1. Introduction
Functional constipation (FC), encompassing normal-transmission constipation (NTC), slow-transmission constipation (STC), obstructed defecation constipation, and mixed constipation (MC), is a common gastrointestinal disorder characterized by difficulty in bowel movements and dry stools. In China, it is estimated that approximately 8.5% of adults suffer from constipation [
1], significantly affecting patients’ quality of life and imposing substantial economic burdens [
2], [
3]. While the pathogenesis of constipation remains unclear, it is largely attributed to dietary habits, lifestyle factors, and other influences [
4], [
5], [
6]. Early diagnosis followed by timely intervention can improve outcomes, whereas delayed diagnosis often leads to disease progression.
Recent studies [
7], [
8] have revealed altered gut microbial composition and metabolic pathways in patients with FC. Specific bacterial species have been implicated in the development of constipation [
9]. Transplantation of feces or characteristic bacteria from constipated patients to germ-free mice has been shown to alter intestinal transit and metabolism [
10], [
11]. Dysbiosis of the gut microbiota can induce disease progression in gut dysmotility and constipation. However, the characteristic flora associated with constipation remains inconclusive. The role of microbiome biomarkers in diagnosing constipation is underexplored, and existing studies are limited by small cohort sizes and lack of multicenter participation. Moreover, there is a paucity of studies integrating different types of multi-omics data, including microbiomes, metabolomes, transcriptomes, and proteomes. Multi-omics technology offers deeper insights into the pathogenesis and diagnosis of constipation.
The Chinese Gut Motility Project (CGMP) aims to study the etiology of constipation and corresponding clinical outcomes from a multi-omics perspective. The multi-omics data will be utilized to identify reliable predictive biomarkers for individual responses to constipation, particularly based on the characteristic microbiota of constipated populations. Additionally, we aim to design microbiota-directed foods (MDF) tailored to different constipated patients’ flora characteristics to pioneer new therapeutic approaches. This cohort’s rich longitudinal phenotypic dataset will facilitate investigations into numerous scientific questions related to constipation.
The primary objectives of the CGMP cohort include: ① Constructing a library of segmented intestinal flora characteristics specific to the constipated population to establish a microecological diagnostic platform; ② developing personalized clinical and MDF intervention strategies for each type of constipation based on gut flora characteristics. Ultimately, this comprehensive microbiological diagnostic platform will provide new possibilities for precision medicine in treating and managing constipation.
The secondary objectives of the CGMP cohort include: ① Exploring the relationship between the constipation microbiome and diet, lifestyle, and exposure; ② analyzing differences in host characteristics and microbiome among constipation patients.
2. Cohort design
2.1. Recruitment of research subjects
The CGMP cohort project aims to enroll at least 2000 patients with constipation and 500 healthy controls from the regions of Shanghai and Jiangsu Provinces in China. Recruitment will be based on recommendations from gastroenterologists at local hospitals, with inclusion criteria adhering to the Rome IV criteria for FC [
12]. Eligible participants will be enrolled in the cohort.
To facilitate recruitment, helpdesks will be established at each hospital to assist with participant enrollment and informed consent procedures. Cohort staff will distribute informational flyers to potential participants, and trained personnel will screen out non-compliant individuals, including those who have recently taken laxatives, according to established standards (
Fig. 1). Participants will be assessed for their willingness to participate and guided through the recruitment process, including consultation in the gastrointestinal department and relevant clinical tests.
Participants will complete several validated questionnaires through face-to-face interviews to assess the severity of constipation and its impact on quality of life. These include the Constipation Scoring System (CSS) [
13], Constipation Assessment Scale (CAS) [
14], Patient Assessment of Constipation Symptoms (PAC-SYM) [
15], Constipation Severity Instrument (CSI) [
16], Patient Assessment of Constipation Quality of Life (PAC-QOL) [
17], and Obstructed Defecation Syndrome Scoring (ODS) [
18]. Additional questionnaires will collect demographic information, lifestyle factors, dietary habits, physical activity, occupational history, medication history, and family history of disease. Biological samples, including fasting blood (12 h), fecal matter, saliva, and intestinal mucosal samples, will be collected within one week of recruitment completion to establish baseline data.
Recruitment for this project began in 2024. By early November 2024, 50 patients with constipation and 74 healthy controls had been recruited. Currently, an average of five constipated patients and two healthy controls are being recruited daily. Thus, we anticipate completing cohort recruitment by the end of 2025. Based on previous research [
19], a sample size of approximately 500 cases per group is sufficient for assessing 1000 histologic features. Given the four subtypes of constipation, a sample size of at least 500 cases per subtype group will be adequate for conducting comprehensive biological and clinical hypothesis tests.
