Genotype score in addition to common risk factors for prediction of type 2 diabetes.

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.

The association of ENPP1 K121Q with diabetes incidence is abolished by lifestyle modification in the diabetes prevention program.

CONTEXT: Insulin resistance is an important feature of type 2 diabetes. Ectoenzyme nucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) inhibits insulin signaling, and a recent meta-analysis reported a nominal association between the Q allele in the K121Q (rs1044498) single nucleotide polymorphism in its gene ENPP1 and type 2 diabetes. OBJECTIVE AND INTERVENTION: We examined the impact of this polymorphism on diabetes incidence as well as insulin secretion and sensitivity at baseline and after treatment with a lifestyle intervention or metformin vs. placebo in the Diabetes Prevention Program (DPP). DESIGN, SETTING, PARTICIPANTS, AND OUTCOME: We genotyped ENPP1 K121Q in 3548 DPP participants and performed Cox regression analyses using genotype, intervention, and interactions as predictors of diabetes incidence. RESULTS: Fasting glucose and glycated hemoglobin were higher in QQ homozygotes at baseline (P < 0.001 for both). There was a significant interaction between genotype at rs1044498 and intervention under the dominant model (P = 0.03). In analyses stratified by treatment arm, a positive association with diabetes incidence was found in Q allele carriers compared to KK homozygotes [hazard ratio (HR), 1.38; 95% confidence interval (CI), 1.08-1.76; P = 0.009] in the placebo arm (n = 996). Lifestyle modification eliminated this increased risk. These findings persisted after adjustment for body mass index and race/ethnicity. Association of ENPP1 K121Q genotype with diabetes incidence under the additive and recessive genetic models showed consistent trends [HR, 1.10 (95% CI, 0.99-1.23), P = 0.08; and HR, 1.16 (95% CI, 0.92-1.45), P = 0.20, respectively] but did not reach statistical significance. CONCLUSIONS: ENPP1 K121Q is associated with increased diabetes incidence; the DPP lifestyle intervention eliminates this increased risk.

Variation in Maturity-Onset Diabetes of the Young Genes Influence Response to Interventions for Diabetes Prevention.

Context: Variation in genes that cause maturity-onset diabetes of the young (MODY) has been associated with diabetes incidence and glycemic traits. Objectives: This study aimed to determine whether genetic variation in MODY genes leads to differential responses to insulin-sensitizing interventions. Design and Setting: This was a secondary analysis of a multicenter, randomized clinical trial, the Diabetes Prevention Program (DPP), involving 27 US academic institutions. We genotyped 22 missense and 221 common variants in the MODY-causing genes in the participants in the DPP. Participants and Interventions: The study included 2806 genotyped DPP participants randomized to receive intensive lifestyle intervention (n = 935), metformin (n = 927), or placebo (n = 944). Main Outcome Measures: Association of MODY genetic variants with diabetes incidence at a median of 3 years and measures of 1-year ß-cell function, insulinogenic index, and oral disposition index. Analyses were stratified by treatment group for significant single-nucleotide polymorphism × treatment interaction (Pint < 0.05). Sequence kernel association tests examined the association between an aggregate of rare missense variants and insulinogenic traits. Results: After 1 year, the minor allele of rs3212185 (HNF4A) was associated with improved ß-cell function in the metformin and lifestyle groups but not the placebo group; the minor allele of rs6719578 (NEUROD1) was associated with an increase in insulin secretion in the metformin group but not in the placebo and lifestyle groups. Conclusions: These results provide evidence that genetic variation among MODY genes may influence response to insulin-sensitizing interventions.

The influence of rare genetic variation in SLC30A8 on diabetes incidence and ß-cell function.

CONTEXT/OBJECTIVE: The variant rs13266634 in SLC30A8, encoding a ß-cell-specific zinc transporter, is associated with type 2 diabetes. We aimed to identify other variants in SLC30A8 that increase diabetes risk and impair ß-cell function, and test whether zinc intake modifies this risk. DESIGN/OUTCOME: We sequenced exons in SLC30A8 in 380 Diabetes Prevention Program (DPP) participants and identified 44 novel variants, which were genotyped in 3445 DPP participants and tested for association with diabetes incidence and measures of insulin secretion and processing. We examined individual common variants and used gene burden tests to test 39 rare variants in aggregate. RESULTS: We detected a near-nominal association between a rare-variant genotype risk score and diabetes risk. Five common variants were associated with the oral disposition index. Various methods aggregating rare variants demonstrated associations with changes in oral disposition index and insulinogenic index during year 1 of follow-up. We did not find a clear interaction of zinc intake with genotype on diabetes incidence. CONCLUSIONS: Individual common and an aggregate of rare genetic variation in SLC30A8 are associated with measures of ß-cell function in the DPP. Exploring rare variation may complement ongoing efforts to uncover the genetic influences that underlie complex diseases.

