Eleonora Morini

A Functional Variant of the Adipocyte Glycerol Channel Aquaporin 7 Gene Is Associated With Obesity and Related Metabolic Abnormalities

Aquaporin 7 (AQP7), the gateway protein controlling glycerol release, has recently emerged as a modulator of adipocyte metabolism. AQP7 knockout mice develop obesity and hyperglycemia. The contribution of AQP7 to these abnormalities in humans is unknown. We examined whether common single nucleotide polymorphisms (SNPs) in the AQP7 gene modulate the risk of obesity and related abnormalities. Among several SNPs we identified, A-953G in the AQP7 promoter was associated with type 2 diabetes in 977 (530 female/447 male) Caucasians: odds ratio for XG (i.e., AG+GG) versus AA individuals was 1.36 (95% CI 1.01–1.84), P = 0.04. This finding was entirely due to the association among females (1.8 [1.2–2.6], P = 0.004), which was no longer significant when adjusted for BMI. In fact, BMI was higher in XG than in AA females (30.8 ± 6.6 vs. 28.9 ± 5.2, P = 0.002). This association was confirmed in independent case-control study (n = 299 female subjects) for morbid obesity (1.66 [1.01–2.74], P = 0.04). Luciferase and mobility shift assays showed that, compared with −953A, the −953G promoter had reduced transcriptional activity (P = 0.001) and impaired ability to bind CCAAT/enhancer binding protein (C/EBP)β transcription factor (P = 0.01). Finally, AQP7 expression in adipose tissue decreased from AA to AG to GG individuals (P = 0.036). These data strongly suggest that AQP7 downregulation is pathogenic for obesity and/or type 2 diabetes.

Insulin signaling regulating genes: Effect on T2DM and cardiovascular risk

Type 2 diabetes mellitus (T2DM) is a complex disorder that has a heterogeneous genetic and environmental background. In this Review, we discuss the role of relatively infrequent polymorphisms of genes that regulate insulin signaling (including the K121Q polymorphism of ENPP1, the G972R polymorphism of IRS1 and the Q84R polymorphism of TRIB3) in T2DM and other conditions related to insulin resistance. The biological relevance of these three polymorphisms has been very thoroughly characterized both in vitro and in vivo and the available data indicate that they all affect insulin signaling and action as well as insulin secretion. They also affect insulin-mediated regulation of endothelial cell function. In addition, several reports indicate that the effects of all three polymorphisms on the risk of T2DM and cardiovascular diseases related to insulin resistance depend on the clinical features of the individual, including their body weight and age at disease onset. Thus, these polymorphisms might be used to demonstrate how difficult it is to ascertain the contribution of relatively infrequent genetic variants with heterogeneous effects on disease susceptibility. Unraveling the role of such variants might be facilitated by improving disease definition and focusing on specific subsets of patients.

The TRIB3 Q84R polymorphism and risk of early-onset type 2 diabetes

CONTEXT The prevalence of type 2 diabetes (T2D), particularly among young adults, has been rising steadily during the past 2 decades. T2D, especially in its early-onset subtype, is under genetic control. TRIB3 inhibits insulin-stimulated Akt phosphorylation and subsequent insulin action. A TRIB3 gain-of-function polymorphism, Q84R (rs2295490), impairs insulin signaling. OBJECTIVE The objective of the study was to verify the association of TRIB3 Q84R with: 1) T2D, either subtyped or not according to age at diagnosis (early-onset, <45 yr, or >or= 45 yr); 2) insulin secretion and sensitivity in nondiabetic individuals; or 3) in vitro insulin secretion from isolated human islets. DESIGN Four different case-control samples comprising a total of 5,469 whites were examined. Insulinogenic and insulin sensitivity indexes and their interplay (disposition index) were assessed in 645 nondiabetic individuals at oral glucose tolerance test, glucose (16.7 mmol/liter)-induced in vitro insulin secretion was assessed in islets isolated from 54 nondiabetic donors. RESULTS In the whole sample, the R84 variant was nominally associated with T2D (odds ratio 1.17, 95% confidence interval 1.00-1.36, P = 0.04). When stratifying according to age of diabetes onset, R84 carriers had an increased risk of early-onset T2D (odds ratio 1.32, 95% confidence interval 1.10-1.58, P = 0.002). Among 645 nondiabetic subjects, R84 carriers had higher glucose levels (P = 0.005) and lower insulinogenic (P = 0.03) and disposition index (P = 0.02) during the oral glucose tolerance test. R84 islets were more likely to display relatively low glucose-stimulated insulin release (P = 0.04). CONCLUSIONS The TRIB3 R84 variant is associated with early-onset T2D in whites. Alteration in the insulin secretion/insulin sensitivity interplay appears to underlie this association.

