers [19, 20]. Moreover, IL-1ß was self-sufficient in causing acute lung tissue injury when overexpressed in mouse lungs [21] and was directly related to ALI in another mouse model [22]. Consistent with current concepts of the role played by the ventilator in ALI, studies by Copland and coworkers [23] identified upregulation of IL-1ß, with cluster analysis confirming linked expression of these genes; this is again consistent with very early signal amplification, which begins to evolve a mechanically stimulated inflammatory phenotype.

The most interesting ALI related candidate genes in this ontological group were B-cell translocation (BTG) and type-2 phosphatidic acid phosphohydrolase (PAP2) genes. Microarray analysis of alveolar microphages [24] showed that expression of BTG-2 was stimulated by diesel exhaust particles, which are a known cause of adverse respiratory system reactions. The correlation between high expression of BTG-2 transcript and cell death was reported for the alveolar epithelial A549 cell line [25]. Our microarray analysis revealed a trend toward upregulation of another candidate gene, BTG-1, in mechanical stretch challenged human pulmonary artery endothelial cells. These finding suggest that the BTG gene family is ubiquitously represented in lung tissues and could be a viable candidate for further investigation.

Another potential candidate for involvement in ALI is the PAP2 gene, which encodes sphingosine-1-phosphate (S1P) and ceramide-1-phosphatases, which are degrading plasma membrane enzymes. It has been reported that pulmonary phosphatidic acid phosphohydrolases directly control surfactant secretion and indirectly regulate cell division, differentiation, apoptosis, and mobility through lowering S1P levels (see review by Nanjundan and Possmayer [26]). As we previously showed, S1P possess properties that are protective against inflammatory lung injury [27] and vascular leakage [28, 29], and therefore the S1P regulating enzyme became a very attractive ALI-related candidate. Moreover, our group also linked S1P effects to chemotaxis, which is yet another gene ontology identified by our candidate gene approach. We demonstrated that S1P regulates secretion of the potent chemo-attractant IL-8 in human bronchial epithelial cells [30] and regulates endothelial cell chemotaxis [31].

Immune response ontology

The gene encoding the cytokine IL-13, similar to another ontology member, namely cytokine IL-1ß, described above, is involved in multiple biologic pathways (Table 1). It has been shown that this cytokine has protective properties and attenuates vascular leakage during lung injury inflicted by IgG immune complexes [32]. Further investigations linked this IL-13 protective effect to pulmonary vascular endothelium. Corne and coworkers [33] showed that IL-13 exerts its effects in part by stimulating pulmonary isoform-specific vascular endothelium growth factor accumulation.

Another gene assigned to this ontology, the VNT gene, which encodes vitronectin, is also involved in pulmonary vascular permeability regulation. Binding of the VNT gene product to avß3 integrin receptor increases vascular leak and activates an integrin-induced proinflammatory response [34]. Interestingly, the avß3 integrin receptor was found on the luminal and abluminal faces of the lung microvascular endothelium and could not be detected on the apical surface of the alveolar epithelium [35].

The same gene product distribution pattern was described for the candidate gene IL1R2 (HopGene Candidate Gene List), which encodes IL-1 receptor type II; based on a cyclic stretch model in human pulmonary endothelial cells [36], this gene was previously selected by our group. Later, overexpression of this gene was confirmed in our in vivo ALI models. The lack of expression of IL1R2 – the ligand of which, IL-1ß, is a central cytokine in ALI – by epithelial cells [37] suggests that this candidate gene also is integrated into the vascular component of ALI. These and other observations throughout the present review relate most of the selected genes to the pulmonary vasculature, which seems crucial to the development of ALI.

Inflammatory response and chemotaxis ontologies

These ontologies were heavily represented by diverse cytokines and cytokine receptors (Table 2). The CC chemokine-2 and the CC chemokine receptor-5 genes were reported to be involved in several lung inflammatory disorders [38] and in amplifying inflammation in lung [39], respectively.

