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1.  Combined Effect of Inflammatory Gene Polymorphisms and the Risk of Ischemic Stroke in a Prospective Cohort of Subjects With Type 2 Diabetes: A Go-DARTS Study 
Diabetes  2010;59(11):2945-2948.
OBJECTIVE
We have previously observed that genetic profiles determined by the combination of five functionally significant single nucleotide polymorphisms (SNPs) (rs1800795, rs5498, rs5361, rs1024611, and rs679620) of genes encoding prototypical inflammatory molecules are associated with history of ischemic stroke. Here we tested the ability of this multigenic model to predict stroke risk in a large population-based prospective cohort of subjects with type 2 diabetes.
RESEARCH DESIGN AND METHODS
This study was conducted using a prospective cohort of individuals with type 2 diabetes participating in the Go-DARTS (Genetics of Diabetes Audit and Research in Tayside Scotland) study, which includes genetic and clinical information of patients with diabetes within the Tayside region of Scotland, U.K. The above-mentioned inflammatory SNPs were investigated in 2,182 Go-DARTS participants. We created an inflammatory risk score (IRS), ranging from 0 to 5, according to the number of “at-risk” genotypes concomitantly carried by a given individual. The primary outcome was the occurrence of fatal or nonfatal stroke of any kind. Mean follow-up time was 6.2 ± 1.1 years.
RESULTS
The incidence of stroke increased according to the IRS. The IRS was significantly and independently associated with increased stroke risk after adjustment for other conventional risk factors (hazard ratio 1.34 [95% CI 1.1–1.7]; P = 0.009). The highest hazard ratio for stroke was found in subjects concomitantly carrying >3 proinflammatory variations and in subjects without previous cardiovascular diseases.
CONCLUSIONS
This large prospective cohort study provides evidence that SNPs of genes encoding prototypical inflammatory molecules may be used to create multigenic models that predict stroke risk in subjects with type 2 diabetes.
doi:10.2337/db09-1690
PMCID: PMC2963555  PMID: 20622166
2.  Genetic Variants of Diabetes Risk and Incident Cardiovascular Events in Chronic Coronary Artery Disease 
PLoS ONE  2011;6(1):e16341.
Objective
To determine whether information from genetic risk variants for diabetes is associated with cardiovascular events incidence.
Methods
From the about 30 known genes associated with diabetes, we genotyped single-nucleotide polymorphisms at the 10 loci most associated with type-2 diabetes in 425 subjects from the MASS-II Study, a randomized study in patients with multi-vessel coronary artery disease. The combined genetic information was evaluated by number of risk alleles for diabetes. Performance of genetic models relative to major cardiovascular events incidence was analyzed through Kaplan-Meier curve comparison and Cox Hazard Models and the discriminatory ability of models was assessed for cardiovascular events by calculating the area under the ROC curve.
Results
Genetic information was able to predict 5-year incidence of major cardiovascular events and overall-mortality in non-diabetic individuals, even after adjustment for potential confounders including fasting glycemia. Non-diabetic individuals with high genetic risk had a similar incidence of events then diabetic individuals (cumulative hazard of 33.0 versus 35.1% of diabetic subjects). The addition of combined genetic information to clinical predictors significantly improved the AUC for cardiovascular events incidence (AUC = 0.641 versus 0.610).
Conclusions
Combined information of genetic variants for diabetes risk is associated to major cardiovascular events incidence, including overall mortality, in non-diabetic individuals with coronary artery disease.
Clinical Trial Registration Information
Medicine, Angioplasty, or Surgery Study (MASS II). Unique identifier: ISRCTN66068876 URL.
doi:10.1371/journal.pone.0016341
PMCID: PMC3024434  PMID: 21283728
3.  Reduced-Function SLC22A1 Polymorphisms Encoding Organic Cation Transporter 1 and Glycemic Response to Metformin: A GoDARTS Study 
Diabetes  2009;58(6):1434-1439.
OBJECTIVE
Metformin is actively transported into the liver by the organic cation transporter (OCT)1 (encoded by SLC22A1). In 12 normoglycemic individuals, reduced-function variants in SLC22A1 were shown to decrease the ability of metformin to reduce glucose excursion in response to oral glucose. We assessed the effect of two common loss-of-function polymorphisms in SLC22A1 on metformin response in a large cohort of patients with type 2 diabetes.
RESEARCH DESIGN AND METHODS
The Diabetes Audit and Research in Tayside Scotland (DARTS) database includes prescribing and biochemistry information and clinical phenotypes of all patients with diabetes within Tayside, Scotland, from 1992 onwards. R61C and 420del variants of SLC22A1 were genotyped in 3,450 patients with type 2 diabetes who were incident users of metformin. We assessed metformin response by modeling the maximum A1C reduction in 18 months after starting metformin and investigated whether a treatment target of A1C <7% was achieved. Sustained metformin effect on A1C between 6 and 42 months was also assessed, as was the time to metformin monotherapy failure. Covariates were SLC22A1 genotype, BMI, average drug dose, adherence, and creatinine clearance.
RESULTS
A total of 1,531 patients were identified with a definable metformin response. R61C and 420del variants did not affect the initial A1C reduction (P = 0.47 and P = 0.92, respectively), the chance of achieving a treatment target (P = 0.83 and P = 0.36), the average A1C on monotherapy up to 42 months (P = 0.44 and P = 0.75), or the hazard of monotherapy failure (P = 0.85 and P = 0.56).
CONCLUSIONS
The SLC22A1 loss-of-function variants, R61C and 420del, do not attenuate the A1C reduction achieved by metformin in patients with type 2 diabetes.
doi:10.2337/db08-0896
PMCID: PMC2682689  PMID: 19336679
4.  Polygenic Risk Variants for Type 2 Diabetes Susceptibility Modify Age at Diagnosis in Monogenic HNF1A Diabetes 
Diabetes  2009;59(1):266-271.
OBJECTIVE
Mutations in the HNF1A gene are the most common cause of maturity-onset diabetes of the young (MODY). There is a substantial variation in the age at diabetes diagnosis, even within families where diabetes is caused by the same mutation. We investigated the hypothesis that common polygenic variants that predispose to type 2 diabetes might account for the difference in age at diagnosis.
RESEARCH DESIGN AND METHODS
Fifteen robustly associated type 2 diabetes variants were successfully genotyped in 410 individuals from 203 HNF1A-MODY families, from two study centers in the U.K. and Norway. We assessed their effect on the age at diagnosis both individually and in a combined genetic score by summing the number of type 2 diabetes risk alleles carried by each patient.
