SMAD3 Is Associated with the Total Burden of Radiographic Osteoarthritis: The Chingford Study
Bibliographic record
Abstract
BACKGROUND: A newly-described syndrome called Aneurysm-Osteoarthritis Syndrome (AOS) was recently reported. AOS presents with early onset osteoarthritis (OA) in multiple joints, together with aneurysms in major arteries, and is caused by rare mutations in SMAD3. Because of the similarity of AOS to idiopathic generalized OA (GOA), we hypothesized that SMAD3 is also associated with GOA and tested the hypothesis in a population-based cohort. METHODS: Study participants were derived from the Chingford study. Kellgren-Lawrence (KL) grades and the individual features of osteophytes and joint space narrowing (JSN) were scored from radiographs of hands, knees, hips, and lumbar spines. The total KL score, osteophyte score, and JSN score were calculated and used as indicators of the total burden of radiographic OA. Forty-one common SNPs within SMAD3 were genotyped using the Illumina HumanHap610Q array. Linear regression modelling was used to test the association between the total KL score, osteophyte score, and JSN score and each of the 41 SNPs, with adjustment for patient age and BMI. Permutation testing was used to control the false positive rate. RESULTS: A total of 609 individuals were included in the analysis. All were Caucasian females with a mean age of 60.9±5.8. We found that rs3825977, with a minor allele (T) frequency of 20%, in the last intron of SMAD3, was significantly associated with total KL score (β = 0.14, Ppermutation = 0.002). This association was stronger for the total JSN score (β = 0.19, Ppermutation = 0.002) than for total osteophyte score (β = 0.11, Ppermutation = 0.02). The T allele is associated with a 1.47-fold increased odds for people with 5 or more joints to be affected by radiographic OA (Ppermutation = 0.046). CONCLUSION: We found that SMAD3 is significantly associated with the total burden of radiographic OA. Further studies are required to reveal the mechanism of the association.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".