Abstract 4258: Influence of lifestyle factors on adipocyte size in human breast tissue
Bibliographic record
Abstract
Abstract Background: Accumulating epidemiological studies positively associate healthy body mass index (BMI) and higher physical activity with lowered risk of postmenopausal breast cancer. Many of the proposed biomarkers underlying these associations, such as insulin, inflammatory markers, steroid hormones, and adipokines, are produced or regulated by adipose tissue. However, the biological impact of lifestyle factors at the level of the breast tissue, particularly adipose tissue in the breast, is unclear and may play a role in the etiology of breast cancer. Methods: Using a cross-sectional design, we examined the impact of demographic and lifestyle factors on histological features of breast adipose tissue. Women (age) undergoing reduction mammoplasty surgery were consented to collection of their cancer-free breast tissue at the time of surgery. An adipose rich section of the sample was dissected under sterile conditions and formalin fixed. Samples were sectioned at 7 µm thickness and stained with hematoxylin and eosin. The stained sections were imaged and mean adipocyte size was determined as diameter (µm) from 3 randomly selected areas at 10X magnification and each sample was scored by two independent assessors using Image J software. BMI status documented at the time of surgery was abstracted form medical records. A subset of women completed an additional visit where percent total body fat was measured by air displacement plethysmography and aerobic fitness (VO2peak) was measured by a maximal graded exercise test with expired gas collection. The association between adipocyte size and demographic/lifestyle factors was examined using multivariate linear regression adjusted for age and menopausal status. Results: Participants (n=42) were primarily Caucasian (77%) and pre/peri-menopausal (62%), with a mean age of 44.6±12.9 years (range 19-70) and mean BMI of 27.7±5.1 kg/m2 (range 19.1-37.4). Adipocyte size was associated with BMI (per 5 kg/m2 increase, β = 5.6±2.15, p=0.01) and number of pregnancies (β = 6.04±2.34, p=0.02), but not age (β = 0.1±0.3, p=0.81). In the subset of participants who completed an additional study visit (n=9), there was a trend towards an inverse association between adipocyte size and aerobic fitness (per 2 ml/kg/min of O2 consumption, β = -3.54±1.52, p=0.07) and percent body fat (per 2% increase, β = 1.94±1.28, p=0.17) in unadjusted analyses. Conclusion: Higher BMI is associated with larger adipocyte size in adipose tissue taken from the breast, suggesting a biological role for body composition in influencing gross histological features of adipocytes and its behavior that would impact the health of the mammary gland. A better understanding of the biological mechanisms underlying the observed epidemiological associations are needed to guide the development of intervention strategies and the most effective public health messages for breast cancer prevention. Citation Format: Kristin L. Campbell, Nagarajan Kannan, Sarah E. Neil-Sztramko, Connie J. Eaves, Jonathan P. Little, Ilona Csizmadi, David Zhu, Sarah Sayyari, Kelcey Bland, James D. Johnson. Influence of lifestyle factors on adipocyte size in human breast tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4258. doi:10.1158/1538-7445.AM2017-4258
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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 | 0.000 |
| 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 | 0.001 |
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".