Data From An Epidemiological Study On The Insulin Resistance Syndrome Research Articles

Jointly Modelling Single Nucleotide Polymorphisms With Longitudinal and Time-to-Event Trait: An Application to Type 2 Diabetes and Fasting Plasma Glucose.

In observational cohorts, longitudinal data are collected with repeated measurements at predetermined time points for many biomarkers, along with other variables measured at baseline. In these cohorts, time until a certain event of interest occurs is reported and very often, a relationship will be observed between some biomarker repeatedly measured over time and that event. Joint models were designed to efficiently estimate statistical parameters describing this relationship by combining a mixed model for the longitudinal biomarker trajectory and a survival model for the time until occurrence of the event, using a set of random effects to account for the relationship between the two types of data. In this paper, we discuss the implementation of joint models in genetic association studies. First, we check model consistency based on different simulation scenarios, by varying sample sizes, minor allele frequencies and number of repeated measurements. Second, using genotypes assayed with the Metabochip DNA arrays (Illumina) from about 4,500 individuals recruited in the French cohort D.E.S.I.R. (Data from an Epidemiological Study on the Insulin Resistance syndrome), we assess the feasibility of implementing the joint modelling approach in a real high-throughput genomic dataset. An alternative model approximating the joint model, called the Two-Step approach (TS), is also presented. Although the joint model shows more precise and less biased estimators than its alternative counterpart, the TS approach results in much reduced computational times, and could thus be used for testing millions of SNPs at the genome-wide scale.

Early metabolic markers identify potential targets for the prevention of type 2 diabetes

Aims/hypothesisThe aims of this study were to evaluate systematically the predictive power of comprehensive metabolomics profiles in predicting the future risk of type 2 diabetes, and to identify a panel of the most predictive metabolic markers.MethodsWe applied an unbiased systems medicine approach to mine metabolite combinations that provide added value in predicting the future incidence of type 2 diabetes beyond known risk factors. We performed mass spectrometry-based targeted, as well as global untargeted, metabolomics, measuring a total of 568 metabolites, in a Finnish cohort of 543 non-diabetic individuals from the Botnia Prospective Study, which included 146 individuals who progressed to type 2 diabetes by the end of a 10 year follow-up period. Multivariate logistic regression was used to assess statistical associations, and regularised least-squares modelling was used to perform machine learning-based risk classification and marker selection. The predictive performance of the machine learning models and marker panels was evaluated using repeated nested cross-validation, and replicated in an independent French cohort of 1044 individuals including 231 participants who progressed to type 2 diabetes during a 9 year follow-up period in the DESIR (Data from an Epidemiological Study on the Insulin Resistance Syndrome) study.ResultsNine metabolites were negatively associated (potentially protective) and 25 were positively associated with progression to type 2 diabetes. Machine learning models based on the entire metabolome predicted progression to type 2 diabetes (area under the receiver operating characteristic curve, AUC = 0.77) significantly better than the reference model based on clinical risk factors alone (AUC = 0.68; DeLong’s p = 0.0009). The panel of metabolic markers selected by the machine learning-based feature selection also significantly improved the predictive performance over the reference model (AUC = 0.78; p = 0.00019; integrated discrimination improvement, IDI = 66.7%). This approach identified novel predictive biomarkers, such as α-tocopherol, bradykinin hydroxyproline, X-12063 and X-13435, which showed added value in predicting progression to type 2 diabetes when combined with known biomarkers such as glucose, mannose and α-hydroxybutyrate and routinely used clinical risk factors.Conclusions/interpretationThis study provides a panel of novel metabolic markers for future efforts aimed at the prevention of type 2 diabetes.

Reassessment of the putative role of BLK-p.A71T loss-of-function mutation in MODY and type 2 diabetes

MODY is believed to be caused by at least 13 different genes. Five rare mutations at the BLK locus, including only one non-synonymous p.A71T variant, were reported to segregate with diabetes in three MODY families. The p.A71T mutation was shown to abolish the enhancing effect of BLK on insulin content and secretion from pancreatic beta cell lines. Here, we reassessed the contribution of BLK to MODY and tested the effect of BLK-p.A71T on type 2 diabetes risk and variations in related traits. BLK was sequenced in 64 unelucidated MODY samples. The BLK-p.A71T variant was genotyped in a French type 2 diabetes case-control study including 4,901 cases and 4,280 controls, and in the DESIR (Data from an Epidemiological Study on the Insulin Resistance Syndrome) and SUVIMAX (Supplementation en Vitamines et Mineraux Antioxydants) population-based cohorts (n = 6,905). The variant effects were assessed by logistic and linear regression models. No rare non-synonymous BLK mutations were found in the MODY patients. The BLK p.A71T mutation was present in 52 normoglycaemic individuals, making it very unlikely that this loss-of-function mutation causes highly penetrant MODY. We found a nominal association between this variant and increased type 2 diabetes risk, with an enrichment of the mutation in the obese diabetic patients, although no significant association with BMI was identified. No mutation in BLK was found in our MODY cohort. From our findings, the BLK-p.A71T mutation may weakly influence type 2 diabetes risk in the context of obesity; however, this will require further validation.

