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OBJECTIVE: Automated algorithms to identify individuals with type 1 diabetes using electronic health records are increasingly used in biomedical research. It is not known whether the accuracy of these algorithms differs by self-reported race. We investigated whether polygenic scores improve identification of individuals with type 1 diabetes. RESEARCH DESIGN AND METHODS: We investigated two large hospital-based biobanks (Mass General Brigham [MGB] and BioMe) and identified individuals with type 1 diabetes using an established automated algorithm. We performed medical record reviews to validate the diagnosis of type 1 diabetes. We implemented two published polygenic scores for type 1 diabetes (developed in individuals of European or African ancestry). We assessed the classification algorithm before and after incorporating polygenic scores. RESULTS: The automated algorithm was more likely to incorrectly assign a diagnosis of type 1 diabetes in self-reported non-White individuals than in self-reported White individuals (odds ratio 3.45; 95% CI 1.54–7.69; P = 0.0026). After incorporating polygenic scores into the MGB Biobank, the positive predictive value of the type 1 diabetes algorithm increased from 70 to 97% for self-reported White individuals (meaning that 97% of those predicted to have type 1 diabetes indeed had type 1 diabetes) and from 53 to 100% for self-reported non-White individuals. Similar results were found in BioMe. CONCLUSIONS: Automated phenotyping algorithms may exacerbate health disparities because of an increased risk of misclassification of individuals from underrepresented populations. Polygenic scores may be used to improve the performance of phenotyping algorithms and potentially reduce this disparity. [ABSTRACT FROM AUTHOR]

The pathogenesis of type 2 diabetes (T2D) might change with increasing age. Here, we used a stratification based on age of diagnosis to gain insight into the genetics and causal risk factors of T2D across different age-groups. We performed genome-wide association studies (GWAS) on T2D and T2D subgroups based on age of diagnosis (<50, 50-60, 60-70, and >70 years) (total of 24,986 cases). As control subjects, participants were at least 70 years of age at the end of follow-up without developing T2D (N =187,130). GWAS identified 208 independent lead single nucleotide polymorphism (SNPs) mapping to 69 loci associated with T2D (P < 1.0e-8). Among others, SNPs mapped to CDKN2B-AS1 and multiple independent SNPs mapped to TCF7L2 were more strongly associated with cases diagnosed after age 70 years than with cases diagnosed before age 50 years. Based on the different case groups, we performed two-sample Mendelian randomization. Most notably, we observed that of the investigated risk factors, the association between BMI and T2D attenuated with increasing age of diagnosis. Collectively, our results indicate that stratification of T2D based on age of diag-nosis reveals subgroup-specific genetics and causal determinants, supporting the hypothesis that the pathogenesis of T2D changes with increasing age. [ABSTRACT FROM AUTHOR]

OBJECTIVE--Genome-wide association studies have identified common variants in CDKAL1, CDKN2A/B, IGF2BP2, SLC30A8, HHEX/IDE, EXT2, and LOC387761 loci that significantly increase the risk of type 2 diabetes. We aimed to replicate these observations in a population-based cohort of Chinese Hans and examine the associations of these variants with type 2 diabetes and diabetes-related phenotypes. RESEARCH DESIGN AND METHODS--We genotyped 17 single nucleotide polymorhisms (SNPs) in 3,210 unrelated Chinese Hans, including 424 participants with type 2 diabetes, 878 with impaired fasting glucose (IFG), and 1,908 with normal fasting glucose. RESULTS--We confirmed the associations between type 2 diabetes and variants near CDKAL1 (odds ratio 1.49 [95% CI 1.27-1.75]; P = 8.91 x 10-7) and CDKN2A/B (1.31 [1.12-1.54]; P = 1.0 x 10-3). We observed significant association of SNPs in IGF2BP2 (1.17 [1.03-1.32]; P = 0.014) and SLC30A8 (1.12 [1.01-1.25]; P = 0.033) with combined IFG/type 2 diabetes. The SNPs in CDKAL1, IGF2BP2, and SLC30A8 were also associated with impaired β-cell function estimated by homeostasis model assessment of β-cell function. When combined, each additional risk allele from CDKAL1-rs9465871, CDKN2A/B-rs10811661, IGF2BP2-rs4402960, and SLC30A8-rs13266634 increased the risk for type 2 diabetes by 1.24-fold (P = 2.85 x 10-7) or for combined IFG/type 2 diabetes by 1.21-fold (P = 6.31 x 10-11). None of the SNPs in EXT2 or LOC387761 exhibited significant association with type 2 diabetes or IFG. Significant association was observed between the HHEX/IDE SNPs and type 2 diabetes in individuals from Shanghai only (P < 0.013) but not in those from Beijing (P > 0.33). CONCLUSIONS--Our results indicate that in Chinese Hans, common variants in CDKAL1, CDKN2A/B, IGF2BP2, and SLC30A8 loci independently or additively contribute to type 2 diabetes risk, likely mediated through β-cell dysfunction. Diabetes 57:2834-2842, 2008 [ABSTRACT FROM AUTHOR]

