Showing papers by "Jose C. Florez published in 2008"

Genotype Score in Addition to Common Risk Factors for Prediction of Type 2 Diabetes

Abstract: Background Multiple genetic loci have been convincingly associated with the risk of type 2 diabetes mellitus. We tested the hypothesis that knowledge of these loci allows better prediction of risk than knowledge of common phenotypic risk factors alone. Methods We genotyped single-nucleotide polymorphisms (SNPs) at 18 loci associated with diabetes in 2377 participants of the Framingham Offspring Study. We created a genotype score from the number of risk alleles and used logistic regression to generate C statistics indicating the extent to which the genotype score can discriminate the risk of diabetes when used alone and in addition to clinical risk factors. Results There were 255 new cases of diabetes during 28 years of follow-up. The mean (±SD) genotype score was 17.7±2.7 among subjects in whom diabetes developed and 17.1±2.6 among those in whom diabetes did not develop (P<0.001). The sex-adjusted odds ratio for diabetes was 1.12 per risk allele (95% confidence interval, 1.07 to 1.17). The C statistic was 0.534 without the genotype score and 0.581 with the score (P = 0.01). In a model adjusted for sex and self-reported family history of diabetes, the C statistic was 0.595 without the genotype score and 0.615 with the score (P = 0.11). In a model adjusted for age, sex, family history, body-mass index, fasting glucose level, systolic blood pressure, high-density lipoprotein cholesterol level, and triglyceride level, the C statistic was 0.900 without the genotype score and 0.901 with the score (P = 0.49). The genotype score resulted in the appropriate risk reclassification of, at most, 4% of the subjects. Conclusions A genotype score based on 18 risk alleles predicted new cases of diabetes in the community but provided only a slightly better prediction of risk than knowledge of common risk factors alone.

Newly identified loci highlight beta cell dysfunction as a key cause of type 2 diabetes: where are the insulin resistance genes?

Abstract: Although type 2 diabetes has been traditionally understood as a metabolic disorder initiated by insulin resistance, it has recently become apparent that an impairment in insulin secretion contributes to its manifestation and may play a prominent role in its early pathophysiology. The genetic dissection of Mendelian and, more recently, polygenic types of diabetes confirms the notion that primary defects in insulin synthesis, processing and/or secretion often give rise to the common form of this disorder. This concept, first advanced with the discovery and physiological characterisation of various genetic subtypes of MODY, has been extended to other forms of monogenic diabetes (e.g. neonatal diabetes). It has also led to the identification of common risk variants via candidate gene approaches (e.g. the E23K polymorphism in KCNJ11 or common variants in the MODY genes), and it has been validated by the description of the robust physiological effects conferred by polymorphisms in the TCF7L2 gene. More recently, the completion and integration of genome-wide association scans for this disease has uncovered a number of heretofore unsuspected variants, several of which also affect insulin secretion. This review provides an up-to-date account of genetic loci that influence risk of common type 2 diabetes via impairment of beta cell function, outlines their presumed mechanisms of action, and places them in the context of gene-gene and/or gene-environment interactions. Finally, a strategy for the analogous discovery of insulin resistance genes is proposed.

The prevention of type 2 diabetes.

Abstract: Type 2 diabetes mellitus (T2DM) affects more than 7% of adults in the US and leads to substantial personal and economic burden. In prediabetic states insulin secretion and action--potential targets of preventive interventions--are impaired. In trials lifestyle modification (i.e. weight loss and exercise) has proven effective in preventing incident T2DM in high-risk groups, although weight loss has the greatest effect. Various medications (e.g. metformin, thiazolidinediones and acarbose) can also prevent or delay T2DM. Whether diabetes-prevention strategies also ultimately prevent the development of diabetic vascular complications is unknown, but cardiovascular risk factors are favorably affected. Preventive strategies that can be implemented in routine clinical settings have been developed and evaluated. Widespread application has, however, been limited by local financial considerations, even though cost-effectiveness might be achieved at the population level.

Common variants in the adiponectin gene (ADIPOQ) associated with plasma adiponectin levels, type 2 diabetes, and diabetes-related quantitative traits: the Framingham Offspring Study.

