Clinical Characteristics of Different Primary Constipation Subtypes in a Chinese Population

Association between fecal short-chain fatty acid levels and constipation severity in subjects with slow transit constipation

OBJECTIVE

We measured the fecal levels of short-chain fatty acids (SCFAs) in subjects with slow transit constipation (STC) and assessed the correlation between SCFA levels and disease severity as well as quality of life.

METHODS

We isolated the supernatant from fecal samples of healthy and STC subjects and measured the SCFA levels. To assess the correlation between fecal SCFA levels and disease severity as well as quality of life, we used the Constipation Scoring System, Patient Assessment of Constipation Symptoms, and Patient Assessment of Constipation Quality of Life questionnaires.

RESULTS

16 STC subjects and 16 healthy controls were enrolled. STC subjects had lower SCFA levels, but the difference was not statistically significant (475.85 ± 251.68 vs. 639.77 ± 213.97 µg/ml, P = 0.056). Additionally, STC subjects had lower acetic and propionic acid levels (149.06 ± 88.54 vs. 261.33 ± 109.75 µg/ml and 100.60 ± 60.62 vs. 157.34 ± 66.37 µg/ml, respectively, P < 0.05) and higher isobutyric and isovaleric acid levels (27.21 ± 15.06 vs. 18.16 ± 8.65 µg/ml and 31.78 ± 18.81 vs. 16.90 ± 10.05 µg/ml, respectively, P < 0.05). At 252.21 µg/ml acetic acid, the specificity and sensitivity to distinguish healthy from STC subjects were 93.7% and 56.3%, respectively. In STC subjects, there were significant negative correlations between acetic and propionic acid levels and Constipation Scoring System scores.

CONCLUSION

Fecal SCFA, acetic acid, and propionic acid levels decreased in STC subjects. There were significant negative correlations between the levels of the two acids and constipation severity.

Nobiletin, an active component of Wenyang Yiqi formula, alleviates constipation associated depression through targeting MAPT to inhibit the MAPK signaling pathway

BACKGROUND

Slow transit constipation (STC) is a common gastrointestinal disorder that is often accompanied by depression. Nobiletin is a natural compound that has been shown to have anti-inflammatory and anti-depressant effects.

PURPOSE

To study the effects of nobiletin extracted from Wenyang Yiqi Formula 19 (WYF) on STC accompanied by depression and the related mechanism in STC mouse models.

METHODS

In this study, the effects of nobiletin on STC accompanied by depression were investigated in both an STC animal model and an in vitro study. The animal model was induced by loperamide, and the in vitro study used Interstitial cells of Cajal (ICCs) isolated from STC mice. The efficacy of nobiletin was assessed by comparing various parameters, including stool particle counts, moisture content, intestinal propulsive rate, colon histopathology, microtubule-associated protein-tau (MAPT) expression in colon tissue, serum levels of TNF-α, IL-1β, IL-6, IFN-γ, and the levels of MAPK pathway-related proteins among three experimental groups.

RESULTS

Nobiletin treatment significantly improved stool particle counts, moisture content, intestinal propulsive rate, and colon histopathology in the STC animal model. Nobiletin also decreased MAPT expression in colon tissue and serum levels of TNF-α, IL-1β, IL-6, IFN-γ, and the levels of MAPK pathway-related proteins. In the in vitro study, nobiletin treatment reversed the increased cell proliferation and cell apoptosis observed in ICC isolated from the STC model.

CONCLUSION

The findings of this study indicate that nobiletin exhibits promising therapeutic potential in addressing STC accompanied by depression. This potential may be attributed to its ability to regulate the function of ICC by targeting MAPT.

Gastrointestinal Characteristics of Constipation from the Perspectives of Microbiome and Metabolome

BACKGROUND

Constipation is one of the most common gastrointestinal complaints. Yet, the underlying mechanisms of constipation remain to be explored deeply. Integration of microbiome and metabolome is powerful and promising to demonstrate characteristics of constipation.

