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Functional Genomics of Lung Disease

CONTENTS

Introduction S3

Surfactant Protein C: Regulation and Interstitial Lung Disease S4

Genes and Gene Polymorphisms Associated with Idiopathic Pulmonary Fibrosis S9

Progress in Chronic Obstructive Pulmonary Disease Genetic Epidemiology S13

Single Nucleotide Polymorphisms, Chips, and Functional Genomics in Acute Lung Injury S18

Resolving Gene–Environment Interactions in Complex Traits: Acute Lung Injury S23

Genetics of Obstructive Sleep Apnea and Related Phenotypes S35

Expression Analysis in Lung Cancer: The Search for Biomarkers S39

Genetics and Gene Expression in Lymphangioleiomyomatosis S45

Genetic Regulation of Innate Immunity: Lessons Learned from TLR4 S48

Regulation of Alveogenesis by Reciprocal Proximodistal Fibroblast Growth Factor and Retinoic Acid Signaling S52

Biochemical Remodeling of Airway Smooth Muscle Relaxation–Contraction by ß₂-Adrenergic Receptor Crosstalk S58

New Experimental Approaches to the Signaling of Innate Immunity S62

Digital Gene Expression Profiling by Serial Analysis of Gene Expression S67

Identifying Regulatory Networks: Lessons from Yeast to Humans S72

The Second Pittsburgh Lung Conference: Are We Ready for Pulmonomics? S76

Author Affiliations, Acknowledgments, and Conflict of Interest Statements S79

Introduction

From the opening plenary address by Dr. Jeffrey A. Whitsett highlighting the importance of genetics and expression of surfactant-B in lung disorders to Dr. Naftali Kaminski's conference summary, our pulmonary trainees and investigators were treated to an exciting venue. An internationally recognized faculty highlighted the breadth and complexity of this topic in the field of respiratory medicine. The conference also served to highlight future directions for investigators in the field.

Our goal with the Pittsburgh International Lung Conference is to establish a forum for junior and senior lung investigators to isolate themselves, focus on state-of-the-art investigation in a selected area of lung disease, and foster collaborative, collegial, and productive interactions. Akin to the successful First Pittsburgh International Lung Conference on Idiopathic Pulmonary Fibrosis, the Second Pittsburgh International Lung Conference on Functional Genomics of Lung Disease was a huge success! We will try our best once again to achieve this goal with the Third Annual Pittsburgh International Lung Conference on October 16–21, 2004. The focus for this conference will be Adult Respiratory Distress Syndrome/Acute Lung Injury. We welcome all of you to visit our website (http://paccm.upmc.edu) to learn more about the conference and register for attendance.

Augustine M. K. Choi, M.D.

Division of Pulmonary, Allergy and Critical Care Medicine University of Pittsburgh School of Medicine Pittsburgh, Pennsylvania

Surfactant Protein C

Regulation and Interstitial Lung Disease

In the present work, we will review the structure, function, and regulation of surfactant protein C (SP-C). Recent studies, both in transgenic mice and in humans, demonstrate the importance of SP-C in surfactant function and alveolar homeostasis. Mutations in the gene encoding SP-C (SFTPC) cause acute and chronic lung disease in infants, children, and adults.

Structure and Function of SP-C

SP-C is an extremely hydrophobic 33– to 34–amino acid polypeptide isolated from surfactant phospholipids obtained by alveolar lavage (1, 2). SP-C mRNA is selectively expressed in type II alveolar epithelial cells in the lung, and depending upon alternative splicing at the beginning of exon 5 is translated to produce a 191– or 197–amino acid polypeptide that is palmitoylated and proteolytically processed to the active peptide found in the alveolus (Figure 1) (3, 4). Complete proteolytic processing of proSP-C requires the presence of SP-B (2, 5). The active SP-C peptide is trafficked to lamellar bodies and packaged with phospholipids before secretion (6). Thereafter, SP-B, SP-C, and surfactant phospholipids are secreted into the airspace to form tubular myelin and the surface active monolayers and bilayers that reduce surface tension at the air–liquid interface. SP-C perturbs phospholipid acyl packing, enhancing surface absorption and stability of surfactant lipids in the alveolus (7, 8). SP-C plays an important role in the recruitment and maintenance of the surfactant film that reduces surface tension throughout the respiratory cycle. Of clinical importance, SP-C is an active protein ingredient in surfactant preparations used for therapy of respiratory distress syndrome (RDS) in preterm infants (9). Recent studies demonstrate that SP-C may also play a role in innate host defense, binding LPS with high affinity (10).

View larger version (18K): [in this window] [in a new window]   Figure 1. Gene regulation and proteolytic processing of proSP-C. The human SFTPC gene is located on chromosome 8. TTF-1 (thyroid transcription factor-1), NF-1 (nuclear factor-1), and GATA-6 are nuclear transcription factors that bind to cis-acting elements forming a transcription complex in the 5' region of the gene, activating expression of the SFTPC. SP-C mRNA is produced by transcription of exons 1–6 and is translated to produce a 191– or 197–amino acid precursor (proSP-C) that is palmitoylated in the endoplasmic reticulum and proteolytically processed during transport from multivesicular bodies to lamellar bodies in type II alveolar epithelial cells. The 34–amino acid active SP-C peptide (dark shading, 24–58) is secreted with surfactant lipids and SP-B into the alveolus.

Gene Targeting
In initial studies in Swiss black outbred mice, inactivation of the SFTPC locus modestly disturbed surfactant function, but did not alter perinatal survival (11). Surfactant isolated from the SP-C null mutant (SP-C^–/–) mice was less stable than normal surfactant when studied by bubble surfactometry. In sharp contrast, when SP-C^–/– mice were backcrossed into the 129/Sv strain, marked changes in lung function and histology were readily apparent in the postnatal period (12). Postnatal survival of adult SP-C^–/– 129/Sv mice was decreased and associated with the development of emphysema, pulmonary inflammation, abnormal tissue lipid accumulations, and goblet cell hyperplasia. These differences demonstrated that SP-C is required for alveolar homeostasis in the postnatal period and that this requirement is strongly influenced by modifier genes, which differ in the 129/Sv compared with the Swiss black strain.

Mutation of the SP-C Proprotein Structure Disrupted Lung Morphogenesis
A truncated SP-C peptide, expressed under control of the mouse 13-kb SFTPC promoter that is selectively active in type II epithelial cells, disrupted lung morphogenesis, causing death at birth (13). Transgenic mice expressing a SFTPC mutation associated with interstitial lung disease in humans also died at birth with severe lung dysmorphogenesis (14). Both the truncated and mutant transgenes were expressed in the presence of two normal SFTPC alleles indicating that the mutant gene was dominant. Thus, either deletion or mutation of the SFTPC gene caused severe lung pathology.

Mutations in the Human SFTPC Gene Cause Familial and Sporadic Interstitial Lung Disease

Severe interstitial lung disease was associated with the absence of SP-C expression (15). Likewise, dominantly inherited mutations in the SFTPC gene were associated with both acute lung failure and chronic interstitial lung disease in human patients (16, 17). A number of distinct mutations in the SFTPC gene have been associated with interstitial lung disease. Lung pathology in these patients was classified as either chronic idiopathic pneumonitis of childhood (CIP), desquamating interstitial pneumonitis (DIP), usual interstitial pneumonitis (UIP), or nonspecific interstitial pneumonitis (NSIP). The histologic findings varied with age and severity of lung disease, perhaps indicating modification of the disease process by environmental and genetic factors. Thomas and coworkers reported a large kindred of individuals with dominantly inherited, interstitial lung disease, who exhibited variability in age of onset and severity of lung disease associated with a mutation in the SFTPC gene (17). Sporadic ILD associated with an apparent de novo SP-C gene mutation has also been recognized (18). Recently, a number of infants with SFTPC gene mutations were identified who suffered severe, and even lethal, neonatal respiratory distress (L. M. Nogee and colleagues, unpublished observations). Thus, mutations in the SFTPC gene cause diverse inherited forms of lung disease with remarkable differences in severity, age of onset and disease progression. Both acute respiratory distress syndrome and chronic interstitial lung disease with pulmonary fibrosis have been associated with SFTPC gene mutations. Therefore, pulmonary disorders associated with SFTPC gene mutations appear to be strongly influenced by modifier genes and/or environmental factors in both mice and humans.

Proposed Mechanisms Underlying the Pathogenesis of Pulmonary Disease in SFTPC Mutations

Findings in both mice and humans support the hypothesis that deficiency of SP-C underlies abnormalities in lung function and remodeling, leading to acute and chronic lung disease. This concept is supported by the finding of patients lacking SP-C expression and null mice lacking expression of SP-C or proSP-C who develop interstitial lung disease (Figure 2) (12, 15). Expression of mutant proSP-C peptides is also associated with intracellular accumulation of proSP-C, raising the possibility that misfolded protein, as well as SP-C deficiency, may contribute to disease pathogenesis. Mutations in one SFTPC allele, which lead to misfolding of the encoded SP-C proprotein, result in retention and degradation of the mutant protein via the endoplasmic reticulum–associated degradation (ERAD) pathway. Because proSP-C can form homodimers (19), the product of the wild-type SFTPC allele may also be trapped in the ER and degraded. The net effect of the mutation is deficiency of SP-C in the airspaces. Under certain circumstances, degradation of misfolded proSP-C may be compromised leading to accumulation of a cytotoxic form of the proprotein and inappropriate cell death. In transgenic mice expressing mutant SP-C proprotein, accumulation of misfolded protein likely occurred because the high concentration of the transgenic protein saturated the degradation pathway (14). In human patients bearing SFTPC gene mutations, accumulation of misfolded proprotein may occur when additional stress, e.g., viral infection, is superimposed on a clearance pathway that is already operating at or near capacity. Thus, both intracellular accumulation of a misfolded, cytotoxic SP-C proprotein and deficiency of the mature peptide in the airspaces may contribute to the pathogenesis of lung disease (Figure 3).

View larger version (137K): [in this window] [in a new window]   Figure 2. Pulmonary histopathology in SP-C–/– null mutant mice and in a patient with an SFTPC mutation. (A) Normal pulmonary alveoli are observed in lungs from adult wild-type mice. (B) Interstitial lymphocytic pneumonitis with mild alveolar septal wall thickening and macrophage accumulations are observed in the lungs of SP-C null mutant mice. (C) Alveolar septal wall thickening, accumulation of alveolar macrophages and amorphous, eosinophilic material (lipoproteinosis) in the alveolar spaces are found in the lungs of a 7-mo-old child diagnosed with childhood interstitial pneumonitis caused by a mutation in exon 4 of the SFTPC gene. (D) Accumulation of abnormal proSP-C in alveolar type II cells is detected in the lungs of this child using an antibody generated against proSP-C. A–C: Hematoxylin and eosin stains. D: Immunoperoxidase staining for proSP-C. Bar = 100 µm for all panels.

View larger version (11K): [in this window] [in a new window]   Figure 3. Pathogenesis of pulmonary disease associated with mutation in SFTPC. A mutation in one allele of the SFTPC gene produces a mutant proSP-C protein that is misfolded. The mutant proSP-C interacts with wild-type SP-C proproteins in the endoplasmic reticulum, inhibiting processing of normal proSP-C and blocking production of the active peptide. Both proproteins are degraded leading to SP-C deficiency in the airspaces. Lung injury may be mediated by the lack of SP-C and the accumulation of abnormal proSP-C/mutant proSP-C proteins. ProSP-C may accumulate intracellularly resulting in cytotoxicity and lung pathology.

With the recognition that SP-C was expressed in a highly lung epithelial–specific pattern and was induced in the perinatal period, studies were undertaken to identify the mechanisms controlling its expression. Bohinski and coworkers identified the critical role of thyroid transcription factor-1 (TTF-1) in the activation of promoter elements in the SFTPC gene, as well as other lung epithelial–selective genes (20). The SFTPC promoter has been highly useful in the introduction of genes into the lungs of transgenic mice, for gene addition, mutation, or deletion. Relatively small regions of the promoter are adequate to direct lung epithelial cell–specific expression (21, 22). The SFTPC promoter has been useful in studies to discern the roles of genes influencing lung formation and function. For example, SFTPC promoter elements have been used for constitutive expression of genes in the respiratory epithelium of transgenic mice and for conditional expression or deletion of genes under control of the SP-C-rtTA (reverse tetracycline transactivator protein) transgene (23). Conditional expression of Cre-recombinase with this system has been used for recombination of floxed genes in vivo, which has been useful for cell lineage analysis, as well as for gene addition and deletion, to study lung function and formation in vivo (24–26).

Genetic Elements Controlling Lung Epithelial Cell Gene Expression: TTF-1

Bohinski and colleagues identified a critical role for TTF-1 in the regulation of a number of genes selectively expressed in respiratory epithelial cells, including SP-A, SP-B, SP-C, and the Clara cell secretory protein (CCSP) (20). TTF-1 binds and activates cis-elements (TTF-1 response elements [TRE]) located in the 5' regions of these target genes. Mutations of TREs markedly or completely abrogated gene expression normally induced by the interaction of TTF-1 with the promoter elements in these target genes (Figure 1). TTF-1 is expressed in the forebrain, thyroid, and lung, and is a member of the Nkx family of homeodomain-containing nuclear transcription factors (27). Deletion of TTF-1 per se causes severe brain abnormalities, as well as thyroid and lung hypoplasia, demonstrating its critical role in brain, thyroid, and lung morphogenesis (28). Haploinsufficiency of TTF-1 gene (TITF-1) in humans resulting from loss-of-function mutations on one allele is associated with hypothyroidism, choreoathetosis, and chronic lung disease (29). In the fetal lung, TTF-1 is detected in respiratory epithelial cells lining both conducting and peripheral lung tubules. In the postnatal lung, TTF-1 is expressed in subsets of bronchiolar cells and type II epithelial cells in the alveolus, but not in type I epithelial cells (30, 31). Deletion of the TITF-1 gene causes tracheoesophageal fistula and marked lung hypoplasia associated with the absence of SP-A, -B, and -C (28, 32). In contrast, ciliated bronchiolar epithelial cells and associated markers, including FOXJ1 and ß-tubulin IV, are expressed in TTF-1^–/– mice, demonstrating that TTF-1 selectively influences peripheral lung formation and gene expression (33).

Gene Substitution: TTF-1 Phosphorylation Mutant

The severe lung hypoplasia characteristic of TTF-1^–/– mice limited their utility for identification of the molecular targets and functions of TTF-1 later in gestation (28). Because phosphorylation of TTF-1 influences its activity in the transcriptional activation of target genes, the endogenous TITF-1 allele was replaced with a mutant allele in which serine phosphorylation sites were mutated to alanine (TTF-1[PM]) (34). Lung formation was substantially rescued in the TTF-1(PM) mice compared with the TTF-1^–/– mice. TTF-1(PM) mice died of respiratory failure at the time of birth, indicating that the mutant represented a hypomorphic allele. To identify potential transcriptional targets of TTF-1 before birth, RNA microarray analysis was performed on lungs at E18.5. A number of genes whose expression was influenced by TTF-1(PM) were identified, including genes regulating surfactant homeostasis, host defense, fluid and electrolyte transport, gene transcription, differentiation, vasculogenesis, and alveologenesis (see Figures 4 and 5). Promoter elements from a number of these genes contained TREs located in the regulatory regions, indicating the likelihood that these genes represent direct transcriptional targets of TTF-1 in respiratory epithelial cells. A number of known molecular targets of TTF-1, including SP-A, -B, -C, and CCSP, as well as previously unknown targets (tcf7, Lef1, ß-catenin, Sox17, and Mdk) were identified. Subsets of genes expressed primarily in nonepithelial cells are likely to be indirect targets of TTF-1, their expression being dependent upon paracrine or cell–cell signals derived from the respiratory epithelium, which, in turn, influence expression and formation of the underlying stromal elements that form the alveolar walls, as well as the vascular and lymphatic systems of the lung.

View larger version (61K): [in this window] [in a new window]   Figure 4. Heat map of hierarchical clustering of lung mRNAs influenced by the TTF-1(PM). Microarray analysis was performed on lung mRNA at E18.5 in TTF-1(PM) mutant mice (Mut) and control littermates (Con). Red represents mRNAs that were significantly increased, whereas green represents those decreased in TTF-1(PM) lung tissue. The heat map provides a representative list of altered genes. A complete list of these genes is provided in deFelice and coworkers (34).

View larger version (26K): [in this window] [in a new window]   Figure 5. Schemata of classes of mRNAs influenced by the TTF-1(PM) mutation. TTF-1 influences the expression of gene transcription, surfactant homeostasis, ion and water transport, signaling, vasculogenesis, cell differentiation, and host defense. The sites of serine to alanine substitutions (A) made in the TTF-1(PM) phosphorylation mutant gene are shown as described in deFelice and coworkers (34). HD is the homeodomain region of TTF-1 that binds to cis-acting elements in TTF-1 target genes.

Study of the SP-C protein and SFTPC gene have provided unexpected insights into the molecular pathways influencing the pathogenesis of interstitial lung disease and the regulation of gene expression in the peripheral lung. The molecular tools and models derived from these studies have been useful in identifying genes and processes that are likely to mediate adaptation to air breathing at birth. It is hoped that future studies of the pathways mediating lung formation, as well as those linking SP-C to acute and chronic lung disease, will provide new insights into the pathogenesis of pulmonary disease, which will be useful in identifying novel therapies for both RDS and interstitial lung disease.

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Genes and Gene Polymorphisms Associated with Idiopathic Pulmonary Fibrosis

Historically, the lung fibrosis observed in patients with IPF was considered to be a deteriorating consequence of persistent lung inflammation associated with continuous cellular injury from unknown insults (4). However, growing evidence in recent years suggests that the inflammatory response may not precede the fibrosis nor play a major role in the IPF development. This is supported by the lack of responsiveness of patients with IPF to anti-inflammatory treatments. Instead, IPF may be a disease of impaired wound healing involving the epithelial/fibroblastic pathway (5, 6). The triggering event in IPF may be multiple and continuous microscopic insults to the alveolar epithelial cells. Aberrant wound healing subsequently leads to fibroblast proliferation, transformation into myofibroblasts, formation of fibroblastic foci, deposition of extracellular matrix, and ultimately fibrosis.