Abstract: OBJECTIVE— Variants in ADIPOQ have been inconsistently associated with adiponectin levels or diabetes. Using comprehensive linkage disequilibrium mapping, we genotyped single nucleotide polymorphisms (SNPs) in ADIPOQ to evaluate the association of common variants with adiponectin levels and risk of diabetes. RESEARCH DESIGN AND METHODS— Participants in the Framingham Offspring Study ( n = 2,543, 53% women) were measured for glycemic phenotypes and incident diabetes over 28 years of follow-up; adiponectin levels were quantified at exam 7. We genotyped 22 tag SNPs that captured common (minor allele frequency >0.05) variation at r 2 > 0.8 across ADIPOQ plus 20 kb 5′ and 10 kb 3′ of the gene. We used linear mixed effects models to test additive associations of each SNP with adiponectin levels and glycemic phenotypes. Hazard ratios (HRs) for incident diabetes were estimated using an adjusted Cox proportional hazards model. RESULTS— Two promoter SNPs in strong linkage disequilibrium with each other ( r 2 = 0.80) were associated with adiponectin levels (rs17300539; P nominal [ P n ] = 2.6 × 10 −8 ; P empiric [ P e ] = 0.0005 and rs822387; P n = 3.8 × 10 −5 ; P e = 0.001). A 3′-untranslated region (3′UTR) SNP (rs6773957) was associated with adiponectin levels ( P n = 4.4 × 10 −4 ; P e = 0.005). A nonsynonymous coding SNP (rs17366743, Y111H) was confirmed to be associated with diabetes incidence (HR 1.94 [95% CI 1.16–3.25] for the minor C allele; P n = 0.01) and with higher mean fasting glucose over 28 years of follow-up ( P n = 0.0004; P e = 0.004). No other significant associations were found with other adiposity and metabolic phenotypes. CONCLUSIONS— Adiponectin levels are associated with SNPs in two different regulatory regions (5′ promoter and 3′UTR), whereas diabetes incidence and time-averaged fasting glucose are associated with a missense SNP of ADIPOQ .

The Genetics of Type 2 Diabetes: A Realistic Appraisal in 2008

Abstract: Context: Over the last few months, genome-wide association studies have contributed significantly to our understanding of the genetic architecture of type 2 diabetes. If and how this information will impact clinical practice is not yet clear. Evidence Acquisition: Primary papers reporting genome-wide association studies in type 2 diabetes or establishing a reproducible association for specific candidate genes were compiled. Further information was obtained from background articles, authoritative reviews, and relevant meeting conferences and abstracts. Evidence Synthesis: As many as 17 genetic loci have been convincingly associated with type 2 diabetes; 14 of these were not previously known, and most of them were unsuspected. The associated polymorphisms are common in populations of European descent but have modest effects on risk. These loci highlight new areas for biological exploration and allow the initiation of experiments designed to develop prediction models and test possible pharmacogenetic and other applications. Conclusions: Although substantial progress in our knowledge of the genetic basis of type 2 diabetes is taking place, these new discoveries represent but a small proportion of the genetic variation underlying the susceptibility to this disorder. Major work is still required to identify the causal variants, test their role in disease prediction and ascertain their therapeutic implications.

A genetic link between type 2 diabetes and prostate cancer.

Abstract: Epidemiological studies suggest that men with type 2 diabetes are less likely than non-diabetic men to develop prostate cancer. The cause of this association is not known. Recent genetic studies have highlighted a potential genetic link between the two diseases. Two studies have identified a version (allele) of a variant in the HNF1B (also known as TCF2) gene that predisposes to type 2 diabetes, and one of them showed that the same allele protects men from prostate cancer. Other, separate, studies have identified different variants in the JAZF1 gene, one associated with type 2 diabetes, another associated with prostate cancer. These findings are unlikely to completely explain the epidemiological association between the two diseases but they provide new insight into a possible direct causal link, rather than one that is confounded or biased in some way.

The ENPP1 K121Q polymorphism is associated with type 2 diabetes in European populations: evidence from an updated meta-analysis in 42,042 subjects.

