Genetic variant in HK1 is associated with a proanemic state and A1C but not other glycemic control-related traits

NK2R control of energy expenditure and feeding to treat metabolic diseases

The combination of decreasing food intake and increasing energy expenditure represents a powerful strategy for counteracting cardiometabolic diseases such as obesity and type 2 diabetes1. Yet current pharmacological approaches require conjugation of multiple receptor agonists to achieve both effects2-4, and so far, no safe energy-expending option has reached the clinic. Here we show that activation of neurokinin 2 receptor (NK2R) is sufficient to suppress appetite centrally and increase energy expenditure peripherally. We focused on NK2R after revealing its genetic links to obesity and glucose control. However, therapeutically exploiting NK2R signalling has previously been unattainable because its endogenous ligand, neurokinin A, is short-lived and lacks receptor specificity5,6. Therefore, we developed selective, long-acting NK2R agonists with potential for once-weekly administration in humans. In mice, these agonists elicit weight loss by inducing energy expenditure and non-aversive appetite suppression that circumvents canonical leptin signalling. Additionally, a hyperinsulinaemic-euglycaemic clamp reveals that NK2R agonism acutely enhances insulin sensitization. In diabetic, obese macaques, NK2R activation significantly decreases body weight, blood glucose, triglycerides and cholesterol, and ameliorates insulin resistance. These findings identify a single receptor target that leverages both energy-expending and appetite-suppressing programmes to improve energy homeostasis and reverse cardiometabolic dysfunction across species.

Genetic association of novel SNPs in HK-1 (rs201626997) and HK-3 (rs143604141) with type 2 diabetes mellitus in Bangladeshi population

BACKGROUND

Hexokinase, a key enzyme in glycolysis, has isoforms like HK-1, HK-2, HK-3, and Glucokinase. Unpublished exome sequencing data showed that two novel polymorphisms in HK-1 rs201626997 (G/T) and HK-3 rs143604141 (G/A) exist in the Bangladeshi population. We investigated the possible relationship of these SNPs with T2DM.

MATERIALS AND METHODS

Peripheral blood samples from the study participants were used to isolate their genomic DNA. An allele-specific PCR was standardized that can discriminate between the wild-type and mutant-type alleles of HK-1 (rs201626997) and HK-3 (rs143604141) polymorphisms. The data was analyzed by SPSS for statistics.

RESULTS

We performed allele-specific PCR for 249 diabetic patients and 195 control samples. For HK-1 (rs201626997), 24 (5.4%) have a mutant allele, and for HK-3 (rs143604141), 25 (5.6%) are mutant. There is no significant relationship between the individuals' disease condition and the HK-1 polymorphism (P value 0.537). But the GA genotype of the HK-3 rs143604141 pertains to an increased risk of diabetes (P value 0.039). HK-3 rs143604141 polymorphism has a moderate correlation (P value 0.078, OR, 3.11, 95% CI, 0.88-10.94) with a family diabetic history. Both polymorphisms showed no significant correlation with gender or BMI. However, hexokinase-1 polymorphism significantly related with diastolic blood pressure (P value 0.048).

CONCLUSION

This study will help us to easily detect the polymorphisms of HK-1 (rs201626997) and HK-3 (rs143604141) in different populations of the world. Further studies with a greater number of participants and more physiological information are required to better understand the underlying genetic causes of T2DM susceptibility in Bangladesh.

Variants influencing age at diagnosis of HNF1A-MODY

BACKGROUND

HNF1A-MODY is a monogenic form of diabetes caused by variants in the HNF1A gene. Different HNF1A variants are associated with differences in age of disease onset, but other factors are postulated to influence this trait. Here, we searched for genetic variants influencing age of HNF1A-MODY onset.

METHODS

Blood samples from 843 HNF1A-MODY patients from Czech Republic, France, Poland, Slovakia, the UK and the US were collected. A validation set consisted of 121 patients from the US. We conducted a genome-wide association study in 843 HNF1A-MODY patients. Samples were genotyped using Illumina Human Core arrays. The core analysis was performed using the GENESIS package in R statistical software. Kinship coefficients were estimated with the KING and PC-Relate algorithms. In the linear mixed model, we accounted for year of birth, sex, and location of the HNF1A causative variant.

RESULTS

A suggestive association with age of disease onset was observed for rs2305198 (p = 2.09E-07) and rs7079157 (p = 3.96E-06) in the HK1 gene, rs2637248 in the LRMDA gene (p = 2.44E-05), and intergenic variant rs2825115 (p = 2.04E-05). Variant rs2637248 reached nominal significance (p = 0.019), while rs7079157 (p = 0.058) and rs2825115 (p = 0.068) showed suggestive association with age at diabetes onset in the validation set.

