Association between the FTO rs9939609 polymorphism and the metabolic syndrome in a non-Caucasian multi-ethnic sample
Bibliographic record
Abstract
BACKGROUND: The rs9939609 T>A single-nucleotide polymorphism (SNP) in the FTO gene has previously been found to be associated with obesity in European Caucasian samples. The objective of this study is to examine whether this association extends to metabolic syndrome (MetS) and applies in non-Caucasian samples. METHODS: The FTO rs9939609 SNP was genotyped in 2121 subjects from four different non-Caucasian geographical ancestries. Subjects were classified for the presence or absence of MetS according to the International Diabetes Federation (IDF) and National Cholesterol Education Program Adult Treatment Panel (NCEP ATP) III definitions. RESULTS: Carriers of > or = 1 copy of the rs9939609 A allele were significantly more likely to have IDF-defined MetS (35.8%) than non-carriers (31.2%), corresponding to a carrier odds ratio (OR) of 1.23 (95% confidence interval [CI] 1.01 to 1.50), with a similar trend for the NCEP ATP III-defined MetS. Subgroup analysis showed that the association was particularly strong in men. The association was related to a higher proportion of rs9939609 A allele carriers meeting the waist circumference criterion; a higher proportion also met the HDL cholesterol criterion compared with wild-type homozygotes. CONCLUSION: Thus, the FTO rs9939609 SNP was associated with an increased risk for MetS in this multi-ethnic sample, confirming that the association extends to non-Caucasian population samples.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".