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1.  Multiple Functional Polymorphisms in the G6PC2 Gene Contribute to the Association with Higher Fasting Plasma Glucose Levels 
Diabetologia  2013;56(6):1306-1316.
We previously identified the G6PC2 locus as a strong determinant of fasting plasma glucose (FPG) and showed that a common G6PC2 intronic single nucleotide polymorphism (SNP) (rs560887) and two common G6PC2 promoter SNPs (rs573225 and rs13431652) are highly associated with FPG. However, these promoter SNPs have complex effects on G6PC2 fusion gene expression, and our data suggested that only rs13431652 is a potentially causative SNP. Here we examine the effect of rs560887 on G6PC2 pre-mRNA splicing and the contribution of an additional common G6PC2 promoter SNP, rs2232316, to the association signal.
Mini-gene analyzes characterized the effect of rs560887 on G6PC2 pre-mRNA splicing. Fusion gene and gel retardation analyses characterized the effect of rs2232316 on G6PC2 promoter activity and transcription factor binding. The genetic association of rs2232316 with FPG variation was assessed using regression adjusted for age, gender and body mass index in 4,220 Europeans with normal FPG.
Results & Conclusions
The rs560887-G allele was shown to enhance G6PC2 pre-mRNA splicing while the rs2232316-A allele enhanced G6PC2 transcription by promoting Foxa2 binding. Genetic analyses provide evidence for association of the rs2232316-A allele with increased FPG (β=0.04 mmol/l; P=4.3×10−3) as part of the same signal as rs560887, rs573225 and rs13431652. As with rs13431652 the in situ functional data with rs560887 and rs2232316 are in accord with the putative function of G6PC2 in pancreatic islets and suggest that all three are potentially causative SNPs that contribute to the association between G6PC2 and FPG.
PMCID: PMC4106008  PMID: 23508304
beta cell; fasting plasma glucose; G6PC2/IGRP; pancreatic islet; splicing; transcription
2.  Genetic and Functional Assessment of the Role of the rs13431652-A and rs573225-A Alleles in the G6PC2 Promoter That Are Strongly Associated With Elevated Fasting Glucose Levels 
Diabetes  2010;59(10):2662-2671.
Genome-wide association studies have identified a single nucleotide polymorphism (SNP), rs560887, located in a G6PC2 intron that is highly correlated with variations in fasting plasma glucose (FPG). G6PC2 encodes an islet-specific glucose-6-phosphatase catalytic subunit. This study examines the contribution of two G6PC2 promoter SNPs, rs13431652 and rs573225, to the association signal.
We genotyped 9,532 normal FPG participants (FPG <6.1 mmol/l) for three G6PC2 SNPs, rs13431652 (distal promoter), rs573225 (proximal promoter), rs560887 (3rd intron). We used regression analyses adjusted for age, sex, and BMI to assess the association with FPG and haplotype analyses to assess comparative SNP contributions. Fusion gene and gel retardation analyses characterized the effect of rs13431652 and rs573225 on G6PC2 promoter activity and transcription factor binding.
Genetic analyses provide evidence for a strong contribution of the promoter SNPs to FPG variability at the G6PC2 locus (rs13431652: β = 0.075, P = 3.6 × 10−35; rs573225 β = 0.073 P = 3.6 × 10−34), in addition to rs560887 (β = 0.071, P = 1.2 × 10−31). The rs13431652-A and rs573225-A alleles promote increased NF-Y and Foxa2 binding, respectively. The rs13431652-A allele is associated with increased FPG and elevated promoter activity, consistent with the function of G6PC2 in pancreatic islets. In contrast, the rs573225-A allele is associated with elevated FPG but reduced promoter activity.
Genetic and in situ functional data support a potential role for rs13431652, but not rs573225, as a causative SNP linking G6PC2 to variations in FPG, though a causative role for rs573225 in vivo cannot be ruled out.
PMCID: PMC3279535  PMID: 20622168
3.  Additive Effects of Genetic Variation in GCK and G6PC2 on Insulin Secretion and Fasting Glucose 
Diabetes  2009;58(12):2946-2953.
Glucokinase (GCK) and glucose-6-phosphatase catalytic subunit 2 (G6PC2) regulate the glucose-cycling step in pancreatic β-cells and may regulate insulin secretion. GCK rs1799884 and G6PC2 rs560887 have been independently associated with fasting glucose, but their interaction on glucose-insulin relationships is not well characterized.
We tested whether these variants are associated with diabetes-related quantitative traits in Mexican Americans from the BetaGene Study and attempted to replicate our findings in Finnish men from the METabolic Syndrome in Men (METSIM) Study.
rs1799884 was not associated with any quantitative trait (corrected P > 0.1), whereas rs560887 was significantly associated with the oral glucose tolerance test 30-min incremental insulin response (30′ Δinsulin, corrected P = 0.021). We found no association between quantitative traits and the multiplicative interaction between rs1799884 and rs560887 (P > 0.26). However, the additive effect of these single nucleotide polymorphisms was associated with fasting glucose (corrected P = 0.03) and 30′ Δinsulin (corrected P = 0.027). This additive association was replicated in METSIM (fasting glucose, P = 3.5 × 10−10 30′ Δinsulin, P = 0.028). When we examined the relationship between fasting glucose and 30′ Δinsulin stratified by GCK and G6PC2, we noted divergent changes in these quantitative traits for GCK but parallel changes for G6PC2. We observed a similar pattern in METSIM.
Our data suggest that variation in GCK and G6PC2 have additive effects on both fasting glucose and insulin secretion.
PMCID: PMC2780888  PMID: 19741163
4.  Racial and ethnic disparities in the control of cardiovascular disease risk factors in Southwest American veterans with type 2 diabetes: the Diabetes Outcomes in Veterans Study 
Racial/ethnic disparities in cardiovascular disease complications have been observed in diabetic patients. We examined the association between race/ethnicity and cardiovascular disease risk factor control in a large cohort of insulin-treated veterans with type 2 diabetes.
We conducted a cross-sectional observational study at 3 Veterans Affairs Medical Centers in the American Southwest. Using electronic pharmacy databases, we randomly selected 338 veterans with insulin-treated type 2 diabetes. We collected medical record and patient survey data on diabetes control and management, cardiovascular disease risk factors, comorbidity, demographics, socioeconomic factors, psychological status, and health behaviors. We used analysis of variance and multivariate linear regression to determine the effect of race/ethnicity on glycemic control, insulin treatment intensity, lipid levels, and blood pressure control.
The study cohort was comprised of 72 (21.3%) Hispanic subjects (H), 35 (10.4%) African Americans (AA), and 226 (67%) non-Hispanic whites (NHW). The mean (SD) hemoglobin A1c differed significantly by race/ethnicity: NHW 7.86 (1.4)%, H 8.16 (1.6)%, AA 8.84 (2.9)%, p = 0.05. The multivariate-adjusted A1c was significantly higher for AA (+0.93%, p = 0.002) compared to NHW. Insulin doses (unit/day) also differed significantly: NHW 70.6 (48.8), H 58.4 (32.6), and AA 53.1 (36.2), p < 0.01. Multivariate-adjusted insulin doses were significantly lower for AA (-17.8 units/day, p = 0.01) and H (-10.5 units/day, p = 0.04) compared to NHW. Decrements in insulin doses were even greater among minority patients with poorly controlled diabetes (A1c ≥ 8%). The disparities in glycemic control and insulin treatment intensity could not be explained by differences in age, body mass index, oral hypoglycemic medications, socioeconomic barriers, attitudes about diabetes care, diabetes knowledge, depression, cognitive dysfunction, or social support. We found no significant racial/ethnic differences in lipid or blood pressure control.
