GALNT2 expression is associated with glucose control and serum metabolites in patients with type 2 diabetes.

AIMS: Aim of this study was to investigate in type 2 diabetes whether expression level of GALNT2, a positive modulator of insulin sensitivity, is associated with a metabolic signature. METHODS: Five different metabolite families, including acylcarnitines, aminoacids, biogenic amines, phospholipids and sphingolipids were investigated in fasting serum of 70 patients with type 2 diabetes, by targeted metabolomics. GALNT2 expression levels were measured in peripheral white blood cells by RT-PCR. The association between GALNT2 expression and serum metabolites was assessed using false discovery rate followed by stepwise selection and, finally, multivariate model including several clinical parameters as confounders. The association between GALNT2 expression and the same clinical parameters was also investigated. RESULTS: GALNT2 expression was independently correlated with HbA1c levels (P value = 0.0052), a finding that is the likely consequence of the role of GALNT2 on insulin sensitivity. GALNT2 expression was also independently associated with serum levels of the aminoacid glycine (P value = 0.014) and two biogenic amines phenylethylamine (P value = 0.0065) and taurine (P value = 0.0011). The association of GALNT2 expression with HbA1c was not mediated by these three metabolites. CONCLUSIONS: Our data indicate that in type 2 diabetes the expression of GALNT2 is associated with several serum metabolites. This association needs to be further investigated to understand in depth its role in mediating the effect of GALNT2 on insulin sensitivity, glucose control and other clinical features in people with diabetes.

Validation in type 2 diabetes of a metabolomic signature of all-cause mortality.

CONTEXT: Mortality in type 2 diabetes is twice that of the normoglycemic population. Unravelling biomarkers that identify high-risk patients for referral to the most aggressive and costly prevention strategies is needed. OBJECTIVE: To validate in type 2 diabetes the association with all-cause mortality of a 14-metabolite score (14-MS) previously reported in the general population and whether this score can be used to improve well-established mortality prediction models. METHODS: This is a sub-study consisting of 600 patients from the "Sapienza University Mortality and Morbidity Event Rate" (SUMMER) study in diabetes, a prospective multicentre investigation on all-cause mortality in patients with type 2 diabetes. Metabolic biomarkers were quantified from serum samples using high-throughput proton nuclear magnetic resonance metabolomics. RESULTS: In type 2 diabetes, the 14-MS showed a significant (p < 0.0001) association with mortality, which was lower (p < 0.0001) than that reported in the general population. This difference was mainly due to two metabolites (histidine and ratio of polyunsaturated fatty acids to total fatty acids) with an effect size that was significantly (p = 0.01) lower in diabetes than in the general population. A parsimonious 12-MS (i.e. lacking the 2 metabolites mentioned above) improved patient discrimination and classification of two well-established mortality prediction models (p < 0.0001 for all measures). CONCLUSIONS: The metabolomic signature of mortality in the general population is only partially effective in type 2 diabetes. Prediction markers developed and validated in the general population must be revalidated if they are to be used in patients with diabetes.

Circulating metabolites improve the prediction of renal impairment in patients with type 2 diabetes.

INTRODUCTION: Low glomerular filtration rate (GFR) is a leading cause of reduced lifespan in type 2 diabetes. Unravelling biomarkers capable to identify high-risk patients can help tackle this burden. We investigated the association between 188 serum metabolites and kidney function in type 2 diabetes and then whether the associated metabolites improve two established clinical models for predicting GFR decline in these patients. RESEARCH DESIGN AND METHODS: Two cohorts comprising 849 individuals with type 2 diabetes (discovery and validation samples) and a follow-up study of 575 patients with estimated GFR (eGFR) decline were analyzed. RESULTS: Ten metabolites were independently associated with low eGFR in the discovery sample, with nine of them being confirmed also in the validation sample (ORs range 1.3-2.4 per 1SD, p values range 1.9×10-2-2.5×10-9). Of these, five metabolites were also associated with eGFR decline (ie, tiglylcarnitine, decadienylcarnitine, total dimethylarginine, decenoylcarnitine and kynurenine) (ß range -0.11 to -0.19, p values range 4.8×10-2 to 3.0×10-3). Indeed, tiglylcarnitine and kynurenine, which captured all the information of the other three markers, improved discrimination and reclassification (all p<0.01) of two clinical prediction models of GFR decline in people with diabetes. CONCLUSIONS: Further studies are needed to validate our findings in larger cohorts of different clinical, environmental and genetic background.

