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1.  Influence of Apolipoproteins on the Association Between Lipids and Insulin Sensitivity 
Diabetes Care  2013;36(12):4125-4131.
We evaluated whether the association of insulin sensitivity with HDL cholesterol (HDL) and triglycerides is influenced by major plasma apolipoproteins, as suggested by recent experimental evidence.
This study included a cross-sectional analysis of the RISC Study, a multicenter European clinical investigation in 1,017 healthy volunteers balanced in sex (women 54%) and age strata (range 30–60 years). Insulin sensitivity (M/I in µmol ⋅ min−1 ⋅ kgFFM−1 ⋅ nM−1) was measured by the clamp technique and apolipoproteins (ApoB, -C3, -A1, and -E) by Multiplex Technology.
The center-, sex-, and age-adjusted standardized regression coefficients (STDβ) with M/I were similar for HDL and triglycerides (+19.9 ± 1.9 vs. −20.0 ± 2.0, P < 0.0001). Further adjustment for triglycerides (or HDL), BMI, and adiponectin (or nonesterified fatty acid) attenuated the strength of the association of M/I with both HDL (STDβ +6.4 ± 2.3, P < 0.01) and triglycerides (−9.5 ± 2.1, P < 0.001). Neither ApoA1 nor ApoE and ApoB showed any association with M/I independent from plasma HDL cholesterol and triglycerides. ApoC3, in contrast, in both men and women, was positively associated with M/I independently of plasma lipids. A relative enrichment of plasma lipids with ApoC3 is associated with lower body fat percentage and lower plasma alanine amino transferase.
Our results suggest that HDL cholesterol modulates insulin sensitivity through a mechanism that is partially mediated by BMI and adiponectin but not by ApoA1. Similarly, the influence of triglycerides on insulin sensitivity is in part mediated by BMI and is unrelated to ApoE or ApoB, but it is significantly modulated by ApoC3, which appears to protect from the negative effect of plasma lipids.
PMCID: PMC3836122  PMID: 24130363
2.  Long-Term Safety and Efficacy of Empagliflozin, Sitagliptin, and Metformin 
Diabetes Care  2013;36(12):4015-4021.
To investigate the long-term safety and efficacy of empagliflozin, a sodium glucose cotransporter 2 inhibitor; sitagliptin; and metformin in patients with type 2 diabetes.
In this randomized, open-label, 78-week extension study of two 12-week, blinded, dose-finding studies of empagliflozin (monotherapy and add-on to metformin) with open-label comparators, 272 patients received 10 mg empagliflozin (166 as add-on to metformin), 275 received 25 mg empagliflozin (166 as add-on to metformin), 56 patients received metformin, and 56 patients received sitagliptin as add-on to metformin.
Changes from baseline in HbA1c at week 90 were −0.34 to −0.63% (−3.7 to −6.9 mmol/mol) with empagliflozin, −0.56% (−6.1 mmol/mol) with metformin, and −0.40% (−4.4 mmol/mol) with sitagliptin. Changes from baseline in weight at week 90 were −2.2 to −4.0 kg with empagliflozin, −1.3 kg with metformin, and −0.4 kg with sitagliptin. Adverse events (AEs) were reported in 63.2–74.1% of patients on empagliflozin and 69.6% on metformin or sitagliptin; most AEs were mild or moderate in intensity. Hypoglycemic events were rare in all treatment groups, and none required assistance. AEs consistent with genital infections were reported in 3.0–5.5% of patients on empagliflozin, 1.8% on metformin, and none on sitagliptin. AEs consistent with urinary tract infections were reported in 3.8–12.7% of patients on empagliflozin, 3.6% on metformin, and 12.5% on sitagliptin.
Long-term empagliflozin treatment provided sustained glycemic and weight control and was well tolerated with a low risk of hypoglycemia in patients with type 2 diabetes.
PMCID: PMC3836134  PMID: 24186878
3.  Human Insulin Resistance Is Associated With Increased Plasma Levels of 12α-Hydroxylated Bile Acids 
Diabetes  2013;62(12):4184-4191.
Bile acids (BAs) exert pleiotropic metabolic effects, and physicochemical properties of different BAs affect their function. In rodents, insulin regulates BA composition, in part by regulating the BA 12α-hydroxylase CYP8B1. However, it is unclear whether a similar effect occurs in humans. To address this question, we examined the relationship between clamp-measured insulin sensitivity and plasma BA composition in a cohort of 200 healthy subjects and 35 type 2 diabetic (T2D) patients. In healthy subjects, insulin resistance (IR) was associated with increased 12α-hydroxylated BAs (cholic acid, deoxycholic acid, and their conjugated forms). Furthermore, ratios of 12α-hydroxylated/non–12α-hydroxylated BAs were associated with key features of IR, including higher insulin, proinsulin, glucose, glucagon, and triglyceride (TG) levels and lower HDL cholesterol. In T2D patients, BAs were nearly twofold elevated, and more hydrophobic, compared with healthy subjects, although we did not observe disproportionate increases in 12α-hydroxylated BAs. In multivariate analysis of the whole dataset, controlling for sex, age, BMI, and glucose tolerance status, higher 12α-hydroxy/non–12α-hydroxy BA ratios were associated with lower insulin sensitivity and higher plasma TGs. These findings suggest a role for 12α-hydroxylated BAs in metabolic abnormalities in the natural history of T2D and raise the possibility of developing insulin-sensitizing therapeutics based on manipulations of BA composition.
