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

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.


Statistics
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Software and code
Policy information about availability of computer code Data collection The interactome was manually compiled from published large-scale studies on human protein-protein interactions. Genes associated with endophenotypes were manually collected from an open source Phenopedia. All the resources are referenced in the manuscript and available from the corresponding author upon request. No software was used for data collection.

Data analysis
Differentially expressed genes were identified using EdgeR which is a free Bioconductor software package. Network construction based on correlation changes was implemented by our own R and Python scripts. We have deposited our codes in a publicly available website (DOI: 10.5281/zenodo.4429826).
For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors and reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.

Data
Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability The HCM RNA-seq data and HCM exome VCF files have been uploaded to the GEO database (accession ID: GSE160997). All of the source programming code used in this study has been uploaded to Gihub (https://github.com/bwh784/HCM), which is a platform for sharing software packages. Other data that support the findings of this study are available from the corresponding author upon reasonable request. The RNA-seq and DNA sequencing data that support the findings of this study

April 2020
have been deposited in the GEO database. Accession ID GSE160997[https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE160997]. Other data that support the findings of this study are available from the corresponding author upon reasonable request.

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Sample size
The Data exclusions Upon optimizing the experimental methods, all data were included in the analyses unless a specific technical reason was present that confounded the interpretation of a finding. Specifically, technical problems that obscured clear visualization of data occurred for experiments relating to Figure 3A (real time qPCR experiments performed on myocardial tissue, which was due to primer optimization), Figure 3B (immunofluorescence on myocardial samples, due primarily to antibody concentration optimization), Figures 3D,E (western blot using homogenized myocardial samples, which was due primarily to problems with film development, antibody-target binding, or other typical methodological issues that may arise during this experimental protocol), and Figure 3F and Supplemental Figure 4D (trichrome staining, which was due primarily to problems related to staining intensity). If a technical limitation was not identified in an experiment, the data were included in the analysis presented in the manuscript.

Replication
For data in Figures 3A, 3B, 3D, 3E, 3F and Supplemental Figure 4D experimental data were reproduced across at least 3 iterations of the same experiment. For data in Figures 3A, 3B, 3D, and 3E, the experiments were performed on different days by author S.S.. Data presented in Figure 3F were replicated independently by author E.A. Data presented in Supplemental Figure 4 were performed by author B.A.M. In the absence of a technical problem with an experiment, data from replication experiments were always consistent with results from prior iterations of the experiments or included in the analyses as part of the data variance.
Randomization Randomization was not relevant to this study, and could not have been achieved. The reason randomization was not relevant to this project is because there was no treatment intervention involved in this study, and there were no in vivo models used in this study.

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