Gene Expression Changes in Adipose Tissue with Diet- and/or Exercise-Induced Weight Loss
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Bibliographic record
Abstract
Adipose tissue plays a role in obesity-related cancers via increased production of inflammatory factors, steroid hormones, and altered adipokines. The impact of weight loss on adipose tissue gene expression may provide insights into pathways linking obesity with cancer risk. We conducted an ancillary study within a randomized trial of diet, exercise, or combined diet + exercise versus control among overweight/obese postmenopausal women. In 45 women, subcutaneous adipose tissue biopsies were conducted at baseline and after 6 months, and changes in adipose tissue gene expression were determined by microarray with an emphasis on prespecified candidate pathways as well as by unsupervised clustering of more than 37,000 transcripts (Illumina). Analyses were conducted first by randomization group and then by degree of weight change at 6-months in all women combined. At 6 months, diet, exercise, and diet + exercise participants lost a mean of 8.8, 2.5, and 7.9 kg (all P < 0.05 vs. no change in controls). There was no significant change in candidate gene expression by intervention group. In analysis by weight change category, greater weight loss was associated a decrease in 17β-hydroxysteroid dehydrogenase-1 (HSD17B1, Ptrend < 0.01) and leptin (LEP, Ptrend < 0.01) expression, and marginally significant increased expression of estrogen receptor-1 (ESR1, Ptrend = 0.08) and insulin-like growth factor-binding protein-3 (IGFBP3, Ptrend = 0.08). Unsupervised clustering revealed 83 transcripts with statistically significant changes. Multiple gene expression changes correlated with changes in associated serum biomarkers. Weight loss was associated with changes in adipose tissue gene expression after 6 months, particularly in two pathways postulated to link obesity and cancer, that is, steroid hormone metabolism and IGF signaling. Cancer Prev Res; 6(3); 217-31. ©2013 AACR.
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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) | 0.003 | 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 it