Co-segregation analysis and functional trial in vivo of candidate genes for monogenic diabetes

Abstract

IntroductionThe aim of this study was to perform familial co-segregation analysis and functional trial in vivo during mixed meal tolerance test (MMTT) of novel variants in diabetes candidate genes.Research design and methodsIt is a continuation of the project “Genetic diabetes in Lithuania” with the cohort of 1209 patients with diabetes. Prior screening for autoimmune markers confirmed type 1 diabetes (T1D) diagnosis in 88.1% (n=1065) of patients, and targeted next-generation sequencing identified 3.5% (n=42) pathogenic variants in MODY genes. Subsequently, 102 patients were classified as having diabetes of unknown etiology. 12/102 were found to have novel variants in potential diabetes genes (RFX2,RREB1,SLC5A1(3 patients with variants in this gene),GCKR,MC4R,CASP10,TMPRSS6,HGFAC,DACH1,ZBED3). Co-segregation analysis and MMTT were carried out in order to study beta-cell function in subjects with specific variants.ResultsMMTT analysis showed that probands with variants inMC4R,CASP10,TMPRSS6,HGFAC, andSLC5A1(c.1415T>C) had sufficient residual beta-cell function with stimulated C-peptide (CP) >200 pmol/L. Seven individuals with variants inRFX2,RREB1,GCKR,DACH1,ZBED3andSLC5A1(c.1415T>C, and c.932A>T) presented with complete beta-cell failure. No statistical differences were found between patients with sufficient CP production and those with complete beta-cell failure when comparing age at the onset and duration of diabetes. Nineteen family members were included in co-segregation analysis; no diabetes cases were reported among them. Only in patient with the variant c.1894G>A inRFX2gene, none of the family members were affected by proband’s variant.ConclusionsFunctional beta-cell study in vivo allowed to select five most probable genes for monogenic diabetes. Familial co-segregation analysis showed that novel variant inRFX2gene could be a possible cause of diabetes. Future functional analysis in vitro is necessary to support or rule out the genetic background as a cause of diabetes.

To identify biomarkers associated with the transfer of diabetes combined with cancer in human genes using bioinformatics analysis

“…[5][6][7] Only a few pathogenic genes, such as MIR-21, Rfx2, HNF1A, Nus1, GP2, HBA 1c, MR-148B-3P, and MR-27A-3P, are thought to play significant roles in the development of metastasis in cancer patients with DM and associated disorders. [8][9][10][11][12][13] However, the relationship between these biomarkers and DM has not been adequately studied. Moreover, the differential expression of metastasis-related genes in patients with DM, with and without metastases, has not been studied.…”