Safe Utilization and Sharing of Genomic Data: Amendment to the Health and Medical Data Utilization Guidelines of South Korea
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Purpose In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration Number: 11-1352000-0052828-14). This study aimed to show the overall impact of the guideline revision, with a focus on clinical genomic data. Materials and Methods This study amended the pseudonymization of genomic data defined in the previous version through a joint study led by the Ministry of Health and Welfare, the Korea Health Information Service, and the Korea Genome Organization. To develop the previous version, we held three conferences with four main medical research institutes and seven academic societies. We conducted two surveys targeting special genome experts in academia, industry, and institutes. Results We found that cases of pseudonymization in the application of genome data were rare and that there was ambiguity in the terminology used in the previous version of the guidelines. Most experts (>~90%) agreed that the ‘reserved’ condition should be eliminated to make genomic data available after pseudonymization. In this study, the scope of genomic data was defined as clinical next-generation sequencing data, including FASTQ, BAM/SAM, VCF, and medical records. Pseudonymization targets genomic sequences and metadata, embedding specific elements, such as germline mutations, short tandem repeats, single-nucleotide polymorphisms, and identifiable data (for example, ID or environmental values). Expression data generated from multi-omics can be used without pseudonymization. Conclusion This amendment will not only enhance the safe use of healthcare data but also promote advancements in disease prevention, diagnosis, and treatment.
Abstract
Purpose In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration Number: 11-1352000-0052828-14). This study aimed to show the overall impact of the guideline revision, with a focus on clinical genomic data. Materials and Methods This study amended the pseudonymization of genomic data defined in the previous version through a joint study led by the Ministry of Health and Welfare, the Korea Health Information Service, and the Korea Genome Organization. To develop the previous version, we held three conferences with four main medical research institutes and seven academic societies. We conducted two surveys targeting special genome experts in academia, industry, and institutes. Results We found that cases of pseudonymization in the application of genome data were rare and that there was ambiguity in the terminology used in the previous version of the guidelines. Most experts (>~90%) agreed that the ‘reserved’ condition should be eliminated to make genomic data available after pseudonymization. In this study, the scope of genomic data was defined as clinical next-generation sequencing data, including FASTQ, BAM/SAM, VCF, and medical records. Pseudonymization targets genomic sequences and metadata, embedding specific elements, such as germline mutations, short tandem repeats, single-nucleotide polymorphisms, and identifiable data (for example, ID or environmental values). Expression data generated from multi-omics can be used without pseudonymization. Conclusion This amendment will not only enhance the safe use of healthcare data but also promote advancements in disease prevention, diagnosis, and treatment.
참고문헌 (24)
- "Genomics market (by product and service: systems & software, consumables, services; by technology: sequencing,microarray, PCR, nucleic acid extraction and purification andothers; by application: diagnostic application, drug discovery and development, agriculture and medical research andprecision medicine and other; by end user: research institute,hospital and clinic, and others) - global industry analysis,size, share, growth, regional outlook and forecast 2023 to 2032" (2023)[URL]
- Ramirez AH, "Progress with the All ofUs Research Program : opening access for researchers", JAMA, 325, pp.2441~2442 (2021)
- All of Us Research Program Investigators, "The"All ofUs"Research Program", N Engl J Med, 381, pp.668~676 (2019)
- Ramirez AH, "The All of Us Research Program : dataquality, utility, and diversity", Patterns(N Y), 3, pp.100570~ (2022)
- Bycroft C, "The UK Biobank resource with deep phenotyping andgenomic data", Nature, 562, pp.203~209 (2018)
- Collins R, "What makes UK Biobank special?", Lancet, 379, pp.1173~1174 (2012)
- Littlejohns TJ, "The UK Biobank imaging enhancement of 100, 000 participants : rationale, data collection, management and future directions", Nat Commun, 11, pp.2624~ (2020)
- Lee B, "Introduction of the Korea BioData Station(K-BDS)for sharing biological data", Genomics Inform, 21, pp.e12~ (2023)
- Kim YJ, "The contribution of common and rare genetic variants to variation in metabolic traits in 288, 137 East Asians", Nat Commun, 13, pp.6642~ (2022)
- Kim Y, "Cohort profile : the KoreanGenome and Epidemiology Study(KoGES)Consortium", Int JEpidemiol, 46, pp.e20~ (2017)
- Jeon Y, "Welfare genome project : a participatory Korean Personal Genome Project with free health check-up and genetic report followed by counseling", Front Genet, 12, pp.633731~ (2021)
- "Enforcement Rule of Bioethics and Safety Act" (2023)[URL]
- Edge MD, "Linkage disequilibrium matches forensic genetic records to disjoint genomic marker sets", Proc Natl Acad Sci U S A, 114, pp.5671~5676 (2017)
- Carter AB, "Considerations for genomic data privacy and security when working in the cloud", J Mol Diagn, 21, pp.542~552 (2019)
- Phillips C, "Ancestry analysis in the 11-M Madridbomb attack investigation", PLoS One, 4, pp.e6583~ (2009)
- Sanchez JJ, "A multiplex assay with 52 single nucleotidepolymorphisms for human identification", Electrophoresis, 27, pp.1713~1724 (2006)
- Pakstis AJ, "SNPs for a universal individual identification panel", Hum Genet, 127, pp.315~324 (2010)
- Li H, "Fast and accurate short read alignment withBurrows-Wheeler transform", Bioinformatics, 25, pp.1754~1760 (2009)
- McKenna A, "The Genome Analysis Toolkit : a MapReduce framework for analyzing next-generation DNA sequencing data", Genome Res, 20, pp.1297~1303 (2010)
- Li H, "The Sequence Alignment", Map format and SAMtools, 2009, pp.25, 2078~2079
- Jeon S, "Korea4K : whole genome sequences of 4, 157 Koreans with 107 phenotypes derived from extensive health check-ups", Gigascience, 13, pp.giae014~ (2024)
- Kuo TT, "iDASHsecure genome analysis competition 2018 : blockchain genomic data access logging, homomorphic encryption on GWAS, and DNA segment searching", BMC Med Genomics, 13(Suppl 7), pp.98~ (2020)
- Raisaro JL, "Protecting privacy and security ofgenomic data in i2b2 with homomorphic encryption and differential privacy", IEEE, 2018, pp.15, 1413~1426