RESULTS
We confirmed the effects of environmental and genetic factors known to modify the age at HNF1A-MODY diagnosis, namely intrauterine hyperglycemia (−5.1 years if present, P = 1.6 × 10−10) and HNF1A mutation position (−5.2 years if at least two isoforms affected, P = 1.8 × 10−2). Additionally, our data showed strong effects of sex (females diagnosed 3.0 years earlier, P = 6.0 × 10−4) and age at study (0.3 years later diagnosis per year increase in age, P = 4.7 × 10−38). There were no strong individual single nucleotide polymorphism effects; however, in the combined genetic score model, each additional risk allele was associated with 0.35 years earlier diabetes diagnosis (P = 5.1 × 10−3).
CONCLUSIONS
We show that type 2 diabetes risk variants of modest effect sizes reduce the age at diagnosis in HNF1A-MODY. This is one of the first studies to demonstrate that clinical characteristics of a monogenic disease can be modified by common polygenic variants.
doi:10.2337/db09-0555
PMCID: PMC2797932  PMID: 19794065
5.  Genetic variants predicting left ventricular hypertrophy in a diabetic population: a Go-DARTS study including meta-analysis 
Background
Left ventricular hypertrophy has multiple aetiologies including diabetes and genetic factors. We aimed to identify genetic variants predicting left ventricular hypertrophy in diabetic individuals.
Methods
Demographic, echocardiographic, prescribing, morbidity, mortality and genotyping databases connected with the Genetics of Diabetes Audit and Research in Tayside, Scotland project were accurately linked using a patient-specific identifier. Left ventricular hypertrophy cases were identified using echocardiographic data.
Genotyping data from 973 cases and 1443 non-left ventricular hypertrophy controls were analysed, investigating whether single nucleotide polymorphisms associated with left ventricular hypertrophy in previous Genome Wide Association Studies predicted left ventricular hypertrophy in our population of individuals with type 2 diabetes. Meta-analysis assessed overall significance of these single nucleotide polymorphisms, which were also used to create gene scores. Logistic regression assessed whether these scores predicted left ventricular hypertrophy.
Results
Two single nucleotide polymorphisms previously associated with left ventricular hypertrophy were significant: rs17132261: OR 2.03, 95% CI 1.10-3.73, p-value 0.02 and rs2292462: OR 0.82, 95% CI 0.73-0.93 and p-value 2.26x10-3. Meta-analysis confirmed rs17132261 and rs2292462 were associated with left ventricular hypertrophy (p=1.03x10-8 and p=5.86x10-10 respectively) and one single nucleotide polymorphisms in IGF1R (rs4966014) became genome wide significant upon meta-analysis although was not significant in our study. Gene scoring based on published single nucleotide polymorphisms also predicted left ventricular hypertrophy in our study.
Rs17132261, within SLC25A46, encodes a mitochondrial phosphate transporter, implying abnormal myocardial energetics contribute to left ventricular hypertrophy development. Rs2292462 lies within the obesity-implicated neuromedin B gene. Rs4966014 lies within the IGF1R1 gene. IGF1 signalling is an established factor in cardiac hypertrophy.
Conclusions
We created a resource to study genetics of left ventricular hypertrophy in diabetes and validated our left ventricular hypertrophy phenotype in replicating single nucleotide polymorphisms identified by previous genome wide association studies investigating left ventricular hypertrophy.
doi:10.1186/1475-2840-12-109
PMCID: PMC3729417  PMID: 23879873
Left ventricular hypertrophy; Genetics; Type 2 diabetes mellitus
6.  Mendelian Randomization Studies Do Not Support a Role for Raised Circulating Triglyceride Levels Influencing Type 2 Diabetes, Glucose Levels, or Insulin Resistance 
Diabetes  2011;60(3):1008-1018.
OBJECTIVE
The causal nature of associations between circulating triglycerides, insulin resistance, and type 2 diabetes is unclear. We aimed to use Mendelian randomization to test the hypothesis that raised circulating triglyceride levels causally influence the risk of type 2 diabetes and raise normal fasting glucose levels and hepatic insulin resistance.
RESEARCH DESIGN AND METHODS
We tested 10 common genetic variants robustly associated with circulating triglyceride levels against the type 2 diabetes status in 5,637 case and 6,860 control subjects and four continuous outcomes (reflecting glycemia and hepatic insulin resistance) in 8,271 nondiabetic individuals from four studies.
RESULTS
Individuals carrying greater numbers of triglyceride-raising alleles had increased circulating triglyceride levels (SD 0.59 [95% CI 0.52–0.65] difference between the 20% of individuals with the most alleles and the 20% with the fewest alleles). There was no evidence that the carriers of greater numbers of triglyceride-raising alleles were at increased risk of type 2 diabetes (per weighted allele odds ratio [OR] 0.99 [95% CI 0.97–1.01]; P = 0.26). In nondiabetic individuals, there was no evidence that carriers of greater numbers of triglyceride-raising alleles had increased fasting insulin levels (SD 0.00 per weighted allele [95% CI −0.01 to 0.02]; P = 0.72) or increased fasting glucose levels (0.00 [−0.01 to 0.01]; P = 0.88). Instrumental variable analyses confirmed that genetically raised circulating triglyceride levels were not associated with increased diabetes risk, fasting glucose, or fasting insulin and, for diabetes, showed a trend toward a protective association (OR per 1-SD increase in log10 triglycerides: 0.61 [95% CI 0.45–0.83]; P = 0.002).
CONCLUSIONS
Genetically raised circulating triglyceride levels do not increase the risk of type 2 diabetes or raise fasting glucose or fasting insulin levels in nondiabetic individuals. One explanation for our results is that raised circulating triglycerides are predominantly secondary to the diabetes disease process rather than causal.
doi:10.2337/db10-1317
PMCID: PMC3046819  PMID: 21282362
7.  Loss-of-function CYP2C9 variants: finding the correct clinical role for Type 2 diabetes pharmacogenetic testing 
Continuing advances in genetic discovery have uncovered several dozen loci that are associated with Type 2 diabetes, including genetic variants that appear to modify responses to commonly prescribed diabetes medications. The use of an individual’s genetic information to guide therapy choices raises the possibility of ‘personalized medicine’, wherein each patient’s treatment plan is tailored based on genotype results. However, before such a model of care can be implemented, research is needed to more clearly quantify the association of genetic variation with treatment outcomes and adverse effects. In this article, we review a study examining the association of genetic variation in the cytochrome P450 2C9 enzyme with glycemic response to sulfonylureas in a large cohort of patients with Type 2 diabetes from the Genetics of Diabetes Audit and Research Tayside Study (Go-DARTS).
doi:10.1586/erc.10.5
PMCID: PMC2852129  PMID: 20222813
cytochrome P450 enzyme; genetic polymorphisms; personalized medicine; pharmacogenetics; sulfonylureas; Type 2 diabetes
8.  Mendelian Randomization Studies do not Support a Role for Raised Circulating Triglyceride Levels influencing Type 2 Diabetes, Glucose Levels, or Insulin Resistance 
Diabetes  2011;60(3):1008-1018.
