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Enregistrement W4410347140 · doi:10.1097/cm9.0000000000003548

Inflammatory bowel disease is a conundrum

2025· article· en· W4410347140 sur OpenAlexaffabout
Consolato Sergi

Notice bibliographique

RevueChinese Medical Journal · 2025
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueInflammatory Bowel Disease
Établissements canadiensChildren's Hospital of Eastern OntarioUniversity of AlbertaUniversity of Ottawa
Organismes subventionnairesnon disponible
Mots-clésInflammatory bowel diseaseMedicineDiseaseGastroenterologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

To the Editor: Inflammatory bowel disease (IBD) is increasing worldwide. Since the first reported patient in China in 1956, the rate has increased and has been an overwhelming challenge for public health. Nutrition and IBD are confusing because the individual patients’ lifestyles, environments, and microbiomes differ. Here, we emphasize the microbiome, the genetic landscape, and the nutritional factors associated with IBD. Dietary factors, microbiomes, and genetic susceptibilities may play a role in determining how this disease represents a puzzle in medicine.[1] Although overlaps are well known, Crohn’s disease (CD) and ulcerative colitis (UC) are the two primary diagnoses identifiable in IBD. As observed by Yang and Qian[2] recently, there is a geographic gradient in China, with UC more prevalent in the northern region and CD more commonplace in the southern region, and temporal trends up to 2030 are pretty alarming. Gut microbiome and genetics: The gut microbiome comprises over 100 trillion microbial organisms, including bacteria, fungi, viruses, and protozoa, and most intestinal bacteria are classified into four phyla: Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria, with Firmicutes and Bacteroidetes predominating in healthy adults. The gut microbiome is essential for various aspects of host homeostasis, including nutrition, immune development, metabolism, and pathogen defense. IBD is believed to arise from the disarrayed interplay of environmental, microbial, and immune-mediated variables in a genetically predisposed host [Supplementary Figure 1, https://links.lww.com/CM9/C376].[3,4] Numerous genetic changes linked to IBD pertain to immune function, particularly the interactions between the immune system and the microbiota. The genes encompass nucleotide oligomerization domain 2 (NOD2), autophagy-related 16-like 1 (ATG16L1), caspase recruitment domain-containing protein 9 (CARD9), and C-type lectin domain family 7 member A (CLEC7A). NOD2 encodes an intracellular pattern recognition receptor that engages with the peptidoglycan present in both gram-positive and gram-negative bacteria. NOD2 is expressed in intestinal epithelial cells, is a defensive factor against intracellular bacteria, and contributes to the immune response to commensal microbes. In murine models of colitis, NOD2-deficient mice have an altered microbiome with increased susceptibility to colitis compared with wild-type (WT) mice. In addition, bacteria that are typically commensal, such as Bacteroides vulgatus, have been associated with alterations in mucosal barrier function and expression of inflammatory genes in NOD2 mice, with resolution of mucosal barrier function and a decrease in inflammatory cytokines with elimination of this bacterium. In human subjects, mutations in NOD2 are associated with reduced levels of interleukin (IL)-10, an anti-inflammatory cytokine, and increased numbers of mucosa-associated bacteria. Patients with NOD2 mutations have a microbiota characterized by a decreased abundance of Faecalibacterium species and an increased abundance of Escherichia species. In patients with CD, NOD2 is associated with ileal disease, an increased risk of postoperative recurrence after ileocecal resection, and a more aggressive fistulizing and fibrostenotic disease phenotype. ATG16L1 regulates the autophagy pathway, facilitates lysosomal degradation, and eliminates intracellular bacteria. NOD2 engages with ATG16L1 at the protein level by directing it to the plasma membrane at bacterial invasion sites. Genetic mutations in either NOD2 or ATG16L1 in individuals with CD disrupt their interaction, thereby hindering bacterial clearance and antigen presentation. CARD9 is associated with the adaptor protein caspase recruitment domain, which is implicated in Dectin-1 (CLEC7A) signaling. Dectin-1 is a pattern-recognition protein receptor that identifies fungal cell wall components. CARD9 signaling is activated upon the detection of fungal ligands by Dectin-1. Modifications in CLEC7A have been linked