Abstract: OBJECTIVE— Functional studies suggest that the nonsynonymous K121Q polymorphism in the ectoenzyme nucleotide pyrophosphate phosphodiesterase 1 (ENPP1) may confer susceptibility to insulin resistance; genetic evidence on its effect on type 2 diabetes, however, has been conflicting. We therefore conducted a new meta-analysis that includes novel unpublished data from the ENPP1 Consortium and recent negative findings from large association studies to address the contribution of K121Q to type 2 diabetes. RESEARCH DESIGN AND METHODS— After a systematic review of the literature, we evaluated the effect of ENPP1 K121Q on diabetes risk under three genetic models using a random-effects approach. Our primary analysis consisted of 30 studies comprising 15,801 case and 26,241 control subjects. Due to considerable heterogeneity and large differences in allele frequencies across populations, we limited our meta-analysis to those of self-reported European descent and, when available, included BMI as a covariate. RESULTS— We found a modest increase in risk of type 2 diabetes for QQ homozygotes in white populations (combined odds ratio [OR] 1.38 [95% CI 1.10–1.74], P = 0.005). There was no evidence of publication bias, but we noted significant residual heterogeneity among studies ( P = 0.02). On meta-regression, 16% of the effect was accounted for by the mean BMI of control subjects. This association was stronger in studies in which control subjects were leaner but disappeared after adjustment for mean control BMI (combined OR 0.93 [95% CI 0.75–1.15], P = 0.50). CONCLUSIONS— The ENPP1 Q121 variant increases risk of type 2 diabetes under a recessive model of inheritance in whites, an effect that appears to be modulated by BMI.

Extension of Type 2 Diabetes Genome-Wide Association Scan Results in the Diabetes Prevention Program

Abstract: OBJECTIVE: Genome-wide association scans (GWASs) have identified novel diabetes-associated genes. We evaluated how these variants impact diabetes incidence, quantitative glycemic traits, and respon ...

Assessing gene-treatment interactions at the FTO and INSIG2 loci on obesity-related traits in the Diabetes Prevention Program.

Abstract: Aims/hypothesis The single nucleotide polymorphism (SNP) rs9939609 in the fat mass and obesity associated gene (FTO) and the rs7566605 SNP located 10 kb upstream of the insulin-induced gene 2 gene (INSIG2) have been proposed as risk factors for common obesity.

Testing of diabetes-associated WFS1 polymorphisms in the Diabetes Prevention Program

Abstract: Aims/hypothesis Wolfram syndrome (diabetes insipidus, diabetes mellitus, optic atrophy and deafness) is caused by mutations in the WFS1 gene. Recently, single nucleotide polymorphisms (SNPs) in WFS1 have been reproducibly associated with type 2 diabetes. We therefore examined the effects of these variants on diabetes incidence and response to interventions in the Diabetes Prevention Program (DPP), in which a lifestyle intervention or metformin treatment was compared with placebo.

TCF7L2 Variants Associate with CKD Progression and Renal Function in Population-Based Cohorts

Abstract: Genetic variants may increase susceptibility to both diabetes and kidney disease. Whether known diabetes-associated variants in the transcription factor 7-like 2 (TCF7L2) gene are associated with chronic kidney disease (CKD) progression and markers of kidney function is unknown. Participants of the Atherosclerosis Risk in Communities Study (ARIC; n = 11,061 self-identified white and n = 4014 black), Framingham Heart Offspring Cohort (FHS; n = 2468), and Heredity and Phenotype Intervention Heart Study (HAPI; n = 861) were genotyped at five (ARIC) and two (FHS) common TCF7L2 variants. The diabetes-conferring risk alleles at rs7903146 and rs7901695 were significantly associated with CKD progression among ARIC participants overall and among those without baseline diabetes. The overall adjusted hazard ratios per rs7903146 T allele were 1.17 (95% confidence interval [CI] 1.04 to 1.32) for white individuals and 1.20 (95% CI 1.03 to 1.41) for black individuals. Similarly, the overall hazard ratios per rs7901695 C allele were 1.19 (95% CI 1.06 to 1.34) for white individuals and 1.27 (95% CI 1.09 to 1.48) for black individuals. The FHS cohort supported these results: The rs7903146 T allele was significantly associated with lower estimated GFR (P = 0.01) and higher cystatin C (P = 0.004) in adjusted analyses overall and among those without diabetes. In the HAPI cohort, the rs7901695 C allele was significantly associated with lower estimated GFR in adjusted analyses (P = 0.049), as were several variants upstream and downstream of TCF7L2 (P < 0.003). No identified variant in the ARIC or FHS cohorts was associated with albuminuria. In conclusion, several population-based samples suggest that variants in the TCF7L2 gene are associated with reduced kidney function or CKD progression, overall and specifically among participants without diabetes.

Genetic susceptibility to type 2 diabetes and implications for antidiabetic therapy.

