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Enregistrement W4403850203 · doi:10.4103/sjg.sjg_360_24

The treatment naïve microbiome of pediatric ulcerative colitis and microbial therapeutics: A humbling challenge

2024· article· en· W4403850203 sur OpenAlexaboutno aff
Richárd Kellermayer

Notice bibliographique

RevueSaudi Journal of Gastroenterology · 2024
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueGut microbiota and health
Établissements canadiensnon disponible
Organismes subventionnairesTexas Children's HospitalU.S. Department of Agriculture
Mots-clésMedicineUlcerative colitisMicrobiomeFecal bacteriotherapyIntensive care medicineBioinformaticsMicrobiologyInternal medicineDiseaseClostridium difficileAntibioticsBiology

Résumé

récupéré en direct d'OpenAlex

The gut microbiome is a potentially key participant in the developmental origins of inflammatory bowel diseases (IBDs) including Crohn disease (CD) and ulcerative colitis (UC).[1,2] In spite of over 2 decades of increasingly sophisticated microbiome (i.e., the collective genomes of the microorganisms in a given environment)-focused biomedical research, we still cannot confidently determine the role and importance of the microbiota (differentiated from the microbiome by defining living organisms within a given environment: https://qima-lifesciences.com/dermatology/skin-microbiome-dermatology/microbiota-vs-microbiome/) in the pathogenesis and maintenance of IBD.[3,4] In this issue of the journal, El Mouzan and colleagues aimed to improve our understanding of the intestinal microbiome’s role in pediatric UC by comparing the colonic mucosal and fecal microbiomes of treatment naïve patients with UC (20) to non-IBD and heathy controls, respectively.[5] The study was carefully designed and bears conceivable strengths: It was performed in pediatric patients, who arguably have shorter preclinical disease duration and less non-IBD-related comorbidities; therefore, there is less microbiome-based bias from such influences. The findings may translate to adult onset IBD as well, although there are recognized differences in the presentation, treatment response, and course of pediatric IBD compared to adults.[6] It examined treatment naïve cases, which eliminates the direct and indirect (iatrogenically modified immunity) effects of immunomodulators (including biologic agents and small molecules) on the microbiome. It examined both mucosal and fecal microbiomes, although mucosal samples were obtained after colon preparation, which can have differential effects on the mucosal microbiome in IBD patients and controls.[7] Shotgun sequencing was performed, which allowed for species level discrimination, but this was done only for bacterial taxonomic studies and was not utilized to examine other microorganisms such as fungi (fungome or mycobiome)[8,9] nor to observe the metabolic capacity (metagenomics)[10] of the microbiomes. One must assume that the research team plans to exploit the advantages of the shotgun sequencing performed in future studies, since in respect to bacterial taxonomic analyses the technology carries modest value compared to conventional 16S rRNA sequencing.[11] It compared dietary intake of the subjects, but potential associations with taxonomic findings were not made in this respect. Beyond the strengths of the study, it is important to recognize that just as any other nucleic-acid-based microbiome analysis, the work of Mohammad El Mouzan and colleagues is challenged by the numerous limitations of the methodology.[12] For example, nucleic-acid-based sequencing of microbiomes cannot differentiate between dead or living microorganisms in a sample.[13] Furthermore, at least 30% of the bacteria, which can be discriminated, are still nonculturable.[13] Secondary to such limitations, we currently cannot confidently determine through nucleic acid testing whether even an opportunistic microorganism, such as Clostridioides difficile[14] or cytomegalovirus,[15] is a pathogen or a bystander (i.e., colonizer/colonization or pass-through) in challenging clinical scenarios involving patients with IBD. Indeed, dead or alive, pathogen or commensal, good or bad, and cause or effect are unknown when it comes to specific microorganisms in a microbiome solely examined by nucleic acid sequencing.[3,16] With the strengths and limitations in mind, El Mouzan et al. found significant differences between mucosal and fecal microbiomes in separating between pediatric patients with UC and controls.[5] While fecal microbiomes separated significantly by alpha and beta diversity measures between pediatric UC and control, this was not the case for the mucosal microbiomes, similar to our findings in treatment naïve pediatric UC patients.[17] It should be noted, however, that even in the case of the fecal microbiomes, significant separation resulted from a relatively small effect size[18] (17.6 and 12.4% of microbiome separation explained by UC, respectively; see Figure 2[5]). Arguably, it is the mucosa-associated microbiome, which may be more important in the microbial origins of IBD, including UC.[19] The findings that only three genera separated UC colonic mucosal microbiomes from controls, even under inflamed conditions, where differences might arise secondary to inflammation itself,[3] are in line with indirect observations implicating less importance of the microbiome in the developmental origins of UC than CD. Namely, early childhood antibiotic exposure more prominently increases the risk of subsequent CD than UC.[20] Additionally, while taking the polygenic risk of IBD[21] into consideration, the carefully crafted Canadian GEM Project (https://crohnsandcolitis.ca/Research/Funded-research/The-gem-project) found that an altered fecal microbiome composition is a better predictor for CD than genetic risk,[22] but this was not observed for UC (with admittedly low power in that respect). In line with these observations and in contrast with UC, we found that terminal ileal mucosal (plausibly causal) microbiomes were more predictive of pediatric CD than fecal (plausibly consequential) ones.