PMCID: PMC3837033  PMID: 23884887
4.  Common genetic variants highlight the role of insulin resistance and body fat distribution in type 2 diabetes, independently of obesity 
Diabetes  2014;63(12):4378-4387.
We aimed to validate genetic variants as instruments for insulin resistance and secretion, to characterise their association with intermediate phenotypes, and to investigate their role in T2D risk among normal-weight, overweight and obese individuals.We investigated the association of genetic scores with euglycaemic-hyperinsulinaemic clamp- and OGTT-based measures of insulin resistance and secretion, and a range of metabolic measures in up to 18,565 individuals. We also studied their association with T2D risk among normal-weight, overweight and obese individuals in up to 8,124 incident T2D cases. The insulin resistance score was associated with lower insulin sensitivity measured by M/I value (β in SDs-per-allele [95%CI]:−0.03[−0.04,−0.01];p=0.004). This score was associated with lower BMI (−0.01[−0.01,−0.0;p=0.02) and gluteofemoral fat-mass (−0.03[−0.05,−0.02;p=1.4×10−6), and with higher ALT (0.02[0.01,0.03];p=0.002) and gamma-GT (0.02[0.01,0.03];p=0.001). While the secretion score had a stronger association with T2D in leaner individuals (pinteraction=0.001), we saw no difference in the association of the insulin resistance score with T2D among BMI- or waist-strata(pinteraction>0.31). While insulin resistance is often considered secondary to obesity, the association of the insulin resistance score with lower BMI and adiposity and with incident T2D even among individuals of normal weight highlights the role of insulin resistance and ectopic fat distribution in T2D, independently of body size.
PMCID: PMC4241116  PMID: 24947364
Genetics; type 2 diabetes; insulin resistance; insulin secretion; adipose expandability
5.  Long-Term Effects of Bariatric Surgery on Meal Disposal and β-Cell Function in Diabetic and Nondiabetic Patients 
Diabetes  2013;62(11):3709-3717.
Gastric bypass surgery leads to marked improvements in glucose tolerance and insulin sensitivity in obese type 2 diabetes (T2D); the impact on glucose fluxes in response to a physiological stimulus, such as a mixed meal test (MTT), has not been determined. We administered an MTT to 12 obese T2D patients and 15 obese nondiabetic (ND) subjects before and 1 year after surgery (10 T2D and 11 ND) using the double-tracer technique and modeling of β-cell function. In both groups postsurgery, tracer-derived appearance of oral glucose was biphasic, a rapid increase followed by a sharp drop, a pattern that was mirrored by postprandial glucose levels and insulin secretion. In diabetic patients, surgery lowered fasting and postprandial glucose levels, peripheral insulin sensitivity increased in proportion to weight loss (∼30%), and β-cell glucose sensitivity doubled but did not normalize (compared with 21 nonsurgical obese and lean controls). Endogenous glucose production, however, was less suppressed during the MMT as the combined result of a relative hyperglucagonemia and the rapid fall in plasma glucose and insulin levels. We conclude that in T2D, bypass surgery changes the postprandial response to a dumping-like pattern and improves glucose tolerance, β-cell function, and peripheral insulin sensitivity but worsens endogenous glucose output in response to a physiological stimulus.
PMCID: PMC3806605  PMID: 23835342
6.  Hepatitis C virus infection and type 1 and type 2 diabetes mellitus 
World Journal of Diabetes  2014;5(5):586-600.
Hepatitis C virus (HCV) infection and diabetes mellitus are two major public health problems that cause devastating health and financial burdens worldwide. Diabetes can be classified into two major types: type 1 diabetes mellitus (T1DM) and T2DM. T2DM is a common endocrine disorder that encompasses multifactorial mechanisms, and T1DM is an immunologically mediated disease. Many epidemiological studies have shown an association between T2DM and chronic hepatitis C (CHC) infection. The processes through which CHC is associated with T2DM seem to involve direct viral effects, insulin resistance, proinflammatory cytokines, chemokines, and other immune-mediated mechanisms. Few data have been reported on the association of CHC and T1DM and reports on the potential association between T1DM and acute HCV infection are even rarer. A small number of studies indicate that interferon-α therapy can stimulate pancreatic autoimmunity and in certain cases lead to the development of T1DM. Diabetes and CHC have important interactions. Diabetic CHC patients have an increased risk of developing cirrhosis and hepatocellular carcinoma compared with non-diabetic CHC subjects. However, clinical trials on HCV-positive patients have reported improvements in glucose metabolism after antiviral treatment. Further studies are needed to improve prevention policies and to foster adequate and cost-effective programmes for the surveillance and treatment of diabetic CHC patients.