IPF is a complex disease influenced by multiple genetic predisposition factors and environmental exposure. Gene expression analysis of lung tissues from patients with IPF has yielded insights into the molecular pathways that may be important in IPF development (7). However, genetic studies of IPF have been hindered by limited familial cases, late disease onsets, phenotypic heterogeneity, and the high mortality rate associated with this disease. Identification of genetic factors that provide susceptibility to IPF and/or modify disease progression will be vital in understanding the pathogenesis of IPF.

Surfactant Protein C Gene Mutation in Familial IPF

Based on a clinical and epidemiologic study conducted in the United Kingdom, the incidence of familial IPF was estimated to be 2% of all diagnosed IPF cases (8). However, according to a recent report, as many as 10% of all patients with IPF may have IPF history in their families (9). In comparison with sporadic cases, the patients with familial IPF have earlier disease onset and nearly 20% mortality before age 50 (9). Using a family affected by IPF, consisting of five generations and eleven affected individuals, Thomas and coworkers have identified a heterozygous exon 5 +128 T to A transversion in the surfactant protein C (SP-C) gene from all affected individuals (10). SP-C is a member of the surfactant-associated protein family that affects lung mechanics, gas exchange, and host defense (11). The exon 5 +128 T to A mutation results in a glutamine for leucine substitution at a highly conserved codon within the carboxyl-terminal domain of the SP-C protein precursor. Aberrant cellular distribution of the SP-C protein was observed in lung tissues of affected individuals from this family. The exon 5 +128 T to A mutation may produce a misfolded protein with abnormal cellular trafficking. Given the important roles of SP-C in the structural integrity of alveolar type II cells, alterations in the cellular distribution of SP-C protein may provide susceptibility to injury for the alveolar type II cells. Missense and splicing site mutations of the SP-C gene were also reported in sporadic and familial cases of other interstitial lung diseases (12, 13).

Gene Polymorphisms Associated with Sporadic IPF

Although SP-C gene mutations form a genetic basis for some familial cases of IPF, mutations in SP-C are not associated with all of the families with IPF. In addition, the majority of patients with IPF lack a family history suggesting a complex genetics of this disease. The development of IPF is likely to be determined by multiple genetic factors that each contribute a modest effect to the predisposition of this disease. In combination with appropriate environmental or cellular triggers, individuals who possess these predisposition factors may develop IPF. The lack of genome-wide linkage analyses and chromosomal loci for IPF make the positional cloning of these genes impossible and, therefore, population-based association is the method of choice for the genetic study of IPF.

To date, limited gene and gene polymorphisms have been evaluated in IPF cohorts and even fewer of them have demonstrated confirmed associations (Table 1). Coinciding with the traditional paradigm for the pathogenesis of IPF, candidate genes that have been analyzed for this disease are primarily involved in inflammatory and immune responses. Given the intrinsic pitfalls of population stratification, misclassification of phenotypes, and insufficient study subjects associated with genetic case-control studies, cautious interpretation of the outcomes of these studies is important.

Transforming Growth Factor-ß Gene
Transforming growth factor-ß (TGF-ß) is a central player in pulmonary fibrosis, and its expression is elevated in the lung tissues of patients with interstitial lung diseases (15, 16). Overexpression of TGF-ß in the lung tissues induced prolonged pulmonary fibrosis in an animal model (17). Using a cohort consisting of 128 subjects with IPF and 140 ethnicity-matched healthy control subjects, Xaubet and associates have demonstrated no association for two nonsynonymous SNPs, 869T>C/L10P and 915G>C/R25P, of the TGF-ß gene with the IPF phenotype (18). However, the 10P allele was associated with an increased deterioration of the disease as measured by gas exchange (18). As noted by the authors, this allele was not correlated with other functional parameters of IPF, and the levels of TGF-ß in both cases and control subjects were not determined. Therefore, further evaluation using independent IPF cohorts is necessary to determine the true roles of the 10P allele as well as other polymorphisms within the TGF-ß gene in IPF.

Interleukin-1 Gene Cluster
Interleukin-1 (IL-1) is a proinflammatory and fibrogenic cytokine. IL-1, IL-1ß, and their naturally occurring inhibitor IL-1 receptor antagonist (IL-1RN) are localized in a cluster on chromosome 2q13 (19). Using an IPF cohort from the United Kingdom and Italy, Whyte and coworkers demonstrated an association between the rare C allele of the +2018C>T SNP in the IL-1RN gene for both populations (20). However, this association was not confirmed with cohorts from the United States and Europe (21, 22). The –889T allele in the IL-1 gene was also associated with severity of gas transfer deficits in patients with IPF. No association was identified for multiple polymorphisms in IL-1, IL-1ß, and IL-1RN genes using an IPF cohort from the Czech Republic (22).

Tumor Necrosis Factor-, IL-6, and Related Genes
Expression analysis of the tumor necrosis factor- (TNF-) in lung tissues of patients with IPF has shown an elevated level in the alveolar type II epithelial cells (23, 24). Using two well-defined IPF cohorts, Whyte and colleagues first reported an association with the –308A allele of TNF-A gene (20). However, a subsequent study using a third study cohort did not detect the same association between IPF and the –308A allele of TNF-A gene (25). In addition, association was not detected for multiple polymorphisms in the TNF-A, TNF-receptor II (TNF-RII) and lymphotoxin (LT-) genes using the third IPF cohort (25). Interestingly, the G allele of the IL-6 intron 4 A>G SNP was associated with rapid disease progression of the patients with IPF in this cohort (25). Co-carriage of the TNF-RII 1690C allele and the IL-6 intron 4G allele were also strongly associated with the IPF phenotype, suggesting a combinatory effect of these two genes in the IPF development (25).

Angiotensin-Converting Enzyme Gene
A functional insertion/deletion polymorphism in intron 16 of the angiotensin-converting enzyme (ACE) gene has been associated with plasma levels of ACE and angiotensin (26). The D allele correlating with high plasma ACE level has been shown to have association with systemic sclerosis, a disease with high propensity to interstitial lung diseases (27). Using a very small North American IPF cohort, Morrison and colleagues have detected an increased D allele frequency for IPF cases in comparison with matched control subjects (42% versus 31%) (28). Because this study population consists of both subjects with IPF and subjects with NSIP (nonspecific interstitial pneumonia), no reliable conclusion should be made from this small study cohort.

Complement Receptor 1 Gene
Recently, Zorzetto and colleagues analyzed polymorphisms of the complement receptor 1 (CR1) gene using an Italian IPF cohort (29). CR1 is important in the clearance of immune complexes. The polymorphism C5570G in exon 33 has been correlated with the levels of CR1 expressed on erythrocytes that may directly correlate with the clearance of the immune complex (30). Using the RFLP method, they demonstrated significant association for the GG genotype of the C5570G polymorphisms with IPF (29). The GG genotype was also associated with sarcoidosis in the same population (31). Because sarcoidosis and IPF are two clinically distinct identities of interstitial lung diseases, the likelihood of sharing the same genetic predisposition factors are low and, therefore, confirmation of the CR1 association in additional IPF study cohorts are necessary.

In contrast to the genes and gene polymorphisms that have been shown to be associated with IPF, lack of association with IPF development has been documented for polymorphisms in plasminogen activator inhibitor-1 and genes involved in the Th1/Th2 response (32–34). Systematic analyses of these genes using functional genomic tools may be necessary to determine their roles in the development of IPF.

Future Genetic Polymorphism Studies in IPF

With limited familial cases and late disease onset associated with IPF, identification of genetic predisposition factors will mainly rely on population-based association studies. One of the major potential pitfalls of case-control genetic association studies is population stratification (35). Population stratification arises as a result of admixture of two distinct populations that differ in allele frequencies at both the marker and trait loci. This allele frequency difference can mimic allelic association (even when the trait and marker loci are unlinked) that can be replicated in subsequent sampling from the same admixed population. Therefore, every effort should be made in selecting ethnicity-matched control subjects to minimize population stratification. The population stratification may also be controlled experimentally. One of the approaches that have been used to control this potential problem is the Genomic Control (GC) method (36, 37). GC automatically adjusts test statistics of association for the presence of population stratification by evaluating other markers. Although the impact of population stratification on well-selected association studies is unclear, GC is straightforward to implement (36, 37). Devlin and Roeder present GC methods that can be implemented in the simplest situations in case-control studies (36). GC methods provide the advantage of robustness against spurious association due to population stratification while eliminating the need to collect a significantly greater number of samples for the case-control study (37). Alternatively, as introduced by Pritchard and Rosenberg, the population stratification can also be controlled by simply analyzing 15–20 unlinked microsatellite markers of the study population (38).

Another critical component for conducting a case-control study is the accurate characterization of clinical phenotypes. According to the American Thoracic Society/European Respiratory Society (ATS/ERS), IPF is a "Specific form of chronic fibrosing interstitial pneumonia limited to the lung and associated with the histologic appearance of usual interstitial pneumonia (UIP)." It is characterized by progressive dyspnea, worsening pulmonary function, and a typical radiographic pattern (39). According to Dacic and Yousem, diagnosis of IPF should be based on (i) histological findings consistent with UIP from multiple lung biopsies, (ii) clinical findings excluding known underlying diseases such as connective tissue and autoimmune diseases, and (iii) radiographic presentations demonstrating typical features of pulmonary fibrosis with little active inflammation (2). Misdiagnosis of cases in an IPF study cohort may mask the genetic differences between the case and control groups and prevent the identification of IPF-associated genes.

Unlike the rare gene mutations associated with Mendelian genetic diseases, genetic polymorphisms associated with complex traits may be common in the population. The presence of one disease-associated allele may not be sufficient to cause disease. Therefore, carriage of a disease-associated polymorphism does not translate into a clinical diagnosis. It is the specific combination of multiple disease-associated loci (gene–gene interaction) and the presence of environmental triggers (gene–environmental interactions) that lead to the development of specific complex phenotypes. The disease-associated alleles may either provide susceptibility to initial disease triggers or modify the disease development after initial pathogenic changes.

Integration of gene expression/proteomic studies of affected tissues may permit the identification of cellular and molecular pathways important in the disease pathogenesis. Identification of these pathways is crucial for guiding the selection of candidate genes in association studies. As demonstrated in autoimmune diseases, different genes or gene polymorphisms that are involved in the same pathway may independently contribute to the development of same or related clinical phenotypes. Recently, three distinct regulatory polymorphisms have been independently associated with systemic lupus erythematosus, rheumatoid arthritis, and psoriasis (40–42). Although these three polymorphisms are localized in different genomic locations and may regulate four candidate genes for autoimmunity, the genetic variations in these polymorphisms alter the binding sites for a common transcription factor, runt-related transcription factor 1 (RUNX1). Therefore, systemic analysis of crucial genes involved in important pathways of IPF pathogenesis will be vital in determining their combinatory roles in the IPF development.

In addition to the genetic predisposition, environmental exposure may be equally important in the development of IPF. One of the well-known risk factors for IPF is smoking. Stratification of the study populations based on their environmental exposure in genetic association studies is essential to determine gene–environment interactions in IPF. Once a gene or gene polymorphism is identified, it is important to verify the functional relevance in IPF using molecular and functional genomic approaches as well as animal models. Identification of genetic factors that either offer susceptibility or modify the disease development of IPF will ultimately provide genetic profiles that may predict disease onsets, disease progression, and treatment outcomes.

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Progress in Chronic Obstructive Pulmonary Disease Genetic Epidemiology

In this review, we will briefly discuss 1-antitrypsin (AAT) deficiency as a proven genetic determinant of COPD, we will consider the evidence for familial aggregation of COPD unrelated to AAT deficiency, and we will focus on the recent genetic linkage analysis studies of COPD.

Severe AAT Deficiency

Approximately 1–2% of patients with COPD inherit severe AAT deficiency (typically phenotype PI Z) (4). AAT is encoded by the PI (protease inhibitor) gene, which is located on chromosome 14. Individuals with phenotype PI Z (corresponding to genotypes ZZ or Znull) have severely reduced serum AAT levels and are clearly at increased risk for the development of COPD—especially if they smoke (5–7).

Because most subjects with phenotype PI Z are identified because they already have COPD, ascertainment bias has had a significant impact on the perceived natural history of lung disease in severe AAT deficiency. In a study of 52 subjects with phenotype PI Z and their families at Washington University in St. Louis, nonindex subjects with phenotype PI Z, who were not ascertained due to COPD, often had normal pulmonary function (8). Not surprisingly, index subjects with phenotype PI Z, who were ascertained with COPD, all had significant airflow obstruction. Seersholm and colleagues also found significantly higher baseline FEV₁ values in nonindex subjects with phenotype PI Z compared to index subjects with phenotype PI Z despite similar ages and smoking histories in the index and nonindex subjects (9).

Cigarette smoking is clearly a major determinant of pulmonary function variability among individuals with phenotype PI Z. However, some smokers with phenotype PI Z maintain normal FEV₁ values at least into middle age; by this age, some nonsmokers with phenotype PI Z have already developed significant airflow obstruction. Results of genetic modeling from the St. Louis AAT Study suggested that additional genetic factors influence the development of airflow obstruction in AAT deficiency (10). By comparing the slopes of the relationship between FEV₁ and pack-years of smoking (known as the norms of reaction) in subjects with phenotypes PI Z, PI MZ, and PI M, significant genotype-by-environment interaction between PI type and pack-years of smoking was demonstrated in the St. Louis AAT Study (11).

Only a few other studies have considered whether factors other than cigarette smoking influence the development of lung disease in subjects with phenotype PI Z. For example, Black and Kueppers found significant variability in pulmonary function and clinical symptoms among nonsmoking individuals with phenotype PI Z (12). In a study of more than 200 nonsmokers with phenotype PI Z, Piitulainen and colleagues showed that, as expected, increasing age was associated with reduced pulmonary function (13). Among nonsmokers with phenotype PI Z older than 50 years, male sex, wheezing symptoms, and occupational exposures to respiratory irritants were also associated with reduced pulmonary function. Ongoing studies in AAT-deficient families hold promise to identify genetic modifiers of the development of lung disease in individuals with phenotype PI Z.

Familial Aggregation of Spirometry and COPD

Studies of spirometric measurements performed in families and in twins from the general population have suggested that genetic factors influence pulmonary function variation (14, 15). Studies in relatives of individuals with COPD have also suggested a role for genetic factors in COPD susceptibility by demonstrating higher rates of airflow obstruction in first-degree relatives of patients with COPD compared with control subjects (16, 17).

In the Boston Early-Onset COPD Study, our research group has focused on severe, early-onset COPD probands, because the study of early-onset cases in other complex disorders has successfully led to the identification of susceptibility genes (e.g., breast cancer). Severe early-onset COPD probands in this study met the following criteria: Age < 53 yr; FEV₁ < 40% predicted; physician-diagnosed COPD; absence of severe AAT deficiency; and no other lung disease to account for chronic airflow obstruction. The majority of these severe, early-onset COPD probands have been identified from lung transplantation and lung volume reduction surgery programs.

To maximize the genetic information from these rare severe, early-onset COPD probands, all available first-degree relatives (siblings, parents, and children) and older second-degree relatives (half-siblings, aunts, uncles, and grandparents) were invited to participate in the study. In addition, other relatives with diagnosed COPD were included, and all first-degree relatives of any family members with moderate airflow obstruction (FEV₁ < 60% predicted, FEV₁/FVC < 90% predicted) were also invited to participate.

The first phase of the Boston Early-Onset COPD Study included 44 severe, early-onset COPD probands with 204 first-degree relatives (18). To confirm that the Boston Early-Onset COPD Study probands were correctly diagnosed with COPD, reports of previously performed chest CT scans and lung pathological samples were reviewed. Chest CT scan reports were available for 36 subjects; 34/36 chest CT reports noted emphysema, and for one of the subjects without gross emphysema, attenuated pulmonary vasculature consistent with emphysema was noted. Reports regarding lung pathological specimens were available for 17 subjects, and all of these specimens showed emphysema. Thus, the Boston Early-Onset COPD Study probands had severe airflow obstruction with emphysema, and the diagnosis of COPD among these COPD probands appears to be quite accurate.

The 44 early-onset COPD probands were selected to have severe airflow obstruction at an early age, and a profound degree of airflow obstruction in these subjects (mean FEV₁ 16.9% predicted) was observed. Only 2 of the first 44 early-onset COPD probands were lifelong nonsmokers.

A high prevalence of females (> 70%) was found among the Boston Early-Onset COPD Study probands; subsequent studies also demonstrated an increased risk to smoking female first-degree relatives of early-onset COPD probands for severe airflow obstruction compared with smoking male first-degree relatives (19). The etiology of the female predominance in the Boston Early-Onset COPD Study compared with the male predominance in most previous studies of severe COPD remains to be defined. However, our sample included, on average, younger subjects with lower FEV₁ values than previous studies.

The key phenotypes selected for familial aggregation analysis in the Boston Early-Onset COPD Study were spirometric measures of airflow obstruction, including FEV₁ and FEV₁/FVC. Because reduced FEV₁ can result from restrictive lung diseases (e.g. interstitial lung diseases, neuromuscular diseases), analysis of the FEV₁/FVC ratio selects for effects of airflow obstruction. In addition, chronic bronchitis, a clinically defined condition of cough productive of phlegm for at least 3 mo/yr for at least 2 yr, is a COPD-related phenotype that can be assessed reasonably well by questionnaire.

The 204 first-degree relatives of severe, early-onset COPD probands were compared to 83 control subjects that participated in previous population-based studies at the Channing Laboratory and agreed to participate in this study. First-degree relatives of early-onset COPD probands had significantly lower mean values for FEV₁ (percent predicted) and FEV₁/FVC (percent predicted) than control subjects (P < 0.01), despite similar values for age and pack-years of smoking. Although the difference in mean FEV₁ (% predicted) between all first-degree relatives of early-onset COPD probands and all control subjects was modest, compared with current or ex-smoking control subjects, current or ex-smoking first-degree relatives of early-onset COPD probands had substantially lower FEV₁ (76.1% predicted versus 89.2% predicted) and FEV₁/FVC (83.5% predicted versus 94.3% predicted) (P < 0.01 for each comparison). The distribution of FEV₁ values in smoking first-degree relatives of early-onset COPD probands compared with smoking control subjects is shown in Figure 1. On the other hand, the FEV₁ and FEV₁/FVC values in lifelong nonsmoking first-degree relatives and nonsmoking control subjects were quite similar.

