LB15. SER-109, an Investigational Microbiome Therapeutic, Reduces Abundance of Antimicrobial Resistance Genes in Patients with Recurrent Clostridioides difficile Infection (rCDI) after Standard-of-Care Antibiotics
Notice bibliographique
Résumé
Abstract Background The gastrointestinal microbiota is the first line of defense against colonization with antimicrobial resistant (AR) bacteria, particularly in vulnerable hosts with frequent antibiotic exposure. In a double-blind Phase 3 trial of rCDI patients, SER-109, an orally formulated consortia of purified Firmicutes spores, was superior to placebo in reducing CDI recurrence at week 8 post clinical resolution on standard-of-care (SoC) antibiotics. Overall recurrence rates were lower in SER-109 vs placebo (12.4% vs 39.8%, respectively) relative risk, 0.32 [95% CI, 0.18–0.58; p< 0.001 for RR< 1.0; p< 0.001 for RR< 0.833]. This is a post-hoc analysis examining the impact of SER-109 on antimicrobial resistance genes (ARGs) abundance in the intestinal microbiota compared to placebo. Methods Subjects with rCDI received SoC antibiotics, then were randomized 1:1 to SER-109 or placebo at baseline. Of 182 subjects, 140 who had paired stool samples at baseline and 1-week post-treatment were included in this analysis. ARG abundances and taxonomic profiles were generated from whole metagenomic shotgun sequencing. t-tests were used to compare changes in ARG abundance from baseline; mixed linear models were used to associate ARG and taxon abundances across time points. Results ARG abundance was reduced overall by week 1, with a significantly greater decrease in SER-109 subjects vs. placebo at week 1 (Fig. 1). Proteobacteria relative abundance were positively correlated with ARG abundance across all samples (Fig. 2), with the Enterobacteriaceae family associated with the abundance of 95 ARGs (all p < 0.05). Enterococcaceae relative abundance was associated with glycopeptide AR abundance (p < 0.001). At week 1, Proteobacteria relative abundance was significantly decreased from baseline in SER-109 subjects vs. placebo (p < 0.001). Enterobacteriaceae and Enterococcaceae relative abundances were also decreased from baseline in SER-109 subjects vs. placebo (p < 0.001 and p = 0.007, respectively). Figure 1. Significant reduction in ARG abundance at week 1 from baseline in SER-109 treatment compared to placebo. Figure 2. Total ARG abundance is associated with the relative abundance of Proteobacteria in SER-109 and placebo subjects at baseline and week 1. Conclusion SER-109 was associated with significantly greater reduction of ARGs and AR bacteria abundances compared to placebo at 1 week post treatment. These findings support a potential role of microbiome therapeutics in rapid decolonization of AR bacteria with implications for infection prevention. Disclosures Timothy J. Straub, MS, Seres Therapeutics (Employee) Liyang Diao, PhD, Seres Therapeutics (Employee) Christopher Ford, PhD, Seres Therapeutics (Employee, Shareholder) Matthew Sims, MD, PhD, Astra Zeneca (Independent Contractor)Diasorin Molecular (Independent Contractor)Epigenomics Inc (Independent Contractor)Finch (Independent Contractor)Genentech (Independent Contractor)Janssen Pharmaceuticals NV (Independent Contractor)Kinevant Sciences gmBH (Independent Contractor)Leonard-Meron Biosciences (Independent Contractor)Merck and Co (Independent Contractor)OpGen (Independent Contractor)Prenosis (Independent Contractor)Regeneron Pharmaceuticals Inc (Independent Contractor)Seres Therapeutics Inc (Independent Contractor)Shire (Independent Contractor)Summit Therapeutics (Independent Contractor) Thomas J. Louie, MD, Artugen (Advisor or Review Panel member)Crestone (Consultant, Grant/Research Support)Da Volterra (Advisor or Review Panel member)Finch Therapeutics (Grant/Research Support, Advisor or Review Panel member)MGB Biopharma (Grant/Research Support, Advisor or Review Panel member)Rebiotix (Consultant, Grant/Research Support)Seres Therapeutics (Consultant, Grant/Research Support)Summit PLC (Grant/Research Support)Vedanta (Grant/Research Support, Advisor or Review Panel member) Colleen S. Kraft, MD, MSc, Rebiotix (Individual(s) Involved: Self): Advisor or Review Panel member Stuart H. Cohen, MD, Seres (Research Grant or Support) Stuart H. Cohen, MD, Nothing to disclose Mary-Jane Lombardo, PhD, Seres Therapeutics (Employee, Shareholder) Barbara McGovern, MD, Seres Therapeutics (Employee, Shareholder) Lisa von Moltke, MD, Seres Therapeutics (Employee, Shareholder) Matt Henn, PhD, Seres Therapeutics (Employee, Shareholder)
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».