Comparison Log 2026-03-15 08:18:24.398624 mwtab Python Library Version: 2.0.0 Source: https://www.metabolomicsworkbench.org/rest/study/analysis_id/AN007809/mwtab/... Study ID: ST004630 Analysis ID: AN007809 Status: Inconsistent Sections "PROJECT" contain missmatched items: {'PROJECT_SUMMARY': ['Background and Objective: While alterations in gut microbiota have been implicated in childhood eating disorders, a comprehensive understanding of the functional and metabolic consequences in non-organic anorexia (NOA) remains limited. This study aimed to employ an integrated multi-omics approach to systematically characterize the gut microbial composition, functional potential, and associated metabolic profiles in children with NOA compared to healthy controls. Methods: A case-control study was conducted involving 88 children aged 1-5 years (48 NOA, 40 healthy controls). Gut microbiota composition was assessed via 16S rRNA gene sequencing of all fecal samples. Subsequently, the five most representative samples from each group were selected for deep shotgun metagenomic sequencing and liquid chromatography-mass spectrometry (LC-MS) based non-targeted metabolomics. Results: 16S rRNA sequencing revealed significantly higher microbial richness and diversity (Chao1 and Shannon indices, P < 0.001) in the NOA group. Taxonomic analysis showed a distinct structural shift: the NOA group exhibited increased relative abundances of the phyla Firmicutes and Bacteroidota, and the genera Bacteroides, Faecalibacterium, Subdoligranulum, and Roseburia, while Actinobacteriota, Bifidobacterium, and Enterococcus were decreased. Metagenomic analysis indicated significant alterations in key metabolic pathways, including a notable downregulation of riboflavin (Vitamin B2) metabolism (P < 0.05) and upregulation of pathways related to fat digestion and absorption in the NOA group. Metabolomic profiling identified 33 significantly altered fecal metabolites. Specifically, levels of L-carnitine derivatives were lower, whereas tyramine glucuronide was higher in the NOA group and was enriched in bile secretion-related pathways. Spearman correlation analysis demonstrated significant associations between these differential metabolites and the altered bacterial genera. Conclusion: Our integrated multi-omics analysis demonstrates that NOA in children is associated with a specific gut ecosystem characterized by altered microbiota structure, perturbed microbial metabolic functions (particularly riboflavin metabolism), and corresponding host-microbiota co-metabolic disturbances. These findings provide novel evidence for the disrupted "microbiota-metabolite" axis in NOA, offering new mechanistic insights and potential targets for intervention.', 'Background and Objective: While alterations in gut microbiota have been implicated in childhood eating disorders, a comprehensive understanding of the functional and metabolic consequences in non-organic anorexia (NOA) remains limited. This study aimed to employ an integrated multi-omics approach to systematically characterize the gut microbial composition, functional potential, and associated metabolic profiles in children with NOA compared to healthy controls. Methods: A case-control study was conducted involving 88 children aged 1-5 years (48 NOA, 40 healthy controls). Gut microbiota composition was assessed via 16S rRNA gene sequencing of all fecal samples. Subsequently, the five most representative samples from each group were selected for deep shotgun metagenomic sequencing and liquid chromatography-mass spectrometry (LC-MS) based non-targeted metabolomics. Results: 16S rRNA sequencing revealed significantly higher microbial richness and diversity (Chao1 and Shannon indices, P < 0.001) in the NOA group. Taxonomic analysis showed a distinct structural shift: the NOA group exhibited increased relative abundances of the phyla Firmicutes and Bacteroidota, and the genera Bacteroides, Faecalibacterium, Subdoligranulum, and Roseburia, while Actinobacteriota, Bifidobacterium, and Enterococcus were decreased. Metagenomic analysis indicated significant alterations in key metabolic pathways, including a notable downregulation of riboflavin (Vitamin B2) metabolism (P < 0.05) and upregulation of pathways related to fat digestion and absorption in the NOA group. Metabolomic profiling identified 33 significantly altered fecal metabolites. Specifically, levels of L-carnitine derivatives were lower, whereas tyramine glucuronide was higher in the NOA group and was enriched in bile secretion-related pathways. Spearman correlation analysis demonstrated significant associations between these differential metabolites and the altered bacterial genera. Conclusion: Our integrated multi-omics analysis demonstrates that NOA in children is associated with a specific gut ecosystem characterized by altered microbiota structure, perturbed microbial metabolic functions (particularly riboflavin metabolism), and corresponding host-microbiota co-metabolic disturbances. These findings provide novel evidence for the disrupted microbiota-metabolite axis in NOA, offering new mechanistic insights and potential targets for intervention.'], 'DEPARTMENT': ["Guizhou Branch of Shanghai Children's Medical Center", "Guizhou