View larger version (12K): [in this window] [in a new window]   Figure 1. Significantly lower FEV1 (% predicted) values were found in smoking first-degree relatives of severe, early-onset COPD probands (filled bars) compared to smoking control subjects (open bars) in the Boston Early-Onset COPD Study (from Ref. 18).

Very similar results in terms of familial aggregation of airflow obstruction were also found by McCloskey, Lomas, and colleagues in a sample of families from the United Kingdom (21). Significantly increased odds for airflow obstruction were found in smoking first-degree relatives of COPD probands compared to smoking control subjects, but no increased risk for airflow obstruction was found in nonsmoking first-degree relatives of COPD probands.

The results of the Boston Early-Onset COPD Study and the McCloskey/Lomas study suggest that the increased risk for airflow obstruction found only in current or ex-smoking first-degree relatives of COPD probands may relate to genotype-by-environment interactions between cigarette smoking and one or more unidentified genetic factors.

Linkage Analysis of Severe, Early-Onset COPD

After the analysis of familial aggregation of COPD-related phenotypes in the Boston Early-Onset COPD Study pedigrees, additional pedigrees were recruited, and 607 members of 72 early-onset COPD pedigrees were included in a genome scan linkage analysis. After excluding 22 subjects due to pedigree inconsistencies (likely related to nonpaternity), a 9-cM genome scan of short tandem repeat (STR) markers, performed by the NHLBI Mammalian Genotyping Service, was analyzed for linkage to COPD-related phenotypes. Because the optimal COPD-related phenotypes for linkage analysis were not known, a series of analyses were performed, including qualitative phenotypes, quantitative prebronchodilator phenotypes, and quantitative postbronchodilator phenotypes.

Qualitative COPD-related phenotypes, including airflow obstruction and chronic bronchitis, were analyzed using multipoint nonparametric linkage analysis by assessing allele sharing among affected relatives with the ALLEGRO program (22). In the initial qualitative phenotype genome scan, the strongest evidence for linkage to moderate airflow obstruction (FEV₁ < 60% predicted with FEV₁/FVC < 90% predicted) was found on chromosomes 12 (LOD = 1.70 at 36 cM) and 19 (LOD = 1.54 at 42 cM). For mild airflow obstruction (FEV₁ < 80% predicted with FEV₁/FVC < 90% predicted), the strongest evidence for linkage was noted on chromosomes 8 (LOD = 1.36 at 76 cM) and 19 (LOD = 1.09 at 42 cM). Limiting analysis to cigarette smokers substantially increased the evidence for linkage of mild airflow obstruction to chromosome 12 (LOD = 1.54 at 32 cM). For linkage analysis of chronic bronchitis, analysis of smokers only provided increased evidence for linkage in several regions, including chromosomes 19 (LOD = 1.73 at 42 cM) and 22 (LOD = 2.08 at 36 cM). None of these initial linkage results met the criteria for significant linkage, and only the analysis of chronic bronchitis in smokers met the criteria for suggestive linkage (23).

Subsequently, genome scan linkage analysis of quantitative prebronchodilator spirometric phenotypes was undertaken (24). Multipoint variance component linkage analysis (using SOLAR) was performed for quantitative prebronchodilator phenotypes including FEV₁ and FEV₁/FVC, with covariates including pack-years of smoking. In the initial quantitative phenotype genome scan, significant evidence for linkage to FEV₁/FVC was demonstrated to chromosome 2q (LOD = 4.12 at 222 cM); suggestive evidence was found for linkage to FEV₁/FVC on chromosomes 1 (LOD = 1.92 at 120 cM) and 17 (LOD = 2.03 at 67 cM). The highest LOD score for FEV₁ in the initial genome scan was 1.53 on chromosome 12 at 36 cM, which did not reach the threshold for suggestive linkage (23).

Thus, the initial genome scan linkage analysis of chronic bronchitis and prebronchodilator qualitative and quantitative spirometric phenotypes with STR markers at an average of 9-cM intervals led to the identification of several chromosomal regions with significant or suggestive evidence for linkage to COPD-related phenotypes.

To determine whether pre- or postbronchodilator spirometric measurements would be optimal phenotypes for linkage analysis, and to assess linkage to bronchodilator responsiveness phenotypes, our research group has recently completed variance component linkage analysis of postbronchodilator spirometric measures and several measures of bronchodilator responsiveness using the genome scan STR genotyping data (25). We included 560 subjects in 72 pedigrees who had both pre- and postbronchodilator spirometry.

For bronchodilator responsiveness phenotypes (absolute volume change in FEV₁, change in FEV₁ as a percent of baseline FEV₁, and change in FEV₁ as a percentage of predicted FEV₁), the maximum LOD scores did not reach the threshold for suggestive linkage. The maximum observed LOD score for absolute volume change in FEV₁ after bronchodilator was 1.56 on chromosome 4; the maximum LOD score for change in FEV₁ as a percentage of predicted FEV₁ (LOD = 1.55) was also found on chromosome 4. Although the maximum LOD scores for bronchodilator responsiveness phenotypes were modest, increased evidence for linkage to postbronchodilator spirometric measures was found compared to prebronchodilator spirometric phenotypes in multiple genomic regions. Postbronchodilator FEV₁ was linked to multiple regions, most significantly to markers on chromosome 8p (LOD = 3.30 at 2 cM) and 1p (LOD = 2.24 at 136 cM). Postbronchodilator FEV₁/FVC was also linked to multiple regions, most significantly to markers on chromosome 2q (LOD = 4.42 at 222 cM) and 1p (LOD = 2.52 at 118 cM). When compared to prebronchodilator spirometric indices, the LOD score for the 8p linkage to FEV₁ roughly doubled from 1.58 to 3.30, which corresponds to significant linkage, whereas the evidence for linkage of FEV₁/FVC to chromosome 2q increased from 4.05 to 4.42. Postbronchodilator spirometric phenotypes appear to provide stronger evidence for linkage in many regions, potentially because day-to-day variability in the level of bronchoconstriction is reduced by uniformly analyzing spirometric values after albuterol treatment.

To increase the genotypic information for linkage analysis, additional STR markers were genotyped at 2- to 3-cM intervals within several regions of linkage to COPD-related phenotypes in the 585 subjects in 72 pedigrees included in the genome scan. Within the region of linkage to airflow obstruction on chromosome 12p (18–49 cM), twelve additional STR markers were genotyped. Multipoint nonparametric linkage analysis using all of the chromosome 12 markers provided increased evidence for linkage to moderate airflow obstruction, with a maximum LOD score of 2.13 at 36 cM in all subjects (22). Multipoint variance component linkage analysis (using SOLAR) was also performed for quantitative prebronchodilator spirometric phenotypes, with covariates including pack-years of smoking, for the full set of chromosome 12 STR markers. Suggestive evidence for linkage of FEV₁ (LOD = 2.43 at 37 cM) was demonstrated to this region (24). Thus, suggestive evidence for linkage of chromosome 12p to both qualitative airflow obstruction and quantitative FEV₁ phenotypes was found.

The linkage analysis results for spirometric phenotypes in the Boston Early-Onset COPD Study are summarized in Table 1. Seven regions of at least suggestive linkage to spirometric phenotypes have been identified on chromosomes 1p (two regions), 2q, 8p, 12q, 17q, and 19q. Relatively wide genomic regions of linkage have been identified. Only modest reductions in the regions of interest have been achieved by genotyping additional short tandem repeat markers in regions like 12p, suggesting that other factors contribute to the relatively wide linkage intervals, potentially including incomplete penetrance, genetic heterogeneity, environmental phenocopies, and multiple genetic determinants within a linkage peak. Now that these regions of linkage have been identified, positional candidate genes can be tested for association to COPD-related phenotypes, and systematic screening across regions of linkage can be performed.

Several recent studies have reported genome scan linkage analysis of pulmonary function measurements in general population samples. Joost and colleagues analyzed quantitative prebronchodilator spirometric measurements in 1,578 individuals from 330 pedigrees in the Framingham Study using the variance component linkage method in the SOLAR program (26). They found suggestive linkage of FEV₁ to chromosome 6q, with a maximum LOD score of 2.4. After genotyping additional STR markers on chromosome 6q in a subset of that population, the evidence for linkage to FEV₁ increased substantially, with a maximum LOD score of 5.0 (27).

Malhotra and colleagues also performed genome scan linkage analysis of prebronchodilator spirometric measurements in a sample of 264 individuals from 26 extended pedigrees from the CEPH project that were not selected for any respiratory disease (28). They found suggestive evidence for linkage of FEV₁/FVC to chromosome 2q, in a similar region to the significant FEV₁/FVC linkage reported in the Boston Early-Onset COPD Study, as well as to chromosome 5q.

Thus far, the linkage results of spirometric measurements in the early-onset COPD pedigrees and general population pedigrees have not been very consistent—with the notable exception of the FEV₁/FVC linkage to chromosome 2q. Of interest, that chromosomal region was not linked to qualitative airflow obstruction measurements in the Boston Early-Onset COPD Study, and the genetic determinant in that region (if it exists) could influence dysanapsis rather than severe airflow obstruction—which would be relevant to both COPD and general population samples. Possible explanations for the otherwise inconsistent results between linkage analysis in families with COPD and general population pedigrees include: (i) genetic determinants of normal spirometry may differ from COPD; (ii) multiple genetic determinants of these spirometric measurements may be present, and there may not be adequate power to detect them all; and (iii) different genetic determinants may be important in different source populations. Clearly, additional linkage studies in both families with COPD and families unselected for respiratory disease will be required before a definitive conclusion can be reached regarding common genetic determinants of normal variation in spirometry and COPD.

Association Studies of Candidate Genes

A series of genetic association studies have compared the distribution in subjects with COPD and control subjects of variants within genes that were hypothesized to be involved in the development of COPD based on COPD pathophysiology (summarized in Ref. 29). In addition to heterozygosity of the Z allele at the PI locus, other genetic loci in protease/antiprotease pathways, as well as candidate genes from oxidant/antioxidant and other pathways, have been assessed as possible candidate genes in COPD. In general, the results of these genetic association studies have been inconsistent, with positive findings in one study not being replicated in another study.

A variety of factors could contribute to the inconsistent results of previous COPD case-control genetic association studies (30). Genetic heterogeneity between different study populations could contribute to inconsistent replication. False-positive or false-negative results, potentially exacerbated by the small sample sizes that have been used in many COPD genetic association studies, could lead to inconsistent results. Case-control genetic association studies are susceptible to false-positive (and false-negative) associations due to population stratification (31). No case-control association studies in COPD have been reported that assessed for population stratification effects. Other methodologic problems in some previous case-control COPD genetic association studies have included the failure to assess for Hardy-Weinberg equilibrium in the control group and the lack of adjustment for the multiple statistical comparisons involved in studying more than one genetic locus. In addition, as noted above, no association studies based on positional candidate genes selected from the recent linkage studies in COPD have been published.

Thus far, based on the inconsistent results of COPD genetic association studies, no COPD genetic determinants (other than severe AAT deficiency) have been identified with certainty. Nonetheless, it is quite possible that at least some of the inconsistently associated candidate genes will ultimately prove to be valid COPD susceptibility genes. Moreover, the recent genetic linkage studies of COPD have provided an array of positional candidate genes for future association studies. Further efforts at replication of significant genetic associations using large sample sizes and demonstration of functional significance of associated genetic variants using animal models and/or in vitro systems will be required to confirm novel genetic determinants of COPD susceptibility.

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Single Nucleotide Polymorphisms, Chips, and Functional Genomics in Acute Lung Injury

HopGene Program in Genomic Applications

The nineteenth-century German mathematician David Hilbert aptly stated that "significant advances require the development of sharper tools for exploration" (3). Until recently, studies targeting the molecular basis of complex disorders, such as ALI, were limited to a gene-by-gene approach. The capacity for high-throughput sequencing, coupled with the mapping of the Human Genome, heralded additional revolutionary technologic breakthroughs with tools for a large-scale analysis of the genome, including rapid, high-throughput gene expression profiling and genotyping. Access to the complete genome sequences of prokaryotes, eukaryotic model organisms, and the mouse, rat, and canine genome sequences has sparked efforts to identify specific gene expression patterns via large-scale microarray analysis that will ultimately help diagnose, prognosticate, guide therapy, or otherwise contribute to our overall understanding of human disease.

Increasing evidence derived from association-based studies suggests that genetic variations contribute to ALI susceptibility and severity (4–9). The genetic basis of ALI remains incompletely understood, with multiple factors increasing the difficulty in defining the exact nature of genetic factors relevant to ALI. For example, ALI arises from diverse precipitating factors in a critically ill population exhibiting large phenotypic variance. Incomplete gene penetrance, complex gene–environment interactions, and a strong potential for locus heterogeneity further contribute to the challenge of identifying ALI genetic factors. The sporadic nature of ALI precludes a conventional genomic approach such as heritability studies or linkage mapping (or "positional cloning"), a strategy which is effective in other lung disorders, such as asthma, where large families with both affected and unaffected individuals can be examined for loci linked to the trait of interest (as described elsewhere in this Supplement).

The HopGene Program for Genomic Applications (PGA) is an NHLBI-sponsored program targeting the elucidation of the genetic basis of several complex lung disorders, including asthma, chronic obstructive pulmonary disease (COPD), cystic fibrosis, pulmonary hypertension, lung transplant rejection, and sarcoidosis. In this quest, HopGene has embraced a "candidate gene approach" with extensive gene expression profiling studies in animal models of human lung disease to identify potential candidate genes (http://www.hopkins-genomics.org) (see Figure 1). Our preliminary evaluation, focusing on ALI, suggests that the candidate gene approach is a robust strategy to provide novel insights into the genetic basis of this poorly understood trait, and for the identification of potentially novel therapeutic targets. This program has provided invaluable resources available on the HopGene Website (Table 1) for the study of ALI. Additional resources are available for the heart, lung, blood, and sleep research community (array analysis and normalization software, single nucleotide polymorphism (SNP) analysis, phenotyping of animal models of disease) on the PGA home page (http://www.nhlbi.nih.gov/resources/pga).

View larger version (19K): [in this window] [in a new window]   Figure 1. Overview of the candidate gene approach. Candidate genes are identified by expression arrays from both human disease and animal models of human disease, or by published association or linkage studies. The selection of these candidate genes for further genotyping are validated using knockout and transgenic technologies, and the structure and function of their corresponding gene products are evaluated using proteomic methods. Ultimately, genotyping of SNPs in these genes using well phenotyped patient populations will allow the identification of genetic polymorphisms in disease-specific predictor genes that are associated with increased risk or severity of disorders such as acute lung injury.

Case-control studies, hampered by small cohort sizes (typically < 100 patients), have demonstrated the preliminary applicability of the candidate gene approach to the analysis of acute respiratory distress syndrome (ARDS)/ALI (10–12) with implied associations between the frequency of the target variant allele (polymorphism) in a given gene and ALI. These studies have suggested that polymorphisms in genes encoding pulmonary surfactant proteins (for example the Thr131Ile amino acid variant in the gene encoding SP-B) may be associated with ALI (10, 12) and contribute to disease susceptibility. The availability of large, public databases facilitates the study of an association between one or more SNPs and a disease.

Although the search for candidate genes for any trait (especially in the absence of heritability or linkage data) is daunting, expression profiling with robust genechip arrays from animal models of disease or human tissues is helpful in identifying potential candidates and in the selection of genes for subsequent SNP analysis on the basis of either enhanced or reduced expression. As an excellent example, we sought to identify genetic determinants that render patients susceptible to the adverse effects of mechanical ventilation and to the resultant increased mechanical stress observed in the setting of ALI. We generated extensive array data for models of ventilator-associated ALI (rat, murine, canine, human), allowing us to build an ALI candidate gene list with preliminary evaluation for relevant SNPs and genotyping of these variants which can be found on the HopGene website (http://www.hopkins-genomics.org). Recent reports have underscored the utility of this approach (13, 14). These findings indicate that gene expression alterations in response to mechanical ventilation alone, in the absence of additional inflammatory stimuli, are easily detected by microarray techniques and provide a powerful framework to characterize normal lung responses to mechano-transduction stresses. Upregulation of genes such as IL-1B, HSP70, and key transcription factors are of obvious significance in stretch-induced lung injury (15–18) and ARDS (19), again consistent with very early signal amplification which begins to evolve into a mechanically-stimulated inflammatory phenotype.

As ALI susceptibility and severity are unlikely to be determined by the activity of a single gene, we employed a bioinformatics approach to gene expression data and ontology analyses to identify groups of genes that may be involved in the response to mechanical stress (20). Known biological pathways and genes (either activated or suppressed by exposure to mechanical stress) were used to validate novel candidate genes that were implicated in the same pathway. Using an ortholog database created by HopGene scientists (20), the responses of four different biological systems (rat, mouse, dog, and human lung endothelial cells) to levels of mechanical stretch relevant to ALI were investigated. Figure 2 demonstrates that the major mechanical stretch-related ALI biological process was blood coagulation with genes in this ontology including fibrinogen A, coagulation factor III, plasminogen activator, urokinase receptor (uPAR), tissue factor, and plasminogen activator inhibitor type 1 (PAI-1). These same genes have been implicated elsewhere as potential ALI gene candidates (21–23) and in ventilator-induced lung injury (24, 25). In addition to coagulation, other ontologies included inflammation, immune response, and cell motility/chemotaxis. Interleukin (IL)-1 and IL-6 genes were common to three of these four categories consistent with potential roles as major ALI candidate genes. Interestingly, IL-1 and IL-6 concentrations are elevated in bronchoalveolar lavage fluid (BALF) from patients with established severe ALI (26, 27) and overexpression of IL-1 leads to ALI in mouse lungs (28). A detailed list of the genes identified by this approach can be accessed on the HopGene website (http://www.hopkins-genomics.org). Based on these reports and data generated by our cross-species analysis of ALI, we speculate that mechanical stretch directly upregulates coagulation and inflammatory gene expression by pulmonary endothelium accompanied by activation of the coagulation cascade, inflammatory cell recruitment, and the development of ALI, a scenario consistent with clinical reports on the effect of excessive tidal volume ventilation (29). Although provocative, further studies of ALI are obviously needed, especially focusing on the time-course analysis of expression pattern of selected candidate genes in response to ALI.

