Identification of factors associated with non-responders to total joint replacement and sustained knee pain in primary osteoarthritis patients by epidemiological and multi-omic studies
Bibliographic record
Abstract
Osteoarthritis (OA) is among the most common rheumatic diseases, affecting 30% of the world’s population over 60 years. Currently, total joint replacement (TJR) is considered the most effective treatment for end-stage OA. However, up to 20% of patients do not see clinically significant improvement in pain or function after the surgery. This thesis aims to identify epidemiological, metabolic, and genetic factors which are significantly associated with non-responders to TJR and patients with sustained, treatment-resistant pain in a large cohort from Newfoundland and Labrador (NL), Canada. First, we identified a number of epidemiological factors significantly associated with non-responders to TJR including clinical depression, younger age, and multisite musculoskeletal pain (MSMP). This highlighted potential roles for altered pain perception and pain sensitization in non-responders. Subsequently, we used a targeted metabolomic approach which profiled 186 metabolites in plasma and identified three metabolite ratios and two metabolite networks which were significantly associated with pain or function non-responders. Our findings highlighted phosphatidylcholines (PCs), branched chain amino acids (BCAAs), and acylcarnitines, all of which are involved in inflammatory processes, as metabolites of interest for further study in non-responders. Next, we used the same metabolomic approach to assess metabolites and metabolite ratios associated with sustained knee pain in two independent cohorts, one from NL and the other from Ontario, Canada. We identified one metabolite and three metabolite ratios to be associated with sustained pain, further highlighting roles for PCs, acylcarnitines, and sphingomyelins (SMs) in OA knee pain. We then investigated mechanisms underlying sustained pain in the NL cohort using a multi-omic approach which identified KALRN as a candidate gene and a significant role for central pain sensitization in sustained knee pain. Finally, we developed and evaluated a method to profile eicosanoids and endocannabinoids, a large group of inflammatory mediators involved in pain generation, in plasma for use in future studies on non-responders and patients with sustained knee pain. Overall, our findings highlighted potential roles for inflammation and pain sensitization in OA pain and non-response to TJR and offer interesting routes for future studies in this area and could have potential utility in predicting surgical outcome or as druggable targets to modify outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".