The gene encoding CXC chemokine ligand (CXCL)2 was recently linked to ventilator-induced ALI [40] and hyperoxia-induced ALI [41], and it contributes to three out of five identified ALI-related bioprocesses. CXCL2 is involved in the inflammatory response as a potent neutrophil chemoattractant, and inhibition of its receptor (CXC chemokine receptor [CXCR]2) leads to a marked reduction in neutrophil sequestration and lung injury [40]. A similar expression and ontology pattern to CXCL2 is noted for another chemokine receptor, namely CXCR4, which is expressed by human bronchial epithelial cells [42]. It has been shown that this receptor is heavily involved in allergic airway processes [43] and promotes small cell lung cancer cell migration by altering cytoskeletal regulation [44]. The role of this potential candidate gene in ALI is yet to be identified, but the similarity in expression, bioprocess involvement, and comparable upregulation of CXCL2 and CXCR4 by IL-1ß [42, 45] warrant further investigation of the involvement of CXCR4 in ALI.

Another candidate gene regulated by IL-1ß, namely that which encodes annexin1 (ANXA1), is involved in these ontologies (Table 2) and limits neutrophil infiltration and reduces production of inflammatory mediators in vivo [46] by mimicking the effects of steroids at inflammatory sites [47]. This suggests a tightly IL-1ß regulated mechanism of neutrophil migration out of the bloodstream and into lung tissues during development of ALI.

The enzyme gene family was represented by the prostaglandin-endoperoxide synthase 2/cyclo-oxygenase-2 gene, the product of which is involved in eicosanoid synthesis and appears to be important in both edemagenesis and the pattern of pulmonary perfusion in experimental ALI. Gust and coworkers [48] showed that the effect of endotoxin on pulmonary perfusion in ALI could be in part the result of activation of inducible cyclo-oxygenase-2. Upregulation of the cyclo-oxygenase-2 gene is also linked to increased pulmonary microvascular permeability during combined burn and smoke inhalation injury in a sheep model [49].

There is evidence of epithelial involvement in ALI, such as upregulation of the CCAAT enhancer binding protein gene (C/EBP), which regulates [50] expression of surfactant proteins A and D; these are heavily involved in pulmonary host defense and innate immunity [51] during ALI [52, 53]. However, the number of candidate genes related to vascular endothelium, as was mentioned above, is striking. The following gene ontology was completely represented by vasculature related genes.

Blood coagulation ontology

That involvement of the blood coagulation pathway was identified in ALI-related bioprocesses is not unexpected. There are several reports of increased levels of coagulation factor III (tissue factor) and plasminogen activator inhibitor type 1 in patients with ALI [54–56] and ventilator-induced lung injury [57, 58]. Fibrinogen A and plasminogen activator, urokinase receptor are involved in IL-1ß signaling and regulation, respectively. It has been shown that fibrinogen indirectly activates transcription of IL-1ß [59], which in turn increases expression of urokinase receptor [60]. Urokinase-type plasminogen activated receptor (uPAR) was assigned to blood coagulation and chemotaxis pathways by our approach (Table 2), and represents direct linkage between these two biological processes. It has been shown that uPAR not only promotes degradation of fibrin but also confers adhesive properties to cells by binding vitronectin. Staining of lung biopsy specimens from patients with ALI indicated that fibrin and vitronectin colocalize at exudative sites where macrophages bearing uPAR accumulate [61]. Opposite to expression of the PLAUR gene (which encodes plasminogen activator, urokinase receptor), downregulation of the VNT gene (Table 2) suggests dual regulatory mechanisms of macrophage sequestration at the injury site. Another downregulated gene was that which encodes plasma prekallikrein (KLKB1). It has been shown that prekallikrein not only participates in blood coagulation in tandem with factor XII [62] but also is a major source of bradykinin (potent stimulus of vascular permeability) during the inflammatory response [63].

