Genomic Data Privacy in the Era of Decentralised Systems

Decentralised systems such as distributed ledger technology (DLT) offer promising opportunities for addressing the significant concern of genomic data privacy in the era of affordable genomic sequencing. By empowering individuals with greater control over their data ownership and enhancing data security through its tamper proof nature, DLT can establish a trusted and secure data ecosystem that promotes efficient and effective genomic research.

Genomic data privacy is a significant concern in the era of rapid and affordable genomic sequencing [1]. Millions, if not billions, of people’s genomes may be sequenced in the near future and aggregation of such datasets pose risks of unauthorised access and re-identification leading to privacy concerns [2]. Decentralised systems, such as distributed ledger technology (DLT), offer a solution to address these risks [3].

DLT includes technologies like blockchain, hash graphs, and directed acyclic graphs (DAGs). They use digital signatures to create a transparent and auditable record of data across a network of nodes or peers and unlike traditional systems, DLT does not rely on a central authority to manage data but requires consensus among peers to approve any data changes. This enables DLT to be immutable, tamper-proof, and traceable providing significant advantages for protecting genomic data.

  • DLT empowers individuals with greater control over their data ownership as all informed consent states for an individual's data use are stored on the ledger, consent can be provided or revoked on their terms.
  • DLT can be implemented to comply with GDPR and HIPPA's right-to-erasure guidelines by storing only the metadata on the ledger while the genomic data are stored using decentralised solutions such as IPFS, and StorJ.
  • DLT facilitates secure data sharing through encryption and smart contracts, enforcing rules and permissions for data access and use.

Furthermore, the use of verifiable signatures based on decentralised identity frameworks, such as the Self-Soverign Identity SSI), can provide an additional layer of security for genomic data. These frameworks enable only authorised users with valid signatures to access the data, while also allowing individuals to choose which parts of their personal data to share with whom. This minimises the risks of data breaches and unauthorized access, creating a secure platform for genomic data storage and sharing [4].

There are challenges that decentralised systems face particular to genomics including:

  • User adoption can be a key hurdle due to low awareness and high anxiety towards new technologies in healthcare and sensitive data.
  • User-friendliness for both individuals and researchers as current systems can be complex thereby hindering adoption.
  • Interoperability between different DLT platforms is currently limited, although initiatives like the Hyperledger platform developed by the Linux Foundation show promise in addressing this issue.
  • Security of smart contracts, self-executing software on the ledger, show increasing vulnerabilites and potential privacy breaches.
  • Scalability of computing resource requirements and power consumption as the number of users increases

In conclusion, decentralised systems like DLT and SSI are promising opportunities to create a more cooperative and inclusive environment for genomic research. Although challenges such as data interoperability and adoption need to be addressed, decentralised systems can establish a trusted and secure data ecosystem that promotes efficient and effective genomic research. By enabling the secure sharing of data from various sources while maintaining individuals' data sovereignty, decentralised systems have the potential to benefit both researchers and individuals who contribute their data, ultimately advancing our understanding of genomics and improving health outcomes.

References

Malakar et al. Balancing the safeguarding of privacy and data sharing: perceptions of genomic professionals on patient genomic data ownership in Australia 2023. DOI: 10.1038/s41431-022-01273-w.
Wan et al. Sociotechnical safeguards for genomic data privacy. Nature Reviews Genetics 2022. DOI: 10.1038/s41576-022-00455-y.
Alghazwi et al. Blockchain for genomics: a systematic literature review. Procedia Computer Science 2022. DOI: 10.1145/3563044.
Gürsoy et al. Using blockchain to log genome dataset access: efficient storage and query. BMC Medical Genomics 2022. DOI: 10.1186/s12920-020-0716-z.