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Progression of hyperglycemia is mediated by loss of β-cell function, but we lack a marker which would be sufficiently accurate and convenient to use in large prospective trials. To determine if the 1 hour OGTT plasma glucose (1hrOGTT) could serve such a purpose, we compared it to standard measures of the disposition index (DI, insulin secretion*insulin action) in 584 European adults without known diabetes in the Relationship between Insulin Sensitivity and Cardiovascular Disease Risk (RISC) study dataset, to predict progression over 3 years. Measures included DImodeling (OGTT modeling β-cell glucose sensitivity*insulin sensitivity), DI-ISI ([0-30min ΔC-peptide/Δglucose]*[1/fasting insulin]), DIclamp (acute C-peptide response to glucose*euglycemic clamp glucose disposal [M/I]), and DIhybrid (OGTT modeling β-cell glucose sensitivity*M/I). Using ADA OGTT criteria, for predicting progression from normal glucose to any dysglycemia (diabetes [DM, FPG >126 or 2hrPG >200 mg/dl] or prediabetes [IFG, FPG 100-125, or IGT, 2hrPG 140-199 mg/dl], n=115), the area under receiver operating characteristic curves (ROC) for the 1hrOGTT was 0.637 vs. 0.607, 0.602, 0.565, and 0.582 for DImodeling, DI-ISI, DIclamp, and DIhybrid, respectively. For non-high risk progressing to high risk dysglycemia ([DM] or [IFG + IGT], n=40), the 1hrOGTT ROC was 0.790 vs. 0.738, 0.737, 0.647, and 0.729 for the DI indices, respectively, and for non-DM progressing to DM (n=6), the 1hrOGTT ROC was 0.910, vs. 0.899, 0.822, 0.741, and 0.837 for the DI indices, respectively. Conclusions: The 1hrOGTT plasma glucose level appears to be comparable or superior to the DI based on more labor-intensive and costly direct assessments of insulin secretion and action in predicting progression of hyperglycemia over 3 years. Consideration should be given to use of the 1hrOGTT glucose as both an accurate and convenient indirect measure of β-cell function in clinical trials, and possibly also of the risk of development and progression of hyperglycemia in clinical practice. Disclosure B.T. Legvold: None. A. Zhang: None. M.K. Rhee: Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc. L.R. Staimez: None. K. Utzschneider: Other Relationship; Self; Medtronic. L.P. Savoye: None. J.R. Petrie: Advisory Panel; Self; Novo Nordisk A/S. Consultant; Self; Advanced Clinical Intelligence, IQVIA. Research Support; Self; AstraZeneca, Janssen Pharmaceuticals, Inc. Speaker’s Bureau; Self; Merck KGaA, Novo Nordisk A/S. B. Balkau: None. L.S. Phillips: Research Support; Self; AbbVie Inc., Diasome Pharmaceuticals, Inc., Eli Lilly and Company, GlaxoSmithKline plc., Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Pfizer Inc., Sanofi-Aventis. Other Relationship; Self; Diasyst, Janssen Pharmaceuticals, Inc. Funding U.S. Department of Veterans Affairs (CX001025, BX003340, CX001737); National Institutes of Health (DK099716, DK091958, DK098246, DK111024, AI133172)

OBJECTIVE 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). RESEARCH DESIGN AND METHODS 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. RESULTS 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]). CONCLUSIONS 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.

OBJECTIVE To assess the impact of genetic susceptibility on evolution toward type 2 diabetes (T2D) by analyzing time trajectories of fasting glucose, glycated hemoglobin (HbA1c), insulin sensitivity (homeostasis model assessment [HOMA2%S]), and β-cell secretion (HOMA2%B) in a large nondiabetic cohort. We also examined whether baseline HbA1c modified the effect of genetic predisposition on the time trajectories. RESEARCH DESIGN AND METHODS Time trajectories were drawn in 4,744 participants from the French Data from an Epidemiological Study on the Insulin Resistance Syndrome (D.E.S.I.R.) cohort based on samples collected every 3 years over a 9-year follow-up. Trajectories were analyzed according to the TCF7L2 common variant, a family history of T2D, and a combination of at-risk alleles from nine T2D-associated genes. RESULTS There was a marked decrease in HOMA2%B in parallel to a steep increase in HbA1c over the 3 years before incident diabetes, which was not influenced by genetic predisposition when considered alone. However, after the onset of T2D, the TCF7L2 at-risk variant was associated with a greater decrease in HOMA2%B. There was a joint effect of a family history of T2D with the presence of the TCF7L2 risk allele with a greater rise in HbA1c conferred by the coexistence of a family history and the T risk allele. An HbA1c ≥5.7% at baseline was associated with a greater increase in both glycemia and HbA1c levels in the presence of a combination of diabetes at-risk alleles. CONCLUSIONS After incident T2D, TCF7L2 at-risk variants were associated with a faster decrease in β-cell function compared with those with the CC genotype. There was a joint effect of family history of T2D and TCF7L2 risk variant on the rise in glycemia and the decrease in insulin secretion at the end of follow-up, suggesting the joint influence of the combination of diabetes genetic predisposition with familial factors on the evolution of glycemia over time.