[23] In any case, focusing on the three UC differentiating mucosal genera of the study by El Mouzan et al.,[5]Parabacteroides stands out as the most significant (decreased in UC compared to control). We find that potentially important since our background studies on the developmental maturation of the pediatric colonic mucosa observed an age-dependent flux in Parabacteroides abundance (increase) in control patients.[24] Based on these findings, one could speculate that there might be a relative delay in the mucosa-associated gut microbiome’s natural maturation in pediatric patients with UC, and Parabacteroides may participate through such in the developmental origins of the disease. It is important to note that the study by El Mouzan et al. included dietary information as well. Extrapolating the % patients presented in their Table 1,[5] one can make interesting observations. More control (60%) children ate chicken daily, while the control cohort ate less red meat, vegetables, and fruits on a daily basis than the UC cohort, per report [Table 1]. By our opinion, these findings implicate higher income (relative wealth) and increased dietary alternation in the families with children diagnosed with UC than in the control families. Such demographics would corroborate prior epidemiologic and translational studies in North America. Specifically, we have highlighted increased family income[25] and the conceivably positively associated rapid alternation in food types[25-27] as well as inversely correlating household size[28] to partake in the pediatric developmental origins of IBD. Our observations in respect to family wealth/socioeconomic status[29] and household/family size[30] have been recently supported by larger-scale epidemiologic studies, respectively. How such environmental factors impact the microbiome and the subsequent development of IBD is still poorly understood. Such an understanding, however, could set the basis for microbiome-directed preventative measures against IBD.[31,32]Table 1: Extrapolated number of patients reporting the food type consumption according to El Mouzan, et al.[ 5 ]As for microbial therapeutics (elimination or supplementation) against IBD, we have yet to make breakthrough discoveries, repeatedly stemming from the complexity of the gut microbiome. Oral broad spectrum antibiotics have only modest and commonly transient therapeutic effects in both UC and CD.[33] Oral vancomycin, however, can have long-standing therapeutic effects in primary sclerosing cholangitis-associated IBD (PSC-IBD)[34] and some cases with very early onset IBD (VEO-IBD),[35] but the mechanism is poorly understood. Selective elimination of bacteria with phage therapy has intriguing potential as an IBD therapeutic, but it is in its early preclinical stages.[36] As for supplementation/modulation by addition of microorganisms, there are three therapeutic modalities: fecal microbiota transplantation (FMT: addition of a microbiota through stool from a healthy person), addition of engineered consortia of microorganisms (complex probiotics), or addition of a single microorganism (probiotic).[37] FMT may increase the rates of clinical and endoscopic remission, but current evidence is week for it to maintain long-term remission in UC.[38] FMT is challenged, however, by multiple layers of safety, regulatory, and clinical considerations,[16] especially since the COVID-19 pandemic.[39] Beyond FMT, there are multiple active clinical trials in IBD, which aim to evaluate complex and single probiotics as therapeutics. It is difficult to meticulously study probiotic efficacy,[40] and rigorous meta-analyses of completed trials concluded that similar to CD, “The overall CoE (certainty of evidence) across all critical outcomes for probiotics for induction or maintenance of remission in children or adults with ulcerative colitis was Low”.[41] We have highlighted the humbling challenges in unraveling the microbial developmental origins of IBD and the currently limited evidence for microbial therapy to combat most of the cases. Similar to the Hubble telescope (https://www.youtube.com/watch?v=99uWHUQ-dC0), novel technology is providing us a glance into the limitless complexity of the gut microbiome and meta-metabolome.[42] In agreement with Albert Einstein (“The most beautiful and deepest experience a man can have is the sense of the mysterious.”) and Richard P. Feynman (“See that the imagination of nature is far, far greater than the imagination of man.”), it is a most exhilarating experience to recognize such wondrous complexity[4] and the metaphysical presence in biology.[43] Amid the humbling realization of our limitations when it comes to the gut microbiome, El Mouzan et al.[5] are applauded for their efforts.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,014
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,033

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,014
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,002
Communication savante0,0030,004
Science ouverte0,0010,002
Intégrité de la recherche0,0020,005
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,015
Tête enseignante GPT0,277
Écart entre enseignants0,262 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

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

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

En bref

Citations1
Publié2024
Routes d'admission1
Résumé présentoui

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Même revueSaudi Journal of GastroenterologyMême sujetGut microbiota and healthTravaux en français237 207