Age-dependent genetic regulation of osteoarthritis: independent effects of immune system genes

Abstract Objectives Osteoarthritis (OA) is a joint disease with a heritable component. Genetic loci identified via genome-wide association studies (GWAS) account for an estimated 26.3% of the disease trait variance in humans. Currently, there is no method for predicting the onset or progression of OA. We describe the first use of the Collaborative Cross (CC), a powerful genetic resource, to investigate knee OA in mice, with follow-up targeted multi-omics analysis of homologous regions of the human genome. Methods We histologically screened 275 mice for knee OA and conducted quantitative trait locus (QTL) mapping in the complete cohort (> 8 months) and the younger onset sub-cohort (8–12 months). Multi-omic analysis of human genetic datasets was conducted to investigate significant loci. Results We observed a range of OA phenotypes. QTL mapping identified a genome-wide significant locus on mouse chromosome 19 containing Glis3, the human equivalent of which has been identified as associated with OA in recent GWAS. Mapping the younger onset sub-cohort identified a genome-wide significant locus on chromosome 17. Multi-omic analysis of the homologous region of the human genome (6p21.32) indicated the presence of pleiotropic effects on the expression of the HLA − DPB2 gene and knee OA development risk, potentially mediated through the effects on DNA methylation. Conclusions The significant associations at the 6p21.32 locus in human datasets highlight the value of the CC model of spontaneous OA that we have developed and lend support for an immune role in the disease. Our results in mice also add to the accumulating evidence of a role for Glis3 in OA.摘要 ### 目的 骨关节炎（Osteoarthritis, OA）是一类具有遗传易感特征的关节疾病。据估算，通过全基因组关联研究（Genome-wide Association Study, GWAS）鉴定出的遗传位点可解释人类约26.3%的疾病性状方差。目前尚无有效手段可预测骨关节炎的发病或疾病进展。本研究首次利用协作杂交小鼠模型（Collaborative Cross, CC）这一强大的遗传资源库，探究小鼠膝关节骨关节炎，并针对人类基因组同源区域开展后续靶向多组学（multi-omics）分析。 ### 方法 我们对275只小鼠开展膝关节骨关节炎的组织学筛查，并在全队列（年龄＞8个月）及早发亚队列（8~12月龄）中开展数量性状位点（Quantitative Trait Locus, QTL）定位分析。同时对人类遗传数据集开展多组学（multi-omics）分析以鉴定显著关联位点。 ### 结果 本研究观察到多样化的骨关节炎表型。QTL定位分析在小鼠19号染色体上鉴定出一个全基因组显著关联位点，该区域包含Glis3基因，其人类同源基因在近期的GWAS研究中被证实与骨关节炎相关。针对早发亚队列的定位分析则在小鼠17号染色体上鉴定出另一个全基因组显著关联位点。对人类基因组同源区域（6p21.32）的多组学分析显示，该区域可通过调控DNA甲基化，对人类白细胞抗原（Human Leukocyte Antigen, HLA）-DPB2基因的表达产生多效性效应，并进而影响膝关节骨关节炎的发病风险。 ### 结论 人类数据集中共6p21.32位点的显著关联结果，凸显了本研究构建的自发性骨关节炎CC小鼠模型的应用价值，同时为免疫机制参与骨关节炎发病提供了实验依据。本研究在小鼠中的实验结果也进一步补充了Glis3参与骨关节炎发病的相关研究证据。