In our cohort, insulin-treated minority veterans, particularly AA, had poorer glycemic control and received lower doses of insulin than NHW. However, we found no differences for control of other cardiovascular disease risk factors. The diabetes treatment disparity could be due to provider behaviors and/or patient behaviors or preferences. Further research with larger sample sizes and more geographically diverse populations are needed to confirm our findings.
PMCID: PMC1513224  PMID: 16716235
5.  Racial and Ethnic Differences in an Estimated Measure of Insulin Resistance Among Individuals With Type 1 Diabetes 
Diabetes Care  2009;33(3):614-619.
Insulin resistance is greater in racial/ethnic minorities than in non-Hispanic whites (NHWs) for those with and without type 2 diabetes. Because previous research on insulin resistance in type 1 diabetes was limited to NHWs, racial/ethnic variation in an estimated measure of insulin resistance in type 1 diabetes was determined.
The sample included 79 individuals with type 1 diabetes diagnosed at age <18 years (32.9% NHWs, 46.8% non-Hispanic black [NHB], 7.6% other/mixed, and 12.7% Hispanic) and their families. Estimated glucose disposal rate (eGDR) (milligrams per kilogram per minute; a lower eGDR indicates greater insulin resistance) was calculated using A1C, waist circumference, and hypertension status.
Mean current age was 13.5 years (range 3.2–32.5) and diabetes duration was 5.7 years (0.1–19.9). eGDR was inversely associated with age. Compared with that in NHWs, age-adjusted eGDR was significantly lower among nonwhites (NHB, other/mixed, and Hispanic: Δ = −1.83, P = 0.0006). Age-adjusted eGDR was negatively associated with body fat, triglycerides, urinary albumin/creatinine, acanthosis nigricans, parental obesity, and parental insulin resistance and positively related to HDL and sex hormone–binding globulin. In multivariable analysis, lower eGDR was significantly associated with older age, nonwhite race/ethnicity, acanthosis, and lower HDL.
Minorities with type 1 diabetes are significantly more insulin resistant, as measured by eGDR, than NHWs. Exploring potential mechanisms, including disparities in care and/or physiological variation, may contribute to preventing racial/ethnic differences in insulin resistance–associated outcomes.
PMCID: PMC2827519  PMID: 20007942
6.  Cardiometabolic Plasticity in Response to a Short-Term Diet and Exercise Intervention in Young Hispanic and NonHispanic White Adults 
PLoS ONE  2011;6(2):e16987.
Young adult Mexican Americans (MA) exhibit lower insulin sensitivity (Si) than nonHispanic whites (NHW), even when controlling for fitness and adiposity. It is unclear if MA are as responsive to the same lifestyle intervention as NHW.
We developed a model to examine cardiometabolic plasticity (i.e., changes in Si and plasma lipids) in MA compared to NHW adults in response to a diet-exercise intervention.
Sedentary subjects (20 NHW: 11F, 9M, 23.0 y, 25.5 kg/m2; 17 MA: 13F, 4M, 22.7 y, 25.4 kg/m2) consumed their habitual diets and remained sedentary for 7 days, after which fasting blood samples were obtained, and a 3-h intravenous glucose tolerance test (IVGTT) was performed with the insulin area under the curve (IAUC) used to estimate Si. Subjects then completed a 7-day diet/exercise intervention (diet: low saturated fat, low added sugar, high fiber; exercise: cycling, six total sessions lasting 40–45 min/session at 65% VO2 max). Pre-intervention tests were repeated.
Pre intervention IAUC was 28% higher (p<0.05) in MA (IAUC pre  =  2298 µU*180 min/mL) than in NHW (IAUC = 1795 µU*180 min/mL). Following the intervention, there was a significant reduction in IAUC in MA (29%) and NHW (32%), however, the IAUC remained higher (p<0.05) for MA (post  = 1635 µU*180 min/mL) than for NHW (post = 1211 µU*180 min/mL). Pre test plasma lipids were not different in MA compared to NHW. Plasma cholesterol and TG concentrations significantly improved in both groups, but concentrations of low density lipoprotein-cholesterol and small dense LDL particles significantly improved only in the NHW.
With a short-term diet-exercise intervention, the magnitude of improvements in Si and serum cholesterol and TG in Hispanics are similar to those in NHW. However, because at the outset MA were less insulin sensitive compared to NHW, within the short timeframe studied the ethnic gap in insulin sensitivity remained.
PMCID: PMC3043099  PMID: 21364957
7.  Metabolic Syndrome and the Burden of Cardiovascular Disease in Caribbean Hispanic Women Living in Northern Manhattan: A Red Flag for Education 
Metabolic syndrome has the highest prevalence among Mexican-American women. Little information is available for Caribbean Hispanics, the largest and fastest growing ethnic minority in the United States. We sought to evaluate the frequency of metabolic syndrome and its relationship with race/ethnicity, socioeconomic position, and education in women of largely Caribbean Hispanic origin.
There were 204 women enrolled in a cross-sectional study who had demographics, fasting glucose, lipid profile, waist circumference, and blood pressure determined. Metabolic syndrome (defined by the National Cholesterol Education Program/Adult Treatment Panel III [NCEP/ATP III]) was analyzed using univariate and multivariate logistic regression to test age, race/ethnicity, education, health insurance, and residence on the risk of metabolic syndrome. A P value <0.05 was considered significant.
Mean age was 58 ± 11 years, Hispanic 44.1% (93% Caribbean), non-Hispanic white (NHW) 38.7%, and non-Hispanic black 9.8%. Education was some high school (
Metabolic syndrome showed an alarming rate in less educated Caribbean Hispanic women and was independently associated with lower education level.
PMCID: PMC3141735  PMID: 19558272
BMC Medical Genetics  2012;13:30.
Hemoglobin A1c (HbA1c) levels diagnose diabetes, predict mortality and are associated with ten single nucleotide polymorphisms (SNPs) in white individuals. Genetic associations in other race groups are not known. We tested the hypotheses that there is race-ethnic variation in 1) HbA1c-associated risk allele frequencies (RAFs) for SNPs near SPTA1, HFE, ANK1, HK1, ATP11A, FN3K, TMPRSS6, G6PC2, GCK, MTNR1B; 2) association of SNPs with HbA1c and 3) association of SNPs with mortality.
We studied 3,041 non-diabetic individuals in the NHANES (National Health and Nutrition Examination Survey) III. We stratified the analysis by race/ethnicity (NHW: non-Hispanic white; NHB: non-Hispanic black; MA: Mexican American) to calculate RAF, calculated a genotype score by adding risk SNPs, and tested associations with SNPs and the genotype score using an additive genetic model, with type 1 error = 0.05.