Monogenic diabetes.

Monogenic diabetes includes several clinical conditions generally characterized by early-onset diabetes, such as neonatal diabetes, maturity-onset diabetes of the young (MODY) and various diabetes-associated syndromes. However, patients with apparent type 2 diabetes mellitus may actually have monogenic diabetes. Indeed, the same monogenic diabetes gene can contribute to different forms of diabetes with early or late onset, depending on the functional impact of the variant, and the same pathogenic variant can produce variable diabetes phenotypes, even in the same family. Monogenic diabetes is mostly caused by impaired function or development of pancreatic islets, with defective insulin secretion in the absence of obesity. The most prevalent form of monogenic diabetes is MODY, which may account for 0.5-5% of patients diagnosed with non-autoimmune diabetes but is probably underdiagnosed owing to insufficient genetic testing. Most patients with neonatal diabetes or MODY have autosomal dominant diabetes. More than 40 subtypes of monogenic diabetes have been identified to date, the most prevalent being deficiencies of GCK and HNF1A. Precision medicine approaches (including specific treatments for hyperglycaemia, monitoring associated extra-pancreatic phenotypes and/or following up clinical trajectories, especially during pregnancy) are available for some forms of monogenic diabetes (including GCK- and HNF1A-diabetes) and increase patients' quality of life. Next-generation sequencing has made genetic diagnosis affordable, enabling effective genomic medicine in monogenic diabetes.

Association of osteocalcin, osteoprotegerin, and osteopontin with cardiovascular disease and retinopathy in type 2 diabetes.

BACKGROUND: Novel biomarkers of vascular disease in diabetes could help identify new mechanistic pathways. Osteocalcin, osteoprotegerin, and osteopontin are key molecules involved in bone and vascular calcification processes, both of which are compromised in diabetes. We aimed to evaluate possible associations of osteocalcin, osteoprotegerin, and osteopontin with cardiovascular disease (CVD) and diabetic retinopathy (DR) among people with type 2 diabetes (T2D). MATERIALS AND METHODS: Osteocalcin, osteoprotegerin, and osteopontin concentrations were measured at enrolment in 848 participants with T2D from the Sapienza University Mortality and Morbidity Event Rate (SUMMER) Study (ClinicalTrials.gov: NCT02311244). Logistic regression models and propensity score matching were used to assess possible associations of osteocalcin, osteoprotegerin, and osteopontin with a history of CVD and with evidence of any grade of DR adjusting for confounders. RESULTS: Previous CVD was reported in 139 (16.4%) participants, while 144 (17.0%) had DR. After adjusting for possible confounders, osteocalcin but not osteoprotegerin or osteopontin concentrations were associated with a history of CVD (Odds Ratio [OR] and 95% CI for one standard deviation (SD) increase in osteocalcin concentrations (natural log): 1.35 (1.06-1.72), p = 0.014). Associations with prevalent DR were seen for osteoprotegerin (OR for one SD increase in osteoprotegerin concentrations (natural log): 1.25 (1.01-1.55), p = 0.047) and osteopontin (OR for one SD increase in osteopontin concentrations (natural log): 1.25 (1.02-1.53), p = 0.022), but not osteocalcin. CONCLUSIONS: In T2D, higher serum osteocalcin concentrations are associated with macrovascular complications and higher osteoprotegerin and osteopontin concentrations with microvascular complications, suggesting that these osteokines might be involved in pathways directly related to vascular disease.

Leveraging Genetics to Address the Role of GALNT2 on Atherogenic Dyslipidemia.

