Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations.
Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations.
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DOI：
10.1111/jth.15698
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发表时间：
2022-06
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遗传相关表型的多表型分析可以提高检测与多个性状相关的基因座的统计能力，从而发现新的基因座。这是迄今为止第一个全面分析不同止血特征中共同的遗传效应以及这些特征及其相关疾病结局之间的研究。结合相关止血特征和疾病事件的汇总数据，发现新的遗传关联。基因组全关联研究（GWAS）的汇总统计数据来自7个止血性状（因子VII [FVII]、因子VIII [FVIII]、血管性血液病因子[VWF]因子XI [FXI]、纤维蛋白原、组织纤溶酶原激活剂[tPA]、纤溶酶原激活剂抑制剂1 [PAI - 1]）和3个主要心血管事件（静脉血栓栓塞[VTE]、冠状动脉疾病[CAD]、缺血性卒中[IS]）的27个多性状联合使用meta - usat。使用连锁不平衡评分回归（LDSC）计算表型之间的遗传相关性。研究了新的相关位点的共定位。我们考虑在对进行的多性状组合数量进行Bonferroni校正后获得的显著性阈值为1.85 × 10−9 （n = 27）。在27个多性状分析中，我们发现了4个新的多性状位点（XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL），这些位点在原始的个体数据集中不显著，在以前的个体性状GWAS中没有描述，并且在所研究的表型之间表现出共同的相关变异。四个新基因座的发现有助于理解止血和心血管事件之间的关系，并阐明这些特征之间的共同遗传因素。
Multi‐phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Summary statistics from genome wide‐association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI‐1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi‐trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10−9 obtained after applying Bonferroni correction for the number of multi‐trait combinations performed (n = 27). Across the 27 multi‐trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits.
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影响因子：
3.7
作者：
Brunel H;Massanet R;Martinez-Perez A;Ziyatdinov A;Martin-Fernandez L;Souto JC;Perera A;Soria JM
通讯作者：
Soria JM
影响因子：
120.7
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通讯作者：
DAGOSTINO, RB
影响因子：
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通讯作者：
Neale, Benjamin M.
影响因子：
14.9
作者：
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通讯作者：
Parkinson, Helen
影响因子：
4
作者：
Bot C;Pfeiffer A;Giordano F;Manjeera DE;Dantuma NP;Ström L
通讯作者：
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