NYU cohort. Based on a priori knowledge, we expect a minimum of 30% of participants to progress (defined as JSN ≥0.5 mm/24 months) , and a minimum of 30% to show no evidence of progression (JSN =0mm/24 months. Therefore, we recruited 132 additional patients to our prior cohort of 111 patients with SKOA (n=243) who completed a 24-month NIH-funded prospective study evaluating biomarkers in OA (11, 12) (Figure 1), satisfying a power analysis to detect an effect size of 0.3 for biomarkers at significance level of 0.05 and power of 0.85.
NYU Cohort Inclusion and Exclusion Criteria: As part of an NIH-funded study, we recruited and followed for 24 months SKOA patients who met American College of Rheumatology (ACR) knee OA radiographic criteria [Kellgren-Lawrence (KL) grade ≥1] and clinical symptomatic criteria with at least 3 of the following: age >50 years, stiffness <30 min, crepitus, bony tenderness, bony enlargement, no palpable warmth (25). Patients having any of the following were excluded: any other form of arthritis (including rheumatoid arthritis, spondyloarthritis, active crystal arthropathy); body mass index (BMI) ≥33; any disorder requiring the use of systemic corticosteroids within 1 week of screening, history of bilateral knee replacements; major co-morbidities including diabetes mellitus, non-cutaneous cancer within 5 years of screening, chronic hepatic or renal disease, chronic infectious disease, congestive heart failure; and hyaluronan and/or corticosteroid injections to the affected knee within 3 months of screening. Some exclusion criteria, such as the BMI cutoff, were chosen to mitigate potential effects of the covariate on inflammatory peripheral blood leukocyte (PBL) transcriptome markers, which were investigated as a separate aim of this study and reported upon elsewhere (17). The Institutional Review Board at NYU Medical Center approved the protocol. Informed consent was obtained from all subjects.
Clinical assessments. All subjects had completed the Visual Analog Scale (VAS) and WOMAC pain assessments at baseline and every 6 months for the duration of the study. Pain questions were specific to the more painful knee (signal knee). Subjects also had a physical exam by a study physician at baseline and after 24 months.
NYU Imaging: Radiograph and MRI acquisition and scoring
Knee radiographs. Subjects underwent standardized weight-bearing fixed-flexion posteroanterior knee radiographs using the SynaFlexer™ X-ray positioning frame (Synarc) at baseline and 24 months as described previously (16, 29). The radiographic beam angle was optimized for the medial joint space compartment. Radiographic readings were done separately by two musculoskeletal radiologists (LR, JB) blinded to patient demographics, clinical information, and MRI readings. X-rays were scored for KL grade 0-4 (30), and medial and lateral joint space width (JSW) measured at the mid-portion of the joint space via electronic calipers. Joint space narrowing (JSN) was calculated as the change in JSW, in millimeters, from baseline to 24-month follow up. Disagreements between the two readers were resolved by consensus. Cohen's kappa coefficient for interrater agreement on KL grades was 0.85 and 0.77 for the right knee and left knee, respectively, and kappas for JSW were ≥ 0.93 for medial compartments of both the right and left knees. Based on the high inter-reader correlations, a single reader (LR) was employed for the 24-month follow up. Osteopbyte scoring - both medial and lateral osteophytes in tibial and femoral regions scored semi-quantitatively (0-3) [0= absent, 1-mild, 2-moderate, and 3= severe]. Since the majority of both the NYU and OAI subjects (approximately 80%) had medial compartment disease, we restricted our analysis to medial radiographic JSN progressors.
NYU Knee MR imaging protocol. Of the 243 subjects enrolled, only 111 subjects had MR imaging performed [on a 3.0T clinical scanner (Magnetom Tim Trio; Siemens Medical Solutions, Erlangen, Germany) using an eight-channel transmit-receive phased-array knee coil (In vivo Corporation, FL)]. The knee imaging protocol consisted of a sagittal 3D-high resolution T1-weighted-fast low angle shot (FLASH) sequence with selective water excitation (TR/TE = 25/4ms; flip angle = 25; FOV = 15x15 cm; slice thickness = 1.5 mm; matrix = 512x384; receiver bandwidth = 200Hz/pixel) as well as sagittal T2-weighted fat-saturated spin echo (TR/TE = 4000/75 ms; FOV = 15x15 cm; slice thickness = 3 mm; matrix = 256x128; receiver bandwidth = 130Hz/pixel).