Objective
The causal nature of associations between circulating triglycerides, insulin resistance and type 2 diabetes is unclear. We aimed to use Mendelian randomization to test the hypothesis that raised circulating triglyceride levels causally influence the risk of type 2 diabetes, raised normal fasting glucose levels, and hepatic insulin resistance.
Research design and methods
We tested 10 common genetic variants robustly associated with circulating triglyceride levels against type 2 diabetes status in 5637 cases, 6860 controls, and four continuous outcomes (reflecting glycemia and hepatic insulin resistance) in 8271 non-diabetic individuals from four studies.
Results
Individuals carrying greater numbers of triglyceride-raising alleles had increased circulating triglyceride levels (0.59 SD [95% CI: 0.52, 0.65] difference between the 20% of individuals with the most alleles and the 20% with the fewest alleles). There was no evidence that carriers of greater numbers of triglyceride-raising alleles were at increased risk of type 2 diabetes (per weighted allele odds ratio (OR) 0.99 [95% CI: 0.97, 1.01]; P = 0.26). In non-diabetic individuals, there was no evidence that carriers of greater numbers of triglyceride-raising alleles had increased fasting insulin levels (0.00 SD per weighted allele [95% CI: −0.01, 0.02]; P = 0.72) or increased fasting glucose levels (0.00 SD per weighted allele [95% CI: −0.01, 0.01]; P = 0.88). Instrumental variable analyses confirmed that genetically raised circulating triglyceride levels were not associated with increased diabetes risk, fasting glucose or fasting insulin, and, for diabetes, showed a trend towards a protective association (OR per 1 SD increase in log10-triglycerides: 0.61 [95% CI: 0.45, 0.83]; P = 0.002).
Conclusion
Genetically raised circulating triglyceride levels do not increase the risk of type 2 diabetes, or raise fasting glucose or fasting insulin levels in non-diabetic individuals. One explanation for our results is that raised circulating triglycerides are predominantly secondary to the diabetes disease process rather than causal.
doi:10.2337/db10-1317
PMCID: PMC3046819  PMID: 21282362
9.  Genetic Risk Score Constructed Using 14 Susceptibility Alleles for Type 2 Diabetes Is Associated With the Early Onset of Diabetes and May Predict the Future Requirement of Insulin Injections Among Japanese Individuals 
Diabetes Care  2012;35(8):1763-1770.
OBJECTIVE
We evaluated the clinical usefulness of a genetic risk score (GRS) based on 14 well-established variants for type 2 diabetes.
RESEARCH DESIGN AND METHODS
We analyzed 14 SNPs at HHEX, CDKAL1, CDKN2B, SLC30A8, KCNJ11, IGF2BP2, PPARG, TCF7L2, FTO, KCNQ1, IRS-1, GCKR, UBE2E2, and C2CD4A/B in 1,487 Japanese individuals (724 patients with type 2 diabetes and 763 control subjects). A GRS was calculated according to the number of risk alleles by counting all 14 SNPs (T-GRS) as well as 11 SNPs related to β-cell function (β-GRS) and then assessing the association between each GRS and the clinical features.
RESULTS
Among the 14 SNPs, 4 SNPs were significantly associated with type 2 diabetes in the present Japanese sample (P < 0.0036). The T-GRS was significantly associated with type 2 diabetes (P = 5.9 × 10−21). Among the subjects with type 2 diabetes, the β-GRS was associated with individuals receiving insulin therapy (β = 0.0131, SE = 0.006, P = 0.0431), age at diagnosis (β = −0.608, SE = 0.204, P = 0.0029), fasting serum C-peptide level (β = −0.032, SE = 0.0140, P = 0.022), and C-peptide index (β = −0.031, SE = 0.012, P = 0.0125).
CONCLUSIONS
Our data suggest that the β-GRS is associated with reduced β-cell functions and may be useful for selecting patients who should receive more aggressive β-cell–preserving therapy.
doi:10.2337/dc11-2006
PMCID: PMC3402252  PMID: 22688542
10.  A Variant in the KCNQ1 Gene Predicts Future Type 2 Diabetes and Mediates Impaired Insulin Secretion 
Diabetes  2009;58(10):2409-2413.
OBJECTIVE
Two independent genome-wide association studies for type 2 diabetes in Japanese subjects have recently identified common variants in the KCNQ1 gene that are strongly associated with type 2 diabetes. Here we studied whether a common variant in KCNQ1 would influence BMI as well as insulin secretion and action and predict future type 2 diabetes in subjects from Sweden and Finland.
RESEARCH DESIGN AND METHODS
Risk of type 2 diabetes conferred by KCNQ1 rs2237895 was studied in 2,830 type 2 diabetic case subjects and 3,550 control subjects from Sweden (Malmö Case-Control) and prospectively in 16,061 individuals from the Malmö Preventive Project (MPP). Association between genotype and insulin secretion/action was assessed cross- sectionally in 3,298 nondiabetic subjects from the Prevalence, Prediction and Prevention of Diabetes (PPP)-Botnia Study and longitudinally in 2,328 nondiabetic subjects from the Botnia Prospective Study (BPS). KCNQ1 expression (n = 18) and glucose-stimulated insulin secretion (n = 19) were measured in human islets from nondiabetic cadaver donors.
RESULTS
The C-allele of KCNQ1 rs2237895 was associated with increased risk of type 2 diabetes in both the Malmö Case-Control (odds ratio 1.23 [95% CI 1.12–1.34]; P = 5.6 × 10−6) and the prospective (1.14 [1.06–1.22]; P = 4.8 × 10−4) studies. Furthermore, the C-allele was associated with decreased insulin secretion (corrected insulin response [CIR] P = 0.013; disposition index [DI] P = 0.013) in the PPP-Botnia Study and in the BPS at baseline (CIR P = 3.6 × 10−4; DI P = 0.0058) and after follow-up (CIR P = 0.0018; DI P = 0.0030). C-allele carriers showed reduced glucose-stimulated insulin secretion in human islets (P = 2.5 × 10−6).
