Novel Symptom Subgroups in Individuals With Irritable Bowel Syndrome Predict Disease Impact and Burden

Novel Irritable Bowel Syndrome Subgroups Are Reproducible in the Global Adult Population

BACKGROUND & AIMS

Current classification systems for irritable bowel syndrome (IBS) based on bowel habit do not consider psychological impact. We validated a classification model in a UK population with confirmed IBS, using latent class analysis, incorporating psychological factors. We applied this model in the Rome Foundation Global Epidemiological Survey (RFGES), assessing impact of IBS on the individual and the health care system, and examining reproducibility.

METHODS

We applied our model to 2195 individuals in the RFGES with Rome IV-defined IBS. As described previously, we identified 7 clusters, based on gastrointestinal symptom severity and psychological burden. We assessed demographics, health care-seeking, symptom severity, and quality of life in each. We also used the RFGES to derive a new model, examining whether the broader concepts of our original model were replicated, in terms of breakdown and characteristics of identified clusters.

RESULTS

All 7 clusters were identified. Those in clusters with highest psychological burden, and particularly cluster 6 with high overall gastrointestinal symptom severity, were more often female, exhibited higher levels of health care-seeking, were more likely to have undergone previous abdominal surgeries, and had higher symptom severity and lower quality of life (P < .001 for trend for all). When deriving a new model, the best solution consisted of 10 clusters, although at least 2 seemed to be duplicates, and almost all mapped on to the previous clusters.

CONCLUSIONS

Even in the community, our original clusters derived from patients with physician-confirmed IBS identified groups of individuals with significantly higher rates of health care-seeking and abdominal surgery, more severe symptoms, and impairments in quality of life.

Common misconceptions and controversies in the management of irritable bowel syndrome

Despite an increase in our understanding of the pathophysiology of irritable bowel syndrome (IBS), in the context of abnormal gut-brain axis communication, and advances in both pharmacological and non-pharmacological treatment of the disorder, there remain areas in which there are misconceptions and controversies in the clinical management of IBS. This Perspective aims to highlight some of the most common misconceptions and controversies in IBS management, including those that the scientific literature has resolved, but for which further education of clinicians dealing with patients with IBS might be required to implement the findings from medical research. Areas of remaining contention are also discussed, as are suggestions as to how these issues could be addressed, both by advances in clinical practice and by further research.

Rome Foundation Working Team Report on overlap in disorders of gut-brain interaction

In patients with disorders of gut-brain interaction (DGBI), overlapping non-gastrointestinal conditions such as fibromyalgia, headaches, gynaecological and urological conditions, sleep disturbances and fatigue are common, as is overlap among DGBI in different regions of the gastrointestinal tract. These overlaps strongly influence patient management and outcome. Shared pathophysiology could explain this scenario, but details are not fully understood. This overlap has been shown to be of great relevance for DGBI. In addition, symptoms considered to be caused by a DGBI could have a detectable organic cause, and in patients with a diagnosed organic gastrointestinal disease, symptoms not clearly explained by the pathology defining this organic disease are common. Thus, the aims of this Rome Foundation Working Team Report were to review the literature on overlapping conditions among patients with paediatric and adult DGBI and, based on the available epidemiological and clinical evidence, make recommendations for the current diagnostic and therapeutic approach, and for future research. Specifically, we focused on other DGBI in the same or different gastrointestinal anatomical region(s), DGBI overlap with organic bowel diseases in remission, and DGBI overlap with non-gastrointestinal, non-structural conditions.

Gastrointestinal transit abnormalities in irritable bowel syndrome and their relation to symptoms

INTRODUCTION

Measurement of gastrointestinal (GI) transit is increasingly becoming a valuable tool in understanding the pathophysiology of symptoms of many digestive diseases, including irritable bowel syndrome (IBS). The objective of this article is to review the relevance of GI transit abnormalities for symptoms of IBS. These abnormalities relate to gastric emptying, small bowel transit, and colonic transit (whole gut transit).

AREAS COVERED

The article briefly describes the current methods of assessment, factors that influence the result of these methods and the relationship of abnormalities of GI transit with symptoms that have been reported in IBS patients. Finally, a recommendation to guide the application of transit studies in IBS in both clinical practice and research is provided.

