Suppr超能文献

炎症性外周血基因表达与影像学生物标志物相结合可增强对膝关节骨关节炎影像学进展的预测。

The combination of an inflammatory peripheral blood gene expression and imaging biomarkers enhance prediction of radiographic progression in knee osteoarthritis.

作者信息

Attur Mukundan, Krasnokutsky Svetlana, Zhou Hua, Samuels Jonathan, Chang Gregory, Bencardino Jenny, Rosenthal Pamela, Rybak Leon, Huebner Janet L, Kraus Virginia B, Abramson Steven B

机构信息

Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA.

Division of Rheumatology, Rheumatology Research laboratory, NYU Langone Orthopedic Hospital, 301 East 17th Street, Suite 1612, New York, NY, 10003, USA.

出版信息

Arthritis Res Ther. 2020 Sep 10;22(1):208. doi: 10.1186/s13075-020-02298-6.

Abstract

OBJECTIVE

Predictive biomarkers of progression in knee osteoarthritis are sought to enable clinical trials of structure-modifying drugs. A peripheral blood leukocyte (PBL) inflammatory gene signature, MRI-based bone marrow lesions (BML) and meniscus extrusion scores, meniscal lesions, and osteophytes on X-ray each have been shown separately to predict radiographic joint space narrowing (JSN) in subjects with symptomatic knee osteoarthritis (SKOA). In these studies, we determined whether the combination of the PBL inflammatory gene expression and these imaging findings at baseline enhanced the prognostic value of either alone.

METHODS

PBL inflammatory gene expression (increased mRNA for IL-1β, TNFα, and COX-2), routine radiographs, and 3T knee MRI were assessed in two independent populations with SKOA: an NYU cohort and the Osteoarthritis Initiative (OAI). At baseline and 24 months, subjects underwent standardized fixed-flexion knee radiographs and knee MRI. Medial JSN (mJSN) was determined as the change in medial JSW. Progressors were defined by an mJSN cut-point (≥ 0.5 mm/24 months). Models were evaluated by odds ratios (OR) and area under the receiver operating characteristic curve (AUC).

RESULTS

We validated our prior finding in these two independent (NYU and OAI) cohorts, individually and combined, that an inflammatory PBL inflammatory gene expression predicted radiographic progression of SKOA after adjustment for age, sex, and BMI. Similarly, the presence of baseline BML and meniscal lesions by MRI or semiquantitative osteophyte score on X-ray each predicted radiographic medial JSN at 24 months. The combination of the PBL inflammatory gene expression and medial BML increased the AUC from 0.66 (p = 0.004) to 0.75 (p < 0.0001) and the odds ratio from 6.31 to 19.10 (p < 0.0001) in the combined cohort of 473 subjects. The addition of osteophyte score to BML and PBL inflammatory gene expression further increased the predictive value of any single biomarker. A causal analysis demonstrated that the PBL inflammatory gene expression and BML independently influenced mJSN.

CONCLUSION

The use of the PBL inflammatory gene expression together with imaging biomarkers as combinatorial predictive biomarkers, markedly enhances the identification of radiographic progressors. The identification of the SKOA population at risk for progression will help in the future design of disease-modifying OA drug trials and personalized medicine strategies.

摘要

目的

寻找膝关节骨关节炎进展的预测生物标志物,以开展结构改良药物的临床试验。外周血白细胞(PBL)炎症基因特征、基于磁共振成像(MRI)的骨髓损伤(BML)和半月板挤压评分、半月板损伤以及X线片上的骨赘,已分别被证明可预测有症状膝关节骨关节炎(SKOA)患者的影像学关节间隙狭窄(JSN)。在这些研究中,我们确定了基线时PBL炎症基因表达与这些影像学表现的组合是否能增强单独任何一项的预后价值。

方法

在两个独立的SKOA人群(纽约大学队列和骨关节炎倡议组织(OAI))中评估PBL炎症基因表达(白细胞介素-1β、肿瘤坏死因子α和环氧化酶-2的mRNA增加)、常规X线片和3T膝关节MRI。在基线和24个月时,受试者接受标准化固定屈曲位膝关节X线片和膝关节MRI检查。内侧JSN(mJSN)被确定为内侧关节间隙宽度(JSW)的变化。进展者通过mJSN切点(≥0.5毫米/24个月)来定义。通过比值比(OR)和受试者操作特征曲线下面积(AUC)对模型进行评估。

结果

我们在这两个独立的(纽约大学和OAI)队列中,分别及联合验证了我们之前的发现,即炎症性PBL炎症基因表达在调整年龄、性别和体重指数后可预测SKOA的影像学进展。同样,MRI显示的基线BML和半月板损伤或X线片上的半定量骨赘评分各自都可预测24个月时的影像学内侧JSN。在473名受试者的联合队列中,PBL炎症基因表达与内侧BML的组合使AUC从0.66(p = 0.004)提高到0.75(p < 0.0001),比值比从6.31提高到19.10(p < 0.0001)。在BML和PBL炎症基因表达中加入骨赘评分进一步提高了任何单一生物标志物的预测价值。因果分析表明,PBL炎症基因表达和BML独立影响mJSN。

结论

将PBL炎症基因表达与影像学生物标志物作为组合预测生物标志物使用,可显著提高对影像学进展者的识别。识别有进展风险的SKOA人群将有助于未来设计改善病情的骨关节炎药物试验和个性化医疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53c7/7488029/3416e8e16c8b/13075_2020_2298_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验