Systems prediction of chronic lung allograft dysfunction: Results and perspectives from the Cohort of Lung Transplantation and Systems prediction of Chronic Lung Allograft Dysfunction cohorts

Abstract

Background: Chronic lung allograft dysfunction (CLAD) is the leading cause of poor long-term survival after lung transplantation (LT). Systems prediction of Chronic Lung Allograft Dysfunction (SysCLAD) aimed to predict CLAD.

Methods: To predict CLAD, we investigated the clinicome of patients with LT; the exposome through assessment of airway microbiota in bronchoalveolar lavage cells and air pollution studies; the immunome with works on activation of dendritic cells, the role of T cells to promote the secretion of matrix metalloproteinase-9, and subpopulations of T and B cells; genome polymorphisms; blood transcriptome; plasma proteome studies and assessment of MSK1 expression.

Results: Clinicome: the best multivariate logistic regression analysis model for early-onset CLAD in 422 LT eligible patients generated a ROC curve with an area under the curve of 0.77. Exposome: chronic exposure to air pollutants appears deleterious on lung function levels in LT recipients (LTRs), might be modified by macrolides, and increases mortality. Our findings established a link between the lung microbial ecosystem, human lung function, and clinical stability post-transplant. Immunome: a decreased expression of CLEC1A in human lung transplants is predictive of the development of chronic rejection and associated with a higher level of interleukin 17A; Immune cells support airway remodeling through the production of plasma MMP-9 levels, a potential predictive biomarker of CLAD. Blood CD9-expressing B cells appear to favor the maintenance of long-term stable graft function and are a potential new predictive biomarker of BOS-free survival. An early increase of blood CD4 + CD57 + ILT2+ T cells after LT may be associated with CLAD onset. Genome: Donor Club cell secretory protein G38A polymorphism is associated with a decreased risk of severe primary graft dysfunction after LT. Transcriptome: blood POU class 2 associating factor 1, T-cell leukemia/lymphoma domain, and B cell lymphocytes, were validated as predictive biomarkers of CLAD phenotypes more than 6 months before diagnosis. Proteome: blood A2MG is an independent predictor of CLAD, and MSK1 kinase overexpression is either a marker or a potential therapeutic target in CLAD.

Conclusion: Systems prediction of Chronic Lung Allograft Dysfunction generated multiple fingerprints that enabled the development of predictors of CLAD. These results open the way to the integration of these fingerprints into a predictive handprint.

Keywords: Frontiers in medicine; bronchiolitis obliterans syndrome; chronic lung allograft dysfunction; chronic rejection; pulmonary section; restrictive allograft syndrome.

Figure 1

Flow chart diagram of the evaluated population, adapted from (23).

Figure 2

Averaged 12-month concentration of particulate matter with an aerodynamic cut-off of 2.5 μm (PM2.5) and 10 μm (PM10), NO2 and O3 across France in 2011, adapted from (20).

Figure 3

Adjusted associations between air pollutants exposure and level of (A) FEV₁% predicted and (B) FVC% predicted in the whole population and according to the use of macrolides. PMx: particulate matter with an aerodynamic cross section of x μm, adapted from (20).

Figure 4

Prominent bacterial genera associated with inflammation, intermediate, or remodeling profiles in a subset of 75 bronchoalveolar lavage fluid samples, and in vitro assessment of innate cell activation through various stimuli including reconstituted bacterial communities. (A) Relative abundance of bacterial genera derived from 16S sequencing data. Genera are classified as per membership to Prevotella or infectious communities and the underlying innate activation profile is indicated. (B) Phylogenetic tree showing phylum assignment of the main bacterial genera, the structure of their endotoxin derived from a previous study (35), and their membership to Prevotella or infectious communities (color code). (C) Proportion of inflammation, intermediate, and remodeling activation within three sample subsets with decreasing relative abundance of Prevotella community. (D,E) Quantitative polymerase chain reaction–based gene expression analysis at 18-h post-stimulation enabling quantification of markers of either inflammation (TNF, COX-2) or remodeling (PDGFD, TIMP1/MMP12 ratio), under immunosuppressive conditions. Bacteria belonging to species representative of either infectious communities (Staphylococcus aureus and Pseudomonas aeruginosa) or Prevotella community (Streptococcus pneumoniae and Prevotella melaninogenica) were incubated with THP-DM at a ratio of 10 colony-forming units per cell. Bacteria of different species were used separately (D), paired based on community membership, or within reconstituted bacterial communities comprising four species at indicated ratios (E). Data were generated in six independent experiments with duplicates or triplicates. Error bars represent SEM. Statistical significance was determined using the Kruskal-Wallis test and Dunn post-hoc analysis. *p<0.05, **p<0.01, ***p<0.001. COX, cyclooxygenase; MMP, matrix metalloproteinase; PDGFD, platelet-derived growth factor D; THP-DM, THP-1-derived macrophages; TIMP, tissue inhibitor of metalloproteinase; TNF, tumor necrosis factor, adapted from (18).

