Multi-omics Integration Identifies Genes Influencing Traits Associated with Cardiovascular Risks: The Long Life Family Study.
Multi-omics Integration Identifies Genes Influencing Traits Associated with Cardiovascular Risks: The Long Life Family Study.
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多组学整合识别影响心血管风险相关特征的基因：长寿家庭研究。
DOI：
10.1101/2024.03.04.24303657
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发表时间：
2024
期刊：
影响因子：
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通讯作者：
Brent,MichaelR
中科院分区：
文献类型：
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作者：
Acharya,Sandeep;Liao,Shu;Jung,WooseokJ;Kang,YuS;Moghaddam,VahaA;Feitosa,Mary;Wojczynski,Mary;Lin,Shiow;Anema,JasonA;Schwander,Karen;Connell,JeffO;Province,Mike;Brent,MichaelR
长寿家庭研究(LLFS)招募了4953名参与者，他们来自539个表现出非凡长寿的家系。为了确定在LLFS人群中影响心血管风险的遗传机制，我们开发了一个多组学整合管道，并将其应用于11个与心血管风险相关的性状。使用我们的流水线，我们通过相关Meta分析(CMA)聚集了来自稀有变异分析、GWAS和基因表达-性状关联的基因水平统计数据。在所有性状中，中国心脏协会在Bonferroni校正后发现了的显著基因(p≤2.8x10−7)，其中29个基因在弗雷明翰心脏研究队列中重复。值得注意的是，在29个重复的基因中，有20个在50kb的GWAS目录中没有先前已知的与性状相关的变体。蛋白质-蛋白质相互作用(PPI)网络中的13个模块显著富含至少一个性状的低荟萃分析p值的基因，其中3个在FHS队列中重复。这些模块中基因的功能注释显示了与性状相关的生物学过程的显著过度表达，包括类固醇运输、蛋白质-脂肪复合体重构和免疫反应调节。在我们的主要发现中，我们的结果表明甘油三酯相关和肥大细胞功能基因FCER1A、MS4A2、GATA2、HDC和HRH4在动脉粥样硬化风险中发挥作用。我们的发现还表明，ATG2A的低表达可能既是肥胖的原因，也是肥胖的后果。我们发现ATG2A与BMI相关。最后，我们的结果表明，ENPP3可能在甘油三酯诱导的炎症中起中介作用。我们的流水线是免费提供的，并以NextFlow工作流语言实现，因此很容易在任何计算平台(https://nf-co.re/omicsgenetraitassociation).)上运行
The Long Life Family Study (LLFS) enrolled 4,953 participants in 539 pedigrees displaying exceptional longevity. To identify genetic mechanisms that affect cardiovascular risks in the LLFS population, we developed a multi-omics integration pipeline and applied it to 11 traits associated with cardiovascular risks. Using our pipeline, we aggregated gene-level statistics from rare-variant analysis, GWAS, and gene expression-trait association by Correlated Meta-Analysis (CMA). Across all traits, CMA identified 64 significant genes after Bonferroni correction (p ≤ 2.8×10−7), 29 of which replicated in the Framingham Heart Study (FHS) cohort. Notably, 20 of the 29 replicated genes do not have a previously known trait-associated variant in the GWAS Catalog within 50 kb. Thirteen modules in Protein-Protein Interaction (PPI) networks are significantly enriched in genes with low meta-analysis p-values for at least one trait, three of which are replicated in the FHS cohort. The functional annotation of genes in these modules showed a significant over-representation of trait-related biological processes including sterol transport, protein-lipid complex remodeling, and immune response regulation. Among major findings, our results suggest a role of triglyceride-associated and mast-cell functional genes FCER1A, MS4A2, GATA2, HDC, and HRH4 in atherosclerosis risks. Our findings also suggest that lower expression of ATG2A, a gene we found to be associated with BMI, may be both a cause and consequence of obesity. Finally, our results suggest that ENPP3 may play an intermediary role in triglyceride-induced inflammation. Our pipeline is freely available and implemented in the Nextflow workflow language, making it easily runnable on any compute platform (https://nf-co.re/omicsgenetraitassociation).