CONCLUSIONS
A common variant in the KCNQ1 gene is associated with increased risk of future type 2 diabetes in Scandinavians, which partially can be explained by an effect on insulin secretion.
doi:10.2337/db09-0246
PMCID: PMC2750226  PMID: 19584308
11.  Comprehensive Association Study of Type 2 Diabetes and Related Quantitative Traits With 222 Candidate Genes 
Diabetes  2008;57(11):3136-3144.
OBJECTIVE—Type 2 diabetes is a common complex disorder with environmental and genetic components. We used a candidate gene–based approach to identify single nucleotide polymorphism (SNP) variants in 222 candidate genes that influence susceptibility to type 2 diabetes.
RESEARCH DESIGN AND METHODS—In a case-control study of 1,161 type 2 diabetic subjects and 1,174 control Finns who are normal glucose tolerant, we genotyped 3,531 tagSNPs and annotation-based SNPs and imputed an additional 7,498 SNPs, providing 99.9% coverage of common HapMap variants in the 222 candidate genes. Selected SNPs were genotyped in an additional 1,211 type 2 diabetic case subjects and 1,259 control subjects who are normal glucose tolerant, also from Finland.
RESULTS—Using SNP- and gene-based analysis methods, we replicated previously reported SNP-type 2 diabetes associations in PPARG, KCNJ11, and SLC2A2; identified significant SNPs in genes with previously reported associations (ENPP1 [rs2021966, P = 0.00026] and NRF1 [rs1882095, P = 0.00096]); and implicated novel genes, including RAPGEF1 (rs4740283, P = 0.00013) and TP53 (rs1042522, Arg72Pro, P = 0.00086), in type 2 diabetes susceptibility.
CONCLUSIONS—Our study provides an effective gene-based approach to association study design and analysis. One or more of the newly implicated genes may contribute to type 2 diabetes pathogenesis. Analysis of additional samples will be necessary to determine their effect on susceptibility.
doi:10.2337/db07-1731
PMCID: PMC2570412  PMID: 18678618
12.  Cumulative Effect of Common Genetic Variants Predicts Incident Type 2 Diabetes: A Study of 21,183 Subjects from Three Large Prospective Cohorts 
Recent genome-wide association studies (GWAS) and their meta-analyses have identified multiple genetic loci that are associated with type 2 diabetes (T2D). Except for variants in the TCF7L2 gene which had a modest effect on diabetic risk, most genetic variants identified so far have only a weak association with diabetes. It is possible that the combination of multiple variants may have a larger effect on disease risk and improve risk prediction. In this study, we focus on SNPs that had been robustly replicated in previous GWAS and were also genotyped in a large sample of 21,183 participants from three large prospective cohorts, including Atherosclerosis Risk in Communities (ARIC) Study, Framingham Offspring Study (FOS) and Multi-Ethnic Study of Atherosclerosis (MESA). Among these, we were able to successfully confirm the associations of 12 SNPs with baseline prevalent T2D in these two cohorts. A genotype risk score (GRS) using these12 risk variants was constructed to examine whether GRS predicts incident diabetes. In a combined meta-analysis, subjects in the highest tertile of GRS had a 1.62-fold increased risk of incident T2D (95% CI, 1.08–2.44, P=1.5×10−14) compared to those in the lowest tertile of GRS after adjustment for age, sex, race, smoking, body mass index (BMI), lipids (HDL and LDL) and systolic blood pressure. Moreover, GRS significantly improves risk prediction and reclassification in T2D beyond known risk factors.
PMCID: PMC3956676  PMID: 24653947
Type 2 diabetes; Single nucleotide polymorphism; Genotype risk score; Incident diabetes
13.  Confirmation of Genetic Associations at ELMO1 in the GoKinD Collection Supports Its Role as a Susceptibility Gene in Diabetic Nephropathy 
Diabetes  2009;58(11):2698-2702.
OBJECTIVE
To examine the association between single nucleotide polymorphisms (SNPs) in the engulfment and cell motility 1 (ELMO1) gene, a locus previously shown to be associated with diabetic nephropathy in two ethnically distinct type 2 diabetic populations, and the risk of nephropathy in type 1 diabetes.
RESEARCH DESIGN AND METHODS
Genotypic data from a genome-wide association scan (GWAS) of the Genetics of Kidneys in Diabetes (GoKinD) study collection were analyzed for associations across the ELMO1 locus. In total, genetic associations were assessed using 118 SNPs and 1,705 individuals of European ancestry with type 1 diabetes (885 normoalbuminuric control subjects and 820 advanced diabetic nephropathy case subjects).
RESULTS
The strongest associations in ELMO1 occurred at rs11769038 (odds ratio [OR] 1.24; P = 1.7 × 10−3) and rs1882080 (OR 1.23; P = 3.2 × 10−3) located in intron 16. Two additional SNPs, located in introns 18 and 20, respectively, were also associated with diabetic nephropathy. No evidence of association for variants previously reported in type 2 diabetes was observed in our collection.
CONCLUSIONS
Using GWAS data from the GoKinD collection, we comprehensively examined evidence of association across the ELMO1 locus. Our investigation marks the third report of associations in ELMO1 with diabetic nephropathy, further establishing its role in the susceptibility of this disease. There is evidence of allelic heterogeneity, contributed by the diverse genetic backgrounds of the different ethnic groups examined. Further investigation of SNPs at this locus is necessary to fully understand the commonality of these associations and the mechanism(s) underlying their role in diabetic nephropathy.
doi:10.2337/db09-0641
PMCID: PMC2768169  PMID: 19651817
14.  Genetic predisposition to obesity leads to increased risk of type 2 diabetes 
Diabetologia  2011;54(4):776-782.
Aims/hypothesis
Obesity is a major risk factor for type 2 diabetes. Recent genome-wide association (GWA) studies have identified multiple loci robustly associated with BMI and risk of obesity. However, information on their associations with type 2 diabetes is limited. Such information could help increase our understanding of the link between obesity and type 2 diabetes. We examined the associations of 12 obesity susceptibility loci, individually and in combination, with risk of type 2 diabetes in the population-based European Prospective Investigation of Cancer (EPIC) Norfolk cohort.