This interconnection of coagulation and inflammation is well recognized in that inflammation leads to increased coagulation, and the two are linked by the vascular endothelium, which is particularly relevant to ALI (see review by Russell [64]). The cytokines IL-1ß and IL-6 activate neutrophils and monocytes, which in turn alter endothelial integrity. Furthermore, platelets bind to the injured endothelial surface and trigger a procoagulant and inflammatory response. These cytokines also directly activate tissue factor and plasminogen activator inhibitor type 1, which lead to activation of the extrinsic pathway of coagulation and inhibition of fibrinolysis, respectively. There is some evidence that the 'crosstalk' between coagulation and inflammation can be reversed. It has been shown that blood coagulation in vitro stimulates release of inflammatory mediators from neutrophils and endothelial cells [65, 66]. Based on these reports and data generated by our cross-species analysis of ALI, we speculated that mechanical stretch causes the initial injury to the pulmonary endothelium, which is followed by platelet aggregation at the damaged site and activation of the coagulation cascade. Therefore, procoagulation genes become major players in early stages of the onset of ALI, and then proinflammatory genes become upregulated and promote further ALI development. In order to prove or disprove this hypothesis, further studies of ALI are needed, especially time course analysis of the expression patterns of selected candidate genes in response to ALI.

Conclusion

Our data suggest that combined gene expression and gene ontology analyses of ortholog-linked multiple ALI models can be useful tools in selecting candidate genes that are involved in this patho-biologic process. We showed that 18 out of 33 genes selected by our procedure were previously linked to ALI. These results strongly implicate the other 15 selected genes as potential ALI-related candidates. Further analysis of these candidate genes may provide insight into the mechanisms of ALI and uncover unsuspected evolutionarily conserved targets that may lead to therapeutic strategies in this illness. The genetic determinants that render patients susceptible to the adverse effects of mechanical ventilation in the setting of ALI are unknown. The identification of novel therapeutic targets is essential if progress is to be made in the treatment of this condition. New molecular targets will be deduced from genetic susceptibility loci for ventilator-associated lung injury and evaluated. This approach will help to unravel the pathophysiologic mechanisms of ventilator-associated lung injury and will accelerate the development of therapies for this devastating disease.

Abbreviations

ALI:

acute lung injury

CXCL:

CXC chemokine ligand

CXCR:

CXC chemokine receptor

IL:

interleukin

PGA:

Program for Genomic Applications

S1P:

sphingosine-1-phosphate

SNP:

single nucleotide polymorphism

uPAR:

urokinase-type plasminogen activated receptor.

References

  1. Ware LB, Matthay MA: The acute respiratory distress syndrome. N Engl J Med 2000, 342: 1334-1349. 10.1056/NEJM200005043421806

    CAS  Article  PubMed  Google Scholar 

  2. The Acute Respiratory Distress Syndrome Network: Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. N Engl J Med 2000, 342: 1301-1308. 10.1056/NEJM200005043421801

    Article  Google Scholar 

  3. Zhang H, Downey GP, Suter PM, Slutsky AS, Ranieri VM: Conventional mechanical ventilation is associated with bronchoalveolar lavage-induced activation of polymorphonuclear leukocytes: a possible mechanism to explain the systemic consequences of ventilator-induced lung injury in patients with ARDS. Anesthesiology 2002, 97: 1426-1433. 10.1097/00000542-200212000-00014

    Article  PubMed  Google Scholar 

  4. Prows DR, McDowell SA, Aronow BJ, Leikauf GD: Genetic susceptibility to nickel-induced acute lung injury. Chemosphere 2003, 51: 1139-1148. 10.1016/S0045-6535(02)00710-5

    CAS  Article  PubMed  Google Scholar 

  5. Villar J, Flores C, Mendez-Alvarez S: Genetic susceptibility to acute lung injury. Crit Care Med 2003, (Suppl):S272-S275. 10.1097/01.CCM.0000057903.11528.6D

  6. Leikauf GD, McDowell SA, Wesselkamper SC, Hardie WD, Leikauf JE, Korfhagen TR, Prows DR: Acute lung injury: functional genomics and genetic susceptibility. Chest 2002, (Suppl):70S-75S. 10.1378/chest.121.3_suppl.70S

  7. Wesselkamper SC, Prows DR, Biswas P, Willeke K, Bingham E, Leikauf GD: Genetic susceptibility to irritant-induced acute lung injury in mice. Am J Physiol Lung Cell Mol Physiol 2000, 279: L575-L582.

