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PMID: 40886259 已发表 · ppublish 英语

BRCA-CN: a blockchain-based framework to support public variant databases sharing in multi-center community for diagnostic reference and China regulatory science.

Human genetics ·第 144 卷 ·第 8 期 ·2025-08-00

Qu S, Liu R, Li S, Huang C, Zhang Y, Gao X, Dai P, Xu C, Yang R, Li X, Ouyang G, Shao K, Chang X, Mu F, Yang M, Huang J

摘要

High-quality, regulatory-grade databases for precise genetic variant interpretation are critically needed for Chinese populations, where existing fragmented databases impede clinical effectiveness evaluations. We developed BRCA-CN, a consortium blockchain-based governance framework specifically designed for BRCA gene variant interpretation in Chinese populations. Our framework compiled 66,485 variants from 6,031 samples across six Chinese laboratories. A 15-expert panel conducted systematic variant curation using unified interpretation standards based on ACMG/AMP guidelines. Smart contracts ensured data integrity and accountability throughout the consensus process. After deduplication, we established a comprehensive database of 950 unique variants (BRCA1: 365, BRCA2: 585), completing consensus reviews for 607 sites with 462 achieving definitive interpretations. Comparison with ClinVar revealed 83.6% concordance, with AI validation (PrimateAI, REVEL, EVE) confirming high interpretation accuracy. The blockchain framework successfully enabled secure cross-institutional collaboration while maintaining data sovereignty and regulatory compliance. BRCA-CN demonstrates the transformative potential of blockchain technology in genomic medicine, addressing critical challenges in data sharing, standardization, and regulatory oversight. This framework provides a robust foundation for clinical decision-making and establishes a replicable model for population-specific genomic databases. Access to the BRCA-CN portal, user guides, and test data is provided in the supplementary materials, available at: https://oxygen-chamber.mgi-tech.com/sdb2.

文献信息
期刊
Human genetics
期刊简称
Hum Genet
ISSN
1432-1203
发表日期
2025-08-00
语言
英语
国家/地区
Germany
NLM ID
7613873
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