Back

Transcriptomic analyses reveal regional signatures in lung allograft recipients

Agudelo-Romero, P.; Ling, K.-M.; Lavander, M. A.; Wrobel, J. P.; Musk, M.; Stick, S. S.; Kicic, A.

2023-04-03 transplantation
10.1101/2023.04.03.23288063 medRxiv
Show abstract

BackgroundLong term outcomes of allograft recipients are compromised by the development of chronic lung allograft dysfunction (CLAD) promoting bronchiolitis obliterans syndrome (BOS). We established baseline transcriptomic profiles of both the large and small airway epithelial cells (referred as LAEC and SAEC, respectively) to identify regional differences irrespective of initiating disease. MethodsWe obtained matched primary LAEC and SAEC from lung allograft recipients (n=4, 42.5 {+/-} 4.2 years) and established primary cultures. Bulk RNA sequencing was performed to determine differentially expressed genes. ResultsWe observed differences in the transcriptional program between LAEC and SAEC Transcription factors (TF) were ranked within the top ten differentially regulated genes. The most abundant TF families included C2H2-ZF, homeobox and bHLH. Upstream regulator analyses identified homeobox genes being significantly in LAEC. Protein-protein interaction network analysis emphasised the role of TFs (ISL1, MSX1, HOXA1, GATA6, ZNF423) in airway modulation. Additionally, functional enrichment analysis revealed the activation of chemotaxis, metalloendipeptidase/metallopeptidase activity and pro-inflammatory signatures (IL17 signalling and RAGE), in LAEC, while SAEC were characterised by elevated expression of surfactant metabolism related genes. Moreover, alveolar and club cells-related genes were expressed in SAEC, suggesting a lower airway-specific signature. ConclusionOur analysis shows robust transcriptional differences between LAEC and SAEC. We suggest a potential role for homeobox TF family as well as the activation of the immune system in the biology of LAEC. Conversely, we observed an alveoli-like transcriptional signature in SAEC, including gas-exchange signals and surfactant metabolism; pathways involved in lung homeostasis.

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.