View larger version (60K): [in this window] [in a new window]   Figure 2. Genomic schema depicting pathobiologic events in acute lung injury. Mechanical stress and stimuli (such as the bacteria lipopolysaccharide, LPS), activate both alveolar and lung endothelial cells, resulting in induction of innate immunity genes. Gene activation facilitates inflammatory pathways and increased vascular permeability through paracellular endothelial gaps and ultimately alveolar flooding. Variation in the expression of these genes may help to explain differences in susceptibility to and severity of acute lung injury in the population.

Much of the genetic variation between individuals lies in differences known as SNPs, which are variant forms of genes that occur in at least 1% of the population. Although most SNPs do not have a functional effect, these types of polymorphisms can influence either the transcriptional regulation of the gene, if the SNP resides within the promoter region, or alter the structure/function of the gene product (i.e., protein) via processes which might include post-translational modification. The underpinning of this approach is that an association between functional variants of a gene and a clinical phenotype may help to identify key pathophysiologic processes during disease and provide genetic factors and potential therapeutic targets. SNPs can be used by epidemiologic associations to test susceptibilities to common diseases as well as explain the diversity of clinical manifestations, outcome, and risk of chronicity among patients with a given disease. A large number of human SNPs are available through public databases (http://www.ncbi.nlm.nih.gov/SNP/snp_summary.cgi) with > 5 million SNPs to date.

The HopGene program has experienced substantial success in using the candidate gene approach in the complex lung disease of ALI via extensive temporal expression profiling in human, rodent, and canine models of sepsis/ventilator-associated lung injury (VALI), which has allowed the generation of a robust candidate gene list (Table 2). We have confirmed altered expression in several reported candidates (such as IL-6, AQP1, MIF, PAI1) (5, 7, 28, 30–32) as well as several unknown candidates (PBEF, MLCK, TSP, IL-1RA, FRA-1) (6, 8, 11, 15, 33) with prominent representation of genes involved in the innate immunity pathway (MIF, CD14, TNF, IL-1RA, C5aR, IL-6) (see Figure 3). We have preliminarily explored the relevance of these candidates in defining risk factors and ethnic predilection in patients with ALI, as well as the potential genetic influences on ALI susceptibility and outcome, a process which has been greatly facilitated by the development of an ALI Genomic DNA Repository. This DNA bank from patients with sepsis and ALI (currently 450 samples), involves a collaborative enrollment network entitled Consortium to Evaluate Lung Edema Genetics (CELEG) spearheaded by scientists from HopGene and Physiologic Genomics PGAs (http://pga.mcw.edu/). Preliminary genotyping of patients with sepsis, patients with ALI, and control subjects revealed an astonishing ethnic-specific predilection of allelic variants in candidate genes associated with ALI among the African-American patients with ALI and sepsis (5–7).

View larger version (13K): [in this window] [in a new window]   Figure 3. Bioinformatic evaluation of lung gene ontologies involved in the response to mechanical stress. We used MAPPFinder (www.genMAPP.org), a program that uses a relational database to link the thousands of genes in an array dataset with corresponding gene ontologies (GOs), to identify gene ontologies involved in the response to mechanical ventilation or cyclic stretch across four species (rat, mouse, canine, human) (detailed in Ref. 20). MappFinder displays results in a searchable browser that allows the identification of specific gene ontologies with high levels of gene expression changes. The relative importance of an ontology is represented by the z score, a statistical rating of the relative gene expression activity for each ontology term in each MAPP. The z score is used to rank GO terms by the relative amounts of gene expression changes. GenMAPP (Gene MicroArray Pathoway Profiler at www.genMAPP.org) is an application that allows gene expression data to be organized in maps representing biological pathways and gene groupings. A MAPP thus generated shows biological relationships between genes and gene products, giving experimental gene array expression data a biological context. Data were filtered by number of genes changed, z score (> 3.0), and % change ( 10%).

With the completion of the Human Genome Project, the availability of high-throughput biology and parallel developments in computational analysis has heralded the era of molecular medicine and revolutionized the concept of translational biomedical research. For pulmonary scientists, the quest is to understand the genetic basis of highly complex lung pathophysiology as well as the role of genes in normal human lung development and physiology. Significant challenges to the exploration of the genetic basis of complex lung disorders exist for diseases such as ALI. However, advantaged by the HopGene PGA, our data strongly indicate that the candidate gene approach, when coupled to creative bioinformatics approaches and extensive expression profiling, can yield novel and valuable information delineating genetic factors in ALI. Further analysis of select candidate genes by additional SNP discovery and mid- or high-level throughput genotyping will undoubtedly provide important insights into the genetic basis for ALI susceptibility and severity. This explosion in genomic discovery is generating mechanistic insights into the complex ALI pathobiologic processes with the ultimate goal to translate this knowledge to the bedside. The era of molecular medicine, in its truest sense, represents the capacity of genomics to bring clinicians, clinician-scientists, and basic biomedical biologists together for a common goal in a way not previously imagined. Critical care physicians of the future will be armed with high-throughput technologies and phenotyping protocols that will customize care of the patient in the ICU, improve the survival of patients with critical illness, and herald a new era in critical care medicine.

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Resolving Gene–Environment Interactions in Complex Traits

Acute Lung Injury

Acute lung injury is a common and often fatal respiratory condition ( 150,000 cases with 45,000 deaths/yr in the United States) (1–5). The etiology of this syndrome is complex and associated with numerous, chemically diverse precipitating factors including smoke inhalation, hyperoxia, near drowning, local or systemic infection (pneumonia or sepsis), and trauma. Its pathology is marked by epithelial and endothelial cell damage, cytokine and reactive oxygen/nitrogen species release, inflammatory cell sequestration and activation, and prothrombotic events. Together these changes trigger immediate and delayed responses through proteinase activation and growth factor receptor signaling. Manifested histologically as diffuse alveolar and endothelial damage, acute lung injury is marked by structural impairment in the alveolar–capillary surface. Injury to the alveolar–capillary membrane disrupts the endothelial barrier, with subsequent increased pulmonary vascular permeability, progressive inflammation, and noncardiogenic pulmonary edema. Gas exchange and mechanical properties of the lung decline as air and interstitial spaces fill with fluid (6, 7). Serum-laden fluid inactivates pulmonary surfactant, particularly in the absence of surfactant-associated proteins (SFTP) (8–16). These events underlie the principal clinical manifestations of the syndrome—pulmonary edema, surfactant disruption, and atelectasis—that culminate in respiratory failure.

Acute lung injury is sometimes used interchangeably with acute respiratory distress syndrome (ARDS); however, by strict criteria, ARDS has been reserved for the most severe cases of acute lung injury (17). Likewise, acute lung injury can encompass other syndromes, including infant respiratory distress syndrome and severe acute respiratory syndrome (SARS), which can progress to acute lung injury (18).

Although extensive information has been obtained regarding the molecular mechanisms that control acute lung injury, the clinical value of these findings has had mixed success. Several past studies have identified numerous mediators in bronchoalveolar (BAL) fluid or the circulation of persons suffering from this condition in attempts to find biological markers with prognostic value in predicting survival (19, 20). Similarly, mediators have been identified in animal models of acute lung injury that involve induction by sepsis, lipopolysaccharide (LPS), hyperoxia, embolism, or oleic acid (21). Data from these models have been combined with clinical experience in attempts to develop supportive measures including adjustment of ventilatory pressure. Embarking on a parallel but alternative strategy to better understand this complex process, we have joined others who have employed functional genomic approaches that take advantage of information rapidly emerging from the human and mouse genome projects (22–32).

Our approach involves the combined analyses of genome-wide mapping (linkage analysis), differential gene expression (microarray), and mouse transgenesis to investigate genes that control susceptibility to acute lung injury. The purpose of starting with a linkage analysis with polymorphic DNA markers distributed throughout the mouse genome is to identify genomic regions that co-segregate with a phenotype. Thus, by probing the entire genome without a priori assumptions of the role of a specific mediator or pathway, novel insights on this perplexing condition are beginning to arise. Using a model species with paralleled genomic information anticipates a homology search in humans.

Genetic Approach to Determine Loci Linked to a Phenotype

Several genetic tools have been developed to determine the factors controlling a phenotype of interest. Traits of human biological significance are frequently quantitative in nature. A quantitative trait is a phenotype that can be measured as a continuous variable among different individuals. Often, quantitative traits are controlled by the cumulative action of alleles at multiple loci, and multiple gene–environment interactions. Because of the numerous factors involved in trait variation, genetic analysis of these complex traits by classical Mendelian methods is not possible. However, due to advances in statistical programs capable of analyzing extensive genetic data, rapid quantitative trait mapping became feasible (33, 34). When combined with selective breeding designs in animals, this approach identifies loci that later can be compared for synteny in humans.

Quantitative traits are most amenable to genetic analysis in mice, when different inbred strains have nonoverlapping phenotype distributions among 20 members/strain (35). Determination of the quantitative trait locus (QTL) locations by linkage analysis relies on a high-density genetic map of polymorphic DNA markers (36, 37). First, the phenotypes of backcross or F₂ mice generated from the two progenitor strains are determined. Next, each mouse is genotyped for DNA markers spaced throughout the genome (genome-wide scan). This genetic information reveals chromosomal regions segregating with (likely to encode genes that influence) the phenotype (33, 38). Marker loci (genotype) with the greatest frequencies of association with the trait (phenotype) are assumed "linked" to (i.e., physically near) the locus encoding the gene that causally influences the trait. We have successfully identified genetic loci with linkage to acute lung injury in mice.

The use of inbred mice for initial determination of genetic traits controlling human conditions has several advantages. First, inbred mice allow research to focus on the mechanisms of resistance. For example, at high irritant concentrations, clear distinctions in susceptibility among inbred strains of mice have been determined, suggesting a genetic component to the trait. Second, the number of related subjects having the desired trait is usually limited and costly, difficult, and time-consuming to determine in the general population. However, once the trait of interest is determined in mice, they can be bred appropriately to give desired numbers of offspring quickly. Third, classic methods for human population genetics (i.e., familial or other linkage studies) require a large number of related individuals with a proportionate number of affected subjects to determine the pattern of inheritance. This is often a limiting factor in genetic analysis, but is an almost insurmountable challenge for acute injury that sporadically inflicts family members. Finally, because the mouse genome has been mapped and is in large part (> 97%) syntenic with the human genome, determination of homologous genes in humans will be significantly accelerated.

The mouse has proven to be a powerful model species for the dissection of genetic factors contributing to complex disorders (39, 40) and the identification of modifier genes for variable phenotypes such as cancer predisposition (41), coagulation disorders (42–43), and susceptibility to infection (44, 45). Genomics approaches afford the ability to uncover gene(s) not previously associated with acute lung injury. Such discoveries, although requiring considerable time and effort, can yield new information about the underlying biology of a disease process. Alternatively, the major gene(s) identified in newly discovered QTLs (and modifiers) could be existing genes currently associated with the disease process. This outcome would provide added significance to one or two of the hundreds of proteins associated with a condition, because thousands of genes are analyzed through a genomic scan. Either result could yield information valuable in assessing further therapeutic strategies and genetic differences that alter susceptibility.

Animal Models of Acute Lung Injury

A prominent feature of acute lung injury is the release of reactive oxygen/nitrogen species, inflammatory mediators, and the activation of proteinases. These events often precede or are coincident to a marked influx of polymorphonuclear leukocytes (PMNs, primarily neutrophils), and the latter has been a major focus of many investigations using animal models. In humans, neutrophil influx into the airspaces occurs before the development of acute lung injury (46–48). However, ARDS may also develop in patients with neutropenia (49, 50). Although PMNs can play a direct or indirect role in acute lung injury in certain circumstances (51), auxiliary non–PMN-dependent pathways (including those involving activated macrophages) also exist.

Considerable evidence supports the hypothesis that reactive oxygen/nitrogen species contribute to the development of acute lung injury (52–58). However, the source, nature, and local effects of the oxidants are not completely understood (e.g., NO remains somewhat controversial). One source may be phagocytic cells that produce reactive species, which in turn oxidize proteins/lipids in cell membranes (59, 60). Patients with ARDS exhibit increased levels of volatile oxidants in exhaled breath (61–63) and oxidized lipids and proteins in their BAL fluid (64–67). The lung interstitial matrix and basement membrane are also damaged by oxygen-derived species, leading to increased edema formation (68, 69). Reactive species can stimulate the release of chemotactic factors and other mediators. Normally, endogenous antioxidant systems limit damage by oxidative reactions, but excessive oxidant injury is a central feature of many diseases (70, 71) and occurs when antioxidant defenses are overwhelmed (72).

These observations have led to diverse animal models to mimic certain attributes of lung injury. Each has strengths and weaknesses, and collectively they have advanced our understanding of the pathophysiology and possible mechanisms of the human disease. Animal models of acute lung injury include direct (e.g., inhaled or aspirated agents, embolism, lung contusion, near drowning, or infectious pneumonia) and indirect (e.g., trauma, sepsis, reperfusion, or pancreatitis) insults that cause the pulmonary damage (17, 21). Agents can be administered into the airway (e.g., hyperoxia, phorbol ester, immune complexes, oxidant-generating systems, or complement) or via the circulation (e.g., bacterial products, oleic acid, phorbol ester, oxidant-generating systems, eicosanoids, cytokines, fibrinopeptides, microemboli, or drugs) (73). Some animal models of acute lung injury are neutrophil-dependent (including gram-negative endotoxin, phorbol ester, cobra venom factor, hyperoxia, microembolisms, and complement), whereas others are neutrophil-independent (e.g., gram-positive endotoxin, oleic acid, and oxidant-generating systems). These studies have been conducted in laboratory species including the mouse, which offers many advantages for genomics and transgenic studies. As evidenced by the diversity of animal models, acute lung injury appears to be a common outcome of many different biochemical events.

Nickel-Induced Acute Lung Injury

Previously, several genetic studies have examined susceptibility to lung injury induced by a common respiratory oxidant, ozone. Individuals vary in sensitivity to bronchoconstriction (74, 75) and inbred mouse strains vary in sensitivity to acute lung injury, pulmonary inflammation, and BAL protein (76–100). In mice, ozone-induced acute lung injury is a polygenic trait controlled by multiple genetic loci that differ from those controlling PMN migration or BAL protein levels. Less is known about the susceptibility to other irritants. We reasoned that because numerous agonists can induce acute lung injury, studying additional agonists could reveal common mechanisms that evoke pathways that control macrophage activation, epithelial injury, and activation of proteinases (101–103). For example, insoluble ultrafine particulate matter, such as those generated from polytetrafluoroethylene (PTFE), can induce acute lung injury (101, 104, 105). We found a similar strain phenotype pattern for acute lung injury in mice after exposure to PTFE as with ozone (106, 107).

Because certain transition metals also can induce acute lung injury, we subsequently studied particulate NiSO₄. These studies were derived from studies of particulate matter that indicated water-soluble metals (e.g., nickel, vanadium, or chromium) are, in part, responsible for the observed lung injury, inflammation, and macrophage activation (108–117). Transition metals also can lead to oxidative stress directly (through redox cycling when electrochemical potential is favored in a biological medium) or indirectly (through leukocyte priming and activation, through interactions with amino acids, or through the displacement of other metals that can redox cycle) (118–123). In addition, transition metals (particularly zinc) are essential, and are contained in the reactive domains of several activating enzymes including those in the following proteinase families: matrix metalloproteinase (MMP), A Disintegrin And Metalloproteinase (ADAM), and A Disintegrin And Metalloproteinase domain, with ThromboSpondin type-1 modules (ADAMTS).

Exposure to low NiSO₄ concentrations (i.e., below the current occupational standard: 100 µg Ni/m³) produced acute lung injury that progresses slower than that caused by ozone (thereby resembling a delayed clinical course noted in humans) (106). Reported cases of NiSO₄ poisonings and acute lung injury in humans are limited. Nonetheless, of the metals with extensive human exposure in the environment, nickel compounds are particularly pernicious (124–126). Nickel exists primarily in soluble (e.g., NiSO₄) and insoluble (e.g., NiO and elemental Ni) forms that enter the environment via high temperature combustion, electroplating, and smelting processes (125–129). Nickel concentrations in natural settings are usually low (0.0006–0.08 µg/m³) but can be higher in industrialized areas (0.3 µg/m³) (129–131). Nickel concentrations near production sites are not measured routinely, but at one site in Canada, median levels ranged from 0.001 to 0.7 µg/m³ (132) with excursions up to 6 µg/m³ (133–135), and another U.S. site reached 15 µg/m³ (136). Soluble and insoluble nickel species are components of mainstream cigarette smoke in concentrations (0.35 µg Ni/cigarette) (137), and toxic release inventories into the air exceed 1.0 billion lbs/yr (138). The USEPA estimates that 160 million people live within 12.5 miles of Ni-emitting sources (136). In occupational environments, soluble NiSO₄ concentrations have averaged 260–760 µg Ni/m³ with short-term peaks exceeding 2,000 µg/m³ (124, 139). Occupational levels of both soluble and insoluble nickel have ranged from 200 to 10,000 µg/m³ (124, 139). Because chronic pulmonary disease including pulmonary fibrosis may result from these exposures (140–142), the recommended occupational standard is 100 µg Ni/m³.

The respiratory tract is the primary target tissue of inhaled nickel compounds. The insoluble forms (e.g., nickel subsulfide and nickel oxide) are thought to be more carcinogenic (126, 143–147), whereas soluble forms (e.g., nickel sulfate, nickel chloride, and nickel acetate) are more acutely irritating (136, 140, 143, 146–150). Similar to soluble nickel, gaseous forms of nickel (e.g., nickel carbonyl that is produced by combining nickel with carbon monoxide) are acutely irritating to the lung. Submicrometer soluble nickel aerosols (like that used in our studies) and nickel carbonyl can penetrate the conducting airways to the alveolus, and are capable of crossing membranes rapidly, delivering ionic nickel (Ni²⁺) to the cytoplasm (151). Nickel carbonyl has been associated with numerous incidences of acute lung injury and death among welders (152–156). We have studied submicrometer NiSO₄ instead of nickel carbonyl for several reasons. The primary reason is that nickel carbonyl is difficult to produce and exposure concentrations are hard to control. In addition, nickel sulfate is typically one of the largest contributors (often 50%) of complex occupational exposures that include other nickel species (129, 139, 157–159).

