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Record W4392900933 · doi:10.1093/ecco-jcc/jjae032

Unravelling the Smoke Trail: Maternal Smoking, Childhood Exposure, and their Impact on Inflammatory Bowel Diseases

2024· editorial· en· W4392900933 on OpenAlexaff
Panu Wetwittayakhlang, Péter L. Lakatos

Bibliographic record

VenueJournal of Crohn s and Colitis · 2024
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseInflammatory Bowel DiseasesSmokeEnvironmental healthInternal medicineDisease

Abstract

fetched live from OpenAlex

The impact of maternal smoking and early life exposure to passive smoking in the development of inflammatory bowel disease [IBD] remains a subject of controversy. In an earlier prospective study in 2007, patients with Crohn’s disease [CD] were more likely to have prenatal smoke exposure than controls (odds ratio [OR] 1.72, 95% confidence interval [CI]; 1.1–2.7) and were also more likely to have passive smoke exposure during childhood, with one or both parents or other household members being smokers [OR 2.04, 95% CI; 1.28–3.31].1 However, a meta-analysis conducted in 2008 by Jones D et al. found no strong association between childhood or prenatal passive smoke exposure and IBD.2 Recently, two noteworthy studies on the impact of maternal smoking during pregnancy [MSDP] and childhood smoking exposure on the development of IBD have been published in the current issue of the journal. The first report, conducted by Linmin Hu et al., is entitled ‘Impact of maternal smoking, offspring smoking, and genetic susceptibility on Crohn’s disease and ulcerative colitis’.3 Another study, titled ‘Tobacco smoke exposure in early childhood and later risk of inflammatory bowel disease’ was conducted by Ida Sigvardsson et al. Both reports emphasise the importance of understanding early life exposure to passive smoking in the development of IBD.4 Linmin Hu et al. conducted a comprehensive analysis of associations between maternal smoking, offspring smoking, and genetic susceptibility in relation to the subsequent risk of developing IBD. They used large, prospective, population-based data from the UK Biobank spanning from 2006 to 2010. The study revealed that MSDP increased the risk of offspring developing CD (hazard ratio [HR] 1.18, 95% CI; 1.01–1.39) but not ulcerative colitis [UC] [HR 1.03, 95% CI; 0.92–1.16]. Notably, personal [offspring] smoking behaviour heightened the risk of both CD and UC, with a numerically amplified impact when combined with MSDP. Individuals with a genetic risk and MSDP had an estimated two to three times greater risk of developing CD and UC.3 In the other study, Ida Sigvardsson et al. conducted a prospective Scandinavian birth cohort study spanning from 1997 to 2009, examining the association between early life smoking exposure and a child’s risk of IBD. The study revealed that a higher level of MSDP with an average of ≥6 cigarettes per day, compared with no smoking, resulted in a pooled adjusted HR of 1.60 [95% CI; 1.08–2.38], and was associated with offspring IBD. Additionally, exposure to environmental tobacco smoke in the first year of life was also linked to a later development of IBD, with a pooled adjusted HR of 1.32 [95% CI; 1.03–1.69].4 Based on earlier data, smoking is a well-established environmental factor in the pathogenesis of inflammatory bowel disease [IBD], with the first report dating back to the 1980s. One of the first case-control studies indicated that individuals who smoked before disease onset had a relative risk of developing Crohn’s disease [CD] of 4.8, and those with a current smoking habit had a relative risk of 3.5.5 The meta-analysis in 2006 by Mahid S et al. demonstrated an association between current smoking and CD [OR 1.76, 95% CI; 1.40–2.22] and former smoking and UC [OR 1.79, 95% CI; 1.37–2.34]. Conversely, current smoking exhibited a protective effect on the development of UC compared with non-smokers [OR 0.58, 95% CI; 0.45–0.75].6 Consistent with a recent umbrella review of meta-analyses in 2019 by Piovani D et al., active smoking at diagnosis increased the risk of CD [OR 1.76, 95% CI; 1.40–2.22] but decreased the risk of UC [OR 0.58, 95% CI; 0.45–0.75] compared with non-smokers.7 The impact of smoking differs not only between disease phenotypes [UC and CD] but also varies based on gender, age at diagnosis, and disease location. Smoking’s influence on the disease course has been observed in both CD and UC. Data from the Veszprem population-based, incident cohort spanning from 1977 to 2008 suggested that the effect of smoking may be linked to gender, being more deleterious in male patients, and to the age at diagnosis, with the most prominent impact observed in young adult onset disease. Moreover in CD, smoking habits during the course of the disease were reported to influence a shift in disease behaviour, leading to changes from inflammatory disease to either stenosing or penetrating [OR 2.02, 95% CI; 1.30–3.16]. In UC, smoking was linked to more extensive disease at diagnosis [OR 1.67, 95% CI; 1.12–2.47]. Interestingly, current smoking showed a tendency for a decreased need for colectomy [HR 0.25;, 95% CI; 0.06–1.06] in patients with UC.8 Furthermore, the effect of smoking exhibits ethnicity and geography dependence. The association between smoking and an increased risk of CD is predominantly observed in Western populations.5 Prospective studies conducted in Asian and Jewish populations found no significant association between smoking and CD.9,10 Notably NOD2 mutations, identified as the strongest genetic determinant for CD in Europeans, are not present in Asians.11,12 The mechanisms through which smoking influences IBD appear to be intricate, involving various substances such as nicotine, free radicals, and carbon monoxide. These substances act on adaptive and immune responses, leading to dysfunction of the gastrointestinal mucosa.8 During pregnancy, smoking has been linked to alterations in gut microbiota and differential DNA methylation in the child, potentially contributing to the development of IBD. The impact of smoking on an individual may result from the interplay of different host genetic factors and multiple environmental influences, including antibiotic exposure, urban living, appendectomy, tonsillectomy, oral contraceptive use, and dietary and nutrient factors.7 Recently a large, population-based cohort, studying the time trends of environmental factors in IBD patients over 40 years, demonstrated a significant decrease in the proportions of CD patients with an active smoking habit at diagnosis. The percentage decreased from approximately 60% in the early cohort [1977–1995] to 39% in the recent cohort [2009–2020]. This observation suggests that the relative importance of smoking may have become less in the present era in certain populations, as the rates of smoking at the time of diagnosis have significantly decreased over time, despite the increased incidence and prevalence of IBD.13 In conclusion, the two current papers further strengthen the reported interaction between smoking and IBD. However, the impact of smoking on disease susceptibility or course of IBD may be altered by host genetic factors, sex, age, and ethnicity; as a consequence, the observed net effect of smoking may be variable in different IBD cohorts. Recent data emphasise that this influence extends beyond individual smoking habits, with maternal smoking during pregnancy and early life childhood smoke exposure significantly increasing the risk of IBD in offspring. Furthermore, this risk may be augmented by underlying genetic susceptibility. These new findings suggest that the lasting, long-term consequences of smoking on IBD may be more deleterious than previously believed.

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)0.012
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.017
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.025
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0070.005
Open science0.0050.002
Research integrity0.0170.026
Insufficient payload (model declined to judge)0.0080.005

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 head0.005
GPT teacher head0.234
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2024
Admission routes1
Has abstractno

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