Common Variants in <i>FTO, MC4R, TMEM18, PRL, AIF1</i>, and <i>PCSK1</i> Show Evidence of Association With Adult Obesity in the Greek Population
Bibliographic record
Abstract
Twenty-four single-nucleotide polymorphisms (SNPs) have been reproducibly associated with obesity. We performed a follow-up study for obesity in the Greek adult population. A total of 510 obese and 469 lean adults were genotyped for 24 SNPs. We tested the association with obesity status using logistic regression and we evaluated the combined genetic risk of 24 SNPs by calculating the area under the receiver-operating characteristic (ROC) curves. We nominally replicated the association with obesity (BMI ≥30 kg/m(2)) of six SNPs in or near the FTO, MC4R, TMEM18, PRL, AIF1, and PCSK1 loci (1.28 ≤ odds ratio (OR) ≤ 1.35; 0.004 ≤ P ≤ 0.043). The discrimination ability for obesity was slightly stronger (P = 9.59 × 10(-6)) when the genetic information of the 24 SNPs was added to nongenetic risk factors (area under the curve (AUC) = 0.722) in comparison with nongenetic factors analyzed alone (AUC = 0.685). Our data suggest that SNPs in or near the FTO, MC4R, TMEM18, PRL, AIF1, and PCSK1 loci contribute to obesity risk in the Greek population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".