OBJECTIVE--Recently, genome-wide association studies have provided evidence that several common variants within the fat mass-- and obesity-associated (FTO) gene were significantly associated with obesity in populations of European origin. However, their effects in other ethnic populations remain to be elucidated. RESEARCH DESIGN AND METHODS--In this study, we examined the association between three FTO variants (rs8050136, rs9939609, and rs9930506) and obesity and related traits in a population-based study of 3,210 unrelated Chinese Han subjects from Shanghai and Beijing. In secondary analyses, we also tested for association with type 2 diabetes and related traits. Logistics regression and generalized linear models were used to test for additive and dominant effects of the risk alleles. RESULTS--The minor allele frequencies of rs8050136, rs9939609, and rs9930506 in our population (0.12, 0.12, and 0.20, respectively) were substantially lower than those observed for populations of European descent (e.g., for CEU population of HapMap: 0.45, 0.48, and 0.45, respectively). Despite our study being sufficiently powered to detect effects similar to those previously reported, none of the FTO SNPs were found to be associated with obesity, overweight, BMI, waist circumference, or body fat percentage. In addition, none of the SNPs exhibited significant associations with fasting levels of plasma glucose, A1C, insulin, or β-cell function (estimated via homeostasis model assessment) under either an additive or a dominant model in the quantitative trait analyses. Analyses stratified by sex or geographical region did not change these observations. CONCLUSIONS--Our data do not support that the FTO common variants are major contributors of obesity or type 2 diabetes in the Chinese Han population. Diabetes 57:264-268, 2008 [ABSTRACT FROM AUTHOR]

Rapidly accumulating evidence shows that common T-cell transcription factor (TCF)7L2 polymorphisms confer risk of type 2 diabetes through unknown mechanisms. We examined the association between four TCF7L2 single nucleotide polymorphisms (SNPs), including rs7903146, and measures of insulin sensitivity and insulin secretion in 1,697 Europid men and women of the population-based MRC (Medical Research Council)-Ely study. The T-(minor) allele of rs7903146 was strongly and positively associated with fasting proinsulin (P = 4.55 x 10(-9)) and 32,33 split proinsulin (P = 1.72 x 10(-4)) relative to total insulin levels; i.e., differences between T/T and C/C homozygotes amounted to 21.9 and 18.4% respectively. Notably, the insulin-to-glucose ratio (IGR) at 30-min oral glucose tolerance test (OGTT), a frequently used surrogate of first-phase insulin secretion, was not associated with the TCF7L2 SNP (P > 0.7). However, the insulin response (IGR) at 60-min OGTT was significantly lower in T-allele carriers (P = 3.5 x 10(-3)). The T-allele was also associated with higher A1C concentrations (P = 1.2 x 10(-2)) and reduced beta-cell function, assessed by homeostasis model assessment of beta-cell function (P = 2.8 x 10(-2)). Similar results were obtained for the other TCF7L2 SNPs. Of note, both major genes involved in proinsulin processing (PC1, PC2) contain TCF-binding sites in their promoters. Our findings suggest that the TCF7L2 risk allele may predispose to type 2 diabetes by impairing beta-cell proinsulin processing. The risk allele increases proinsulin levels and diminishes the 60-min but not 30-min insulin response during OGTT. The strong association between the TCF7L2 risk allele and fasting proinsulin but not insulin levels is notable, as, in this unselected and largely normoglycemic population, external influences on beta-cell stress are unlikely to be major factors influencing the efficiency of proinsulin processing. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10−8). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10−4), improved β-cell function (P = 1.1 × 10−5), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10−6). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.