Although it is unknown whether NiSO₄ is associated with human acute lung injury, it has proven useful to model this injury in mice with this compound. Initially we examined ozone-induced acute lung injury and found survival to be a complex trait controlled by at least three QTLs, designated acute lung injury QTL1 (Aliq1), Aliq2, and Aliq3. We then explored whether similar genes might be involved in survival to 100 µg/m³ NiSO₄-induced acute lung injury, taking advantage of the 2-fold difference in MSTs between the sensitive A/J and resistant C57BL/6J inbred mouse strains (99). QTL analysis of 307 backcross mice generated from these strains identified significant linkage to chromosome 6 (Aliq4) and suggestive linkages on chromosomes 1, 9, 12, and 16. Comparing MSTs of backcross mice with similar haplotypes identified an allelic combination of 4–5 QTLs that could account for the difference in survival time between the parental strains. Importantly, the QTL intervals on chromosomes 6 and 12 were previously identified with ozone (98), suggesting that the interplay between different combinations of relatively few genes might be important for irritant-induced acute lung injury survival. Furthermore, the region on chromosome 6 contained several candidate genes including transforming growth factor- (TGF-) and surfactant-associated protein B (Sftpb).

The concentrations of NiSO₄ used in our studies are reasonable when compared with occupational exposures, with as little as 3–24 h of exposure to 100 µg Ni/m³ altering expression of numerous genes related to acute lung injury (58, 160). Clustering of co-regulated genes (i.e., genes displaying similar temporal expression patterns) revealed the altered expression of relatively few genes (about one hundred of the thousands probed). Increased mRNA levels occurred in several genes associated with host defense, extracellular matrix injury and repair, and hypoxia-inducible factor–mediated sequences (Figure 1). For example, five genes related to host defense (e.g., oxidative stress) were increased within 3–8 h and included metallothionein 1 (> 10-fold), glutamate-cysteine ligase, catalytic/modifier subunits (> 5-fold), heme oxygenase 1 (> 4-fold), lysyl oxidase (> 3 fold), and thioredoxin reductase 1 (> 2-fold). The expression of p21 (synonymous with cyclin-dependent kinase inhibitor 1A) also increased rapidly, and this gene is associated with cell cycle arrest. Subsequent to these changes, mRNA levels of lung-specific genes declined to 5–20% of control and included surfactant proteins (especially Sftpb and Sftpc), uteroglobin (synonymous with Clara cell secretory protein), and cytochrome P450 enzymes.

View larger version (20K): [in this window] [in a new window]   Figure 1. Temporal relationship of functional gene clusters during acute lung injury in mice. Microarray analysis of lung mRNA during exposure to nickel sulfate (or hyperoxia) demonstrated immediate (starting within 3–8 h) increases in genes associated with Host Defense (including increased metallothionein-1; heme oxygenase 1; glutamate cysteine ligase, catalytic subunit; thioredoxin reductase 1; lysyl oxidase) and Signal Transduction (including increased cyclin-dependent kinase inhibitor 1A [P21]; signal transducer and activator of transcription 3). This was followed (beginning around 24 h) by increases in genes associated with Extracellular Matrix Repair and Remodeling (including cysteine-rich protein 61; secreted phosphoprotein 1 [osteopontin]; thrombospondin 1; tenascin C; lectin, galactose binding, soluble 3; resistin like [found in inflammatory zone 1]; small proline-rich protein 1A; integrin V; follistatin) and Protease (matrix metalloproteinase 3 [stromelysin 1]; cathepsin H; matrix metalloproteinase 9) and Antiprotease activity (including serine [or cysteine] proteinase inhibitor, clade E, member 1 [Plasminogen activator inhibitor, type I]; tissue inhibitor of metalloproteinase 1). This period is accompanied with increases in transcript levels of several Epidermal Growth Factor Receptor Ligands (including transforming growth factor , amphiregulin, betacellulin, and epiregulin). Also delayed by 24–48 h is a decrease in genes involved in Lung Epithelial Cell Function (including surfactant associated protein A, B, and C; uteroglobin; cytochrome P450, family 2, subfamily f, polypeptide 2).

Other related genes associated with extracellular matrix injury, repair and remodeling that were changed during nickel-induced acute lung injury included: secreted phosphoprotein 1 (osteopontin); thrombospondin 1; tenascin C; lectin, galactose binding, soluble 3; resistin like (found in inflammatory zone 1); small proline-rich protein 1A; integrin V; and follistatin. These genes increased with changes in proteases [including matrix metalloproteinase 3 (stromelysin 1); cathepsin H; matrix metalloproteinase 9] and anti-proteases [including serine (or cysteine) proteinase inhibitor, clade E, member 1 (Plasminogen activator inhibitor, type I); tissue inhibitor of metalloproteinase 1].

Epidermal Growth Factor Receptor in Lung Injury

Because we had found that TGF- was contained in the QTL associated with survival during acute lung injury in mice exposed to ozone or nickel (Aliq4), we wanted to explore the possible role of its receptor, epidermal growth factor receptor (EGFR) (V-ERB-B Avian Erythrobastic leukemia viral oncogene homolog: ErbB1, or Herstatin: HER1), in lung injury. This receptor transduces signals from the extracellular milieu to trigger diverse cell functions critical to organogenesis, tissue maintenance and repair, and, when dysregulated, to lung cancer (162–164). EGFR belongs to a receptor tyrosine kinases protein family (with the related proteins: ErbB2/Neu/HER2, ErbB3/HER3, and ErbB4/HER4) (165). Depending on the activating ligand, EGFR family members form various homo- or heterodimers with different biological capacities (166). EGFR signaling regulates development in Drosophila, nematodes, and mice and is critical in humans, as underscored by its frequent involvement in cancer (167).

The major ligands for EGFR include: EGF, TGF-, heparin-binding EGF-like growth factor (HB-EGF), amphiregulin, betacellulin, heregulin, epiregulin, and epigen. Each is synthesized as a transmembrane precursor and is proteolytically cleaved by metalloproteinases to release the mature protein (168). Ligand-occupied EGFR undergoes autophosphorylation and activates four signaling pathways. The initial one studied was the mitogen-activated protein kinase (MAPK)/extracellular regulated kinase (ERK) pathway, which is activated through tyrosine phosphorylation of the adaptor protein SHC, subsequent formation of a SHC-Grb2-Sos complex, and Ras-mediated induction of Raf1 function (169). This signaling pathway couples EGFR stimulation to gene transcription and mitogenesis. In addition, three other activation pathways downstream from EGFR include: (i) cJun NH₂-terminal kinase (JNK)/stress-activated protein kinase (SAPK) pathway; (ii) p38 MAPK/p21-activated protein kinase (PAK) pathway; and (iii) "big MAP kinase"/mitogen-activated, extracellular-regulated kinase 5 (MEK5)-ERK5 pathway (170). Initially, these processes were thought to be controlled by metalloproteinase activation of ligands, but in recent years, it is recognized that ligand binding transactivation may be influenced by additional mechanisms. These include cell surface receptor cross-talk (e.g., between receptor tyrosine kinases and G protein–coupled receptors [GPCRs]), receptor–extracellular matrix interactions (e.g., EGFR:integrin complexes), intracellular activation, and by structural mutations within the receptor itself (165, 167).

Transmembrane growth factor precursor activation, nonetheless, is the major activation event and is dependent on cleavage by metalloproteinases. These enzymes contain transition metals within their catalytic domains (171, 172). These domains may be influenced by interaction/displacement with other metals. For example, exogenous transition metals can increase and decrease MMP-2 and MMP-9 activity in vitro (173, 174); thus, they may modulate the availability of EGFR ligand (174). In addition, activation of EGFR and proteins in downstream signaling pathways may be influenced directly because transition metals (particularly V, As, Cu, or Zn) can induce EGFR autophosphorylation. EGFR inhibitors diminish metal-induced phosphorylation of downstream kinases in cultured airway epithelial cells (175–178). In addition, the effects of ultrafine particles, which can be mediated through oxidative stress (179–181), induce TGF- and other EGFR ligand gene expression in vitro (182).

Six EGFR ligands (including TGF-, EGF, HB-EGF, amphiregulin, betacellulin, and heregulin) have been localized to the lung (or in lung cells) (183–189). Other EGFR ligands that have yet to be observed in the lung include epiregulin (190) and epigen (191). In mice, our microarray analyses yielded significant increases (> 2-fold with a false discovery rate < 0.10) in TGF-, amphiregulin, betacellulin, and epiregulin, but not in EGF or HB-EGF (heregulin and epigen were not in the array library tested). Although proteolytic cleavage is the most effective activation mechanism, ligands can engage and activate EGFR in both their soluble and membrane-anchored forms that may be tethered to a substratum (192–195). In addition, EGFR signaling and mitogenesis can be fully signaled from plasma membrane–restricted receptors (194, 196). Because internalization of ligand serves to attenuate signaling (194, 197) presenting an EGFR ligand as part of a larger extracellular complex allows complex signaling and modulatory possibilities. For example, matrix bound ligand can co-position activated integrin and growth factor receptors to modulate integrin functioning in processes like cell migration.

Role of TGF- in Lung Injury

Typically, TGF- is synthesized as a 160–amino acid membrane anchored pro-peptide, which becomes a mature, 50–amino acid active peptide upon release through proteolytic cleavage (198). This may be accomplished by proteinases that are activated at sites of injury, including MMPs and ADAMs (e.g., ADAM17, also known as TNF-–converting enzyme [TACE]) (184, 199). Studies using metalloproteinase inhibitors demonstrated that cleavage of EGF ligands to the soluble form enhance induction of cell proliferation (200).

The cellular production sites and maximal levels of TGF- and accompanying EGFR ligands vary during injury. Produced throughout gestation, TGF- plays a role in the growth of the developing (201) and postnatal lung (202). A mitogen for many types of epithelial and mesenchymal cells (198), TGF- induces pulmonary epithelial cell proliferation (203), motility, and spreading (204). Mechanically denuded regions of confluent alveolar epithelial cell monolayers returned to confluence more rapidly in the presence of exogenous TGF-, and a neutralizing antibody to TGF-, in the absence of exogenous peptide, reduced the rate of repair (204). Similarly, interleukin (IL)-1ß enhanced wound repair in these cells (205), and the IL-13–enhanced proliferation of human bronchial epithelial cells (206) can be inhibited by a neutralizing TGF- antibody or treatment with EGFR inhibitors, indicating mediation through a TGF-/EGF/EGFR-dependent mechanism.

In lung injury, TGF- synthesis and secretion is increased in epithelial cells and macrophages in the lungs of infants with bronchopulmonary dysplasia (201, 207) and in LPS-stimulated human and concanavalin A–stimulated rat alveolar macrophages (208, 209). Increased TGF- is identified in alveolar epithelial and septal cells of rat lungs following bleomycin injury (210). In addition, EGFR tyrosine kinase inhibition augments bleomycin-induced pulmonary fibrosis (211) and may induce acute lung injury as a side effect in patients being treated for cancer (212). Asbestos and naphthalene increase TGF- (and EGF) in proliferating bronchiolar epithelial and interstitial cells (213, 214), and the asbestos-induced proliferation and proto-oncogene expression is reversed in mice expressing a dominant-negative mutant EGFR (215).

Topical administration of either recombinant TGF- or EGF has not been examined extensively in the lung, but has been studied in other epithelial tissues. In pigs and humans, TGF- or EGF accelerates the rate of epidermal regeneration following skin burns (216), induces antimicrobial/antiprotease peptides (including a lipocalin-related protein and secretory leukocyte protease inhibitor) (217), and enhances ocular wound healing (218). In laboratory animals, parenteral TGF- decreases gastric mucosal damage induced by ethanol, aspirin, or stress (219–224). Complementary studies using TGF- knockout and induced transgenic mice observed increased and decreased, colitis, respectively (225, 226). Moreover, a recent preliminary clinical study suggests that EGFR ligands may be an effective treatment for ulcerative colitis (227).

Importantly, epithelial EGFR and TGF- are elevated in humans and animals during several lung diseases. Enhanced EGFR-immunoreactive protein was detected in injured regions of bronchial epithelium in patients with asthma. In the same study, return to confluence of disrupted monolayers of bronchial epithelial cells was impeded by inhibitors of EGFR signaling (228). Additionally, TGF- has been identified in epithelial and interstitial cells of patients with interstitial fibrosis or cystic fibrosis (229, 230). Administration of EGF to rats enhanced postpneumonectomy lung growth compared with untreated rats (231). Hyperoxia leads to increased TGF- release from pulmonary fibroblasts, in vitro (232). As fibrosis progresses following acute injury, in vivo, TGF- protein increases (with a delayed appearance of mature lower molecular weight TGF- isoforms) (233). Furthermore, TGF- levels are increased in edema and BAL fluid of patients with acute lung injury and idiopathic pulmonary fibrosis (210, 229, 234, 235).

In our model of irritant-induced lung injury, nickel inhalation increased TGF- (and related EGFR ligands: amphiregulin, betacellulin, and epiregulin) expression on the microarray. Nickel also altered pulmonary permeability with increases in BAL protein, altered wet:dry weight ratios, and histologic evidence of perivascular and septal edema. Several lines of evidence suggest that TGF- may reduce pulmonary edema inasmuch as another EGFR ligand, EGF, delivered to rat lungs in aerosolized saline enhanced lung liquid clearance and increased Na⁺K⁺ATPase activity in alveolar epithelial cells from the treated lungs (236). TGF- enhanced clearance of instilled Ringers lactate in rats (similar to adrenergic stimulation) and this was diminished by an EGFR inhibitor. Amiloride inhibited the TGF- effect, demonstrating a role for Na⁺ transport (237), and EGF induces Na⁺ transporter a1 and b1 subunits expression (238).

A number of human and animal studies support a role for EGFR ligands, particularly TGF-, in the induction, progression, and possible recovery from lung injury. We have developed transgenic mouse lines expressing TGF- exclusively in the lung and demonstrated protection of the lung from inhaled toxicant injury. We have recently generated transgenic mice expressing regulable levels of TGF- in the lung. These transgenic lines will permit determination of the dose and timing of gene expression patterns critical to protecting the lung during inhaled nickel injury.

Integrated Cell Signaling

Communication between different cellular signaling systems has emerged as a common principle that enables cells to integrate a multitude of signals from its environment. For instance, it is becoming increasingly clear that many functions critical to cell proliferation, cell survival, and wound healing are controlled by multiple interacting gene networks. As noted above, while cell proliferation could be considered the main bailiwick of EGFR signaling, GPCRs can interact with EGFR signaling to enable cross talk between multiple pathways and provide complex and integrated responses to environmental stimuli (239–243). Different regulatory networks give rise to complex signals through interactions in common pathways, which suggests that future work is needed to identify novel expression patterns that lead to an integration of signals from different pathways

One example of how TGF- mediates complex interactions in the lung involves its possible role in the production of other mediators. TGF- may influence apoptosis or cytokine formation in the lung and interactions between TGF- and other inflammatory mediators are likely to be complex. In keratinocytes, TGF- counteracts tumor necrosis factor- (TNF-)–induced apoptosis, without involving altered regulation of TNF- receptors (244, 245). Although the precise mechanism is not known, TGF purportedly alters levels of pro-apoptotic molecules such as caspases, receptors, or intracellular signaling molecules. Alternatively, suppressors of apoptosis such as Bcl-2, PAI-2, or mitochondrial superoxide dismutase could increase in expression. Because TGF- is a recognized mitogen, it could also alter the levels of cyclins, cyclin-dependent kinases, or cyclin-dependent kinase inhibitors. IL-1ß enhanced repair of cultured alveolar epithelial cells through an EGF- and TGF-–dependent process, indicating that some effects of cytokines are actually mediated through the EGFR family (205). Stimulation of EGFR in keratinocytes can decrease levels of cytokines CCL2/MCP-1, CCL5/RANTES, and CXCL10/IP-10 while increasing CXCL8/IL-8. In consort, EGFR signaling blockade produces opposite effects, increasing CCL2, CCL5, and CXCL10, and reducing CXCL8 (246). Similarly, TGF- can alter prostaglandin synthesis in keratinocytes (247). Clearly, more work is needed to understand how these key gene networks are altered by TGF- during lung injury.

Surfactant Protein B (Sftpb) Repression in Acute Lung Injury

In addition to the informative data relating TGF- to Aliq4, another candidate gene of interest in this region was Sftpb. Sftpb mRNA expression as determined by microarray and RNAse protection assays was markedly decreased in this model of acute lung injury (160). The production of pulmonary surfactant proteins is essential for normal functioning of the lung. Surfactant proteins provide mechanical stability to the alveoli (i.e., reduction of surface tension), prevent alveolar edema, and play a key role in the pulmonary defense system. In particular, Sftpb is a 79–amino acid amphiphilic polypeptide that inserts into surfactant phospholipids, and is expressed in nonciliated bronchiolar and alveolar type II epithelial cells in humans and mice (248, 249). Deficiency in Sftpb is associated with respiratory distress syndrome in premature infants and adults (250, 251). Ablation of the Sftpb gene in mice (Sftpb^–/–) causes respiratory failure shortly after birth, whereas mice with one copy of the normal Sftpb allele (Sftpb^+/–) express alveolar Sftpb protein levels 50% of normal and survive (252). When Sftpb^–/– mice are crossed with mice that have doxycycline-regulated expression of Sftpb, treatment with doxycycline restores Sftpb protein levels, corrects lung function, and protects from respiratory failure at birth (16). Withdrawal of doxycycline in adult mice derived from this cross results in respiratory failure. This occurs when alveolar Sftpb protein levels are reduced to or below 25% of normal.

