Biclustering reveals potential knee OA phenotypes in exploratory analyses: Data from the Osteoarthritis Initiative.
Biclustering reveals potential knee OA phenotypes in exploratory analyses: Data from the Osteoarthritis Initiative.
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双聚类揭示了探索性分析中潜在的膝关节 OA 表型：来自骨关节炎倡议的数据。
DOI：
10.1371/journal.pone.0266964
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发表时间：
2022
期刊：
影响因子：
3.7
通讯作者：
Marron, J. S.
中科院分区：
文献类型：
--
作者：
Nelson, Amanda F.;Keefe, Thomas F.;Schwartz, Todd M.;Callahan, Leigh;Loeser, Richard;Golightly, Yvonne;Arbeeva, Liubov;Marron, J. S.
应用双聚类，一种最初为分析基因表达数据而开发的方法，同时聚类观察结果和临床特征，以首次探索膝关节骨关节炎（KOA）的候选表型。对骨关节炎倡议（OAI）基线访视的数据进行清理、转换和标准化（留下6461个膝关节，86个特征）。Biclustering产生了整个数据矩阵的子矩阵，代表了变量子集的相似观察结果。使用新型SigClust程序确定统计学验证。在确定双簇后，评估了与关键结局指标的关系，包括放射学KOA进展、全膝关节置换术、关节间隙宽度丢失以及96个月随访期间的西安大略和麦克马斯特大学骨关节炎指数（WOMAC）评分恶化。最终分析集包括来自3330名个体的6461个膝关节（平均年龄61岁，平均体重指数28 kg/m2，57%为女性，86%为白色）。我们确定了6个相互排斥的双聚类，其特征在于基线时的不同特征，特别是与症状和功能相关的特征。与整个膝关节队列相比，双簇分别代表总体预后更好（#1）、相似（#2、3、6）和较差（#4、5）。一般而言，双簇4和5中的膝关节结构进展更多（基于Kelling-Lawrence分级、全膝关节置换术和关节间隙宽度丢失），但随着时间的推移，WOMAC疼痛评分趋于改善。相比之下，与整个队列相比，双集群1中的膝关节发生和进展性KOA较少，全膝关节置换术较少，关节间隙宽度损失较少，疼痛评分稳定。我们在基线OAI数据集中确定了六个双聚类，它们与KOA的关键结果有不同的关系。这样的双簇代表了较大队列中的潜在表型，并可能表明随着时间的推移，亚组的进展风险更大或更小。
To apply biclustering, a methodology originally developed for analysis of gene expression data, to simultaneously cluster observations and clinical features to explore candidate phenotypes of knee osteoarthritis (KOA) for the first time. Data from the baseline Osteoarthritis Initiative (OAI) visit were cleaned, transformed, and standardized as indicated (leaving 6461 knees with 86 features). Biclustering produced submatrices of the overall data matrix, representing similar observations across a subset of variables. Statistical validation was determined using the novel SigClust procedure. After identifying biclusters, relationships with key outcome measures were assessed, including progression of radiographic KOA, total knee arthroplasty, loss of joint space width, and worsening Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores, over 96 months of follow-up. The final analytic set included 6461 knees from 3330 individuals (mean age 61 years, mean body mass index 28 kg/m2, 57% women and 86% White). We identified 6 mutually exclusive biclusters characterized by different feature profiles at baseline, particularly related to symptoms and function. Biclusters represented overall better (#1), similar (#2, 3, 6), and poorer (#4, 5) prognosis compared to the overall cohort of knees, respectively. In general, knees in biclusters #4 and 5 had more structural progression (based on Kellgren-Lawrence grade, total knee arthroplasty, and loss of joint space width) but tended to have an improvement in WOMAC pain scores over time. In contrast, knees in bicluster #1 had less incident and progressive KOA, fewer total knee arthroplasties, less loss of joint space width, and stable pain scores compared with the overall cohort. We identified six biclusters within the baseline OAI dataset which have varying relationships with key outcomes in KOA. Such biclusters represent potential phenotypes within the larger cohort and may suggest subgroups at greater or lesser risk of progression over time.
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DOI：
10.1016/j.rdc.2020.09.001
发表时间：
2021-03
期刊：
Rheumatic diseases clinics of North America
影响因子：
--
作者：
Callahan LF;Cleveland RJ;Allen KD;Golightly Y
通讯作者：
Golightly Y
影响因子：
2.9
作者：
Robbins SR;Melo LRS;Urban H;Deveza LA;Asher R;Johnson VL;Hunter DJ
通讯作者：
Hunter DJ
影响因子：
1.7
作者：
Feng, Qing;Hannig, Jan;Marron, J. S.
通讯作者：
Marron, J. S.
影响因子：
5.3
作者：
Kurtz, Steven M.;Ong, Kevin L.;Bozic, Kevin J.
通讯作者：
Bozic, Kevin J.
影响因子：
7
作者：
Guan, B.;Liu, F.;Kijowski, R.
通讯作者：
Kijowski, R.