美国麻省理工学院和哈佛大学布罗德研究所Patrick T. Ellinor团队近期取得重要工作进展，他们研究分析了跨生物库和祖先的人类疾病罕见编码变异。相关研究成果2024年8月29日在线发表于《自然—遗传学》杂志上。

据介绍，大规模测序为研究罕见编码变异在人类表型变异中的作用提供空前的机会。

研究人员对来自三个大型生物库的测序数据进行了泛血统分析，包括All of Us研究项目。使用混合效应模型，研究人员对748879人的601种疾病进行了基于基因的罕见变异检测，其中包括155236名与欧洲人血统不同的人。

研究确定了363个显著关联，突出了人类疾病现象的核心基因，并确定了潜在的新关联，包括心脏代谢疾病的UBR3和精神疾病的YLPM1。泛血统负担测试代表了一种在不同数据集中发现的包容性和有用的方法，尽管研究人员也强调了血统特异性敏感性分析在这种情况下的重要性。

最后，研究人员表明，在与欧洲血统和其他遗传祖先相似的样本中，罕见蛋白质破坏变体的效应大小是一致的（β_Deming = 0.7-1.0）。

总之，这一研究结果对人类疾病测序关联研究中的多血统和跨生物库方法具有重要意义。

附：英文原文

Title: Rare coding variant analysis for human diseases across biobanks and ancestries

Author: Jurgens, Sean J., Wang, Xin, Choi, Seung Hoan, Weng, Lu-Chen, Koyama, Satoshi, Pirruccello, James P., Nguyen, Trang, Smadbeck, Patrick, Jang, Dongkeun, Chaffin, Mark, Walsh, Roddy, Roselli, Carolina, Elliott, Amanda L., Wijdeveld, Leonoor F. J. M., Biddinger, Kiran J., Kany, Shinwan, Rm, Joel T., Natarajan, Pradeep, Aragam, Krishna G., Flannick, Jason, Burtt, Nol P., Bezzina, Connie R., Lubitz, Steven A., Lunetta, Kathryn L., Ellinor, Patrick T.

Issue&Volume: 2024-08-29

Abstract: Large-scale sequencing has enabled unparalleled opportunities to investigate the role of rare coding variation in human phenotypic variability. Here, we present a pan-ancestry analysis of sequencing data from three large biobanks, including the All of Us research program. Using mixed-effects models, we performed gene-based rare variant testing for 601 diseases across 748,879 individuals, including 155,236 with ancestry dissimilar to European. We identified 363 significant associations, which highlighted core genes for the human disease phenome and identified potential novel associations, including UBR3 for cardiometabolic disease and YLPM1 for psychiatric disease. Pan-ancestry burden testing represented an inclusive and useful approach for discovery in diverse datasets, although we also highlight the importance of ancestry-specific sensitivity analyses in this setting. Finally, we found that effect sizes for rare protein-disrupting variants were concordant between samples similar to European ancestry and other genetic ancestries (βDeming=0.7–1.0). Our results have implications for multi-ancestry and cross-biobank approaches in sequencing association studies for human disease.

DOI: 10.1038/s41588-024-01894-5

Source: https://www.nature.com/articles/s41588-024-01894-5