Individualized interactomes for network-based precision medicine in hypertrophic cardiomyopathy with implications for other clinical pathophenotypes

Bradley A. Maron (), Rui-Sheng Wang, Sergei Shevtsov, Stavros G. Drakos, Elena Arons, Omar Wever-Pinzon, Gordon S. Huggins, Andriy O. Samokhin, William M. Oldham, Yasmine Aguib, Magdi H. Yacoub, Ethan J. Rowin, Barry J. Maron, Martin S. Maron and Joseph Loscalzo
Additional contact information
Bradley A. Maron: Brigham and Women’s Hospital and Harvard Medical School
Rui-Sheng Wang: Brigham and Women’s Hospital and Harvard Medical School
Sergei Shevtsov: Brigham and Women’s Hospital and Harvard Medical School
Stavros G. Drakos: University of Utah School of Medicine
Elena Arons: Brigham and Women’s Hospital and Harvard Medical School
Omar Wever-Pinzon: University of Utah School of Medicine
Gordon S. Huggins: Tufts Medical Center
Andriy O. Samokhin: Brigham and Women’s Hospital and Harvard Medical School
William M. Oldham: Brigham and Women’s Hospital and Harvard Medical School
Yasmine Aguib: Imperial College of London
Magdi H. Yacoub: Imperial College of London
Ethan J. Rowin: Tufts Medical Center
Barry J. Maron: Tufts Medical Center
Martin S. Maron: Tufts Medical Center
Joseph Loscalzo: Brigham and Women’s Hospital and Harvard Medical School

Nature Communications, 2021, vol. 12, issue 1, 1-11

Abstract: Abstract Progress in precision medicine is limited by insufficient knowledge of transcriptomic or proteomic features in involved tissues that define pathobiological differences between patients. Here, myectomy tissue from patients with obstructive hypertrophic cardiomyopathy and heart failure is analyzed using RNA-Seq, and the results are used to develop individualized protein-protein interaction networks. From this approach, hypertrophic cardiomyopathy is distinguished from dilated cardiomyopathy based on the protein-protein interaction network pattern. Within the hypertrophic cardiomyopathy cohort, the patient-specific networks are variable in complexity, and enriched for 30 endophenotypes. The cardiac Janus kinase 2-Signal Transducer and Activator of Transcription 3-collagen 4A2 (JAK2-STAT3-COL4A2) expression profile informed by the networks was able to discriminate two hypertrophic cardiomyopathy patients with extreme fibrosis phenotypes. Patient-specific network features also associate with other important hypertrophic cardiomyopathy clinical phenotypes. These proof-of-concept findings introduce personalized protein-protein interaction networks (reticulotypes) for characterizing patient-specific pathobiology, thereby offering a direct strategy for advancing precision medicine.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41467-021-21146-y Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21146-y

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-021-21146-y

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().