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A Novel Index of Early-life Growth Conditions Moderates Susceptibility to Later-life Cigarette Smoking-associated Airflow Obstruction and Systemic Inflammation

2025· article· en· W4410277021 on OpenAlexaff
Yige Bao, R. Goldman-Pham, Qing Duan, James C. Engert, Benjamin M. Smith

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsMcGill University Health CentreQueen's UniversityMcGill University
Fundersnot available
KeywordsMedicineSystemic inflammationCigarette smokingInflammationInternal medicine

Abstract

fetched live from OpenAlex

Abstract Rationale: Early-life growth conditions and later-life cigarette smoking are major pathways to chronic obstructive pulmonary disease (COPD), but whether these factors interact is poorly understood. Attained height is determined in part by early-life growth conditions and by genetics, and the difference between attained and genotype-predicted height (height-GaP) is a prospectively validated index of early-life growth conditions. This study sought to investigate whether height-GaP moderates susceptibility to cigarette smoking-associated airflow obstruction and systemic inflammation. Methods: UKBiobank is cohort of community-dwelling adults 40-69 years old at enrolment. Participants completed standardised assessments of anthropometry, smoking behaviours, genotyping, spirometry and serum C-reactive protein concentration (CRP). Genotype-predicted height was calculated using a polygenic height score derived from individual genotype data. Airflow obstruction was defined using pre-bronchodilator FEV1/FVC <0.70. Regression models of airflow obstruction prevalence and CRP were fit with 10+ pack-years and current smoking status as the respective independent variables of interest. Moderation of these associations by height-GaP were assessed by including a height-GaP product term in each model and were additionally adjusted for age, age2, sex, principal components of genetic ancestry, and genotype-predicted height. Results: Among 293,018 adults with quality-verified spirometry, height, genotype and pack-year data (mean±SD age 56±8 years, 54.2% female, 27.4% smoked 10+ pack-years, 15.9% airflow obstruction prevalence), 10+ pack-years of cigarette smoking was associated with 10.3% excess airflow obstruction prevalence, but this association varied with height-GaP (p-interaction=4.35e-06). Smoking 10+ pack-years in the lowest height-GaP quintile (i.e., largest height deficit) was associated with 12.2% excess airflow obstruction prevalence compared to 8.7% excess airflow obstruction prevalence in the highest height-GaP quintile (Figure 1a) – a +40% relative excess of airflow obstruction prevalence. Among 461,108 adults with serum CRP, height, genotype and smoking status data (mean±SD age 56±8 years, 54.2% female, 10.5% current smokers, median (IQR) serum CRP 1.33 (0.66-2.76) mg/L), current smoking was associated with +0.84 mg/L higher CRP concentration, but this association varied with height-GaP (p-interaction=1.05e-12). Current smoking in the lowest height-GaP quintile (i.e., largest height deficit) was associated with +1.06 mg/L higher CRP concentration compared to +0.62 mg/L higher CRP in the highest quintile – a +70% relative increment in serum CRP concentration (Figure 1b). Conclusion: Early-life growth conditions, quantified as the difference between attained height and genotype-predicted height, appear to moderate susceptibility to cigarette smoking-associated airflow obstruction and systemic inflammation. These findings suggest that early-life conditions that affect growth may alter later-life susceptibility to pro-inflammatory stimuli and associated health outcomes.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.313
Teacher spread0.294 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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