Several studies have shown that downregulation of GALNT2 (Polypeptide N-Acetylgalactosaminyltransferase 2), encoding polypeptide N-acetylgalactosaminyltransferase 2, decreases high-density lipoprotein cholesterol (HDL-C) and increases triglycerides levels by glycosylating key enzymes of lipid metabolism, such as angiopoietin like 3, apolipoprotein C-III, and phospholipid transfer protein. GALNT2 is also a positive modulator of insulin signaling and action, associated with in vivo insulin sensitivity and during adipogenesis strongly upregulates adiponectin. Thus, the hypothesis that GALNT2 affects HDL-C and triglycerides levels also through insulin sensitivity and/or circulating adiponectin, is tested. In 881 normoglycemic individuals the G allele of rs4846914 SNP at the GALNT2 locus, known to associate with GALNT2 downregulation, is associated with low HDL-C and high values of triglycerides, triglycerides/HDL-C ratio, and theHomeostatic Model Assessment of insulin resistance HOMAIR (p-values = 0.01, 0.027, 0.002, and 0.016, respectively). Conversely, no association is observed with serum adiponectin levels (p = 0.091). Importantly, HOMAIR significantly mediates a proportion of the genetic association with HDL-C (21%, 95% CI: 7-35%, p = 0.004) and triglyceride levels (32%, 95% CI: 4-59%, p = 0.023). The results are compatible with the hypothesis that, besides the effect on key lipid metabolism enzymes, GALNT2 alters HDL-C and triglyceride levels also indirectly through a positive effect on insulin sensitivity.

Contribution of rare variants in monogenic diabetes-genes to early-onset type 2 diabetes.

AIM: This study investigated whether rare, deleterious variants in monogenic diabetes-genes are associated with early-onset type 2 diabetes (T2D). METHODS: A nested case-control study was designed from 9712 Italian patients with T2D. Individuals with age at diabetes onset ≤35 yrs (n = 300; cases) or ≥65 yrs (n = 300; controls) were selected and screened for variants in 27 monogenic diabetes-genes by targeted resequencing. Rare (minor allele frequency-MAF <1%) and possibly deleterious variants were collectively tested for association with early-onset T2D. The association of a genetic risk score (GRS) based on 17 GWAS-SNPs for T2D was also tested. RESULTS: When all rare variants were considered together, each increased the risk of early-onset T2D by 65% (allelic OR =1.64, 95% CI: 1.08-2.48, p = 0.02). Effects were similar when the 600 study participants were stratified according to their place of recruitment (Central-Southern Italy, 182 cases vs. 142 controls, or Rome urban area, 118 vs. 158, p for heterogeneity=0.53). Progressively less frequent variants showed increasingly stronger effects in the risk of early-onset T2D for those with MAF <0.001% (OR=6.34, 95% CI: 1.87-22.43, p = 0.003). One unit of T2D-GRS significantly increased the risk of early-onset T2D (OR 1.09, 95% CI: 1.01-1.18; p = 0.02). This association was stronger among rare variants carriers as compared to non-carriers (p = 0.02). CONCLUSION: Rare variants in monogenic-diabetes genes are associated with an increased risk of early-onset T2D, and interact with common T2D susceptibility variants in shaping it. These findings might help develop prediction tools to identify individuals at high risk of developing T2D in early adulthood.

Circulating Metabolites Associate With and Improve the Prediction of All-Cause Mortality in Type 2 Diabetes.