CONCLUSIONS

rs2637248 in the LRMDA gene is associated with age at diabetes onset in HNF1A-MODY patients.

A systematic review of non-genetic predictors and genetic factors of glycated haemoglobin in type 1 diabetes one year after diagnosis

Type 1 diabetes (T1D) results from autoimmune destruction of the pancreatic βcells. Although all T1D patients require daily administration of exogenous insulin, their insulin requirement to achieve good glycaemic control may vary significantly. Glycated haemoglobin (HbA1c) level represents a stable indicator of glycaemic control and is a reliable predictor of long-term complications of T1D. The purpose of this article is to systematically review the role of non-genetic predictors and genetic factors of HbA1c level in T1D patients after the first year of T1D, to exclude the honeymoon period. A total of 1974 articles published since January 2011 were identified and 78 were finally included in the analysis of non-genetic predictors. For genetic factors, a total of 277 articles were identified and 14 were included. The most significantly associated factors with HbA1c level are demographic (age, ethnicity, and socioeconomic status), personal (family characteristics, parental care, psychological traits...) and features related to T1D (duration of T1D, adherence to treatment …). Only a few studies have searched for genetic factors influencing HbA1c level, most of which focused on candidate genes using classical genetic statistical methods, with generally limited power and incomplete adjustment for confounding factors and multiple testing. Our review shows the complexity of explaining HbA1c level variations, which involves numerous correlated predictors. Overall, our review underlines the lack of studies investigating jointly genetic and non-genetic factors and their interactions to better understand factors influencing glycaemic control for T1D patients.

Overexpression of metabolic markers HK1 and PKM2 contributes to lymphatic metastasis and adverse prognosis in Chinese gastric cancer

Hexokinase 1 (HK1) and pyruvate kinase M2 (PKM2) are two key regulators in glycosis and oncogenic markers in cancers. In the present study, we investigated the expression profile by Western blotting and immunohistochemistry and determined their prognostic values in the gastric cancer. Expression of HK1 and PKM2 was remarkably increased in gastric cancer tissues and was significantly associated lymphatic metastasis and advanced TNM staging. In the COX regression model, HK1 and TNM stage were analyzed as adverse prognostic indicators in gastric cancer. Furthermore, patients with HK1 expression showed remarkable shorter survival duration in both lymphatic metastasis cohort and advanced staging cohort. Our results suggest that overexpression of PKM2 and HK1, especially the latter, significantly associates with lymphatic metastasis, advanced clinical staging and unfavorable prognosis in gastric cancer.

Rare and common genetic events in type 2 diabetes: what should biologists know?

Type 2 diabetes (T2D) had long been referred to as the "geneticist's nightmare." Genome-wide association studies have fully confirmed the polygenic nature of T2D, demonstrating the role of many genes in T2D risk. The increasingly busier picture of T2D genetics is quite difficult to understand for the diabetes research community, which can create misunderstandings with geneticists, and can eventually limit both basic research and translational outcomes of these genetic discoveries. The present review wishes to lift the fog around genetics of T2D with the hope that it will foster integrated diabetes modeling approaches from genetic defects to personalized medicine.

Expression patterns of three regulation enzymes in glycolysis in esophageal squamous cell carcinoma: association with survival

Enhanced glycolysis is a common trait of many types of human cancers. This study was to detect the expression pattern of three regulatory enzymes during glycolysis in esophageal squamous cell carcinoma (ESCC) and to investigate their correlation with patients' outcome based on banked pathology material. A total of 141 surgically resected specimens of primary ESCC patients without prior treatments were retrospectively recruited from the First Affiliated Hospital of Wenzhou Medical College Hospital from 2007 to 2009. Expression of HK1, PFKB, and PKM2 in ESCC specimens was analyzed by immunohistochemical staining and Western blotting analysis. HK1-shRNA was used to knock down HK1 expression in ESCC cells, and the functional significance was assessed by CCK8 assay. It was found that the expression of two glycolytic enzymes, HK1 and PKM2, was associated with disease progression, invasion, and poor survival of patients with ESCC. Silence of HK1-inhibited cell proliferation in vitro and suppressed phospho-S6 kinase expression. Our findings suggest that activation of key enzymes in glycolysis might serve as potential therapeutic targets and/or prognostic factors for patients with ESCC.

