Molecular diagnostics for CLAD: When and where?

Abstract

Improving long-term survival following lung transplantation will require new therapeutic approaches to chronic lung allograft dysfunction (CLAD). While CLAD is predominantly driven by obliterative bronchiolitis pathology, substantial small airways loss is needed to result in the 20% decline in FEV1 that defines this diagnosis. At the same time, several distinct biologic processes can drive FEV1 decline. This diagnostic challenge limits the development of mechanism-specific therapies and clouds prognosis. Thus, there is strong motivation to develop molecular approaches to diagnose and phenotype CLAD. Mechanistically, CLAD is thought to represent airway and parenchymal remodeling secondary to chronic alloimmune injury. A key question in developing CLAD diagnostics is whether to focus on immune activation, airway remodeling, or both. The study by Parkes et al.1 investigates transbronchial biopsy (TBB) gene expression changes in CLAD involving 498 TBBs collected across 10 centers. Because the risk for CLAD increases with time, the authors determined differentially expressed genes independently associated with time and CLAD. Parkes et al. found that the most CLAD-selective transcripts corrected for time reflected tissue injury-related genes, including HIF1A, IGF1, and SERPINE2. However, genes associated with inflammation segregated more with time, but were found to be less selective for CLAD. The finding of a tissue injury pattern in CLAD stands distinct from prior transcriptomic studies of BAL or airway brushings.2, 3 Outside of two TNFRSF6B-related transcripts, the top 20 gene list did not overlap with an externally validated CLAD gene signature, where type 1 immune response genes predominated.4 Parkes et al. compare CLAD to “everything else,” which could include other acute lung allograft dysfunction (ALAD) events such as acute cellular rejection and infection. This deliberate strategy could potentially lead to an underestimation of inflammatory changes associated with CLAD when the control group contains samples from ALAD episodes rather than stable, quiescent controls. Such a strategy is useful in revealing the quintessential features of CLAD. However, the most compelling goal in molecular CLAD diagnostics is not so much to identify subjects with FEV1 decline, or even predict those who will go on to graft failure, but to identify those who will respond to specific treatments. One could speculate that inflammatory and fibrotic subtypes of CLAD exist, the former which would respond to augmented immune suppression but could be missed in a gene signature that potentially underestimates inflammation. At the same time, the observation of evolving molecular pathways across the time course of CLAD suggests that the most differentially expressed gene list will be highly dependent on how cases and controls are divided.3 Another issue influencing the results of molecular diagnostic and biomarker studies in CLAD is the method of tissue sampling and where within the lung allograft is sampled. Obliterative bronchiolitis is the predominant histopathologic feature of the bronchiolitis obliterans syndrome (BOS) subtype of CLAD and frequently identified in the restrictive allograft syndrome (RAS) subtype as well. This airway-centric pathology involves intraluminal and peribronchiolar collagen deposition and fibrosis, leading to luminal narrowing and small airway occlusion. However, the alveoli and lung parenchyma are frequently spared.5 Consistent with this, prior studies have demonstrated that TBBs have low sensitivity for diagnosing BOS/CLAD.3, 6 Further, direct comparison of CLAD-associated differential gene expression between TBB and small airway brushes showed increased signal to noise in the small airways, such that classifiers using airway brushes outperformed those based on TBB tissue.3 Similarly, sampling the alveolar compartment more than the small airways might contribute to the lack of inflammatory signals observed relative to other studies.4 The Parkes et al. study is the most comprehensive assessment of a molecular signature for CLAD in TBBs to date, leveraging clinically obtained samples as part of standard clinical practice. The large cohort collected across multiple sites suggests findings will generalize to other sites. Methodologically, their CLAD classifier takes the median result across 12 machine learning approaches. This democratic method has the potential to avoid biases specific to any one machine learning approach. These methods are not entirely independent, however, and so biases inherent to multiple methods might persist. Further, with this approach, the relationship between expression of specific genes and CLAD status is unclear. Nonetheless, this classifier provides strong correlation with clinical CLAD, with an intensification of the signature in advanced CLAD (stages 2 and 3). Molecular diagnostics for CLAD are poised to provide clarity, improve prognosis, and guide therapy. This study takes us one step closer to answering the critical outstanding questions of which transcripts to measure, and when and where to measure them. JRG is supported by the National Heart, Lung, and Blood Institute (HL151552) and the VA Office of Research and Development (CX002011). JFM is supported by the National Heart, Lung, and Blood Institute (HL133184) and the Cystic Fibrosis Foundation (00832G221). The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.