Identifying multivariate disease trajectories and potential phenotypes of early knee osteoarthritis in the CHECK cohort

OBJECTIVE

To gain better understanding of osteoarthritis (OA) heterogeneity and its predictors for distinguishing OA phenotypes. This could provide the opportunity to tailor prevention and treatment strategies and thus improve care.

DESIGN

Ten year follow-up data from CHECK (1002 early-OA subjects with first general practitioner visit for complaints ≤6 months before inclusion) was used. Data were collected on WOMAC (pain, function, stiffness), quantitative radiographic tibiofemoral (TF) OA characteristics, and semi-quantitative radiographic patellofemoral (PF) OA characteristics. Using functional data analysis, distinctive sets of trajectories were identified for WOMAC, TF and PF characteristics, based on model fit and clinical interpretation. The probabilities of knee membership to each trajectory were used in hierarchical cluster analyses to derive knee OA phenotypes. The number and composition of potential phenotypes was selected again based on model fit (silhouette score) and clinical interpretation.

RESULTS

Five trajectories representing different constant levels or changing WOMAC scores were identified. For TF and PF OA, eight and six trajectories respectively were identified based on (changes in) joint space narrowing, osteophytes and sclerosis. Combining the probabilities of knees belonging to these different trajectories resulted in six clusters ('phenotypes') of knees with different degrees of functional (WOMAC) and radiographic (PF) parameters; TF parameters were found not to significantly contribute to clustering. Including baseline characteristics as well resulted in eight clusters of knees, dominated by sex, menopausal status and WOMAC scores, with only limited contribution of PF features.

CONCLUSIONS

Several stable and progressive trajectories of OA symptoms and radiographic features were identified, resulting in phenotypes with relatively independent symptomatic and radiographic features. Sex and menopausal status may be especially important when phenotyping knee OA patients, while radiographic features contributed less. Possible phenotypes were identified that, after validation, could aid personalized treatments and patients selection.

Cohort profile: The Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) study: a 2-year, European, cohort study to describe, validate and predict phenotypes of osteoarthritis using clinical, imaging and biochemical markers

PURPOSE

The Applied Public-Private Research enabling OsteoArthritis Clinical Headway (APPROACH) consortium intends to prospectively describe in detail, preselected patients with knee osteoarthritis (OA), using conventional and novel clinical, imaging, and biochemical markers, to support OA drug development.

PARTICIPANTS

APPROACH is a prospective cohort study including 297 patients with tibiofemoral OA, according to the American College of Rheumatology classification criteria. Patients were (pre)selected from existing cohorts using machine learning models, developed on data from the CHECK cohort, to display a high likelihood of radiographic joint space width (JSW) loss and/or knee pain progression.

FINDINGS TO DATE

Selection appeared logistically feasible and baseline characteristics of the cohort demonstrated an OA population with more severe disease: age 66.5 (SD 7.1) vs 68.1 (7.7) years, min-JSW 2.5 (1.3) vs 2.1 (1.0) mm and Knee injury and Osteoarthritis Outcome Score pain 31.3 (19.7) vs 17.7 (14.6), except for age, all: p<0.001, for selected versus excluded patients, respectively. Based on the selection model, this cohort has a predicted higher chance of progression.

FUTURE PLANS

Patients will visit the hospital again at 6, 12 and 24 months for physical examination, pain and general health questionnaires, collection of blood and urine, MRI scans, radiographs of knees and hands, CT scan of the knee, low radiation whole-body CT, HandScan, motion analysis and performance-based tests.After two years, data will show whether those patients with the highest probabilities for progression experienced disease progression as compared to those wit lower probabilities (model validation) and whether phenotypes/endotypes can be identified and predicted to facilitate targeted drug therapy.

TRIAL REGISTRATION NUMBER

NCT03883568.

Alterations in the chondrocyte surfaceome in response to pro-inflammatory cytokines

Background

Chondrocytes are exposed to an inflammatory micro-environment in the extracellular matrix (ECM) of articular cartilage in joint diseases such as osteoarthritis (OA) and rheumatoid arthritis (RA). In OA, degenerative changes and low-grade inflammation within the joint transform the behaviour and metabolism of chondrocytes, disturb the balance between ECM synthesis and degradation, and alter the osmolality and ionic composition of the micro-environment. We hypothesize that chondrocytes adjust their physiology to the inflammatory microenvironment by modulating the expression of cell surface proteins, collectively referred to as the ‘surfaceome’. Therefore, the aim of this study was to characterize the surfaceome of primary equine chondrocytes isolated from healthy joints following exposure to the pro-inflammatory cytokines interleukin-1-beta (IL-1β) and tumour necrosis factor-alpha (TNF-α). We employed combined methodology that we recently developed for investigating the surfaceome in stem cells. Membrane proteins were isolated using an aminooxy-biotinylation technique and analysed by mass spectrometry using high throughput shotgun proteomics. Selected proteins were validated by western blotting.

Results

Amongst the 431 unique cell surface proteins identified, a high percentage of low-abundance proteins, such as ion channels, receptors and transporter molecules were detected. Data are available via ProteomeXchange with identifier PXD014773. A high number of proteins exhibited different expression patterns following chondrocyte stimulation with pro-inflammatory cytokines. Low density lipoprotein related protein 1 (LPR-1), thrombospondin-1 (TSP-1), voltage dependent anion channel (VDAC) 1–2 and annexin A1 were considered to be of special interest and were analysed further by western blotting.

Conclusions

Our results provide, for the first time, a repository for proteomic data on differentially expressed low-abundance membrane proteins on the surface of chondrocytes in response to pro-inflammatory stimuli.