Biomarkers in chronic obstructive pulmonary disease: confusing or useful?

Abstract

The field of biomarker research has almost reached unmanageable proportions in chronic obstructive pulmonary disease (COPD). The developments of new technology platforms have generated a huge information data base, both cross sectionally and increasingly, longitudinally. The knowledge emerging provides an enormous potential for understanding the disease pathophysiology, for developing markers specific for long-term outcomes, and for developing new therapeutic strategies. However, the excitement must be tempered with an understanding of the limitations of the data collection techniques, and of the variations in disease state, activity, impact, and progression. Nevertheless, the most crucial aspect in interpreting the current literature is the recognition of the relatively superficial characterization of what is a complex group of pathological processes with a common end point of airflow limitation. The current review explores some of these issues together with those areas where real progress appears to have been made, and provides caution on interpretation.

Keywords: emphysema; inflammation; secretions; technology platforms.

Figure 1

Line graph representation of disease progression in 3 idealized patients. Patient (Pt) A has slow disease progression and with age may notice or report few symptoms (ie, low impact/low disease activity/mild disease). Patient B has greater progression and symptoms become noticeable in the 60s (moderate impact/moderate disease activity/moderate disease). Patient C has rapid disease progression leading to symptoms in the 30s (major impact/high disease activity/mild disease).

Figure 2

Relationship between health status recorded as the SGRQ score and decreasing lung density as a marker of emphysema. Individual patient data points are shown and the significance of the correlation is given. Abbreviation: CT, computed tomography.

Figure 3

The pathological process involved in emphysema. (1) cigarette smoke activates macrophages (2), epithelial cells (3) and airway neutrophils (4) to release pro inflammatory cytokines and neutrophil chemoattractants. At the same time oxidant stress in smoke damages local airway proteins (3). Harvesting airway secretions (A) detects markers of these effects including the influence of airway colonisation (5) and local mucus over production. The chemokines activate endothelial cells and circulating neutrophils (6) leading to adhesion and migration. Blood biomarkers (C) reflect these events. Migrating neutrophils ± local activated macrophages destroy connective tissue releasing specific fragments into the lymph and together with locally produced chemokines circulate into the circulation where they can be detected (B). Abbreviations: LTB4, leukotriene B4; IL8, interleukin 8.

Figure 4

Interrelation of proteinases and TNF. Cigarette smoking leads to TNF release and sequential events leading to emphysema (1). Serine proteinases released by recruited neutrophils activate MMP12 and inactivate its’ cognate inhibitor/s (2). MMP12 inactivates α1AT facilitating its own activation by serine proteinases (3). MMP12 then leads to extracellular processing of the interaction of TNF with its receptor (4) facilitating the main pathway (1). Abbreviations: α1 AT, alpha 1-antitrypsin; CT, computed tomography; MMP12, matrix metallopeptidase 12; TIMP, tissue inhibitor of metalloproteinase; TNFα, tumor necrosis factor α.

Figure 5

A two dimensional proteomics read out. Each dot/blot represents a single peptide. Changes in density/presence are considered as biomarkers of the disease progress or activity.