Effects of genetic variants previously associated with fasting glucose and insulin in the Diabetes Prevention Program.

Common genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies) in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes Prevention Program participants. We analyzed variants for association with baseline glycemic traits, incident diabetes and their interaction with response to metformin or lifestyle intervention. We replicated associations with fasting glucose at MTNR1B (P<0.001), G6PC2 (P = 0.002) and GCKR (P = 0.001). We noted impaired ß-cell function in carriers of glucose-raising alleles at MTNR1B (P<0.001), and an increase in the insulinogenic index for the glucose-raising allele at G6PC2 (P<0.001). The association of MTNR1B with fasting glucose and impaired ß-cell function persisted at 1 year despite adjustment for the baseline trait, indicating a sustained deleterious effect at this locus. We also replicated the association of MADD with fasting proinsulin levels (P<0.001). We detected no significant impact of these variants on diabetes incidence or interaction with preventive interventions. The association of several polymorphisms with quantitative glycemic traits is replicated in a cohort of high-risk persons. These variants do not have a detectable impact on diabetes incidence or response to metformin or lifestyle modification in the Diabetes Prevention Program.

Association testing of previously reported variants in a large case-control meta-analysis of diabetic nephropathy.

We formed the GEnetics of Nephropathy-an International Effort (GENIE) consortium to examine previously reported genetic associations with diabetic nephropathy (DN) in type 1 diabetes. GENIE consists of 6,366 similarly ascertained participants of European ancestry with type 1 diabetes, with and without DN, from the All Ireland-Warren 3-Genetics of Kidneys in Diabetes U.K. and Republic of Ireland (U.K.-R.O.I.) collection and the Finnish Diabetic Nephropathy Study (FinnDiane), combined with reanalyzed data from the Genetics of Kidneys in Diabetes U.S. Study (U.S. GoKinD). We found little evidence for the association of the EPO promoter polymorphism, rs161740, with the combined phenotype of proliferative retinopathy and end-stage renal disease in U.K.-R.O.I. (odds ratio [OR] 1.14, P = 0.19) or FinnDiane (OR 1.06, P = 0.60). However, a fixed-effects meta-analysis that included the previously reported cohorts retained a genome-wide significant association with that phenotype (OR 1.31, P = 2 × 10(-9)). An expanded investigation of the ELMO1 locus and genetic regions reported to be associated with DN in the U.S. GoKinD yielded only nominal statistical significance for these loci. Finally, top candidates identified in a recent meta-analysis failed to reach genome-wide significance. In conclusion, we were unable to replicate most of the previously reported genetic associations for DN, and significance for the EPO promoter association was attenuated.

Triglyceride response to an intensive lifestyle intervention is enhanced in carriers of the GCKR Pro446Leu polymorphism.

CONTEXT: Glucokinase regulatory protein (GCKR) regulates the trafficking and enzymatic activity of hepatic glucokinase, the rate-limiting enzyme in glycogen synthesis and glycolysis. The intronic single-nucleotide polymorphism (SNP) rs780094 (intron 16) and the missense SNP rs1260326 (P446L) in the GCKR gene are strongly associated with increased circulating triglyceride and C-reactive protein levels and, paradoxically, reductions in diabetes incidence, fasting glucose levels, and insulin resistance. OBJECTIVE, SETTING, AND PATIENTS: We sought to replicate these associations and evaluate interactions with lifestyle and metformin interventions in the multiethnic Diabetes Prevention Program (DPP). INTERVENTIONS AND MAIN OUTCOME MEASURES: We genotyped the two GCKR SNP in 3346 DPP participants and evaluated association with progression to diabetes and both baseline levels and changes in triglycerides, homeostasis model assessment of insulin resistance (HOMA-IR), oral disposition index, and inflammatory markers along with their interactions with DPP interventions. RESULTS: GCKR variation did not predict development of type 2 diabetes. At baseline, the 446L allele was associated with higher triglyceride and C-reactive protein levels (both P < 0.0001) and lower fasting glucose (P = 0.001) and HOMA-IR (P = 0.06). The lifestyle intervention was associated with a decrease in magnitude of the effect of the 446L allele on triglyceride levels (interaction P = 0.04). Metformin was more effective in reducing HOMA-IR in carriers of the P446 allele (interaction P = 0.05). CONCLUSIONS: Intensive lifestyle intervention appears to partially mitigate the effect of the 446L allele on higher triglycerides, whereas the P446 allele appears to enhance responsiveness to the HOMA-IR-lowering effect of metformin.

