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Record W3138034125 · doi:10.1016/j.cgh.2021.03.021

A Systematic Review of Monogenic Inflammatory Bowel Disease

2021· review· en· W3138034125 on OpenAlexafffund
Ryusuke Nambu, Neil Warner, Daniel J. Mulder, Daniel Kotlarz, Dermot McGovern, Judy H. Cho, Christoph Klein, Scott B. Snapper, Anne M. Griffiths, Itaru Iwama, Aleixo M. Muise

Bibliographic record

VenueClinical Gastroenterology and Hepatology · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of TorontoSickKids FoundationHospital for Sick Children
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsMedicineInflammatory bowel diseaseInflammatory Bowel DiseasesGastroenterologyDiseasePathology

Abstract

fetched live from OpenAlex

Background & AimsAdvances in genomic technologies have led to increasing reports of monogenic inflammatory bowel disease (IBD). Here, we systematically review the literature to determine the clinical features, genetic profile, and previously used treatment strategies in monogenic IBD.MethodsA systematic review of MEDLINE articles published between January 2000 and December 2020 was conducted. A total of 750 individual monogenic IBD cases were identified from 303 eligible articles.ResultsThe most frequently reported monogenic IBD genes were IL10RA/B, XIAP, CYBB, LRBA, and TTC7A. In total, 63.4% of patients developed IBD before 6 years of age, 17.4% developed IBD between ages 10 and 17.9 years, and 10.9% developed IBD after age 18. There was a substantial difference between these age groups and the underlying monogenic disorders. Only 31.7% had any history of extraintestinal comorbidity (EIC) before IBD onset, but 76.0% developed at least 1 EIC during their clinical course. The most common EICs were atypical infection (44.7%), dermatologic abnormality (38.4%), and autoimmunity (21.9%). Bowel surgery, biologic therapy, and hematopoietic stem cell transplantation were performed in 27.1%, 32.9%, and 23.1% of patients, respectively.ConclusionsMonogenic IBD cases, although rare, have varied extraintestinal comorbidities and limited treatment options including surgery and transplant. Early identification and improved understanding of the characteristics of the genes and underlying disease processes in monogenic IBD is important for effective management. Advances in genomic technologies have led to increasing reports of monogenic inflammatory bowel disease (IBD). Here, we systematically review the literature to determine the clinical features, genetic profile, and previously used treatment strategies in monogenic IBD. A systematic review of MEDLINE articles published between January 2000 and December 2020 was conducted. A total of 750 individual monogenic IBD cases were identified from 303 eligible articles. The most frequently reported monogenic IBD genes were IL10RA/B, XIAP, CYBB, LRBA, and TTC7A. In total, 63.4% of patients developed IBD before 6 years of age, 17.4% developed IBD between ages 10 and 17.9 years, and 10.9% developed IBD after age 18. There was a substantial difference between these age groups and the underlying monogenic disorders. Only 31.7% had any history of extraintestinal comorbidity (EIC) before IBD onset, but 76.0% developed at least 1 EIC during their clinical course. The most common EICs were atypical infection (44.7%), dermatologic abnormality (38.4%), and autoimmunity (21.9%). Bowel surgery, biologic therapy, and hematopoietic stem cell transplantation were performed in 27.1%, 32.9%, and 23.1% of patients, respectively. Monogenic IBD cases, although rare, have varied extraintestinal comorbidities and limited treatment options including surgery and transplant. Early identification and improved understanding of the characteristics of the genes and underlying disease processes in monogenic IBD is important for effective management.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.183
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.341
Teacher spread0.317 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations145
Published2021
Admission routes2
Has abstractyes

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