Figure 5

Airway microbiota signals anabolic and catabolic remodeling in the transplanted lung, graphical abstract, adapted from (24).

Figure 6

Associations among host remodeling, inflammation, and infection. Relationship among host remodeling and BAL cell differential (A), expression of inflammatory genes COX2 and TNF-a (B), the prevalence of suspected clinical infection (C), and bacteria isolated by culture and/or driving dysbiosis (D). In panels A and B, medians and IQRs are indicated. *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001, adapted from (21).

Figure 7

Decreased CLEC1A expression in lung transplants is predictive of CLAD. Lung transplants from stable patients or from patients prior to the development of CLAD were subjected to qRT-PCR for HPRT, CLEC1A, IL17A, IFNG, and TGFB1. Results were expressed in histograms as mean 6SEM of 7 samples in each group and were expressed in AU of specific cytokine/HPRT ratio. *p, 0.05; **p, 0.01. mRNA, messenger RNA, adapted from (19).

Figure 8

Summary of the main findings. TGF-β can be produced within the graft by alveolar macrophages, neutrophils, endothelial cells, or fibroblasts. CCL2 produced by activated T cells binds to CCR2 and supports the production of MMP-9 in synergy with TGF-β. MMP-9 then contributes to the remodeling processes leading to airway obstruction adapted from (22).

Figure 9

Summary of the main findings. (A) Steady-state: cytosolic β-catenin is phosphorylated by the GSK complex and targeted to the proteasome for degradation. (B) Wnt ligand production after TGF-β exposure stabilizes the GSK complex at the cell membrane and reduces β-catenin degradation. (C) Then, the massive relocation of β-catenin after poly (I: C) treatment, fuels the Wnt/β-catenin pathway and allows β-catenin translocation in the nucleus for MMP-9 expression adapted from (24).

Figure 10

Analysis of CD4⁺CD25^hiFoxP3⁺ T-cell proportions early post LT as a predictive biomarker of BOS development. (A) ROC curve of the proportion of CD4⁺CD25^hiFoxP3⁺ T cells among CD4 T cells at 1 month after transplantation for BOS (n = 8) and STA (n = 6). (B) Kaplan–Meier analysis of BOS-free survival according to CD4⁺CD25^hiFoxP3⁺ T-cell proportions among CD4 T cells at 1-month post-transplantation with a cut-off a t2.4% (n = 14). (C) ROC curve of the proportion of CD4⁺CD25^hiFoxP3⁺ T cells among CD4 T cells at 6 months post LT for BOS (n = 11) and STA (n = 24). (D) Kaplan–Meier analysis of BOS-free survival according to CD4⁺CD25^hiFoxP3⁺ T-cell proportions among CD4 T cells at 6 months post-transplantation with a cut-off at 2.4%(n = 35). Results are expressed as mean ± SEM. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001, adapted from (26).

Figure 11

Comparison of graft survival between patients with a % of CD4 + CD57 + ILT2+ T cells (% of CD4+ T cells) ≤ first IQR (25%) at 1-month (A) and 6 months (B) post-LT vs. those with % CD4 + ILT2 + CD57+ T cells (% of CD4+ T cells) > first IQR (25%) adapted from (27).

Figure 12

ROC curve and Kaplan–Meier analysis of the level of CD9 + B cells 24 months post-LT in BOS and STA patients of the validation cohort, adapted from (31).

Figure 13

Illustration of the hypothesis: in lung grafts with the G allele of CCSP polymorphism, IR causes an increase in p53 associated with an increase in apoptosis and a decrease in the production of CCSP in lung epithelial cells, thus constituting a vicious circle that may lead to PGD. Conversely, in lung grafts with the A allele of CCSP G38A polymorphism, IR-induced p53 increase has no effect on CCSP expression and CCSP levels, adapted from (29).

Figure 14

Independent validation. Microarray gene expression data (bar histograms) were validated by quantitative PCR in an independent set of patients (dot histograms) comparing STA and PRED (A) and STA and DIAG (B). Mann–Whitney p values are indicated, adapted from (25).

Figure 15

Evolution over time of MSK1 expression in CLAD and stable patients represented by relative RNA expression (1 biopsy per patient and time point). Dots represent value for each patient’s biopsy and line the evolution of expression for each patient over time: for CLAD patients as months before diagnosis, and for stable patients as Mo posttransplantation. CLAD, chronic lung allograft dysfunction; Mo, months; MSK1, mitogen-and stress-activated kinase 1, adapted from (30).

Figure 16

Predictive and/or early marker of CLAD after lung transplantation, main contributions of the COLT and SyCLAD cohorts, reference issued from our cohort studies.