Dataset Information

Understanding the role of GLUT2 in dysglycemia associated with Fanconi-Bickel syndrome

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE198678 | GEO | 2022/09/28

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Since the intronic mutation in SLC2A2 did not influence the activity of GLUT2, we undertook more investigation to understand the underlying molecular mechanisms of dysglycemia in FBS. We ran Nanostring miRNA panel v3b covering ~800 miRNAs in the patient, mother, and aged- and gender-matching healthy controls with no family history of dysglycemia. We noticed a higher degree of correlation between the patient and the gender and age-matched healthy control, rather than between the patient and the mother, suggesting that the miRNA expression profile might be more influenced by the age and gender rather than relatedness (Supplementary Fig. S5). The unsupervised hierarchical clustering revealed 123 miRs expressed specifically in the patient sample (Supplementary Table S2). The function of these miRNAs was interrogated by using Ingenuity Pathway (IPA) analysis software which returned 118 mapped miRs (Fig. 10). Here we report 30 miRNAs with the highest number of counts difference in the patient in comparison to controls (Fig. 11). We found that 14 of them were correlated with T1DM: 10 miRNAs (miR-199a, miR-25-3p, miR-93-5p, miR-19b-3p, miR-107, miR-24-3p. miR-18a-5p, miR-125b-5p, miR-324-5p, miR-331-3p, and hsa-miR-143-3p) were overexpressed in the control as compared to the patient, and 3 miRNAs (miR-144-3p , let-7e-5p, hsa-miR-29a-3p) were significantly overexpressed in the patient in comparison to the control. Molecular networks, including molecules inferred from previous studies, were generated by IPA functional analysis software (Supplementary Fig. S6). The molecular networks were given a score based on the number of molecules represented in the study dataset as compared to the literature. Network 1 (score 33) includes the genes and miRNAs implicated in organismal injury and abnormalities, skeletal and muscular system development and function, and tissue morphology. The miR-144 family integrated into the network 1. Network 2 (score 31) includes insulin and other genes and miRNAs implicated in glomerular injury, inflammatory disease, inflammatory response, and included miR-29 and let-7 families. These results suggest that dysglycemia in the patient with intronic mutation might be associated with the deregulation of miRNAs involved in insulin production and secretion in beta cells.

Dataset Information

Understanding the role of GLUT2 in dysglycemia associated with Fanconi-Bickel syndrome

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure