Single-cell multi-omic analysis of post-transplant mesenchymal cells reveals molecular signatures and putative regulators of lung fibrosis

Primary graft dysfunction (PGD) and chronic lung allograft dysfunction (CLAD) are critical challenges in lung transplantation. Dysregulated gene expression and epigenomic states in lung mesenchymal cells (MCs) play a key role in these conditions, but further work is needed to elucidate the biomarkers and molecular drivers. Single-cell multi-omic technologies offer an unprecedented opportunity to address this gap by jointly measuring gene expression and chromatin accessibility in diseased and healthy cells. We performed single-cell multi-omic profiling and genetic demultiplexing on MCs isolated from human bronchoalveolar lavage samples of lung transplant recipients with CLAD and PGD, compared with time-matched controls. A classification model trained on these profiles classified the disease status of individual cells with > 98% accuracy using a small set of signature genes. We further identified 8 subtypes of MCs each characterized by distinct transcriptomic and epigenomic signatures, including a CLAD-enriched subtype and a PGD-enriched subtype. The CLAD-enriched subtype expresses markers of fibrosis, while the PGD-enriched subtype expresses pro-inflammatory genes. Finally, we used co-accessibility and co-expression to identify C/EBPD, SOX4, and FOXP2 as key regulators of the genes and chromatin accessibility peaks that are dysregulated in the CLAD-enriched cell population. Knocking down C/EBPD with siRNA partially reverted the CLAD gene expression signature, confirming the importance of this factor in the dysregulated molecular state of CLAD-associated MCs. Additional scRNA-seq analysis of MCs from human lung autopsy samples showed that cultured MCs retained key transcriptomic signatures from their in vivo counterparts. Sub-clustering analysis identified a CLAD-enriched MC sub-cluster with high C/EBPD expression, further linking these cells to the fibrotic state seen in vitro. Our results provide deeper insights into the transcriptomic and epigenomic changes in post-transplant MCs, nominating biomarkers and disease-associated factors with implications for future therapeutic efforts.