    CAS  PubMed  Google Scholar 

  8. Kwon JM, Goate AM: The candidate gene approach. Alcohol Res Health 2000, 24: 164-168.

    CAS  PubMed  Google Scholar 

  9. Grigoryev DN, Ma S-F, Irrizari RI, Ye SQ, Quackenbush J, Garcia JGN: Orthologous gene-expression profiling in multi-species models: search for candidate genes. Genome Biol 2004, 5: R34. 10.1186/gb-2004-5-5-r34

    PubMed Central  Article  PubMed  Google Scholar 

  10. Tsai J, Sultana R, Lee Y, Pertea G, Karamycheva S, Antonescu V, Cho J, Parvizi B, Cheung F, Quackenbush J: RESOURCERER: a database for annotating and linking microarray resources within and across species. Genome Biol 2001, 2: software0002.1-0002.4. 10.1186/gb-2001-2-11-software0002

    Article  Google Scholar 

  11. Dahlquist KD, Salomonis N, Vranizan K, Lawlor SC, Conklin BR: GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways. Nat Genet 2002, 31: 19-20. 10.1038/ng0502-19

    CAS  Article  PubMed  Google Scholar 

  12. Doniger SW, Salomonis N, Dahlquist KD, Vranizan K, Lawlor SC, Conklin BR: MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data. Genome Biol 2003, 4: R7. 10.1186/gb-2003-4-1-r7

    PubMed Central  Article  PubMed  Google Scholar 

  13. Munson PJ: Mining a gene expression database. In Proceedings of the 2nd Annual Symposium on the Functional Genomics of Critical Illness and Injury Bethesda, Maryland; National Institutes of Health 2003, 35.

    Google Scholar 

  14. Jison ML, Munson PJ, Barb JJ, Suffredini AF, Talwar S, Logun C, Raghavachari N, Beigel JH, Shelhamer JH, Danner RL, Gladwin MT: Blood mononuclear cell gene expression profiles characterize the oxidant, hemolytic and inflammatory stress of sickle cell disease. Blood 2004, 104: 270-280. epub 2004 Mar 18. PMID: 15031206 10.1182/blood-2003-08-2760

    CAS  Article  PubMed  Google Scholar 

  15. Lieskovska J, Guo D, Derman E: Growth impairment in IL-6-overexpressing transgenic mice is associated with induction of SOCS3 mRNA. Growth Horm IGF Res 2003, 13: 26-35. 10.1016/S1096-6374(02)00135-1

    CAS  Article  PubMed  Google Scholar 

  16. Klein B, Tarte K, Jourdan M, Mathouk K, Moreaux J, Jourdan E, Legouffe E, De Vos J, Rossi JF: Survival and proliferation factors of normal and malignant plasma cells. Int J Hematol 2003, 78: 106-113.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  17. Diehl S, Rincon M: The two faces of IL-6 on Th1/Th2 differentiation. Mol Immunol 2002, 39: 531-536. 10.1016/S0161-5890(02)00210-9

    CAS  Article  PubMed  Google Scholar 

  18. Dinarello CA: The IL-1 family and inflammatory diseases. Clin Exp Rheumatol 2002, (Suppl 27):S1-S13.

  19. Park WY, Goodman RB, Steinberg KP, Ruzinski JT, Radella F II, Park DR, Pugin J, Skerrett SJ, Hudson LD, Martin TR: Cytokine balance in the lungs of patients with acute respiratory distress syndrome. Am J Respir Crit Care Med 2001, 164: 1896-1903.

