Does the 5-Aminosalicylate Concentration Correlate with the Efficacy of Oral 5-Aminosalicylate and Predict Response in Patients with Inflammatory Bowel Disease?: A Systematic Review

BACKGROUND: Oral 5-aminosalicylic acid (5-ASA, mesalazine) is the first choice therapeutic agent for treating mild-to-moderate ulcerative colitis (UC). Unfortunately a significant group of patients fail to respond. Therapeutic drug monitoring might help to maintain or induce remission by providing a tool for optimization of 5-ASA therapy. However, plasma and urine concentrations of 5-ASA reflect systemic uptake and are not useful to evaluate therapeutic effect. OBJECTIVES: To explore if mucosal and faecal 5-ASA values correlate with disease activity and/or therapeutic effects in patients with inflammatory bowel disease, especially UC. METHOD: We identified studies that analysed 5-ASA in faeces or mucosa of humans using an oral 5-ASA formulation, using PubMed and Embase. RESULTS: In total, 39 studies (n = 939) were included, 27 on faecal 5-ASA, 9 on mucosal concentrations, and 3 on both faecal and mucosal values. We included 33 cross-sectional studies, 3 randomised clinical trials, 2 longitudinal cohorts and 1 randomized cross-over study. Mucosal 5-ASA concentrations in healthy subjects and patients on equivalent doses of 5-ASA were not found to differ remarkably. In the sub-analysis of mucosal 5-ASA concentrations in patients with active or quiescent UC, a higher concentration was seen during remission. Faecal concentrations were associated with 5-ASA doses but not with disease activity. Differences in faecal or mucosal 5-ASA values could not be ascribed to different 5-ASA formulations. CONCLUSIONS: An increase of the mucosal 5-ASA concentrations was observed during remission in patients with UC. No clear relationship between the faecal 5-ASA excretion and the therapeutic efficacy was identified

Outcome of Reverse Switching From CT-P13 to Originator Infliximab in Patients With Inflammatory Bowel Disease

BACKGROUND: Patients suffering from inflammatory bowel diseases (IBD) and treated with originator infliximab are increasingly being switched to biosimilars. Some patients, however, are "reverse switched" to treatment with the originator. Here we assess the prevalence of reverse switching, including its indication and outcomes. METHODS: In this retrospective multicenter cohort study, data on patients with IBD from 9 hospitals in the Netherlands were collected. All adult patients with IBD were included if they previously had been switched from originator infliximab to the biosimilar CT-P13 and had a follow-up time of at least 52 weeks after the initial switch. The reasons for reverse switching were categorized into worsening gastrointestinal symptoms, adverse effects, or loss of response to CT-P13. Drug persistence was analyzed through survival analyses. RESULTS: A total of 758 patients with IBD were identified. Reverse switching was observed in 75 patients (9.9%). Patients with reverse switching were predominantly female (70.7%). Gastrointestinal symptoms (25.5%) and dermatological symptoms (21.8%) were the most commonly reported reasons for reverse switching. In 9 patients (12.0%), loss of response to CT-P13 was the reason for reverse switching. Improvement of reported symptoms was seen in 73.3% of patients after reverse switching and 7 out of 9 patients (77.8%) with loss of response regained response. Infliximab persistence was equal between patients who were reverse-switched and those who were maintained on CT-P13. CONCLUSIONS: Reverse switching occurred in 9.9% of patients, predominantly for biosimilar-attributed adverse effects. Switching back to originator infliximab seems effective in patients who experience adverse effects, worsening gastrointestinal symptoms, or loss of response after switching from originator infliximab to CT-P13

Loss of response to anti-TNF alpha agents depends on treatment duration in patients with inflammatory bowel disease

