Bentvelzen Mieke L M, Welsing Paco M J, Moingeon Philippe, Mastbergen Simon C, Kloppenburg Margreet, Blanco Francisco J, Haugen Ida K, Berenbaum Francis, Uh Hae-Won, Jansen Mylène P, El Bouhaddani Said
Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.
University Paris Saclay, UFR Pharmacy, Saclay France.
PLoS One. 2025 Jun 24;20(6):e0325819. doi: 10.1371/journal.pone.0325819. eCollection 2025.
Knee osteoarthritis (OA) is a heterogeneous disease with different endotypes and phenotypes, resulting in patients' varying clinical and structural progression. Several genomic markers have been associated with knee OA presence. This study aimed to find new associations of these genetic markers with knee OA progression and to investigate the risk of knee OA progression using a polygenic risk score (PRS).
Data from knee OA patients (n = 297) from the IMI-APPROACH cohort with detailed measurements on disease progression were used. Knee OA progression definitions were based on the decrease in minimum joint space width in mm (minJSW; primary outcome), increase in pain on the Knee injury and Osteoarthritis Outcome Score (KOOS), and presence of radiographic OA (based on the Kellgren-Lawrence score) over 24 months. 30 previously reported single nucleotide polymorphisms (SNPs) associated with presence of OA irrespective of affected joints or knee OA specifically were investigated. We performed a SNP based genome-wide association analysis using the disease progression definitions. Furthermore, a PRS was created using the 30 presence SNPs to predict knee OA progression.
Existing genetic markers for knee OA presence were not found to be associated with knee OA progression. The PRS of the SNPs for knee OA presence did also not show significant predictive value for knee OA progression. Unexpectedly, nineteen different variants were associated significantly (P < 5 × 10-8) with minJSW decrease. Ten SNPs are located near protein coding genes PLCL2, CDYL2, and NTNG1, and several SNPs are located in or near long non-coding RNAs (lncRNA).
The 30 OA risk SNPs individually and combined in a PRS are not associated with progression of knee OA in the IMI-APPROACH cohort. 19 different SNPs were associated with minJSW decrease. We demonstrated how to employ multiple bioinformatics tools to, despite a limited dataset, still prioritise potential biomarkers for associations to knee OA progression.
膝关节骨关节炎（OA）是一种具有不同内型和表型的异质性疾病，导致患者临床和结构进展各异。多种基因组标记已与膝关节OA的存在相关。本研究旨在寻找这些遗传标记与膝关节OA进展的新关联，并使用多基因风险评分（PRS）来研究膝关节OA进展的风险。
使用来自IMI-APPROACH队列的膝关节OA患者（n = 297）的数据，这些数据对疾病进展进行了详细测量。膝关节OA进展的定义基于毫米为单位的最小关节间隙宽度（minJSW；主要结局）的减少、膝关节损伤和骨关节炎结局评分（KOOS）中疼痛的增加，以及24个月内放射学OA的存在（基于Kellgren-Lawrence评分）。研究了30个先前报道的与OA存在相关的单核苷酸多态性（SNP），无论受影响的关节如何或具体针对膝关节OA。我们使用疾病进展定义进行了基于SNP的全基因组关联分析。此外，使用这30个存在的SNP创建了一个PRS来预测膝关节OA进展。
未发现现有的膝关节OA存在的遗传标记与膝关节OA进展相关。膝关节OA存在的SNP的PRS对膝关节OA进展也未显示出显著的预测价值。出乎意料的是，19个不同的变异与minJSW减少显著相关（P < 5×10-8）。10个SNP位于蛋白质编码基因PLCL2、CDYL2和NTNG1附近，还有几个SNP位于长链非编码RNA（lncRNA）内或附近。
在IMI-APPROACH队列中，30个OA风险SNP单独或组合在PRS中均与膝关节OA进展无关。19个不同的SNP与minJSW减少相关。我们展示了如何使用多种生物信息学工具，尽管数据集有限，但仍能优先考虑与膝关节OA进展相关的潜在生物标志物。
