Curriculum in Genetics and Molecular Biology, University of North Carolina, Chapel Hill, NC 27599, USA.
Curriculum in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, NC 27599, USA.
Genetics. 2022 Nov 30;222(4). doi: 10.1093/genetics/iyac141.
Genome-wide association studies have identified over 100 loci associated with osteoarthritis risk, but the majority of osteoarthritis risk variants are noncoding, making it difficult to identify the impacted genes for further study and therapeutic development. To address this need, we used a multiomic approach and genome editing to identify and functionally characterize potential osteoarthritis risk genes. Computational analysis of genome-wide association studies and ChIP-seq data revealed that chondrocyte regulatory loci are enriched for osteoarthritis risk variants. We constructed a chondrocyte-specific regulatory network by mapping 3D chromatin structure and active enhancers in human chondrocytes. We then intersected these data with our previously collected RNA-seq dataset of chondrocytes responding to fibronectin fragment, a known osteoarthritis trigger. Integration of the 3 genomic datasets with recently reported osteoarthritis genome-wide association study variants revealed a refined set of putative causal osteoarthritis variants and their potential target genes. One of the putative target genes identified was SOCS2, which was connected to a putative causal variant by a 170-kb loop and is differentially regulated in response to fibronectin fragment. CRISPR-Cas9-mediated deletion of SOCS2 in primary human chondrocytes from 3 independent donors led to heightened expression of inflammatory markers after fibronectin fragment treatment. These data suggest that SOCS2 plays a role in resolving inflammation in response to cartilage matrix damage and provides a possible mechanistic explanation for its influence on osteoarthritis risk. In total, we identified 56 unique putative osteoarthritis risk genes for further research and potential therapeutic development.
全基因组关联研究已经确定了 100 多个与骨关节炎风险相关的基因位点，但大多数骨关节炎风险变异是无编码的，这使得确定受影响的基因进行进一步研究和治疗开发变得困难。为了解决这一需求，我们使用多组学方法和基因组编辑来识别和功能表征潜在的骨关节炎风险基因。对全基因组关联研究和 ChIP-seq 数据的计算分析表明，软骨细胞调节基因座富含骨关节炎风险变异。我们通过绘制人类软骨细胞的 3D 染色质结构和活性增强子，构建了一个软骨细胞特异性调节网络。然后，我们将这些数据与我们之前收集的软骨细胞对纤维连接蛋白片段反应的 RNA-seq 数据集进行了交叉分析，纤维连接蛋白片段是一种已知的骨关节炎触发物。将这 3 个基因组数据集与最近报道的骨关节炎全基因组关联研究变异体进行整合，揭示了一组经过精炼的潜在因果骨关节炎变异体及其潜在的靶基因。鉴定出的一个潜在靶基因是 SOCS2，它通过一个 170kb 的环与一个潜在的因果变异体相连，并且对纤维连接蛋白片段的反应是不同调节的。CRISPR-Cas9 介导的 3 个独立供体的原代人软骨细胞中的 SOCS2 缺失导致纤维连接蛋白片段处理后炎症标志物的表达升高。这些数据表明 SOCS2 在响应软骨基质损伤时发挥作用，有助于解决炎症，并为其对骨关节炎风险的影响提供了可能的机制解释。总的来说，我们确定了 56 个独特的潜在骨关节炎风险基因，以进行进一步的研究和潜在的治疗开发。