Death rate is increased in type 2 diabetes. Unraveling biomarkers of novel pathogenic pathways capable to identify high-risk patients is instrumental to tackle this burden. We investigated the association between serum metabolites and all-cause mortality in type 2 diabetes and then whether the associated metabolites mediate the effect of inflammation on mortality risk and improve ENFORCE (EstimatioN oF mORtality risk in type2 diabetic patiEnts) and RECODe (Risk Equation for Complications Of type 2 Diabetes), two well-established all-cause mortality prediction models in diabetes. Two cohorts comprising 856 individuals (279 all-cause deaths) were analyzed. Serum metabolites (n = 188) and pro- and anti-inflammatory cytokines (n = 7) were measured. In the pooled analysis, hexanoylcarnitine, kynurenine, and tryptophan were significantly and independently associated with mortality (hazard ratio [HR] 1.60 [95% CI 1.43-1.80]; 1.53 [1.37-1.71]; and 0.71 [0.62-0.80] per 1 SD). The kynurenine-to-tryptophan ratio (KTR), a proxy of indoleamine-2,3-dioxygenase, which degrades tryptophan to kynurenine and contributes to a proinflammatory status, mediated 42% of the significant association between the antiatherogenic interleukin (IL) 13 and mortality. Adding the three metabolites improved discrimination and reclassification (all P < 0.01) of both mortality prediction models. In type 2 diabetes, hexanoylcarnitine, tryptophan, and kynurenine are associated to and improve the prediction of all-cause mortality. Further studies are needed to investigate whether interventions aimed at reducing KTR also reduce the risk of death, especially in patients with low IL-13.

Role of Actionable Genes in Pursuing a True Approach of Precision Medicine in Monogenic Diabetes.

Monogenic diabetes is a genetic disorder caused by one or more variations in a single gene. It encompasses a broad spectrum of heterogeneous conditions, including neonatal diabetes, maturity onset diabetes of the young (MODY) and syndromic diabetes, affecting 1-5% of patients with diabetes. Some of these variants are harbored by genes whose altered function can be tackled by specific actions ("actionable genes"). In suspected patients, molecular diagnosis allows the implementation of effective approaches of precision medicine so as to allow individual interventions aimed to prevent, mitigate or delay clinical outcomes. This review will almost exclusively concentrate on the clinical strategy that can be specifically pursued in carriers of mutations in "actionable genes", including ABCC8, KCNJ11, GCK, HNF1A, HNF4A, HNF1B, PPARG, GATA4 and GATA6. For each of them we will provide a short background on what is known about gene function and dysfunction. Then, we will discuss how the identification of their mutations in individuals with this form of diabetes, can be used in daily clinical practice to implement specific monitoring and treatments. We hope this article will help clinical diabetologists carefully consider who of their patients deserves timely genetic testing for monogenic diabetes.

Role of GALNT2 on Insulin Sensitivity, Lipid Metabolism and Fat Homeostasis.

O-linked glycosylation, the greatest form of post-translational modifications, plays a key role in regulating the majority of physiological processes. It is, therefore, not surprising that abnormal O-linked glycosylation has been related to several human diseases. Recently, GALNT2, which encodes the GalNAc-transferase 2 involved in the first step of O-linked glycosylation, has attracted great attention as a possible player in many highly prevalent human metabolic diseases, including atherogenic dyslipidemia, type 2 diabetes and obesity, all clustered on the common ground of insulin resistance. Data available both in human and animal models point to GALNT2 as a molecule that shapes the risk of the aforementioned abnormalities affecting diverse protein functions, which eventually cause clinically distinct phenotypes (a typical example of pleiotropism). Pathways linking GALNT2 to dyslipidemia and insulin resistance have been partly identified, while those for type 2 diabetes and obesity are yet to be understood. Here, we will provide a brief overview on the present knowledge on GALNT2 function and dysfunction and propose novel insights on the complex pathogenesis of the aforementioned metabolic diseases, which all impose a heavy burden for patients, their families and the entire society.

Gain of Function of Malate Dehydrogenase 2 and Familial Hyperglycemia.