    CAS  Article  PubMed  Google Scholar 

  20. Takala A, Jousela I, Takkunen O, Kautiainen H, Jansson SE, Orpana A, Karonen SL, Repo H: A prospective study of inflammation markers in patients at risk of indirect acute lung injury. Shock 2002, 17: 252-257. 10.1097/00024382-200204000-00002

    Article  PubMed  Google Scholar 

  21. Kolb M, Margetts PJ, Anthony DC, Pitossi F, Gauldie J: Transient expression of IL-1beta induces acute lung injury and chronic repair leading to pulmonary fibrosis. J Clin Invest 2001, 107: 1529-1536.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  22. Chess PR, Johnston CJ, Wright TW, Jordan HD: Murine model of mechanical ventilation-induced lung injury [abstract]. Am J Respir Crit Care Med 2003, 167: A625.

    Google Scholar 

  23. Copland IB, Kavanagh BP, Engelberts D, McKerlie C, Belik J, Post M: Early changes in lung gene expression due to high tidal volume. Am J Respir Crit Care Med 2003, 168: 1051-1059. 10.1164/rccm.200208-964OC

    Article  PubMed  Google Scholar 

  24. Verheyen GR, Nuijten JM, Van Hummelen P, Schoeters GR: Microarray analysis of the effect of diesel exhaust particles on in vitro cultured macrophages. Toxicol In Vitro 2004, 18: 377-391. 10.1016/j.tiv.2003.10.007

    CAS  Article  PubMed  Google Scholar 

  25. Chen JG, Yang CP, Cammer M, Horwitz SB: Gene expression and mitotic exit induced by microtubule-stabilizing drugs. Cancer Res 2003, 63: 7891-7899.

    CAS  PubMed  Google Scholar 

  26. Nanjundan M, Possmayer F: Pulmonary phosphatidic acid phosphatase and lipid phosphate phosphohydrolase. Am J Physiol Lung Cell Mol Physiol 2003, 284: L1-L23.

    CAS  Article  PubMed  Google Scholar 

  27. Peng X, Hassoun PM, Sammani S, McVerry BJ, Burne MJ, Rabb H, Pearse D, Tuder RM, Garcia JG: Protective effects of sphingosine 1-phosphate in murine endotoxin-induced inflammatory lung injury. Am J Respir Crit Care Med 2004, 169: 1245-1251. 10.1164/rccm.200309-1258OC

    Article  PubMed  Google Scholar 

  28. Dudek SM, Jacobson JR, Chiang ET, Birukov KG, Wang P, Zhan X, Garcia JG: Pulmonary endothelial cell barrier enhancement by sphingosine 1-phosphate: Roles for cortactin and myosin light chain kinase. J Biol Chem 2004, 279: 24692-24700. 10.1074/jbc.M313969200

    CAS  Article  PubMed  Google Scholar 

  29. Schaphorst KL, Chiang E, Jacobs KN, Zaiman A, Natarajan V, Wigley F, Garcia JG: Role of sphingosine-1 phosphate in the enhancement of endothelial barrier integrity by platelet-released products. Am J Physiol Lung Cell Mol Physiol 2003, 285: L258-L267.

    CAS  Article  PubMed  Google Scholar 

  30. Cummings RJ, Parinandi NL, Zaiman A, Wang L, Usatyuk PV, Garcia JG, Natarajan V: Phospholipase D activation by sphingosine 1-phosphate regulates interleukin-8 secretion in human bronchial epithelial cells. J Biol Chem 2002, 277: 30227-30235. 10.1074/jbc.M111078200

    CAS  Article  PubMed  Google Scholar 

  31. Liu F, Verin AD, Wang P, Day R, Wersto RP, Chrest FJ, English DK, Garcia JG: Differential regulation of sphingosine-1-phosphate- and VEGF-induced endothelial cell chemotaxis. Involvement of G(ialpha2)-linked Rho kinase activity. Am J Respir Cell Mol Biol 2001, 24: 711-719.

    CAS  Article  PubMed  Google Scholar 

  32. Mulligan MS, Warner RL, Foreback JL, Shanley TP, Ward PA: Protective effects of IL-4, IL-10, IL-12, and IL-13 in IgG immune complex-induced lung injury: role of endogenous IL-12. J Immunol 1997, 159: 3483-3489.