Serum Resistin, Cardiovascular Disease and All-Cause Mortality in Patients with Type 2 Diabetes

Background High serum resistin has been associated with increased risk of cardiovascular disease in the general population, Only sparse and conflicting results, limited to Asian individuals, have been reported, so far, in type 2 diabetes. We studied the role of serum resistin on coronary artery disease, major cardiovascular events and all-cause mortality in type 2 diabetes. Methods We tested the association of circulating resistin concentrations with coronary artery disease, major cardiovascular events (cardiovascular death, non-fatal myocardial infarction and non-fatal stroke) and all-cause mortality in 2,313 diabetic patients of European ancestry from two cross-sectional and two prospective studies. In addition, the expression of resistin gene (RETN) was measured in blood cells of 68 diabetic patients and correlated with their serum resistin levels. Results In a model comprising age, sex, smoking habits, BMI, HbA1c, and insulin, antihypertensive and antidyslipidemic therapies, serum resistin was associated with coronary artery disease in both cross-sectional studies: OR (95%CI) per SD increment = 1.35 (1.10–1.64) and 1.99 (1.55–2.55). Additionally, serum resistin predicted incident major cardiovascular events (HR per SD increment = 1.31; 1.10–1.56) and all-cause mortality (HR per SD increment = 1.16; 1.06–1.26). Adjusting also for fibrinogen levels affected the association with coronary artery disease and incident cardiovascular events, but not that with all cause-mortality. Finally, serum resistin was positively correlated with RETN mRNA expression (rho = 0.343). Conclusions This is the first study showing that high serum resistin (a likely consequence, at least partly, of increased RETN expression) is a risk factor for cardiovascular disease and all-cause mortality in diabetic patients of European ancestry.

Interaction Between PPARγ2 Variants and Gender on the Modulation of Body Weight

Conflicting results have been reported regarding the effect of the peroxisome proliferator‐activated receptor‐γ−2 (PPARγ2) Pro12Ala polymorphism, (singly or in combination with the silent C1431T polymorphism) on BMI. Gender‐based dimorphism has been evidenced for genes that affect BMI, but few and conflicting data are available regarding PPARγ2. We sought to investigate whether the Pro12Ala interacts with gender in modulating BMI in 566 nondiabetic unrelated white subjects (men:women = 211:355, age 36.59 ± 11.85; BMI 25.36 ± 4.53). In the whole study population, BMI, fasting glucose and insulin levels, and lipid profile were similar in Ala12 carriers (i.e., XA) and Pro/Pro homozygous subjects. Among the men, but not among the women, X/Ala individuals showed higher BMI (25.9 ± 3.6 vs. 28.2 ± 4.9, P = 0.006) and risk of obesity (odds ratio = 2.85, 95% confidence interval = 1.07–7.62). A significant gene‐gender interaction in modulating BMI was observed (P = 0.039). Among the men, but not among the women, those carrying Ala‐T haplotype (i.e., containing both Ala12 and T1431 variants) showed the highest BMI (haplo‐score = 3.72, P = 0.0014). Our data indicate that in whites from Italy the PPARγ2 Pro12Ala polymorphism interacts with gender in modulating BMI, thereby replicating some, but not all, earlier data obtained in different populations. Whether the PPARγ2‐gender interaction is a general phenomenon across different populations, is still an open question, the answer to which requires additional, specifically designed, studies.