AIM OF STUDY

This study aimed to characterize intestinal microbiome and metabolome of constipation. In addition, this study revealed the correlations among behaviors, intestinal microbiota, and metabolites interrupted by constipation.

METHODS

Firstly, the constipation model was successfully applied. At the macro level, the ability of learning, memory, locomotor activity, and the defecation index of rats with constipation-like phenotype were characterized. At the micro-level, 16S rRNA sequencing was applied to analyze the intestinal microbiota in rats with constipation-like phenotype. 1H nuclear magnetic resonance (NMR)-based metabolomics was employed to investigate the metabolic phenotype of constipation. In addition, we constructed a correlation network, intuitively showing the correlations among behaviors, intestinal microbiota, and metabolites.

RESULTS

Constipation significantly attenuated the locomotor activity, memory recognition, and frequency of defecation of rats, while increased the time of defecation. Constipation significantly changed the diversity of intestinal microbial communities, which correspondingly involved in 5 functional pathways. Besides, 28 fecal metabolites were found to be associated with constipation, among which 14 metabolites were further screened that can be used to diagnose constipation. On top of this, associated networks intuitively showed the correlations among behaviors, intestinal microbiota, and metabolites.

CONCLUSIONS

The current findings are significant in terms of not only laying a foundation for understanding characteristics of constipation, but also providing accurate diagnosis and treatments of constipation clinically.

GI factors, potential to predict prostate motion during radiotherapy; a scoping review

Purpose

A scoping literature review was conducted to identify gastrointestinal (GI) factors most likely to influence prostate motion during radiotherapy. We proffer that patient specific measurement of these GI factors could predict motion uncertainty during radiotherapy, facilitating personalised care by optimising treatment technique e.g., daily adaption or via bespoke patient pre-habilitation and preparation.

Methods

The scoping review was undertaken as per JBI guidelines. Searches were conducted across four databases: Ovid Medline®, EMBASE, CINAHL and EBSCO discovery. Articles written in English from 2010-present were included. Those pertaining to paediatrics, biological women exclusively, infectious and post-treatment GI morbidity and diet were excluded.Common GI factors impacting men were identified and related symptoms, incidence and measurement tools examined. Prevalence among persons with prostate cancer was explored and suitable assessment tools discussed.

Results

A preliminary search identified four prominent GI-factors: mental health, co-morbidity and medication, physical activity, and pelvic floor disorder. The scoping search found 3644 articles; 1646 were removed as duplicates. A further 1249 were excluded after title and abstract screening, 162 remained subsequent to full text review: 42 mental health, 53 co-morbidity and medication, 39 physical activity and 28 pelvic floor disorder.Six GI factors prevalent in the prostate cancer population and estimated most likely to influence prostate motion were identified: depression, anxiety, diabetes, obesity, low physical activity, and pelvic floor disorder. Reliable, quick, and easy to use tools are available to quantify these factors.

Conclusion

A comprehensive GI factor assessment package suitable to implement into the radiotherapy clinic has been created. Unveiling these GI factors upfront will guide improved personalisation of radiotherapy.

Subtyping intractable functional constipation in children using clinical and laboratory data in a classification model

Background

Children with intractable functional constipation (IFC) who are refractory to traditional pharmacological intervention develop severe symptoms that can persist even in adulthood, resulting in a substantial deterioration in their quality of life. In order to better manage IFC patients, efficient subtyping of IFC into its three subtypes, normal transit constipation (NTC), outlet obstruction constipation (OOC), and slow transit constipation (STC), at early stages is crucial. With advancements in technology, machine learning can classify IFC early through the use of validated questionnaires and the different serum concentrations of gastrointestinal motility-related hormones.