Methods
We genotyped 12 SNPs, identified by GWA studies of BMI, in 20,428 individuals (aged 39–79 years at baseline) with an average follow-up of 12.9 years, during which 729 individuals developed type 2 diabetes. A genetic predisposition score was calculated by adding the BMI-increasing alleles across the 12 SNPs. Associations with incidence of type 2 diabetes were examined by logistic regression models.
Results
Of the 12 SNPs, eight showed a trend with increased risk of type 2 diabetes, consistent with their BMI-increasing effects. Each additional BMI-increasing allele in the genetic predisposition score was associated with a 4% increased odds of developing type 2 diabetes (OR 1.041, 95% CI 1.005–1.078; p = 0.02). Adjustment for BMI completely abolished the association with incident type 2 diabetes (OR 1.003, 95% CI 0.967–1.039; p = 0.89).
Conclusions/interpretation
The genetic predisposition to obesity leads to increased risk of developing type 2 diabetes, which is completely mediated by its obesity-predisposing effect.
Electronic supplementary material
The online version of this article (doi:10.1007/s00125-011-2044-5) contains supplementary material, which is available to authorized users.
doi:10.1007/s00125-011-2044-5
PMCID: PMC3052481  PMID: 21267540
Genetic predisposition; Genome-wide association studies; Obesity; Type 2 diabetes
15.  Genetic Risk Assessment of Type 2 Diabetes–Associated Polymorphisms in African Americans 
Diabetes Care  2012;35(2):287-292.
OBJECTIVE
Multiple single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D) susceptibility have been identified in predominantly European-derived populations. These SNPs have not been extensively investigated for individual and cumulative effects on T2D risk in African Americans.
RESEARCH DESIGN AND METHODS
Seventeen index T2D risk variants were genotyped in 2,652 African American case subjects with T2D and 1,393 nondiabetic control subjects. Individual SNPs and cumulative risk allele loads were assessed for association with risk for T2D. Cumulative risk was assessed by counting risk alleles and evaluating the difference in cumulative risk scores between case subjects and control subjects. A second analysis weighted risk scores (ln [OR]) based on previously reported European-derived effect sizes.
RESULTS
Frequencies of risk alleles ranged from 8.6 to 99.9%. Eleven SNPs had ORs >1, and 5 from ADAMTS9, WFS1, CDKAL1, JAZF1, and TCF7L2 trended or had nominally significant evidence of T2D association (P < 0.05). Individuals carried between 13 and 29 risk alleles. Association was observed between T2D and increase in risk allele load (unweighted OR 1.04 [95% CI 1.01–1.08], P = 0.010; weighted 1.06 [1.03–1.10], P = 8.10 × 10−5). When TCF7L2 SNP rs7903146 was included as a covariate, the risk score was no longer associated with T2D in either model (unweighted 1.02 [0.98–1.05], P = 0.33; weighted 1.02 [0.98–1.06], P = 0.40).
CONCLUSIONS
The trend of increase in risk for T2D with increasing risk allele load is similar to observations in European-derived populations; however, these analyses indicate that T2D genetic risk is primarily mediated through the effect of TCF7L2 in African Americans.
doi:10.2337/dc11-0957
PMCID: PMC3263882  PMID: 22275441
16.  Combining Information from Common Type 2 Diabetes Risk Polymorphisms Improves Disease Prediction 
PLoS Medicine  2006;3(10):e374.
Background
A limited number of studies have assessed the risk of common diseases when combining information from several predisposing polymorphisms. In most cases, individual polymorphisms only moderately increase risk (~20%), and they are thought to be unhelpful in assessing individuals' risk clinically. The value of analyzing multiple alleles simultaneously is not well studied. This is often because, for any given disease, very few common risk alleles have been confirmed.
Methods and Findings
Three common variants (Lys23 of KCNJ11, Pro12 of PPARG, and the T allele at rs7903146 of TCF7L2) have been shown to predispose to type 2 diabetes mellitus across many large studies. Risk allele frequencies ranged from 0.30 to 0.88 in controls. To assess the combined effect of multiple susceptibility alleles, we genotyped these variants in a large case-control study (3,668 controls versus 2,409 cases). Individual allele odds ratios (ORs) ranged from 1.14 (95% confidence interval [CI], 1.05 to 1.23) to 1.48 (95% CI, 1.36 to 1.60). We found no evidence of gene-gene interaction, and the risks of multiple alleles were consistent with a multiplicative model. Each additional risk allele increased the odds of type 2 diabetes by 1.28 (95% CI, 1.21 to 1.35) times. Participants with all six risk alleles had an OR of 5.71 (95% CI, 1.15 to 28.3) compared to those with no risk alleles. The 8.1% of participants that were double-homozygous for the risk alleles at TCF7L2 and Pro12Ala had an OR of 3.16 (95% CI, 2.22 to 4.50), compared to 4.3% with no TCF7L2 risk alleles and either no or one Glu23Lys or Pro12Ala risk alleles.
Conclusions
Combining information from several known common risk polymorphisms allows the identification of population subgroups with markedly differing risks of developing type 2 diabetes compared to those obtained using single polymorphisms. This approach may have a role in future preventative measures for common, polygenic diseases.
Combining information from several known common risk polymorphisms allows the identification of subgroups of the population with markedly differing risks of developing type 2 diabetes.
Editors' Summary
Background.
Diabetes is an important and increasingly common global health problem; the World Health Organization has estimated that about 170 million people currently have diabetes worldwide. One particular form, type 2 diabetes, develops when cells in the body become unable to respond to a hormone called insulin. Insulin is normally released by the pancreas and controls the ability of body cells to take in glucose (sugar). Therefore, when cells become insensitive to insulin as in people with type 2 diabetes, glucose levels in the body are not well controlled and may become dangerously high in the blood. These high levels can have long-term damaging effects on various organs in the body, particularly the eyes, nerves, heart, and kidneys. There are many different factors that affect whether someone is likely to develop type 2 diabetes. These factors can be broadly grouped into two categories: environmental and genetic. Environmental factors such as obesity, a diet high in sugar, and a sedentary lifestyle are all risk factors for developing type 2 diabetes in later life. Genetically, a number of variants in many different genes may affect the risk of developing the disease. Generally, these gene variants are common in human populations but each gene variant only mildly increases the risk that a person possessing it will get type 2 diabetes.
Why Was This Study Done?
