As open as possible, as closed as necessary: responsible sharing of multi-omics data in inherited cardiomyopathy

Open Research objectives/practices

• Making the outputs of research freely available
• Increasing the transparency of research processes and methodologies

Introduction

Inherited cardiomyopathies are rare diseases for which access to human tissue and disease-specific experimental models is limited. In our recent study of phospholamban (PLN) cardiomyopathy, we integrated proteomics and phosphoproteomics of explanted human myocardium with CRISPR-engineered human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), RNA sequencing, functional experiments and antisense oligonucleotide treatment.

As an Open Research practice, we created a freely accessible Zenodo repository containing the datasets that could responsibly be shared. These include replicate-level proteomic and phosphoproteomic measurements from our experimental cardiomyocyte models, complete differential proteomic and phosphoproteomic analyses, RNA-sequencing analyses, and data following antisense oligonucleotide treatment. This provides access to the underlying molecular data rather than only the statistically significant findings presented in the publication.

Not all data could ethically be made openly available. Individual-level molecular data from the explanted patient hearts were not deposited publicly. PLN R14del cardiomyopathy is a relatively rare inherited condition and our myocardial cohort was necessarily small. In combination with clinical characteristics reported in the publication, individual molecular profiles could create a risk of participant re-identification. We therefore followed the principle of making our research as open as possible and as closed as necessary.

Motivation

Our immediate motivation for formal data deposition was linked to publication and data-sharing requirements. However, preparing the datasets for public release highlighted a broader opportunity: data generated during a study can remain valuable well beyond the specific questions addressed in the resulting publication.

For the experimental component of our study, we saw little reason for other researchers to be restricted to the proteins, phosphorylation sites and pathways that we selected for presentation. By sharing the underlying data, including replicate-level measurements, researchers can independently reanalyse our results, investigate individual targets, compare our findings with other cardiovascular datasets and generate new hypotheses. This is particularly valuable for data-rich technologies such as phosphoproteomics, where a single dataset contains substantially more information than can be explored in one publication.

Open sharing also increases transparency and reproducibility. Other researchers can access the data underlying our conclusions and evaluate or reuse them without having to reproduce resource-intensive experiments. We hope this is particularly useful to researchers studying inherited cardiomyopathies, cardiac signalling and oligonucleotide therapeutics.

At the same time, this process changed our perspective on what responsible openness means in human research. The patients who donated myocardial tissue made an exceptionally valuable contribution, but maximizing data availability cannot take priority over their privacy. We therefore deliberately applied different levels of openness according to the nature of the data: experimental molecular datasets were made freely reusable, whereas potentially identifiable patient-level data remain protected.

Our experience demonstrates that Open Research does not necessarily mean making everything public. Instead, it means maximizing transparency, accessibility and reuse wherever possible while recognizing legitimate ethical boundaries. By openly sharing the data that can safely be shared, we aim to increase the value generated from our research and enable others to build upon it.

URLs, references and further information

• Open Zenodo repository: https://zenodo.org/records/18602605
  The repository contains open proteomics, phosphoproteomics and RNA-sequencing datasets associated with the study, including replicate-level experimental data.
• Associated open-access publication: https://www.nature.com/articles/s41392-026-02791-5
  Deiman FE et al. Phosphoproteomics distinguishes disease-specific mechanisms for human phospholamban cardiomyopathy reversible by RNA therapy. Signal Transduction and Targeted Therapy. 2026;11:199.