Comment on: Park et al. Association of Serum Ferritin and the Development of Metabolic Syndrome in Middle-Aged Korean Men: A 5-Year Follow-up Study. Diabetes Care 2012;35:2521–2526

We read with great interest the article by Park et al. (1) in Diabetes Care . The results they report in middle-aged Korean men are very similar to ours published in 2007 in Diabetes Care for both sexes from the DESIR (Data from an Epidemiological Study on the Insulin Resistance Syndrome) prospective study in a …

Dietary fat intake and polymorphisms at the PPARG locus modulate BMI and type 2 diabetes risk in the D.E.S.I.R. prospective study

Fat-rich diets are involved in many disorders such as obesity and type 2 diabetes (T2D). The Pro12Ala variant of peroxisome proliferator-activated receptor-γ (PPARγ) is known to modulate body mass index (BMI) and T2D risk. Our aim was to study the interaction effect between PPARγ gene (PPARG) polymorphisms Pro12Ala and 1431C>T and fat intake on incident T2D and BMI in a 9-year prospective cohort drawn from the French general population, the D.E.S.I.R. (Data from an Epidemiological Study on the Insulin Resistance Syndrome) study (n=4676). Nutritional intake was assessed by a food frequency self-questionnaire completed by each participant. Statistical analyses included logistic regression, analysis of covariance and haplotype analysis, with adjustment for confounding variables. A high fat consumption (the third sex-specific tertile of fat intake, as a percentage of energy intake) was associated with an increased T2D risk among ProPro and CC homozygotes (P(interaction)=0.05, odds ratio (OR) (95% confidence interval (95% CI))=1.73 (1.19-2.52) P=0.004 and OR=1.85 (1.27-2.71) P=0.001, respectively) but not in Ala and T carriers. There was a significant interaction effect between Pro12Ala and 1431C>T on BMI (P(interaction)=0.004); Ala was associated with lower BMI in CC homozygotes and with higher BMI in T carriers while the opposite was found for ProPro. There was also an interaction effect between Pro12Ala and dietary fat intake on BMI (P(interaction)=0.02); AlaAla individuals had a higher BMI than Pro carriers among high fat consumers (27.1 ± 1.0 versus 24.9 ± 0.1 for AlaAla and Pro+, respectively). There was no interaction effect between the 1431C>T single-nucleotide polymorphism and fat intake on BMI. Our results indicate strong genetic and nutritional interaction effects on BMI and T2D risk at the PPARG locus in a general population.

Hemoglobin A1c and Fasting Plasma Glucose Levels as Predictors of Retinopathy at 10 Years

To evaluate the predictive values of hemoglobin A(1c) (HbA(1c)) and fasting plasma glucose (FPG) for retinopathy 10 years after the baseline examination. Seven hundred men and women from the DESIR (Data From an Epidemiological Study on the Insulin Resistance Syndrome) Study underwent evaluation for retinopathy using a nonmydriatic digital camera. During the preceding 9 years, 235 had diabetes mellitus (treated or FPG level of ≥126 mg/dL at least once), 227 had an impaired FPG level (110-125 mg/dL) at least once, and 238 always had glucose levels within reference limits (<110 mg/dL). Compared with those without retinopathy, the 44 participants with retinopathy at 10 years had higher baseline mean (SD) levels of FPG (130 [49] vs 106 [22] mg/dL) and HbA(1c) (6.4% [1.6%] vs 5.7% [0.7%]) (both, P<.001). The frequency of retinopathy at 10 years, standardized according to the distribution of glycemia across the entire DESIR population, was 3.6%. In our population, FPG levels of 108 and 116 mg/dL had positive predictive values of 8.4% and 14.0%, respectively, for retinopathy at 10 years; HbA(1c) levels of 6.0% and 6.5% had positive predictive values of 6.0% and 14.8%, respectively. After 10 years of follow-up, retinopathy was equally frequent in participants with impaired FPG levels and in those who became diabetic during the study (8.6% and 6.7%, respectively), lower than in those with diabetes at baseline (13.9%). Because the positive predictive values for retinopathy increase sharply from 108 mg/dL for FPG and from 6.0% for HbA(1c) levels, these thresholds are proposed to identify those at risk of retinopathy 10 years later.