The investigators performing this study wanted to understand how different gene variants combine to affect an individual's risk of getting type 2 diabetes. That is, if a person carries many different variants, does their overall risk increase a lot or only a little?
What Did the Researchers Do and Find?
First, the researchers surveyed the published reports to identify those gene variants for which there was strong evidence of an association with type 2 diabetes. They found mutations in three genes that had been shown reproducibly to be associated with type 2 diabetes in different studies: PPARG (whose product is involved in regulation of fat tissue), KCNJ11 (whose product is involved in insulin production), and TCF7L2 (whose product is thought to be involved in controlling sugar levels). Then, they compared two groups of white people in the UK: 2,409 people with type 2 diabetes (“cases”), and 3,668 people from the general population (“controls”). The researchers compared the two groups to see which individuals possessed which gene variants, and did statistical testing to work out to what extent having particular combinations of the gene variants affected an individual's chance of being a “case” versus a “control.” Their results showed that in the groups studied, having an ever-increasing number of gene variants increased the risk of developing diabetes. The risk that someone with none of the gene variants would develop type 2 diabetes was about 2%, while the chance for someone with all gene variants was about10%.
What Do These Findings Mean?
These results show that the risk of developing type 2 diabetes is greater if an individual possesses all of the gene variants that were examined in this study. The analysis also suggests that using information on all three variants, rather than just one, is likely to be more accurate in predicting future risk. How this genetic information should be used alongside other well-known preventative measures such as altered lifestyle requires further study.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0030374.
NHS Direct patient information on diabetes
National Diabetes Information Clearinghouse information on type 2 diabetes
World Health Organization Diabetes Programme
Centers for Disease ControlDiabetes Public Health Resource
doi:10.1371/journal.pmed.0030374
PMCID: PMC1584415  PMID: 17020404
17.  Sequencing PDX1 (insulin promoter factor 1) in 1788 UK individuals found 5% had a low frequency coding variant, but these variants are not associated with Type 2 diabetes 
Diabetic Medicine  2011;28(6):681-684.
Aim
Genome-wide association studies have identified > 30 common variants associated with Type 2 diabetes (> 5% minor allele frequency). These variants have small effects on individual risk and do not account for a large proportion of the heritable component of the disease. Monogenic forms of diabetes are caused by mutations that occur in < 1:2000 individuals and follow strict patterns of inheritance. In contrast, the role of low frequency genetic variants (minor allele frequency 0.1–5%) in Type 2 diabetes is not known. The aim of this study was to assess the role of low frequency PDX1 (also called IPF1) variants in Type 2 diabetes.
Methods
We sequenced the coding and flanking intronic regions of PDX1 in 910 patients with Type 2 diabetes and 878 control subjects.
Results
We identified a total of 26 variants that occurred in 5.3% of individuals, 14 of which occurred once. Only D76N occurred in > 1%. We found no difference in carrier frequency between patients (5.7%) and control subjects (5.0%) (P = 0.46). There were also no differences between patients and control subjects when analyses were limited to subsets of variants. The strongest subset were those variants in the DNA binding domain where all five variants identified were only found in patients (P = 0.06).
Conclusion
Approximately 5% of UK individuals carry a PDX1 variant, but there is no evidence that these variants, either individually or cumulatively, predispose to Type 2 diabetes. Further studies will need to consider strategies to assess the role of multiple variants that occur in < 1 in 1000 individuals.
doi:10.1111/j.1464-5491.2011.03269.x
PMCID: PMC3586655  PMID: 21569088
diabetes; genetics; polygenic; variants
18.  Common Inherited Variation in Mitochondrial Genes Is Not Enriched for Associations with Type 2 Diabetes or Related Glycemic Traits 
PLoS Genetics  2010;6(8):e1001058.
Mitochondrial dysfunction has been observed in skeletal muscle of people with diabetes and insulin-resistant individuals. Furthermore, inherited mutations in mitochondrial DNA can cause a rare form of diabetes. However, it is unclear whether mitochondrial dysfunction is a primary cause of the common form of diabetes. To date, common genetic variants robustly associated with type 2 diabetes (T2D) are not known to affect mitochondrial function. One possibility is that multiple mitochondrial genes contain modest genetic effects that collectively influence T2D risk. To test this hypothesis we developed a method named Meta-Analysis Gene-set Enrichment of variaNT Associations (MAGENTA; http://www.broadinstitute.org/mpg/magenta). MAGENTA, in analogy to Gene Set Enrichment Analysis, tests whether sets of functionally related genes are enriched for associations with a polygenic disease or trait. MAGENTA was specifically designed to exploit the statistical power of large genome-wide association (GWA) study meta-analyses whose individual genotypes are not available. This is achieved by combining variant association p-values into gene scores and then correcting for confounders, such as gene size, variant number, and linkage disequilibrium properties. Using simulations, we determined the range of parameters for which MAGENTA can detect associations likely missed by single-marker analysis. We verified MAGENTA's performance on empirical data by identifying known relevant pathways in lipid and lipoprotein GWA meta-analyses. We then tested our mitochondrial hypothesis by applying MAGENTA to three gene sets: nuclear regulators of mitochondrial genes, oxidative phosphorylation genes, and ∼1,000 nuclear-encoded mitochondrial genes. The analysis was performed using the most recent T2D GWA meta-analysis of 47,117 people and meta-analyses of seven diabetes-related glycemic traits (up to 46,186 non-diabetic individuals). This well-powered analysis found no significant enrichment of associations to T2D or any of the glycemic traits in any of the gene sets tested. These results suggest that common variants affecting nuclear-encoded mitochondrial genes have at most a small genetic contribution to T2D susceptibility.
Author Summary
Mitochondria play a crucial role in metabolic homeostasis, and alteration of mitochondrial function is a hallmark of diabetes. While mitochondrial activity is reduced in people with diabetes, it is unclear whether mitochondrial dysfunction is a cause or effect of type 2 diabetes. Genome-wide association studies for type 2 diabetes have explained ≈10% of the heritability of the disease, but none of the loci are known to affect mitochondrial activity. It is possible though that a mitochondrial contribution is hidden in the remaining 90%. Hence, we tested the hypothesis that multiple mitochondria-related genes encoded in the nucleus, each having a weak effect (hard to detect individually), can collectively influence type 2 diabetes. To address this, we developed a computational method (MAGENTA) that allowed us to adequately analyze large collective datasets of human genetic variation obtained from collaborative studies of type 2 diabetes and related glycemic traits. Despite the increased sensitivity of MAGENTA compared to single-DNA variant analysis, we found no support for a causal relationship between mitochondrial dysfunction and type 2 diabetes. These results may help steer future efforts in understanding the pathogenesis of the disease. MAGENTA is broadly applicable to testing associations between other biological pathways and common diseases or traits.
doi:10.1371/journal.pgen.1001058
PMCID: PMC2920848  PMID: 20714348
19.  Birth Weight, Genetic Susceptibility, and Adulthood Risk of Type 2 Diabetes 
Diabetes Care  2012;35(12):2479-2484.
