Psychiatric comorbidities among adult patients with disorders of gut-brain interaction: Prevalence and relationships to treatment outcomes

The COVID-19 pandemic as a modifier of DGBI symptom severity: A systematic review and meta-analysis

BACKGROUND

This SRMA reviewed and assessed the changes in the severity of disorders of gut-brain interaction (DGBI) symptoms during the COVID-19 pandemic, and evaluated factors associated with symptom severity changes.

METHODS

Electronic databases were searched until February 2024, for articles reporting on changes in symptom severity in DGBI patients during the COVID-19 pandemic. The proportion of DGBI patients who reported a change in their symptom severity were pooled using a random-effects model, and subgroup analyses were conducted to assess the effect of socio-cultural modifiers on symptom severity in DGBI.

KEY RESULTS

Twelve studies including 3610 DGBI patients found that 31.4% (95% CI, 15.9-52.5) of DGBI patients experienced symptom deterioration, while 24.3% (95% CI, 10.2-47.5) experienced improvement. Countries with high gross domestic product (GDP) had a 43.5% (95% CI, 16.3-75.2) likelihood of symptom deterioration, compared to 9.2% (95% CI, 1.4-42.2) in lower GDP countries. Similarly, countries with low COVID fatality rates had a 60.1% (95% CI, 19.7-90.3) likelihood of symptom deterioration, compared to 18.3% (95% CI, 7.8-36.9) in higher fatality rate countries. Countries with lenient COVID policies had a 58.4% (95% CI, 14.1-92.3) likelihood of symptom deterioration, compared to 19% (95% CI, 8.2-38.1) in countries with stricter policies. Patients in high vaccine hesitancy countries had a 51.4% (95% CI, 19.5-82.2) likelihood of symptom deterioration, compared to 10.6% (95% CI, 2.7-33.4) in low vaccine hesitancy countries.

CONCLUSIONS & INFERENCES

This meta-analysis reveals that a significantly higher proportion of DGBI patients experienced deterioration of symptoms during the COVID-19 pandemic. Various sociocultural, economic and environmental factors potentially modify the effects of the COVID-19 pandemic on DGBI.

Latent profile analysis reveals the central role of psychological symptoms in driving disease severity in chronic constipation

BACKGROUND

Chronic constipation (CC) is defined by symptom criteria reflecting heterogenous physiology. However, many patients with CC have significant psychological comorbidities-an alternative definition using a biopsychosocial classification model could be warranted to inform future treatments. We sought to: (1) empirically derive psychological symptom profiles of patients with CC using latent profile analysis and (2) validate these profiles by comparing them on symptom severity, GI-specific anxiety, body mass index (BMI), and anorectal manometry findings.

METHODS

Participants included adults presenting for anorectal manometry for CC (N = 468, 82% female, Mage = 47). Depression/anxiety symptoms and eating disorder (ED) symptoms (EAT-26) were used as indicators (i.e., variables used to derive profiles) representing unique psychological constructs. Constipation symptoms, GI-specific anxiety, BMI, and anorectal manometry results were used as validators (i.e., variables used to examine the clinical utility of the resulting profiles).

KEY RESULTS

A 5-profile solution provided the best statistical fit, comprising the following latent profiles (LPs): LP1 termed "high dieting, low bulimia;" LP2 termed "high ED symptoms;" LP3 termed "moderate ED symptoms;" LP4 termed "high anxiety and depression, low ED symptoms;" and LP5 termed "low psychological symptoms." The low psychological symptom profile (61% of the sample) had lower abdominal and overall constipation severity and lower GI-specific anxiety compared to the four profiles characterized by higher psychological symptoms (of any type). Profiles did not significantly differ on BMI or anorectal manometry results.

CONCLUSIONS AND INFERENCES

Profiles with high psychological symptoms had increased constipation symptom severity and GI-specific anxiety in adults with CC. Future research should test whether these profiles predict differential treatment outcomes.

Characterizing the Impact of Disorders of the Gut-Brain Interaction on Mental and Physical Health Functioning Among Spanish-Speaking Latino Adults Living in the United States

INTRODUCTION

Latino individuals are underrepresented in the disorders of the gut-brain interaction (DGBI) literature, and no work has explored how disorders of the gut-brain interaction affect health and well-being in this group.

