Diagnosis and treatment of Crohn disease
Diagnosis and treatment of all patients followed the European Crohn’s and Colitis Organization (ECCO) guidelines and the Chinese expert consensus on the diagnosis and management of pediatric inflammatory bowel disease [9–11]. The diagnosis of CD should be based on clinical manifestations, endoscopy, histopathology, and imaging results. Follow up observation was made to improve the accuracy of diagnosis. Disease activity was assessed by pediatric Crohn disease activity index (PCDAI) and patients with PCDAI < 10.0 were considered to be in remission. The PCDAI between 10.0-27.5 was defined as mild activity, 30.0-37.5 as moderate activity, and 40.0-100.0 as severe activity.
Study Cohort And Recruitment Of Subjects
To investigate the gut microbiota in CD patients, we first recruited a total of 163 children with chronic abdominal pain from the department of Pediatrics of the First Affiliated Hospital of Fujian Medical University between January 2018 and December 2021.The inclusion criteria for patients with chronic abdominal pain were as follows: 4 to 14 years of age, the course of abdominal pain is more than 3 months, at least once a month abdominal pain attacks, affecting children's daily life and learning. The after-exclusion criteria were applied to initial recruitment.
The exclusion criteria include: using antibiotics, probiotics, prebiotics, symbiosis, hormonal drugs, laxatives, proton pump inhibitors, insulin sensitizers, or herbal medicine in the recent 3 months. In addition, volunteers with a history of other autoimmune diseases, such as autoimmune thyroid disease, multiple sclerosis, rheumatoid arthritis, malignant tumors or history of gastrointestinal surgery, etc. are also excluded.
All the volunteers were divided into 3 groups according to the results of examination items: the control group (Col, n = 9), CD patient group (CD, n = 7). CD patients in remission group (CDR, n = 5) were obtained from the treatment and follow-up of the CD group. The inclusion criteria of the control group were as follows: children with chronic abdominal pain, normal C-reactive protein (CRP), normal procalcitonin (PCT), normal erythrocyte sedimentation rate (ESR), normal gastroenteroscopy, no abnormality of small intestine observed in intestinal magnetic resonance, and pathological results of mucosal biopsy not consistent with Crohn's disease. The experimental design is illustrated in Fig. 1.
Sample Collection
For bowel preparation for colonoscopy, each subject ingested 2 liters of polyethylene glycol electrolyte (PEG) solution. Then, the specimen was obtained from the ileocecal junction with biopsy forceps. The diameter of the specimen is about 2 mm. Fresh samples were then immediately placed in liquid nitrogen, and transferred to -80 ℃ refrigerator until use. Whole blood was collected via venipuncture from healthy donors after obtaining written informed consent. Blood was drawn into citrate (3.2% w/v) vacutainers using a 21-gauge needle. Whole blood samples were kept at low temperature until use.
Blood tests were performed at various stages of the disease for hemoglobin (Hb), hematocrit (Hct), white blood cell count (WBC), serum protein (Alb), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP).
Dna Isolation And Sequencing
DNA isolation, 16S rRNA gene amplification and sequencing were done as described previously [12]. Briefly, DNA were isolated by QIAamp UCP Pathogen Mini Kit (Qigen, Hilden, Germany). Distinct regions of V3-V4 were amplified by specific primers (341F: 5’-CCTACGGGRSGCAGCAG-3’; 806R: 5’-GGACTACVVGGGTATCTAATC-3’) with the barcode. Then, PCR products PCR product was purified with GeneJET™ Gel Extraction Kit (Thermo Scientific). Library preparation and sequencing were carried out by the Lybaybio library preparation kit (Lybaybio, Tianjin, China), and the library quality was assessed on the Qubit 2.0 Fluorometer (Thermo Scientific, CA, USA). At last, the library was sequenced on an Illumina Miseq platform (Illumina, CA, USA) and 300bp pare-end reads were generated.
Sequencing Data Analysis
The quality of the raw sequence data was initially evaluated with FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Then the sequences were split into groups corresponding to their taxonomy at the level of order, and then were assigned to operational taxonomic units (OTUs) at 97% similarity level [13]. All effective tags were clustered by Uparse software (V7.0.1001) [14]. A representative sequence of each OTU was assigned to a taxonomic level in the SILVA database (http://www.arb-silva.de). According to the results of OTU taxonomy, the abundance distribution and composition of each sample at five classification levels (phylum, class, order, family and genus) were obtained using QIIME software. The alpha diversity and beta diversity analyses were performed based on OTUs. Alpha diversity indices, including chao1, good-coverage, observed-species, PD_whole_tree, and Shannon, were calculated using QIIME (V1.8, http://qiime.org/scripts/alpha_rarefaction.html). Beta diversity on unweighted unifrac was also calculated by the QIIME software. Principal coordinate analysis (PCoA) was performed to visualize principal coordinates from complex multidimensional data. According to the composition and sequence distribution of each sample at each taxonomic level, the abundance differences of each taxon between two or more samples (groups) could be compared one by one. In the present study, the difference of abundance between groups at each taxonomic level was analyzed using Wilcoxon test. Hierarchical cluatering analysis (Hcluster) was generated using the UPGMA (Unweighted pair group method with arithmetic mean) sequential clustering method through the DendroUPGMA web server (URL: genomes.urv.cat/UPGMA). In addition, LDA Effect Size (LEfSe) analysis was conducted to search biomarkers with statistical differences between groups using LEfSe software with LDA Score of 3.