Kinetics of C-peptide during mixed meal test and its value for treatment optimization in monogenic diabetes patients

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

INTRODUCTION

The 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 METHODS

It 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.

RESULTS

MMTT analysis showed that probands with variants in MC4R, CASP10, TMPRSS6, HGFAC, and SLC5A1 (c.1415T>C) had sufficient residual beta-cell function with stimulated C-peptide (CP) >200 pmol/L. Seven individuals with variants in RFX2, RREB1, GCKR, DACH1, ZBED3 and SLC5A1 (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 in RFX2 gene, none of the family members were affected by proband's variant.

CONCLUSIONS

Functional beta-cell study in vivo allowed to select five most probable genes for monogenic diabetes. Familial co-segregation analysis showed that novel variant in RFX2 gene 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.

Pancreatic beta-cell function dynamics in youth with GCK, HNF1A, and KCNJ11 genes mutations during mixed meal tolerance test

OBJECTIVE

The aims were (1) to assess beta-cell function in GCK diabetes patients over 2-year period; (2) to evaluate the dynamics of beta-cell function in HNF1A and KCNJ11 patients after treatment optimization; using mixed meal tolerance test (MMTT) as a gold standard for non-invasive beta-cell function assessment.

RESEARCH DESIGN AND METHODS

Twenty-two GCK diabetes patients, 22 healthy subjects, 4 patients with HNF1A and 2 with KCNJ11 were recruited. Firstly, beta-cell function was compared between GCK patients versus controls; the dynamics of beta-cell function were assessed in GCK patients with two MMTTs in 2-year period. Secondly, the change of beta-cell function was evaluated in HNF1A and KCNJ11 patients after successful treatment optimization in 2-year period.

RESULTS

GCK diabetes patients had lower area under the curve (AUC) of C-peptide (CP), average CP and peak CP compared to controls. Also, higher levels of fasting, average, peak and AUC of glycemia during MMTT were found in GCK patients compared to healthy controls. No significant changes in either CP or glycemia dynamics were observed in GCK diabetes group comparing 1st and 2nd MMTTs. Patients with HNF1A and KCNJ11 diabetes had significantly improved diabetes control 2 years after the treatment was optimized (HbA1c 7.1% vs. 5.9% [54 mmol/mol vs. 41 mmol/mol], respectively, p = 0.028). Higher peak CP and lower HbA1c were found during 2nd MMTT in patients with targeted treatment compared to the 1st MMTT before the treatment change.

CONCLUSION

In short-term perspective, GCK diabetes group revealed no deterioration of beta-cell function. Individualized treatment in monogenic diabetes showed improved beta-cell function.