Genetic Background of Mesalamine-induced Fever and Diarrhea in Japanese Patients with Inflammatory Bowel Disease

RGS10 Deficiency Alleviated Intestinal Mucosal Inflammation Through Suppression of Th1/Th17 Cell Immune Responses in Ulcerative Colitis

Regulator of G-protein signalling (RGS) 10 plays critical roles in several immune related diseases. However, whether RGS10 is involved in colonic inflammation of ulcerative colitis (UC) is still obscure. This study aimed to investigate the role of RGS10 in UC. In this study, RGS10 expression was examined by quantitative real-time polymerase chain reaction (qRT-PCR), western blotting, immunohistochemistry, and immunofluorescent analysis. Single-cell RNA sequencing of intestinal mucosa was performed to identify key immune cells with differentially expressed RGS10. RGS10 knockout mice were generated and established dextran sulphate sodium (DSS)-induced colitis. Expression of inflammatory cytokines on mRNA and protein levels was detected by qRT-PCR, enzyme-linked immunosorbent assay, and flow cytometry. We found that RGS10 expression was significantly elevated in UC patients, especially in CD4+ T cells, compared with healthy subjects. Intriguingly, RGS10 deficiency markedly alleviated DSS-induced colitis and decreased the proportion of Th1 and Th17 cells in lamina propria mononuclear cells (LPMCs), peripheral blood (PB), spleens, and mesenteric lymph nodes (mLNs). Mechanistically, RGS10 deficiency blocked the differentiation of Th1 and Th17 cells by inhibiting the phosphorylation of signal transducer and activator of transcription (STAT) 1 and STAT3. The co-immunoprecipitation analysis further showed that RGS10 could interact with protein tyrosine phosphatase non-receptor type 2 (PTPN2), and further regulated Th1 and Th17 cells differentiation of CD4+ T cells. In conclusion, RGS10 deficiency alleviated intestinal mucosal inflammation through inhibition of Th1/Th17 cell-mediated immune responses via interaction with PTPN2 in CD4+ T cells. Therefore, targeting RGS10 may represent a novel therapeutic approach for UC treatment.

A real-world disproportionality analysis of mesalazine data mining of the public version of FDA adverse event reporting system

Background: Mesalazine, a preparation of 5-aminosalicylic acid, is a medication widely used in clinical practice as a first-line therapy in the treatment of mild and moderate inflammatory bowel disease. However, the long-term safety of mesalazine in large sample population was unknown. The current study was to assess mesalazine -related adverse events of real-world through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: Disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio the Bayesian confidence propagation neural network and the multi-item gamma Poisson shrinker (MGPS) algorithms were employed to quantify the signals of mesalazine -associated AEs. Results: Out of 14,149,980 reports collected from the FDA Adverse Event Reporting System database, 24,284 reports of mesalazine -associated AEs were identified. A total of 170 significant disproportionality preferred terms conforming to the four algorithms simultaneously were retained. The most common AEs included colitis ulcerative, diarrhoea, condition aggravated, crohn's disease, fatigue, abdominal pain, nausea, haematochezia, which were corresponding to those reported in the specification and clinical trials. Unexpected significant AEs as dizziness, drug ineffective, drug hypersensitivity, infection, off label use, weight decreased, decreased appetite, arthralgia, rash might also occur. The median onset time of mesalazine -related AEs was 1,127 days (interquartile range [IQR] 1,127-1,674 days), and most of the cases occurred 2 years later (n = 610, 70.93%) and within the first 1 month (n = 89, 10.35%) after mesalazine initiation. Conclusion: Results of our study were consistent with clinical observations. We also found potential new and unexpected AEs signals for mesalazine, suggesting prospective clinical studies were needed to confirm these results and illustrate their relationship. Our results could provide valuable evidence for further safety studies of mesalazine.

New genetic biomarkers predicting 5-aminosalicylate-induced adverse events in patients with inflammatory bowel diseases

Background

Notably, 5-aminosalicylates (5-ASA) are vital in treating inflammatory bowel diseases (IBD). The adverse events of 5-ASA rarely occur but they could be fatal.

Objectives

We aimed to discover new genetic biomarkers predicting 5-ASA-induced adverse events in patients with IBD.

Design

This was a retrospective observational study.

Methods

We performed a genome-wide association study on patients with IBD in South Korea. We defined subset 1 as 39 all adverse events and 272 controls; subset 2 as 20 severe adverse events and 291 controls (mild adverse events and control); subset 3 as 20 severe adverse events and 272 controls; and subset 4 as 19 mild adverse events and 272 controls. Logistic regression analysis was performed and commonly found associated genes were determined as candidate single-nucleotide polymorphisms predicting 5-ASA adverse events.

