Individualized Interactomes from Pulmonary Arterial Hypertension Cell Biopsies Predict Therapeutic Response Article Swipe
Rui Sheng Wang
,
Navneet Singh
,
Henri Wathieu
,
Grayson Baird
,
KATHERINE COX-FLAHERTY
,
James R. Klinger
,
Christopher J Mullin
,
Mandy Pereira
,
Mary Whittenhall
,
Elizabeth O. Harrington
,
Bradley A. Maron
,
Corey E. Ventetuolo
,
Rui-Sheng Wang
,
Christopher Mullin
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.11.13.25340200
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.11.13.25340200
Pulmonary arterial hypertension (PAH) is characterized by molecular heterogeneity and variable pharmacotherapeutic responses. We used an in silico clinical trial design to test whether transcriptomic data from pulmonary artery endothelial cell biopsies collected during right heart catheterization could be used to build individualized protein-protein interactomes and inform treatment response. Twenty-five PAH participants (56 [range: 30-84] yr; 91% female; 81%, white) and three controls contributed 32 and three cell biopsy specimens, respectively. Patient-specific interactomes varied widely in topology and complexity. All 32 individualized PAH interactomes were enriched significantly with key PAH endophenotypes genes such as hypoxia, oxidant stress, and apoptosis. Concordance between the molecular targets of a prescribed PAH pharmacotherapy class and the corresponding individualized interactome topology was associated with improvement in multiple PAH metrics, including a reduction in brain natriuretic peptide levels at 6 months (β -627.6 pg/mL, [95% CI -986.4, -268.8]; p = 0.003) and a decrease from high to intermediate REVEAL 2.0 Risk scores at 6 months (β -1.3 units, [95% CI -2.6, -0.04]; p=0.043) that persisted at 12 months (β -1.7, [95% CI -3.4, -0.1]; p=0.059). Integration of transcriptomics acquired at point-of-care with network medicine may individualize treatment selection and improve clinically relevant endpoints in PAH.
Related Topics
Concepts
Interactome
Transcriptome
Medicine
Concordance
Bioinformatics
Cell
Clinical trial
Computational biology
Selection (genetic algorithm)
Internal medicine
Personalized medicine
Phenotype
Gene expression profiling
Oncology
Biology
Endophenotype
Gene
Cell type
Metabolome
Drug
Comorbidity
Pharmacology
Biopsy
Randomized controlled trial
Systems biology
Protein–protein interaction
Biomarker
Proteomics
Metadata
- Type
- article
- Landing Page
- https://doi.org/10.1101/2025.11.13.25340200
- https://www.medrxiv.org/content/medrxiv/early/2025/11/15/2025.11.13.25340200.full.pdf
- OA Status
- green
- References
- 38
- OpenAlex ID
- https://openalex.org/W7105802351
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W7105802351Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2025.11.13.25340200Digital Object Identifier
- Title
-
Individualized Interactomes from Pulmonary Arterial Hypertension Cell Biopsies Predict Therapeutic ResponseWork title
- Type
-
articleOpenAlex work type
- Publication year
-
2025Year of publication
- Publication date
-
2025-11-15Full publication date if available
- Authors
-
Rui Sheng Wang, Navneet Singh, Henri Wathieu, Grayson Baird, KATHERINE COX-FLAHERTY, James R. Klinger, Christopher J Mullin, Mandy Pereira, Mary Whittenhall, Elizabeth O. Harrington, Bradley A. Maron, Corey E. Ventetuolo, Rui-Sheng Wang, Christopher MullinList of authors in order
- Landing page
-
https://doi.org/10.1101/2025.11.13.25340200Publisher landing page
- PDF URL
-
https://www.medrxiv.org/content/medrxiv/early/2025/11/15/2025.11.13.25340200.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.medrxiv.org/content/medrxiv/early/2025/11/15/2025.11.13.25340200.full.pdfDirect OA link when available
- Concepts
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Interactome, Transcriptome, Medicine, Concordance, Bioinformatics, Cell, Clinical trial, Computational biology, Selection (genetic algorithm), Internal medicine, Personalized medicine, Phenotype, Gene expression profiling, Oncology, Biology, Endophenotype, Gene, Cell type, Metabolome, Drug, Comorbidity, Pharmacology, Biopsy, Randomized controlled trial, Systems biology, Protein–protein interaction, Biomarker, ProteomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
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38Number of works referenced by this work
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