The Q121/Q121 Genotype of ENPP1/PC-1 Is Associated with Lower BMI in Non-diabetic Whites

This study investigated the role of the ENPP1/PC‐1 gene K121Q polymorphism in predicting BMI (kg/m2) in non‐diabetic individuals. Three independent samples (n = 631, n = 304, and n = 505) of adult whites were analyzed. Selection criteria were fasting plasma glucose level <126 mg/dL, absence of severe obesity (BMI ≥40 kg/m2), and lack of treatment known to modulate BMI. In Sample 1, BMI values were different in individuals carrying the K121/K121 (KK), K121/Q121 (KQ), and Q121/Q121 (QQ) genotypes (25.5 ± 4.3, 25.3 ± 4.1, and 22.8 ± 2.5 kg/m2, respectively (adjusted p = 0.022); BMI values in Samples 2 and 3 also tended to be different, although the differences, after adjustment for age and sex, did not reach statistical significance. When data were pooled, BMI values were 25.8 ± 4.4, 25.6 ± 4.4, and 23.6 ± 3.3 kg/m2 in KK, KQ, and QQ individuals (adjusted p = 0.029). According to a recessive model, QQ individuals had lower BMI values than KK and KQ individuals combined (23.6 ± 3.3 kg/m2 vs. 25.7 ± 4.4 kg/m2; adjusted p = 0.008). These data suggest that the QQ genotype of the ENPP1/PC‐1 gene is associated with lower BMI. If similar results are confirmed in prospective studies, the K121Q polymorphism may help identify people at risk for obesity.

Loss-of-Function Mutations in APPL1 in Familial Diabetes Mellitus

Diabetes mellitus is a highly heterogeneous disorder encompassing several distinct forms with different clinical manifestations including a wide spectrum of age at onset. Despite many advances, the causal genetic defect remains unknown for many subtypes of the disease, including some of those forms with an apparent Mendelian mode of inheritance. Here we report two loss-of-function mutations (c.1655T>A [p.Leu552(∗)] and c.280G>A [p.Asp94Asn]) in the gene for the Adaptor Protein, Phosphotyrosine Interaction, PH domain, and leucine zipper containing 1 (APPL1) that were identified by means of whole-exome sequencing in two large families with a high prevalence of diabetes not due to mutations in known genes involved in maturity onset diabetes of the young (MODY). APPL1 binds to AKT2, a key molecule in the insulin signaling pathway, thereby enhancing insulin-induced AKT2 activation and downstream signaling leading to insulin action and secretion. Both mutations cause APPL1 loss of function. The p.Leu552(∗) alteration totally abolishes APPL1 protein expression in HepG2 transfected cells and the p.Asp94Asn alteration causes significant reduction in the enhancement of the insulin-stimulated AKT2 and GSK3β phosphorylation that is observed after wild-type APPL1 transfection. These findings-linking APPL1 mutations to familial forms of diabetes-reaffirm the critical role of APPL1 in glucose homeostasis.

Development and validation of a predicting model of all-cause mortality in patients with type 2 diabetes.

OBJECTIVE To develop and validate a parsimonious model for predicting short-term all-cause mortality in patients with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS Two cohorts of patients with T2DM were investigated. The Gargano Mortality Study (GMS, n = 679 patients) was the training set and the Foggia Mortality Study (FMS, n = 936 patients) represented the validation sample. GMS and FMS cohorts were prospectively followed up for 7.40 ± 2.15 and 4.51 ± 1.69 years, respectively, and all-cause mortality was registered. A new forward variable selection within a multivariate Cox regression was implemented. Starting from the empty model, each step selected the predictor that, once included into the multivariate Cox model, yielded the maximum continuous net reclassification improvement (cNRI). The selection procedure stopped when no further statistically significant cNRI increase was detected. RESULTS Nine variables (age, BMI, diastolic blood pressure, LDL cholesterol, triglycerides, HDL cholesterol, urine albumin-to-creatinine ratio, and antihypertensive and insulin therapy) were included in the final predictive model with a C statistic of 0.88 (95% CI 0.82–0.94) in the GMS and 0.82 (0.76–0.87) in the FMS. Finally, we used a recursive partition and amalgamation algorithm to identify patients at intermediate and high mortality risk (hazard ratio 7.0 and 24.4, respectively, as compared with those at low risk). A web-based risk calculator was also developed. CONCLUSIONS We developed and validated a parsimonious all-cause mortality equation in T2DM, providing also a user-friendly web-based risk calculator. Our model may help prioritize the use of available resources for targeting aggressive preventive and treatment strategies in a subset of very high-risk individuals.