RAFs varied widely and at six loci race-ethnic differences in RAF were significant (p < 0.0002), with NHB usually the most divergent. For instance, at ATP11A, the SNP RAF was 54% in NHB, 18% in MA and 14% in NHW (p < .0001). The mean genotype score differed by race-ethnicity (NHW: 10.4, NHB: 11.0, MA: 10.7, p < .0001), and was associated with increase in HbA1c in NHW (β = 0.012 HbA1c increase per risk allele, p = 0.04) and MA (β = 0.021, p = 0.005) but not NHB (β = 0.007, p = 0.39). The genotype score was not associated with mortality in any group (NHW: OR (per risk allele increase in mortality) = 1.07, p = 0.09; NHB: OR = 1.04, p = 0.39; MA: OR = 1.03, p = 0.71).
At many HbA1c loci in NHANES III there is substantial RAF race-ethnic heterogeneity. The combined impact of common HbA1c-associated variants on HbA1c levels varied by race-ethnicity, but did not influence mortality.
PMCID: PMC3433372  PMID: 22540250
Pediatric diabetes  2012;14(2):121-128.
To examine HLA DRB1-DQB1 haplotypes within a multi-ethnic cohort and assess their association with characteristics of diabetes onset.
The sample included 1,662 participants from the SEARCH for Diabetes in Youth Study who tested positive for GADA and/or IA-2A autoantibodies. Blood drawn at the study visit was used to measure fasting C-peptide and genotype HLA DRB1 and DQB1 loci. Diabetic ketoacidosis (DKA) at diagnosis was determined from medical records. Multivariable linear and logistic regression models stratified by race/ethnicity were used to assess associations with DRB1-DQB1 haplotypes.
The frequency of DRB1*03 susceptibility haplotypes ranged 27.5–28.9% in all racial/ethnic groups. The frequency of susceptibility DRB1*04-DQB1*0302 was higher in non-Hispanic white (NHW; 34.1%) and Hispanic (38.9%) compared to non-Hispanic black (NHB; 20.8%) youth. Neutral and protective haplotypes were low frequency in all groups. DBR1*03 haplotypes were associated with younger age at diagnosis in NHW and positivity for multiple autoantibodies in Hispanics. DRB1*04-DQB1*0302 haplotypes were associated with multiple autoantibody positivity in NHW and Hispanics, and lower fasting C-peptide and higher odds of DKA in Hispanics only. Although protective DRB1*04-DQB1*0301 haplotypes were associated with older age at diagnosis in NHW, they were also associated with multiple autoantibody positivity in these youth. Protective DRB1*13 haplotypes were associated with decreased odds of multiple autoantibody positivity in NHB youth.
The distribution of DRB1-DQB1 haplotypes and their association with onset-related characteristics of autoimmune diabetes varies across major racial/ethnic groups in the United States. This may contribute to variation in clinical presentation of autoimmune diabetes by race/ethnicity.
PMCID: PMC3932799  PMID: 22913598
HLA; type 1 diabetes; autoantibodies; diabetic ketoacidosis; fasting C-peptide
Concept of Diabetes Mellitus:
Diabetes mellitus is a group of diseases associated with various metabolic disorders, the main feature of which is chronic hyperglycemia due to insufficient insulin action. Its pathogenesis involves both genetic and environmental factors. The long‐term persistence of metabolic disorders can cause susceptibility to specific complications and also foster arteriosclerosis. Diabetes mellitus is associated with a broad range of clinical presentations, from being asymptomatic to ketoacidosis or coma, depending on the degree of metabolic disorder.
Classification (Tables 1 and 2, and Figure 1):
 Etiological classification of diabetes mellitus and glucose metabolism disorders
Note: Those that cannot at present be classified as any of the above are called unclassifiable.
The occurrence of diabetes‐specific complications has not been confirmed in some of these conditions.
 Diabetes mellitus and glucose metabolism disorders due to other specific mechanisms and diseases
The occurrence of diabetes‐specific complications has not been confirmed in some of these conditions.
 A scheme of the relationship between etiology (mechanism) and patho‐physiological stages (states) of diabetes mellitus. Arrows pointing right represent worsening of glucose metabolism disorders (including onset of diabetes mellitus). Among the arrow lines, indicates the condition classified as ‘diabetes mellitus’. Arrows pointing left represent improvement in the glucose metabolism disorder. The broken lines indicate events of low frequency. For example, in type 2 diabetes mellitus, infection can lead to ketoacidosis and require temporary insulin treatment for survival. Also, once diabetes mellitus has developed, it is treated as diabetes mellitus regardless of improvement in glucose metabolism, therefore, the arrow lines pointing left are filled in black. In such cases, a broken line is used, because complete normalization of glucose metabolism is rare.
The classification of glucose metabolism disorders is principally derived from etiology, and includes staging of pathophysiology based on the degree of deficiency of insulin action. These disorders are classified into four groups: (i) type 1 diabetes mellitus; (ii) type 2 diabetes mellitus; (iii) diabetes mellitus due to other specific mechanisms or diseases; and (iv) gestational diabetes mellitus. Type 1 diabetes is characterized by destruction of pancreatic β‐cells. Type 2 diabetes is characterized by combinations of decreased insulin secretion and decreased insulin sensitivity (insulin resistance). Glucose metabolism disorders in category (iii) are divided into two subgroups; subgroup A is diabetes in which a genetic abnormality has been identified, and subgroup B is diabetes associated with other pathologic disorders or clinical conditions. The staging of glucose metabolism includes normal, borderline and diabetic stages depending on the degree of hyperglycemia occurring as a result of the lack of insulin action or clinical condition. The diabetic stage is then subdivided into three substages: non‐insulin‐ requiring, insulin‐requiring for glycemic control, and insulin‐dependent for survival. The two former conditions are called non‐insulin‐dependent diabetes and the latter is known as insulin‐dependent diabetes. In each individual, these stages may vary according to the deterioration or the improvement of the metabolic state, either spontaneously or by treatment.
Diagnosis (Tables 3–7 and Figure 2):
 Criteria of fasting plasma glucose levels and 75 g oral glucose tolerance test 2‐h value
*Casual plasma glucose ≥200 mg/dL (≥11.1 mmol/L) and HbA1c≥6.5% are also regarded as to indicate diabetic type.
Even for normal type, if 1‐h value is 180 mg/dL (10.0 mmol/L), the risk of progression to diabetes mellitus is greater than for <180 mg/dL (10.0 mmol/L) and should be treated as with borderline type (follow‐up observation, etc.). Fasting plasma glucose level of 100–109 mg/dL (5.5–6.0 mmol/L) is called ‘high‐normal’: within the range of normal fasting plasma glucose.
Plasma glucose level after glucose load in oral glucose tolerance test (OGTT) is not included in casual plasma glucose levels. The value for HbA1c (%) is indicated with 0.4% added to HbA1c (JDS) (%).
 Procedures for diagnosing diabetes mellitus
*The value for HbA1c (%) is indicated with 0.4% added to HbA1c (JDS) (%). **Hyperglycemia must be confirmed in a non‐stressful condition. OGTT, oral glucose tolerance test.
 Disorders and conditions associated with low HbA1c values
 Situations where a 75‐g oral glucose tolerance test is recommended
*The value for HbA1c (%) is indicated with 0.4% added to HbA1c (JDS) (%).
 Definition and diagnostic criteria of gestational diabetes mellitus
(IADPSG Consensus Panel, Reference 42, partly modified with permission of Diabetes Care).
