The genetic epidemiology of idiopathic scoliosis
Bibliographic record
Abstract
PURPOSE: Idiopathic scoliosis is a complex developmental syndrome defined by an abnormal structural curvature of the spine. High treatment costs, chronic pain/discomfort, and the need for monitoring at-risk individuals contribute to the global healthcare burden of this musculoskeletal disease. Although many studies have endeavored to identify underlying genes, little progress has been made in understanding the etiopathogenesis. The objective of this comprehensive review was to summarize genetic associations/linkages with idiopathic scoliosis, as well as explore the strengths and weaknesses of each study, such that it may serve as a guide for the design and interpretation of future genetic studies in scoliosis. METHODS: We searched PubMed and Human Genome Epidemiology (HuGE) Navigator using the search terms "gene and scoliosis". Linkage or association studies published in English and available full-text were further analyzed as regards results, experimental design, and statistical approach. RESULTS: We identified and analyzed 50 studies matching our criteria. These consisted of 34 candidate gene studies (6 linkage, 28 association) and 16 genome-wide studies [14 pedigree-based linkage, 2 genome-wide association studies (GWAS)]. Findings involved genes related to connective tissue structure, bone formation/metabolism, melatonin signaling pathways, puberty and growth, and axon guidance pathways. Variability in results between studies suggested ethnic and/or genetic heterogeneity. CONCLUSIONS: The major difficulty in idiopathic scoliosis research is phenotypic and genetic heterogeneity. Genetic research was overrepresented by underpowered studies. The use of biological endophenotypes, as well as restricted clinical definitions, may help to partition variation and increase the power of studies to detect or confirm an effect.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".