Variants at the endocannabinoid receptor CB1 gene (CNR1) and insulin sensitivity, type 2 diabetes, and coronary heart disease.

Inhibition of the endocannabinoid receptor CB1 improves insulin sensitivity, lowers glycemia, and slows atherosclerosis. We analyzed whether common variants in the gene encoding CB1, CNR1, are associated with insulin resistance, risk of type 2 diabetes (T2D) or coronary heart disease (CHD). We studied 2,411 participants of the Framingham Offspring Study (mean age 60 years, 52% women) for quantitative traits and CHD, and the Framingham SHARe database for T2D risk. We genotyped 19 single-nucleotide polymorphisms (SNPs) that tagged 85% (at r(2) = 0.8) of common (>5%) CNR1 SNPs. Fasting blood glucose and insulin at the 7th (1999-2001) exam were collected. We used age-, sex-, BMI-adjusted models to test additive associations of genotype with homeostasis model assessment of insulin resistance (HOMA(IR)) (linear mixed-effect models), T2D, or CHD. To account for multiple tests of SNPs, we generated empirical P values. The C allele at SNP rs806365 (frequency, 57.4%), ~4.1 kb 3' from CNR1, was associated with increased HOMA(IR) (n = 2,261, ß = 0.05 per C, empirical P = 0.01), risk of T2D (674 cases, odds ratio = 1.19 per C, nominal P = 0.01) and CHD (237 cases, hazard ratio = 1.23 per C, nominal P = 0.04). The association of rs806365 with HOMA(IR) was replicated in a meta-analysis of two independent cohorts (National Health and Nutrition Examination Survey III genetic cohort (NHANES-III) plus Partners Case-Control Diabetes Study; 2,540 white individuals, ß = 0.037, nominal P = 0.007), but not in the large Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) Consortium (n = 29,248, nominal P = 0.74). The association of rs806365 was not replicated either with T2D in Diabetes Genetics Replication and Meta-analysis (DIAGRAM) (n = 10,128, nominal P = 0.31), or with CHD in PROCARDIS (n = 13,614, nominal P = 0.37). Although supported by initial results, we found no reproducible statistical association of common variation at CNR1 with insulin resistance, T2D, or CHD.

Updated genetic score based on 34 confirmed type 2 diabetes Loci is associated with diabetes incidence and regression to normoglycemia in the diabetes prevention program.

OBJECTIVE: Over 30 loci have been associated with risk of type 2 diabetes at genome-wide statistical significance. Genetic risk scores (GRSs) developed from these loci predict diabetes in the general population. We tested if a GRS based on an updated list of 34 type 2 diabetes-associated loci predicted progression to diabetes or regression toward normal glucose regulation (NGR) in the Diabetes Prevention Program (DPP). RESEARCH DESIGN AND METHODS: We genotyped 34 type 2 diabetes-associated variants in 2,843 DPP participants at high risk of type 2 diabetes from five ethnic groups representative of the U.S. population, who had been randomized to placebo, metformin, or lifestyle intervention. We built a GRS by weighting each risk allele by its reported effect size on type 2 diabetes risk and summing these values. We tested its ability to predict diabetes incidence or regression to NGR in models adjusted for age, sex, ethnicity, waist circumference, and treatment assignment. RESULTS: In multivariate-adjusted models, the GRS was significantly associated with increased risk of progression to diabetes (hazard ratio [HR] = 1.02 per risk allele [95% CI 1.00-1.05]; P = 0.03) and a lower probability of regression to NGR (HR = 0.95 per risk allele [95% CI 0.93-0.98]; P < 0.0001). At baseline, a higher GRS was associated with a lower insulinogenic index (P < 0.001), confirming an impairment in ß-cell function. We detected no significant interaction between GRS and treatment, but the lifestyle intervention was effective in the highest quartile of GRS (P < 0.0001). CONCLUSIONS: A high GRS is associated with increased risk of developing diabetes and lower probability of returning to NGR in high-risk individuals, but a lifestyle intervention attenuates this risk.