Results

Patients with Crohn's disease (CD) were significantly negatively associated with the development of adverse events compared to patients with ulcerative colitis (UC) (5.3% versus 22.9%). However, sex and age at diagnosis were unassociated with the adverse events of 5-ASA. rs13898676 [odds ratio (OR), 20.33; 95% confidence interval (CI), 5.69-72.67; p = 3.57 × e-6], rs12681590 (OR, 7.35; 95% CI, 2.85-19.00; p = 3.78 × e-5), rs10967320 (OR, 4.51; 95% CI, 2.18-9.31; p = 4.72 × e-5), and rs78726924 (OR, 3.54; 95% CI, 1.69-7.40; p = 7.96 × e-5) were genetic biomarkers predicting 5-ASA-induced severe adverse events in patients with IBD.

Conclusion

The adverse events of 5-ASA were more common in patients with UC than those with CD in our study. We found that novel rs13898676 nearby WSB2 was the most significant genetic locus contributing to 5-ASA's adverse event risk.

Regulators of G-Protein Signaling (RGS) in Sporadic and Colitis-Associated Colorectal Cancer

Colorectal cancer (CRC) is one of the most common neoplasms worldwide. Among the risk factors of CRC, inflammatory bowel disease (IBD) is one of the most important ones leading to the development of colitis-associated CRC (CAC). G-protein coupled receptors (GPCR) are transmembrane receptors that orchestrate a multitude of signaling cascades in response to external stimuli. Because of their functionality, they are promising targets in research on new strategies for CRC diagnostics and treatment. Recently, regulators of G-proteins (RGS) have been attracting attention in the field of oncology. Typically, they serve as negative regulators of GPCR responses to both physiological stimuli and medications. RGS activity can lead to both beneficial and harmful effects depending on the nature of the stimulus. However, the atypical RGS-AXIN uses its RGS domain to antagonize key signaling pathways in CRC development through the stabilization of the β-catenin destruction complex. Since AXIN does not limit the efficiency of medications, it seems to be an even more promising pharmacological target in CRC treatment. In this review, we discuss the current state of knowledge on RGS significance in sporadic CRC and CAC with particular emphasis on the regulation of GPCR involved in IBD-related inflammation comprising opioid, cannabinoid and serotonin receptors.

Applying polygenic risk score methods to pharmacogenomics GWAS: challenges and opportunities

Polygenic risk scores (PRSs) have emerged as promising tools for the prediction of human diseases and complex traits in disease genome-wide association studies (GWAS). Applying PRSs to pharmacogenomics (PGx) studies has begun to show great potential for improving patient stratification and drug response prediction. However, there are unique challenges that arise when applying PRSs to PGx GWAS beyond those typically encountered in disease GWAS (e.g. Eurocentric or trans-ethnic bias). These challenges include: (i) the lack of knowledge about whether PGx or disease GWAS/variants should be used in the base cohort (BC); (ii) the small sample sizes in PGx GWAS with corresponding low power and (iii) the more complex PRS statistical modeling required for handling both prognostic and predictive effects simultaneously. To gain insights in this landscape about the general trends, challenges and possible solutions, we first conduct a systematic review of both PRS applications and PRS method development in PGx GWAS. To further address the challenges, we propose (i) a novel PRS application strategy by leveraging both PGx and disease GWAS summary statistics in the BC for PRS construction and (ii) a new Bayesian method (PRS-PGx-Bayesx) to reduce Eurocentric or cross-population PRS prediction bias. Extensive simulations are conducted to demonstrate their advantages over existing PRS methods applied in PGx GWAS. Our systematic review and methodology research work not only highlights current gaps and key considerations while applying PRS methods to PGx GWAS, but also provides possible solutions for better PGx PRS applications and future research.

Critical Signaling Transduction Pathways and Intestinal Barrier: Implications for Pathophysiology and Therapeutics

The intestinal barrier is a sum of the functions and structures consisting of the intestinal mucosal epithelium, mucus, intestinal flora, secretory immunoglobulins, and digestive juices. It is the first-line defense mechanism that resists nonspecific infections with powerful functions that include physical, endocrine, and immune defenses. Health and physiological homeostasis are greatly dependent on the sturdiness of the intestinal barrier shield, whose dysfunction can contribute to the progression of numerous types of intestinal diseases. Disorders of internal homeostasis may also induce barrier impairment and form vicious cycles during the response to diseases. Therefore, the identification of the underlying mechanisms involved in intestinal barrier function and the development of effective drugs targeting its damage have become popular research topics. Evidence has shown that multiple signaling pathways and corresponding critical molecules are extensively involved in the regulation of the barrier pathophysiological state. Ectopic expression or activation of signaling pathways plays an essential role in the process of shield destruction. Although some drugs, such as molecular or signaling inhibitors, are currently used for the treatment of intestinal diseases, their efficacy cannot meet current medical requirements. In this review, we summarize the current achievements in research on the relationships between the intestinal barrier and signaling pathways. The limitations and future perspectives are also discussed to provide new horizons for targeted therapies for restoring intestinal barrier function that have translational potential.