PMCID: PMC4138583  PMID: 25317237
Hepatitis C virus infection; Type 1 diabetes mellitus; Type 2 diabetes mellitus; Epidemiology; Pathogenesis; Prevention; Treatment
7.  Mendelian Randomization Studies Do Not Support a Causal Role for Reduced Circulating Adiponectin Levels in Insulin Resistance and Type 2 Diabetes 
Yaghootkar, Hanieh | Lamina, Claudia | Scott, Robert A. | Dastani, Zari | Hivert, Marie-France | Warren, Liling L. | Stancáková, Alena | Buxbaum, Sarah G. | Lyytikäinen, Leo-Pekka | Henneman, Peter | Wu, Ying | Cheung, Chloe Y.Y. | Pankow, James S. | Jackson, Anne U. | Gustafsson, Stefan | Zhao, Jing Hua | Ballantyne, Christie M. | Xie, Weijia | Bergman, Richard N. | Boehnke, Michael | el Bouazzaoui, Fatiha | Collins, Francis S. | Dunn, Sandra H. | Dupuis, Josee | Forouhi, Nita G. | Gillson, Christopher | Hattersley, Andrew T. | Hong, Jaeyoung | Kähönen, Mika | Kuusisto, Johanna | Kedenko, Lyudmyla | Kronenberg, Florian | Doria, Alessandro | Assimes, Themistocles L. | Ferrannini, Ele | Hansen, Torben | Hao, Ke | Häring, Hans | Knowles, Joshua W. | Lindgren, Cecilia M. | Nolan, John J. | Paananen, Jussi | Pedersen, Oluf | Quertermous, Thomas | Smith, Ulf | Lehtimäki, Terho | Liu, Ching-Ti | Loos, Ruth J.F. | McCarthy, Mark I. | Morris, Andrew D. | Vasan, Ramachandran S. | Spector, Tim D. | Teslovich, Tanya M. | Tuomilehto, Jaakko | van Dijk, Ko Willems | Viikari, Jorma S. | Zhu, Na | Langenberg, Claudia | Ingelsson, Erik | Semple, Robert K. | Sinaiko, Alan R. | Palmer, Colin N.A. | Walker, Mark | Lam, Karen S.L. | Paulweber, Bernhard | Mohlke, Karen L. | van Duijn, Cornelia | Raitakari, Olli T. | Bidulescu, Aurelian | Wareham, Nick J. | Laakso, Markku | Waterworth, Dawn M. | Lawlor, Debbie A. | Meigs, James B. | Richards, J. Brent | Frayling, Timothy M.
Diabetes  2013;62(10):3589-3598.
Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics–based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26–0.35) increase in fasting insulin, a 0.34-SD (0.30–0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47–2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI −0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (−0.20 SD; 95% CI −0.38 to −0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75–1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: −0.03 SD; 95% CI −0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95–1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.
PMCID: PMC3781444  PMID: 23835345
8.  Genetic Variants Associated With Glycine Metabolism and Their Role in Insulin Sensitivity and Type 2 Diabetes 
Diabetes  2013;62(6):2141-2150.
Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity–related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites—glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)—and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits.
PMCID: PMC3661655  PMID: 23378610
9.  Personalized Management of Hyperglycemia in Type 2 Diabetes 
Diabetes Care  2013;36(6):1779-1788.
In June 2012, 13 thought leaders convened in a Diabetes Care Editors’ Expert Forum to discuss the concept of personalized medicine in the wake of a recently published American Diabetes Association/European Association for the Study of Diabetes position statement calling for a patient-centered approach to hyperglycemia management in type 2 diabetes. This article, an outgrowth of that forum, offers a clinical translation of the underlying issues that need to be considered for effectively personalizing diabetes care. The medical management of type 2 diabetes has become increasingly complex, and its complications remain a great burden to individual patients and the larger society. The burgeoning armamentarium of pharmacological agents for hyperglycemia management should aid clinicians in providing early treatment to delay or prevent these complications. However, trial evidence is limited for the optimal use of these agents, especially in dual or triple combinations. In the distant future, genotyping and testing for metabolomic markers may help us to better phenotype patients and predict their responses to antihyperglycemic drugs. For now, a personalized (“n of 1”) approach in which drugs are tested in a trial-and-error manner in each patient may be the most practical strategy for achieving therapeutic targets. Patient-centered care and standardized algorithmic management are conflicting approaches, but they can be made more compatible by recognizing instances in which personalized A1C targets are warranted and clinical circumstances that may call for comanagement by primary care and specialty clinicians.
PMCID: PMC3661796  PMID: 23704680
10.  Early Metabolic Markers of the Development of Dysglycemia and Type 2 Diabetes and Their Physiological Significance 
Diabetes  2013;62(5):1730-1737.
