The authors of this study genotyped single-nucleotide polymorphisms (SNPs) at 18 diabetes-associated loci in participants of the Framingham Offspring Study. A genotype score based on these risk ...alleles predicted new cases of diabetes but resulted in only a slightly better prediction of risk than knowledge of common risk factors alone.
In this study, a genotype score based on 18 diabetes-associated loci predicted new cases of diabetes but resulted in only a slightly better prediction of risk than knowledge of common risk factors alone.
Type 2 diabetes mellitus is a major health problem worldwide.
1
Fortunately, its development can be prevented in many instances,
2
and persons at risk can be readily identified with the measurement of a few common risk factors.
3
–
5
Type 2 diabetes is heritable, with a risk for people with familial diabetes as compared with those without familial diabetes that is increased by a factor of 2 to 6.
6
,
7
Recent genetic association studies have provided convincing evidence that several novel loci are associated with the risk of diabetes,
8
–
13
each with a 5 to 37% increase in the relative odds of . . .
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.
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.
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.
We have identified potential genetic determinants of metformin response. These results merit confirmation in independent samples.
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).
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.
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 β-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).
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.
Association of Variants in RETN With Plasma Resistin Levels and Diabetes-Related Traits in the Framingham Offspring Study
Marie-France Hivert 1 2 ,
Alisa K. Manning 3 ,
Jarred B. McAteer 4 5 ,
Josée ...Dupuis 3 ,
Caroline S. Fox 6 7 ,
L. Adrienne Cupples 3 ,
James B. Meigs 1 2 and
Jose C. Florez 2 4 5
1 General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts
2 Department of Medicine, Harvard Medical School, Boston, Massachusetts
3 Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
4 Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General
Hospital, Boston, Massachusetts
5 Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge,
Massachusetts
6 Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
7 National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts
Corresponding author: Jose C. Florez, jcflorez{at}partners.org
Abstract
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 r 2 > 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 ( P e ) 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, P e <0.05 after multiple testing correction). rs10401670 was also associated with fasting plasma glucose ( P e = 0.02, BMI adjusted) and mean glucose over follow-up ( P e = 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.
Footnotes
Published ahead of print at http://diabetes.diabetesjournals.org on 15 December 2008.
Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work
is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore
be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Accepted December 10, 2008.
Received September 29, 2008.
DIABETES
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 β-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 β-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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
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.
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.
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
Allan F. Moore 1 2 3 4 † ,
Kathleen A. Jablonski 5 ,
Jarred B. McAteer 1 4 ,
Richa Saxena 1 4 ,
...Toni I. Pollin 6 ,
Paul W. Franks 7 ,
Robert L. Hanson 8 ,
Alan R. Shuldiner 6 ,
William C. Knowler 8 ,
David Altshuler 1 2 3 4 9 ,
Jose C. Florez 1 2 3 4 and
for the Diabetes Prevention Program Research Group
1 Center for Human Genetic Research, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
2 Diabetes Center, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
3 Department of Medicine, Harvard Medical School, Boston, Massachusetts
4 Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge,
Massachusetts
5 The Biostatistics Center, George Washington University, Rockville, Maryland
6 Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore,
Maryland
7 Genetic Epidemiology and Clinical Research Group, Department of Public Health and Clinical Medicine, Division of Medicine,
Umeå University Hospital, Umeå, Sweden
8 Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix,
Arizona
9 Department of Genetics, Harvard Medical School, Boston, Massachusetts
Corresponding author: Jose C. Florez, dppmail{at}biostat.bsc.gwu.edu
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 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 β-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 .
Footnotes
Published ahead of print at http://diabetes.diabetesjournals.org on 10 June 2008.
Clinical trial reg. no. NCT00004992, clinicaltrials.gov.
A complete list of Diabetes Prevention Program Research Group investigators is provided in the online appendix available at
http://dx.doi.org/10.2337/db08-0284 .
†
† Dr. Allan F. Moore passed away on 24 July 2008. This article, to which he contributed his privileged intellect and unwavering
enthusiasm, is dedicated to his memory. His colleagues and peers will miss him.
Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work
is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore
be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Accepted June 1, 2008.
Received February 28, 2008.
DIABETES
Abstract
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 β-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 β-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.
Genetic variation in MODY genes was associated with response to diabetes prevention interventions as measured by β-cell function and diabetes incidence.
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.
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.
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).
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.
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.
PDF