Transcriptome profiling Revealed the potential mechanisms of Shen Lin Bai Zhu San n-butanol extract on DSS induced Colitis in Mice and LC-MS analysis

BACKGROUND

Inflammatory bowel disease (IBD) is a chronic and recurrent inflammatory disorder in gastrointestinal tract. Shen Ling Bai Zhu San (SLBZS), which has a long history of use in Traditional Chinese Medicine (TCM), has been widely used to treat gastrointestinal diseases. The isolated fractions of TCM have also been proved to possess an important potential for treating diseases, which are due to their effective components.

PURPOSE

In this study, we examined the possibility that SLBZS and its isolated active fractions may prevent DSS-induced colitis, and investigated the potential mechanisms by regulating genetic profile of colon.

METHODS

Colitis mice were induced by 2.5% DSS for 7 days, and then SLBZS and different SLBZS extracts were administrated to protect the mice for 7 days. Body weight, diarrhea, bleeding in stool, colon length, spleen weight, cytokines of serum and colon and pathology of colon were assessed. The level of Ginsenoside Rg1, Re and Rb1 in different SLBZS extracts and qualitative analysis of n-butanol extract of SLBZS (S-Nb) was performed by HPLC and LC-MS, respectively. And the effects of S-Nb on the transcriptome in colitis were investigated.

RESULTS

Our results showed that SLBZS and S-Nb significantly regained body weight, reduced DAI, splenomegaly and the length of colon and attenuated histological damage of the colon. Meanwhile, SLBZS and S-Nb markedly reduced the levels of TNF-α, IL-1β and IL-6 and increased the level of IL-10 in serum and colon. These effects may be associated with the high levels of Ginsenoside Rg1, Re and Rb1 and rich variety of compounds in S-Nb including 6 ginsenosides, glycyrrhizin, L-tryptophan, and so on. Transcriptome analysis revealed that S-Nb selectively regulated 103 differentially expressed genes (DEGs), 36 of which were changed in DSS-induced mice. And the genes of Per2, Per3, Npy and Serpina3m were closely related to colitis and also restored by S-Nb with different extent. Remarkably, these DEGs modulated the biological functions of colitis mice, including extracellular region, response to external stimulus, MAPK signaling pathway and arginine and proline metabolism.

CONCLUSIONS

These data indicated that SLBZS and S-Nb blunted DSS-induced colitis by modulating differentially expression gene profile and biological functions based on their ginsenosides and rich compounds.

Precision medicine and drug optimization in adult inflammatory bowel disease patients

Inflammatory bowel diseases (IBD) encompass two main entities including ulcerative colitis and Crohn's disease. Although having a common global pathophysiological mechanism, IBD patients are characterized by a significant interindividual heterogeneity and may differ by their disease type, disease locations, disease behaviours, disease manifestations, disease course as well as treatment needs. Indeed, although the therapeutic armamentarium for these diseases has expanded rapidly in recent years, a proportion of patients remains with a suboptimal response to medical treatment due to primary non-response, secondary loss of response or intolerance to currently available drugs. Identifying, prior to treatment initiation, which patients are likely to respond to a specific drug would improve the disease management, avoid unnecessary side effects and reduce the healthcare expenses. Precision medicine classifies individuals into subpopulations according to clinical and molecular characteristics with the objective to tailor preventative and therapeutic interventions to the characteristics of each patient. Interventions would thus be performed only on those who will benefit, sparing side effects and expense for those who will not. This review aims to summarize clinical factors, biomarkers (genetic, transcriptomic, proteomic, metabolic, radiomic or from the microbiota) and tools that could predict disease progression to guide towards a step-up or top-down strategy. Predictive factors of response or non-response to treatment will then be reviewed, followed by a discussion about the optimal dose of drug required for patients. The time at which these treatments should be administered (or rather can be stopped in case of a deep remission or in the aftermath of a surgery) will also be addressed. IBD remain biologically complex, with multifactorial etiopathology, clinical heterogeneity as well as temporal and therapeutic variabilities, which makes precision medicine especially challenging in this area. Although applied for many years in oncology, it remains an unmet medical need in IBD.

