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Record 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 on OpenAlexaboutno aff
Richárd Kellermayer

Bibliographic record

VenueSaudi Journal of Gastroenterology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersTexas Children's HospitalU.S. Department of Agriculture
KeywordsMedicineUlcerative colitisMicrobiomeFecal bacteriotherapyIntensive care medicineBioinformaticsMicrobiologyInternal medicineDiseaseClostridium difficileAntibioticsBiology

Abstract

fetched live from 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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.277
Teacher spread0.262 · 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.

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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