A GWAS follow‐up of obesity‐related SNPs in <i>SYPL2</i> reveals sex‐specific association with hip circumference
Bibliographic record
Abstract
Summary Objective A novel single‐nucleotide polymorphism (SNP) associated with morbid obesity was recently identified by exome sequencing. The purpose of this study was to follow up this low‐frequency coding SNP located within the SYPL2 locus and associated with body mass index in order to reveal novel associations with obesity‐related traits. Methods The body mass index‐associated SNP (rs62623713 A>G [chr1:109476817/hg19]) and two tagging SNPs within the SYPL2 locus, rs9661614 T>C (chr1:109479215) and rs485660 G>A (chr1:109480810), were genotyped in the obesity (n = 3,017) and the infogene (n = 676) cohorts, which were further combined, leading to a larger cohort of 3,693 individuals. Association testing was performed by general linear models in the obesity cohort and validated by joint analysis in the combined cohort. Results rs9661614 and rs485660 were significantly associated with hip circumference (HC) in the obesity cohort, with heterozygotes exhibiting a significantly lower HC. These results were validated by joint analysis for rs9661614 (false discovery rate [FDR]‐corrected P = 7.5 × 10−4) and, to a lesser extent, for rs485660 (FDR corrected P = 3.9 × 10−2). The association with HC remained significant for rs9661614 when tested independently in women (FDR‐corrected P = 1.7 × 10−2), but not for rs485660 (FDR‐corrected P = 0.2). Both associations were absent in men. Conclusions This study reveals strong evidence for a novel association between rs9661614 (T>C) and HC in women, which likely reflects a preferential association of SYPL2 to a gynoid profile of fat distribution. The study findings support a clinical significance of SYPL2 worth considering when assessing risk factors associated with obesity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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; 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".