OBJECTIVE 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. RESEARCH DESIGN AND METHODS 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). RESULTS 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. CONCLUSIONS 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.

OBJECTIVE A1C is widely considered the gold standard for monitoring effective blood glucose levels. Recently, a genome-wide association study reported an association between A1C and rs7072268 within HK1 (encoding hexokinase 1), which catalyzes the first step of glycolysis. HK1 deficiency in erythrocytes (red blood cells [RBCs]) causes severe nonspherocytic hemolytic anemia in both humans and mice. RESEARCH DESIGN AND METHODS The contribution of rs7072268 to A1C and the RBC-related traits was assessed in 6,953 nondiabetic European participants. We additionally analyzed the association with hematologic traits in 5,229 nondiabetic European individuals (in whom A1C was not measured) and 1,924 diabetic patients. Glucose control–related markers other than A1C were analyzed in 18,694 nondiabetic European individuals. A type 2 diabetes case-control study included 7,447 French diabetic patients. RESULTS Our study confirms a strong association between the rs7072268–T allele and increased A1C (β = 0.029%; P = 2.22 × 10−7). Surprisingly, despite adequate study power, rs7072268 showed no association with any other markers of glucose control (fasting- and 2-h post-OGTT–related parameters, n = 18,694). In contrast, rs7072268–T allele decreases hemoglobin levels (n = 13,416; β = −0.054 g/dl; P = 3.74 × 10−6) and hematocrit (n = 11,492; β = −0.13%; P = 2.26 × 10−4), suggesting a proanemic effect. The T allele also increases risk for anemia (836 cases; odds ratio 1.13; P = 0.018). CONCLUSIONS HK1 variation, although strongly associated with A1C, does not seem to be involved in blood glucose control. Since HK1 rs7072268 is associated with reduced hemoglobin levels and favors anemia, we propose that HK1 may influence A1C levels through its anemic effect or its effect on glucose metabolism in RBCs. These findings may have implications for type 2 diabetes diagnosis and clinical management because anemia is a frequent complication of the diabetes state.

OBJECTIVE Genome-wide association studies have identified several variants within the MTNR1B locus that are associated with fasting plasma glucose (FPG) and type 2 diabetes. We refined the association signal by direct genotyping and examined for associations of the variant displaying the most independent effect on FPG with isolated impaired fasting glycemia (i-IFG), isolated impaired glucose tolerance (i-IGT), type 2 diabetes, and measures of insulin release and peripheral and hepatic insulin sensitivity. RESEARCH DESIGN AND METHODS We examined European-descent participants in the Inter99 study (n = 5,553), in a sample of young healthy Danes (n = 372), in Danish twins (n = 77 elderly and n = 97 young), in additional Danish type 2 diabetic patients (n = 1,626) and control subjects (n = 505), in the Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR) study (n = 4,656), in the North Finland Birth Cohort 86 (n = 5,258), and in the Haguenau study (n = 1,461). RESULTS The MTNR1B intronic variant, rs10830963, carried most of the effect on FPG and showed the strongest association with FPG (combined P = 5.3 × 10−31) and type 2 diabetes. The rs10830963 G-allele increased the risk of i-IFG (odds ratio [OR] 1.64, P = 5.5 × 10−11) but not i-IGT. The G-allele was associated with a decreased insulin release after oral and intravenous glucose challenges (P < 0.01) but not after injection of tolbutamide. In elderly twins, the G-allele associated with hepatic insulin resistance (P = 0.017). CONCLUSIONS The G-allele of MTNR1B rs10830963 increases risk of type 2 diabetes through a state of i-IFG and not through i-IGT. The same allele associates with estimates of β-cell dysfunction and hepatic insulin resistance.