Metabolomic screening of fasting plasma from nondiabetic subjects identified α-hydroxybutyrate (α-HB) and linoleoyl-glycerophosphocholine (L-GPC) as joint markers of insulin resistance (IR) and glucose intolerance. To test the predictivity of α-HB and L-GPC for incident dysglycemia, α-HB and L-GPC measurements were obtained in two observational cohorts, comprising 1,261 nondiabetic participants from the Relationship between Insulin Sensitivity and Cardiovascular Disease (RISC) study and 2,580 from the Botnia Prospective Study, with 3-year and 9.5-year follow-up data, respectively. In both cohorts, α-HB was a positive correlate and L-GPC a negative correlate of insulin sensitivity, with α-HB reciprocally related to indices of β-cell function derived from the oral glucose tolerance test (OGTT). In follow-up, α-HB was a positive predictor (adjusted odds ratios 1.25 [95% CI 1.00–1.60] and 1.26 [1.07–1.48], respectively, for each standard deviation of predictor), and L-GPC was a negative predictor (0.64 [0.48–0.85] and 0.67 [0.54–0.84]) of dysglycemia (RISC) or type 2 diabetes (Botnia), independent of familial diabetes, sex, age, BMI, and fasting glucose. Corresponding areas under the receiver operating characteristic curve were 0.791 (RISC) and 0.783 (Botnia), similar in accuracy when substituting α-HB and L-GPC with 2-h OGTT glucose concentrations. When their activity was examined, α-HB inhibited and L-GPC stimulated glucose-induced insulin release in INS-1e cells. α-HB and L-GPC are independent predictors of worsening glucose tolerance, physiologically consistent with a joint signature of IR and β-cell dysfunction.
PMCID: PMC3636608  PMID: 23160532
11.  Renal Glucose Handling 
Diabetes Care  2013;36(5):1260-1265.
Ipragliflozin, a sodium-glucose cotransporter 2 inhibitor, stimulates glycosuria and lowers glycemia in patients with type 2 diabetes (T2DM). The objective of this study was to assess the pharmacodynamics of ipragliflozin in T2DM patients with impaired renal function.
Glycosuria was measured before and after a single ipragliflozin dose in 8 nondiabetic subjects and 57 T2DM patients (age 62 ± 9 years, fasting glucose 133 ± 39 mg/dL, mean ± SD) with normal renal function (assessed as the estimated glomerular filtration rate [eGFR]) (eGFR1 ≥90 mL · min–1 · 1.73 m−2), mild (eGFR2 ≥60 to <90), moderate (eGFR3 ≥30 to <60), or severe reduction in eGFR (eGFR4 ≤15 to <30).
Ipragliflozin significantly increased urinary glucose excretion in each eGFR class (P < 0.0001). However, ipragliflozin-induced glycosuria declined (median [IQR]) across eGFR class (from 46 mg/min [33] in eGFR1 to 8 mg/min [7] in eGFR4, P < 0.001). Ipragliflozin-induced fractional glucose excretion (excretion/filtration) was 39% [27] in the T2DM patients (pooled data), similar to that of the nondiabetic subjects (37% [17], P = ns). In bivariate analysis of the pooled data, ipragliflozin-induced glycosuria was directly related to eGFR and fasting glucose (P < 0.0001 for both, r2 = 0.55), predicting a decrement in 24-h glycosuria of 15 g for each 20 mL/min decline in eGFR and an increase of 7 g for each 10 mg/dL increase in glucose above fasting normoglycemia.
In T2DM patients, ipragliflozin increases glycosuria in direct, linear proportion to GFR and degree of hyperglycemia, such that its amount can be reliably predicted in the individual patient. Although absolute glycosuria decreases with declining GFR, the efficiency of ipragliflozin action (fractional glucose excretion) is maintained in patients with severe renal impairment.
PMCID: PMC3631866  PMID: 23359360
13.  Canagliflozin, a sodium glucose co-transporter 2 inhibitor, improves model-based indices of beta cell function in patients with type 2 diabetes 
Diabetologia  2014;57(5):891-901.
In rodent models of diabetes, treatment with sodium glucose co-transporter 2 (SGLT2) inhibitors improves beta cell function. This analysis assessed the effects of the SGLT2 inhibitor, canagliflozin, on model-based measures of beta cell function in patients with type 2 diabetes.
Data from three Phase 3 studies were analysed, in which: (Study 1) canagliflozin 100 and 300 mg were compared with placebo as monotherapy for 26 weeks; (Study 2) canagliflozin 100 and 300 mg were compared with placebo as add-on to metformin + sulfonylurea for 26 weeks; or (Study 3) canagliflozin 300 mg was compared with sitagliptin 100 mg as add-on to metformin + sulfonylurea for 52 weeks. In each study, a subset of patients was given mixed-meal tolerance tests at baseline and study endpoint, and model-based beta cell function parameters were calculated from plasma glucose and C-peptide.
In Studies 1 and 2, both canagliflozin doses increased beta cell glucose sensitivity compared with placebo. Placebo-subtracted least squares mean (LSM) (SEM) changes were 23 (9) and 18 (9) pmol min−1 m−2 (mmol/l)−1 with canagliflozin 100 and 300 mg, respectively (p < 0.002, Study 1), and 16 (8) and 10 (9) pmol min−1 m−2 (mmol/l)−1 (p < 0.02, Study 2). In Study 3, beta cell glucose sensitivity was minimally affected, but the insulin secretion rate at 9 mmol/l glucose increased to similar degrees from baseline with canagliflozin and sitagliptin [LSM (SEM) changes 38 (8) and 28 (9) pmol min−1 m−2, respectively; p < 0.05 for both].
Treatment with canagliflozin for 6 to 12 months improved model-based measures of beta cell function in three separate Phase 3 studies.
