| Literature DB >> 27716343 |
Jannie M B Sand1,2, Diana J Leeming3, Inger Byrjalsen3, Asger R Bihlet3, Peter Lange4,5, Ruth Tal-Singer6, Bruce E Miller6, Morten A Karsdal3, Jørgen Vestbo7.
Abstract
BACKGROUND: There is a need to identify individuals with COPD at risk for disease progression and mortality. Lung tissue remodeling is associated with the release of extracellular matrix (ECM) fragments into the peripheral circulation. We hypothesized that ECM remodeling was associated with mortality in COPD and measured neo-epitopes originating from ECM proteins associated with lung tissue remodeling.Entities:
Keywords: Biomarker; COPD; Collagen; Elastin; Extracellular matrix; Mortality; Prognostic; Remodeling
Mesh:
Substances:
Year: 2016 PMID: 27716343 PMCID: PMC5050854 DOI: 10.1186/s12931-016-0440-6
Source DB: PubMed Journal: Respir Res ISSN: 1465-9921
Fig. 1Extracellular matrix composition in healthy and COPD lungs. In healthy lungs, the epithelial cells create a tight barrier thereby blocking entry of foreign particles from the inhaled air to the tissue. This is further enforced by the underlying basement membrane (BM) which mainly consists of collagen type IV. The interstitial matrix (IM) is below the BM and consists mainly of fibrillar collagens and elastin. In COPD, the continuous epithelial layer is disrupted and the underlying BM is exposed. The inflammatory response to repetitive tissue injury results in up-regulation of proteases and disruption of the BM, allowing for injury to the underlying IM. In response to this, fibroblasts are activated and converted to pro-fibrotic myofibroblasts that secrete collagens which accumulate in the IM of the airway wall. Both collagens and elastin undergoes proteolytic degradation in the airway and alveolar walls. The processes of synthesis and degradation release extracellular matrix (ECM) fragments which may enter the bloodstream from where they can be assessed as biomarkers of ECM remodeling
Biomarker specifications
| Biomarker | Specifications | Measure | References |
|---|---|---|---|
| BGM | Biglycan degraded by MMPs | IM remodeling | [ |
| C1M | Collagen type I degraded by MMPs | IM remodeling | [ |
| C3A | Collagen type III degraded by ADAMTS | IM remodeling | Unpublisheda |
| C3M | Collagen type III degraded by MMP | IM remodeling | [ |
| C4M | Collagen type IV degraded by MMPs | BM remodeling | [ |
| C6M | Collagen type VI degraded by MMPs | IM remodeling | [ |
| CRPM | CRP degraded by MMPs | Local chronic inflammation | [ |
| ELM7 | Elastin degraded by MMP-7 | IM remodeling | [ |
| EL-NE | Elastin degraded by neutrophil elastase | IM remodeling | [ |
| Pro-C6 | Collagen type VI C5 domain (released) | IM remodeling | [ |
MMP matrix metalloproteinase, ADAMTS a disintegrin and metalloproteinase with thrombospondin motifs, IM interstitial matrix, BM basement membrane, CRP C-reactive protein
aThe C3A assay was validated following a standard protocol as described in [11]
Subject characteristics at baseline
| Survivors | Non-survivors |
| |
|---|---|---|---|
| ( | ( | ||
| Demographics | |||
| Age (yrs)* | 63 ± 7 | 68 ± 6 | <0.0001 |
| Female gendera | 352 (36) | 11 (37) | 0.97 |
| BMI (kg/m2)* | 26.8 ± 5.8 | 27.3 ± 7.8 | 0.78 |
| Current smoker (%)a | 366 (38) | 3 (10) | 0.004 |
| Pack years (yrs)* | 47 ± 25 | 56 ± 42 | 0.27 |
| Clinical variables | |||
| FEV1 (L)* | 1.42 ± 0.51 | 1.27 ± 0.43 | 0.11 |
| FEV1 (% predicted)* | 51 ± 15 | 48 ± 13 | 0.44 |
| GOLD Stageb | |||
| II | 480 (49) | 14 (47) | 0.93 |
| III | 392 (40) | 14 (47) | |
| IV | 98 (10) | 2 (7) | |
| Number of previous exacerbationsb | |||
| 0 | 531 (55) | 20 (67) | 0.29 |
| 1 | 239 (25) | 5 (17) | |
| 2 | 116 (12) | 2 (7) | |
| > 2 | 84 (9) | 3 (10) | |
| 6MWD (meters)* | 386 ± 119 | 335 ± 105 | 0.02 |
| mMRC dyspnoea score; median (Q1; Q3) b | 1 (1;2) | 2 (1;3) | 0.02 |
| %LAA (%)* | 16.3 ± 11.3 | 17.4 ± 10.5 | 0.61 |
| BODE index; median (Q1; Q3) b | 3 (1;4) | 3.5 (2;5) | 0.06 |
| SGRQ total score* | 46 ± 18 | 50 ± 20 | 0.29 |
| FACIT fatigue score* | 36 ± 10 | 31 ± 12 | 0.01 |
| Comorbiditiesa | |||