    CAS  PubMed  Google Scholar 

  33. Corne J, Chupp G, Lee CG, Homer RJ, Zhu Z, Chen Q, Ma B, Du Y, Roux F, McArdle J, Waxman AB, Elias JA: IL-13 stimulates vascular endothelial cell growth factor and protects against hyperoxic acute lung injury. J Clin Invest 2000, 106: 783-791.

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  34. Bhattacharya S, Patel R, Sen N, Quadri S, Parthasarathi K, Bhattacharya J: Dual signaling by the alpha(v)beta(3)-integrin activates cytosolic PLA(2) in bovine pulmonary artery endothelial cells. Am J Physiol Lung Cell Mol Physiol 2001, 280: L1049-L1056.

    CAS  PubMed  Google Scholar 

  35. Singh B, Fu C, Bhattacharya J: Vascular expression of the alpha(v)beta(3)-integrin in lung and other organs. Am J Physiol Lung Cell Mol Physiol 2000, 278: L217-L226.

    CAS  PubMed  Google Scholar 

  36. Birukov KG, Jacobson JR, Flores AA, Ye SQ, Birukova AA, Verin AD, Garcia JG: Magnitude-dependent regulation of pulmonary endothelial cell barrier function by cyclic stretch. Am J Physiol Lung Cell Mol Physiol 2003, 285: L785-L797.

    CAS  Article  PubMed  Google Scholar 

  37. Coulter KR, Wewers MD, Lowe MP, Knoell DL: Extracellular regulation of interleukin (IL)-1beta through lung epithelial cells and defective IL-1 type II receptor expression. Am J Respir Cell Mol Biol 1999, 20: 964-975.

    CAS  Article  PubMed  Google Scholar 

  38. Rose CE Jr, Sung SS, Fu SM: Significant involvement of CCL2 (MCP-1) in inflammatory disorders of the lung. Microcirculation 2003, 10: 273-288. 10.1038/sj.mn.7800193

    CAS  Article  PubMed  Google Scholar 

  39. Dixon AE, Mandac JB, Madtes DK, Martin PJ, Clark JG: Chemokine expression in Th1 cell-induced lung injury: prominence of IFN-gamma-inducible chemokines. Am J Physiol Lung Cell Mol Physiol 2000, 279: L592-L599.

    CAS  PubMed  Google Scholar 

  40. Belperio JA, Keane MP, Burdick MD, Londhe V, Xue YY, Li K, Phillips RJ, Strieter RM: Critical role for CXCR2 and CXCR2 ligands during the pathogenesis of ventilator-induced lung injury. J Clin Invest 2002, 110: 1703-1716. 10.1172/JCI200215849

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  41. Sue RD, Belperio JA, Burdick MD, Murray LA, Xue YY, Dy MC, Kwon JJ, Keane MP, Strieter RM: CXCR2 is critical to hyperoxia-induced lung injury. J Immunol 2004, 172: 3860-3868.

    CAS  Article  PubMed  Google Scholar 

  42. Eddleston J, Christiansen SC, Zuraw BL: Functional expression of the C-X-C chemokine receptor CXCR4 by human bronchial epithelial cells: regulation by proinflammatory mediators. J Immunol 2002, 169: 6445-6451.

    CAS  Article  PubMed  Google Scholar 

  43. Gonzalo JA, Lloyd CM, Peled A, Delaney T, Coyle AJ, Gutierrez-Ramos JC: Critical involvement of the chemotactic axis CXCR4/stromal cell-derived factor-1 alpha in the inflammatory component of allergic airway disease. J Immunol 2000, 165: 499-508.

    CAS  Article  PubMed  Google Scholar 

  44. Kijima T, Maulik G, Ma PC, Tibaldi EV, Turner RE, Rollins B, Sattler M, Johnson BE, Salgia R: Regulation of cellular proliferation, cytoskeletal function, and signal transduction through CXCR4 and c-Kit in small cell lung cancer cells. Cancer Res 2002, 62: 6304-6311.