OBJECTIVE
Both stressful intrauterine milieus and genetic susceptibility have been linked to later-life diabetes risk. The current study aims to examine the interaction between low birth weight, a surrogate measure of stressful intrauterine milieus, and genetic susceptibility in relation to risk of type 2 diabetes in adulthood.
RESEARCH DESIGN AND METHODS
The analysis included two independent, nested case-control studies of 2,591 type 2 diabetic case subjects and 3,052 healthy control subjects. We developed two genotype scores: an obesity genotype score based on 32 BMI-predisposing variants and a diabetes genotype score based on 35 diabetes-predisposing variants.
RESULTS
Obesity genotype scores showed a stronger association with type 2 diabetes risk in individuals with low birth weight. In low–birth weight individuals, the multivariable-adjusted odds ratio (OR) was 2.55 (95% CI 1.34–4.84) by comparing extreme quartiles of the obesity genotype score, while the OR was 1.27 (1.04–1.55) among individuals with birth weight >2.5 kg (P for interaction = 0.017). We did not observe significant interaction between diabetes genotype scores and birth weight with regard to risk of type 2 diabetes. In a comparison of extreme quartiles of the diabetes gene score, the multivariable-adjusted OR was 3.80 (1.76–8.24) among individuals with low birth weight and 2.27 (1.82–2.83) among those with high birth weight (P for interaction = 0.16).
CONCLUSIONS
Our data suggest that low birth weight and genetic susceptibility to obesity may synergistically affect adulthood risk of type 2 diabetes.
doi:10.2337/dc12-0168
PMCID: PMC3507591  PMID: 22923665
20.  Interrogating Type 2 Diabetes Genome-Wide Association Data Using a Biological Pathway-Based Approach 
Diabetes  2009;58(6):1463-1467.
OBJECTIVE
Recent genome-wide association studies have resulted in a dramatic increase in our knowledge of the genetic loci involved in type 2 diabetes. In a complementary approach to these single-marker studies, we attempted to identify biological pathways associated with type 2 diabetes. This approach could allow us to identify additional risk loci.
RESEARCH DESIGN AND METHODS
We used individual level genotype data generated from the Wellcome Trust Case Control Consortium (WTCCC) type 2 diabetes study, consisting of 393,143 autosomal SNPs, genotyped across 1,924 case subjects and 2,938 control subjects. We sought additional evidence from summary level data available from the Diabetes Genetics Initiative (DGI) and the Finland-United States Investigation of NIDDM Genetics (FUSION) studies. Statistical analysis of pathways was performed using a modification of the Gene Set Enrichment Algorithm (GSEA). A total of 439 pathways were analyzed from the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and BioCarta databases.
RESULTS
After correcting for the number of pathways tested, we found no strong evidence for any pathway showing association with type 2 diabetes (top Padj = 0.31). The candidate WNT-signaling pathway ranked top (nominal P = 0.0007, excluding TCF7L2; P = 0.002), containing a number of promising single gene associations. These include CCND2 (rs11833537; P = 0.003), SMAD3 (rs7178347; P = 0.0006), and PRICKLE1 (rs1796390; P = 0.001), all expressed in the pancreas.
CONCLUSIONS
Common variants involved in type 2 diabetes risk are likely to occur in or near genes in multiple pathways. Pathway-based approaches to genome-wide association data may be more successful for some complex traits than others, depending on the nature of the underlying disease physiology.
doi:10.2337/db08-1378
PMCID: PMC2682674  PMID: 19252133
21.  Genetic Risk Reclassification for Type 2 Diabetes by Age Below or Above 50 Years Using 40 Type 2 Diabetes Risk Single Nucleotide Polymorphisms 
Diabetes Care  2010;34(1):121-125.
OBJECTIVE
To test if knowledge of type 2 diabetes genetic variants improves disease prediction.
RESEARCH DESIGN AND METHODS
We tested 40 single nucleotide polymorphisms (SNPs) associated with diabetes in 3,471 Framingham Offspring Study subjects followed over 34 years using pooled logistic regression models stratified by age (<50 years, diabetes cases = 144; or ≥50 years, diabetes cases = 302). Models included clinical risk factors and a 40-SNP weighted genetic risk score.
RESULTS
In people <50 years of age, the clinical risk factors model C-statistic was 0.908; the 40-SNP score increased it to 0.911 (P = 0.3; net reclassification improvement (NRI): 10.2%, P = 0.001). In people ≥50 years of age, the C-statistics without and with the score were 0.883 and 0.884 (P = 0.2; NRI: 0.4%). The risk per risk allele was higher in people <50 than ≥50 years of age (24 vs. 11%; P value for age interaction = 0.02).
CONCLUSIONS
Knowledge of common genetic variation appropriately reclassifies younger people for type 2 diabetes risk beyond clinical risk factors but not older people.
doi:10.2337/dc10-1265
PMCID: PMC3005447  PMID: 20889853
22.  Glaucoma incidence in an unselected cohort of diabetic patients: is diabetes mellitus a risk factor for glaucoma? 
The British Journal of Ophthalmology  2000;84(11):1218-1224.
AIMS—To evaluate whether diabetes mellitus is a risk factor for the development of primary open angle glaucoma or ocular hypertension (OHT).
METHODS—A historical cohort study of an unselected population comprising all residents of the Tayside region of Scotland was performed using record linkage techniques followed by case note review. Ascertainment of prevalent diabetes was achieved using the Diabetes Audit and Research in Tayside Study (DARTS) validated regional diabetes register. Glaucoma and treated OHT were defined by encashment of community prescriptions and the statutory surgical procedure coding database.