EXPERT OPINION

Gastrointestinal transit is relevant to symptoms of bowel habits (stool frequency and form) and the relevance for other GI symptoms in IBS is not straightforward and needs further characterization. Intervention studies in IBS that incorporate objective measures of gut transit alongside symptom evaluation are warranted. Incorporating artificial intelligence into the methods of measuring transit could improve accuracy and simplify the measurements.

An evidence-based update on the diagnosis and management of irritable bowel syndrome

INTRODUCTION

Irritable bowel syndrome (IBS) is a disorder of gut-brain interaction affecting 5% of the population. The cardinal symptoms are abdominal pain and altered stool form or frequency.

AREAS COVERED

Diagnosis and management of IBS. We searched the literature for diagnostic accuracy studies, randomized controlled trials, and meta-analyses. A positive diagnosis of IBS, alongside testing to exclude celiac disease, is recommended. Exhaustive investigation has a low yield. Patients should be offered traditional dietary advice. If response is incomplete, specialist dietetic guidance should be considered. Probiotics may be beneficial, but quality of evidence is poor. First-line treatment of constipation is with laxatives, with secretagogues used where these are ineffective. Anti-diarrheal drugs should be used first-line for diarrhea, with second-line drugs including 5-hydroxytryptamine-3 antagonists, eluxadoline, or rifaximin, where available. First-line treatment of abdominal pain should be with antispasmodics, with gut-brain neuromodulators prescribed second-line. Low-dose tricyclic antidepressants, such as amitriptyline, are preferred. Brain-gut behavioral therapies are effective and have evidence for efficacy in patients refractory to standard therapies.

EXPERT OPINION

Despite substantial advances, there remains scope for improvement in terms of both the diagnosis and management of IBS. Reinforcement of positive diagnostic strategies for the condition and novel treatment paradigms are required.

Unsupervised machine learning highlights the challenges of subtyping disorders of gut-brain interaction

BACKGROUND

Unsupervised machine learning describes a collection of powerful techniques that seek to identify hidden patterns in unlabeled data. These techniques can be broadly categorized into dimension reduction, which transforms and combines the original set of measurements to simplify data, and cluster analysis, which seeks to group subjects based on some measure of similarity. Unsupervised machine learning can be used to explore alternative subtyping of disorders of gut-brain interaction (DGBI) compared to the existing gastrointestinal symptom-based definitions of Rome IV.

PURPOSE

This present review aims to familiarize the reader with fundamental concepts of unsupervised machine learning using accessible definitions and provide a critical summary of their application to the evaluation of DGBI subtyping. By considering the overlap between Rome IV clinical definitions and identified clusters, along with clinical and physiological insights, this paper speculates on the possible implications for DGBI. Also considered are algorithmic developments in the unsupervised machine learning community that may help leverage increasingly available omics data to explore biologically informed definitions. Unsupervised machine learning challenges the modern subtyping of DGBI and, with the necessary clinical validation, has the potential to enhance future iterations of the Rome criteria to identify more homogeneous, diagnosable, and treatable patient populations.

Personalisation of therapy in irritable bowel syndrome: a hypothesis

Irritable bowel syndrome (IBS) is a common disorder of gut-brain interaction characterised by symptoms of abdominal pain, occurring at least 1 day per week, and a change in stool frequency or form. Individuals with IBS are usually subtyped according to their predominant bowel habit, which is used to direct symptom-based treatment. However, this approach is probably an oversimplification of a complex and multidimensional condition, and other factors, such as psychological health, are known to influence symptom severity and prognosis. We have previously used latent class analysis, a method of mathematical modelling, to show that people with IBS can be classified into seven unique clusters based on a combination of gastrointestinal symptoms, abdominal pain, extraintestinal symptoms, and psychological comorbidity. The clusters can be used to predict the prognosis of IBS (eg, symptom severity), health-care use (eg, consultation behaviour, prescribing, and costs), and impact (eg, quality of life, work and productivity, activities of daily living, and income). These clusters could also be used to increase the personalisation of IBS treatment that better recognises the heterogenous nature of the condition. We present new data providing additional validation of our seven-cluster model and conduct a comprehensive evidence-based review of IBS management. Based on this evidence, we propose a framework of first-line and second-line treatments according to IBS cluster. Finally, we discuss what further research is needed to implement this approach in clinical practice, including the need for randomised trials comparing cluster-based treatment with conventional treatment according to stool subtype.

Effect of Brain-Gut Behavioral Treatments on Abdominal Pain in Irritable Bowel Syndrome: Systematic Review and Network Meta-Analysis

BACKGROUND & AIMS

Some brain-gut behavioral treatments (BGBTs) are beneficial for global symptoms in irritable bowel syndrome (IBS). United States management guidelines suggest their use in patients with persistent abdominal pain, but their specific effect on this symptom has not been assessed systematically.

METHODS

We searched the literature through December 16, 2023, for randomized controlled trials (RCTs) assessing efficacy of BGBTs for adults with IBS, compared with each other or a control intervention. Trials provided an assessment of abdominal pain resolution or improvement at treatment completion. We extracted data as intention-to-treat analyses, assuming dropouts to be treatment failures and reporting pooled relative risks (RRs) of abdominal pain not improving with 95% confidence intervals (CIs), ranking therapies according to the P score.

RESULTS

We identified 42 eligible randomized controlled trials comprising 5220 participants. After treatment completion, the BGBTs with the largest numbers of trials and patients recruited demonstrating efficacy for abdominal pain, specifically, included self-guided/minimal contact cognitive behavioral therapy (CBT) (RR, 0.71; 95% CI, 0.54-0.95; P score, 0.58), face-to-face multicomponent behavioral therapy (RR, 0.72; 95% CI, 0.54-0.97; P score, 0.56), and face-to-face gut-directed hypnotherapy (RR, 0.77; 95% CI, 0.61-0.96; P score, 0.49). Among trials recruiting only patients with refractory global IBS symptoms, group CBT was more efficacious than routine care for abdominal pain, but no other significant differences were detected. No trials were low risk of bias across all domains, and there was evidence of funnel plot asymmetry.

CONCLUSIONS

Several BGBTs, including self-guided/minimal contact CBT, face-to-face multicomponent behavioral therapy, and face-to-face gut-directed hypnotherapy may be efficacious for abdominal pain in IBS, although none was superior to another.

Multiomics Analysis Reveals Gut Virome-Bacteria-Metabolite Interactions and Their Associations with Symptoms in Patients with IBS-D

The gut microbiota is involved in the pathogenesis of diarrhea-predominant irritable bowel syndrome (IBS-D), but few studies have focused on the role of the gut virome in IBS-D. We aimed to explore the characteristics of the gut virome in patients with IBS-D, its interactions with bacteria and metabolites, and the associations between gut multiomics profiles and symptoms. This study enrolled twelve patients with IBS-D and eight healthy controls (HCs). The stool samples were subjected to metavirome sequencing, 16S rRNA gene sequencing, and untargeted metabolomic analysis. The participants completed relevant scales to assess the severity of their gastrointestinal symptoms, depression, and anxiety. The results revealed unique DNA and RNA virome profiles in patients with IBS-D with significant alterations in the abundance of contigs from Siphoviridae, Podoviridae, Microviridae, Picobirnaviridae, and Tombusviridae. Single-omics co-occurrence network analyses demonstrated distinct differences in the gut virus, bacteria, and metabolite network patterns between patients with IBS-D and HCs. Multiomics networks revealed that short-chain fatty acid-producing bacteria occupied more core positions in IBS-D networks, but had fewer links to viruses. Amino acids and their derivatives exhibit unique connectivity patterns and centrality features within the IBS-D network. The gastrointestinal and psychological symptom factors of patients with IBS-D were highly clustered in the symptom-multiomics network compared with those of HCs. Machine learning models based on multiomics data can distinguish IBS-D patients from HCs and predict the scores of gastrointestinal and psychological symptoms. This study provides insights into the interactions among gut viruses, bacteria, metabolites, and clinical symptoms in patients with IBS-D, indicating further classification and personalized treatment for IBS-D.

Utility of irritable bowel syndrome subtypes and most troublesome symptom in predicting disease impact and burden

BACKGROUND

Little is known about the characteristics of individuals with irritable bowel syndrome (IBS) according to stool subtype or the most troublesome symptom reported by the individual, or whether these are useful in predicting the impact of IBS.