 Flow chart outlining steps in the clinical diagnosis of diabetes mellitus. *The value for HbA1c (%) is indicated with 0.4% added to HbA1c (JDS) (%).
Categories of the State of Glycemia:  Confirmation of chronic hyperglycemia is essential for the diagnosis of diabetes mellitus. When plasma glucose levels are used to determine the categories of glycemia, patients are classified as having a diabetic type if they meet one of the following criteria: (i) fasting plasma glucose level of ≥126 mg/dL (≥7.0 mmol/L); (ii) 2‐h value of ≥200 mg/dL (≥11.1 mmol/L) in 75 g oral glucose tolerance test (OGTT); or (iii) casual plasma glucose level of ≥200 mg/dL (≥11.1 mmol/L). Normal type is defined as fasting plasma glucose level of <110 mg/dL (<6.1 mmol/L) and 2‐h value of <140 mg/dL (<7.8 mmol/L) in OGTT. Borderline type (neither diabetic nor normal type) is defined as falling between the diabetic and normal values. According to the current revision, in addition to the earlier listed plasma glucose values, hemoglobin A1c (HbA1c) has been given a more prominent position as one of the diagnostic criteria. That is, (iv) HbA1c≥6.5% is now also considered to indicate diabetic type. The value of HbA1c, which is equivalent to the internationally used HbA1c (%) (HbA1c [NGSP]) defined by the NGSP (National Glycohemoglobin Standardization Program), is expressed by adding 0.4% to the HbA1c (JDS) (%) defined by the Japan Diabetes Society (JDS).
Subjects with borderline type have a high rate of developing diabetes mellitus, and correspond to the combination of impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) noted by the American Diabetes Association (ADA) and WHO. Although borderline cases show few of the specific complications of diabetes mellitus, the risk of arteriosclerosis is higher than those of normal type. When HbA1c is 6.0–6.4%, suspected diabetes mellitus cannot be excluded, and when HbA1c of 5.6–5.9% is included, it forms a group with a high risk for developing diabetes mellitus in the future, even if they do not have it currently.
Clinical Diagnosis:  1 If any of the criteria for diabetic type (i) through to (iv) is observed at the initial examination, the patient is judged to be ‘diabetic type’. Re‐examination is conducted on another day, and if ‘diabetic type’ is reconfirmed, diabetes mellitus is diagnosed. However, a diagnosis cannot be made only by the re‐examination of HbA1c alone. Moreover, if the plasma glucose values (any of criteria [i], [ii], or [iii]) and the HbA1c (criterion [iv]) in the same blood sample both indicate diabetic type, diabetes mellitus is diagnosed based on the initial examination alone. If HbA1c is used, it is essential that the plasma glucose level (criteria [i], [ii] or [iii]) also indicates diabetic type for a diagnosis of diabetes mellitus. When diabetes mellitus is suspected, HbA1c should be measured at the same time as examination for plasma glucose.2 If the plasma glucose level indicates diabetic type (any of [i], [ii], or [iii]) and either of the following conditions exists, diabetes mellitus can be diagnosed immediately at the initial examination.• The presence of typical symptoms of diabetes mellitus (thirst, polydipsia, polyuria, weight loss)• The presence of definite diabetic retinopathy3 If it can be confirmed that the above conditions 1 or 2 existed in the past, diabetes mellitus can be diagnosed or suspected regardless of the current test results.4 If the diagnosis of diabetes cannot be established by these procedures, the patient is followed up and re‐examined after an appropriate interval.5 The physician should assess not only the presence or absence of diabetes, but also its etiology and glycemic stage, and the presence and absence of diabetic complications or associated conditions.
Epidemiological Study:  For the purpose of estimating the frequency of diabetes mellitus, ‘diabetes mellitus’ can be substituted for the determination of ‘diabetic type’ from a single examination. In this case, HbA1c≥6.5% alone can be defined as ‘diabetes mellitus’.
Health Screening:  It is important not to misdiagnose diabetes mellitus, and thus clinical information such as family history and obesity should be referred to at the time of screening in addition to an index for plasma glucose level.
Gestational Diabetes Mellitus:  There are two hyperglycemic disorders in pregnancy: (i) gestational diabetes mellitus (GDM); and (ii) diabetes mellitus. GDM is diagnosed if one or more of the following criteria is met in a 75 g OGTT during pregnancy:
1 Fasting plasma glucose level of ≥92 mg/dL (5.1 mmol/L)2 1‐h value of ≥180 mg/dL (10.0 mmol/L)3 2‐h value of ≥153 mg/dL (8.5 mmol/L)
However, diabetes mellitus that is diagnosed by the clinical diagnosis of diabetes mellitus defined earlier is excluded from GDM. (J Diabetes Invest, doi: 10.1111/j.2040‐1124.2010.00074.x, 2010)
PMCID: PMC4020724  PMID: 24843435
Diabetes mellitus; Clinical diagnosis; HbA1c
Annals of Epidemiology  2011;21(12):899-906.
To examine the mortality risk associated with diabetes in the Mexico City Diabetes Study (MCDS) and the San Antonio Heart Study (SAHS).
Prospective cohorts conducted 1990-2007 in MCDS and 1979-2000 in SAHS. Mortality risk was examined using Cox proportional hazard models in 1,402 non-Hispanic whites (NHW), 1,907 U.S.-born Mexican Americans (MA), 444 Mexican-born MA, 2,281 Mexico City residents (MCR) between the ages of 35 and 64.
Age- and sex-adjusted mortality HRs comparing U.S.-born MA, Mexican-born MA and MCR to NHW were 1.09 (95% CI: 0.86, 1.37), 1.23 (95% CI: 0.86, 1.76) and 0.97 (95% CI: 0.77, 1.23), respectively, in non-diabetic individuals; in contrast, mortality risk varied in diabetic individuals with respective HRs of 1.77 (95% CI: 1.20, 2.61), 1.08 (95% CI: 0.59, 1.97) and 2.27 (95% CI: 1.53, 3.35) (interaction p-value=0.0003). Excluding Mexican-born MA and non-diabetic individuals, controlling for medication use, insulin use, fasting glucose levels and duration of diabetes explained a significant proportion of the mortality differential (HRs relative to NHW were 1.31 (95% CI: 0.87, 1.98) in U.S.-born MA and 1.38 (95% CI: 0.89, 2.12) in MCR).
This study provides evidence that diabetes is more lethal in U.S.-born MA and MCR than in NHW.
PMCID: PMC3271801  PMID: 21840730
Journal of General Internal Medicine  2011;26(11):1278-1283.
Few studies have examined racial/ethnic differences in blood pressure (BP) control over time, especially in an equal access system. We examined racial/ethnic differences in longitudinal BP control in Veterans with type 2 diabetes.
We collected data on a retrospective cohort of 5,319 Veterans with type 2 diabetes and initially uncontrolled BP followed from 1996 to 2006 at a Veterans Administration (VA) facility in the southeastern United States. The mean blood pressure value for each subject for each year was used for the analysis with BP control defined as <140/<90 mmHg. The primary outcome measure was proportion with controlled BP. The main predictor variable was race/ethnicity categorized as non-Hispanic White (NHW), non-Hispanic Black (NHB), or Hispanic/Other (H/O). Other covariates included age, gender, employment, marital status, service connectedness, and ICD-9 coded medical and psychiatric comorbidities. Generalized linear mixed models were used to assess the relationship between race/ethnicity and BP control after adjusting for covariates.