Objective: Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for β-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants. Research Design and Methods: We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes. Results: We observed a significant association of total zinc intake with lower fasting glucose levels (β-coefficient ± SE per 1 mg/day of zinc intake: −0.0012 ± 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC30A8 rs11558471 variant on fasting glucose levels (β-coefficient ± SE per A allele for 1 mg/day of greater total zinc intake: −0.0017 ± 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant. Conclusions: Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels.

OBJECTIVE— Genome-wide association studies have identified common variants in CDKAL1, CDKN2A/B, IGF2BP2, SLC30A8, HHEX/IDE, EXT2, and LOC387761 loci that significantly increase the risk of type 2 diabetes. We aimed to replicate these observations in a population-based cohort of Chinese Hans and examine the associations of these variants with type 2 diabetes and diabetes-related phenotypes. RESEARCH DESIGN AND METHODS— We genotyped 17 single nucleotide polymorhisms (SNPs) in 3,210 unrelated Chinese Hans, including 424 participants with type 2 diabetes, 878 with impaired fasting glucose (IFG), and 1,908 with normal fasting glucose. RESULTS— We confirmed the associations between type 2 diabetes and variants near CDKAL1 (odds ratio 1.49 [95% CI 1.27–1.75]; P = 8.91 × 10−7) and CDKN2A/B (1.31 [1.12–1.54]; P = 1.0 × 10−3). We observed significant association of SNPs in IGF2BP2 (1.17 [1.03–1.32]; P = 0.014) and SLC30A8 (1.12 [1.01–1.25]; P = 0.033) with combined IFG/type 2 diabetes. The SNPs in CDKAL1, IGF2BP2, and SLC30A8 were also associated with impaired β-cell function estimated by homeostasis model assessment of β-cell function. When combined, each additional risk allele from CDKAL1-rs9465871, CDKN2A/B-rs10811661, IGF2BP2-rs4402960, and SLC30A8-rs13266634 increased the risk for type 2 diabetes by 1.24-fold (P = 2.85 × 10−7) or for combined IFG/type 2 diabetes by 1.21-fold (P = 6.31 × 10−11). None of the SNPs in EXT2 or LOC387761 exhibited significant association with type 2 diabetes or IFG. Significant association was observed between the HHEX/IDE SNPs and type 2 diabetes in individuals from Shanghai only (P < 0.013) but not in those from Beijing (P > 0.33). CONCLUSIONS— Our results indicate that in Chinese Hans, common variants in CDKAL1, CDKN2A/B, IGF2BP2, and SLC30A8 loci independently or additively contribute to type 2 diabetes risk, likely mediated through β-cell dysfunction.