We noted that nickel markedly reduced Sftpb gene expression during nickel exposure, 24–48 h before mice died due to respiratory failure (160). Similarly, mice that had alveolar Sftpb protein levels of 28% succumb to respiratory failure with nickel exposure (253). In contrast, transgenic mouse lines with TGF- expression directed to lung epithelium maintained Sftpb levels (53% of control), and were protected from acute lung injury. This is in agreement with the observation that Sftpb^+/– mice with 50% alveolar Sftpb protein levels, survive suggesting that a loss of 50% Sftpb can be tolerated. In addition, Sftpb^+/– mice are susceptible to acute lung injury induced by hyperoxia, developing greater pulmonary edema and hemorrhage compared with wild-type mice (254). Administration of surfactant with the active Sftpb peptide to Sftpb^+/– mice can prevent these effects (255). These findings demonstrate the importance of the repression of Sftpb synthesis in acute lung injury. The spatial and temporal regulations of Sftpb synthesis are controlled at both the transcriptional and post-transcriptional levels (256). At numerous sties within the human and mouse Sftpb promoters, several different transcription factor-binding sites have been shown to control the regulation of SFTPB expression, the most notable of which are presented in Table 1.

Importantly, TGF- induces production of metalloproteinases (including MMP-2 and MMP-9) in certain tumor cell lines (261–263), and a broad spectrum MMP inhibitor (marimastat) inhibits growth of certain lung cells (264). This inhibition could be reversed by exogenous addition of TGF-, consistent with an autocrine signaling through EGFR within tumor cells. Inasmuch as members of ADAM family of metalloproteinases are necessary for ectodomain shedding of cytokines and growth factors, it is conceivable that EGF family members could lead to production of metalloproteinases that activate modulators in response to acute lung injury. Additional time- and dose-dependent studies could facilitate an understanding of the complex interactions of TGF- and inflammatory mediators in the course of NiSO₄ injury.

Future research could examine critical gene expression patterns important in TGF- protection in acute lung injury. The recognition of gene regulatory networks will facilitate the design of future animal models to test critical components of the protective pathways. Gene array analyses of the dose- and time-dependent gene expression patterns in transgenic mouse lungs could facilitate models to explain the protection of the lung conferred by TGF- from NiSO₄ injury. TGF- is known to regulate or interact with a number of gene products that may be part of the network conferring protection from nickel injury. For example, EGF increased antioxidants protein activities in rat lung explants exposed to hyperoxia, suggesting a link between levels of EGF family peptide members and antioxidant protection (265). Because toxicant inhalation injury involves at least one component of oxidative stress, it is of interest to establish patterns of gene expression of the oxidant and antioxidant genes in the transgenic models.

In summary, the etiology of acute lung injury is complex and its incidence is high, with past estimates suggesting that 150,000 patients develop acute lung injury annually in the United States (266–268). Recent estimates argue that this number may be low, suggesting that a better estimate may be 187,400 (calculated from 642 cases per 10⁶ person-years x 292 x 10⁶ persons) (4). Conventional therapy includes supportive measures aimed at maintaining physiologic functions (i.e., gas exchange, organ perfusion, and aerobic metabolism) while the acute lung injury resolves (2, 5–7). However, specific therapy to address cellular and subcellular pathology (i.e., permeability abnormality, surfactant disruption, and epithelial damage and healing) in these patients is limited. Despite improvements in supportive care and multiple therapeutic effects directed at modifying the course of the disease, mortality remains high. Most studies report that patients with acute lung injury die in 14 d (269, 270) and estimate 28-d mortality rates of greater than 30% (269, 271–275). This leads to a considerable number of deaths ( 60,000 deaths/yr), rivaling other common diseases like colon cancer ( 48,000 deaths/yr), often the second leading cause of cancer deaths, and breast cancer ( 40,000 deaths/yr). To date, animal and clinical studies of therapeutic agents have had mixed results, but few new approaches have affected outcome significantly. Thus, alternative methods to advance our understanding of the pathobiology of acute lung injury are essential. One such approach would be to first determine the gene(s) loci controlling the development of acute lung injury and utilize mouse models to directly address the functional significance of candidate genes in these regions. It is our belief that this approach offers a fresh look at a retractable problem.

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Genetics of Obstructive Sleep Apnea and Related Phenotypes

OSA has a multitude of associated comorbidities related to recurrent overnight exposures to profound adverse physiologic stresses. The apneas and hypopneas that disrupt sleep lead to variable combinations of hypoxemia, hypercapnia, chemoreflex activation, fragmented sleep, selective reduction in delta and REM sleep, arousal, and sympathetic nervous system activation (4–6). Desaturation nadirs may be extreme, and are often accompanied by blood pressure and heart rate surges (7). Overnight hypoxemia leads to increased morning catecholamine levels (8), and augments pro-thrombotic processes (9). These physiologic exposures likely explain the accumulating epidemiologic data indicating that OSA is a risk factor for hypertension, cardiovascular disease, stroke, and mortality (10–12). These studies suggest that even modest levels of OSA increase risk of hypertension by 40–70% (13) and of cardiovascular disease by 30–40% (14). Neurocognitive impairment and reduced quality of life also have been reported (15). Costs related to the diagnosis and treatment of OSA are estimated as between $3 million (for the most severely affected) to $40 billion (including those less affected) (16). The clear public health burden of OSA underscores the need to better understand its causes, including genetic susceptibility, facilitating identification of susceptible individuals who are most likely to benefit from treatment, and better defining pathophysiologic processes that may be amenable to specific therapies.

Definition of the OSA Phenotype

Most family and genetic studies of OSA have used the AHI to define phenotype, using statistical transformations of the AHI for quantitative trait analyses, or by identifying age-specific thresholds for defining disease status for association studies. The advantages of using the AHI include its relative simplicity, high night-to-night reproducibility, and widespread use clinically (17). However, the AHI presents special challenges in genetic studies, due to its highly skewed statistical distribution, its age and body mass index (BMI) dependency, and the limited information this "count" provides regarding the full range of severity of the disorder, which may be related to the duration of individual events, degree of associated hypoxemia and arousal, event characteristics ("central" versus "obstructive"), extent of pleural pressure swings, and associated functional and physiologic consequences. Combining polysomnographic data with other information, including symptoms, signs, and outcome data, to derive a multidimensional phenotype is one approach for a more comprehensive assessment of the phenotype.

Genetic Epidemiology of OSA: Familial Aggregation Studies

Significant familial aggregation of the AHI, or of symptoms of OSA, has been observed in studies from the United States, Finland, Denmark, Iceland, the United Kingdom, and Israel (18–22). A familial basis for snoring was found in a large Finnish twin study (18) and in a Danish cohort study (19). In the latter, the age-, BMI-, and comorbidity-adjusted risk of snoring was increased 3-fold when one first-degree relative was a snorer, and increased 4-fold when both parents were snorers. The prevalence of OSA among first-degree relatives of OSA probands has been reported to vary from 22 to 84% (23, 24). Among the studies that included control subjects, the odds ratios, relating the odds of an individual with OSA in a family with affected relatives to that for someone without an affected relative, have varied from 2 to 46 (20–22, 24).

In our cohort, OSA occurred more commonly as a multiplex (affecting 2 members) than a simplex disorder in > 50% of the families with at least one affected member. We have observed OSA, defined as elevated age-specific AHI levels, in 21% of the first-degree relatives of OSA probands, compared with 12% of control subjects. The odds of OSA syndrome (an AHI > 15 and daytime sleepiness), given 1, 2, or 3 affected relatives with these findings, as compared with individuals with no affected relatives, adjusted for age, gender, race and BMI are shown in Table 1 (22).

We also have quantified the familial aggregation of OSA, using continuous measures of the AHI, showing approximately equivalent parent–offspring and sib–sib correlations. Parent–offspring and sib–sib correlations for age, sex-adjusted log-AHIs were each 0.21, which were only slightly lower after BMI adjustment (0.18–.19) (22). Consideration of smoking and alcohol exposures did not affect the results (Table 2).

Patterns of Inheritance

Our research team has completed an investigation of the mode of inheritance of OSA. Segregation analyses of Caucasians (177 families, 1,202 members) and African Americans (123 families, 709 members) suggest that the observed distribution of the AHI is consistent with the segregation of major genetic factors within both sets of families (25), although the results suggested possible racial differences in the mode of inheritance. In Caucasians, analysis suggested recessive Mendelian inheritance of the AHI, accounting for 21–27% of the variance, with an additional 8–9% of the variation due to other familial factors, either environmental or polygenic. In African Americans, the BMI and age-adjusted AHI gave evidence of segregation of a co-dominant gene with an allele frequency of 0.14, accounting for 35% of the total variance. Interestingly, adjustment of the AHI for BMI weakened the findings in the whites and strengthened them in the African Americans.

Risk Factors and their Use as Intermediate Phenotypes

In OSA a number of risk factors probably interact to increase propensity for repetitive upper airway collapse occurring with sleep. In any person, this is determined by anatomic and neuromuscular factors that influence upper airway size and collapsibility. Recognized risk factors are obesity, male sex, small upper airway size (26), and ventilatory control mechanisms (27, 28). Identifying genes that determine "intermediate" phenotypes that are on a causal pathway leading to OSA may facilitate identifying susceptibility genes. Such traits may be more closely associated with specific gene products, and may be less influenced by environmental modification than more complex phenotypes. Our group has proposed three "intermediate" pathogenic pathways through which genes might act to increase susceptibility to OSA: (i) obesity and related metabolic syndrome phenotypes; (ii) craniofacial morphometry; and (iii) ventilatory control. Additionally, genes that control sleep and circadian rhythm also may be important in the expression of OSA.

Obesity and Body Fat Distribution
Obesity increases the risk of OSA 10- to 14-fold, with the most marked effects observed in middle age. Central body fat distribution appears especially important. It is unclear whether this is because of the mechanical effects of central fat on lung mechanics and ventilation and/or upper airway size, or because visceral fat is metabolically active. Both central obesity and OSA are associated with hypertension, Type II diabetes, and hyperlipidemia (29). Thus, the association of central obesity and OSA may indicate a specific phenotype based on a gene or set of genes influencing adipocyte biology, ventilatory control, chemoreflexes, and/or cranio-facial morphology. Candidate genes for obesity are therefore relevant for studies of the genetics of OSA, both because of the prominence of obesity in the OSA phenotype, and because of the potential impact of these genes on the expression of other traits of potential relevance to OSA.

Cranio-Facial Morphology
Variation in cranio-facial morphology, affecting both bony and soft tissues, predisposes to OSA by reducing the size of the upper airway (30). We have uniquely identified head form (brachycephaly—a relatively wide but shallow shaped head form) as a risk factor for OSA, suggesting that global differences in head shape influence upper airway collapsibility (31). Preliminary work from our laboratory utilizing acoustic reflectometry, a noninvasive technique for assessing airway cross-sectional area as a function of airway distance, indicates associations of OSA with mean and minimal airway cross-sectional areas. Other groups have used more sophisticated techniques, such as magnetic resonance imaging, to precisely characterize anatomy in terms of muscle, fat, and bony contributions. These investigators have shown that the lateral pharyngeal wall and tongue are larger in patients with OSA compared with matched control subjects (32), with preliminary data from twin studies indicating that these characteristics are also highly heritable.

Ventilatory Control
Airway patency is influenced dynamically by an array of complex processes associated with the control of respiratory neuromuscular function. Ventilatory control abnormalities may predispose to obstructive or central sleep apnea, or both, by influencing ventilation during sleep and increasing upper airway collapsibility. This might be by preferential reduction in the level of activation of upper airway muscles as compared with chest wall muscles (33); by promoting ventilatory instability and, subsequently, periodic breathing (34); or by impairing the arousal response to airway obstruction (35). Ventilatory control instability could result from either blunted or augmented chemosensitivity.

Candidate Genes and Biochemical Markers

Genes that influence obesity and body fat distribution, cranio-facial morphology, and ventilatory control are relevant. Numerous genes have been identified, in rodents, that influence the expression or regulation of proteins or receptors that could be relevant in these intermediate physiologic processes. Some potential candidate genes for intermediate OSA phenotypes include the following:

• Body Fat Distribution. Leptin, pro-opiomelanocortin, melanocortin-3 receptor, insulin growth factor, glucokinase, adenosine deaminase, tumor necrosis factor-, glucose regulatory protein, agouti protein and protein-related peptide, ß3 adrenergic receptor, orexins.
  
• Ventilatory Control. RET-proto-oncogene, receptor tyrosine kinase, neurotrophic growth factors (brain-derived and glial derived neurotrophic factors), endothelin-1, endothelin-3, leptin, krox-20, orexins.
  
• Cranio-Facial Structure. Class I homeobox genes, growth hormone receptors, growth factor receptors, retinoic acid, endothelin-1, collagen type I and II, tumor necrosis factor-.
  

Heritability Estimates for the AHI and Related Traits

Given the range of potentially relevant traits that may be informative for understanding the genetics of OSA, we have applied variance component analysis to assess the heritability of several, adjusting each for age, sex, and significant covariates (see Table 3). These data underscore the strong familial, and probable genetic, bases for OSA-related phenotypes.

We have undertaken causal-pathway modeling (36) to dissect the genetic etiology of OSA and associated traits by investigating the sharing or nonsharing of the genetic and nongenetic determinants of correlated phenotypes. Our extended analyses have allowed estimation of the overlap among genetic determinants of the OSA-associated traits studied. Evidence of shared additive genetic determinants would suggest that the close association of these traits with OSA and each other is at least partially the result of shared genetic factors. Evidence of unshared additive genetic determinants suggests the existence of multiple, distinct genetic pathways modulating genetic susceptibility to OSA. Figures 1A and 1B show the estimated inter-relationships among the genetic determinants of AHI and some important OSA-associated traits—HDL cholesterol, BMI, and neck circumference (Neck C). These preliminary data suggest that (i) the patterns of association are different among white and African-American families, and (ii) that the pathogenic mechanisms leading to OSA are complex, and involve a number of genetically distinct pathways. Our results suggest that there are both shared and unshared genetic factors underlying susceptibility to OSA and obesity. The results of our whole genome scan were consistent with this hypothesis, and suggested that the inter-relationship of OSA and obesity may be partially explained by a common causal pathway involving one or more genes regulating both AHI and BMI (37).

View larger version (48K): [in this window] [in a new window]   Figure 1. Shared and unshared additive genetic determinants (2A) in white (A) and African-American (B) families. Neck C, neck circumference; HDL, high-density lipoprotein cholesterol tables.

To identify susceptibility loci for OSA, we conducted a genome-wide scan in 66 pedigrees of European-American origin (n = 349 subjects) (37) and in 59 African-American families (n = 277). A multipoint model-free linkage analysis was conducted of both AHI and BMI. In Caucasians, for the log-transformed, age-adjusted value of AHI, 12 multipoint LOD scores above 1.0 were found on 13 chromosomes. The highest LOD scores were 1.64 on chromosome 2 (74 cM from pter, at marker D2S1352; 2p16), 1.43 on chromosome 12 (7cM, flanked by markers D12S372 and GATA49D12; 12p13), and 1.40 on chromosome 19 (74cM, flanked by markers D19S245 and D19S559; 19q13). After adjustment for BMI, 10 of these linkages were greatly reduced (LOD < 0.7), suggesting that any susceptibility loci in these regions modulating AHI act through a pathway also involving BMI. However, the linkages on chromosomes 2p and 19q remained essentially unchanged, suggesting that these potential linkages were to gene(s) modulating AHI largely independently of BMI. Distinct linkages were observed in our African-American sample (38).

BMI was linked to multiple regions, most significantly to markers on chromosome 2p (lod = 3.08), 7p (lod = 2.53), and 12p (lod = 3.41) in whites (37). Distinct linkages were noted in the African Americans (38). Interestingly, after adjustment for AHI, some of the primary linkages to BMI were greatly reduced while others remained suggestive, suggesting that there are both shared and unshared genetic factors underlying susceptibility to OSA and obesity, and that the genetic determinants of obesity in this population are modulated by OSA severity (37).

Several biologically plausible candidate genes are located within the most promising chromosomal regions in our analysis. The chromosome 2p region contains acid phosphatase 1, apoprotein B precursor, proopiomelanocortin (POMC), and the -2B–adrenergic receptor. These are especially plausible candidates for obesity, and have been previously associated with BMI, percentage of body fat, and/or serum leptin levels (39).

Leptin, an Example of a Gene Product with Pleiotropic Effects of Relevance to OSA
There is growing evidence that leptin, an adipose-derived circulating hormone, known to influence appetite regulation, energy expenditure, and obesity, may also influence other traits of relevance to OSA. Mouse models have suggested that leptin levels modulate lung growth (40), respiratory control (41), and sleep architecture (42). Studies of leptin-deficient mice, studied before and after leptin replacement, suggest that leptin deficiency causes depressed ventilatory responses to hypercapnia in both wakefulness and sleep (41). Although leptin-deficient mouse models have not been studied for OSA per se, these studies provide important supporting data implicating the pleiotropic effects of a single protein on several aspects of the OSA phenotype (obesity, abnormal ventilatory control, and disturbed sleep architecture) (40–42). Given our linkages to both AHI and BMI on chromosome 2p, POMC, which is associated with leptin levels, is a biologically plausible candidate that could explain the observed results and would be consistent with a genetically regulated metabolic component to OSA pathogenesis.

Another area of great interest is the chromosome 19q region identified in our linkage analysis, which contains the apolipoprotein E gene. Apolipoprotein E regulates lipid metabolism, and the 4 allele has been associated with cardiovascular disease, dementia, and OSA (43). Thus, this association also provides an interesting example of a potential gene product with pleiotropic effects relevant to OSA.

Conclusions

In summary, OSA clearly aggregates within families, and many studies have demonstrated evidence of a genetic component to the familial aggregation. The recurrence of OSA in families is suggestive of a multifactorial etiology. The evidence suggests that some of the intermediate phenotypes associated with OSA are due to an oligogenic background. Promising candidate genes include several proteins that influence a number of inter-related traits, including respiratory, metabolic, and sleep phenotypes. Technological advances in positional cloning and candidate loci linkage-disequilibrium mapping techniques using SNPs will likely further accelerate our understanding of the pathophysiology of OSA.