Mean follow-up was 5.0 years. The sample was 46% NHW, 26% NHB, 19% H/O, and 9% unknown. The average age was 68 years. In the final model, after adjusting for covariates, NHB race (OR = 1.38, 95%CI: 1.2, 1.6) and H/O race (OR = 1.57, 95% CI: 1.3, 1.8) were associated with increased likelihood of poor BP control (>140/>90 mmHg) over time compared to NHW patients.
Ethnic minority Veterans with type 2 diabetes have significantly increased odds of poor BP control over ∼5 years of follow-up compared to their non-Hispanic White counterparts independent of sociodemographic factors and comorbidity patterns.
PMCID: PMC3208462  PMID: 21671132
blood pressure control; diabetes; epidemiology; race/ethnicity
Diabetes  2009;58(11):2703-2708.
Fasting plasma glucose and risk of type 2 diabetes are higher among Indian Asians than among European and North American Caucasians. Few studies have investigated genetic factors influencing glucose metabolism among Indian Asians.
We carried out genome-wide association studies for fasting glucose in 5,089 nondiabetic Indian Asians genotyped with the Illumina Hap610 BeadChip and 2,385 Indian Asians (698 with type 2 diabetes) genotyped with the Illumina 300 BeadChip. Results were compared with findings in 4,462 European Caucasians.
We identified three single nucleotide polymorphisms (SNPs) associated with glucose among Indian Asians at P < 5 × 10−8, all near melatonin receptor MTNR1B. The most closely associated was rs2166706 (combined P = 2.1 × 10−9), which is in moderate linkage disequilibrium with rs1387153 (r2 = 0.60) and rs10830963 (r2 = 0.45), both previously associated with glucose in European Caucasians. Risk allele frequency and effect sizes for rs2166706 were similar among Indian Asians and European Caucasians: frequency 46.2 versus 45.0%, respectively (P = 0.44); effect 0.05 (95% CI 0.01–0.08) versus 0.05 (0.03–0.07 mmol/l), respectively, higher glucose per allele copy (P = 0.84). SNP rs2166706 was associated with type 2 diabetes in Indian Asians (odds ratio 1.21 [95% CI 1.06–1.38] per copy of risk allele; P = 0.006). SNPs at the GCK, GCKR, and G6PC2 loci were also associated with glucose among Indian Asians. Risk allele frequencies of rs1260326 (GCKR) and rs560887 (G6PC2) were higher among Indian Asians compared with European Caucasians.
Common genetic variation near MTNR1B influences blood glucose and risk of type 2 diabetes in Indian Asians. Genetic variation at the MTNR1B, GCK, GCKR, and G6PC2 loci may contribute to abnormal glucose metabolism and related metabolic disturbances among Indian Asians.
PMCID: PMC2768158  PMID: 19651812
Diabetes  2009;58(12):2939-2945.
The goal of this study was to investigate whether the effects of common genetic variants associated with fasting glucose in adults are detectable in healthy children.
Single nucleotide polymorphisms in MTNR1B (rs10830963), G6PC2 (rs560887), and GCK (rs4607517) were genotyped in 2,025 healthy European children aged 9–11 and 14–16 years. Associations with fasting glucose, insulin, homeostasis model assessment (HOMA)-insulin resistance (IR) and HOMA-B were investigated along with those observed for type 2 diabetes variants available in this study (CDKN2A/B, IGF2BP2, CDKAL1, SLC30A8, HHEX-IDE, and Chr 11p12).
Strongest associations were observed for G6PC2 and MTNR1B, with mean fasting glucose levels (95% CI) being 0.084 (0.06–0.11) mmol/l, P = 7.9 × 10−11 and 0.069 (0.04–0.09) mmol/l, P = 1.9 × 10−7 higher per risk allele copy, respectively. A similar but weaker trend was observed for GCK (0.028 [−0.006 to 0.06] mmol/l, P = 0.11). All three variants were associated with lower β-cell function (HOMA-B P = 9.38 × 10−5, 0.004, and 0.04, respectively). SLC30A8 (rs13266634) was the only type 2 diabetes variant associated with higher fasting glucose (0.033 mmol/l [0.01–0.06], P = 0.01). Calculating a genetic predisposition score adding the number of risk alleles of G6PC2, MTNR1B, GCK, and SLC30A8 showed that glucose levels were successively higher in children carrying a greater number of risk alleles (P = 7.1 × 10−17), with mean levels of 5.34 versus 4.91 mmol/l comparing children with seven alleles (0.6% of all children) to those with none (0.5%). No associations were found for fasting insulin or HOMA-IR with any of the variants.
The effects of common polymorphisms influencing fasting glucose are apparent in healthy children, whereas the presence of multiple risk alleles amounts to a difference of >1 SD of fasting glucose.
PMCID: PMC2780884  PMID: 19741166
Although early recognition and treatment of diabetes may be essential to prevent complications, roughly one-fifth of diabetes remains undiagnosed.
Examine cardio-metabolic risk factors and their control in non-Hispanic white (NHW), non-Hispanic black (NHB) and Mexican American (MA) individuals with undiagnosed diabetes.
Nationally representative cross-sectional study of participants in the National Health and Nutrition Examination Survey (NHANES) continuous cycles conducted 1999 through 2008.
Of 22,621 non-pregnant individuals aged ≥20 years, 2521 had diagnosed diabetes. Of the remaining 20,100 individuals, 17,963 had HbA1c measured, 551 of whom were classified as having undiagnosed diabetes and comprise the study population.
Main Measures
Undiagnosed diabetes was defined as HbA1c ≥ 6.5% without a self-report of physician diagnosed diabetes. Cardio-metabolic risk factor control was examined using regression methods for complex survey data.
Key Results
Among individuals with undiagnosed diabetes, mean HbA1c level was 7.7% (95% CI: 7.5, 7.9), 19.3% (95% CI: 14.2, 24.3) smoked, 59.7% (95% CI: 54.5, 64.8%) had hypertension and 96.5% (95% CI: 94.6, 98.4%) had dyslipidemia. Lipid profiles were remarkably different across racial-ethnic groups: NHB had the highest LDL- and HDL-cholesterol, but the lowest triglycerides, while MA had the highest triglycerides and the lowest LDL-cholesterol. After adjusting for age, sex, NHANES examination cycle and use of either blood pressure or lipid medication, the odds of having blood pressure ≥130/80 mmHg was higher in NHB [1.92 (95% CI: 1.09, 3.55)] than NHW, while the odds of having LDL-cholesterol >100 mg/dl was higher in NHW[2.93 (95% CI: 1.37, 6.24)] and NHB[3.34 (95% CI: 1.08, 10.3)] than MA.
In a nationally representative sample of individuals with undiagnosed diabetes, cardio-metabolic risk factor levels were high across all racial/ethnic groups, but NHB and MA had poorer control compared to NHW. Interventions that target identification of diabetes and treatment of cardio-metabolic risk factors are needed.
PMCID: PMC3403154  PMID: 22415867
undiagnosed diabetes; disparities; cardio-metabolic risk; HbA1c
Diabetes  2010;60(1):345-354.
To assess whether recently discovered genetic loci associated with hyperglycemia also predict long-term changes in glycemic traits.