Method

A hundred and one children with IFC and 50 controls were enrolled in this study. Three supervised machine-learning methods, support vector machine, random forest, and light gradient boosting machine (LGBM), were used to classify children with IFC into the three subtypes based on their symptom severity, self-efficacy, and quality of life which were quantified using certified questionnaires and their serum concentrations of the gastrointestinal hormones evaluated with enzyme-linked immunosorbent assay. The accuracy of machine learning subtyping was evaluated with respect to radiopaque markers.

Results

Of 101 IFC patients, 37 had NTC, 49 had OOC, and 15 had STC. The variables significant for IFC subtype classification, according to SelectKBest, were stool frequency, the satisfaction domain of the Patient Assessment of Constipation Quality of Life questionnaire (PAC-QOL), the emotional self-efficacy for Functional Constipation questionnaire (SEFCQ), motilin serum concentration, and vasoactive intestinal peptide serum concentration. Among the three models, the LGBM model demonstrated an accuracy of 83.8%, a precision of 84.5%, a recall of 83.6%, a f1-score of 83.4%, and an area under the receiver operating characteristic curve (AUROC) of 0.89 in discriminating IFC subtypes.

Conclusion

Using clinical characteristics measured by certified questionnaires and serum concentrations of the gastrointestinal hormones, machine learning can efficiently classify pediatric IFC into its three subtypes. Of the three models tested, the LGBM model is the most accurate model for the classification of IFC, with an accuracy of 83.8%, demonstrating that machine learning is an efficient tool for the management of IFC in children.

Characteristics of fecal microbiota in different constipation subtypes and association with colon physiology, lifestyle factors, and psychological status

Background

Patients with chronic constipation (CC) show altered gut microbial composition.

Objectives

To compare the fecal microbiota with different constipation subtypes and to identify potential influencing factors.

Design

This is a prospective cohort study.

Methods

The stool samples of 53 individuals with CC and 31 healthy individuals were analyzed using 16S rRNA sequencing. The associations between microbiota composition and colorectal physiology, lifestyle factors, and psychological distress were analyzed.

Results

In all, 31 patients with CC were classified as having slow-transit constipation, and 22 were classified under normal-transit constipation. The relative abundance of Bacteroidaceae was lower, and the relative abundance of Peptostreptococcaceae, Christensenellaceae, and Clostridiaceae was higher in slow-transit than in normal-transit group. In all, 28 and 25 patients with CC had dyssynergic defecation (DD) and non-DD, respectively. The relative abundance of Bacteroidaceae and Ruminococcaceae was higher in DD than in non-DD. Rectal defecation pressure was negatively correlated with the relative abundance of Prevotellaceae and Ruminococcaceae but positively correlated with that of Bifidobacteriaceae in CC patients. Multiple linear regression analysis suggested that depression was a positive predictor of Lachnospiraceae relative abundance, and sleep quality was an independent predictor of decreased relative abundance of Prevotellaceae.

Conclusion

Patients with different CC subtypes showed different characteristics of dysbiosis. Depression and poor sleep were the main factors that affected the intestinal microbiota of patients with CC.

Plain language summary

Characteristics of fecal microbiota in different constipation subtypes and association with colon physiology, lifestyle factors, and psychological status Patients with chronic constipation (CC) show altered gut microbial composition. Previous studies in CC are limited by lacking of subtype stratification, which is reflected in the lack of agreement in findings across the large number of microbiome studies. We analyzed stool microbiome of 53 CC patients and 31 healthy individuals using 16S rRNA sequencing. We found that the relative abundance of Bacteroidaceae was lower, and the relative abundance of Peptostreptococcaceae, Christensenellaceae, and Clostridiaceae was higher in slow-transit than in normal-transit CC patients. The relative abundance of Bacteroidaceae and Ruminococcaceae was higher in dyssynergic defecation (DD) than in non-DD patients with CC. In addition, depression was a positive predictor of Lachnospiraceae relative abundance, and sleep quality was an independent predictor of decreased relative abundance of Prevotellaceae in all CC patients. This study emphasizes patients with different CC subtypes have different characteristics of dysbiosis. Depression and poor sleep may be the main factors that affect the intestinal microbiota of patients with CC.