OBJECTIVE— Physical activity is a modifiable risk factor for type 2 diabetes, partly through its action on insulin sensitivity. We report the relation between insulin sensitivity and physical activity measured by accelerometry. RESEARCH DESIGN AND METHODS— This is a cross-sectional study of 346 men and 455 women, aged 30–60 years, without cardiovascular disease and not treated by drugs for diabetes, hypertension, dyslipidemia, or obesity. Participants were recruited in 18 clinical centers from 13 European countries. Insulin sensitivity was measured by hyperinsulinemic-euglycemic clamp. Physical activity was recorded by accelerometry for a median of 6 days. We studied the relationship of insulin sensitivity with total activity (in counts per minute), percent of time spent sedentary, percent of time in light activity, and activity intensity (whether the participant recorded some vigorous or some moderate activity). RESULTS— In both men and women, total activity was associated with insulin sensitivity (P < 0.0001). Time spent sedentary, in light activity, and activity intensity was also associated with insulin sensitivity (P < 0.0004/0.01, 0.002/0.03, and 0.02/0.004, respectively, for men/women) but lost significance once adjusted for total activity. Adjustment for confounders such as adiposity attenuated the relationship with total activity; there were no interactions with confounders. Even in the 25% most sedentary individuals, total activity was significantly associated with better insulin sensitivity (P < 0.0001). CONCLUSIONS— Accumulated daily physical activity is a major determinant of insulin sensitivity. Time spent sedentary, time spent in light-activity, and bouts of moderate or vigorous activity did not impact insulin sensitivity independently of total activity.

OBJECTIVE— Hepatic glucokinase (GCK) is a key regulator of glucose storage and disposal in the liver, where its activity is competitively modulated, with respect to glucose, by binding to glucokinase regulatory protein (GCKR) in the presence of fructose 6-phosphate. Genome-wide association studies for type 2 diabetes identified GCKR as a potential locus for modulating triglyceride levels. We evaluated, in a general French population, the contribution of the GCKR rs1260326-P446L polymorphism to quantitative metabolic parameters and to dyslipidemia and hyperglycemia risk. RESEARCH DESIGN AND METHODS— Genotype effects of rs1260326 were studied in 4,833 participants from the prospective DESIR (Data from an Epidemiological Study on the Insulin Resistance syndrome) cohort both at inclusion and using the measurements at follow-up. RESULTS— The minor T-allele of rs1260326 was strongly associated with lower fasting glucose (−1.43% per T-allele; P = 8 × 10−13) and fasting insulin levels (−4.23%; P = 3 × 10−7), lower homeostasis model assessment of insulin resistance index (−5.69%; P = 1 × 10−8), and, conversely, higher triglyceride levels (3.41%; P = 1 × 10−4) during the 9-year study. These effects relate to a lower risk of hyperglycemia (odds ratio [OR] 0.79 [95% CI 0.70–0.88]; P = 4 × 10−5) and of incident cases during the study (hazard ratio [HR] 0.83 [0.74–0.95]; P = 0.005). Moreover, an additive effect of GCKR rs1260326(T) and GCK (−30G) alleles conferred lower fasting glycemia (P = 1 × 10−13), insulinemia (P = 5 × 10−6), and hyperglycemia risk (P = 1 × 10−6). CONCLUSIONS— GCKR-L446 carriers are protected against type 2 diabetes despite higher triglyceride levels and risk of dyslipidemia, which suggests a potential molecular mechanism by which these two components of the metabolic syndrome can be dissociated.

