Genetic factors and insulin secretion: gene variants in the IGF genes

IGFs are important regulators of pancreatic beta-cell development, growth, and maintenance. Mutations in the IGF genes have been found to be associated with type 2 diabetes, myocardial infarction, birth weight, and obesity. These associations could result from changes in insulin secretion. We have analyzed glucose-stimulated insulin secretion using hyperglycemic clamps in carriers of a CA repeat in the IGF-I promoter and an ApaI polymorphism in the IGF-II gene. Normal and impaired glucose-tolerant subjects (n = 237) were independently recruited from three different populations in the Netherlands and Germany to allow independent replication of associations. Both first- and second-phase insulin secretion were not significantly different between the various IGF-I or IGF-II genotypes. Remarkably, noncarriers of the IGF-I CA repeat allele had both a reduced insulin sensitivity index (ISI) and disposition index (DI), suggesting an altered balance between insulin secretion and insulin action. Other diabetes-related parameters were not significantly different for both the IGF-I and IGF-II gene variant. We conclude that gene variants in the IGF-I and IGF-II genes are not associated with detectable variations in glucose-stimulated insulin secretion in these three independent populations. Further studies are needed to examine the exact contributions of the IGF-I CA repeat alleles to variations in ISI and DI

Plasma Metabolomics Identifies Markers of Impaired Renal Function: A Meta-analysis of 3089 Persons with Type 2 Diabetes

CONTEXT: There is a need for novel biomarkers and better understanding of the pathophysiology of diabetic kidney disease. OBJECTIVE: To investigate associations between plasma metabolites and kidney function in people with type 2 diabetes (T2D). DESIGN: 3089 samples from individuals with T2D, collected between 1999 and 2015, from 5 independent Dutch cohort studies were included. Up to 7 years follow-up was available in 1100 individuals from 2 of the cohorts. MAIN OUTCOME MEASURES: Plasma metabolites (n = 149) were measured by nuclear magnetic resonance spectroscopy. Associations between metabolites and estimated glomerular filtration rate (eGFR), urinary albumin-to-creatinine ratio (UACR), and eGFR slopes were investigated in each study followed by random effect meta-analysis. Adjustments included traditional cardiovascular risk factors and correction for multiple testing. RESULTS: In total, 125 metabolites were significantly associated (PFDR = 1.5×10-32 - 0.046; β = -11.98-2.17) with eGFR. Inverse associations with eGFR were demonstrated for branched-chain and aromatic amino acids (AAAs), glycoprotein acetyls, triglycerides (TGs), lipids in very low-density lipoproteins (VLDL) subclasses, and fatty acids (PFDR < 0.03). We observed positive associations with cholesterol and phospholipids in high-density lipoproteins (HDL) and apolipoprotein A1 (PFDR < 0.05). Albeit some metabolites were associated with UACR levels (P < 0.05), significance was lost after correction for multiple testing. Tyrosine and HDL-related metabolites were positively associated with eGFR slopes before adjustment for multiple testing (PTyr = 0.003; PHDLrelated < 0.05), but not after. CONCLUSIONS: This study identified metabolites associated with impaired kidney function in T2D, implying involvement of lipid and amino acid metabolism in the pathogenesis. Whether these processes precede or are consequences of renal impairment needs further investigation

Metformin and statin use associate with plasma protein N-glycosylation in people with type 2 diabetes

INTRODUCTION: Recent studies revealed N-glycosylation signatures of type 2 diabetes, inflammation and cardiovascular risk factors. Most people with diabetes use medication to reduce cardiovascular risk. The association of these medications with the plasma N-glycome is largely unknown. We investigated the associations of metformin, statin, ACE inhibitor/angiotensin II receptor blocker (ARB), sulfonylurea (SU) derivatives and insulin use with the total plasma N-glycome in type 2 diabetes. RESEARCH DESIGN AND METHODS: After enzymatic release from glycoproteins, N-glycans were measured by matrix-assisted laser desorption/ionization mass spectrometry in the DiaGene (n=1815) and Hoorn Diabetes Care System (n=1518) cohorts. Multiple linear regression was used to investigate associations with medication, adjusted for clinical characteristics. Results were meta-analyzed and corrected for multiple comparisons. RESULTS: Metformin and statins were associated with decreased fucosylation and increased galactosylation and sialylation in glycans unrelated to immunoglobulin G. Bisection was increased within diantennary fucosylated non-sialylated glycans, but decreased within diantennary fucosylated sialylated glycans. Only few glycans were associated with ACE inhibitor/ARBs, while none associated with insulin and SU derivative use. CONCLUSIONS: We conclude that metformin and statins associate with a total plasma N-glycome signature in type 2 diabetes. Further studies are needed to determine the causality of these relations, and future N-glycomic research should consider medication a potential confounder