A shared genetic susceptibility underlies diabetes, adiposity, and kidney phenotypes, yet few studies have leveraged this common genetic architecture in an attempt to clarify molecular functions, identify mechanistic common denominators, and prioritize variants for functional interrogation. We systematically interrogated evidence of a shared genetic architecture across adiposity (BMI [N=90,813], waist circumference[N=68,389], and waist to hip ratio [WHR, N=63,747]), type 2 diabetes (T2D, [N=98,686, Ncase=26,440], fasting glucose [FG, N=52,211], HbA1c [N=23,357], and fasting insulin [FI, N=48,395]), and kidney (eGFR [N=52,555] and chronic kidney disease [CKD, N=91,382, Ncase=10,883]) phenotypes in an ancestrally diverse study population (28% African American, 31% European ancestry, 28% Hispanic; 69% female; average age 56.9 (range 18-90)) within PAGE. We conducted a cross-trait meta-analysis using Adaptive Sum of Powered Score Tests (aSPU). We have identified 42 loci associated across these traits, (P<5e-8), including one preliminary novel cross-trait association for rs200812701, a nonsynonymous variant in KIF4B p.Ala491Valthat was associated with BMI, waist circumference, and HbA1c. rs200812701 is rare (minor allele frequency [MAF]<0.1%) in all populations except Native Hawaiians (MAF=25%) and Asians (MAF=8%). Many of these loci are known for one trait, but the identification of shared genetic susceptibility for these loci is novel. For example, the PEPD locus is established for adiposity measures, namely WHR; however, this cross-trait association is driven more so by FI, T2D and eGFR. Our systematic interrogation of the shared genetic susceptibility underlying diabetes, adiposity, and kidney traits in an ancestrally diverse population has revealed novel loci and evidence of molecular functions and mechanistic common denominators underlying GWAS findings, demonstrating the utility of our approach. Disclosure: H.M. Highland: None. C. Downie: None. S.F. Dimos: None. M. Graff: None. L.M. Polfus: None. B.F. Darst: None. A.R.M. Baldassari: None. C. Sitlani: None. A. Howard: None. C.L. Kooperberg: None. R. Loos: None. T. Matise: None. A.K. Mottl: None. K.E. North: None. C.L. Avery: Research Support; Self; Amgen. Funding: American Diabetes Association (1-19-PDF-045 to H.M.M.); National Institutes of Health (T32HL007055, T32HL129982, R01HL142825) [ABSTRACT FROM AUTHOR]

Leptin acts as a satiety signal regulating food intake and energy expenditure. The relation between variants in the leptin (LEP; 19 G>A) gene and its receptor (LEPR; Q223R and K109R) with obesity and type 2 diabetes has been studied extensively, but results are inconclusive and the relation remains unclear. In a population-based association study, we examined the effect of these variants on pre-diabetic phenotypes measured in young healthy twins. In this study, 396 monozygotic and 230 dizygotic twins (286 men and 340 women, mean age 25 years) were recruited from the East Flanders Prospective Twin Survey. Several diabetes-related traits were measured, including birth weight, adult body composition, fasting concentrations of cholesterol (LDL and HDL), triglycerides, free fatty acids, leptin, insulin and glucose. Genotyping was performed using Pyrosequencing. Linear mixed models, including a random effect term for twin pair membership, were used to evaluate associations between the variants and the measured traits. When appropriate, traits were adjusted for covariates including sex, (gestational) age, height and fat. Subjects carrying the 19 G allele of LEP had higher HDL-cholesterol levels compared to 19 A homozygotes (GX vs AA (95% CI): 1.62 (1.58-1.66) vs 1.49 (1.40-1.58) mmol/1;p=0.008). The K109R variant in the LEPR was associated with birth weight (KK, KR and RR (95% CI): 2507 (2462-2553), 2577 (2519-2536) and 2762 (2643-2882) gram; p=0.0002). Also the Q223R variant in the LEPR showed association with birth weight (QQ, QR and RR (95% CI): 2493 (2431-2554), 2542 (2492-2591) and 2670 (2583-2756) gram; p=0.002). These results indicate that genetic variation in the LEP gene affects HDL-cholesterol levels. Furthermore, this study suggests a possible role for the LEPR in explaining the inverse relationship between birth weight and the development of metabolic diseases in adult life. [ABSTRACT FROM AUTHOR]