Trial registration: NCT01081834 (Study 1); NCT01106625 (Study 2); NCT01137812 (Study 3)
Electronic supplementary material
The online version of this article (doi:10.1007/s00125-014-3196-x) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
PMCID: PMC3980039  PMID: 24585202
Beta cell function; Canagliflozin; Insulin secretion; SGLT2; Sodium glucose co-transporter 2 inhibitor; Type 2 diabetes
14.  Metabolic response to sodium-glucose cotransporter 2 inhibition in type 2 diabetic patients 
Background. Sodium-glucose cotransporter 2 (SGLT2) inhibitors lower glycemia by enhancing urinary glucose excretion. The physiologic response to pharmacologically induced acute or chronic glycosuria has not been investigated in human diabetes.
Methods. We evaluated 66 patients with type 2 diabetes (62 ± 7 years, BMI = 31.6 ± 4.6 kg/m2, HbA1c = 55 ± 8 mmol/mol, mean ± SD) at baseline, after a single dose, and following 4-week treatment with empagliflozin (25 mg). At each time point, patients received a mixed meal coupled with dual-tracer glucose administration and indirect calorimetry.
Results. Both single-dose and chronic empagliflozin treatment caused glycosuria during fasting (median, 7.8 [interquartile range {IQR}, 4.4] g/3 hours and 9.2 [IQR, 5.2] g/3 hours) and after meal ingestion (median, 29.0 [IQR, 12.5] g/5 hours and 28.2 [IQR, 15.4] g/5 hours). After 3 hours of fasting, endogenous glucose production (EGP) was increased 25%, while glycemia was 0.9 ± 0.7 mmol/l lower (P < 0.0001 vs. baseline). After meal ingestion, glucose and insulin AUC decreased, whereas the glucagon response increased (all P < 0.001). While oral glucose appearance was unchanged, EGP was increased (median, 40 [IQR, 14] g and 37 [IQR, 11] g vs. 34 [IQR, 11] g, both P < 0.01). Tissue glucose disposal was reduced (median, 75 [IQR, 16] g and 70 [IQR, 21] g vs. 93 [IQR, 18] g, P < 0.0001), due to a decrease in both glucose oxidation and nonoxidative glucose disposal, with a concomitant rise in lipid oxidation after chronic administration (all P < 0.01). β Cell glucose sensitivity increased (median, 55 [IQR, 35] pmol•min–1•m–2•mM–1 and 55 [IQR, 39] pmol•min–1•m–2•mM–1 vs. 44 [IQR, 32] pmol•min–1•m–2•mM–1, P < 0.0001), and insulin sensitivity was improved. Resting energy expenditure rates and those after meal ingestion were unchanged.
Conclusions. In patients with type 2 diabetes, empagliflozin-induced glycosuria improved β cell function and insulin sensitivity, despite the fall in insulin secretion and tissue glucose disposal and the rise in EGP after one dose, thereby lowering fasting and postprandial glycemia. Chronic dosing shifted substrate utilization from carbohydrate to lipid.
Trial registration. ClinicalTrials.Gov NCT01248364 (EudraCT no. 2010-018708-99).
Funding. This study was funded by Boehringer Ingelheim.
PMCID: PMC3904627  PMID: 24463454
15.  Residual macrovascular risk in 2013: what have we learned? 
Cardiovascular disease poses a major challenge for the 21st century, exacerbated by the pandemics of obesity, metabolic syndrome and type 2 diabetes. While best standards of care, including high-dose statins, can ameliorate the risk of vascular complications, patients remain at high risk of cardiovascular events. The Residual Risk Reduction Initiative (R3i) has previously highlighted atherogenic dyslipidaemia, defined as the imbalance between proatherogenic triglyceride-rich apolipoprotein B-containing-lipoproteins and antiatherogenic apolipoprotein A-I-lipoproteins (as in high-density lipoprotein, HDL), as an important modifiable contributor to lipid-related residual cardiovascular risk, especially in insulin-resistant conditions. As part of its mission to improve awareness and clinical management of atherogenic dyslipidaemia, the R3i has identified three key priorities for action: i) to improve recognition of atherogenic dyslipidaemia in patients at high cardiometabolic risk with or without diabetes; ii) to improve implementation and adherence to guideline-based therapies; and iii) to improve therapeutic strategies for managing atherogenic dyslipidaemia. The R3i believes that monitoring of non-HDL cholesterol provides a simple, practical tool for treatment decisions regarding the management of lipid-related residual cardiovascular risk. Addition of a fibrate, niacin (North and South America), omega-3 fatty acids or ezetimibe are all options for combination with a statin to further reduce non-HDL cholesterol, although lacking in hard evidence for cardiovascular outcome benefits. Several emerging treatments may offer promise. These include the next generation peroxisome proliferator-activated receptorα agonists, cholesteryl ester transfer protein inhibitors and monoclonal antibody therapy targeting proprotein convertase subtilisin/kexin type 9. However, long-term outcomes and safety data are clearly needed. In conclusion, the R3i believes that ongoing trials with these novel treatments may help to define the optimal management of atherogenic dyslipidaemia to reduce the clinical and socioeconomic burden of residual cardiovascular risk.