Hip geometry variation is associated with bone mineralization pathway gene variants: The Framingham Study.

Mineralization of bone matrix is an important process in bone formation; thus defects in mineralization have been implicated in bone mineral density (BMD) and bone structure alterations. Three central regulators of phosphate balance, ALPL, ANKH, and ENPP1, are central in the matrix mineralization process; therefore, the genes encoding them are considered important candidates genes for BMD and bone geometry. To test for an association between these three candidate genes and BMD and bone geometry traits, 124 informative singlenucleotide polymorphisms (SNPs) were selected and genotyped in 1513 unrelated subjects from the Framingham offspring cohort. Initial results showed that SNP rs1974201 in the gene ENPP1 was a susceptibility variant associated with several hip geometric indices, with the strongest p value of 3.8 × 10(7) being observed for femoral neck width. A few modest associations were observed between SNPs in or near ALPL and several bone traits, but no association was observed with ANKH. The association signals observed for SNPs around rs1974201 were attenuated after conditional analysis on rs1974201. Transcription factor binding-site prediction revealed that the HOXA7 binding site was present in the reference sequence with the major allele, whereas this potential binding site is lost in the sequence with the minor allele of rs1974201. In conclusion, we found evidence for association of bone geometry variation with an SNP in ENPP1, a gene in the mineralization pathway. The alteration of a binding site of the deregulator of extracellular matrix HOXA7 warrants further investigation.

Common variants in 40 genes assessed for diabetes incidence and response to metformin and lifestyle intervention in the diabetes prevention program.

OBJECTIVE: Genome-wide association studies have begun to elucidate the genetic architecture of type 2 diabetes. We examined whether single nucleotide polymorphisms (SNPs) identified through targeted complementary approaches affect diabetes incidence in the at-risk population of the Diabetes Prevention Program (DPP) and whether they influence a response to preventive interventions. RESEARCH DESIGN AND METHODS: We selected SNPs identified by prior genome-wide association studies for type 2 diabetes and related traits, or capturing common variation in 40 candidate genes previously associated with type 2 diabetes, implicated in monogenic diabetes, encoding type 2 diabetes drug targets or drug-metabolizing/transporting enzymes, or involved in relevant physiological processes. We analyzed 1,590 SNPs for association with incident diabetes and their interaction with response to metformin or lifestyle interventions in 2,994 DPP participants. We controlled for multiple hypothesis testing by assessing false discovery rates. RESULTS: We replicated the association of variants in the metformin transporter gene SLC47A1 with metformin response and detected nominal interactions in the AMP kinase (AMPK) gene STK11, the AMPK subunit genes PRKAA1 and PRKAA2, and a missense SNP in SLC22A1, which encodes another metformin transporter. The most significant association with diabetes incidence occurred in the AMPK subunit gene PRKAG2 (hazard ratio 1.24, 95% CI 1.09-1.40, P = 7 × 10(-4)). Overall, there were nominal associations with diabetes incidence at 85 SNPs and nominal interactions with the metformin and lifestyle interventions at 91 and 69 mostly nonoverlapping SNPs, respectively. The lowest P values were consistent with experiment-wide 33% false discovery rates. CONCLUSIONS: We have identified potential genetic determinants of metformin response. These results merit confirmation in independent samples.

Association of variants in RETN with plasma resistin levels and diabetes-related traits in the Framingham Offspring Study.

OBJECTIVE: The RETN gene encodes the adipokine resistin. Associations of RETN with plasma resistin levels, type 2 diabetes, and related metabolic traits have been inconsistent. Using comprehensive linkage disequilibrium mapping, we genotyped tag single nucleotide polymorphisms (SNPs) in RETN and tested associations with plasma resistin levels, risk of diabetes, and glycemic traits. RESEARCH DESIGN AND METHODS: We examined 2,531 Framingham Offspring Study participants for resistin levels, glycemic phenotypes, and incident diabetes over 28 years of follow-up. We genotyped 21 tag SNPs that capture common (minor allele frequency >0.05) or previously reported SNPs at r2 > 0.8 across RETN and its flanking regions. We used sex- and age-adjusted linear mixed-effects models (with/without BMI adjustment) to test additive associations of SNPs with traits, adjusted Cox proportional hazards models accounting for relatedness for incident diabetes, and generated empirical P values (Pe) to control for type 1 error. RESULTS: Four tag SNPs (rs1477341, rs4804765, rs1423096, and rs10401670) on the 3' side of RETN were strongly associated with resistin levels (all minor alleles associated with higher levels, Pe<0.05 after multiple testing correction). rs10401670 was also associated with fasting plasma glucose (Pe = 0.02, BMI adjusted) and mean glucose over follow-up (Pe = 0.01; BMI adjusted). No significant association was observed for adiposity traits. On meta-analysis, the previously reported association of SNP -420C/G (rs1862513) with resistin levels remained significant (P = 0.0009) but with high heterogeneity across studies (P < 0.0001). CONCLUSIONS: SNPs in the 3' region of RETN are associated with resistin levels, and one of them is also associated with glucose levels, although replication is needed.