Mechanistic Prediction of Chinese Herb Compound (Zhi Zhu Ma Ren Pill) in the Treatment of Constipation Using Network Pharmacology and Molecular Docking

Background: Constipation is one of the most prevalent chronic gastrointestinal diseases. Notably, previous studies have demonstrated that Chinese herbal compounds may exert effects on constipation. The present study aimed to predict the mechanisms underlying the effects of Zhi Zhu Ma Ren Pill (ZZMRP), which includes Aurantii Fructus Immaturus, Atractylodis Macrocephalae Rhizoma, Fructus Cannabis, Paeonia lactiflora and Radix Asteris in the treatment of constipation, using network pharmacology and molecular docking. Methods: The components and target information of ZZMRP were accessed using the Traditional Chinese Medicine Systems Pharmacology database and analysis platform, and the associated targets of constipation were obtained from the GeneCards, Disgenet, Online Mendelian Inheritance in Man, DrugBANK and Therapeutic Target Database databases. The major targets were subsequently selected using a Venn diagram and network topology analysis, which was followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Molecular docking was performed to authenticate the binding activity between active components and core targets. Results: A total of 44 active components, 249 targets of ZZMRP and 1501 targets associated with constipation were acquired. A total of 122 intersection targets were discovered between ZZMRP and constipation. Subsequently, 18 key targets were authenticated, including tumor protein 53, RAC-alpha serine/threonine-protein kinase, JUN and caspase-3. GO and KEGG pathway enrichment analysis indicated that mitogen-activated protein kinase, tumor necrosis factor, and phosphoinositide 3-kinase/protein kinase B signaling pathways may be involved in the treatment of constipation using ZZMRP. Molecular docking suggested that quercetin, kaempferol, and luteolin exhibited high binding affinities with several of the primary targets. Conclusions: The active components, core targets, and signaling pathways of ZZMRP in the treatment of constipation were predicted, which may be applicable to the development of treatments for constipation and application of ZZMRP.

Prevalence of constipation in adults with obesity class II and III and associated factors

BACKGROUND

Constipation and obesity have common risk factors. However, little is known about the occurrence of constipation in individuals with severe obesity and the associated factors.

OBJECTIVE

To evaluate the prevalence of intestinal constipation and its associated factors in adults with obesity class II and III.

METHOD

This study analyzed baseline data from a randomized clinical trial with adults aged 18-64 with a Body Mass Index (BMI) ≥ 35 kg/m2, living in the metropolitan region of Goiânia, Brazil. Data were collected using a questionnaire containing sociodemographic, lifestyle, level of obesity, presence of comorbidities, water intake and food consumption variables. The outcome variable was constipation assessed by the Rome III criteria and the Bristol Stool Form Scale. Multiple Poisson regression analysis was used to assess the association between explanatory variables and the outcome.

RESULTS

Among the 150 participants, the prevalence of constipation was 24.67% (95% CI: 17.69-31.64). After multiple regression analyses constipation was associated with polypharmacy (adjusted PR: 2.99, 95% CI: 1.18-7.57, p = 0.021), younger age group i.e. 18-29 years (adjusted PR: 3.12, 95% CI: 1.21-8.06, p = 0.019) and former smoking (adjusted PR: 3.24, 95% CI: 1.28-9.14, p = 0.014). There was no statistically significant association between constipation and daily consumption of fiber-rich foods, however, the non-consumption of whole grains was borderline significant (adjusted PR: 2.92, 95% CI: 1.00 to 8.49, p = 0.050).

CONCLUSION

A high prevalence of constipation was found in adults with obesity class II and III. Constipation was significantly associated with the simultaneous use of five or more medications, younger age group and being a former smoker.