A multi-cohort phase 1b trial of rituximab in combination with immunotherapy doublets in relapsed/refractory follicular lymphoma.

Antibodies targeting PD-1 or 4-1BB achieve objective responses in follicular lymphoma (FL), but only in a minority of patients. We hypothesized that targeting multiple immune receptors could overcome immune resistance and increase response rates in patients with relapsed/refractory FL. We therefore conducted a phase 1b trial testing time-limited therapy with different immunotherapy doublets targeting 4-1BB (utomilumab), OX-40 (ivuxolimab), and PD-L1 (avelumab) in combination with rituximab among patients with relapsed/refractory grade 1-3A FL. Patients were enrolled onto 2 of 3 planned cohorts (cohort 1 - rituximab/utomilumab/avelumab; cohort 2 - rituximab/ivuxolimab/utomilumab). 3+3 dose escalation was followed by dose expansion at the recommended phase 2 dose (RP2D). Twenty-four patients were enrolled (16 in cohort 1 and 9 in cohort 2, with one treated in both cohorts). No patients discontinued treatment due to adverse events and the RP2D was the highest dose level tested in both cohorts. In cohort 1, the objective and complete response rates were 44% and 19%, respectively (50% and 30%, respectively, at RP2D). In cohort 2, no responses were observed. The median progression-free survivals in cohorts 1 and 2 were 6.9 and 3.2 months, respectively. In cohort 1, higher density of PD-1+ tumor-infiltrating T-cells on baseline biopsies and lower density of 4-1BB+ and TIGIT+ T-cells in on-treatment biopsies were associated with response. Abundance of Akkermansia in stool samples was also associated with response. Our results support a possible role for 4-1BB agonist therapy in FL and suggest that features of the tumor microenvironment and stool microbiome may be associated with clinical outcomes (NCT03636503).

A two-cohort study on the association between the gut microbiota and bone density, microarchitecture, and strength.

The gut microbiome affects the inflammatory environment through effects on T-cells, which influence the production of immune mediators and inflammatory cytokines that stimulate osteoclastogenesis and bone loss in mice. However, there are few large human studies of the gut microbiome and skeletal health. We investigated the association between the human gut microbiome and high resolution peripheral quantitative computed tomography (HR-pQCT) scans of the radius and tibia in two large cohorts; Framingham Heart Study (FHS [n=1227, age range: 32 - 89]), and the Osteoporosis in Men Study (MrOS [n=836, age range: 78 - 98]). Stool samples from study participants underwent amplification and sequencing of the V4 hypervariable region of the 16S rRNA gene. The resulting 16S rRNA sequencing data were processed separately for each cohort, with the DADA2 pipeline incorporated in the16S bioBakery workflow. Resulting amplicon sequence variants were assigned taxonomies using the SILVA reference database. Controlling for multiple covariates, we tested for associations between microbial taxa abundances and HR-pQCT measures using general linear models as implemented in microbiome multivariable association with linear model (MaAslin2). Abundance of 37 microbial genera in FHS, and 4 genera in MrOS, were associated with various skeletal measures (false discovery rate [FDR] ≤ 0.1) including the association of DTU089 with bone measures, which was independently replicated in the two cohorts. A meta-analysis of the taxa-bone associations further revealed (FDR ≤ 0.25) that greater abundances of the genera; Akkermansia and DTU089, were associated with lower radius total vBMD, and tibia cortical vBMD respectively. Conversely, higher abundances of the genera; Lachnospiraceae NK4A136 group, and Faecalibacterium were associated with greater tibia cortical vBMD. We also investigated functional capabilities of microbial taxa by testing for associations between predicted (based on 16S rRNA amplicon sequence data) metabolic pathways abundance and bone phenotypes in each cohort. While there were no concordant functional associations observed in both cohorts, a meta-analysis revealed 8 pathways including the super-pathway of histidine, purine, and pyrimidine biosynthesis, associated with bone measures of the tibia cortical compartment. In conclusion, our findings suggest that there is a link between the gut microbiome and skeletal metabolism.

Metagenomic assessment of gut microbial communities and risk of severe COVID-19.

BACKGROUND: The gut microbiome is a critical modulator of host immunity and is linked to the immune response to respiratory viral infections. However, few studies have gone beyond describing broad compositional alterations in severe COVID-19, defined as acute respiratory or other organ failure. METHODS: We profiled 127 hospitalized patients with COVID-19 (n = 79 with severe COVID-19 and 48 with moderate) who collectively provided 241 stool samples from April 2020 to May 2021 to identify links between COVID-19 severity and gut microbial taxa, their biochemical pathways, and stool metabolites. RESULTS: Forty-eight species were associated with severe disease after accounting for antibiotic use, age, sex, and various comorbidities. These included significant in-hospital depletions of Fusicatenibacter saccharivorans and Roseburia hominis, each previously linked to post-acute COVID syndrome or "long COVID," suggesting these microbes may serve as early biomarkers for the eventual development of long COVID. A random forest classifier achieved excellent performance when tasked with classifying whether stool was obtained from patients with severe vs. moderate COVID-19, a finding that was externally validated in an independent cohort. Dedicated network analyses demonstrated fragile microbial ecology in severe disease, characterized by fracturing of clusters and reduced negative selection. We also observed shifts in predicted stool metabolite pools, implicating perturbed bile acid metabolism in severe disease. CONCLUSIONS: Here, we show that the gut microbiome differentiates individuals with a more severe disease course after infection with COVID-19 and offer several tractable and biologically plausible mechanisms through which gut microbial communities may influence COVID-19 disease course. Further studies are needed to expand upon these observations to better leverage the gut microbiome as a potential biomarker for disease severity and as a target for therapeutic intervention.