Variants in the CNR1 and the FAAH genes and adiposity traits in the community.

Pharmacologic blockade of the endocannabinoid receptor 1 leads to weight loss and an improved metabolic risk profile in overweight and obese individuals. We hypothesize that common genetic variants in the CNR1 (encoding endocannabinoid receptor 1) and FAAH genes (encoding fatty acid amide hydrolase, a key enzyme hydrolyzing endocannabinoids) are associated with adiposity traits. We genotyped 18 single-nucleotide polymorphisms (SNPs) in the CNR1 gene and 9 SNPs in the FAAH gene in 2,415 Framingham Offspring Study participants (mean age 61 +/- 10 years; 52.6% women; mean BMI 28.2 +/- 5.4 kg/m(2); 30.3% obese) and studied them for association with cross-sectional and longitudinal measures of adiposity (BMI, waist circumference, change over time in BMI and waist circumference, visceral and subcutaneous adipose tissue) using linear mixed-effect models. The selected SNPs captured 85% (r(2) = 0.8) of the common variation (minor allele frequency >5%) at the CNR1 locus and 96% (r(2) = 0.8) of the common variation at the FAAH locus (defined as the genomic segment containing the gene +20 kb upstream and +10 kb downstream). After correction for multiple testing, none of the SNPs in the CNR1 gene or in the FAAH gene displayed statistical evidence for association with BMI, waist circumference, and visceral adipose tissue or subcutaneous adipose tissue (all P > 0.18). Despite comprehensive SNP mapping across the genes and their regulatory regions in a large unselected sample, we failed to find evidence for an association of common variants in the CNR1 and FAAH genes with measures of adiposity in our community-based sample.

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

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.

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

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 > or =5%) with an r(2) value > or =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.

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

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 x 10(-8); P(empiric) [P(e)] = 0.0005 and rs822387; P(n) = 3.8 x 10(-5); P(e) = 0.001). A 3'-untranslated region (3'UTR) SNP (rs6773957) was associated with adiponectin levels (P(n) = 4.4 x 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.

Extension of type 2 diabetes genome-wide association scan results in the diabetes prevention program.

OBJECTIVE: Genome-wide association scans (GWASs) have identified novel diabetes-associated genes. We evaluated how these variants impact diabetes incidence, quantitative glycemic traits, and response to preventive interventions in 3,548 subjects at high risk of type 2 diabetes enrolled in the Diabetes Prevention Program (DPP), which examined the effects of lifestyle intervention, metformin, and troglitazone versus placebo. RESEARCH DESIGN AND METHODS: We genotyped selected single nucleotide polymorphisms (SNPs) in or near diabetes-associated loci, including EXT2, CDKAL1, CDKN2A/B, IGF2BP2, HHEX, LOC387761, and SLC30A8 in DPP participants and performed Cox regression analyses using genotype, intervention, and their interactions as predictors of diabetes incidence. We evaluated their effect on insulin resistance and secretion at 1 year. RESULTS: None of the selected SNPs were associated with increased diabetes incidence in this population. After adjustments for ethnicity, baseline insulin secretion was lower in subjects with the risk genotype at HHEX rs1111875 (P = 0.01); there were no significant differences in baseline insulin sensitivity. Both at baseline and at 1 year, subjects with the risk genotype at LOC387761 had paradoxically increased insulin secretion; adjustment for self-reported ethnicity abolished these differences. In ethnicity-adjusted analyses, we noted a nominal differential improvement in beta-cell function for carriers of the protective genotype at CDKN2A/B after 1 year of troglitazone treatment (P = 0.01) and possibly lifestyle modification (P = 0.05). CONCLUSIONS: We were unable to replicate the GWAS findings regarding diabetes risk in the DPP. We did observe genotype associations with differences in baseline insulin secretion at the HHEX locus and a possible pharmacogenetic interaction at CDKNA2/B.