A Systematic Review of Polygenic Models for Predicting Drug Outcomes

Polygenic models have emerged as promising prediction tools for the prediction of complex traits. Currently, the majority of polygenic models are developed in the context of predicting disease risk, but polygenic models may also prove useful in predicting drug outcomes. This study sought to understand how polygenic models incorporating pharmacogenetic variants are being used in the prediction of drug outcomes. A systematic review was conducted with the aim of gaining insights into the methods used to construct polygenic models, as well as their performance in drug outcome prediction. The search uncovered 89 papers that incorporated pharmacogenetic variants in the development of polygenic models. It was found that the most common polygenic models were constructed for drug dosing predictions in anticoagulant therapies (n = 27). While nearly all studies found a significant association with their polygenic model and the investigated drug outcome (93.3%), less than half (47.2%) compared the performance of the polygenic model against clinical predictors, and even fewer (40.4%) sought to validate model predictions in an independent cohort. Additionally, the heterogeneity of reported performance measures makes the comparison of models across studies challenging. These findings highlight key considerations for future work in developing polygenic models in pharmacogenomic research.

Validity of Diagnostic Algorithms for Inflammatory Bowel Disease in Japanese Hospital Claims Data

Inflammatory bowel disease (IBD) diagnoses are increasing in Japan. Some patients have symptoms that are difficult to control, and further research on IBD is needed. Claims databases, which have a large sample size, can be useful for IBD research. However, it is unclear whether the International Classification of Diseases, Tenth Revision (ICD-10) codes alone can correctly identify IBD. We aimed to develop algorithms to identify IBD in claims databases. We used claims data from the Department of Gastroenterology, Tohoku University Hospital from 1 January 2016 to 31 December 2020. We developed 11 algorithms by combining the ICD-10 code, prescription drug, and workup information. We had access to the database which contains all the information for Crohn’s disease and ulcerative colitis patients who visited our department, and we used it as the gold standard. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value for each algorithm. We enrolled 19,384 patients, and among them, 1012 IBD patients were identified in the gold standard database. Among 11 algorithms, Algorithm 4 (ICD-10 code and ≥1 prescription drugs) showed a strong performance (PPV, 94.8%; sensitivity, 75.6%). The combination of an ICD-10 code and prescription drugs may be useful for identifying IBD among claims data.

Pharmacogenetics-based personalized treatment in patients with inflammatory bowel disease: A review

The development of treatment options has revolutionized the prognosis of inflammatory bowel disease (IBD). However, a particular group of patients still experience therapeutic failure or drug side effects. Although the high inter-patient variability in therapy is associated with clinical factors, including age, disease behavior, and disease duration, they attribute only a small proportion of inter-individual variability. Thus, pharmacogenetics evaluating associations between specific genetic variations and drug responses or side effects have focused on optimizing therapeutic efficacy and minimizing toxicity in IBD treatment. Thiopurine S-methyltransferase (TPMT) and nudix hydrolase 15 (NUDT15) are well-established predictive markers of thiopurine-induced myelosuppression. Low TPMT activity is related to increased 6-thioguanine nucleotide levels, subsequently leading to myelotoxicity. NUDT15 variants are strongly associated with thiopurine-induced early leukopenia in Asians, with a lower incidence of TPMT-deficient allele. The Korean Association for the Study of Intestinal Diseases guidelines recommend pretreatment determination of NUDT15 genotypes, especially in East Asians, and NUDT15 R139C measurement has been approved for clinical use since 2019. Several studies have attempted to identify powerful genetic markers for personalized medicine. In this article, we review the identified pharmacogenetics of currently available drugs, focusing on 5-aminosalicylic acid, glucocorticosteroids, thiopurines, and anti-tumor necrosis factor-alpha agents.

A systematic review and analysis of the use of polygenic scores in pharmacogenomics

Polygenic scores (PGS) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGS for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n=30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGS were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g. schizophrenia-derived PGS for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGS, with between 3 and 6.6 million variants included in the PGS. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGS deposited on the PGS Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.

Effects of molecular weight of chitosan on anti-inflammatory activity and modulation of intestinal microflora in an ulcerative colitis model

This study investigated the therapeutic effects and mechanisms of chitosans (CSs) with different molecular weights on ulcerative colitis (UC). Three size classes of CSs (Mw ≤ 3, 50, and 200 kDa) were used in this study. The effect of large CSs (Mw ≤ 200 kDa) on UC was the best, followed by that of medium CSs (Mw ≤ 50 kDa), and that of small CSs (Mw ≤ 3 kDa) was the least in the LPS-induced Raw 264.7 cell model and DSS-induced UC mice model. The therapeutic mechanisms of three CSs are related to anti-oxidation, anti-inflammation, and regulation of immunoglobulin and intestinal flora by attenuating body weight loss, decreasing the disease activity index (DAI) and MPO activity, suppressing proinflammatory cytokines and IgG levels, down-regulating the level of oxidative stress, increasing anti-inflammatory cytokines, SOD activity and Prevotellaceae_UCG-001 levels, and reducing the abundance of Proteobacteria, Actinobacteria, and Escherichia-Shigella. In general, the molecular weight of CSs influences their efficacy against UC. CSs with an optimal molecular weight demonstrate good development prospects for ameliorating UC.