| Cardiovascular history | 304 (31) | 12 (40) | 0.42 |
| Hypertension | 381 (39) | 14 (47) | 0.53 |
| Asthma history | 225 (23) | 8 (27) | 0.82 |
| Diabetes type II | 82 (8) | 3 (10) | 0.97 |
| Osteoarthritis | 125 (13) | 3 (10) | 0.85 |
| Osteoporosis | 121 (12) | 6 (20) | 0.35 |
| Rheumatoid arthritis | 29 (3) | 0 (0) | 0.68 |
| Inflammatory bowel disorder | 48 (5) | 1 (3) | 0.98 |
| Interventionsa | |||
| Inhaled corticosteroids | 140 (14) | 3 (10) | 0.68 |
| Systemic corticosteroids | 8 (0.8) | 0 (0) | 0.59 |
| Statins | 237 (24) | 6 (20) | 0.73 |
Data are shown as mean ± SD or n (%) at baseline unless otherwise stated
BMI body mass index, FEV postbronchodilator forced expiratory volume in one second, GOLD global initiative for chronic obstructive lung disease, 6MWD 6-min walk distance, mMRC modified Medical Research Council dyspnoea scale, %LAA low attenuation area at −950 Hounsfield Units, BODE BMI, airflow obstruction, dyspnea and exercise capacity index, SGRQ St George’s respiratory questionnaire, FACIT functional assessment of chronic illness therapy
Statistical significance was determined using student’s t-test (*), chi-squared test (a), or Mann–Whitney U test (b)
Fig. 2Biomarker levels in survivors versus non-survivors. Biomarker levels were assessed at month six (BGM, C1M, EL-NE, Pro-C6) or year one (C3A, C3M, C4M, C6M, CRPM, ELM7, CRP, fibrinogen) in survivors (n = 970) and non-survivors (n = 30). All biomarkers, with the exception of BGM, EL-NE, and fibrinogen, were significantly elevated in non-survivors compared to survivors. Data are shown as geometric mean ± SEM. Statistical significance was determined using student’s t-test: *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001
Fig. 3Cox proportional hazards ratios for death. Hazard ratios (HR) for death are shown per one standard deviation increase in biomarker (a + b) and for subjects in the upper vs. lower quartile (c + d). Cox proportional HR with 95 % confidence intervals are shown for crude analyses (a + c) and analyses adjusted for age, BODE, and previous exacerbations (b + d). All biomarkers, with the exception of BGM, ELM7, and EL-NE, were significantly related to mortality outcome in both crude and adjusted analyses. Statistical significant hazard ratios are indicated as *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001
Fig. 4Kaplan-Meier survival curves for biomarker quartiles. Kaplan-Meier survival curves are shown for the biomarkers with crude hazard ratios for quartile 4 vs. 1 above 5. The relationship of biomarker quartiles with survival time from blood sampling are shown for plasma C3A (year one), plasma C3M (year one), plasma C6M (year one), serum ProC6 (month six), and plasma CRP (year one). Subjects in the upper biomarker quartiles (Q4) showed a higher number of deaths within the study period than the lower quartiles
Discriminatory power for the prognosis of death
| AUC (95 % CI) |
| |
|---|---|---|
| Serological biomarkers | ||
| C6M | 0.724 (0.695–0.752) | - |
| Pro-C6 | 0.722 (0.692–0.751) | - |
| CRP | 0.719 (0.689–0.747) | - |
| C6M + Pro-C6 | 0.796 (0.769–0.822) | - |
| C6M + CRP | 0.727 (0.697–0.755) | - |
| Pro-C6 + CRP | 0.775 (0.746–0.802) | - |
| C6M + Pro-C6 + CRP | 0.791 (0.762–0.818) | - |
| Clinical models | ||
| Age + BODE + Previous exacerbations | 0.750 (0.721–0.778) | |
| + C3M | 0.803 (0.776–0.829) | 0.084 |
| + CRPM | 0.807 (0.780–0.832) | 0.044 |
| + C6M | 0.813 (0.786–0.837) | 0.038 |
| + Pro-C6 | 0.826 (0.799–0.851) | 0.071 |
| + CRP | 0.811 (0.783–0.836) | 0.046 |
| + C6M + Pro-C6 | 0.867 (0.843–0.889) | 0.001 |
| + C6M + CRP | 0.817 (0.790–0.842) | 0.023 |
| + C6M + CRPM | 0.818 (0.791–0.842) | 0.036 |
| + Pro-C6 + CRP | 0.863 (0.837–0.886) | 0.001 |
| + Pro-C6 + CRPM | 0.864 (0.840–0.886) | 0.003 |
| + C6M + Pro-C6 + CRP | 0.871 (0.846–0.893) | 0.0004 |
| + C6M + Pro-C6 + CRPM | 0.871 (0.847–0.893) | 0.001 |
Shown are the single biomarkers with an area under the ROC curve (AUC) >0.700 and models with AUC >0.800. P values compare the AUC of the clinical model alone to the clinical model with added biomarker(s)