IRS1 G972R polymorphism and type 2 diabetes: a paradigm for the difficult ascertainment of the contribution to disease susceptibility of 'low-frequency-low-risk' variants.

Aims/hypothesisThe aim of the study was to determine the association between IRS1 G972R polymorphism and type 2 diabetes; published data concerning this association have been conflicting. To obtain further insight into this topic, we performed a meta-analysis of all available case–control studies.MethodsWe performed a meta-analysis of 32 studies (12,076 cases and 11,285 controls).ResultsThe relatively infrequent R972 variant was not significantly associated with type 2 diabetes (OR 1.09, 95% CI 0.96–1.23, p = 0.184 under a dominant model). Some evidence of heterogeneity was observed across studies (p = 0.1). In the 14 studies (9,713 individuals) in which the mean age at type 2 diabetes diagnosis was available, this variable explained 52% of the heterogeneity (p = 0.03). When these studies were subdivided into tertiles of mean age at diagnosis, the OR for diabetes was 1.48 (95% CI 1.17–1.87), 1.22 (95% CI 0.97–1.53) and 0.88 (95% CI 0.68–1.13) in the youngest, intermediate and oldest tertile, respectively (p = 0.0022 for trend of ORs).Conclusions/interpretationOur findings illustrate the difficulties of ascertaining the contribution of ‘low-frequency–low-risk’ variants to type 2 diabetes susceptibility. In the specific context of the R972 variant, ~200,000 study individuals would be needed to have 80% power to identify a 9% increase in diabetes risk at a genome-wide significance level. Under these circumstances, a strategy aimed at improving outcome definition and decreasing its heterogeneity may critically enhance our ability to detect genetic effects, thereby decreasing the required sample size. Our data suggest that focusing on early-onset diabetes, which is characterised by a stronger genetic background, may be part of such a strategy.

PPARγ2 P12A polymorphism and albuminuria in patients with type 2 diabetes: a meta-analysis of case–control studies

BACKGROUND Insulin resistance has a role in diabetic nephropathy. The A12 variant of the PPARγ2 P121A polymorphism has been firmly associated with reduced risk of insulin resistance, while its role on the risk of albuminuria in patients with type 2 diabetes is uncertain. This study investigated whether the PPARγ2 P12A polymorphism modulates the risk of albuminuria in these patients. METHODS We tested the association between the A12 variant and albuminuria in three new case-control studies in diabetic patients from Italy (n = 841, n = 623 and n = 714 patients, respectively) and then performed a meta-analysis of all studies available to date. The nine studies we meta-analysed (six previously published and three presented here) comprised a total of 2376 cases and 4188 controls. RESULTS In none of the three new studies was a significant association observed with odds ratio (OR) [95% confidence intervals (95% CI)] being 1.115, 0.799 and 0.849 (P = 0.603, 0.358 and 0.518, respectively). At meta-analysis, the overall OR (95% CI) for association between A12 and albuminuria was 0.694 (0.528-0.912). A significant heterogeneity of the genetic effect was observed (P = 0.026), which was totally explained by the different method of urine collection and albuminuria definition utilized across the studies. In fact, most of the effect was observed in the four studies determining albumin excretion rate rather than in those using albumin concentration in a single spot (OR, 95% CI: 0.529, 0.397-0.706, P = 0.0000164 and 0.919, 0.733-1.153, P = 0.47, respectively). CONCLUSION The present study shows that the PPARγ2 Ala12 variant is significantly associated with a reduced risk of albuminuria among patients with type 2 diabetes.