    CAS  PubMed  Google Scholar 

  45. Saijo Y, Tanaka M, Miki M, Usui K, Suzuki T, Maemondo M, Hong X, Tazawa R, Kikuchi T, Matsushima K, Nukiwa T: Proinflammatory cytokine IL-1 beta promotes tumor growth of Lewis lung carcinoma by induction of angiogenic factors: in vivo analysis of tumor-stromal interaction. J Immunol 2002, 169: 469-475.

    CAS  Article  PubMed  Google Scholar 

  46. Perretti M, Chiang N, La M, Fierro IM, Marullo S, Getting SJ, Solito E, Serhan CN: Endogenous lipid- and peptide-derived anti-inflammatory pathways generated with glucocorticoid and aspirin treatment activate the lipoxin A4 receptor. Nat Med 2002, 8: 1296-1302. 10.1038/nm786

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  47. Cover PO, Baanah-Jones F, John CD, Buckingham JC: Annexin 1 (lipocortin 1) mimics inhibitory effects of glucocorticoids on testosterone secretion and enhances effects of interleukin-1beta. Endocrine 2002, 18: 33-39. 10.1385/ENDO:18:1:33

    CAS  Article  PubMed  Google Scholar 

  48. Gust R, Kozlowski JK, Stephenson AH, Schuster DP: Role of cyclooxygenase-2 in oleic acid-induced acute lung injury. Am J Respir Crit Care Med 1999, 160: 1165-1170.

    CAS  Article  PubMed  Google Scholar 

  49. Enkhbaatar P, Murakami K, Shimoda K, Chandra A, Traber L, Hawkins H, Herndon D, Traber D: Ketorolac, a nonsteroidal anti-inflammatory agent prevents burn/smoke-induced acute lung injury in sheep by inhibiting nitric oxide [abstract]. Am J Respir Crit Care Med 2003, 167: A665. 10.1164/rccm.200209-1031PP

    Article  Google Scholar 

  50. Sugahara K, Sadohara T, Sugita M, Iyama K, Takiguchi M: Differential expression of CCAAT enhancer binding protein family in rat alveolar epithelial cell proliferation and in acute lung injury. Cell Tissue Res 1999, 297: 261-270. 10.1007/s004410051354

    CAS  Article  PubMed  Google Scholar 

  51. Cheng IW, Ware LB, Greene KE, Nuckton TJ, Eisner MD, Matthay MA: Prognostic value of surfactant proteins A and D in patients with acute lung injury. Crit Care Med 2003, 31: 20-27. 10.1097/00003246-200301000-00003

    CAS  Article  PubMed  Google Scholar 

  52. He Y, Crouch E: Surfactant protein D gene regulation. Interactions among the conserved CCAAT/enhancer-binding protein elements. J Biol Chem 2002, 277: 19530-19537. 10.1074/jbc.M201126200

    CAS  Article  PubMed  Google Scholar 

  53. Rosenberg E, Li F, Reisher SR, Wang M, Gonzales LW, Ewing JR, Malek S, Ballard PL, Notarfrancesco K, Shuman H, Feinstein SI: Members of the C/EBP transcription factor family stimulate expression of the human and rat surfactant protein A (SP-A) genes. Biochim Biophys Acta 2002, 1575: 82-90. 10.1016/S0167-4781(02)00287-7

    CAS  Article  PubMed  Google Scholar 

  54. Groeneveld AB, Kindt I, Raijmakers PG, Hack CE, Thijs LG: Systemic coagulation and fibrinolysis in patients with or at risk for the adult respiratory distress syndrome. Thromb Haemost 1997, 78: 1444-1449.

    CAS  PubMed  Google Scholar 

  55. Prabhakaran P, Ware LB, White KE, Cross MT, Matthay MA, Olman MA: Elevated levels of plasminogen activator inhibitor-1 in pulmonary edema fluid are associated with mortality in acute lung injury. Am J Physiol Lung Cell Mol Physiol 2003, 285: L20-L28.

