Multicenter IPF-PRO Registry Cohort
Posted on (Update: )
- MMPs: matrix metalloproteinases (金属蛋白酶)
- TIMPs: tissue inhibitors of MMPs
- IPF: idiopathic (突发性的，自发性的) pulmonary (肺的) fibrosis (纤维变性)
- CPI: composite physiologic index, 复合生理指数
- ECM: extracellular matrix, 细胞外基质，主要由胶原蛋白和弹性蛋白组成，是支撑皮肤的结构网络。
- FVC: forced vital capacity, 最大肺活量
the study aims to
- determine the utility of circulating MMPs and TIMPs in distinguishing patients with IPF from controls
-
explore associations between MMPs/TIMPs and measures of disease severity in patients with IPF
- IPF-PRO Registry: an observational multicenter registry of patients with IPF that was diagnosed or confirmed at the enrolling center in the past 6 months
- IPF cohort (n=300) from IPF-PRO Registry
- Controls (n=100) without known lung disease from a population-based registry
- GLM used to compare circulating concentrations of MMPs and TIMPs between patients with IPF and controls
- Multivariate models were fit to identify the MMP/TIMPs that best distinguished patients with IPF from controls.
Results:
- except for TIMP2, all the MMP/TIMPs are significant in patients with IPF compared with controls
- MMP8, MMP9, and TIMP1 are selected as top candidates
- higher MMP7, MMP12, MMP13 and TIMP4 are significant associated with lower diffusion capacity of the lung for carbon monoxide and higher CPI (worse disease)
- MMP9 was associated with the composite physiologic index
- No MMP/TIMPs were associated with forced vital capacity
Background
- IPF is a progressive interstitial (组织间隙的) lung disease associated with high mortality.
- Two anti-fibrotic agents can slow the progression of the disease
- the diagnosis and management of IPF remain challenging, with no clinically available biomarkers to serve as adjuncts in diagnosis or prediction of prognosis or treatment response.
- The pathobiology of IPF involves excess production of extracellular matrix (ECM) and dysregulated matrix remodeling.
- MMPs are a family of zinc-dependent endopeptidases important in ECM degradation.
- Expression of MMPs and their physiological inhibitors, tissue inhibitors of MMPs (TIMPs), is tightly regulated in the lung, with notable upregulation during lung development, tissue injury, and host defense.
- The importance of MMPs and TIMPs has been underscored
- murine (鼠科，包括鼠和鼹鼠) models of bleomycin-induced pulmonary fibrosis demonstrated increased expression of MMPs and TIMPs, while mice with genetic deletions in select MMPs had reduced lung fibrosis after bleomycin (博莱霉素) administration compared with wild type mice.
- Patients with IPF showed increased MMP and TIMP expression in the lungs, including in structural cells (e.g., the epithelium (上皮细胞)) and immune cells (e.g., interstitial macrophages (巨噬细胞))
- Circulating levels of MMPs 1,3,7,8 and 9 have been shown to be elevated in patients with IPF, and higher circulating levels of MMP7 to be associated with more severe disease, a higher risk of disease worsening over a 3-year period, and shorter survival time.
- a relative paucity of information on the full range of MMPs and TIMPs detectable in the blood of patients with IPF and their utility as biomarkers.
- Target: determine expression of MMPs 1,2,3,7,8,9,12 and 13 and TIMPs 1,2, and 4 in a cohort of well-characterized patients with IPF, to understand if combinations of MMPs and TIMPs could distinguish patients with IPF from controls, and to investigate associations between MMPs/TIMPs and measures of IPF severity.
Methods
- IPF cohort
- Control cohort: ensure it had a similar age, race and ethnicity distribution to the IPF cohort
- MMP and TIMP quantification:
- plasma (血浆) samples were assayed for antigenic levels of MMPs 1,2,3,7,8,9,12 and 13
- Statistical analyses: SAS 9.4 or R 3.5.1
- GLM was used to compare MMP and TIMP concentrations between patients with IPF and controls.
- data were log10 transformed
- descriptive box-plots
- results of the statistical analyses were back-transformed to the original scale and described as geometric means and geometric mean ratios of the IPF versus control groups.
- correction for multiple comparisons was performed using the BH method to control the false discovery rate at 5%
- Multivariable analyses to assess whether a set of MMPs or TIMPs could differentiate patients with IPF from controls
- log10 data were centred, scaled, and Box-Cox transformed to improve model efficiency
- No MMPs or TIMPs were highly correlated, so all analytes were retained
- 400 = training (300) + testing (100)
- 3 linear models (penalized logistic regression, linear discriminant analysis, partial least squares)
- 4 non-linear models (K-nearest neighbors, SVM, single tree, random forests)
- 10 CV were used to choose the tuning parameters
- Variable importance measures were determined for the best performing models
- Univariate analyses in IPF cohort
- linear regression models on the log10 transformed data to determine the association between circulating levels of each MMP/TIMP and three measures of disease severity (analyzed as continuous variables: FVC % predicted, DLco % predicted, and the composite physiologic index (CPI)), which correlates with the extent of fibrosis on radiography in patients with IPF.
- BH method was used to control the false discovery rate at 5%.
- estimated coefficients and confidence intervals to calculate the estimated difference between the median MMP/TIMP concentration in patients in the lowest tertile (三分之一) of disease severity and the median concentration in patients in the highest tertile of disease severity.
- Multivariable analyses of IPF cohort
- FVC, DLco, CPI were modeled separately to examine their relationship with sets of MMPs/TIMPs.
- pairwise correlation analysis indicated no MMPs or TIMPs were highly correlated.
- 2 linear models (partial least squares and penalized linear regression)
- 4 non-linear models (KNN, SVM, single tree, random forests)
- GLM was used to compare MMP and TIMP concentrations between patients with IPF and controls.
Results
- Cohort characteristics
- Associations between MMP/TIMP levels and presence or severity of IPF
- Level of each MMP and TIMP analyzed was significantly higher in patients with IPF vs controls with the exception of TIMP2
- higher geometric mean ratios of concentration in patients with IPF vs controls were observed with MMP8, MMP1, and MMP9
- no statistically significant associations between levels of MMPs or TIMPs and FVC, but higher levels of MMPs 7, 8, 12 and 13 and TIMP4 were significantly associated with lower DLco % predicted and higher (worse) CPI score
- higher MMP9 were significantly associated with higher CPI
- For estimated effect size, MMP7 > TIMP4 > MMP13
- For smoking status, No significant differences were observed in either the IPF or control populations.
- Sets of MMPs/TIMPs that best discriminate IPF
- linear multivariable models had similar or better operating characteristics compared with more complex non-linear methods in the training set
- Predictions of IPF disease severity using MMP and TIMP measurements
- Maximum R-squared value achieved for predicting any disease severity measure was 0.16 in the training set (Too small??)
Discussion
- the study not only provides insights into how single MMPs/TIMPs relate to IPF status and severity, but also considers the influence of combinations of these proteins
- circulating MMPs and TIMPs are generally elevated among patients with IPF
- combination of MMPs 8 and 9 and TIMP1 demonstrated good performance characteristics in differentiating patients with IPF from controls
- MMPs 7, 8, 12, 13 associated with both DLco and CPI, while MMP9 associated with CPI only
Conclusion
- extension of analyses to examine associations between MMP/TIMP expression and clinical outcomes
- further the goal of improving the diagnosis and management of patients with IPF