to medically refractory UC. CARD9 is essential for producing inflammatory cytokines responding to specific bacterial stimuli and viral infections. IL-6, TNF-α, and IL-1β are cytokines reliant on CARD9 function and protect against fungal infections. CARD9 knockout mice exhibit increased susceptibility to Candida albicans, Aspergillus fumigatus, and Cryptococcus neoformans, among other fungi. In humans, inherited CARD9 deficiency has been associated with the onset of invasive Candida species infections in the central nervous system and digestive tract of otherwise healthy individuals. The absence of CARD9 correlates with a reduction in T helper (Th17) cells, which is crucial for maintaining mucosal barrier integrity and facilitating pathogen clearance at mucosal surfaces. Animal models: Murine models serve as valuable instruments for studying the pathophysiology and etiology of human IBD. Although much evidence has illustrated the significant functions of dysbiosis in the etiology of IBD, the specific methods by which intestinal bacteria contribute to illness development remain inadequately elucidated [Supplementary Table 1, https://links.lww.com/CM9/C376]. The advancement of contemporary biotechnology in animal models has elucidated the intricacy and mysteriousness of IBD. Multiple murine models of IBD have been established, including the chemically induced dextran sodium sulfate (DSS) model, the 2,4,6-trinitrobenzene sulfonic acid (TNBS) model, the acetic acid model, and the Citrobacter rodentium (C. rodentium) model of infectious colitis, aimed at enhancing understanding and expanding therapeutic alternatives.[4] Alipour et al[5] applied grading and quantification to terminal ileum (TI) samples from pediatric IBD subgroups and non-IBD disease controls. Immunofluorescence was used to evaluate the mucosal barrier for mucin (MUC2), immunoglobulin (Ig)A, IgG, and total bacteria (fluorescence in situ hybridization [FISH probe EUB338]). The investigators targeted the makeup of the active mucosa-associated microbiota through sequencing using 16S rRNA amplicon produced from total RNA. Patients with UC showed ileal barrier depletion, as evidenced by decreased mucin and mucin-containing goblet cell production and changed expression of NOD-like receptor family pyrin domain containing 6 (NLRP6) on epithelial cells. IgA and IgG-coated bacteria were able to pierce the TI mucin layer in both UC patients with normal histology and CD patients with ileitis. Dietary factors: The role of diet in shaping the gut microbiome is complex and complicated. The consumption of ultra-processed food may predict active symptomatic disease in some IBD cohorts.[1] Colonic microorganisms ferment non-digestible carbohydrates (fiber and resistant starch), while digestible carbs are broken down in the small intestine.[1] Dietary fibers can be toxic in some circumstances. Still, they can also create gasses, lactate, and short-chain fatty acids (SCFAs), all produced during fermentation, with numerous positive physiological consequences. Low SCFA production is seen mainly in UC. This IBD is associated with the absence of bacteria that produce SCFAs and suggests a potential benefit of fermentable fibers in UC. The administration of β-fructan fibers improved moderate UC and was linked to a higher production of SCFA (butyrate). Since many IBD patients report sensitivity to fiber consumption, the generally beneficial effects of fibers related to fermentation and SCFA production have outweighed any potential drawbacks. Ignoring or misinterpreting this process can result in exclusion diets that eliminate non-digestible fibers. These exclusion diets can alleviate symptoms, but they may also deprive patients of the advantages of fibers, which are particularly significant for patients with IBD. The prebiotic potential of β-fructan fibers, which promotes the growth of “beneficial microbes”, has drawn attention to the role of fiber fermentation in IBD. However, the role of microbiota and the fiber fermentation processes, and their potential benefits or drawbacks, are still poorly understood despite the increased research on the subject. The dietary fibers and the components of microorganisms’ cell walls (such as fungal β-[1,3] glucans) are structurally characterized as polymers of more than three sugars (fructooligosaccharides [FOS] has approximately eight sugars, while grain β-d-glucan approximately three sugars) and as many as 50–100 sugars (inulin; fungal β-[1,3] glucan). These can differ in their degree of polymerization, branching, solubility, and interactions with host cells. The immune system’s reaction to polysaccharides on the surface