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Record W4391520434 · doi:10.1101/2024.02.02.24301815

Evaluating the causal impact of reproductive factors on breast cancer risk: a multivariable mendelian randomization approach

2024· preprint· en· W4391520434 on OpenAlexfundno aff
Claire Prince, Laura D Howe, Eleanor Sanderson, Gemma C. Sharp, Abigail Fraser, Bethan Lloyd‐Lewis, Rebecca C. Richmond

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsnot available
FundersMedical Research CouncilGovernment of CanadaUniversity of BristolCancer Research UKCanadian Institutes of Health ResearchGray FoundationGenome CanadaFondation du cancer du sein du QuébecNational Institutes of HealthOvarian Cancer Research FundElizabeth Blackwell Institute for Health Research, University of BristolBritish Heart FoundationWellcome TrustEuropean CommissionBreast Cancer Research Foundation
KeywordsMendelian randomizationBreast cancerMultivariable calculusMedicineCausal inferenceRandomizationCancerOncologyGynecologyRandomized controlled trialInternal medicineBiologyGeneticsGenetic variantsGeneEngineeringPathology

Abstract

fetched live from OpenAlex

Abstract Background Observational evidence proposes a protective effect of having children and an early age at first birth on the development of breast cancer, however the causality of this association remains uncertain. In this study we assess whether these reproductive factors impact breast cancer risk independently of age at menarche, age at menopause, adiposity measures and other reproductive factors that have been identified as being causally related to or genetically correlated with the reproductive factors of interest. Methods We used genetic data from UK Biobank (273,238 women) for reproductive factors, age at menarche and menopause, and adiposity measures, and the Breast Cancer Association Consortium for risk of overall, estrogen receptor (ER) positive and negative breast cancer as well as breast cancer subtypes. We applied univariable and multivariable Mendelian randomization (MR) to estimate direct effects of ever parous status, ages at first birth and last birth, and number of births on breast cancer risk. Results We found limited evidence of an effect of age at first birth on overall or ER positive breast cancer risk in either the univariable or multivariable analyses. While the univariable analysis revealed an effect of later age at first birth decreasing ER negative breast cancer risk (Odds ratio (OR): 0.76, 95% confidence interval:0.61-0.95 per standard deviation (SD) increase in age at first birth), this effect attenuated with separate adjustment for age at menarche and menopause (e.g., OR 0.83, 0.62-1.06 per SD increase in age at first birth, adjusted for age at menarche). In addition, we found evidence for an effect of later age at first birth on decreased human epidermal growth factor receptor 2 enriched breast cancer risk but only with adjustment for number of births (OR 0.28 (0.11-0.57) per SD increase in age at first birth). We found little evidence for direct effects of ever parous status, age at last birth or number of births on breast cancer risk, however, analyses of ever parous status and age at last birth were limited by weak instruments in the multivariable analysis. Conclusions This study found minimal evidence of a protective effect of earlier age at first birth on breast cancer risk, while identifying some evidence for an adverse effect on ER negative breast cancer risk. However, multivariable MR of ever parous status and age at last birth is limited by weak instruments which might be improved in future studies with larger sample sizes and when additional genetic variants related to reproductive factors are identified.

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 imitation

Not 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.

metaresearch head score (Codex)0.051
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.269

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0510.099
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.045
GPT teacher head0.368
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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