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Abstract A15: Prenatal exposure to polycyclic aromatic hydrocarbons and breast tissue composition in adolescent girls

2020· article· en· W3047203139 on OpenAlexaff
Rebecca D. Kehm, Lothar Lilge, E. Jane Walter, Nur Zeinomar, Jasmine A. McDonald, Parisa Tehranifar, Julie B. Herbstman, Rachel L. Miller, Mary Beth Terry

Bibliographic record

VenueCancer Prevention Research · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBreast cancerPregnancyMedicineCohortCohort studyPhysiologyObstetricsCancerInternal medicineBiologyGenetics

Abstract

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Abstract Polycyclic aromatic hydrocarbons (PAH) are common environmental pollutants that result from incomplete combustion of biomass and fossil fuels. PAH have endocrine-disrupting properties and are known animal carcinogens. Evidence from case-control studies suggests an association between PAH and breast cancer risk, but longitudinal research on PAH exposure during critical windows of susceptibility, such as prenatally and in early life, is limited. The purpose of this study was to prospectively examine whether prenatal exposure to PAH is associated with breast tissue composition, an intermediate marker of breast cancer risk, in adolescent girls. We studied 105 adolescent girls in the Columbia Center for Children’s Environmental Health (CCCEH) birth cohort, which recruited nonsmoking African American and Dominican American pregnant women living in three low-income neighborhoods in New York City from 1998-2006. Women wore a small backpack holding a personal air monitor for 2 consecutive days during the 3rd trimester of pregnancy, which measured concentrations of pyrene and 8 other carcinogenic PAH (summed and categorized into tertiles for analysis). Girls completed a follow-up clinic visit in adolescence (ages 11.2-19.6 years, median=15.8), at which time breast tissue composition was measured by optical spectroscopy (OS). OS is a novel and noninvasive tool that provides a broad compositional view of the breast by capturing variation in the amount of water, lipid, oxy-hemoglobin, deoxy-hemoglobin, and collagen, as well as overall cellular and connective tissue density. OS measured red and near-infrared light transmission of 7 wavelengths (650-1060 nm) at 4 source-detector distances in each breast quadrant, resulting in 16 overlapping tissue volumes. Principal component analysis was used to reduce spectral data and generate principal component (PC) scores for each participant, which were averaged over both breasts. We used multivariable linear regression to examine associations of prenatal PAH measures (pyrene and Σ8 PAH) with each of the first 4 OS PCs, which explained >99% of the spectral variation in the sample. Models were adjusted for age, ethnicity, body mass index (BMI) at time of OS measurement, age at breast development, and mothers’ prepregnancy BMI. After adjusting for covariates, PC1 scores were significantly lower on average in the highest compared to lowest tertile of prenatal ambient Σ8 PAH (β = -0.42, 95% CI = -0.81 to -0.02, p = 0.04). PC1 covered 91.8% of the spectral variations and represents overall light attenuation from higher scattering due to higher cellularity and connective tissues. PC1 also mapped to multiple chromophores including hemoglobin and collagen. No associations were found between prenatal ambient Σ8 PAH and PCs 2-4, and no associations with OS PCs were found for pyrene. To conclude, we found evidence suggesting that prenatal exposure to PAH is associated with breast tissue composition in adolescent girls. Citation Format: Rebecca D. Kehm, Lothar Lilge, E. Jane Walter, Nur Zeinomar, Jasmine A. McDonald, Parisa Tehranifar, Julie B. Herbstman, Rachel L. Miller, Mary Beth Terry. Prenatal exposure to polycyclic aromatic hydrocarbons and breast tissue composition in adolescent girls [abstract]. In: Proceedings of the AACR Special Conference on Environmental Carcinogenesis: Potential Pathway to Cancer Prevention; 2019 Jun 22-24; Charlotte, NC. Philadelphia (PA): AACR; Can Prev Res 2020;13(7 Suppl): Abstract nr A15.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.372
Teacher spread0.315 · 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 teacher head, 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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