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对撒哈拉以南非洲研究的荟萃分析提供了对脂质特征遗传结构的深入了解。

Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits.

机构信息

Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.

South African Medical Research Council/University of the Witwatersrand Developmental Pathways for Health Research Unit, Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.

出版信息

Nat Commun. 2022 May 11;13(1):2578. doi: 10.1038/s41467-022-30098-w.

Abstract

Genetic associations for lipid traits have identified hundreds of variants with clear differences across European, Asian and African studies. Based on a sub-Saharan-African GWAS for lipid traits in the population cross-sectional AWI-Gen cohort (N = 10,603) we report a novel LDL-C association in the GATB region (P-value=1.56 × 10). Meta-analysis with four other African cohorts (N = 23,718) provides supporting evidence for the LDL-C association with the GATB/FHIP1A region and identifies a novel triglyceride association signal close to the FHIT gene (P-value =2.66 × 10). Our data enable fine-mapping of several well-known lipid-trait loci including LDLR, PMFBP1 and LPA. The transferability of signals detected in two large global studies (GLGC and PAGE) consistently improves with an increase in the size of the African replication cohort. Polygenic risk score analysis shows increased predictive accuracy for LDL-C levels with the narrowing of genetic distance between the discovery dataset and our cohort. Novel discovery is enhanced with the inclusion of African data.

摘要

脂质特征的遗传关联已经确定了数百个变体,这些变体在欧洲、亚洲和非洲的研究中存在明显差异。基于对人群横断面 AWI-Gen 队列(N=10603)中脂质特征的撒哈拉以南非洲 GWAS,我们在 GATB 区域报告了一个新的 LDL-C 关联(P 值=1.56×10)。与其他四个非洲队列(N=23718)的荟萃分析为 GATB/FHIP1A 区域的 LDL-C 关联提供了支持证据,并确定了 FHIT 基因附近的一个新的甘油三酯关联信号(P 值=2.66×10)。我们的数据使包括 LDLR、PMFBP1 和 LPA 在内的几个著名脂质特征基因座的精细映射成为可能。在两个大型全球研究(GLGC 和 PAGE)中检测到的信号的可转移性随着非洲复制队列规模的增加而持续提高。多基因风险评分分析表明,随着发现数据集和我们队列之间遗传距离的缩小,LDL-C 水平的预测准确性提高。纳入非洲数据可增强新的发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bfa3/9095599/ca4577874589/41467_2022_30098_Fig1_HTML.jpg

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