PMCID: PMC3922777  PMID: 24460800
Residual cardiovascular risk; Atherogenic dyslipidaemia; Type 2 diabetes; Therapeutic options
16.  A Novel Fasting Blood Test for Insulin Resistance and Prediabetes 
Insulin resistance (IR) can precede the dysglycemic states of prediabetes and type 2 diabetes mellitus (T2DM) by a number of years and is an early marker of risk for metabolic and cardiovascular disease. There is an unmet need for a simple method to measure IR that can be used for routine screening, prospective study, risk assessment, and therapeutic monitoring. We have reported several metabolites whose fasting plasma levels correlated with insulin sensitivity. These metabolites were used in the development of a novel test for IR and prediabetes.
Data from the Relationship between Insulin Sensitivity and Cardiovascular Disease Study were used in an iterative process of algorithm development to define the best combination of metabolites for predicting the M value derived from the hyperinsulinemic euglycemic clamp, the gold standard measure of IR. Subjects were divided into a training set and a test set for algorithm development and validation. The resulting calculated M score, MQ, was utilized to predict IR and the risk of progressing from normal glucose tolerance to impaired glucose tolerance (IGT) over a 3 year period.
MQ correlated with actual M values, with an r value of 0.66. In addition, the test detects IR and predicts 3 year IGT progression with areas under the curve of 0.79 and 0.70, respectively, outperforming other simple measures such as fasting insulin, fasting glucose, homeostatic model assessment of IR, or body mass index.
The result, Quantose™, is a simple test for IR based on a single fasting blood sample and may have value as an early indicator of risk for the development of prediabetes and T2DM.
PMCID: PMC3692221  PMID: 23439165
biomarkers; insulin resistance; metabolomics; prediabetes; Quantose
17.  Mechanisms of the Incretin Effect in Subjects with Normal Glucose Tolerance and Patients with Type 2 Diabetes 
PLoS ONE  2013;8(9):e73154.
The incretin effect on insulin secretion was investigated in 8 subjects with type 2 diabetes (T2D) and 8 with normal glucose tolerance (NGT), using 25, 75, and 125 g oral glucose tolerance tests (OGTT) and isoglycemic intravenous glucose infusions (IIGI). The ß-cell response was evaluated using a model embedding a dose-response (slope = glucose sensitivity), an early response (rate sensitivity), and potentiation (time-related secretion increase). The incretin effect, as OGTT/IIGI ratio, was calculated for each parameter. In NGT, the incretin effect on total secretion increased with dose (1.3±0.1, 1.7±0.2, 2.2±0.2 fold of IIGI, P<0.0001), mediated by a dose-dependent increase of the incretin effect on glucose sensitivity (1.9±0.4, 2.4±0.4, 3.1±0.4, P = 0.005), and a dose-independent enhancement of the incretin effect on rate sensitivity (894 [1145], 454 [516], 783 [1259] pmol m−2 L mmol−1 above IIGI; median [interquartile range], P<0.0001). The incretin effect on potentiation also increased (0.97±0.06, 1.45±0.20, 1.24±0.16, P<0.0001). In T2D, the incretin effect on total secretion (1.0±0.1, 1.1±0.1, 1.3±0.1, P = 0.004) and glucose sensitivity (1.2±0.2, 1.3±0.2, 2.0±0.2, P = 0.005) were impaired vs NGT; however, the incretin effect on rate sensitivity increased already at 25 g (269 [169], 284 [301], 193 [465] pmol m−2 L mmol−1 above IIGI; negligible IIGI rate sensitivity in T2D prevented the calculation of the fold increment). OGTT did not stimulate potentiation above IIGI (0.94±0.04, 0.89±0.06, 1.06±0.09; P<0.01 vs NGT). In the whole group, the incretin effect was inversely associated with total secretion during IIGI, although systematically lower in T2D. In conclusion, 1) In NGT, glucose sensitivity and potentiation mediate the dose-dependent incretin effect increase; 2) In T2D, the incretin effect is blunted vs NGT, but rate sensitivity is enhanced at all loads; 3) Relatively lower incretin effect in NGT is associated with higher secretion during IIGI, suggesting that the reduced incretin effect does not result from ß-cell dysfunction.
PMCID: PMC3760909  PMID: 24019903
19.  Influence of Hyperinsulinemia and Insulin Resistance on In Vivo β-Cell Function 
Diabetes  2011;60(12):3141-3147.
Recent work has shown that insulin stimulates its own secretion in insulin-sensitive humans, suggesting that insulin resistance in the β-cell could cause β-cell dysfunction. We have tested whether insulin exposure and insulin sensitivity modulate β-cell function in subjects with normal glucose tolerance (NGT) and whether they contribute to dysglycemia in impaired glucose regulation (IGR).
Insulin sensitivity (by euglycemic clamp), insulin-induced secretory response at isoglycemia (IISR) (as C-peptide percent change from basal during the clamp), glucose-induced secretory response (GISR) to an intravenous glucose bolus, and β-cell glucose sensitivity (β-GS) (by oral glucose tolerance test [OGTT] modeling) were measured in 1,151 NGT and 163 IGR subjects from the RISC (Relationship between Insulin Sensitivity and Cardiovascular Disease) study.