The Common P446L Polymorphism in GCKR Inversely Modulates Fasting Glucose and Triglyceride Levels and Reduces Type 2 Diabetes Risk in the DESIR Prospective General French Population

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.

Impact of Common Type 2 Diabetes Risk Polymorphisms in the DESIR Prospective Study

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. 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). 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 x 10(-5)) and decreased homeostasis model assessment of beta-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 x 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 x 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. 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.

ABCA1 Single Nucleotide Polymorphisms on High‐Density Lipoprotein‐Cholesterol and Overweight: the D.E.S.I.R. Study

The adenosine triphosphate-binding cassette A1 (ABCA1) gene plays a key role in reverse cholesterol transport. Some ABCA1 gene polymorphisms have been associated with high-density lipoprotein-cholesterol (HDL-C) concentrations. The aim of this study was to assess the effect of three polymorphisms, C69T, G378C, and G1051A (R219K), on HDL-C levels and their interaction with BMI in more than 5000 French whites from the D.E.S.I.R. (Data from an Epidemiological Study on the Insulin Resistance syndrome) cohort study. The T allele of the C69T single nucleotide polymorphism (SNP) was associated with higher HDL-C levels in normal-weight men (BMI <25 kg/m(2)). The C allele of the G378C SNP was associated with lower HDL-C in overweight subjects (BMI > or =25 kg/m(2)). For the G1051A SNP, in the normal-weight group, the minor A allele was significantly associated with higher HDL-C levels. In contrast, in overweight people, the minor allele was associated with lower HDL-C levels. After accounting for multiple testing, empiric p values remained significant for the associations between G378C SNP and HDL-C in the overweight group and between G1051A SNP and HDL-C in the normal-weight group. This study suggests that ABCA1 gene polymorphisms modulate HDL-C concentrations, in interaction with BMI, and, thus, they might influence cardiovascular risk in the general population.

TCF7L2 Variation Predicts Hyperglycemia Incidence in a French General Population

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.

The PPARG Pro12Ala Polymorphism Is Associated With a Decreased Risk of Developing Hyperglycemia Over 6 Years and Combines With the Effect of the APM1 G-11391A Single Nucleotide Polymorphism

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.

A pharmacoepidemiological assessment of the effect of statins and fibrates on fibrinogen concentration

Plasma fibrinogen is strongly associated with cardiovascular morbi-mortality. We investigated in the large cohort of the D.E.S.I.R. (data from an epidemiological study on the insulin resistance syndrome) study, the relationship between change in fibrinogen concentration over a 3-year follow-up and fibrate and statin use. Fibrinogen concentrations were higher at baseline among individuals treated with statins ( n=130) compared to those treated with fibrates ( n=251), even after adjustment for confounding factors (including total cholesterol, HDL cholesterol and triglycerides) (mean (S.D.): 2.8 (0.6) vs. 3.1 (0.6), P<0.001). We compared change in fibrinogen concentrations at 3 years of follow-up, between individuals who started fibrate ( n=126) or statin ( n=127) treatment during the follow-up and individuals ( n=3906) who stayed without treatment during this period. After adjustment for baseline fibrinogen level, age, sex and changes in total cholesterol, triglycerides and alcohol intake, fibrinogen concentration decreased after fibrate treatment, while it increased after statin treatment and in those not using lipid lowering drugs (−0.07 (0.54) vs. 0.10 (0.54) vs. 0.08 (0.52) g/l respectively, P=0.01). No differences were observed between different statins or different fibrates. In conclusion, fibrates in contrast with statins may combine lipid-lowering with a beneficial effect on fibrinogen. This effect is independent of changes in cholesterol and triglyceride concentrations.

