Associations between polymorphisms in leptin and leptin receptor genes and colorectal cancer survival
Bibliographic record
Abstract
Objective: Leptin (LEP) is an obesity-associated adipokine associated with tumor cell growth. We examined the relevance of genetic variants of LEP and leptin receptor (LEPR) to colorectal cancer (CRC) survival by using data from the Newfoundland Familial Colorectal Cancer Study. Methods: A total of 532 patients newly diagnosed with CRC between 1997 and 2003 were followed up until April 2010. Data on their demographics and lifestyles were collected via questionnaires. Genotyping of blood samples was performed with the Illumina Human Omni-Quad Bead chip. Multivariable Cox models were used to assess the relationships of 35 tag single-nucleotide polymorphisms (SNPs) in LEP and LEPR with overall survival (OS), disease-free survival (DFS), and CRC-specific survival. Results: At the gene level, LEP was associated with DFS (P = 0.017), and LEPR was associated with both DFS (P = 0.021) and CRC-specific survival (P = 0.013) in patients with CRC. In single-SNP analysis, LEP rs11763517, LEPR rs9436301, and LEPR rs7602 were associated with DFS after adjustment for multiple testing. The LEPR haplotypes G-C-T (rs7534511-rs9436301-rs1887285) and A-A-G (rs7602-rs970467-rs9436748) were associated with prolonged OS among patients with CRC overall (G-C-T: HR, 0.63; 95% CI, 0.43–0.93; A-A-G: HR, 0.59; 95% CI, 0.38–0.91) and those diagnosed with colon cancer (G-C-T: HR, 0.54; 95% CI, 0.34–0.86; A-A-G: HR, 0.49; 95% CI, 0.29–0.83). Similar results were observed for DFS. Moreover, significant interactions were found among LEPR rs7602 (A vs. G), LEPR rs1171278 (T vs. C), red meat intake, and BMI status: the associations between these variants and prolonged DFS were limited to patients with below-median red meat consumption and body mass index (BMI) < 25 kg/m2. Conclusions: Polymorphic variations in the LEP and LEPR genes were associated with survival of patients after CRC diagnosis. The LEP/LEPR-CRC survival association was modified by participants’ red meat intake and BMI.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".