Differences of the Nasal Microbiome and Mycobiome by Clinical Characteristics of COPD Patients.

Rationale: While studies suggest that the lung microbiome may influence risk of chronic obstructive pulmonary disease (COPD) exacerbations, little is known about the relationship between the nasal biome and clinical characteristics of COPD patients. Methods: We sampled the nasal lining fluid by nasosorption of both nares of 20 people with moderate-to-severe COPD. All 40 samples, plus 4 negative controls, underwent DNA extraction, and 16SV4 ribosomal RNA (rRNA) (bacterial) and ribosomal internal transcribed spacer 2 (ITS2) (fungal) sequencing. We measured the proportion of variance (R2) in beta diversity explained by clinical factors, including age, sex, body mass index (BMI), COPD treatment, disease severity (forced expiratory volume in 1 second [FEV1], symptom/exacerbation frequency), peripheral eosinophil level (≥150 versus <150 cells/µL) and season of sampling, with the PERMANOVA test on the Bray-Curtis dissimilarities, accounting for within-person correlation of samples. We assessed the relative abundance of microbial features in the nasal community and their associations with clinical characteristics using the Microbiome Multivariable Association with Linear Models (MaAsLin2) package. Results: The most abundant nasal fluid bacterial taxa were Corynebacterium, Staphylococcus, Streptococcus, Moraxella, and Dolosigranulum, and fungal taxa were Malassezia, Candida, Malasseziales, Cladosporium and Aspergillus. Bacterial microbiome composition was associated with short-acting muscarinic antagonist use (R2 11.8%, p=0.002), sex (R2 8.3%, p=0.044), nasal steroid use (R2 7.7%, p=0.064), and higher eosinophil level (R2 7.6%, p=0.084). Mycobiome composition was associated with higher eosinophil level (R2 14.4%, p=0.004) and low FEV1 (R2 7.5%, p=0.071). No specific bacterium or fungus differed significantly in relative abundance by clinical characteristics in the multivariate per-feature analysis. Conclusion: The taxonomical composition of the nasal biome is heterogeneous in COPD patients and may be explained in part by clinical characteristics.

Human threat learning is associated with gut microbiota composition.

The ability to learn about threat and safety is critical for survival. Studies in rodent models have shown that the gut microbiota can modulate such behaviors. In humans, evidence showing an association with threat or extinction learning is lacking. Here, we tested whether individual variability in threat and extinction learning was related to gut microbiota composition in healthy adults. We found that threat, but not extinction learning, varies with individuals' microbiome composition. Our results provide evidence that the gut microbiota is associated with excitatory threat learning across species.

Microbiota composition modulates inflammation and neointimal hyperplasia after arterial angioplasty.

BACKGROUND: Neointimal hyperplasia is a major contributor to restenosis after arterial interventions, but the genetic and environmental mechanisms underlying the variable propensity for neointimal hyperplasia between individuals, including the role of commensal microbiota, are not well understood. We sought to characterize how shifting the microbiome using cage sharing and bedding mixing between rats with differing restenosis phenotypes after carotid artery balloon angioplasty could alter arterial remodeling. METHODS: We co-housed and mixed bedding between genetically distinct rats (Lewis [LE] and Sprague-Dawley [SD]) that harbor different commensal microbes and that are known to have different neointimal hyperplasia responses to carotid artery balloon angioplasty. Sequencing of the 16S ribosomal RNA gene was used to monitor changes in the gut microbiome. RESULTS: There were significant differences in neointimal hyperplasia between non-co-housed LE and SD rats 14 days after carotid artery angioplasty (mean intima + media [I + M] area, 0.117 ± 0.014 mm2 LE vs 0.275 ± 0.021 mm2 SD; P < .001) that were diminished by co-housing. Co-housing also altered local adventitial Ki67 immunoreactivity, local accumulation of leukocytes and macrophages (total and M2), and interleukin 17A concentration 3 days after surgery in each strain. Non-co-housed SD and LE rats had microbiomes distinguished by both weighted (P = .012) and unweighted (P < .001) UniFrac beta diversity distances, although without significant differences in alpha diversity. The difference in unweighted beta diversity between the fecal microbiota of SD and LE rats was significantly reduced by co-housing. Operational taxonomic units that significantly correlated with average I + M area include Parabacteroides distasonis, Desulfovibrio, Methanosphaera, Peptococcus, and Prevotella. Finally, serum concentrations of microbe-derived metabolites hydroxyanthranilic acid and kynurenine/tryptophan ratio were significantly associated with I + M area in both rat strains independent of co-housing. CONCLUSIONS: We describe a novel mechanism for how microbiome manipulations affect arterial remodeling and the inflammatory response after arterial injury. A greater understanding of the host inflammatory-microbe axis could uncover novel therapeutic targets for the prevention and treatment of restenosis.

Introducing the Microbiome into Precision Medicine.

Understanding how individual people respond to medical therapy is a key facet of improving the odds ratio that interventions will have a positive impact. Reducing the non-responder rate for an intervention or reducing complications associated with a particular treatment or surgery is the next stage of medical advance. The Precision Medicine Initiative, launched in January 2015, set the stage for enhanced collaboration between researchers and medical professionals to develop next-generation techniques to aid patient treatment and recovery, and increased the opportunities for impactful pre-emptive care. The microbiome plays a crucial role in health and disease, as it influences endocrinology, physiology, and even neurology, altering the outcome of many different disease states, and it augments drug responses and tolerance. We review the implications of the microbiome on precision health initiatives and highlight excellent examples, whereby precision microbiome health has been implemented.