2.2. Long-term follow-up
Constipation is a recurrent condition; thus, participants will undergo up to one year of follow-up to monitor their constipation status. Fecal and saliva samples will be collected monthly for 12 months. For patients with active symptoms, additional blood and intestinal mucosa samples will be collected alongside fecal samples at local medical centers. Follow-up data collection is crucial to address clinical questions such as the stability of gut flora characteristics over time and the influence of diet or other factors on constipation development. To minimize loss to follow-up, we will employ strategies such as offering free health checkups to encourage participants to remain in the study.
2.3. Collection of biological samples
Biological samples from constipated patients will be collected either at home or hospital sites. Fecal samples should be refrigerated (−20 °C) within 15 min of collection and transported under dry ice conditions before being processed and stored at −80 °C in the laboratory. Samples will be preserved in three states: raw fecal samples, fecal samples mixed with RNA protective solution, and samples mixed with 50% glycerol. Saliva samples will be collected in the hospital using tubes containing DNA-protecting solution and transferred to a −80 °C refrigerator within 10 h of collection. Participants must wait at least 30 min after eating, drinking, smoking, or chewing before providing saliva samples and should rinse their mouths with water beforehand. All serum and most whole blood samples are collected after a minimum fasting period of 8 h. Post-collection, these samples are temporarily stored at 4 °C before being aliquoted and preserved at −80 °C. Intestinal mucosal tissue samples are obtained during hospital colonoscopy or bowel surgery, with approximately four samples collected per subject. For each sampling site (including at least the ileum and 10 cm from the rectum), one sample is allocated for standard histopathological analysis, two samples are stored in RNA-protecting solution for molecular data generation (host and microorganisms, stored at −20 °C), and one sample is preserved in sterile tubes containing 5% glycerol (stored at −80 °C).
In general, all sample collections will be carried out using the standardized sampling tubes, normal saline, and nucleic acid preservation solutions provided by the Food Biotechnology Research Centre of Jiangnan University, China. The sample collections (blood and saliva) will be arranged to be conducted in the morning every day as much as possible. Each sample is clearly labeled with basic information such as sample number and collection time for subsequent search and management, and then quickly stored in a hospital −80 °C freezer. One month after the collection, all the biological samples are transported to the Food Biotechnology Research Center of Jiangnan University by means of dry ice or refrigerated trucks after ensuring good sealing, and then stored at −80 °C. Centers must adhere to consistent methods of sample collection, storage, and transport, and the collected samples will be relatively evenly distributed in different processing batches and testing projects, avoiding excessive concentration of samples from specific centers in certain batches. For metabolomics sample determination, is performed uniformly on the measurement platform after sample collection. Metagenomics and transcriptome analysis have good stability, and samples are measured in batches. Prior to data analysis, appropriate statistical methods (e.g., principal component analysis, analysis of variance) are used to assess whether there is a batch effect. If it is judged that there is a batch effect, some specialized statistical methods (e.g., the Combat method, the Empirical Bayes method) can be used to correct the data, thereby improving the repeatability and reliability of the data.
2.4. Clinical examination
Colonic transit time is employed in diagnosing STC. Anorectal manometry assesses the function of the pelvic floor muscles and nervous system, detecting whether the muscles around the anus and rectum contract and relax properly and if the enteric nervous system functions correctly. Defecography primarily identifies outlet obstruction constipation. FC can be further categorized into NTC, STC, obstructed defecation constipation, and MC based on colonic transit time, anorectal manometry, and defecography results.
2.5. Questionnaire Survey
The study’s questionnaires encompass various aspects, including demographics, lifestyle, dietary habits, physical activity, psychosomatic factors, and disease diagnosis and treatment records (Table S1 in Appendix A). These are primarily adapted from previous studies, such as the National Health and Nutrition Examination Survey (NHANES) cohort [
20] and the UK Biobank cohort [
21], with adjustments for regional differences in lifestyle and dietary habits. To streamline data collection and minimize data loss, all questionnaires will be administered via an online platform (Questionnaire Star, Changsha Ranxing Technology, China), which includes automatic alerts for missing or abnormal data. Professionally trained personnel will conduct face-to-face interviews with study participants to gather this information.
2.6. Detection of biological samples
Metabolomics testing will be performed on peripheral blood samples, with non-targeted metabolome analysis of plasma conducted using liquid chromatograph-mass spectrometer (LC-MS) [
22]. Fecal samples will undergo metagenomic sequencing, generating approximately 20 GB of data per sample. Additionally, fecal samples will be analyzed for metabolomics and other omics. Intestinal mucosal tissue samples will be used for transcriptome and microbiome analysis, while saliva samples will be subjected to microbiological analysis.