OBJECTIVE— The emerging picture of type 2 diabetes genetics involves differently assembled gene variants, each modestly increasing risk with environmental exposure. However, the relevance of these genes for disease prediction has not been extensively tested. RESEARCH DESIGN AND METHODS— We analyzed 19 common polymorphisms of 14 known candidate genes for their contribution to prevalence and incidence of glucose intolerance in the DESIR (Data from an Epidemiological Study on the Insulin Resistance syndrome) prospective study of middle-aged Caucasian subjects, including 3,877 participants (16.8% with hyperglycemia and 7.9% with diabetes after the 9-year study). RESULTS— The GCK (Glucokinase) −30A allele was associated with increased type 2 diabetes risk at the end of the follow-up study (adjusted OR 1.34 [95% CI 1.07–1.69]) under an additive model, as supported in independent French diabetic case subjects (OR 1.22, P = 0.007), with increased fasting glycemia (0.85% per A allele, P = 6 × 10−5) and decreased homeostasis model assessment of β-cell function (4%, P = 0.0009). IL6 (Interleukin- 6) −174 G/C interacts with age in disease risk and modulates fasting glycemia according to age (1.36% decrease over 56 years, P = 5 × 10−5). These polymorphisms together with KCNJ11 (Kir6.2)-E23K and TCF7L2-rs7903146 may predict diabetes incidence in the DESIR cohort. Each additional risk allele at GCK, TCF7L2, and IL6 increased risk by 1.34 (P = 2 × 10−6), with an OR of 2.48 (95% CI 1.59–3.86), in carriers of at least four at-risk alleles compared with those with none or one risk allele. CONCLUSIONS— Our data confirm several at-risk polymorphisms for type 2 diabetes in a general population and demonstrate that prospective studies are valuable designs to complement classical genetic approaches.

Recently, case-control studies demonstrated that a TCF7L2 (transcription factor 7-like 2 gene) noncoding variant (rs7903146 T at-risk allele) was strongly associated with an increased risk of type 2 diabetes. However, the predictive value of this marker in a nonselected general population remains unknown. In this study, our aim was to assess the contribution of this variant to the prevalence and incidence of hyperglycemia (type 2 diabetes and impaired fasting glucose) and insulin regulation in a 9-year prospective study of 4,976 middle-aged participants in the French DESIR (Data from an Epidemiological Study on the Insulin Resistance Syndrome) cohort. Our data support previous studies associating the T at-risk allele with a higher prevalence of hyperglycemia at baseline (P = 0.049) and a higher incidence of hyperglycemia after 9 years of follow-up (P = 0.014). The population-attributable risk to develop hyperglycemia due to the T at-risk allele was estimated to be 10.4% at the end of the prospective study. The most likely inheritance model was found to be additive (P = 0.002) rather than deviating from linearity (hazard ratio 1.21 [95% CI 1.05-1.39], P = 0.008) [corrected] An increase in the incidence of hyperglycemia was confirmed by survival analyses among C/C, C/T, and T/T carriers during the 9 years of follow-up (P = 0.028 by log-rank test). Interestingly, in control individuals, there was weak evidence of association of the T at-risk allele with reduced fasting insulin levels and insulin secretion index (homeostasis model assessment of beta-cell function) in control individuals. We conclude that the TCF7L2 T at-risk allele variation (rs7903146) predicts hyperglycemia incidence in a general French population, possibly through a deleterious effect on insulin secretion.

Recently, the transcription factor 7-like 2 (TCF7L2) gene has been associated with type 2 diabetes in subjects of European origin in the DeCode study. We genotyped the two most associated variants (rs7903146 and rs12255372) in 2,367 French type 2 diabetic subjects and in 2,499 control subjects. Both the T-allele of rs7903146 and the T-allele of rs12255372 significantly increase type 2 diabetes risk with an allelic odds ratio (OR) of 1.69 (95% CI 1.55–1.83) (P = 6.0 × 10−35) and 1.60 (1.47–1.74) (P = 7.6 × 10−28), respectively. In nonobese type 2 diabetic subjects (BMI

Although cross-sectional studies have associated the Pro12Ala polymorphism of PPARG with type 2 diabetes, prospective studies offer more opportunities to investigate genetic variants. Associations between PPARG polymorphisms with insulin resistance parameters and with the 6-year incidence of impaired fasting glucose or type 2 diabetes were tested in 3,914 French Caucasians from the DESIR (Data From an Epidemiological Study on the Insulin Resistance Syndrome) cohort. In subjects normoglycemic at baseline (n = 3,498), the 6-year risk of hyperglycemia was lower in PPARG Ala carriers (odds ratio [OR] vs. ProPro = 0.66 [95% CI 0.44–0.99], P = 0.046 adjusted for sex, age, and BMI). Similar results were found with the PPARG C1431T single nucleotide polymorphism (SNP; adjusted OR = 0.65 [0.44–0.96], P = 0.036). Both alleles are in strong linkage disequilibrium (D′ = 0.669, P < 0.001). The baseline mean fasting insulin and homeostasis model assessment of insulin resistance (HOMA-IR) were lower in Ala carriers compared with ProPro homozygotes (P = 0.001 for both), with smaller increases in mean insulin and HOMA-IR during follow-up (P = 0.007 and 0.018, respectively). No association with insulin levels or HOMA-IR was found with C1431T. In this cohort, the APM1 G-11391A SNP is associated with the development of hyperglycemia. The combined effects of PPARG Pro12Ala and APM1 G-11391A SNPs showed no interaction on the risk of 6-year hyperglycemia. The PPARG Ala allele showed a relatively high protective effect in developing hyperglycemia and hyperinsulinemia during a 6-year period. Cumulative rather than synergistic effects of PPARG Pro12Ala and APM1 SNPs on diabetes risk are suggested.