Branch of Shanghai Children''s Medical Center"]} Sections "STUDY" contain missmatched items: {'STUDY_SUMMARY': ['Background and Objective: While alterations in gut microbiota have been implicated in childhood eating disorders, a comprehensive understanding of the functional and metabolic consequences in non-organic anorexia (NOA) remains limited. This study aimed to employ an integrated multi-omics approach to systematically characterize the gut microbial composition, functional potential, and associated metabolic profiles in children with NOA compared to healthy controls. Methods: A case-control study was conducted involving 88 children aged 1-5 years (48 NOA, 40 healthy controls). Gut microbiota composition was assessed via 16S rRNA gene sequencing of all fecal samples. Subsequently, the five most representative samples from each group were selected for deep shotgun metagenomic sequencing and liquid chromatography-mass spectrometry (LC-MS) based non-targeted metabolomics. Results: 16S rRNA sequencing revealed significantly higher microbial richness and diversity (Chao1 and Shannon indices, P < 0.001) in the NOA group. Taxonomic analysis showed a distinct structural shift: the NOA group exhibited increased relative abundances of the phyla Firmicutes and Bacteroidota, and the genera Bacteroides, Faecalibacterium, Subdoligranulum, and Roseburia, while Actinobacteriota, Bifidobacterium, and Enterococcus were decreased. Metagenomic analysis indicated significant alterations in key metabolic pathways, including a notable downregulation of riboflavin (Vitamin B2) metabolism (P < 0.05) and upregulation of pathways related to fat digestion and absorption in the NOA group. Metabolomic profiling identified 33 significantly altered fecal metabolites. Specifically, levels of L-carnitine derivatives were lower, whereas tyramine glucuronide was higher in the NOA group and was enriched in bile secretion-related pathways. Spearman correlation analysis demonstrated significant associations between these differential metabolites and the altered bacterial genera. Conclusion: Our integrated multi-omics analysis demonstrates that NOA in children is associated with a specific gut ecosystem characterized by altered microbiota structure, perturbed microbial metabolic functions (particularly riboflavin metabolism), and corresponding host-microbiota co-metabolic disturbances. These findings provide novel evidence for the disrupted "microbiota-metabolite" axis in NOA, offering new mechanistic insights and potential targets for intervention.', 'Background and Objective: While alterations in gut microbiota have been implicated in childhood eating disorders, a comprehensive understanding of the functional and metabolic consequences in non-organic anorexia (NOA) remains limited. This study aimed to employ an integrated multi-omics approach to systematically characterize the gut microbial composition, functional potential, and associated metabolic profiles in children with NOA compared to healthy controls. Methods: A case-control study was conducted involving 88 children aged 1-5 years (48 NOA, 40 healthy controls). Gut microbiota composition was assessed via 16S rRNA gene sequencing of all fecal samples. Subsequently, the five most representative samples from each group were selected for deep shotgun metagenomic sequencing and liquid chromatography-mass spectrometry (LC-MS) based non-targeted metabolomics. Results: 16S rRNA sequencing revealed significantly higher microbial richness and diversity (Chao1 and Shannon indices, P < 0.001) in the NOA group. Taxonomic analysis showed a distinct structural shift: the NOA group exhibited increased relative abundances of the phyla Firmicutes and Bacteroidota, and the genera Bacteroides, Faecalibacterium, Subdoligranulum, and Roseburia, while Actinobacteriota, Bifidobacterium, and Enterococcus were decreased. Metagenomic analysis indicated significant alterations in key metabolic pathways, including a notable downregulation of riboflavin (Vitamin B2) metabolism (P < 0.05) and upregulation of pathways related to fat digestion and absorption in the NOA group. Metabolomic profiling identified 33 significantly altered fecal metabolites. Specifically, levels of L-carnitine derivatives were lower, whereas tyramine glucuronide was higher in the NOA group and was enriched in bile secretion-related pathways. Spearman correlation analysis demonstrated significant associations between these differential metabolites and the altered bacterial genera. Conclusion: Our integrated multi-omics analysis demonstrates that NOA in children is associated with a specific gut ecosystem characterized by altered microbiota structure, perturbed microbial metabolic functions (particularly riboflavin metabolism), and corresponding host-microbiota co-metabolic disturbances. These findings provide novel evidence for the disrupted microbiota-metabolite axis in NOA, offering new mechanistic insights and potential targets for intervention.'], 'DEPARTMENT': ["Guizhou Branch of Shanghai Children's Medical Center", "Guizhou Branch of Shanghai Children''s Medical Center"]} 'Metabolites' section of 'MS_METABOLITE_DATA' block do not match. 'Data' section of 'MS_METABOLITE_DATA' block do not match.