NYU Knee MR assessments: WORMS scoring. A musculoskeletal radiologist (GC), blinded to the clinical and radiographic information, but not blinded to acquisition time point, performed Whole-organ Magnetic Resonance Imaging Score (WORMS) scoring on sagittal T2-weighted fat-saturated images and sagittal T1-weighted 3-D spoiled gradient-echo images (31). Specifically, cartilage morphology (score of 0-6) and subarticular bone marrow lesions (BML, a score of 0-3) were scored within the anterior, central, and posterior regions of the medial and lateral tibial plateaus; central and posterior regions of the medial and lateral femoral condyles were also scored. Medial and lateral meniscal morphology (score of 0-4) were also evaluated. Inter-rater reliability was assessed by scoring 10 subjects in two separate sessions, one week apart. Paired t-tests, applied for assessing differences for cartilage, BML and meniscus readings (p-values 0.354, 0.797 and 0.766 for cartilage, BML and meniscus readings, respectively), showed that there were no significant differences, which verified reading reliability of our data. Cartilage medial scores were calculated as the sum of the medial femur central, medial femur posterior, medial tibia anterior, medial tibia central and medial tibia posterior regions. Cartilage lateral scores were calculated as the sum of lateral femur central, lateral femur posterior, lateral tibia anterior, lateral tibia central, and lateral tibia posterior regions. Overall, cartilage scores were calculated by summing lateral and medial cartilage scores. BML medial scores were calculated as the sum of the medial femur central, medial femur posterior, medial tibia anterior, medial tibia central and medial tibia posterior regions. BML lateral scores were calculated as the sum of lateral femur central, lateral femur posterior, lateral tibia anterior, lateral tibia central, and lateral tibia posterior regions. Overall, BML scores were calculated by summing lateral and medial BML scores.
The OAI Cohort. The OAI is a multi-center, longitudinal, prospective observational study of knee OA. The main goal of the OAI is to develop a public domain research resource to facilitate the scientific evaluation of biomarkers for knee OA as potential surrogate endpoints for disease onset and progression. Participants were selected from the Osteoarthritis Initiative (OAI; http://www.oai.ucsf.edu/, a longitudinal cohort of 4,796 participants with clinical, radiological, biochemical, and other data collected at baseline and annual follow-up visits. OAI recruited participants with SKOA, and also those with no OA but considered at high risk of incident OA. We selected 204 individuals with body mass index (BMI) ≤33, and Kellgren-Lawrence (KL) score 2 or 3 in the signal knee and for whom we had high quality radiographs (32, 33) (Figure 1). Clinical, radiographic, and MRI data were obtained from the OAI database (https://data-archive.nimh.nih.gov/oai). MRI images. MRI images were scored for BMLs using the semi-quantitative (SQ) (MRI Osteoarthritis Knee Score) MOAKS system available at the OAI site. For each sub-region, MOAKS scores three features using an ordinal score for size, number of BMLs and percentage of lesion that is a BML. The OAI dataset includes both MRI and radiographic images. Baseline clinical data, MRI BML scores, radiographs (baseline and 24 months) and buffy coat samples for transcriptome studies were obtained.
OAI cohort: High Quality OAI (HQ-OAI) Radiographs. The OAI imaging acquisition techniques and reading protocols are publicly available at http://oai.epi-ucsf.org/datarelease. Baseline OA severity was assessed on knee radiographs centrally read and graded according to the Kellgren–Lawrence (KL) system (30). Briefly, bilateral posteroanterior fixed-flexion weight-bearing radiographic views were obtained using a SynaFlexerTM frame (Synarc, Newark, CA, USA). The detailed Radiographic Procedure Manual is available online (https://oai.epiucsf.org/datarelease/operationsManuals/ RadiographicManual.pdf). We selected a cohort of 443 cases, whose knee radiographs had high quality MTP alignment (defined as the inter-margin distance (IMD) of ≤1.70 mm at baseline and 24-month films (32). Furthermore, from this high quality sub-cohort, we have selected patients whose BMI is <33 and signal knee (painful knee) with KL 2 or 3 were selected for this study (Figure 1).