    CAS  Article  PubMed  Google Scholar 

  56. Ruf W, Riewald M: Tissue factor-dependent coagulation protease signaling in acute lung injury. Crit Care Med 2003, (Suppl):S231-S237. 10.1097/01.CCM.0000057848.27456.04

  57. Schultz M, Millo J, Levi M, Garrard C, van der Poll T: Local activation of coagulation and inhibition of fibrinolysis in the lung during ventilator-associated pneumonia [abstract]. Am J Respir Crit Care Med 2003, 167: A861.

    Google Scholar 

  58. Schmidt B, Davis P, La Pointe H, Monkman S, Coates G, deSa D: Thrombin inhibitors reduce intrapulmonary accumulation of fibrinogen and procoagulant activity of bronchoalveolar lavage fluid during acute lung injury induced by pulmonary overdistention in newborn piglets. Pediatr Res 1996, 39: 798-804.

    CAS  Article  PubMed  Google Scholar 

  59. Perez RL, Ritzenthaler JD, Roman J: Transcriptional regulation of the interleukin-1beta promoter via fibrinogen engagement of the CD18 integrin receptor. Am J Respir Cell Mol Biol 1999, 20: 1059-1066.

    CAS  Article  PubMed  Google Scholar 

  60. Hasegawa T, Sorensen L, Dohi M, Rao NV, Hoidal JR, Marshall BC: Induction of urokinase-type plasminogen activator receptor by IL-1 beta. Am J Respir Cell Mol Biol 1997, 16: 683-692.

    CAS  Article  PubMed  Google Scholar 

  61. Simon DI, Rao NK, Xu H, Wei Y, Majdic O, Ronne E, Kobzik L, Chapman HA: Mac-1 (CD11b/CD18) and the urokinase receptor (CD87) form a functional unit on monocytic cells. Blood 1996, 88: 3185-3194.

    CAS  PubMed  Google Scholar 

  62. Imamura T, Dubin A, Moore W, Tanaka R, Travis J: Induction of vascular permeability enhancement by human tryptase: dependence on activation of prekallikrein and direct release of bradykinin from kininogens. Lab Invest 1996, 74: 861-870.

    CAS  PubMed  Google Scholar 

  63. Fernando LP, Natesan S, Joseph K, Kaplan AP: High molecular weight kininogen and factor XII binding to endothelial cells and astrocytes. Thromb Haemost 2003, 90: 787-795.

    CAS  PubMed  Google Scholar 

  64. Russell JA: Genetics of coagulation factors in acute lung injury. Crit Care Med 2003, (Suppl):S243-S247. 10.1097/01.CCM.0000057870.61079.3E

  65. Johnson K, Aarden L, Choi Y, De Groot E, Creasey A: The proinflammatory cytokine response to coagulation and endotoxin in whole blood. Blood 1996, 87: 5051-5060.

    CAS  PubMed  Google Scholar 

  66. Johnson K, Choi Y, DeGroot E, Samuels I, Creasey A, Aarden L: Potential mechanisms for a proinflammatory vascular cytokine response to coagulation activation. J Immunol 1998, 160: 5130-5135.

    CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Center for Translational Respiratory Medicine, Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA

    Dmitry N Grigoryev & James H Finigan

  2. Center for Translational Respiratory Medicine, Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA

    Paul Hassoun

  3. Center for Translational Respiratory Medicine, Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA

    Joe GN Garcia

Authors
  1. Dmitry N Grigoryev
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. James H Finigan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Paul Hassoun
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Joe GN Garcia
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Joe GN Garcia.

Additional information

Competing interests

None declared.

Electronic supplementary material

Authors’ original submitted files for images

Below are the links to the authors’ original submitted files for images.

Authors’ original file for figure 1

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Grigoryev, D.N., Finigan, J.H., Hassoun, P. et al. Science review: Searching for gene candidates in acute lung injury. Crit Care 8, 440 (2004). https://doi.org/10.1186/cc2901

Download citation

  • Published:

  • DOI: https://doi.org/10.1186/cc2901

Keywords

  • acute lung injury
  • candidate genes
  • gene expression
  • gene ontology
  • microarrays
  • polymorphisms

Critical Care

ISSN: 1364-8535