Microalbuminuria and markers of the atherosclerotic process: the D.E.S.I.R. study

The relationship between microalbuminuria and tissue-type plasminogen activator antigen (tPA-ag) and fibrinogen was evaluated in non-diabetic subjects. Subjects were participants of the D.E.S.I.R. (Data from an Epidemiological Study on the Insulin Resistance syndrome) Study. Analyses were carried out on 2248 women and 2402 men for fibrinogen and on 272 women and 284 men for tPA-ag. Microalbuminuria was defined as urinary albumin concentration greater than 20 mg/l. Men with microalbuminuria had a 6% higher fibrinogen concentration than those without (3.07 g/l (95% confidence interval: 2.99,3.15) vs. 2.89 g/l (2.87,2.91), adjusted for age and smoking). This relationship existed in hypertensive as well as non-hypertensive subjects. The association between microalbuminuria and tPA-ag existed only in hypertensive men, those with microalbuminuria having a 21% higher tPA-ag than those without (4.39 ng/ml (3.70,5.08) vs. 3.63 ng/ml (3.32,3.94), adjusted for age and smoking). Adjustment for other risk markers for cardiovascular disease did not change the results. There was no relationship between microalbuminuria and these haemostatic factors in women. The results of this study suggest that in non-diabetic men, microalbuminuria is associated with fibrinogen, but with tPA-ag only when concomitant with hypertension.

Tissue-Type Plasminogen Activator Antigen and Consumption of Dairy Products. The D.E.S.I.R. Study

We investigated whether tissue-type plasminogen activator antigen (t-PA-Ag) was associated with intake of meat, fish, or dairy products. The study population comprised 295 women and 299 men aged 30–64 years, which was a random sample from the D.E.S.I.R. (Data from an Epidemiological Study on the Insulin Resistance syndrome) study comprising 5214 men and women in total. T-PA-Ag was measured in fasting blood samples and the habitual intake of foods was assessed by several questions on a food frequency questionnaire. Cross-sectional data were analyzed. The mean t-PA-Ag concentration was 3.28 ng/mL (SD, 1.26) in men and 2.52 ng/mL (SD, 1.22) in women. The concentration of t-PA-Ag was inversely associated with the consumption of milk and milk products in women ( p for trend: 0.15) and in men ( p for trend: 0.04). The difference between subjects with a low and a high milk consumption was 13% in women and 19% in men. Similar results were observed for consumption of cheese. The concentration of t-PA-Ag was 21 and 8% lower for women and men with a high cheese consumption, respectively, compared to those with a low consumption. Further analyses showed that the association of t-PA-Ag with milk and milk product consumption was independent of cheese consumption and vice versa. No association between meat or fish intake and t-PA-Ag was observed. The results of this study indicate that, if confirmed by others, a high intake of dairy products may influence fibrinolysis by an effect on t-PA-Ag.

Gender Differences in the Relation between Fibrinogen, Tissue-type Plasminogen Activator Antigen and Markers of Insulin Resistance: Effects of Smoking

A stronger positive association between fibrinogen or tissue-type plasminogen activator antigen (tPA-ag) and fasting insulin is observed in women than in men. We investigated whether this effect could be explained by a difference in smoking habits. The relations between markers for insulin resistance [fasting insulin and insulin resistance as estimated by the homeostasis model assessment (HOMA-IR)] and fibrinogen and tPA-ag were examined cross-sectionally in 4976 (582 for tPA-ag) subjects from the D.E.S.I.R. (Data from an Epidemiological Study on the Insulin Resistance syndrome) study. The modifying effect of smoking habits were evaluated. Seventeen percent of women and 27% of men were smokers. Fibrinogen concentrations were higher in smokers than in non-smokers, in men only. Female smokers had lower concentrations of tPA-ag than non-smokers. In both women and men, fibrinogen was positively associated with fasting insulin [women: beta = 0.33 mg/U (95% confidence interval: 0.29, 0.37); men: beta = 0.15 mg/U (0.11, 0.19)] and with HOMA-IR [women: beta = 0.17 microg/microU mol/l (0.15, 0.19): men: beta = 0.06 (0.04, 0.08)]. For tPA-ag these associations were for insulin beta = 0.76 mg/U (0.54, 0.98) and beta = 0.89 mg/U (0.67, 1.11), and for HOMA-IR beta = 0.47 microg/microU mol/l (0.33, 0.61) and beta = 0.45 microg/microU mol/l (0.33, 0.57), women and men respectively. The associations of fibrinogen and tPA-ag with insulin and HOMA-IR were sharply reduced in male smokers compared to male non-smokers, however the strength of the associations in male non-smokers did not reach that in women. Fibrinogen and tPA-ag are independently related with markers of insulin resistance, with the relation with fibrinogen being stronger in women than in men. The strong modifying effect of smoking habits does not completely explain this gender difference.