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Record W4391161448 · doi:10.1093/ecco-jcc/jjad212.1299

P1169 Multimorbidity and Disease Trajectories in Patients with INFLAMMATORY BOWEL DISEASES: Insights from Observational and Genetic Analyses

2024· article· en· W4391161448 on OpenAlexaff
Feng Jiang, Jun Zhao, Jihong Chen, Lili Wang, Shuai Yuan, Rahul Kalla, Judith Wellens, Jan Krzysztof Nowak, S Larrson, Jonas F. Ludvigsson, Jack Satsangi, Evropi Τheodoratou, Xinyu Li

Bibliographic record

VenueJournal of Crohn s and Colitis · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsInflammatory bowel diseaseObservational studyMedicineDiseaseInflammatory Bowel DiseasesMultimorbidityIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background The multi-morbidity pattern of inflammatory bowel disease (IBD) remains under-explored. We integrated both observational and genetic data to elucidate multisystem comorbidities and health consequences of IBD. Methods Phenome-wide association study (PheWAS) based on the international classification of disease (ICD)-diagnosed IBD was conducted to explore its associations with 1,053 unique clinical outcomes in the UK Biobank. Disease trajectory analyses were implemented to illustrate sequential patterns of IBD-related comorbidities. The associations of genetic liability to IBD proxied by a polygenic score with identified clinical outcomes were examined to strengthen causality (N=385,917). To investigate potential shared genetic bases and causality, we performed a cross-trait linkage disequilibrium score regression (LDSC) and two-sample Mendelian randomization (TSMR) analysis using the FinnGen biobank (N=377,277). The impact of IBD subtypes and the age at diagnosis were also evaluated in sensitivity analyses. Results A total of 5,782 cases with IBD (3,940 cases with UC and 1,800 cases with CD) were diagnosed at baseline in the UK Biobank. Observational PheWAS revealed elevated risks of all-cause mortality with HRs of 1.34 (95%CI=1.24-1.45, P<0.001), 1.61 (95%CI=1.41-1.83, P<0.001) and 1.22 (95%CI=1.10-1.34, P<0.001) for patients with IBD, CD or UC respectively. Increased mortality risk was noted across pediatric, early-onset, and later-onset IBD patients. Sequential patterns of IBD-related comorbidities were primarily found in cardiometabolic, respiratory, digestive and autoimmune diseases. The polygenic PheWAS, LDSC and TSMR analyses supported both strong genetic correlations and causal associations of IBD with immune-mediated (notably psoriatic arthropathies, psoriasis, dermatitis, asthma) as well as non-autoimmune diseases ( pneumonia, anemias, and renal failure). Conclusion Our observational and genetic analyses suggest multisystem comorbidities and consequences of IBD, highlighting the need for multidisciplinary clinical management and investigation of shared biologically or genetically regulated mechanisms in the pathogenesis of IBD.

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)0.004
metaresearch head score (Gemma)0.017
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.013
GPT teacher head0.252
Teacher spread0.239 · 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
Published2024
Admission routes1
Has abstractyes

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