In NGT, IISR was related to both insulin sensitivity and antecedent insulin exposure; GISR was related to insulin exposure. IISR was positively, if weakly, related to β-GS (r= 0.16, P < 0.0001). Both IISR (−23 [39] vs. −9 [2]%, median [interquartile range], P < 0.03) and β-GS (69 [47] vs. 118 [83] pmol ⋅ min–1 ⋅ m–2 ⋅ mmol–1 ⋅ L, P < 0.0001) were decreased in IGR compared with NGT. Insulin sensitivity and β-GS were the major determinants of mean OGTT glucose in both NGT and IGR, with a minor role for IISR. In a multivariate logistic model, IGR was predicted by β-GS (odds ratio 4.84 [95% CI 2.89–8.09]) and insulin sensitivity (3.06 [2.19–4.27]) but not by IISR (1.11 [0.77–1.61]).
Pre-exposure to physiological hyperinsulinemia stimulates insulin secretion to a degree that depends on insulin sensitivity. However, this phenomenon has limited impact on β-cell dysfunction and dysglycemia.
PMCID: PMC3219936  PMID: 22028180
20.  Anti-inflammatory and Antioxidant Properties of HDLs Are Impaired in Type 2 Diabetes 
Diabetes  2011;60(10):2617-2623.
In mice, 4F, an apolipoprotein A-I mimetic peptide that restores HDL function, prevents diabetes-induced atherosclerosis. We sought to determine whether HDL function is impaired in type 2 diabetic (T2D) patients and whether 4F treatment improves HDL function in T2D patient plasma in vitro.
HDL anti-inflammatory function was determined in 93 T2D patients and 31 control subjects as the ability of test HDLs to inhibit LDL-induced monocyte chemotactic activity in human aortic endothelial cell monolayers. The HDL antioxidant properties were measured using a cell-free assay that uses dichlorofluorescein diacetate. Oxidized fatty acids in HDLs were measured by liquid chromatography–tandem mass spectrometry. In subgroups of patients and control subjects, the HDL inflammatory index was repeated after incubation with L-4F.
The HDL inflammatory index was 1.42 ± 0.29 in T2D patients and 0.70 ± 0.19 in control subjects (P < 0.001). The cell-free assay was impaired in T2D patients compared with control subjects (2.03 ± 1.35 vs. 1.60 ± 0.80, P < 0.05), and also HDL intrinsic oxidation (cell-free assay without LDL) was higher in T2D patients (1,708 ± 739 vs. 1,233 ± 601 relative fluorescence units, P < 0.001). All measured oxidized fatty acids were significantly higher in the HDLs of T2D patients. There was a significant correlation between the cell-free assay values and the content of oxidized fatty acids in HDL fractions. L-4F treatment restored the HDL inflammatory index in diabetic plasma samples (from 1.26 ± 0.17 to 0.71 ± 0.11, P < 0.001) and marginally affected it in healthy subjects (from 0.81 ± 0.16 to 0.66 ± 0.10, P < 0.05).
In patients with T2D, the content of oxidized fatty acids is increased and the anti-inflammatory and antioxidant activities of HDLs are impaired.
PMCID: PMC3178289  PMID: 21852676
21.  Genome-Wide Association Identifies Nine Common Variants Associated With Fasting Proinsulin Levels and Provides New Insights Into the Pathophysiology of Type 2 Diabetes 
Strawbridge, Rona J. | Dupuis, Josée | Prokopenko, Inga | Barker, Adam | Ahlqvist, Emma | Rybin, Denis | Petrie, John R. | Travers, Mary E. | Bouatia-Naji, Nabila | Dimas, Antigone S. | Nica, Alexandra | Wheeler, Eleanor | Chen, Han | Voight, Benjamin F. | Taneera, Jalal | Kanoni, Stavroula | Peden, John F. | Turrini, Fabiola | Gustafsson, Stefan | Zabena, Carina | Almgren, Peter | Barker, David J.P. | Barnes, Daniel | Dennison, Elaine M. | Eriksson, Johan G. | Eriksson, Per | Eury, Elodie | Folkersen, Lasse | Fox, Caroline S. | Frayling, Timothy M. | Goel, Anuj | Gu, Harvest F. | Horikoshi, Momoko | Isomaa, Bo | Jackson, Anne U. | Jameson, Karen A. | Kajantie, Eero | Kerr-Conte, Julie | Kuulasmaa, Teemu | Kuusisto, Johanna | Loos, Ruth J.F. | Luan, Jian'an | Makrilakis, Konstantinos | Manning, Alisa K. | Martínez-Larrad, María Teresa | Narisu, Narisu | Nastase Mannila, Maria | Öhrvik, John | Osmond, Clive | Pascoe, Laura | Payne, Felicity | Sayer, Avan A. | Sennblad, Bengt | Silveira, Angela | Stančáková, Alena | Stirrups, Kathy | Swift, Amy J. | Syvänen, Ann-Christine | Tuomi, Tiinamaija | van 't Hooft, Ferdinand M. | Walker, Mark | Weedon, Michael N. | Xie, Weijia | Zethelius, Björn | Ongen, Halit | Mälarstig, Anders | Hopewell, Jemma C. | Saleheen, Danish | Chambers, John | Parish, Sarah | Danesh, John | Kooner, Jaspal | Östenson, Claes-Göran | Lind, Lars | Cooper, Cyrus C. | Serrano-Ríos, Manuel | Ferrannini, Ele | Forsen, Tom J. | Clarke, Robert | Franzosi, Maria Grazia | Seedorf, Udo | Watkins, Hugh | Froguel, Philippe | Johnson, Paul | Deloukas, Panos | Collins, Francis S. | Laakso, Markku | Dermitzakis, Emmanouil T. | Boehnke, Michael | McCarthy, Mark I. | Wareham, Nicholas J. | Groop, Leif | Pattou, François | Gloyn, Anna L. | Dedoussis, George V. | Lyssenko, Valeriya | Meigs, James B. | Barroso, Inês | Watanabe, Richard M. | Ingelsson, Erik | Langenberg, Claudia | Hamsten, Anders | Florez, Jose C.
