A methodology for gene level omics-WAS integration identifies genes influencing traits associated with cardiovascular risks: the Long Life Family Study

IF 3.8 2区生物学 Q2 GENETICS & HEREDITY

Human Genetics Pub Date : 2024-09-14 DOI:10.1007/s00439-024-02701-1

Sandeep Acharya, Shu Liao, Wooseok J. Jung, Yu S. Kang, Vaha Akbary Moghaddam, Mary F. Feitosa, Mary K. Wojczynski, Shiow Lin, Jason A. Anema, Karen Schwander, Jeff O. Connell, Michael A. Province, Michael R. Brent

{"title":"A methodology for gene level omics-WAS integration identifies genes influencing traits associated with cardiovascular risks: the Long Life Family Study","authors":"Sandeep Acharya, Shu Liao, Wooseok J. Jung, Yu S. Kang, Vaha Akbary Moghaddam, Mary F. Feitosa, Mary K. Wojczynski, Shiow Lin, Jason A. Anema, Karen Schwander, Jeff O. Connell, Michael A. Province, Michael R. Brent","doi":"10.1007/s00439-024-02701-1","DOIUrl":null,"url":null,"abstract":"The Long Life Family Study (LLFS) enrolled 4953 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).","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":"15 1","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s00439-024-02701-1","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}

引用次数: 0

Abstract

The Long Life Family Study (LLFS) enrolled 4953 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).

Abstract Image

查看原文本刊更多论文

基因水平 omics-WAS 整合方法识别影响心血管风险相关特征的基因：长寿家族研究

长寿家族研究（LLFS）招募了 539 个血统中的 4953 名参与者，这些血统都具有超长寿命。为了确定影响 LLFS 群体心血管风险的遗传机制，我们开发了一个多组学整合管道，并将其应用于与心血管风险相关的 11 个性状。利用我们的管道，我们通过相关元分析（CMA）汇总了来自罕见变异分析、全球基因组研究和基因表达与性状关联的基因水平统计数据。在所有性状中，经过 Bonferroni 校正（p ≤ 2.8 × 10-7）后，CMA 发现了 64 个显著基因，其中 29 个基因在弗雷明汉心脏研究（FHS）队列中得到了复制。值得注意的是，在这 29 个重复的基因中，有 20 个基因在 50 kb 范围内的 GWAS 目录中没有先前已知的性状相关变异。蛋白质-蛋白质相互作用（PPI）网络中的 13 个模块在至少一个性状的荟萃分析 p 值较低的基因中显著富集，其中 3 个模块在 FHS 队列中得到了复制。对这些模块中基因的功能注释显示，与性状相关的生物过程（包括固醇转运、蛋白-脂质复合物重塑和免疫反应调控）的代表性明显偏高。在主要发现中，我们的结果表明甘油三酯相关基因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的作用。我们的研究结果还表明，我们发现与体重指数（BMI）相关的基因 ATG2A 表达较低，这可能既是肥胖的原因，也是肥胖的结果。最后，我们的研究结果表明，ENPP3 可能在甘油三酯诱导的炎症中扮演中间角色。我们的管道是免费提供的，并用 Nextflow 工作流语言实现，因此可以在任何计算平台上轻松运行 (https://nf-co.re/omicsgenetraitassociation)。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Human Genetics 生物-遗传学

CiteScore

10.80

自引率

3.80%

发文量

审稿时长

1 months

期刊介绍： Human Genetics is a monthly journal publishing original and timely articles on all aspects of human genetics. The Journal particularly welcomes articles in the areas of Behavioral genetics, Bioinformatics, Cancer genetics and genomics, Cytogenetics, Developmental genetics, Disease association studies, Dysmorphology, ELSI (ethical, legal and social issues), Evolutionary genetics, Gene expression, Gene structure and organization, Genetics of complex diseases and epistatic interactions, Genetic epidemiology, Genome biology, Genome structure and organization, Genotype-phenotype relationships, Human Genomics, Immunogenetics and genomics, Linkage analysis and genetic mapping, Methods in Statistical Genetics, Molecular diagnostics, Mutation detection and analysis, Neurogenetics, Physical mapping and Population Genetics. Articles reporting animal models relevant to human biology or disease are also welcome. Preference will be given to those articles which address clinically relevant questions or which provide new insights into human biology. Unless reporting entirely novel and unusual aspects of a topic, clinical case reports, cytogenetic case reports, papers on descriptive population genetics, articles dealing with the frequency of polymorphisms or additional mutations within genes in which numerous lesions have already been described, and papers that report meta-analyses of previously published datasets will normally not be accepted. The Journal typically will not consider for publication manuscripts that report merely the isolation, map position, structure, and tissue expression profile of a gene of unknown function unless the gene is of particular interest or is a candidate gene involved in a human trait or disorder.