of fungal cells suggests a potential connection between inflammation and whole unfermented fibers. β-(1,3) glucan interacts with immune cells (like macrophages) on the surface of fungi (like zymosan and curdlan) to induce pro-inflammatory antifungal immunity through Dectin-1 and toll-like receptor (TLR) 2. Likewise, β-fructan fibers, such as FOS and inulin, trigger inflammatory pathways mediated by TLRs. Dietary fibers may stay intact, interact with host cell receptors, and increase gut inflammation in patients with decreased fiber-fermenting bacteria (such as those with IBD). Certain fibers may probably be harmful to individuals without fermentative microbes (such as those with IBD, other chronic illnesses, or prolonged antibiotic use), as there may be more opportunities for interactions between the luminal contents and host immune cells. It may be due to a disruption of the epithelial barrier. When consumed by those with a high fermentative capacity, these same fibers provide health benefits. Breastfeeding has been shown to positively affect the development of IBD and medical and public health practice. Moreover, breastfeeding duration was found to have a dose-dependent association. The most robust reduction in risk for CD and UC occurs when breastfeeding lasts for at least 12 months instead of 3 months or 6 months, which confirms ineluctably the protective effect of breastfeeding against the development of IBD. The Mediterranean diet, known for its low consumption of refined carbohydrates, saturated fats, dairy products, and red meat, positively affects the balance of microorganisms in the intestine and the strength of the intestinal barrier. It has also been linked to a lower risk of type 2 diabetes in older individuals, allowing them to live longer and healthier lives. Using probiotics and prebiotics can also help combat age-related inflammation. Probiotics, such as Lactobacillus and Bifidobacteria, are live microorganisms that can be consumed to support overall health. More specifically, probiotics help improve intestinal barrier function and regulate immune responses by modifying the composition of the intestinal microbiome. However, whether the acidic conditions of the stomach allow probiotics to survive long enough to pass into the intestine is still debated. Finally, prebiotic fiber-containing food, like bananas and oatmeal, is rich in prebiotic fibers, which can notably help reduce inflammation. There may be different aspects of diets in IBD cohorts, and IBD patients may respond differently to each diet. Thus, a constant microbiome investigation and periodic screening of IBD patients may be helpful. In conclusion, the future of IBD management is ambiguous, but several tools have improved our approach to this fuzzy and mysterious disease. Predictably, artificial intelligence may help discern the IBD phenotypes puzzle. Although currently considered unpractical, new methodologies can become useful shortly in assessing the microbiome instantly, and nanotechnologies may deliver prebiotics on specific sites that can promptly help some areas of the bowel heal. Funding This research has been funded by the generosity of the Children’s Hospital of Eastern Ontario, Ottawa, Ontario, and the Stollery Children’s Hospital Foundation and supporters of the Lois Hole Hospital for Women through the Women and Children’s Health Research Institute (WCHRI, No. 2096), Natural Science Foundation of Hubei Province for Hubei University of Technology (100-Talent Grant for Recruitment Program of Foreign Experts Total Funding: Digital PCR and NGS-based diagnosis for infection and oncology, 2017-2022), Österreichische Krebshilfe Tyrol (Krebsgesellschaft Tirol, Austrian Tyrolean Cancer Research Institute, 2007 and 2009–“DMBTI and cholangiocellular carcinomas” and “Hsp70 and HSPBP1 in carcinomas of the pancreas”), Austrian Research Fund (Fonds zur Förderung der wissenschaftlichen Forschung, FWF, No. L313-B13), Canadian Foundation for Women’s Health (“Early Fetal Heart-RES0000928”), Cancer Research Society (von Willebrand factor gene expression in cancer cells), Canadian Institutes of Health Research (Omega-3 Fatty Acids for Treatment of Intestinal Failure Associated Liver Disease: A Translational Research Study, 2011–2014, CIHR 232514), and the Saudi Cultural Bureau, Ottawa, Canada. The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,119
Score d'incertitude au seuil0,762

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,003
Tête enseignante GPT0,255
Écart entre enseignants0,252 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission2
Résumé présentoui

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