bioRxivCell Biology
Adventitial fibroblasts direct smooth muscle cell-state transition in pulmonary vascular disease
Slaven CrnkovićiD, Helene Thekkekara Puthenparampil, Shirin Mulch, Valentina BiasiniD, Nemanja RadiciD, Jochen WilhelmiD, Marek BartkuhniD, Ehsan Bonyadi Rad, Alicja Wawrzen, Ingrid MatzeriD, Ankita MitraiD, Ryan D. LeibiD, Bence Miklos NagyiD, Anita Sahu-Osen, Francesco Valzano, Natalie BordagiD, Matthias EvermanniD, Konrad HöetzeneckeriD, Andrea OlschewskiiD, Senka Ljubojević-HolzeriD, Małgorzata WygreckaiD, Kurt R. StenmarkiD, Leigh Matthew MarshiD, Vinicio de Jesús PéreziD, Grażyna KwapiszewskaiD
Abstract
Pulmonary vascular remodeling is a progressive pathological process characterized by functional alterations within pulmonary artery smooth muscle cells (PASMC) and adventitial fibroblasts (PAAF). Mechanisms driving the transition to a diseased phenotype remain elusive. Utilizing a combination of transcriptomic and proteomic profiling, along with phenotyping of source-matched cells from healthy controls and individuals with idiopathic pulmonary arterial hypertension (IPAH), our investigation uncovered that while PASMC and PAAF retained their original cellular identities, they acquired distinct disease-associated states. Though both cell types exhibited reduced mitochondrial content and hyperpolarization, IPAH-PASMC displayed heightened glycosaminoglycan production and downregulation of contractile machinery, contrasting a hyperproliferative phenotype of IPAH-PAAF. We investigated the involvement of cellular crosstalk in regulating cell state dynamics and identified pentraxin-3 and hepatocyte growth factor as potential modulators of PASMC phenotypic transition orchestrated by PAAF. Our findings contribute to a deeper understanding of pulmonary vascular mesenchyme dynamics in disease pathogenesis.
- organism: human
- assay: bulk RNA-seq
- assay: proteomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: experimental assay
- approach: statistical model
- Citations
- 4
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