RESULTS—The study population comprised 6631 diabetic subjects and 166 144 non-diabetic subjects aged >40 years without glaucoma or OHT at study entry. 65 patients with diabetes and 958 without diabetes were identified as new cases of glaucoma or treated OHT during the 24 month study period, yielding a standardised morbidity ratio of 127 (95% CI, 96-158). Case note review demonstrated non-differential misclassification of prevalent glaucoma and OHT as incident disease (diabetic cohort 20%, non-diabetic cohort 24%; p=0.56) primarily as a result of non-compliance in medically treated disease. Removing misclassified cases and adjusting for age yielded an incidence of primary open angle glaucoma in diabetes of 1.1/1000 patient years (95% CI, 0.89-1.31) compared to 0.7/1000 patient years (95% CI, 0.54-0.86) in the non-diabetic cohort; RR 1.57 (95% CI, 0.99-2.48).
CONCLUSIONS—This study failed to confirm an association between diabetes mellitus and primary open angle glaucoma and ocular hypertension. A non-significant increase in diagnosed and treated disease in the diabetic population was observed, but evidence was also found that detection bias contributes to this association.


doi:10.1136/bjo.84.11.1218
PMCID: PMC1723322  PMID: 11049943
23.  Detailed Investigation of the Role of Common and Low-Frequency WFS1 Variants in Type 2 Diabetes Risk 
Diabetes  2009;59(3):741-746.
OBJECTIVE
Wolfram syndrome 1 (WFS1) single nucleotide polymorphisms (SNPs) are associated with risk of type 2 diabetes. In this study we aimed to refine this association and investigate the role of low-frequency WFS1 variants in type 2 diabetes risk.
RESEARCH DESIGN AND METHODS
For fine-mapping, we sequenced WFS1 exons, splice junctions, and conserved noncoding sequences in samples from 24 type 2 diabetic case and 68 control subjects, selected tagging SNPs, and genotyped these in 959 U.K. type 2 diabetic case and 1,386 control subjects. The same genomic regions were sequenced in samples from 1,235 type 2 diabetic case and 1,668 control subjects to compare the frequency of rarer variants between case and control subjects.
RESULTS
Of 31 tagging SNPs, the strongest associated was the previously untested 3′ untranslated region rs1046320 (P = 0.008); odds ratio 0.84 and P = 6.59 × 10−7 on further replication in 3,753 case and 4,198 control subjects. High correlation between rs1046320 and the original strongest SNP (rs10010131) (r2 = 0.92) meant that we could not differentiate between their effects in our samples. There was no difference in the cumulative frequency of 82 rare (minor allele frequency [MAF] <0.01) nonsynonymous variants between type 2 diabetic case and control subjects (P = 0.79). Two intermediate frequency (MAF 0.01–0.05) nonsynonymous changes also showed no statistical association with type 2 diabetes.
CONCLUSIONS
We identified six highly correlated SNPs that show strong and comparable associations with risk of type 2 diabetes, but further refinement of these associations will require large sample sizes (>100,000) or studies in ethnically diverse populations. Low frequency variants in WFS1 are unlikely to have a large impact on type 2 diabetes risk in white U.K. populations, highlighting the complexities of undertaking association studies with low-frequency variants identified by resequencing.
doi:10.2337/db09-0920
PMCID: PMC2828659  PMID: 20028947
24.  Impact of Common Variation in Bone-Related Genes on Type 2 Diabetes and Related Traits 
Diabetes  2012;61(8):2176-2186.
Exploring genetic pleiotropy can provide clues to a mechanism underlying the observed epidemiological association between type 2 diabetes and heightened fracture risk. We examined genetic variants associated with bone mineral density (BMD) for association with type 2 diabetes and glycemic traits in large well-phenotyped and -genotyped consortia. We undertook follow-up analysis in ∼19,000 individuals and assessed gene expression. We queried single nucleotide polymorphisms (SNPs) associated with BMD at levels of genome-wide significance, variants in linkage disequilibrium (r2 > 0.5), and BMD candidate genes. SNP rs6867040, at the ITGA1 locus, was associated with a 0.0166 mmol/L (0.004) increase in fasting glucose per C allele in the combined analysis. Genetic variants in the ITGA1 locus were associated with its expression in the liver but not in adipose tissue. ITGA1 variants appeared among the top loci associated with type 2 diabetes, fasting insulin, β-cell function by homeostasis model assessment, and 2-h post–oral glucose tolerance test glucose and insulin levels. ITGA1 has demonstrated genetic pleiotropy in prior studies, and its suggested role in liver fibrosis, insulin secretion, and bone healing lends credence to its contribution to both osteoporosis and type 2 diabetes. These findings further underscore the link between skeletal and glucose metabolism and highlight a locus to direct future investigations.
doi:10.2337/db11-1515
PMCID: PMC3402303  PMID: 22698912
25.  Genome-Wide Association Scan for Diabetic Nephropathy Susceptibility Genes in Type 1 Diabetes 
Diabetes  2009;58(6):1403-1410.
OBJECTIVE
Despite extensive evidence for genetic susceptibility to diabetic nephropathy, the identification of susceptibility genes and their variants has had limited success. To search for genes that contribute to diabetic nephropathy, a genome-wide association scan was implemented on the Genetics of Kidneys in Diabetes collection.
RESEARCH DESIGN AND METHODS
We genotyped ∼360,000 single nucleotide polymorphisms (SNPs) in 820 case subjects (284 with proteinuria and 536 with end-stage renal disease) and 885 control subjects with type 1 diabetes. Confirmation of implicated SNPs was sought in 1,304 participants of the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study, a long-term, prospective investigation of the development of diabetes-associated complications.
RESULTS
A total of 13 SNPs located in four genomic loci were associated with diabetic nephropathy with P < 1 × 10−5. The strongest association was at the FRMD3 (4.1 protein ezrin, radixin, moesin [FERM] domain containing 3) locus (odds ratio [OR] = 1.45, P = 5.0 × 10−7). A strong association was also identified at the CARS (cysteinyl-tRNA synthetase) locus (OR = 1.36, P = 3.1 × 10−6). Associations between both loci and time to onset of diabetic nephropathy were supported in the DCCT/EDIC study (hazard ratio [HR] = 1.33, P = 0.02, and HR = 1.32, P = 0.01, respectively). We demonstratedexpression of both FRMD3 and CARS in human kidney.
CONCLUSIONS
We identified genetic associations for susceptibility to diabetic nephropathy at two novel candidate loci near the FRMD3 and CARS genes. Their identification implicates previously unsuspected pathways in the pathogenesis of this important late complication of type 1 diabetes.
doi:10.2337/db08-1514
PMCID: PMC2682673  PMID: 19252134

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