Abstract: Despite major advances in our knowledge of glycemic pathophysiology and the availability of multiple therapeutic options to confront type 2 diabetes, unraveling the complex link between genetic risk and environmental factors in this burgeoning epidemic has proven difficult. Linkage approaches have clarified the etiology of monogenic diabetic syndromes and congenital lipodystrophies, and candidate gene association studies have identified a number of common variants implicated in type 2 diabetes. This year we have witnessed the advent of genome-wide association scanning: As many as nine genetic loci have now been reproducibly associated with type 2 diabetes in five genome-wide scans. Of particular interest are preliminary explorations of the connections between genetic risk and pharmacologic response. An improved understanding of genetic mechanisms should allow us to test whether behavioral or pharmacologic therapies can be tailored and thus the tremendous disease burden inflicted by type 2 diabetes alleviated.

Haplotype structure of the ENPP1 Gene and Nominal Association of the K121Q missense single nucleotide polymorphism with glycemic traits in the Framingham Heart Study.

Abstract: OBJECTIVE—A recent meta-analysis demonstrated a nominal association of the ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) K→Q missense single nucleotide polymorphism (SNP) at position 121 with type 2 diabetes. We set out to confirm the association of ENPP1 K121Q with hyperglycemia, expand this association to insulin resistance traits, and determine whether the association stems from K121Q or another variant in linkage disequilibrium with it. RESEARCH DESIGN AND METHODS—We characterized the haplotype structure of ENPP1 and selected 39 tag SNPs that captured 96% of common variation in the region (minor allele frequency ≥5%) with an r2 value ≥0.80. We genotyped the SNPs in 2,511 Framingham Heart Study participants and used age- and sex-adjusted linear mixed effects (LME) models to test for association with quantitative metabolic traits. We also examined whether interaction between K121Q and BMI affected glycemic trait levels. RESULTS—The Q allele of K121Q (rs1044498) was associated with increased fasting plasma glucose (FPG), A1C, fasting insulin, and insulin resistance by homeostasis model assessment (HOMA-IR; all P = 0.01–0.006). Two noncoding SNPs (rs7775386 and rs7773477) demonstrated similar associations, but LME models indicated that their effects were not independent from K121Q. We found no association of K121Q with obesity, but interaction models suggested that the effect of the Q allele on FPG and HOMA-IR was stronger in those with a higher BMI (P = 0.008 and 0.01 for interaction, respectively). CONCLUSIONS—The Q allele of ENPP1 K121Q is associated with hyperglycemia and insulin resistance in whites. We found an adiposity-SNP interaction, with a stronger association of K121Q with diabetes-related quantitative traits in people with a higher BMI.

Ordered stratification to reduce heterogeneity in linkage to diabetes-related quantitative traits.

Abstract: Phenotypic heterogeneity complicates detection of genomic loci predisposing to type 2 diabetes, potentially obscuring or unmasking specific loci. We conducted ordered-subsets linkage analyses (OSAs) for diabetes-related quantitative traits (fasting insulin and glucose, hemoglobin A1c (HbA1c), and 28-year-time-averaged fasting plasma glucose (FPG)) from 330 families of the Framingham Offspring Study. We calculated mean BMI, waist circumference (WC), and a diabetes "age-of-onset score" for each family. We constructed subsets by adding one family at a time in increasing (lean family to obese) or decreasing (obese to lean) adiposity order, or increasing or decreasing propensity to develop diabetes at a younger age, with the OSA LOD reported as the maximum LOD observed in any subset. Permutation P values tested the hypothesis that phenotypic ordering showed stronger linkage than random ordering. On chromosome 1, ordering by increasing family mean WC increased linkage to time-averaged FPG at 256 cM from LOD = 2.4 to 3.5 (permuted P = 0.02) and to HbA1c at 180 cM from LOD = 2.0 to 3.3 (P = 0.01). On chromosome 19, ordering by decreasing WC increased linkage to fasting insulin at 68 cM from LOD = 2.7 to 4.6 (P = 0.002), and ordering by decreasing propensity to develop diabetes at a young age increased linkage to fasting insulin at 73 cM from LOD = 2.7 to 4.0 (P = 0.046). We conclude that chromosomes 1 and 19 could harbor adiposity-interacting diabetes susceptibility genes. Such interactions might also influence trait-locus associations and may be useful to consider in diabetes genome-wide association studies.