Rabbit Anti-Human NEUROD1 (Phospho-Ser274) polyclonal antibody

Pregnant women with diabetes may have underlying beta cell dysfunction due to mutations/rare variants in genes associated with Maturity Onset Diabetes of the Young (MODY). MODY gene screening would reveal those women genetically predisposed and previously unrecognized with a monogenic form of diabetes for further clinical management, family screening and genetic counselling. However, there are minimal data available on MODY gene variants in pregnant women with diabetes from India. In this study, utilizing the Next generation sequencing (NGS) based protocol fifty subjects were screened for variants in a panel of thirteen MODY genes. Of these subjects 18% (9/50) were positive for definite or likely pathogenic or uncertain MODY variants. The majority of these variants was identified in subjects with autosomal dominant family history, of whom five were in women with preGDM and four with overt-GDM. The identified variants included one patient with HNF1A Ser3Cys, two PDX1 Glu224Lys, His94Gln, two NEUROD1 Glu59Gln, Phe318Ser, one INS Gly44Arg, one GCK, one ABCC8 Arg620Cys and one BLK Val418Met variants. In addition, three of the seven offspring screened were positive for the identified variant. These identified variants were further confirmed by Sanger sequencing. In conclusion, these findings in pregnant women with diabetes, imply that a proportion of GDM patients with autosomal dominant family history may have MODY. Further NGS based comprehensive studies with larger samples are required to confirm these finding

Computational approach for identifying significance of proteins related to a certain disease was proposed as one of the solutions from the problem of experimental method application which is generally cost and time consuming. The case of study was conducted on diabetes mellitus (DM) type 2 disease. The purpose of this research is to identify significant proteins that causes diabetes mellitus type 2 by applying Fuzzy C-Means clustering algorithm and topological analysis from graph theory. A total of 100 proteins were obtained, some of them were identified as most significant proteins such as GCK, HNF4A, SLC30A8, SLC2A2, NEUROD1, PPARG, IRS1, HNF1B, PDX1 and RETN. It is expected that this results can be used by pharmacology researcher to screen the candidates of active compounds that have association with those proteins that representing diabetes mellitus (DM) type 2 disease.