METHODS

We collected demographic, gastrointestinal, and psychological symptoms, healthcare usage and direct healthcare costs, impact on work and activities of daily living, and quality of life data from individuals with Rome IV-defined IBS.

KEY RESULTS

We recruited 752 people with Rome IV IBS. Individuals with IBS-D reported a poorer disease-specific quality of life than those with IBS-C or IBS-M (mean (SD) IBS-QOL 45.3 (23.0) for IBS-D, vs. 52.3 (19.9) for IBS-C, vs. 49.4 (22.0) for IBS-M, p = 0.005). Mean (SD) IBS-QOL scores were also lower amongst those who reported diarrhea (44.8 (22.3)) or urgency (44.6 (22.3)) as their most troublesome symptom, compared with those reporting abdominal pain (52.2 (22.9)), constipation (49.5 (21.8)), or abdominal bloating or distension (50.4 (21.3)). However, there were no differences in mean EQ-5D scores, IBS severity, levels of anxiety, depression, somatoform symptom-reporting, or gastrointestinal symptom-specific anxiety. Direct healthcare costs of IBS were similar across all subtypes and all most troublesome symptom groups, although some differences in work productivity and social leisure activities were detected.

CONCLUSIONS AND INFERENCES

There appears to be limited variation in the characteristics of individuals with Rome IV IBS based on both stool subtypes and most troublesome symptom reported, suggesting that gastrointestinal symptoms alone have limited ability to predict disease impact and burden.

The gut microbiome in disorders of gut-brain interaction

Functional gastrointestinal disorders (FGIDs), chronic disorders characterized by either abdominal pain, altered intestinal motility, or their combination, have a worldwide prevalence of more than 40% and impose a high socioeconomic burden with a significant decline in quality of life. Recently, FGIDs have been reclassified as disorders of gut-brain interaction (DGBI), reflecting the key role of the gut-brain bidirectional communication in these disorders and their impact on psychological comorbidities. Although, during the past decades, the field of DGBIs has advanced significantly, the molecular mechanisms underlying DGBIs pathogenesis and pathophysiology, and the role of the gut microbiome in these processes are not fully understood. This review aims to discuss the latest body of literature on the complex microbiota-gut-brain interactions and their implications in the pathogenesis of DGBIs. A better understanding of the existing communication pathways between the gut microbiome and the brain holds promise in developing effective therapeutic interventions for DGBIs.

Novel symptom clusters predict disease impact and healthcare utilisation in inflammatory bowel disease: Prospective longitudinal follow-up study

BACKGROUND

Predicting adverse disease outcomes and high-volume users of healthcare amongst patients with inflammatory bowel disease (IBD) is difficult.

AIMS

The aim of this study is to use latent class analysis to create novel clusters of patients and to assess whether these predict outcomes during 6.5 years of longitudinal follow-up.

METHODS

Baseline demographic features, disease activity indices, anxiety, depression, and somatoform symptom-reporting scores were recorded for 692 adults. Faecal calprotectin (FC) was analysed at baseline in 348 (50.3%) patients (<250 mcg/g defined biochemical remission). Using baseline gastrointestinal and psychological symptoms, latent class analysis identified specific patient clusters. Rates of glucocorticosteroid prescription or flare, escalation, hospitalisation, or intestinal resection were compared between clusters using multivariate Cox regression.

RESULTS

A three-cluster model was the optimum solution; 132 (19.1%) patients had below-average gastrointestinal and psychological symptoms (cluster 1), 352 (50.9%) had average levels of gastrointestinal and psychological symptoms (cluster 2), and 208 (30.1%) had the highest levels of both gastrointestinal and psychological symptoms (cluster 3). Compared with cluster 1, cluster 3 had significantly increased risk of flare or glucocorticosteroid prescription (hazard ratio (HR): 2.13; 95% confidence interval (CI): 1.46-3.10), escalation (HR: 1.92; 95% CI: 1.34-2.76), a composite of escalation, hospitalisation, or intestinal resection (HR: 2.05; 95% CI: 1.45-2.88), or any of the endpoints of interest (HR: 2.06; 95% CI: 1.45-2.93). Healthcare utilisation was highest in cluster 3.

CONCLUSIONS

Novel model-based clusters identify patients with IBD at higher risk of adverse disease outcomes who are high-volume users of healthcare.