Background: Inflammatory bowel disease (IBD) is often managed with anti-tumour necrosis factor-α therapy (anti-TNFα), but treatment efficacy is compromised by high annual rates of loss of response (13%-21% per patient-year). Aims: To assess whether the incidence of loss of response decreases with longer treatment duration. Methods: This was a multicentre, retrospective cohort study of patients with ulcerative colitis (UC) or Crohn's disease (CD) who received anti-TNFα for at least 4 months between 2011 and 2019. We studied the incidence of loss of response as a function of treatment duration, employing parametric survival modelling. Predictors of loss of response were identified by Cox regression analysis. Secondary outcomes included overall anti-TNFα discontinuation and dose escalation. Results: We included 844 anti-TNFα treatment episodes in 708 individuals. Loss of response occurred in 211 (25.0%) episodes, with anti-drug antibodies detected in 66 (31.3%). During the first year, the incidence of loss of response was three-fold higher than after four years of treatment (17.2% vs 4.8% per patient-year, P < 0.001). The incidence of anti-TNFα discontinuation (28.6% vs 14.0% per patient-year, P < 0.001) and dose escalations (38.0% vs 6.8% per patient-year, P < 0.001) also decreased significantly from the first year to after four years, respectively. Predictors of loss of response included UC (vs CD, adjusted hazard ratio [aHR] 1.53, 95% CI 1.10-2.15) and, among patients with CD, stricturing or penetrating disease (aHR 1.68, 95% CI 1.15-2.46) and male sex (aHR 0.55, 95% CI 0.38-0.78). Immunomodulators were protective against loss of response with anti-drug antibodies (aHR 0.42, 95% CI 0.24-0.74). Conclusions: Patients with sustained benefit to anti-TNFα after 2 years are at low risk of subsequent loss of response

Limited predictive value of the gut microbiome and metabolome for response to biological therapy in inflammatory bowel disease

Emerging evidence suggests the gut microbiome's potential in predicting response to biologic treatments in patients with inflammatory bowel disease (IBD). In this prospective study, we aimed to predict treatment response to vedolizumab and ustekinumab, integrating clinical data, gut microbiome profiles based on metagenomic sequencing, and untargeted fecal metabolomics. We aimed to identify predictive biomarkers and attempted to replicate microbiome-based signals from previous studies. We found that the predictive utility of the gut microbiome and fecal metabolites for treatment response was marginal compared to clinical features alone. Testing our identified microbial ratios in an external cohort reinforced the lack of predictive power of the microbiome. Additionally, we could not confirm previously published predictive signals observed in similar sized cohorts. Overall, these findings highlight the importance of external validation and larger sample sizes, to better understand the microbiome's impact on therapy outcomes in the setting of biologicals in IBD before potential clinical implementation

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.</p

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.</p

MethylScore, a pipeline for accurate and context-aware identification of differentially methylated regions from population-scale plant WGBS data

Whole-genome bisulfite sequencing (WGBS) is the standard method for profiling DNA methylation at single-nucleotide resolution. Many WGBS-based studies aim to identify biologically relevant loci that display differential methylation between genotypes, treatment groups, tissues, or developmental stages. Over the years, different tools have been developed to extract differentially methylated regions (DMRs) from whole-genome data. Often, such tools are built upon assumptions from mammalian data and do not consider the substantially more complex and variable nature of plant DNA methylation. Here, we present MethylScore, a pipeline to analyze WGBS data and to account for plant-specific DNA methylation properties. MethylScore processes data from genomic alignments to DMR output and is designed to be usable by novice and expert users alike. It uses an unsupervised machine learning approach to segment the genome by classification into states of high and low methylation, substantially reducing the number of necessary statistical tests while increasing the signal-to-noise ratio and the statistical power. We show how MethylScore can identify DMRs from hundreds of samples and how its data-driven approach can stratify associated samples without prior information. We identify DMRs in the A. thaliana 1001 Genomes dataset to unveil known and unknown genotype-epigenotype associations. MethylScore is an accessible pipeline for plant WGBS data, with unprecedented features for DMR calling in small- and large-scale datasets; it is built as a Nextflow pipeline and its source code is available at https://github.com/Computomics/MethylScore