Association of Genome-Wide Association Study (GWAS) Identified SNPs and Risk of Breast Cancer in an Indian Population
Bibliographic record
Abstract
To date, no studies have investigated the association of the GWAS-identified SNPs with BC risk in Indian population. We investigated the association of 30 previously reported and replicated BC susceptibility SNPs in 1,204 cases and 1,212 controls from a hospital based case-control study conducted at the Tata Memorial Hospital, Mumbai. As a measure of total susceptibility burden, the polygenic risk score (PRS) for each individual was defined by the weighted sum of genotypes from 21 independent SNPs with weights derived from previously published estimates of association odds-ratios. Logistic regression models were used to assess risk associated with individual SNPs and overall PRS, and stratified by menopausal and receptor status. A total of 11 SNPs from eight genomic regions (FGFR2, 9q31.2, MAP3K, CCND1, ZM1Z1, RAD51L11, ESR1 and UST) showed statistically significant (p-value ≤ 0.05) evidence of association, either overall or when stratified by menopausal status or hormone receptor status. BC SNPs previously identified in Caucasian population showed evidence of replication in the Indian population mainly with respect to risk of postmenopausal and hormone receptor positive BC.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".