2.7. Microbial directed food intervention
Conventional microbiological treatments for constipation often fail to address the needs of all patients due to inter-individual differences in gut microbiota composition and function. MDF, designed to regulate the consumer’s intestinal community characteristics, have garnered attention for their potential to precisely shape or re-establish a healthy gut microbiota, thereby preventing or alleviating related diseases [
23], [
24]. The CGMP aims to develop MDF formulas tailored to the microbiota profiles of constipated patients. This approach seeks to create a novel therapeutic modality that improves constipation symptoms by targeting and modulating the specific microbiota of affected individuals. Dietary ingredients will be screened based on microbiota characteristics, including metabolic function and substrate utilization, and validated through initial formulation tests. These formulations will then undergo further validation in clinical trials (
Fig. 2). Enrolled patients willing to receive the dietary formulations will consume them daily for one month. They will undergo an on-site assessment at the hospital after one month, with follow-up visits at one month and six months post-intervention to evaluate constipation status and microbiota improvement.
2.8. Statistical analysis
In this study, a comprehensive suite of statistical methodologies will be employed to analyze and present descriptive data accurately. Regression analyses will be utilized to evaluate the relationship between the constipation phenotype and variables such as dietary habits, lifestyle, and physical activity. The contribution of these factors to microbiota variations will be assessed using permutational multivariate analysis of variance (PERMANOVA) and Mantel tests. For microbiome analyses, differences in α-diversity indices among study subgroups will be compared using the Kruskal-Wallis test or regression analyses. Species-level analyses will be conducted using microbiome multivariable associations with linear models (MaAsLin) or multiple regression models. Nonlinear dimensionality reduction techniques, such as consistent stream approximation and principal component analysis, will be applied to each histological dataset. Further integrated analyses, including correlation analysis, regression analysis, machine learning, and pathway enrichment analysis, will be performed to elucidate intricate relationships within the data.
3. Strengths and limitations
The CGMP is an ongoing prospective cohort study involving 2000 patients with constipation. This study’s depth is reflected in its comprehensive profiling of participants across various dimensions, including physical measures, lifestyle factors, psychosocial characteristics, medical records, and multi-omics profiles. Further, we also seek to further correlate various data information, such as studying the correlation between questionnaire information and microbiota and constipation, combining metabolomics, proteomics, and metagenomics to explore the metabolic characteristics of the intestinal flora in patients with constipation, and host factors associated with key bacteria are explored by probing the transcriptome and metagenomics of the colonic mucosa, so as to further explore the pathogenic mechanism of key bacteria in constipation. Such extensive data collection allows for a nuanced understanding of the interplay between these factors and constipation.
However, there are limitations to this study. Firstly, the cohort is comprised exclusively of Chinese individuals, which may limit the generalizability of the findings to other populations or ethnic groups. Additionally, as an observational study, it is inherently challenging to establish causal relationships from the cohort data alone.
4. Cohort progress
By November 2024, the CGMP cohort had successfully recruited 50 patients with constipation and 74 healthy individuals from Jiangsu Province based on stringent inclusion and exclusion criteria. The demographic characteristics of these participants are detailed in
Table 1. The age range of participants spans from 19 to 67 years old. Notably, 95.9% of the constipation patients are female, with an average weight and height of (58.50 ± 7.72) kg and (163.31 ± 4.80) cm, respectively. Their Bristol stool scale score and defecation frequency are significantly lower than those of healthy controls ((4.13 ± 1.11) vs (1.98 ± 0.98) and (0.95 ± 0.41) vs (0.45 ± 0.29), respectively). Biological samples collected from participants, including feces and blood, have been preserved at the Food Biotechnology Research Centre of Jiangnan University for future analysis.
Acknowledgments
We are grateful for the participation of all the volunteers and the members of the CGMP consortium. This work was supported by the Major Program of the National Natural Science Foundation of China (32394051).
Collaboration
The CGMP consortium welcomes collaboration with other cohorts. Potential collaborators are encouraged to contact the CGMP consortium via e-mail (wanglinlin@jiangnan.edu.cn) or website (
http://www.cgmp2024.com) for further information.
Data availability statement
Data from the CGMP cohort (CGMP) will be stored in the China National Center for Bioinformation (CNCB,
https://www.cncb.ac.cn). Both individual-level samples and data can be requested for research and scientific purposes, which comply with the informed consent signed by CGMP participants. This specifies that the collected samples and data will not be used for commercial purposes. Access to individual-level data should be approved by the management board of the CGMP consortium (website:
http://www.cgmp2024.com; e-mail address: wanglinlin@jiangnan.edu.cn).
Ethics statement
This cohort was approved by the ethics committee of Shanghai Tenth People’s Hospital (SHSY-IEC-4.1/20-116/01). Informed consent was obtained from all participants of this study.
Appendix A. Supplementary data
Supplementary data to this article can be found online at
https://doi.org/10.1016/j.eng.2024.11.011.
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