D16-01 Spatial Transcriptomic Atlas of the Human Lung in Pulmonary Arterial Hypertension

Abstract Introduction Pulmonary arterial hypertension (PAH) is characterized by progressive pulmonary vascular remodeling, leading to right heart failure and premature death. Subcellular spatial transcriptomic profiling of explanted lung tissue from affected patients presents a promising method for uncovering novel insights into disease pathophysiology. Methods Spatial transcriptomic analysis was conducted on human lung samples from the Pulmonary Hypertension Breakthrough Initiative using the 10x Genomics Xenium workflow (n = 5,101 genes profiled). Rigorous quality control measures were implemented, including removal of low-quality transcripts and segmented cells with low transcript counts (30). Cell populations were annotated through iterative clustering and marker gene identification. Differential gene expression analysis was conducted using a pseudobulk approach with edgeR. Gene set enrichment analysis (GSEA) was performed using the Hallmark pathways. Cell type abundance was investigated and correlated with clinical indices of disease severity. Results Lung samples from 73 individuals were profiled, including 47 PAH and 26 age- and sex-matched control lungs. After quality control, a median of 2,997 cells per sample were captured. Clustering uncovered 39 unique cell types, representing epithelial, immune, endothelial, and stromal lineages of the lung. A median of 122 transcripts and 109 genes were detected per cell. Differentially expressed genes between PAH and control were detected in all major cell populations (FDR 0.05). GSEA revealed interferon response in monocytes and epithelial-to-mesenchymal transition in stromal subpopulations as top upregulated pathways. Various cell populations showed differential abundance in PAH lungs. Notably, myofibroblasts were more abundant in PAH lungs and correlated with higher pulmonary vascular resistance. Conclusion Spatial transcriptomic analysis of human lungs affected by PAH revealed broad dysregulation across genes and pathways. This rich dataset provides a foundation for deeper insights into the molecular mechanisms underlying PAH. This abstract is funded by: NHLBI K08HL169982, K23HL181383