Diabetes  2011;60(10):2624-2634.
Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology.
We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates.
Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10−8). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10−4), improved β-cell function (P = 1.1 × 10−5), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10−6). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets.
We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.
PMCID: PMC3178302  PMID: 21873549
23.  Body Weight, Not Insulin Sensitivity or Secretion, May Predict Spontaneous Weight Changes in Nondiabetic and Prediabetic Subjects 
Diabetes  2011;60(7):1938-1945.
Previous studies have found that high insulin sensitivity predicts weight gain; this association has not been confirmed. Our aim was to systematically analyze metabolic predictors of spontaneous weight changes.
In 561 women and 467 men from the Relationship Between Insulin Sensitivity and Cardiovascular Disease (RISC) cohort (mean age 44 years, BMI range 19–44 kg/m2, 9% impaired glucose tolerance) followed up for 3 years, we measured insulin sensitivity (by a euglycemic clamp) and β-cell function (by modeling of the C-peptide response to oral glucose and by acute insulin response to intravenous glucose).
Insulin sensitivity was similar in weight gainers (top 20% of the distribution of BMI changes), weight losers (bottom 20%), and weight stable subjects across quartiles of baseline BMI. By multiple logistic or linear regression analyses controlling for center, age, sex, and baseline BMI, neither insulin sensitivity nor any β-cell function parameter showed an independent association with weight gain; this was true in normal glucose tolerance, impaired glucose tolerance, and whether subjects progressed to dysglycemia or not. Baseline BMI was significantly higher in gainers (26.1 ± 4.1 kg/m2) and losers (26.6 ± 3.7 kg/m2) than in weight stable subjects (24.8 ± 3.8 kg/m2, P < 0.0001 for both gainers and losers). Baseline waist circumference (or equivalently, BMI or weight) was a positive, independent predictor of both weight gain and weight loss (odds ratio 1.48 [95% CI 1.12–1.97]) in men and (1.67 [1.28–2.12]) in women. In men only, better insulin sensitivity was an additional independent predictor of weight loss.
Neither insulin sensitivity nor insulin secretion predicts spontaneous weight gain. Individuals who have attained a higher weight are prone to either gaining or losing weight regardless of their glucose tolerance.
PMCID: PMC3121437  PMID: 21617179
24.  Obesity and Type 2 Diabetes: What Can Be Unified and What Needs to Be Individualized? 
Diabetes Care  2011;34(6):1424-1430.
This report examines what is known about the relationship between obesity and type 2 diabetes and how future research in these areas might be directed to benefit prevention, interventions, and overall patient care.
An international working group of 32 experts in the pathophysiology, genetics, clinical trials, and clinical care of obesity and/or type 2 diabetes participated in a conference held on 6–7 January 2011 and cosponsored by The Endocrine Society, the American Diabetes Association, and the European Association for the Study of Diabetes. A writing group comprising eight participants subsequently prepared this summary and recommendations. Participants reviewed and discussed published literature and their own unpublished data.
The writing group unanimously supported the summary and recommendations as representing the working group's majority or unanimous opinions.
The major questions linking obesity to type 2 diabetes that need to be addressed by combined basic, clinical, and population-based scientific approaches include the following: 1) Why do not all patients with obesity develop type 2 diabetes? 2) Through what mechanisms do obesity and insulin resistance contribute to β-cell decompensation, and if/when obesity prevention ensues, how much reduction in type 2 diabetes incidence will follow? 3) How does the duration of type 2 diabetes relate to the benefits of weight reduction by lifestyle, weight-loss drugs, and/or bariatric surgery on β-cell function and glycemia? 4) What is necessary for regulatory approval of medications and possibly surgical approaches for preventing type 2 diabetes in patients with obesity? Improved understanding of how obesity relates to type 2 diabetes may help advance effective and cost-effective interventions for both conditions, including more tailored therapy. To expedite this process, we recommend further investigation into the pathogenesis of these coexistent conditions and innovative approaches to their pharmacological and surgical management.
PMCID: PMC3114323  PMID: 21602431
25.  Learning From Glycosuria 
Diabetes  2011;60(3):695-696.
PMCID: PMC3046828  PMID: 21357469

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