4.7 Article

Pre-Diagnostic Saliva Microbiota of School-Aged Children Who Developed Type 1 Diabetes or Inflammatory Bowel Diseases

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MDPI
DOI: 10.3390/ijms24098279

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autoimmune disease; Crohn's disease; microbiome; pediatric; risk factors; ulcerative colitis

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The composition and diversity of saliva microbiota are not successful predictors for pediatric type 1 diabetes mellitus (T1D) or inflammatory bowel diseases (IBD). However, the relative abundances of certain bacteria are altered before the onset of T1D, and the metabolic pathway PWY-5677 is predicted to be lowered. Investigating functional pathways might provide a better approach in searching for biomarkers for autoimmune disease in the future.
Altered commensal microbiota composition has been associated with pediatric type 1 diabetes mellitus (T1D) and inflammatory bowel diseases (IBD), but the causal relationship is still unclear. To search for potential pre-diagnostic biomarkers for pediatric T1D or IBD, we compared microbiota in saliva samples in a nested case-control design comprising children developing T1D (n(children) = 52) or IBD (n(children) = 21) and controls with a similar age, sex, and residential area (n(children) = 79). The pre-diagnostic saliva microbiota alpha- and beta-diversity of children who would develop T1D (n(samples) = 27) or IBD (n(samples) = 14) minimally varied from that of controls. The relative abundances of Abiotrophia were higher, while those of Veillonella, Actinomyces, Megasphaera, Butyrivibrio, and Candidatus ancillula were lower in children who would develop T1D. Within 2 years before diagnosis, the metabolic PWY-5677 pathway (converting succinate into butyrate) was lower in pre-T1D samples than in controls (q = 0.034). No significant pre-IBD differences were found. In conclusion, saliva microbiota diversity or composition were not successful predictors for pediatric T1D nor IBD. Intriguingly, the succinate fermentation pathway was predicted to be lowered before the onset of T1D. Thus, investigating functional pathways might provide a better approach in searching for biomarkers for autoimmune disease in the future.

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