Sixteen fasting glucose-raising loci were genotyped in middle-aged adults from the Gene x Lifestyle interactions And Complex traits Involved in Elevated disease Risk (GLACIER) Study, a population-based prospective cohort study from northern Sweden. Genotypes were tested for association with baseline fasting and 2-h postchallenge glycemia (N = 16,330), and for changes in these glycemic traits during a 10-year follow-up period (N = 4,059).
Cross-sectional directionally consistent replication with fasting glucose concentrations was achieved for 12 of 16 variants; 10 variants were also associated with impaired fasting glucose (IFG) and 7 were independently associated with 2-h postchallenge glucose concentrations. In prospective analyses, the effect alleles at four loci (GCK rs4607517, ADRA2A rs10885122, DGKB-TMEM195 rs2191349, and G6PC2 rs560887) were nominally associated with worsening fasting glucose concentrations during 10-years of follow-up. MTNR1B rs10830963, which was predictive of elevated fasting glucose concentrations in cross-sectional analyses, was associated with a protective effect on postchallenge glucose concentrations during follow-up; however, this was only when baseline fasting and 2-h glucoses were adjusted for. An additive effect of multiple risk alleles on glycemic traits was observed: a weighted genetic risk score (80th vs. 20th centiles) was associated with a 0.16 mmol/l (P = 2.4 × 10−6) greater elevation in fasting glucose and a 64% (95% CI: 33–201%) higher risk of developing IFG during 10 years of follow-up.
Our findings imply that genetic profiling might facilitate the early detection of persons who are genetically susceptible to deteriorating glucose control; studies of incident type 2 diabetes and discrete cardiovascular end points will help establish whether the magnitude of these changes is clinically relevant.
PMCID: PMC3012192  PMID: 20870969
Increased fasting plasma glucose (FPG), which includes impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and diabetes, is a risk factor for arterial stiffness. While IFG is widely accepted as a cardiovascular risk factor, recent studies have argued that subjects with high-normal glucose level were characterized by a high incidence of cardiovascular disease. The purpose of this study is to investigate the relationship between FPG and arterial stiffness in non-diabetic healthy subjects.
We recruited 697 subjects who visited the health promotion center of a university hospital from May 2007 to August 2008. Age, sex, body mass index (BMI), resting heart rate, smoking habits, alcohol intake, exercise, blood pressure, medical history, FPG, lipid profile, high sensitivity C-reactive protein (hs-CRP), and Brachial-ankle pulse wave velocity (ba-PWV) were measured. We performed correlation and multiple linear regression analyses to divide the research subjects into quartiles: Q1(n = 172), 65 mg/dL ≤FPG < 84 mg/dL; Q2(n = 188), 84 mg/dL ≤FPG < 91 mg/dl; Q3(n = 199), 91 mg/dL ≤FPG < 100 mg/dL; Q4(n = 138), 100 mg/dL ≤FPG < 126 mg/dL.
FPG has an independent, positive association with ba-PWV in non-diabetic subjects after correcting for confounding variables, including age, sex, BMI, blood pressure, resting heart rate, hs-CRP, lipid profile, and behavioral habits. The mean ba-PWV of the high-normal glucose group (Q3, 1384 cm/s) was higher than that of the low-normal glucose group (1303 ± 196 cm/s vs.1328 ± 167 cm/s, P < 0.05). The mean ba-PWV value in the IFG group (1469 ± 220 cm/s) was higher than that in the normoglycemic group (P < 0.05, respectively).
An increase in FPG, even within the normal range, was associated with aggravated arterial stiffness. Further research is needed to determine the glycemic target value for the prevention of arterial stiffness in clinical and public health settings.
PMCID: PMC3098149  PMID: 21492487
HIV patients on HAART are prone to metabolic abnormalities, including insulin resistance, lipodystrophy and diabetes. This study purports to investigate the relationship of ethnicity and CD4+ T cell count attained after stable highly-active antiretroviral treatment (HAART) with glucose metabolism in hyperrtriglyceridemic HIV patients without a history of diabetes.
Demographic, anthropometric, clinical, endocrinologic, energy expenditure and metabolic measures were obtained in 199 multiethnic, healthy but hypertriglyceridemic HIV-infected patients [46% Hispanic, 17% African-American, 37% Non-Hispanic White (NHW)] on stable HAART without a history of diabetes. The relationship of glucose and insulin responses to ethnicity, CD4 strata (low (<300/cc) or moderate-to-high (≥ 300/cc)), and their interaction was determined.
African-Americans had significantly greater impairment of glucose tolerance (P < 0.05) and HbA1c levels (P < .001) than either Hispanics or NHWs. In multivariate models, after adjusting for confounders (age, sex, HIV/HAART duration, smoking, obesity, glucose, insulin and lipids), African-Americans and Hispanics had significantly higher HbA1c and 2-hour glucose levels than NHW’s. Demonstrating a significant interaction between ethnicity and CD4 count (P = 0.023), African Americans with CD4 <300/cc and Hispanics with CD4 ≥300/cc had the most impaired glucose response following oral glucose challenge.
Among hypertriglyceridemic HIV patients on HAART, African-Americans and Hispanics are at increased risk of developing diabetes. Ethnicity also interacts with CD4+ T cell count attained on stable HAART to affect post-challenge glycemic response.
PMCID: PMC3751670  PMID: 23607267
African American; Hispanic; Impaired glucose tolerance; HbA1c; Dyslipidemia
Risk factors for cardiovascular disease (CVD) derived from the Framingham study are widely used to guide preventive efforts. It remains unclear whether these risk factors predict CVD death in racial/ethnic minorities as well as they do in the predominately white Framingham cohorts.
Methods and Results
Using linked data from the National Health and Nutrition Examination Survey III (1988-1994) and the National Death Index, we developed Cox proportional-hazard models that predicted time to cardiovascular death separately for non-Hispanic white (NHW), non-Hispanic black (NHB) and Mexican American (MA) participants aged 40-80 with no previous CVD. We compared calibration and discrimination for the three racial/ethnic models. We also plotted predicted 10-year CVD mortality by age for the three racial/ethnic groups while holding other risk factors constant. 3437 NHW, 1854 NHB and 1834 MA subjects met inclusion criteria. Goodness of fit chi-square tests demonstrated adequate calibration for the three models (NHW, p=0.49; NHB, p=0.47; MA, p=0.55 and areas under the receiver operating characteristic curves demonstrated similar discrimination (c-statistics-NHW=0.8126; NHB=0.7679; and MA=0.7854). Older age was more strongly associated with CVD mortality in NHWs (HR-3.37, 95%CI-2.80, 4.05) than NHBs (HR-2.29, 95%CI-1.91, 2.75) and was intermediate in MAs (HR-2.46, 95%CI-1.95, 3.11). Predicted 10-year mortality was highest for NHBs across all age ranges and was higher for MAs than NHWs until late in the seventh decade.
Framingham risk factors predict CVD mortality equally well in NHWs, NHBs and MAs, but the strength of the association between individual risk factors and CVD mortality differs by race and ethnicity. When other risk factors are held constant, minority individuals are at higher risk of CVD mortality at younger ages than NHWs.
PMCID: PMC2853913  PMID: 20124526
Risk factors; cardiovascular diseases; prevention; epidemiology
Journal of Lipids  2011;2011:291954.