The plasma concentration of the adipocyte-derived peptide adiponectin is decreased in patients with obesity and type 2 diabetes. The adiponectin gene is located on chromosome 3q27, where a diabetes susceptibility locus has been mapped. Adiponectin gene polymorphisms (single nucleotide polymorphisms [SNPs]) have been associated with BMI, insulin sensitivity, and type 2 diabetes in some cross-sectional studies. Our aim was to assess the contribution of these SNPs in the development of features of the insulin resistance syndrome in a 3-year prospective study in ∼4,500 French Caucasian subjects from the Epidemiologic Data on the Insulin Resistance Syndrome (DESIR) cohort. For subjects who were normoglycemic at baseline, the 3-year risk of becoming hyperglycemic (diabetes or impaired fasting glucose) was affected by two SNPs: G-11391A and T45G. For G-11391A, the risk was increased in GA carriers (odds ratio [OR] adjusted for sex [versus GG] = 1.60 [95% CI 1.16–2.20]; P = 0.004). For T45G, it was increased in GG carriers (OR [versus TT] = 2.71 [1.31–5.60]; P = 0.007). After 3 years, GG subjects had a greater increase in BMI (P = 0.009) and waist-to-hip ratio (P = 0.007). Adiponectin levels at baseline were associated with the development of hyperglycemia (P = 0.005), but the predictive effects on the risk for hyperglycemia were independent of adiponectin genotypes. In conclusion, in the DESIR study, variations at the adiponectin locus affect body weight gain, body fat distribution, and onset of hyperglycemia, as well as adiponectin levels. Adiponectin gene SNPs may have several phenotypic effects that co-occur with the development of the metabolic syndrome.

In the article listed above, reference 1 was erroneously cited as “Villa R, Mandel AL, Jones BD, La Clair JJ, Burkart MD. …

Null mutations in the PCSK1 gene, encoding the proprotein convertase 1/3 (PC1/3), cause recessive monogenic early onset obesity. Frequent coding variants that modestly impair PC1/3 function mildly increase the risk for common obesity. The aim of this study was to determine the contribution of rare functional PCSK1 mutations to obesity. PCSK1 exons were sequenced in 845 nonconsanguineous extremely obese Europeans. Eight novel nonsynonymous PCSK1 mutations were identified, all heterozygous. Seven mutations had a deleterious effect on either the maturation or the enzymatic activity of PC1/3 in cell lines. Of interest, five of these novel mutations, one of the previously described frequent variants (N221D), and the mutation found in an obese mouse model (N222D), affect residues at or near the structural calcium binding site Ca-1. The prevalence of the newly identified mutations was assessed in 6,233 obese and 6,274 lean European adults and children, which showed that carriers of any of these mutations causing partial PCSK1 deficiency had an 8.7-fold higher risk to be obese than wild-type carriers. These results provide the first evidence of an increased risk of obesity in heterozygous carriers of mutations in the PCSK1 gene. Furthermore, mutations causing partial PCSK1 deficiency are present in 0.83% of extreme obesity phenotypes.

Non-insulin-dependent diabetes mellitus (NIDDM) is known to have a strong genetic basis, but the mode of inheritance is still unknown. Recent studies have suggested that maternal inheritance is important; this complicates the transmission pattern of NIDDM. In our study, the familial aggregation of diabetes and the maternal effect were investigated through three generations. The CODIAB Study recruited 536 NIDDM patients between 35 and 74 years of age from 10 diabetes centers in France. Familial aggregation was confirmed: among 218 NIDDM patients, 66% had at least one diabetic relative. Mothers were implicated 2 times more frequently than fathers (P < 0.001). This maternal effect was confirmed because more diabetic cases were noted among maternal than paternal aunts and uncles (P < 0.02). When we considered the next generation, women had more diabetic offspring than men (P < 0.01). Other factors susceptible to modify the familial aggregation were considered. The maternal effect was not significantly related to the patients' ages (P > 0.2). The genetic component was more important when the diagnosis was made earlier, but the maternal effect was homogeneous (P > 0.3). In conclusion, we found a familial aggregation of diabetes that suggests a strong genetic component with a mode of inheritance that may be influenced by a maternal environment.