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Expression Analysis in Lung Cancer

The Search for Biomarkers

Surrogate Biomarkers

As an example of surrogate biomarker development, our group has focused on the use of microarray expression analysis in human adenocarcinoma tissue and surrounding adjacent tissue (1). Our objective in this study was to discover potentially useful biomarkers for lung cancer by first identifying large gene expression differences between tumor cell lines and normal lung using high density oligonucleotide microarrays (OMAs). The microarray used (Affymetrix HG-U95Av2) incorporates 12,600 probes accounting for a large fraction of the expressed human genome. We searched for biomarkers that were overexpressed in relation to normal tissue, because they are more likely to be useful for detection and screening of accessible specimens such as sputum, peripheral blood, or urine than biomarkers that are underexpressed.

High-density OMAs have been used recently to profile gene expression in lung carcinoma tissue homogenates (2). The length of the lists of potentially interesting genes generated by these studies is daunting, and biological and clinical relevance of these lists remains to be validated. Moreover, specific identification of individual biomarkers that might be used for early detection and surveillance has not been the objective of these early studies. We have developed a schema for combining the data derived from the OMA analysis of a few lung cancer cell lines with immunohistochemical testing of tissue microarrays to rapidly identify biomarkers of potential clinical relevance.

Initially, we profiled gene expression in lung tumor cell lines using the Affymetrix HGU95Av2 OMA. RNA from two non–small cell lung cancer (NSCLC) cell lines (A549 and H647) and two small cell lung cancer (SCLC) cell lines (SHP-77 and UMC-19) were tested. Cells from 1 histologically and cytogenetically normal bronchial epithelial primary culture from a volunteer who had never smoked and 10 samples of histologically unremarkable lung tissue from resection specimens served as normalization controls. Array results were analyzed with Gene Spring software. Results were confirmed by reverse transcription–polymerase chain reaction in an expanded number of cell lines. We then validated the cell line data by immunohistochemical testing for protein using a tissue microarray containing 187 NSCLC clinical samples. Of the 20 most highly expressed genes in the tumor lines, 6 were members of the cancer/testis antigen (CTAG) gene group including 5 MAGE-A subfamily members and NY-ESO-1. SCLC lines strongly expressed all of the MAGE-A genes as well as NY-ESO-1, whereas NSCLC lines expressed a subset of MAGE-A genes at a lower level of intensity and failed to express NY-ESO-1. Reverse transcription–polymerase chain reaction of an extended series of 25 lung cancer cell lines including 13 SCLC, 9 NSCLC, and 3 mesothelioma lines indicated that MAGE-A10 and NY-ESO-1 were expressed only by SCLC, and that MAGE-A1, 3, 6, 12, and 4b were expressed by both SCLC and NSCLC.

By immunohistochemistry using the monoclonal antibody 6C1 that recognizes several MAGE-A gene subfamily members, 44% of NSCLC clearly expressed MAGE-A proteins in cytoplasm and/or nucleus. Expression of MAGE-A genes did not correlate with survival but did correlate with histologic classification with squamous carcinomas more frequently MAGE-A positive than other NSCLC types (P < 0.00002). Figure 1 demonstrates the specificity of staining for MAGE A in squamous cell carcinoma of the lung using the monoclonal antibody 6C1. Both tissue sections of squamous cell carcinoma as well as Cytoprep of expectorated sputum stained for MAGE-A proteins using the monoclonal antibody 6C1 in a sensitive immunoperoxidase method.

View larger version (137K): [in this window] [in a new window]   Figure 1. Immunohistochemical analysis of squamous cell lung carcinoma with MAGE A antibody. A and B demonstrate immunoassaying for MAGE A family proteins in two different squamous cell carcinoma samples. Note the stark distinction of staining for tumor cells and nonstaining of adjacent tissue and stroma. C represents a cytopreparation of expectorated sputum from a patient with inflammation. There is no staining for MAGE A cells in this sample. D demonstrates staining of an expectorated malignant cell from a patient with squamous cell carcinoma of the lung.

Sentinel Biomarkers

Sentinel biomarkers, with the purpose of defining prognostic information, may represent the most anticipated use of microarray technology. Information from high throughput technologies is being used increasingly toward clinical samples and as a means to investigate disease prognosis and treatment approaches. A synopsis of the informatics approach requisite in using microarray expression data applied to survival data is summarized by Li and Luan (3). Meyerson was first to demonstrate that adenocarcinomas of the lung could be classified by molecular signatures, and that a subtype of tumors with neuroendocrine features portends a poorer prognosis, corrected for stage (2). Beer and coworkers demonstrated that, even with unsupervised clustering approaches, lung tumors tended to cluster by clinical grade (4). This group identified a 50-gene risk set that accurately predicted survival in a Kaplan-Meier analysis (4). Similar conclusions regarding lung cancer survival as predicted by high throughput data are obtained by proteomic analysis. Beer and colleagues demonstrated that morphologic assessment of lung tumors often proves to be an inadequate method of predicting patient outcome. By using a two-dimensional polyacrylamide gel electrophoresis analysis, protein profiles were identified to predict survival, even in early stage 1 disease (5). Using a different proteomic method (matrix-assisted laser desorption/ionization mass spectrometry), Carbone and coworkers elegantly defined a proteomic profile that could predict good survival. This group used a class prediction model with a training set, and then validated their approach with an equally large, blinded test set (6).

Although the ability to predict outcomes based on molecular and proteomic signatures continues to be an important application of this these technologies, the great hope is that signatures can be used to define personalized treatments for patients with lung cancer. Toward this end, several exciting new studies have been accomplished. Nakamura and coworkers used laser-capture microdissection and subsequent cDNA microarray analysis to delineate genes associated with both lymph node metastasis and sensitivity to a panel of anti-cancer drugs (7). By using molecular profiling in cell culture and a time-course analysis, genes associated with the development of cisplatin resistance have been determined (8). By analyzing the effects of combination chemotherapeutic modalities on lung cancer cells (and extension of results to ovarian and melanoma cell lines), investigators were able to use this functional genomic approach to define new apoptotic targets (9).

Integral Biomarkers

Integral biomarkers represent changes in expression that mark a focal point of the pathophysiologic process. In the following example, we demonstrate how comparison of orthologous changes in gene expression between a murine model and human lung cancer may provide insight into the development of integral biomarkers. Efforts to detect human lung cancer at earlier stages are hampered by the limited success of current diagnostic methods (10). One approach is to develop better biomarkers for earlier detection that will give a high level of confidence in the diagnosis at more treatable stages. Ideally, biomarker signatures can be developed using samples derived from noninvasive procedures such as blood or sputum. Unfortunately, patients are typically diagnosed with late stage disease, which has a 5-yr survival rate of 5% (11, 12).

The current disease diagnosis methods present a paradoxical situation whereby the early stage patients are not readily identified for analysis. This paradox can be resolved by the use of animal models for human diseases. In the case of lung adenocarcinoma, chemical carcinogenesis murine models have been established with histologic appearance similar to that of human lung adenocarcinoma (13, 14). In addition, both murine and human lung adenocarcinomas have frequent Ki-ras mutations, p16 deletion, and are thought to be derived from the lung Type II cell (15). Given these similarities, we wanted to develop greater confidence in using a murine model of human lung adenocarcinoma for defining early biomarkers. To this end, gene expression analysis of both human and murine lung adenocarcinomas was completed on a large number of samples. Total RNA from human adenocarcinoma and normal (adjacent) tissues were prepared from 10 patients in duplicate. The A/J mouse develops lung adenocarcinomas after a single intraperitoneal injection of urethane. A/J mouse lung tissues were harvested from untreated, age-matched normal controls, and normal (adjacent) and tumor tissues at 24–26 or 42 wk after injection. Mouse tumors at the earlier time point appear as self-contained nodules typical of adenomas, whereas the tumors at the later time point are adenocarcinoma-like, enlarged to fill most of the chest cavity.

A total of 39 human arrays (Affymetrix HG-U95Av2) and 55 mouse arrays (Affymetrix MG-U74Av2) were hybridized with cRNA samples from these tissues and the data were collected with Microarray Suite 5.0 (Affymetrix). The MAS5 pivot table was imported and analyzed using BRB-ArrayTools suite (16, 17) (http://linus.nci.nih.gov/BRB-ArrayTools.html; version 3.0.1a [6/03]). BRB-ArrayTools suite can determine which set of genes can distinguish (classify and/or predict) normal and tumor samples that meet a user-defined level of statistical significance. Because microarray experiments generate a large amount of data per experiment, BRB-ArrayTools calculates its statistical measures in three different ways—parametric, permutational, and estimation of false discovery rate. Genes were selected that met a P value 0.00001 by these tests and included < 1 false positive identification. Resourcerer (18), developed at the Institute for Genomic Research, gives an orthologous gene alignment between human and mouse indexed to the Affymetrix probe IDs. Approximately 5,000 different genes were aligned through Resourcerer (from the 12,000 gene represented on the microarrays). Using this database, the human and mouse gene expression data were aligned to find genes that were similarly regulated between the two species.

The human gene expression data were analyzed to determine which genes correctly classify normal (adjacent) from tumor tissues and resulted in 546 human probe IDs. The mouse gene expression data were analyzed in a similar way, resulting in 1,426 mouse probe IDs. Using Resourcerer, the overlap of the two species' classifier lists was generated, and contained 270 probe IDs. Because the mouse data set included two time points, BRB-ArrayTools suite can use one time point data set for "training" and predict the class of the samples from the other time. In either mode (early predicts late or late predicts early), the probe IDs selected were > 90% accurate in their predictions. A final "best" list was generated as the overlap of the 491 mouse predictor probe IDs with the 270 human and mouse classifier probe IDs. This list was composed of 122 unique genes, of which all but 10 were concordant (agreement in the direction of change in both species) for their tumor versus normal gene expression ratio.

To visualize the data as a whole, an expression "heat-map" was generated using Cluster and Treeview (19), and is shown in Figure 2 (blue, upregulated genes in tumors; yellow, downregulated genes in tumors). The expression pattern is strikingly similar between the human and mouse samples when clustered using the "best" probe ID list. The calculated parametric based Pearson correlation of r = +0.66 (P < 0.0001) and the nonparametric Spearman rank correlation of rho = 0.59 (P < 0.0001) indicated that the human and mouse data were positively correlated and the expression changes in the genes can be similarly ranked. Of the 112 genes with concordant expression levels, 89 were downregulated (79%) whereas 23 were upregulated (21%) in tumor tissue samples. Thirty-four (38%) of the 89 downregulated genes mapped to regions of frequent loss in human lung cancers (20, 21) suggesting a significant role for genomic instability in both species during lung tumor progression. Ninety-one genes had assignments in the Gene Ontology database (22), which grouped them into six functional categories: cell–cell/cell–matrix interactions, inflammation/injury, proliferation, metabolism, transcriptional regulation, and signaling pathways. These results support the conclusion that the A/J mouse-urethane model of lung adenocarcinoma reflects many of the genetic changes, as revealed by gene expression analysis, seen in human adenocarcinoma. Therefore, this murine model should serve as a way to understand the changes in human lung adenocarcinoma at earlier times in disease development.

View larger version (67K): [in this window] [in a new window]   Figure 2. Gene expression data from the nonredundant (nr) probe IDs corresponding to the overlapping set of 122 unique genes is displayed using Cluster and Treeview. The data were median centered by genes and arrays, followed by hierarchical clustering using Spearman rank correlation centering. The GORDER option was used to keep the vertical ordering of the genes similar in both species. Black squares indicate samples that were misclassified by sample type by the Cluster algorithm. On the left, the human adenocarcinoma and adjacent samples are shown, and on the right the mouse samples are shown. Blue color represents genes upregulated in the tumor samples compared with adjacent, paired tissue. Yellow represents genes downregulated. The calculated parametric based Pearson correlation of r = +0.66 (P < 0.0001) and the nonparametric Spearman rank correlation of rho = 0.59 (P < 0.0001) indicated that the human and mouse data were positively correlated and the expression changes in the genes can be similarly ranked. The striking similarity between identical genes across species strongly suggests a common pathogenesis in the murine model and the human condition.

We have used murine models of lung tumorigenesis and transgenic mouse modeling to define the potential chemoprotective role of prostacyclin (PGI₂). The eicosanoids are a family of bioactive lipid metabolites of arachidonic acid (AA). AA is hydrolyzed from membrane phospholipids through the action of phospholipase A₂ (PLA₂). Free AA can then be metabolized through three major pathways: cyclooxygenase (COX) to produce prostaglandins and thromboxane, lipoxygenase to produce leukotrienes and HETES, and cytochrome P-450 to produce EETs. Prostacyclin synthase (PGIS) is the final committed enzymatic step in the pathway of prostacyclin (PGI₂) production, occurring at a branch point where substrate (PGH₂) can be directed either toward PGI₂, thromboxane A₂ (TxA₂), prostaglandin E₂ (PGE₂), or PGD₂. PGI₂ is a naturally occurring eicosanoid that possesses anti-inflammatory and anti-metastatic properties, as well as a suppressive role in tumor growth (23). PGI₂ is one of the main products of arachidonic acid in all vascular tissues tested to date (24). Once released from cells, PGI₂ acts as an autocrine and paracrine effector to regulate the function of various differentiated cells and platelets. Along with other prostaglandins, PGI₂ shares a cytoprotective activity that remains to be fully understood. For example, in models of myocardial infarction, PGI₂ reduces infarct size and oxygen demand (25, 26). Eicosanoid balance is crucial in colon carcinogenesis (27) and will likely prove pivotal in lung carcinogenesis.

In work conducted in our laboratory, the eicosanoid profile in normal lung and non-small cell lung cancer (NSCLC) cell lines have been compared. In normal lung, PGI₂ is the predominant prostaglandin produced (28). However, in NSCLC cell lines, PGE₂ production is more prominent than PGI₂ (29). High levels of PGE₂ are observed in NSCLC containing Ki-ras mutations because these mutations induce constitutively high expression of cPLA₂ and COX-2 (30). Immunohistochemistry performed in our laboratory has shown that selective NSCLC tumors express very little PGIS compared with surrounding normal lung, indicating an imbalance of eicosanoid production.

Based on these findings, we hypothesized that pulmonary-specific overexpression of PGIS in a transgenic mouse model would chemoprevent lung tumors. Transgenic mice with pulmonary PGIS overexpression were created using a construct of the human surfactant protein C promoter and the rat PGIS cDNA (31). The human SPC promoter directs expression of transgenes to alveolar type II and Clara cells (32), which are the progenitors for human and mouse lung adenocarcinomas. To determine a gene-dosing effect, two different transgenic lines were exposed to carcinogens; low expressing mice with a 50% increase in lung PGIS activity (exhibited by a 1.5-fold increase in 6-keto PGF₁, the stable metabolic product of PGI₂) and a high expressing line with a 3-fold increase in lung 6-keto PGF₁. Transgenic mice (Tg⁺) and wild-type littermates (Tg^–), 8–12 wk of age, were subjected to two distinct lung carcinogenesis protocols. In the first model, urethane, a complete carcinogen which selectively induces pulmonary adenomas (33), was administered in a single dose. In an initiation/promotion model, 3-methylcholanthrene (MCA), a polycyclic aromatic hydrocarbon found in tobacco smoke which exhibits dose-dependent initiation of murine lung tumors (34), was given in a single dose, followed by six weekly treatments with butylated hydroxytoluene (BHT). BHT is a tumor promoter and induces reversible pulmonary damage characterized by alveolar type I cell necrosis, selective pulmonary inflammation, and hyperplasia of alveolar type II cells (35).

Transgenic overexpression of PGIS significantly decreased tumor multiplicity and incidence in both carcinogenesis models (36). Tg⁺ mice expressing high levels of PGIS exhibited the greatest chemoprotection, demonstrating an 85% reduction in tumor multiplicity compared with Tg^– littermates (0.8 versus 5.2 tumors/mouse, P < 0.0001). Most importantly, lung tumor incidence was also greatly decreased in these high-expressing mice, with 44% (8/18) of the Tg⁺ mice remaining tumor free as compared with the 100% incidence in Tg^– littermates (P = 0.01, Fisher's exact test). Protection by PGIS overexpression in distinct carcinogenesis models demonstrates the generality of this chemoprevention.

Several lines of evidence suggest that the effects of PGI₂ may be mediated through the activation of the nuclear hormone receptor peroxisome proliferator–activated receptor delta (PPAR), demonstrating the first reported biologic function of this receptor signaling pathway (37). The PPARs are ligand dependent transcription activators which are members of the nuclear receptor superfamily (38). Guided by results from microarray experiments, we have demonstrated that COX-2–derived PGI₂ transactivates the PPAR promoter–responsive element (39). PPAR expression is increased in many human cancers, including colon and lung (40), and may play a critical role in malignant transformation. PPAR is downregulated by APC (ademonatous polyposis coli gene) and upregulated by ß-catenin (41), and APC expression is known to decrease during mouse lung tumorigenesis (42). COX-2 expression is increased in mouse lung tumors. COX-2 overexpression is associated with inhibition of apoptosis (43) and can stimulate the production of angiogenic factors such as vascular endothelial growth factor (44). The finding that both PPAR and COX-2 exhibit decreased expression in the chemoprotected transgenic mice may provide insight into signaling cascades affected by PGIS overexpression. Overall, our murine lung tumorigenesis studies have shown that manipulation of prostaglandin metabolism distal to COX produces more profound lung cancer reduction than COX inhibition, and could be the basis for new approaches to lung cancer chemoprevention.

