A proof‐of‐concept study with the combination of guselkumab and golimumab in patients with ulcerative colitis (UC) has shown that the combination therapy resulted in greater efficacy than the ...individual monotherapies. The current analysis evaluated the pharmacokinetics (PK) and immunogenicity of guselkumab and golimumab in both the combination therapy and individual monotherapies. Blood samples were collected to evaluate serum concentrations and immunogenicity of guselkumab and golimumab. Population PK (PopPK) models were developed to assess the effects of combination therapy and other potential covariates on the PK of guselkumab and golimumab. The guselkumab PK was comparable between monotherapy and combination therapy, whereas golimumab concentrations were slightly higher with combination therapy. The anti‐guselkumab antibody incidence was low with both monotherapy and combination therapy, and guselkumab immunogenicity did not impact the clearance. Conversely, the anti‐golimumab antibody incidence with combination therapy was lower than that for monotherapy. PopPK analysis suggested that the slightly higher golimumab concentrations with combination therapy were partially due to lower immunogenicity and thus lower clearance with combination therapy. C‐reactive protein (CRP) was also a significant covariate on golimumab clearance. The greater improvement of inflammation with combination therapy, as shown by reductions in CRP, may have also contributed to the higher golimumab concentrations. Combination therapy slightly decreased the clearance of golimumab, but not guselkumab clearance, in patients with UC. Lower immunogenicity and greater improvement of inflammation with combination therapy were potential mechanisms for slightly increased golimumab concentrations with combination therapy as compared with golimumab monotherapy.
Abstract
Background and Aims
Diagnostic yield of Small Bowel Capsule Endoscopy (SBCE) for the assessment of small bowel (SB) lesions is higher than radiologic imaging techniques. However, magnetic ...resonance enterography (MRE) data are scarce and inconclusive. Colon Capsule Endoscopy (CCE) is a new capsule modality. The primary aim of our study was to compare MRE and capsule endoscopy (CE) for the assessment of Crohn's disease (CD). The secondary objectives were to compare the diagnostic accuracy of both CE modalities and changes in Montreal classification after each examination.
Methods
We included 47 patients with established (n = 32) or suspected CD (n = 15). MRE was performed first to rule out strictures. In patients with a suspected stricture by MRE, an Agile Patency Capsule was performed. SB disease activity was measured by MaRIA score (MRE) and Lewis Index (CE).
Results
SB lesions were found in 36 of47 patients with CE and in 21 of47 patients with MRE (76.6% vs 44.7%, P = 0.001). Jejunal inflammation was detected by CE in 31.9% of patients and by MRE in 6.4% of patients (15/47 vs 3/47; P = 0.03); lesions in ileum were detected in 57.4% of patients by CE, and in 21.3% of patients by MRE (27/ 47 vs 10/ 47; P = 0.04). Finally, in terminal ileum, CE showed lesions in 68.1% (32/47) of patients, whereas MRE detected lesions in 38.3% (18/ 47 patients), (P = 0.001). The original Montreal classification was changed in 53.1% of patients (25/ 47) based on CE findings and in 12.7% of patients (6/47) based on MRE findings (P < 0.05).
Conclusions
In our cohort CE was significantly superior to MRE for detecting SB lesions, mainly superficial and proximal lesions. CE is useful for a appropriate patients' classification according to Montreal classification.
Personalized medicine requires finding relationships between variables that influence a patient's phenotype and predicting an outcome. Sparse generalized canonical correlation analysis identifies ...relationships between different groups of variables. This method requires establishing a model of the expected interaction between those variables. Describing these interactions is challenging when the relationship is unknown or when there is no pre-established hypothesis. Thus, our aim was to develop a method to find the relationships between microbiome and host transcriptome data and the relevant clinical variables in a complex disease, such as Crohn's disease.
We present here a method to identify interactions based on canonical correlation analysis. We show that the model is the most important factor to identify relationships between blocks using a dataset of Crohn's disease patients with longitudinal sampling. First the analysis was tested in two previously published datasets: a glioma and a Crohn's disease and ulcerative colitis dataset where we describe how to select the optimum parameters. Using such parameters, we analyzed our Crohn's disease data set. We selected the model with the highest inner average variance explained to identify relationships between transcriptome, gut microbiome and clinically relevant variables. Adding the clinically relevant variables improved the average variance explained by the model compared to multiple co-inertia analysis.
The methodology described herein provides a general framework for identifying interactions between sets of omic data and clinically relevant variables. Following this method, we found genes and microorganisms that were related to each other independently of the model, while others were specific to the model used. Thus, model selection proved crucial to finding the existing relationships in multi-omics datasets.
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