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Children with type 1 diabetes (T1D) have a less desirable gut microbiome composition, potentially contributing to the development of the disease, according to new research published in the Journal of Clinical Endocrinology & Metabolism.
Children with type 1 diabetes (T1D) have a less desirable gut microbiome composition, potentially contributing to the development of the disease, according to new research published in the Journal of Clinical Endocrinology & Metabolism.
T1D develops in genetically susceptible individuals via environmental factors that trigger an autoimmune inflammatory process within the pancreatic islets. This process leads to B-cell loss, the authors explain. “Up to now, the causative mechanisms [of T1D] have not been completely defined, and the identification of risk factors represents a challenge with practical, diagnostic, and therapeutic implications,” the researchers write.
It has been hypothesized that gut immune systems and gut microbiota composition play a key role in the development of autoimmunity, as the gut microbiota functions like an endocrine organ. The microbiota translates nutritional factors into hormone-like signals, while its composition is influenced by dietary habits and geographical locations, the authors write.
Using machine learning and genetic analyses, the researchers analyzed the microbiomes of 31 children with newly diagnosed T1D and 25 healthy controls. The majority of children with T1D in the study were male (n = 21), and the average age was 10.3 years. All children reported no history of acute or chronic gastrointestinal diseases and/or antibiotic or probiotic administration during the month prior to examination.
Data on gender, age of diabetes onset, gestational age, mode of delivery, and duration of breast feeding were collected while “expression of endogenous insulin secretion serum C peptide measurement by electrochemiluminescence assay was performed in all patients.” Fecal samples were collected from healthy children and analyzed to serve as controls.
Two machine learning algorithms, Random Forest and l1l2 for biomarker classification and identification, were applied following statistical, visual, and meta-analyses of microbiome data performed by the MicrobiomeAnalyst tool. “Data filtering for low abundance and low variance Operational Taxonomic Units (OTUs) (based on the prevalence in 20% of samples and inter-quartile range [IQR] set at 10%) was applied for all the relative abundance comparisons using different algorithms,” the researchers note.
The analyses found:
"Our data showed that controls had higher alpha diversity than children with T1D," authors conclude.
Despite the findings, the authors note it is currently not possible to clearly state if gut microbiota diversity represents a cause or a consequence of autoimmunity in patients with T1D.
Future longitudinal studies and an increased number of cases will help clarify the role of gut microbiota and autoimmunity in patients with T1D and determine whether gut microbiota modulation can serve as a future therapeutic opportunity.
Reference
Biassoni R, Di Marco E, Squillario M, et al. Gut microbiota in T1DM-onset pediatric patients: machine learning algorithms to classify microorganisms disease-linked. J Clin Endocrinol Metab. Published online July 21, 2020. doi:10.1210/clinem/dgaa407
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