Background. Lipoprotein (a) [Lp(a)] is an independent risk factor for cardiovascular disease (CVD) in Non-Hispanic Whites (NHW). There are known racial/ethnic differences in Lp(a) levels, and the association of Lp(a) with CVD outcomes has not been examined in Asian Americans in the USA. Objective. We hypothesized that Lp(a) levels would differ in Asian Indians and Chinese Americans when compared to NHW and that the relationship between Lp(a) and CVD outcomes would be different in these Asian racial/ethnic subgroups when compared to NHW. Methods. We studied the outpatient electronic health records of 2022 NHW, 295 Asian Indians, and 151 Chinese adults age ≥18 y in Northern California in whom Lp(a) levels were assessed during routine clinical care from 2001 to 2008, excluding those who had received prescriptions for niacin (14.6%). Nonparametric methods were used to compare median Lp(a) levels. Significance was assessed at the P < .0001 level to account for multiple comparisons. CVD outcomes were defined as ischemic heart disease (IHD) (265 events), stroke (122), or peripheral vascular disease (PVD) (87). We used logistic regression to determine the relationship between Lp(a) and CVD outcomes. Results. Both Asian Indians (36 nmol/L) and NHW (29 nmol/L) had higher median Lp(a) levels than Chinese (22 nmol/L, P ≤ .0001 and P = .0032). When stratified by sex, the differences in median Lp(a) between these groups persisted in the 1761 men (AI v CH: P = .001, NHW v CH: P = .0018) but were not statistically significant in the 1130 women (AI v CH: P = .0402, NHW v CH: P = .0761). Asian Indians (OR = 2.0) and Chinese (OR = 4.8) exhibited a trend towards greater risk of IHD with high Lp(a) levels than NHW (OR = 1.4), but no relationship was statistically significant. Conclusion. Asian Indian and NHW men have higher Lp(a) values than Chinese men, with a trend toward, similar associations in women. High Lp(a) may be more strongly associated with IHD in Asian Indians and Chinese, although we did not have a sufficient number of outcomes to confirm this. Further studies should strive to elucidate the relationship between Lp(a) levels, CVD, and race/ethnicity among Asian subgroups in the USA.
PMCID: PMC3108091  PMID: 21660301
Korean Journal of Family Medicine  2012;33(3):152-156.
Testosterone levels are decreased in diabetic patients and recent studies have suggested that high-normal fasting glucose is a risk factor for cardiovascular disease. To further elucidate the relationship between plasma glucose and testosterone, we investigated the association between fasting plasma glucose (FPG) and endogenous sex hormones (serum total testosterone, sex hormone binding globulin, estradiol, and the ratio of testosterone to estradiol) in non-diabetic and pre-diabetic men.
This study included 388 men (age ≥ 40 years) who visited the health promotion center of a university hospital from May 2007 to August 2008. The subjects were divided into quartiles based on their FPG levels and correlation and multiple linear regression analyses were performed. Q1 (65 mg/dL ≤ FPG < 88 mg/dL), Q2 (88 mg/dL ≤ FPG < 94 mg/dL), Q3 (94 mg/dL ≤ FPG < 100 mg/dL) and Q4 (100 mg/dL ≤ FPG < 126 mg/dL).
FPG was independently, inversely associated with total testosterone in the non-diabetic population after adjusting for age, body mass index, smoking, and alcohol consumption (β = -0.082, P < 0.01). Among the quartiles, subjects in the high-normal FPG groups (Q2, Q3, and Q4 with FPG ≥ 88 mg/dL) had significantly decreased testosterone levels when compared with subjects in the normal FPG group (Q1 with FPG < 88 mg/dL, P < 0.005). Sex hormone binding globulin, estradiol and the ratio of testosterone to estradiol were not correlated with FPG.
Our study indicates that high-normal fasting glucose levels are associated with decreased testosterone levels in non-diabetic and pre-diabetic men.
PMCID: PMC3391640  PMID: 22787537
Glucose; Testosterone; Gonadal Steroid Hormones
Prokopenko, Inga | Langenberg, Claudia | Florez, Jose C | Saxena, Richa | Soranzo, Nicole | Thorleifsson, Gudmar | Loos, Ruth J F | Manning, Alisa K | Jackson, Anne U | Aulchenko, Yurii | Potter, Simon C | Erdos, Michael R | Sanna, Serena | Hottenga, Jouke-Jan | Wheeler, Eleanor | Kaakinen, Marika | Lyssenko, Valeriya | Chen, Wei-Min | Ahmadi, Kourosh | Beckmann, Jacques S | Bergman, Richard N | Bochud, Murielle | Bonnycastle, Lori L | Buchanan, Thomas A | Cao, Antonio | Cervino, Alessandra | Coin, Lachlan | Collins, Francis S | Crisponi, Laura | de Geus, Eco J C | Dehghan, Abbas | Deloukas, Panos | Doney, Alex S F | Elliott, Paul | Freimer, Nelson | Gateva, Vesela | Herder, Christian | Hofman, Albert | Hughes, Thomas E | Hunt, Sarah | Illig, Thomas | Inouye, Michael | Isomaa, Bo | Johnson, Toby | Kong, Augustine | Krestyaninova, Maria | Kuusisto, Johanna | Laakso, Markku | Lim, Noha | Lindblad, Ulf | Lindgren, Cecilia M | McCann, Owen T | Mohlke, Karen L | Morris, Andrew D | Naitza, Silvia | Orrù, Marco | Palmer, Colin N A | Pouta, Anneli | Randall, Joshua | Rathmann, Wolfgang | Saramies, Jouko | Scheet, Paul | Scott, Laura J | Scuteri, Angelo | Sharp, Stephen | Sijbrands, Eric | Smit, Jan H | Song, Kijoung | Steinthorsdottir, Valgerdur | Stringham, Heather M | Tuomi, Tiinamaija | Tuomilehto, Jaakko | Uitterlinden, André G | Voight, Benjamin F | Waterworth, Dawn | Wichmann, H-Erich | Willemsen, Gonneke | Witteman, Jacqueline C M | Yuan, Xin | Zhao, Jing Hua | Zeggini, Eleftheria | Schlessinger, David | Sandhu, Manjinder | Boomsma, Dorret I | Uda, Manuela | Spector, Tim D | Penninx, Brenda WJH | Altshuler, David | Vollenweider, Peter | Jarvelin, Marjo Riitta | Lakatta, Edward | Waeber, Gerard | Fox, Caroline S | Peltonen, Leena | Groop, Leif C | Mooser, Vincent | Cupples, L Adrienne | Thorsteinsdottir, Unnur | Boehnke, Michael | Barroso, Inês | Van Duijn, Cornelia | Dupuis, Josée | Watanabe, Richard M | Stefansson, Kari | McCarthy, Mark I | Wareham, Nicholas J | Meigs, James B | Abecasis, Gonçalo R
Nature genetics  2008;41(1):77-81.
To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 = × 10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 × 10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 × 10−7) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 × 10−57) and GCK (rs4607517, P = 1.0 × 10−25) loci.