Retinol binding protein 4 (RBP4) is an adipokine that is up-regulated in the absence of GLUT4, and that increases liver and muscle insulin resistance in mice. In humans, high plasma levels of RBP4 have been correlated with several features of the metabolic syndrome in selected lean, obese or type 2 diabetes (T2D) groups. However individual correlations between RBP4 and specific metabolic indices have been inconsistent, perhaps in part because of different analytic methodologies for RBP4. This study aimed to assess the associations between RBP4 levels and metabolic phenotypes in a population-based cohort with a wide range of levels of insulin resistance, using a robust, commercially available nephelometric assay amenable to high throughput studies. Plasma RBP4 was measured in 198 participants of the MRC Ely study (age=54±5 yrs; Body mass index (BMI) = 26.8±4.4 kg/m²; including 14 people with T2D). Compared to controls, plasma RBP4 levels were higher in type 2 diabetics (4.24mg/l vs. 5.29 mg/l; p=0.003) as described previously. However, RBP4 levels were not different between non-obese (BMI<30) and obese (BMI±30) individuals (4.26mg/1 vs. 4.88mg/l; p=0.65). Regression analyses adjusted for age, sex, BMI and diabetes status showed positive associations between plasma RBP4 levels and triglycerides (p=0.0000001), cholesterol (p=0.00001), leptin (p=0.01) and fasting plasma glucose (p=0.07). High RBP4 levels were also positively associated with fasting plasma insulin (p=0.001) and negatively associated with HOMA-S (p=0.001). Our results demonstrate that RBP4 is strongly associated with features of the metabolic syndrome, particularly hypertriglyceridemia. We also replicated associations of high RBP4 levels .with increased insulin resistance in a population-based cohort. Further studies are required to understand the molecular bases of the link between RBP4, lipid metabolism and insulin resistance. [ABSTRACT FROM AUTHOR]

Objective: To identify genetic risk factors for incident cardiovascular disease (CVD) among people with type 2 diabetes (T2D)., Research Design and Methods: We conducted a multiancestry time-to-event genome-wide association study for incident CVD among people with T2D. We also tested 204 known coronary artery disease (CAD) variants for association with incident CVD., Results: Among 49,230 participants with T2D, 8,956 had incident CVD events (event rate 18.2%). We identified three novel genetic loci for incident CVD: rs147138607 (near CACNA1E/ZNF648, hazard ratio [HR] 1.23, P = 3.6 × 10-9), rs77142250 (near HS3ST1, HR 1.89, P = 9.9 × 10-9), and rs335407 (near TFB1M/NOX3, HR 1.25, P = 1.5 × 10-8). Among 204 known CAD loci, 5 were associated with incident CVD in T2D (multiple comparison-adjusted P < 0.00024, 0.05/204). A standardized polygenic score of these 204 variants was associated with incident CVD with HR 1.14 (P = 1.0 × 10-16)., Conclusions: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D., (© 2024 by the American Diabetes Association.)

