Collaborative Molecular Epidemiology Study of Metabolic Dysregulation, DNA Methylation, and Breast Cancer Risk Among Nigerian Women: MEND Study Objectives and Design
Bibliographic record
Abstract
PURPOSE: To elucidate the role of metabolic dysregulation and associated DNA methylation changes on breast cancer risk and aggressive subtypes among Nigerian women. We describe the design and methods of a collaborative molecular epidemiology study of breast cancer in Nigerian hospitals. METHODS: The Mechanisms for Novel and Established Risk Factors for Breast Cancer in Women of Nigerian Descent (MEND) study was designed as a matched case-control study of 350 patients, age 18 to 75 years, with newly diagnosed, treatment-naïve breast cancer and 350 age-matched healthy controls from surrounding geographic areas. Patients with breast cancer seen for initial diagnosis at four large tertiary hospitals in southwest Nigeria and one affiliated private hospital were recruited. Healthy female controls were selected from a cohort of 4,000 healthy women recruited as part of the Human Heredity and Health (H3) in Africa Chronic Kidney Disease Case-Control Study in Nigeria. Tumor and adjacent normal tissue, and blood and saliva samples were collected for molecular and epigenetic assays. RESULTS: Although recruitment is ongoing, a total of 416 patients have been recruited to date, with tumor and blood samples obtained from at least 310 patients. Data on age-matched (± 6 months) controls have also been obtained and harmonized. Lipid assays for 350 pathologically verified cases and 350 age-matched controls is underway, and pathologic characterization of tumors (including immunohistochemistry for subtyping) is ongoing. Data on DNA methylation for tumors and adjacent normal tissue are expected by the end of the study period. CONCLUSION: The MEND study will provide a unique, high-quality source of data to evaluate the contribution of metabolic dysregulation such as obesity, diabetes, hypertension, and metabolic syndrome to the biology of breast cancer among Nigerian women and foster collaborative studies relevant for women of African descent globally.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".