OBJECTIVE 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). RESEARCH DESIGN AND METHODS 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. RESULTS 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]). CONCLUSIONS 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.

OBJECTIVE 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. RESEARCH DESIGN AND METHODS 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). RESULTS 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. CONCLUSIONS 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.

OBJECTIVE Single nucleotide polymorphisms (SNPs) in intron 1 of fat mass– and obesity-associated gene (FTO) are strongly associated with human adiposity, whereas Fto−/− mice are lean and Fto+/− mice are resistant to diet-induced obesity. We aimed to determine whether FTO mutations are disproportionately represented in lean or obese humans and to use these mutations to understand structure-function relationships within FTO. RESEARCH DESIGN AND METHODS We sequenced all coding exons of FTO in 1,433 severely obese and 1,433 lean individuals. We studied the enzymatic activity of selected nonsynonymous variants. RESULTS We identified 33 heterozygous nonsynonymous variants in lean (2.3%) and 35 in obese (2.4%) individuals, with 8 mutations unique to the obese and 11 unique to the lean. Two novel mutations replace absolutely conserved residues: R322Q in the catalytic domain and R96H in the predicted substrate recognition lid. R322Q was unable to catalyze the conversion of 2-oxoglutarate to succinate in the presence or absence of 3-methylthymidine. R96H retained some basal activity, which was not enhanced by 3-methylthymidine. However, both were found in lean and obese individuals. CONCLUSIONS Heterozygous, loss-of-function mutations in FTO exist but are found in both lean and obese subjects. Although intron 1 SNPs are unequivocally associated with obesity in multiple populations and murine studies strongly suggest that FTO has a role in energy balance, it appears that loss of one functional copy of FTO in humans is compatible with being either lean or obese. Functional analyses of FTO mutations have given novel insights into structure-function relationships in this enzyme.

OBJECTIVE—We performed a comprehensive genetic association study of common variation spanning the IGF2BP2 locus in order to replicate the association of the “confirmed” type 2 diabetes susceptibility variants rs4402960 and rs1470579 in the French Caucasian population and to further characterize the susceptibility variants at this novel locus. RESEARCH DESIGN AND METHODS—We genotyped a total of 21 tagging single nucleotide polymorphisms spanning the IGF2BP2 locus in our type 2 diabetes case-control cohort comprising 3,093 French Caucasian subjects. RESULTS—IGF2BP2 variants rs4402960 and rs1470579 were not associated with type 2 diabetes in the present study (P = 0.632 and P = 0.896, respectively). Meta-analysis of genotype data from over 34,000 subjects demonstrated that our inability to replicate rs4402960/rs1470579 was consistent with the findings from several previous genome-wide association study (GWAS) datasets that were underpowered to detect this modest association signal (odds ratio [OR] 1.14). We obtained novel evidence that rs9826022, a borderline rare variant (5% minor allele frequency) in the 3′ downstream region, was associated with type 2 diabetes (P = 0.0002; OR 1.53 [95% CI 1.22–1.91]). This result was corroborated by the meta-analysis of 10,542 genotypes from the current study and GWAS datasets using both fixed (P = 9.47 × 10−6; 1.30 [1.16–1.46]) and random effects (P = 0.001; 1.30 [1.11–1.52)] calculations. CONCLUSIONS—We were unable to replicate the confirmed rs4402960/rs1470579 susceptibility variants but found novel evidence for a rare variant in the 3′ downstream region of IGF2BP2. Further genetic and functional studies are required to identify the etiological IGF2BP2 variants.

Yang et al. (1) recently reported that insulin usage is associated with a reduced cancer risk. It contrasts with evidence from epidemiological surveys in healthy populations and from pharmaco-epidemiological studies in diabetic patients, suggesting that hyperinsulinemia and growth factors play a key role in the association—maybe causal relationship—between diabetes/hyperglycemia and cancer, as we reviewed recently (2). In the accompanying editorial (3), Johnson and Gale state “pearl of wisdom often taught in introductory epidemiology courses is that one should be wary of implausibly low (or high) …