Trang Khanh B, Sharma Prabhat, Cook Laura, Mount Zachary, Thomas Rajan M, Kulkarni Nikhil N, Pahl Matthew C, Pippin James A, Su Chun, Kaestner Klaus H, O'Brien Joan M, Wagley Yadav, Hankenson Kurt D, Jermusyk Ashley, Hoskins Jason W, Amundadottir Laufey T, Xu Mai, Brown Kevin M, Anderson Stewart A, Yang Wenli, Titchenell Paul M, Seale Patrick, Zemel Babette S, Chesi Alessandra, Romberg Neil, Levings Megan K, Grant Struan F A, Wells Andrew D
Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
medRxiv. 2024 Aug 12:2024.08.12.24311676. doi: 10.1101/2024.08.12.24311676.
A portion of the genetic basis for many common autoimmune disorders has been uncovered by genome-wide association studies (GWAS), but GWAS do not reveal causal variants, effector genes, or the cell types impacted by disease-associated variation. We have generated 3D genomic datasets consisting of promoter-focused Capture-C, Hi-C, ATAC-seq, and RNA-seq and integrated these data with GWAS of 16 autoimmune traits to physically map disease-associated variants to the effector genes they likely regulate in 57 human cell types. These 3D maps of gene -regulatory architecture are highly powered to identify the cell types most likely impacted by disease-associated genetic variation compared to 1D genomic features, and tend to implicate different effector genes than eQTL approaches in the same cell types. Most of the variants implicated by these -regulatory architectures are highly trait-specific, but nearly half of the target genes connected to these variants are shared across multiple autoimmune disorders in multiple cell types, suggesting a high level of genetic diversity and complexity among autoimmune diseases that nonetheless converge at the level of target gene and cell type. Substantial effector gene sharing led to the common enrichment of similar biological networks across disease and cell types. However, trait-specific pathways representing potential areas for disease-specific intervention were identified. To test this, we pharmacologically validated squalene synthase, a cholesterol biosynthetic enzyme encoded by the gene implicated by our approach in MS and SLE, as a novel immunomodulatory drug target controlling inflammatory cytokine production by human T cells. These data represent a comprehensive resource for basic discovery of gene -regulatory mechanisms, and the analyses reported reveal mechanisms by which autoimmune-associated variants act to regulate gene expression, function, and pathology across multiple, distinct tissues and cell types.
全基因组关联研究(GWAS)已经揭示了许多常见自身免疫性疾病的部分遗传基础,但GWAS并未揭示因果变异、效应基因或受疾病相关变异影响的细胞类型。我们生成了由启动子聚焦的Capture-C、Hi-C、ATAC-seq和RNA-seq组成的三维基因组数据集,并将这些数据与16种自身免疫性状的GWAS整合,以便将疾病相关变异物理定位到它们可能在57种人类细胞类型中调控的效应基因上。与一维基因组特征相比,这些基因调控结构的三维图谱在识别最可能受疾病相关遗传变异影响的细胞类型方面具有强大的能力,并且在相同细胞类型中倾向于涉及与表达数量性状位点(eQTL)方法不同的效应基因。这些调控结构所涉及的大多数变异具有高度的性状特异性,但与这些变异相关的靶基因中近一半在多种细胞类型的多种自身免疫性疾病中是共享的,这表明自身免疫性疾病之间存在高度的遗传多样性和复杂性,尽管如此,它们在靶基因和细胞类型水平上存在汇聚。大量效应基因的共享导致了跨疾病和细胞类型的相似生物网络的共同富集。然而,也确定了代表疾病特异性干预潜在领域的性状特异性途径。为了验证这一点,我们通过药理学方法验证了角鲨烯合酶,一种由我们的方法在多发性硬化症(MS)和系统性红斑狼疮(SLE)中涉及的基因编码的胆固醇生物合成酶,作为一种控制人类T细胞炎性细胞因子产生的新型免疫调节药物靶点。这些数据代表了基因调控机制基础发现的综合资源,并且所报告的分析揭示了自身免疫相关变异在多个不同组织和细胞类型中调节基因表达、功能和病理的机制。