Even with current advancements in medical technologies, appropriate diagnosis and management of COPD remains a major challenge. Spirometry as a measure of lung function remains the primary objective test for diagnosis of COPD, but spirometry cannot indicate whether airflow obstruction relates to emphysema, airway disease, or both processes. Additional non- or minimally-invasive approaches would be very useful for disease diagnosis and management.
In recent years, studies have attempted to identify gene expression biomarkers for COPD [13
]. In those studies, genome-wide expression studies have been based on RNA derived from surgically-derived tissue samples. Although gene expression studies of lung tissues may provide useful insights into disease pathogenesis, it is not practical to consider routine COPD diagnosis from a sample that must be obtained through an invasive surgical procedure. Blood samples are less invasive, potentially provide for a larger sample size, and allow repeated sampling to monitor disease progression over time and to study therapeutic response.
Past genome-wide studies on different organ systems have shown that total RNA derived from circulating blood can distinguish between control subjects and patients with various diseases [23
] including inflammatory (e.g. preeclampsia, rheumatoid arthritis, and chronic pancreatitis) and malignant (chronic lymphocytic leukemia and renal cell carcinoma) diseases [32
]. One of the earliest demonstrations that gene expression changes in peripheral blood mononucleocytes (PBMCs) were associated with disease was demonstrated on a rat brain model, where acute neural assaults resulted in gene expression changes in PBMCs within 24 hours [34
]. In the pulmonary system, Showe et al have used peripheral blood gene expression signatures to identify early-stage lung cancer in at-risk populations [35
]. Karimi et al. (2006) showed that in vitro
exposure of PBMC to cigarette smoke induces production of cytokines in a TLR4-dependent manner [36
We hypothesized that peripheral blood gene expression patterns could help to improve COPD detection, diagnosis or progression. We assessed genome-wide expression patterns in RNA obtained from PBMCs isolated from a subset of 24 of the study subjects using the Affymetrix U133 Plus 2.0 microarray. Data analysis revealed novel genes that were differentially expressed in PBMCs from COPD patients. The genes we identified have not been previously implicated in COPD disease pathogenesis, and as such are likely to be true markers rather than etiological. We observed two genes, RP9 and NAPE-PLD, showing decreased expression in both lung tissue and blood of COPD subjects when compared to controls. This suggests that PBMC-derived markers may reflect processes ongoing in diseased tissues. Further, our data serves as a proof-of-principal that peripheral gene expression patterns, defined using minimally invasive samples, can be used to describe COPD.
Genome-wide linkage screens aimed to identify disease-susceptibility genes previously identified three linkage regions (chromosomes 2q33-36, 8pter-22, and 12p13-12) in the Boston Early-Onset COPD cohort [37
] which includes the locus for one of the novel genes identified in our study, AT-rich domain 2 (ARID2
is a transcriptional co-activator involved in the regulation of cardiac gene expression [38
]. Among other genes displaying changes in expression between cases and controls, some have notable functions. Syntaxin 17 (STX17
) expression in macrophages is regulated by Colony-stimulating factor 1 (CSF-1), a growth factor controlling the development of macrophages from myeloid progenitor cells [39
is a member of winged-helix/forkhead transcription factors and is important in monocyte differentiation and macrophage function [40
, a stress inducible sestrin regulated by p53, has been reported to be potent inhibitor of mTOR signaling and regulator of cell growth and proliferation [41
To our knowledge only two studies have previously explored the value of genome-wide peripheral blood expression assessments in patients with COPD [16
]; both defining serum protein levels. Hurst et al assessed paired baseline and exacerbation plasma samples from patients with COPD and identified 36 biomarkers using protein arrays [42
]. They observed that although systemic biomarkers were not helpful in predicting exacerbation severity, acute-phase response at exacerbation was strongly related to monocyte activity. Pinto-Plata et al used protein array on peripheral blood from COPD patients and identified 30 biomarker clusters [16
]. They identified a set of biomarkers correlated with lung function.
One major limitation of the current study is that quantitative real time-PCR (qPCR) validation indicated a potential high false discovery rate. Possible reasons for lack of validation for individual genes include expression levels below sensitivity for the assays used, poor assay specificity, alternative splice forms and inaccuracy of array data. The phenotypic heterogeneity of COPD may also be a cause of limited validation results in the current study. Regardless of the root cause of poor validation, the small size of the current study is a major limitation in the generalization of the results presented. Another limitation of the current study is the diagnosis of lung cancer in most subjects. Recent studies have reported that genetic expression in PBMCs is altered in the context of malignancy [32
]. Lung cancer and COPD are both typically found in smokers and the diagnosis of lung cancer can serve as an independent predictor for COPD, independent of smoking history. Even though we have previously shown any effects of the tumor on gene expression are not significant in distant, histologically normal lung tissue [17
], in the case of PBMCs the presence of tumors may contribute to changes in gene expression. Even though four (PIK3C2A, JUN, FNBP1, ITPR1) of our peripheral biomarkers have been implicated in cancer pathophysiology, none of the PBMC biomarkers were differentially expressed between tumor types (among all subjects, or within cases or controls alone).
In conclusion, we used microarray technology to identify gene expression differences in PBMC obtained from COPD patients and controls. Our data contribute to the understanding of gene expression changes occurring in the blood of patients with obstructive lung disease and provide additional insight into potential mechanisms involved in the disease process. Our data suggest that PBMC may be a source of diagnostic markers. The identification and validation of markers may help to facilitate the development of non-invasive methods for diagnosis, classification of disease subtypes and/or provide a means to define response to therapeutic intervention.