METHODS

This study sought to explore how disorders of the gut-brain interaction affect health factors in a sample of Latino individuals (N = 292; 80.80% female; M age = 37.65 years, SD = 11.98) with (n = 60) and without (n = 232) a disorder of the gut-brain interaction based on current Rome Foundation diagnostic criteria (Rome IV).

RESULTS

DGBI was associated with increased pain intensity, pain disability, cardiovascular risk, depressive symptoms, and anxiety/panic symptoms and lower physical health-related quality of life and mental health-related quality of life controlling for age, sex, and nativity.

DISCUSSION

Better understanding mental health and treatment-seeking behaviors among Latino individuals may help clinical gastroenterologists engage their Latino patients to a greater extent and thus provide higher quality of care.

Combined GWAS and single cell transcriptomics uncover the underlying genes and cell types in disorders of gut-brain interaction

Disorders of gut-brain interaction (DGBIs), formerly known as functional gastrointestinal disorders, are extremely common and historically difficult to manage. This is largely because their cellular and molecular mechanisms have remained poorly understood and understudied. One approach to unravel the molecular underpinnings of complex disorders such as DGBIs is performing genome wide association studies (GWASs). However, due to the heterogenous and non-specific nature of GI symptoms, it has been difficult to accurately classify cases and controls. Thus, to perform reliable studies, we need to access large patient populations which has been difficult to date. Here, we leveraged the UK Biobank (UKBB) database, containing genetic and medical record data of over half a million individuals, to perform GWAS for five DGBI categories: functional chest pain, functional diarrhea, functional dyspepsia, functional dysphagia, and functional fecal incontinence. By applying strict inclusion and exclusion criteria, we resolved patient populations and identified genes significantly associated with each condition. Leveraging multiple human single-cell RNA-sequencing datasets, we found that the disease associated genes were highly expressed in enteric neurons, which innervate and control GI functions. Further expression and association testing-based analyses revealed specific enteric neuron subtypes consistently linked with each DGBI. Furthermore, protein-protein interaction analysis of each of the disease associated genes revealed protein networks specific to each DGBI, including hedgehog signaling for functional chest pain and neuronal function and neurotransmission for functional diarrhea and functional dyspepsia. Finally, through retrospective medical record analysis we found that drugs that inhibit these networks are associated with an increased disease risk, including serine/threonine kinase 32B drugs for functional chest pain, solute carrier organic anion transporter family member 4C1, mitogen-activated protein kinase 6, and dual serine/threonine and tyrosine protein kinase drugs for functional dyspepsia, and serotonin transporter drugs for functional diarrhea. This study presents a robust strategy for uncovering the tissues, cell types, and genes involved in DGBIs, presenting novel predictions of the mechanisms underlying these historically intractable and poorly understood diseases.

Assessment of Self-Reported Executive Function in Patients with Irritable Bowel Syndrome Using a Machine-Learning Framework

Introduction: Irritable bowel syndrome (IBS) is characterized as a disorder of the gut-brain interaction (DGBI). Here, we explored the presence of problems related to executive function (EF) in patients with IBS and tested the relative importance of cognitive features involved in EF. Methods: A total of 44 patients with IBS and 22 healthy controls (HCs) completed the Behavior Rating Inventory of Executive Function (BRIEF-A), used to identify nine EF features. The PyCaret 3.0 machine-learning library in Python was used to explore the data, generate a robust model to classify patients with IBS versus HCs and identify the relative importance of the EF features in this model. The robustness of the model was evaluated by training the model on a subset of data and testing it on the unseen, hold-out dataset. Results: The explorative analysis showed that patients with IBS reported significantly more severe EF problems than the HC group on measures of working memory function, initiation, cognitive flexibility and emotional control. Impairment at a level in need of clinical attention was found in up to 40% on some of these scales. When the nine EF features were used as input to a collection of different binary classifiers, the Extreme Gradient Boosting algorithm (XGBoost) showed superior performance. The working memory subscale was consistently selected with the strongest importance in this model, followed by planning and emotional control. The goodness of the machine-learning model was confirmed in an unseen dataset by correctly classifying 85% of the IBS patients. Conclusions: The results showed the presence of EF-related problems in patients with IBS, with a substantial impact of problems related to working memory function. These results suggest that EF should be part of an assessment procedure when a patient presents other symptoms of IBS and that working memory function should be considered a target when treating patients with the disorder. Further studies should include measures of EF as part of the symptom cluster characterizing patients with IBS and other DGBIs.