CONTEXT: Genes causing familial forms of diabetes mellitus are only partially known. OBJECTIVE: We set out to identify the genetic cause of hyperglycemia in multigenerational families with an apparent autosomal dominant form of adult-onset diabetes not due to mutations in known monogenic diabetes genes. METHODS: Existing whole-exome sequencing (WES) data were used to identify exonic variants segregating with diabetes in 60 families from the United States and Italy. Functional studies were carried out in vitro (transduced MIN6-K8 cells) and in vivo (Caenorhabditis elegans) to assess the diabetogenic potential of 2 variants in the malate dehydrogenase 2 (MDH2) gene linked with hyperglycemia in 2 of the families. RESULTS: A very rare mutation (p.Arg52Cys) in MDH2 strongly segregated with hyperglycemia in 1 family from the United States. An infrequent MDH2 missense variant (p.Val160Met) also showed disease cosegregation in a family from Italy, although with reduced penetrance. In silico, both Arg52Cys and Val160Met were shown to affect MDH2 protein structure and function. In transfected HepG2 cells, both variants significantly increased MDH2 enzymatic activity, thereby decreasing the NAD+/NADH ratio-a change known to affect insulin signaling and secretion. Stable expression of human wild-type MDH2 in MIN6-K8 cell lines enhanced glucose- and GLP-1-stimulated insulin secretion. This effect was blunted by the Cys52 or Met160 substitutions. Nematodes carrying equivalent changes at the orthologous positions of the mdh-2 gene showed impaired glucose-stimulated insulin secretion. CONCLUSION: Our findings suggest a central role of MDH2 in human glucose homeostasis and indicate that gain of function variants in this gene may be involved in the etiology of familial forms of diabetes.

A Serum Resistin and Multicytokine Inflammatory Pathway Is Linked With and Helps Predict All-cause Death in Diabetes.

CONTEXT: Type 2 diabetes (T2D) shows a high mortality rate, partly mediated by atherosclerotic plaque instability. Discovering novel biomarkers may help identify high-risk patients who would benefit from more aggressive and specific managements. We recently described a serum resistin and multicytokine inflammatory pathway (REMAP), including resistin, interleukin (IL)-1ß, IL-6, IL-8, and TNF-α, that is associated with cardiovascular disease. OBJECTIVE: We investigated whether REMAP is associated with and improves the prediction of mortality in T2D. METHODS: A REMAP score was investigated in 3 cohorts comprising 1528 patients with T2D (409 incident deaths) and in 59 patients who underwent carotid endarterectomy (CEA; 24 deaths). Plaques were classified as unstable/stable according to the modified American Heart Association atherosclerosis classification. RESULTS: REMAP was associated with all-cause mortality in each cohort and in all 1528 individuals (fully adjusted hazard ratio [HR] for 1 SD increase = 1.34, P < .001). In CEA patients, REMAP was associated with mortality (HR = 1.64, P = .04) and a modest change was observed when plaque stability was taken into account (HR = 1.58; P = .07). REMAP improved discrimination and reclassification measures of both Estimation of Mortality Risk in Type 2 Diabetic Patients and Risk Equations for Complications of Type 2 Diabetes, well-established prediction models of mortality in T2D (P < .05-< .001). CONCLUSION: REMAP is independently associated with and improves predict all-cause mortality in T2D; it can therefore be used to identify high-risk individuals to be targeted with more aggressive management. Whether REMAP can also identify patients who are more responsive to IL-6 and IL-1ß monoclonal antibodies that reduce cardiovascular burden and total mortality is an intriguing possibility to be tested.

All-cause mortality prediction models in type 2 diabetes: applicability in the early stage of disease.

AIMS: The rate of all-cause mortality is twofold higher in type 2 diabetes than in the general population. Being able to identify patients with the highest risk from the very beginning of the disease would help tackle this burden. METHODS: We tested whether ENFORCE, an established prediction model of all-cause mortality in type 2 diabetes, performs well also in two independent samples of patients with early-stage disease prospectively followed up. RESULTS: ENFORCE's survival C-statistic was 0.81 (95%CI: 0.72-0.89) and 0.78 (95%CI: 0.68-0.87) in both samples. Calibration was also good. Very similar results were obtained with RECODe, an alternative prediction model of all-cause mortality in type 2 diabetes. CONCLUSIONS: In conclusion, our data show that two well-established prediction models of all-cause mortality in type 2 diabetes can also be successfully applied in the early stage of the disease, thus becoming powerful tools for educated and timely prevention strategies for high-risk patients.