Clinical Trial of Iloprost for Lung Cancer Chemoprevention

Based on the preclinical studies summarized above, the National Cancer Institute is currently funding the investigation of Iloprost for lung cancer chemoprevention. Iloprost is a long-acting, orally available prostacyclin analog. The long-term safety of oral Iloprost has been established in more than 1,000 subjects with various conditions, including primary pulmonary hypertension, scleroderma with Raynaud's phenomenon (45), peripheral vascular disease/atherosclerosis with lower extremity ulceration, and Buerger's disease (thromboangiitis obliterans) (46) who have received the drug for 6 mo or longer. Our trial consists of Iloprost or placebo administered to patients at high risk for lung cancer in a double-blind, randomized prospective trial of 6 mo duration. Subjects are stratified according to enrollment center and smoking status (current or ex-smoker), and have at least a 20 pack-year cigarette smoking history and sputum cytologic dysplasia of mild or worse. Laser-Induced Fluorescence Emmission (LIFE) and/or white light bronchoscopy will be performed at baseline and the end of the trial. The planned sample size is 152 patients with 76 patients per arm (Iloprost versus placebo), including 38 smokers per arm and 38 ex-smokers per arm. Eligible patients will be randomly assigned to active treatment or placebo treatment within each stratum. Group sizes of 38 smokers per arm provide a chi-square test of at least 80% power to detect a difference in response rates of 35% (for any combination of response rates yielding a difference of 35%) between Iloprost and placebo treated smokers. Similarly, group sizes of 38 ex-smokers per arm provide a chi-square test of at least 80% power to detect a difference in response rates of 35% (for any combination of response rates) between Iloprost and placebo treated ex-smokers. Measurement of response will include: histology before and after treatment using the WHO classification for bronchial epithelium; Ki-67 labeling index (a secondary endpoint); and a panel of biomarkers (including immunohistochemistry and qRT-PCR for PGIS, COX-2, PPAR and -, along with MCM2, p53, tyrosine kinase receptor proteins [EGFR, HER2/neu, ErbB3, ErbB4, Akt], and microvessel density). The trial design is illustrated in Figure 3. This trial, which will conclude over the course of the next three years, demonstrates the need for the use of "intermediate end-point biomarkers." These biomarkers have the following characteristics: (i) the marker is intermediate on the causal pathway, (ii) is differentially expressed in normal and high-risk tissues, (iii) can be modulated by chemopreventative agents, (iv) appears early in carcinogenesis, and (v) the assay requires great accuracy and is valid.

View larger version (32K): [in this window] [in a new window]   Figure 3. Trial design for the study of Iloprost in lung cancer chemoprevention. Details explained in the text. In summary, after randomization, patients are given either placebo or Iloprost (double-blind, randomized controlled approach). Before study compound use, patients undergo bronchoscopy. Dose escalation occurs over the first 3 mo of the trial. At the end of the trial, a second bronchoscopy is performed. Patients are then followed annually.

In summary, the use of high throughput analysis modalities, both RNA expression and proteomics, have been extensively applied to the study of lung cancer. A conceptual framework for the use of expression analysis in biomarker development is proposed. In essence, biomarkers may be conceived as surrogate, sentinel, or integral. Investigators may find this paradigm helpful as a framework for designing future studies using these technologies. Translational studies will rely increasingly on biomarkers as endpoints, and expression analysis represents a powerful tool for biomarker development.

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Genetics and Gene Expression in Lymphangioleiomyomatosis

Lymphangioleiomyomatosis (LAM) is a rare multisystem disorder affecting primarily women of middle age that is characterized by cystic lung lesions, recurrent pneumothoraces, chylous effusions, lymphatic abnormalities, and abdominal tumors (e.g., angiomyolipomas [AMLs]) (1–3). A hallmark of the disease is the proliferation of abnormal smooth muscle cells (LAM cells) in the lung and along axial lymphatics in the thorax and abdomen. The proliferation of LAM cells leads to the formation of thin-walled cysts in the lungs and fluid-filled cystic structures in the axial lymphatics (i.e., lymphangioleiomyomas). AMLs occur predominantly in the abdomen, in particular, the kidney (1–3), and are characterized by abnormal smooth muscle cells (LAM cells), similar to those found in the lungs and axial lymphatics, and the presence of adipose tissue, intermixed with incompletely developed vascular structures (4).

Patients with LAM present usually with a history of progressive dyspnea, chest pain due to recurrent pneumothoraces, chylous pleural effusions, and hemoptysis. In some patients, the first manifestation of LAM is a spontaneous acute hemorrhage into an AML that requires surgical intervention (1–3). The natural course of LAM is highly variable (5). Some patients have a very rapid loss of respiratory function, proceeding to lung transplantation in only a few years, and others have a chronic course with relatively little deterioration in lung function over time (5). The severity of disease in LAM has been assessed by lung biopsy (6), pulmonary function testing (3, 5), high-resolution computed tomography (CT) scans (7), and cardiopulmonary exercise testing (8).

Matsui and coworkers (6) proposed a LAM histologic score (LHS) of disease severity based on the extent of replacement of lung tissue by cystic lesions and infiltration by LAM cells as seen in open lung biopsy specimens. This scoring system was quantified as follows: LHS-1 score, < 25% of the lung tissue replaced by cysts or proliferative lesions; LHS-2 score, involvement of between 25 and 50% of the lung tissue by cysts or LAM cell infiltrates; and LHS-3 score, > 50% of the lungs are involved. Employing this scoring system, a good correlation was observed between LHS scores and time to transplantation or death in 105 patients with LAM. The 10-yr survival of patients with the LHS-1 score was 100%, whereas the survival of patients with scores of LHS-2 and LHS-3 was only 74% and 52%, respectively (6).

The most common pulmonary function abnormalities in patients with LAM are limitation in gas exchange and airflow obstruction (5). Most patients present with both decreased diffusing capacity for carbon monoxide (DL_CO) and forced expiratory volume in 1 s (FEV₁); however, some patients have predominant impairment of only FEV₁ or DL_CO (5). The severity and progression of disease are probably best quantitatively assessed by pulmonary function tests. Lung function, especially DL_CO, correlates well with LHS scores and may be a predictor of time to transplantation or death (5, 8).

The severity of disease can also be graded, in a semiquantitative manner, with CT scans by estimating the amount of the lung involved with LAM (7). In this scoring method, grade 0 corresponds to normal lungs without lesions, grade 1 corresponds to < 30% lung involvement, grade 2 to 30–60% lung judged to be abnormal, and grade 3 to > 60% of the lungs affected. Lung function abnormalities, especially DL_CO and FEV₁, are well correlated with CT scan scores of severity (7, 8).

Cardiopulmonary exercise testing (CPET) is another method of assessing disease severity in LAM (8). In CPET of 217 patients with LAM, exercise data were correlated with clinical markers of disease severity, CT scans, lung function, and lung histology (8). Seventy-five percent of patients had low maximal oxygen uptake (VO₂ max). VO₂ max correlated with lung function, use of oxygen, resting arterial oxygen tension, and LHS scores. However, VO₂ max was not better than DL_CO in predicting severity of disease, as defined by the CT scan score, and use of supplemental oxygen. DL_CO was the single best predictor of VO₂ max and exercise-induced hypoxemia. Exercise-induced hypoxemia, however, occurred in patients with near normal DL_CO and FEV₁, suggesting that the pulmonary function tests fail to reflect abnormalities of gas exchange that occur during exercise.

Recently we found that the rate of decline of FEV₁ correlates positively with CT grade, with a greater rate of decline seen in CT grade 3. However, the rate of decline of DL_CO correlated inversely with CT grade, so that in contrast to FEV₁, the rate of decline in DL_CO is greater in early stages of disease and slows as the development of cystic lesions progresses (Wendy K. Steagall, Angelo Taveira-DaSilva, unpublished data). This suggests that there is a difference between the pathogenesis of progression of airflow obstruction and that of gas exchange abnormalities. Because DL_CO correlates better than does FEV₁ with LHS scores, which are a predictor of death and time to transplantation, it may also be the best physiologic test for grading the severity and progression of disease and prediction of the time to transplantation (5, 8).

In summary, pulmonary function tests, CT scans, CPET, and LHS scores, when available, are useful methods for grading the severity of disease in LAM. However, the best methods of evaluating the rate of disease progression are a combination of pulmonary function testing with sequential monitoring of DL_CO, FEV₁, and CPET to reveal the presence of occult exercise-induced hypoxemia (5, 8).

Susceptibility Genes

One factor in the rate of decline in pulmonary function may be the presence of susceptibility or modifier genes that influence critical steps involved in pathogenesis of disease. LAM occurs sporadically or in association with tuberous sclerosis complex (TSC), an autosomal dominant genetic disorder with variable penetrance, which is characterized by neurologic, renal, and dermatologic manifestations. Mutations and loss of heterozygosity in the TSC genes, TSC1 and TSC2, have been identified in LAM cells, suggesting a common genetic basis for TSC and LAM (9–11). Women with tuberous sclerosis complex, characterized by hamartomas and benign tumors in the brain, heart, and kidney, are at increased risk to develop LAM. More than 30% of women with TSC have cystic lung lesions, suggesting that TSC1 and 2 act as susceptibility genes for LAM (12, 13).

TSC1, encoding hamartin, and TSC2, encoding tuberin, are tumor suppressor genes, whose mutation leads to cellular proliferation. Tuberin and hamartin form a primarily cytosolic complex via coiled-coil domains. Hamartin is a 1,164–amino acid protein with a probable role in cytoskeletal rearrangement. It interacts with the ezrin-radixin-moesin (ERM) family of proteins and can influence Rho GTPase activity, regulating cell adhesion (14). Tuberin, a 1,359–amino acid protein, has GTPase-activating protein (GAP) activity for the GTP-binding proteins, Rap1A, Rab5, and Rheb (14, 15). Rap1 is a modulator of the Ras pathway involved in cellular proliferation, whereas Rab5 is involved in the endocytic pathway (14). Rheb is believed to regulate the mammalian target of rapamycin (mTOR) signaling (15).

Modifier Genes

LAM is characterized by emphysema-like pulmonary lesions, with a decrease in number and disruption of elastic fibers in the areas of accumulation of LAM cells (16). Cystic destruction of LAM lung may result from the excessive production of matrix metalloproteases (MMPs) or an imbalance between activities of MMPs and the tissue inhibitors of metalloproteinases (TIMPs). An increase in MMPs has been observed in LAM lung, especially in MMP-2 with lesser increases in MMP-1, MMP-14, and MMP-9 (17, 18), and a decrease in TIMP-3, an inhibitor of both MMP-2 and MMP-14 (19).

MMPs are being studied as modifier genes in LAM lung disease. Both MMP-2 and MMP-9 have promoter polymorphisms: there is a cytosine to thymidine single nucleotide polymorphism (SNP) located at position –1,562 in the promoter region of MMP-9 (20) and the same base difference at –1,306 in MMP-2 (21). For both SNPs, one allele is associated with higher promoter activity; T results in greater activity of MMP-9 and C in greater MMP-2 activity. Thus, MMP-2 and MMP-9 have the potential to be modifier genes in LAM.

We are also evaluating the role of surfactant protein genes as modifiers of the disease course in LAM. LAM is characterized by both an obstructive airway pattern, associated with possible compression of the airways by proliferating LAM cells or diminished lung elastic recoil, and by an impairment of the DL_CO due to the loss of gas exchange area. Pulmonary surfactant is a complex mixture of phospholipids and four proteins, surfactant proteins A, B, C, and D. Surfactant maintains alveolar integrity during respiration by decreasing the surface tension at the air–fluid interface on the alveolar epithelium (22) and also contributes to the innate immune system. In particular, surfactant protein B (SP-B) is an essential protein that promotes adsorption and spreading of surfactant phospholipids and stabilizes a phospholipid monolayer on the alveolar surface (23). Although other factors may drive the early progression of pulmonary disease, SP-B may be important in the later stages. SP-B is essential for respiratory function of newborn humans and mice (24, 25), and it has recently been reported that a critical level of SP-B is necessary for adult murine respiratory function (26). Transgenic mice with doxycycline-dependent expression of SP-B exhibited an increased risk of respiratory failure when SP-B levels in bronchoalveolar lavage fluid (BALF) fell to < 50% of normal, and of fatal respiratory distress syndrome when SP-B levels were < 25% of normal (26). The gene for SP-B has four single nucleotide polymorphisms (27). We have observed that a promoter polymorphism, C/A(-18), which is located in the vicinity of the TATA box, affects promoter activity (W. K. S., unpublished data) and thus, SP-B is a candidate modifier gene.

MMP-9 and SP-B are examples of two of the kinds of modifier genes that can affect the course of a disease. MMP-9 has probably an active part in lung destruction, and the polymorphism in the promoter of the gene may directly result in more MMP-9 and more lung destruction in LAM (Connie Glasgow, unpublished data). SP-B may play a more indirect role, however, with no direct effect on disease progression, but rather a role in determining how lung destruction is tolerated by the body, with the production of more SP-B assisting with the adaptation of the pulmonary system to architectural problems present in severe disease.

Gene and Protein Expression in LAM

LAM cells appear to have properties of smooth muscle cells, as they contain smooth muscle actin, vimentin, and desmin, and of melanocytes, with some LAM cells reactive with HMB45, a monoclonal antibody that recognizes the melanocyte gp100 protein (1). To define the patterns of gene expression in nodular proliferative regions of LAM lung, samples of cells were isolated by laser capture microdissection from lungs obtained at surgery or transplantation. The isolated mRNA was subjected to reverse transcriptase–polymerase chain reaction (RT-PCR) with specific primers to evaluate expression of genes for melanosomal Pmel17 and MART-1 and for smooth muscle -actin and SM22. In fact, the LAM nodule mRNA composition was unlike that of several types of human cells (e.g., fibroblasts, melanoma, pulmonary artery smooth muscle cells), but consistent with a population of cells grown from tissue from patients with LAM (Yi Zhang, unpublished data).

Metastatic Potential

There is evidence that LAM cells have a metastatic potential. Fifty percent of sporadic LAM patients without TSC have renal AMLs (28). LAM cells isolated from lung lesions and AMLs from the same patient had the identical mutations in TSC2, consistent with colonization of one of the sites by cells from the other (10). LAM has also recurred after lung transplantion. Bittmann and coworkers (29) described a case of recurrent LAM in which the allograft lung was from a male donor, and the recurrent LAM cells were shown to be female. Karbowniczek and colleagues (30) examined recurrent LAM cells isolated by laser capture microdissection of the transplanted lung after autopsy. In this case, microsatellite marker fingerprinting showed the presence of patient-derived cells in the foci of recurrent LAM in the allograft, and the recurrent LAM cells contained the same TSC2 gene mutation as did the native LAM cells, as would be expected if the recurrent LAM lesion was initiated with original LAM cells. Whereas it appears in some cases that LAM cells from AMLs colonize the lungs, half of the patients with sporadic LAM do not have demonstrable AMLs. These cases, one of which is exemplified by the case of recurrent LAM reported by Karbowniczek and associates (30), suggest that LAM cells may arise from sites other than the lung and kidney (14), with a lymphatic source being a prime possibility. Given the metastatic potential of the benign-appearing cells, we hypothesized that they might be found in peripheral body fluids from patients with LAM. Indeed, LAM cells were isolated from blood, chyle, and urine, consistent with a metastatic potential for this benign-appearing neoplasm (Denise Crooks, unpublished data).

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Genetic Regulation of Innate Immunity

Lessons Learned from TLR4

TLR4 Ligands

The best-studied of the TLRs is TLR4. This receptor is required for the signaling response to lipopolysaccharide (LPS) from Gram-negative bacteria (3), but not for LPS from Gram-positive bacteria. In addition to LPS, the heat shock protein (HSP)60 from Chlamydia pneumonia is also reported to activate TLR4 signaling (4, 5). This finding might be of particular significance to vascular disease because Chlamydial HSP60 has been found in atherosclerotic lesions. Recognition of HSP60 by human TLR4 might exacerbate the inflammatory component of atherosclerosis in individuals harboring C. pneumonia. Other exogenous ligands reported to activate TLR4 signaling include pneumolysin, the cytolytic toxin of Streptococcus pneumoniae (6), the mouse mammary tumor virus (MMTV) (7), and the polysaccharide mannan from the yeasts Saccharomyces cerevisiae and Candida albicans (8). Interestingly, it has been reported that endogenously produced ligands might also activate TLR4 signaling. These endogenous ligands include fibronectin (9), hyaluronic acid (10), heparin sulfate (11), and fibrinogen (12). The release of endogenous TLR4 ligands from damaged tissue might contribute to the inflammatory responses seen in injuries not necessarily associated with pathogenic infection. However, some caution must be taken with reports of novel TLR4 ligands because even minute amounts of contaminating LPS can lead to erroneous conclusions.

TLR4 Signaling

TLRs are part of a larger family that includes the interleukin-1 receptor family (IL-1R). Members of this family share significant homology in their cytoplasmic regions, including a conserved homophilic domain of 200 amino acids known as the Toll/IL-1R (TIR) domain. In keeping with their conserved intracellular domains, TLRs and IL-1Rs signal through common downstream molecules, including the adaptor molecule MyD88 (13), the IL-1RI–associated protein kinases (IRAKs), and the tumor necrosis factor receptor–associated factor 6 (TRAF-6). After ligand binding, MyD88 is recruited to the receptor complex, facilitating the association of IRAK-4 and IRAK-1 with the complex. TRAF-6 is then also recruited, and after some conformational change, IRAK-4/IRAK-1/TRAF-6 associates with another complex comprised of transforming growth factor-ß (TGF-ß)–activated kinase (TAK-1), TAK-1 binding protein 1 (TAB1), and TAB2. Eventually, TAK-1 is activated, which in turn activates IB kinase kinase. When IB becomes phosphorylated, it is released from a complex with nuclear factor (NF)-B, which then migrates to the cell nucleus and activates the transcription of multiple proinflammatory genes, including tumor necrosis factor-, IL-1, and IL-6.

TLR4 Adaptor Molecules

The MyD88-dependent signaling pathway is shared by all TLRs and leads to a common set of responses, including cytokine production. However, in addition to this core response, additional genes can also be induced by TLR signaling (14). This observation suggests that differences in the molecular composition of receptor complexes can lead to distinct downstream signaling events. Studies of this sort were facilitated by the generation and characterization of MyD88-deficient mice (15), which were shown to preserve (although with delayed kinetics) the LPS-induced MAPK cascade leading to NF-B activation (15–17). In addition, these mice also undergo induction of type I interferons (IFN) and IFN-inducible genes through IFN regulatory factor (IRF)-3 (18). Together, these data implied the existence of alternative adaptor proteins that can at least partially compensate for the absence of MyD88. Database searches for genes having homology to MyD88 revealed additional molecules that have now been shown to have adaptor activities. One of these molecules, TIRAP (also known as Mal), is required for LPS-induced NF-