Interleukin-1 genetic polymorphisms in knee osteoarthritis: What do we know? A meta-analysis and systematic review
Bibliographic record
Abstract
PURPOSE: Interleukin-1 is the main proinflammatory cytokine in osteoarthritis (OA). Several single-nucleotide polymorphisms (SNPs) within the IL-1 gene cluster (IL-1β, IL-1R1, and IL-1RN) have been determined, but their associations with knee OA remain poorly understood. The present study aimed to identify the associations between IL-1 SNPs and knee osteoarthritis. METHODS: This meta-analysis and systematic review included all comparative studies published in the MEDLINE/PubMed, Embase, Google Scholar, and Cochrane Library databases. We performed a systematic search to identify relevant studies on the evaluation of the correlation between the IL-1 gene and knee OA published up to February 2020 that met the eligibility criteria. Nine studies on a total of 2256 knees with OA and 3527 healthy knees met the eligibility criteria. Results associated with IL-1A, IL-1B, IL-1R1, and IL-1RN SNPs were extracted and compared between knees with OA and healthy knees. Methodological quality was assessed using the Newcastle-Ottawa scale (NOS). All studies with fair or good quality were included. RESULTS: The meta-analysis showed that the risk of knee OA is decreased by the IL-1RN*1 and IL-1RN*1/*1 genotypes and increased by the IL-1RN*2 and I-L1RN*1/*2 genotypes. The systematic review revealed only two studies associating the IL-1RN allele, none associating the IL-1B polymorphism, and only one study associating IL-1A and IL-1R1 polymorphisms with knee OA. CONCLUSIONS: Several IL-1RN alleles and genotypes play a role in knee OA but other genetic variations in the IL-1 region were still conflicting in its association with knee OA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.014 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".