期刊
NATURE COMMUNICATIONS
卷 12, 期 1, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41467-021-21049-y
关键词
-
资金
- National Key Research and Development Program of China [2017YFC0909001]
- HKU Postgraduate Scholarships
- Edward and Yolanda Wong Fund
- National Natural Science Foundation of China [81970450, 81801636]
- Science and Technology Project of Guangzhou [201903010074]
- Research Grant Council of Hong Kong [GRF 17146616,17106320]
- Hong Kong PhD fellowship scheme (HKPF)
- World Cancer Research Fund (WCRF)
The study revealed genetic differences in SLE among ancestral groups and identified ancestry-specific susceptibility loci, with better risk prediction using matched ancestral data.
Systemic lupus erythematosus (SLE), a worldwide autoimmune disease with high heritability, shows differences in prevalence, severity and age of onset among different ancestral groups. Previous genetic studies have focused more on European populations, which appear to be the least affected. Consequently, the genetic variations that underlie the commonalities, differences and treatment options in SLE among ancestral groups have not been well elucidated. To address this, we undertake a genome-wide association study, increasing the sample size of Chinese populations to the level of existing European studies. Thirty-eight novel SLE-associated loci and incomplete sharing of genetic architecture are identified. In addition to the human leukocyte antigen (HLA) region, nine disease loci show clear ancestral differences and implicate antibody production as a potential mechanism for differences in disease manifestation. Polygenic risk scores perform significantly better when trained on ancestry-matched data sets. These analyses help to reveal the genetic basis for disparities in SLE among ancestral groups. The presentation of systemic lupus erythematosus has been known to differ by ancestry, but the underlying genetic factors remain unclear. Here, the authors report ancestry-specific susceptibility loci and better risk prediction when using data from matched ancestral groups.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据