PMCID: PMC2682768  PMID: 19060907
Prokopenko, Inga | Langenberg, Claudia | Florez, Jose C. | Saxena, Richa | Soranzo, Nicole | Thorleifsson, Gudmar | Loos, Ruth J.F. | Manning, Alisa K. | Jackson, Anne U. | Aulchenko, Yurii | Potter, Simon C. | Erdos, Michael R. | Sanna, Serena | Hottenga, Jouke-Jan | Wheeler, Eleanor | Kaakinen, Marika | Lyssenko, Valeriya | Chen, Wei-Min | Ahmadi, Kourosh | Beckmann, Jacques S. | Bergman, Richard N. | Bochud, Murielle | Bonnycastle, Lori L. | Buchanan, Thomas A. | Cao, Antonio | Cervino, Alessandra | Coin, Lachlan | Collins, Francis S. | Crisponi, Laura | de Geus, Eco JC | Dehghan, Abbas | Deloukas, Panos | Doney, Alex S F | Elliott, Paul | Freimer, Nelson | Gateva, Vesela | Herder, Christian | Hofman, Albert | Hughes, Thomas E. | Hunt, Sarah | Illig, Thomas | Inouye, Michael | Isomaa, Bo | Johnson, Toby | Kong, Augustine | Krestyaninova, Maria | Kuusisto, Johanna | Laakso, Markku | Lim, Noha | Lindblad, Ulf | Lindgren, Cecilia M. | McCann, Owen T. | Mohlke, Karen L. | Morris, Andrew D | Naitza, Silvia | Orrù, Marco | Palmer, Colin N A | Pouta, Anneli | Randall, Joshua | Rathmann, Wolfgang | Saramies, Jouko | Scheet, Paul | Scott, Laura J. | Scuteri, Angelo | Sharp, Stephen | Sijbrands, Eric | Smit, Jan H. | Song, Kijoung | Steinthorsdottir, Valgerdur | Stringham, Heather M. | Tuomi, Tiinamaija | Tuomilehto, Jaakko | Uitterlinden, André G. | Voight, Benjamin F. | Waterworth, Dawn | Wichmann, H.-Erich | Willemsen, Gonneke | Witteman, Jacqueline CM | Yuan, Xin | Zhao, Jing Hua | Zeggini, Eleftheria | Schlessinger, David | Sandhu, Manjinder | Boomsma, Dorret I | Uda, Manuela | Spector, Tim D. | Penninx, Brenda WJH | Altshuler, David | Vollenweider, Peter | Jarvelin, Marjo Riitta | Lakatta, Edward | Waeber, Gerard | Fox, Caroline S. | Peltonen, Leena | Groop, Leif C. | Mooser, Vincent | Cupples, L. Adrienne | Thorsteinsdottir, Unnur | Boehnke, Michael | Barroso, Inês | Van Duijn, Cornelia | Dupuis, Josée | Watanabe, Richard M. | Stefansson, Kari | McCarthy, Mark I. | Wareham, Nicholas J. | Meigs, James B. | Abecasis, Goncalo R.
Nature genetics  2008;41(1):77-81.
To identify novel genetic loci associated with fasting glucose concentrations, we examined the leading association signals in 10 genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding the melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G-allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95%CI 0.06–0.08) mmol/L in fasting glucose levels (P=3.2×10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P=1.1×10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05–1.12), per G allele P=3.3×10−7) in a meta-analysis of thirteen case-control studies totalling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P=1.1×10−57) and GCK (rs4607517, P=1.0×10−25) loci.
PMCID: PMC2682768  PMID: 19060907
Genetic epidemiology  2010;34(7):665-673.
Although GWAS have been performed in longitudinal studies, most used only a single trait measure. GWAS of fasting glucose have generally included only normoglycemic individuals. We examined the impact of both repeated measures and sample selection on GWAS in ARIC, a study which obtained four longitudinal measures of fasting glucose and included both individuals with and without prevalent diabetes. The sample included Caucasians and the Affymetrix 6.0 chip was used for genotyping. Sample sizes for GWAS analyses ranged from 8372 (first study visit) to 5782 (average fasting glucose). Candidate SNP analyses with SNPs identified through fasting glucose or diabetes GWAS were conducted in 9133 individuals, including 761 with prevalent diabetes. For a constant sample size, smaller p-values were obtained for the average measure of fasting glucose compared to values at any single visit, and two additional significant GWAS signals were detected. For four candidate SNPs (rs780094, rs10830963, rs7903146, and rs4607517), the strength of association between genotype and glucose was significantly (p-interaction < .05) different in those with and without prevalent diabetes and for all five fasting glucose candidate SNPs (rs780094, rs10830963, rs560887, rs4607517, rs13266634) the association with measured fasting glucose was more significant in the smaller sample without prevalent diabetes than in the larger combined sample of those with and without diabetes. This analysis demonstrates the potential utility of averaging trait values in GWAS studies and explores the advantage of using only individuals without prevalent diabetes in GWAS of fasting glucose.
PMCID: PMC2964401  PMID: 20839289
GWAS; fasting glucose; type 2 diabetes; sample selection
A genome-wide association study associated 5 genetic variants with hepatic steatosis (identified by computerized tomography) in individuals of European ancestry. We investigated whether these variants were associated with measures of hepatic steatosis (HS) in non-Hispanic white (NHW), non-Hispanic black, and Mexican American (MA) participants in the US population-based National Health and Nutrition Examination Survey III, phase 2.
We analyzed data from 4804 adults (1825 NHW, 1442 non-Hispanic black, and 1537 MA; 51.7% women; mean age at examination, 42.5 y); the weighted prevalence of HS was 37.3%. We investigated whether ultrasound-measured HS, with and without increased levels of alanine aminotransferase (ALT), or level of ALT alone, was associated with rs738409 (patatin-like phospholipase domain-containing protein 3 [PNPLA3]), rs2228603 (neurocan [NCAN]), rs12137855 (lysophospholipase-like 1), rs780094 (glucokinase regulatory protein [GCKR]), and rs4240624 (protein phosphatase 1, regulatory subunit 3b [PPP1R3B]) using regression modeling in an additive genetic model, controlling for age, age-squared, sex, and alcohol consumption.
The G allele of rs738409 (PNPLA3) and the T allele of rs780094 (GCKR) were associated with HS with a high level of ALT (odds ratio [OR], 1.36; P = .01; and OR, 1.30; P = .03, respectively). The A allele of rs4240624 (PPP1R3B) and the T allele of rs2228603 (NCAN) were associated with HS (OR, 1.28; P = .03; and OR, 1.40; P = .04, respectively). Variants of PNPLA3 and NCAN were associated with ALT level among all 3 ancestries. Some single-nucleotide polymorphisms were associated with particular races or ethnicities: variants in PNPLA3, NCAN, GCKR, and PPP1R3B were associated with NHW and variants in PNPLA3 were associated with MA. No variants were associated with NHB.
We used data from the National Health and Nutrition Examination Survey III to validate the association between rs738409 (PNPLA3), rs780094 (GCKR), and rs4240624 (PPP1R3B) with HS, with or without increased levels of ALT, among 3 different ancestries. Some, but not all, associations between variants in NCAN, lysophospholipase-like 1, GCKR, and PPP1R3B with HS (with and without increased ALT level) were significant within subpopulations.
PMCID: PMC4197011  PMID: 23416328
Nonalcoholic Fatty Liver Disease; Replication; Candidate Gene Study; Genome-wide Association Study; SNP

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