Objective: We aimed to identify hemoglobin A 1c (HbA 1c )-associated genetic variants and examine their implications for glycemic status evaluated by HbA 1c in U.S. Hispanics/Latinos with diverse genetic ancestries., Research Design and Methods: We conducted a genome-wide association study (GWAS) of HbA 1c in 9,636 U.S. Hispanics/Latinos without diabetes from the Hispanic Community Health Study/Study of Latinos, followed by a replication among 4,729 U.S. Hispanics/Latinos from three independent studies., Results: Our GWAS and replication analyses showed 10 previously known and novel loci associated with HbA 1c at genome-wide significance levels ( P < 5.0 × 10 -8 ). In particular, two African ancestry-specific variants, HBB- rs334 and G6PD -rs1050828, which are causal mutations for sickle cell disease and G6PD deficiency, respectively, had ∼10 times larger effect sizes on HbA 1c levels (β = -0.31% [-3.4 mmol/mol]) and -0.35% [-3.8 mmol/mol] per minor allele, respectively) compared with other HbA 1c -associated variants (0.03-0.04% [0.3-0.4 mmol/mol] per allele). A novel Amerindian ancestry-specific variant, HBM -rs145546625, was associated with HbA 1c and hematologic traits but not with fasting glucose. The prevalence of hyperglycemia (prediabetes and diabetes) defined using fasting glucose or oral glucose tolerance test 2-h glucose was similar between carriers of HBB- rs334 or G6PD -rs1050828 HbA 1c -lowering alleles and noncarriers, whereas the prevalence of hyperglycemia defined using HbA 1c was significantly lower in carriers than in noncarriers (12.2% vs. 28.4%, P < 0.001). After recalibration of the HbA 1c level taking HBB -rs334 and G6PD -rs1050828 into account, the prevalence of hyperglycemia in carriers was similar to noncarriers (31.3% vs. 28.4%, P = 0.28)., Conclusions: This study in U.S. Hispanics/Latinos found several ancestry-specific alleles associated with HbA 1c through erythrocyte-related rather than glycemic-related pathways. The potential influences of these nonglycemic-related variants need to be considered when the HbA 1c test is performed., (© 2019 by the American Diabetes Association.)

Elevated concentrations of albumin in the urine, albuminuria, are a hallmark of diabetic kidney disease and are associated with an increased risk for end-stage renal disease and cardiovascular events. To gain insight into the pathophysiological mechanisms underlying albuminuria, we conducted meta-analyses of genome-wide association studies and independent replication in up to 5,825 individuals of European ancestry with diabetes and up to 46,061 without diabetes, followed by functional studies. Known associations of variants in CUBN, encoding cubilin, with the urinary albumin-to-creatinine ratio (UACR) were confirmed in the overall sample (P = 2.4 × 10(-10)). Gene-by-diabetes interactions were detected and confirmed for variants in HS6ST1 and near RAB38/CTSC. Single nucleotide polymorphisms at these loci demonstrated a genetic effect on UACR in individuals with but not without diabetes. The change in the average UACR per minor allele was 21% for HS6ST1 (P = 6.3 × 10(-7)) and 13% for RAB38/CTSC (P = 5.8 × 10(-7)). Experiments using streptozotocin-induced diabetic Rab38 knockout and control rats showed higher urinary albumin concentrations and reduced amounts of megalin and cubilin at the proximal tubule cell surface in Rab38 knockout versus control rats. Relative expression of RAB38 was higher in tubuli of patients with diabetic kidney disease compared with control subjects. The loci identified here confirm known pathways and highlight novel pathways influencing albuminuria., (© 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics-based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26-0.35) increase in fasting insulin, a 0.34-SD (0.30-0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47-2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI -0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (-0.20 SD; 95% CI -0.38 to -0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75-1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: -0.03 SD; 95% CI -0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95-1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.

Objective: Glycated hemoglobin (HbA₁(c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA₁(c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA₁(c) levels., Research Design and Methods: We studied associations with HbA₁(c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA₁(c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening., Results: Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10⁻²⁶), HFE (rs1800562/P = 2.6 × 10⁻²⁰), TMPRSS6 (rs855791/P = 2.7 × 10⁻¹⁴), ANK1 (rs4737009/P = 6.1 × 10⁻¹²), SPTA1 (rs2779116/P = 2.8 × 10⁻⁹) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10⁻⁹), and four known HbA₁(c) loci: HK1 (rs16926246/P = 3.1 × 10⁻⁵⁴), MTNR1B (rs1387153/P = 4.0 × 10⁻¹¹), GCK (rs1799884/P = 1.5 × 10⁻²⁰) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10⁻¹⁸). We show that associations with HbA₁(c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA₁(c)) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA₁(c)., Conclusions: GWAS identified 10 genetic loci reproducibly associated with HbA₁(c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA₁(c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA₁(c).

Objective: Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin., Research Design and Methods: Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant., Results: Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele., Conclusions: Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.