Heritability of low back pain and the role of disc degeneration
Bibliographic record
Abstract
Twin studies suggest that both disc degeneration and back pain have a genetic component. We were interested in estimating the heritability of low back pain in men and examining whether genetic influences on back pain are mediated through genetic influences on disc degeneration. Thus, we conducted a classic twin study with multivariate quantitative genetic models to estimate the degree to which genetic (or environmental) effects on back pain were correlated with genetic (or environmental) effects on disc degeneration. Subjects included 147 monozygotic and 153 dizygotic male twin pairs (N=600 subjects) from the population-based Finnish Twin Cohort. All subjects underwent lumbar magnetic resonance imaging and completed an extensive interview, including back pain history and exposure to suspected risk factors. Disc height narrowing was the degenerative finding most associated with pain history, and was used to index disc degeneration in the models. Statistically significant genetic correlations were found for disc height narrowing and different definitions of back pain, such as duration of the worst back pain episode (r(g)=0.46) and hospitalization for back problems (r(g)=0.49), as well as disability in the previous year from back pain (r(g)=0.33). The heritability estimates for these back pain variables ranged from 30% to 46%. There also were statistically significant, but weaker, environmental correlations for disc height narrowing with back symptoms over the prior year. A substantial minority of the genetic influences on pain was due to the same genetic influences affecting disc degeneration. This suggests that disc degeneration is one pathway through which genes influence back pain.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".