MR image acquisition and quantitative measures. Non-contrast MRIs were obtained on 3T Trio systems (Siemens Healthcare, Erlangen, Germany), and the complete pulse sequence protocol and sequence parameters have been described previously (34). BML MOAKS Score: MRI BML scores available for all the subjects for whom transcriptome data available were downloaded from the OAI site. Briefly, BML was scored using the semi-quantitative MRI Osteoarthritis Knee Score (MOAKS) system, which is available at the OAI site (35). For each sub-region, MOAKS scores three features using an ordinal score for size, number of BMLs, and percentage of lesion that is a BML. The utilization of study protocol and biospecimens were reviewed and approved by the NYU School of Medicine IRB.
Radiographic progression: For the medial JSN outcome variable, our definition of radiographic progression was similar to the case definitions described previously based on previously published reports (8, 10, 27). SKOA patients who had narrowing in the medial tibiofemoral compartment by at least 0.5 mm over 24 months from baseline in the signal knee. We defined non-progressors or no progression as no increase, defined as JSN ≤0.0 mm over 24 months.
Sample collection and assessment
PBL isolation and inflammatory gene expression. NYU cohort: at the time of baseline knee radiographs, non-fasting blood samples were collected in pyrogen-free heparinized tubes for PBL isolation using the Ficoll-Hypaque density gradient centrifugation. Total RNA was isolated from PBLs and from citrate buffy coats (OAI cohort) using the Qiagen RNeasy Kit (Qiagen) as described previously (15, 17). For both NYU and OAI studies, relative expression of inflammatory mRNA expression in PBLs was determined using Predesigned TaqMan primer sets (IL1B – Hs00174097_m1; TNFA – Hs00174128 _m1; PTGS2 (COX-2) – Hs00153133_m1) (Applied Biosystems). qPCR was performed as previously described (15), normalized against housekeeping genes GAPDH and 18S, and fold change was calculated using the delta Ct method (36). For the OAI study, the relative fold-change data were calculated against super-control (n=100) obtained from OAI biorepository who did not develop knee OA over 8 years of follow up and the qPCR obtained CT values of each target(s) including the housekeeping genes were shared with the OAI biorepository team for de-identification and the following association studies.
OAI MRI BML Scores. BMLs were scored using the MRI OA Knee Score (MOAKS) system available at the OAI site (35). The OAI dataset includes both MRI and radiographic images, including osteophytes.
Statistical methods. The relationships between baseline clinical, demographic, and imaging variables, including Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain, visual analog scale (VAS) pain, JSW, osteophytes, MRI-determined cartilage and BML scores, age, sex and BMI were determined by Spearman’s correlation. Associations between variables were assessed by partial correlations controlling for age, sex, and BMI. Receiver operating characteristic (ROC) curves were constructed, and area under the curve (AUC) computed (AUC ranges from 0 to 1, with 1 indicating perfect predictivity and 0.5 indicating random guess) to determine the predictive power of MRI and/or PBL transcriptome biomarkers for progression (37). Logistic regression models were fitted with 10-fold cross-validation and repeated 100 times. AUC values were compared against random models for significance using Delong’s test (38). False discovery rate (FDR) was used to adjust the p values for multivariate comparison (39). To evaluate whether medial BML as an additional predictor improved the regression model, we used 2 methods: 1) Delong’s test comparing the AUCs from the model with biomarkers plus medial BML against the model with biomarkers alone, and 2) ANOVA comparing linear regression models of JSN with biomarkers plus medial BML versus biomarkers alone.
Causal graph analysis was performed, for which we used the FCI algorithm in the TETRAD software package (http://www.phil.cmu.edu/projects/tetrad/version 4.3.10-7). This method is capable of discovering a causal graph that most closely resembles the data distribution (9). Independence testing was based on Fisher’s Z test, with the significance level set to 0.10. No data manipulation of any kind (e.g., transformation, imputation, thresholding) was applied; therefore, these analyses were not biased toward particular causal hypotheses.