Methodological development of molecular endotype discovery from synovial fluid of individuals with knee osteoarthritis: the STEpUP OA Consortium

Abstract

Objectives: To develop and validate a pipeline for quality controlled (QC) protein data for largescale analysis of synovial fluid (SF), using SomaLogic technology. Design: Knee SF and associated clinical data were from partner cohorts. SF samples were centrifuged, supernatants stored at -80oC, then analysed by SomaScan Discovery Plex V4.1 (>7000 SOMAmers/proteins). Setting: An international consortium of 9 academic and 8 commercial partners (STEpUP OA). Participants: 1746 SF samples from 1650 individuals comprising OA, joint injury, healthy controls and inflammatory arthritis controls, divided into discovery (n=1045) and replication (n=701) datasets. Primary and secondary outcome measures: An optimised approach to standardisation was developed iteratively, monitoring reliability and precision (comparing coefficient of variation [%CV] of 'pooled' SF samples between plates and correlation with prior immunoassay for 9 analytes). Pre-defined technical confounders were adjusted for (by Limma) and batch correction was by ComBat. Poorly performing SOMAmers and samples were filtered. Variance in the data was determined by principal component (PC) analysis. Data were visualised by Uniform Manifold Approximation and Projection (UMAP). Results: Optimal SF standardisation aligned with that used for plasma, but without median normalisation. There was good reliability (<20 %CV for >80% of SOMAmers in pooled samples) and overall good correlation with immunoassay. PC1 accounted for 48% of variance and strongly correlated with individual SOMAmer signal intensities (median correlation coefficient 0.70). These could be adjusted using an 'intracellular protein score'. PC2 (7% variance) was attributable to processing batch and was batch-corrected by ComBat. Lesser effects were attributed to other technical confounders. Data visualisation by UMAP revealed clustering of injury and OA cases in overlapping but distinguishable areas of high-dimensional proteomic space. Conclusions: We define a standardised approach for SF analysis using the SOMAscan platform and identify likely 'intracellular' protein as being a major driver of variance in the data.

Deconvoluting synovial fluid molecular endotypes in knee osteoarthritis: primary results from the STEpUP OA Consortium

“…All participants gave written informed consent with local (institution specific) ethical approvals in place. Following the QC procedure, 1361 samples were identified from unique participants with established OA [27] . Individual cohorts were assigned, a priori , into Discovery (N = 708) and Replication (N = 653) datasets (Supplementary Table 1).…”

“…We have also previously shown that proteins regulated in knee OA or after knee injury, compared with healthy controls, are readily detected in the SF but correlate poorly in paired blood [22–25] . Furthermore, we have previously confirmed the utility of high scale protein measurements in SF using the SomaScan® platform (SomaLogic, Inc, Boulder, Colorado), an aptamer-based assay [26, 27] . The SomaScan® platform V4.1 measures over 6596 distinct human proteins.…”

“…Most samples were spun after joint aspiration but appropriate correction was applied when unspun samples were included in analyses. Full details of the cohorts and their associated metadata, how SF was collected and processed prior to SomaScan analysis, as well as how we corrected for predefined technical and other confounders can be found in Deng et al 2023 [27] . The primary Discovery statistical analysis was pre-specified and cross-sectional (Data Analysis Plan, see link below).…”

“…To search for molecular endotypes in OA using SF protein profiles, the f(K) cluster metric was employed. We had previously reported that a large contributor of variance in the initial processed data (principal component 1, accounting for 48% of variance), was due to intracellular proteins [27] .…”

“…We set out to perform an unsupervised analysis of a single SF sample from 1361 individuals with established OA where cross-sectional clinical data were also available. The standardised protocol, which describes the cohorts in detail, and includes how we adjusted for pre-defined technical and other confounding factors is available elsewhere [27] . Here we present the primary analysis of STEpUP OA, in which we determine whether protein molecular endotypes exist in the SF of participants with established knee OA, and further explore the relationship between proteomic signatures and structural and symptomatic disease.…”