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Record W4323353105 · doi:10.1093/jcag/gwac036.005

A5 A MOUSE MODEL TO UNRAVEL THE PATHOPHYSIOLOGICAL LINK BETWEEN CROHN’S DISEASE AND TYPE-2 DIABETES-ASSOCIATED METABOLIC DISORDERS

2023· article· en· W4323353105 on OpenAlexaff
T Mukherjee, J Yadav, N Nathan, D Tsang, Allie Yan, S Cash, C Cummins, Paraskevi A. Vlachou, S Girardin, D Philpott

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPathogenesisDysbiosisNOD2InflammationImmunologyType 2 diabetesDiseaseCrohn's diseaseMedicineInflammatory bowel diseaseDiabetes mellitusPathophysiologyBioinformaticsGut floraBiologyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Abstract Background Crohn’s disease (CD), an idiopathic inflammatory bowel disease (IBD), has been recently shown to increase the risk of developing type 2 diabetes (T2D). Moreover, treatment with anti-diabetic drugs has a protective role in preventing the severity and course of CD progression. However, the pathophysiological basis of T2D development in CD remains unclear. Findings have highlighted the contribution of adipose tissue (AT) to the development of chronic inflammatory diseases and have identified parallels between T2D and CD that may provide hints to common mechanisms of disease pathogenesis. Typically, microbial dysbiosis, hyperpermeable intestinal barrier, and intra-abdominal AT accumulation are the common features of both diseases, yet how the interplay of these factors contribute to pathogenesis is not known. Therefore, common pathogenic paradigms underlying both T2D and CD have led us to hypothesize that chronic intestinal inflammation serves as an initiator of AT dysfunction in CD, predisposing individuals to T2D. Further, the lack of appropriate animal models of CD with chronic intestinal inflammation that manifests accumulation of intra-abdominal AT, and extra-intestinal metabolic disorder as observed in CD and T2D patients has been a limitation. Purpose To develop a genetic mouse model to investigate if gut inflammation-mediated microbial dysbiosis and metabolic dysregulation of AT are at the nexus that cause T2D in CD. Method We developed a CD-mouse model, where we challenged Nod2-deficient mice (NOD2 being the strongest genetic risk factor contributing to CD) with a chronic inflammatory insult regime, using dextran sulfate sodium (cDSS) for 3 cycles. Subsequently, intraperitoneal insulin and oral glucose tolerance tests, metabolic caging, and MRI imaging of mice were performed. Changes in AT metabolism and microbial infiltration into AT were analyzed by quantitative real-time PCR (qRT-PCR) and/or immunohistochemistry (IHC). Result(s) Our new CD-mouse model revealed increased gut inflammation (TNF and type-I IFN) in Nod2-deficient mice compared to wild-type control mice post-cDSS. Surprisingly, Nod2-deficient mice gained body weight, which was at least in part accounted for by an increased intra-abdominal AT accumulation along with decreased AT fatty-acid metabolism (Cpt1a, Fabp4 expression) and AT browning (Ucp1, Cidea expression, and UCP-1 staining), reduced intestinal goblet cell numbers, increased gut bacterial infiltration within the fat, more insulin resistance and energy expenditure. Conclusion(s) This experimental mouse model mimicking CD-associated T2D will provide insights into how the microbiome-AT axis fuel chronic inflammation-mediated extra-intestinal metabolic disorder and immune dysregulation. Understanding these connections will be transformative, as it will help us devise novel therapeutic strategies to prevent T2D development in progressive CD patients. Disclosure of Interest None Declared

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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 designBench or experimental
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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Citations1
Published2023
Admission routes1
Has abstractyes

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Same venueJournal of the Canadian Association of GastroenterologySame topicInflammatory Bowel DiseaseFrench-language works237,207