Elhussein, Ahmed, Baymuradov, Ulugbek, NYGC ALS Consortium, Elhadad, Noémie, Natarajan, Karthik, Gürsoy, Gamze (September 2024) A framework for sharing of clinical and genetic data for precision medicine applications. Nature Medicine. ISSN 1078-8956 (Public Dataset)
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Abstract
Precision medicine has the potential to provide more accurate diagnosis, appropriate treatment and timely prevention strategies by considering patients' biological makeup. However, this cannot be realized without integrating clinical and omics data in a data-sharing framework that achieves large sample sizes. Systems that integrate clinical and genetic data from multiple sources are scarce due to their distinct data types, interoperability, security and data ownership issues. Here we present a secure framework that allows immutable storage, querying and analysis of clinical and genetic data using blockchain technology. Our platform allows clinical and genetic data to be harmonized by combining them under a unified framework. It supports combined genotype-phenotype queries and analysis, gives institutions control of their data and provides immutable user access logs, improving transparency into how and when health information is used. We demonstrate the value of our framework for precision medicine by creating genotype-phenotype cohorts and examining relationships within them. We show that combining data across institutions using our secure platform increases statistical power for rare disease analysis. By offering an integrated, secure and decentralized framework, we aim to enhance reproducibility and encourage broader participation from communities and patients in data sharing.
| Item Type: | Paper |
|---|---|
| Subjects: | bioinformatics bioinformatics > genomics and proteomics > genetics & nucleic acid processing bioinformatics > genomics and proteomics |
| CSHL Authors: | |
| Communities: | CSHL labs > Hammell M. lab |
| SWORD Depositor: | CSHL Elements |
| Depositing User: | CSHL Elements |
| Date: | 3 September 2024 |
| Date Deposited: | 16 Sep 2024 18:25 |
| Last Modified: | 16 Sep 2024 18:25 |
| Related URLs: | |
| Dataset ID: |
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| URI: | https://repository.cshl.edu/id/eprint/41669 |
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