National Cancer Institute, NIH, Bethesda, MD, 20892, USA.
Altius Institute for Biomedical Sciences, Seattle, WA, 98121, USA.
Genome Biol. 2022 Jan 7;23(1):13. doi: 10.1186/s13059-021-02560-3.
Genome-wide association study (GWAS) single nucleotide polymorphisms (SNPs) are known to preferentially co-locate to active regulatory elements in tissues and cell types relevant to disease aetiology. Further characterisation of associated cell type-specific regulation can broaden our understanding of how GWAS signals may contribute to disease risk.
To gain insight into potential functional mechanisms underlying GWAS associations, we developed FORGE2 ( https://forge2.altiusinstitute.org/ ), which is an updated version of the FORGE web tool. FORGE2 uses an expanded atlas of cell type-specific regulatory element annotations, including DNase I hotspots, five histone mark categories and 15 hidden Markov model (HMM) chromatin states, to identify tissue- and cell type-specific signals. An analysis of 3,604 GWAS from the NHGRI-EBI GWAS catalogue yielded at least one significant disease/trait-tissue association for 2,057 GWAS, including > 400 associations specific to epigenomic marks in immune tissues and cell types, > 30 associations specific to heart tissue, and > 60 associations specific to brain tissue, highlighting the key potential of tissue- and cell type-specific regulatory elements. Importantly, we demonstrate that FORGE2 analysis can separate previously observed accessible chromatin enrichments into different chromatin states, such as enhancers or active transcription start sites, providing a greater understanding of underlying regulatory mechanisms. Interestingly, tissue-specific enrichments for repressive chromatin states and histone marks were also detected, suggesting a role for tissue-specific repressed regions in GWAS-mediated disease aetiology.
In summary, we demonstrate that FORGE2 has the potential to uncover previously unreported disease-tissue associations and identify new candidate mechanisms. FORGE2 is a transparent, user-friendly web tool for the integrative analysis of loci discovered from GWAS.
全基因组关联研究(GWAS)单核苷酸多态性(SNP)已知优先位于与疾病发病机制相关的组织和细胞类型的活跃调控元件附近。进一步描述相关的细胞类型特异性调控作用,可以拓宽我们对 GWAS 信号如何可能导致疾病风险的理解。
为了深入了解 GWAS 关联背后的潜在功能机制,我们开发了 FORGE2(https://forge2.altiusinstitute.org/),这是 FORGE 网络工具的更新版本。FORGE2 使用扩展的细胞类型特异性调控元件注释图谱,包括 DNase I 热点、五种组蛋白标记类别和 15 个隐马尔可夫模型(HMM)染色质状态,来识别组织和细胞类型特异性信号。对 NHGRI-EBI GWAS 目录中的 3604 项 GWAS 进行的分析,至少有 2057 项 GWAS 与一种疾病/特征组织具有显著关联,其中包括 400 多项与免疫组织和细胞类型中的表观遗传标记特异性相关的关联、30 多项与心脏组织特异性相关的关联,以及 60 多项与大脑组织特异性相关的关联,突出了组织和细胞类型特异性调控元件的关键潜力。重要的是,我们证明 FORGE2 分析可以将先前观察到的可及染色质富集分为不同的染色质状态,例如增强子或活跃的转录起始位点,从而更深入地了解潜在的调控机制。有趣的是,还检测到组织特异性的抑制性染色质状态和组蛋白标记的富集,这表明组织特异性抑制区域在 GWAS 介导的疾病发病机制中可能发挥作用。
总之,我们证明 FORGE2 有可能揭示以前未报告的疾病-组织关联,并确定新的候选机制。FORGE2 是一个透明、用户友好的网络工具,用于整合 GWAS 发现的基因座分析。