Reassessment of the putative role of BLK-p.A71T loss-of-function mutation in MODY and type 2 diabetes

AIMS/HYPOTHESIS

MODY is believed to be caused by at least 13 different genes. Five rare mutations at the BLK locus, including only one non-synonymous p.A71T variant, were reported to segregate with diabetes in three MODY families. The p.A71T mutation was shown to abolish the enhancing effect of BLK on insulin content and secretion from pancreatic beta cell lines. Here, we reassessed the contribution of BLK to MODY and tested the effect of BLK-p.A71T on type 2 diabetes risk and variations in related traits.

METHODS

BLK was sequenced in 64 unelucidated MODY samples. The BLK-p.A71T variant was genotyped in a French type 2 diabetes case-control study including 4,901 cases and 4,280 controls, and in the DESIR (Data from an Epidemiological Study on the Insulin Resistance Syndrome) and SUVIMAX (Supplementation en Vitamines et Mineraux Antioxydants) population-based cohorts (n = 6,905). The variant effects were assessed by logistic and linear regression models.

RESULTS

No rare non-synonymous BLK mutations were found in the MODY patients. The BLK p.A71T mutation was present in 52 normoglycaemic individuals, making it very unlikely that this loss-of-function mutation causes highly penetrant MODY. We found a nominal association between this variant and increased type 2 diabetes risk, with an enrichment of the mutation in the obese diabetic patients, although no significant association with BMI was identified.

CONCLUSIONS/INTERPRETATION

No mutation in BLK was found in our MODY cohort. From our findings, the BLK-p.A71T mutation may weakly influence type 2 diabetes risk in the context of obesity; however, this will require further validation.

Determinants of HbA1c in nondiabetic Dutch adults: genetic loci and clinical and lifestyle parameters, and their interactions in the Lifelines Cohort Study

OBJECTIVES

Glycated haemoglobin (HbA1c) is associated with cardiovascular disease risk in individuals without diabetes, and its use has been recommended for diagnosing diabetes. Therefore, it is important to gain further understanding of the determinants of HbA1c. The aim of this study was to investigate the effects of genetic loci and clinical and lifestyle parameters, and their interactions, on HbA1c in nondiabetic adults.

DESIGN

Population-based cohort study.

SETTING

Three northern provinces of the Netherlands.

SUBJECTS

A total of 2921 nondiabetic adults participating in the population-based LifeLines Cohort Study.

MEASUREMENTS

Body mass index (BMI), waist circumference, HbA1c, fasting plasma glucose (FPG) and erythrocyte indices were measured. Data on current smoking and alcohol consumption were collected through questionnaires. Genome-wide genotyping was performed, and 12 previously identified single-nucleotide polymorphisms (SNPs) were selected for replication and categorized as 'glycaemic' and 'nonglycaemic' SNPs according to their presumed mechanism(s) of action on HbA1c. Genetic risk scores (GRSs) were calculated as the sum of the weighted effect of HbA1c-increasing alleles.

RESULTS

Age, gender, BMI, FPG, mean corpuscular haemoglobin, mean corpuscular haemoglobin concentration, current smoking and alcohol consumption were independent predictors of HbA1c, together explaining 26.2% of the variance in HbA1c, with FPG contributing 10.9%. We replicated three of the previously identified SNPs and the GRSs were also found to be independently associated with HbA1c. We found a smaller effect of the 'nonglycaemic GRS' in females compared with males and an attenuation of the effect of the GRS of all 12 SNPs with increasing BMI.

CONCLUSIONS

Our results suggest that a substantial portion of HbA1c is determined by nonglycaemic factors. This should be taken into account when considering the use of HbA1c as a diagnostic test for diabetes.

Dominant form of congenital hyperinsulinism maps to HK1 region on 10q

BACKGROUND/AIMS

In a family with congenital hyperinsulinism (HI), first described in the 1950s by McQuarrie, we examined the genetic locus and clinical phenotype of a novel form of dominant HI.

METHODS

We surveyed 25 affected individuals, 7 of whom participated in tests of insulin dysregulation (24-hour fasting, oral glucose and protein tolerance tests). To identify the disease locus and potential disease-associated mutations we performed linkage analysis, whole transcriptome sequencing, whole genome sequencing, gene capture, and next generation sequencing.

RESULTS

Most affecteds were diagnosed with HI before age one and 40% presented with a seizure. All affecteds responded well to diazoxide. Affecteds failed to adequately suppress insulin secretion following oral glucose tolerance test or prolonged fasting; none had protein-sensitive hypoglycemia. Linkage analysis mapped the HI locus to Chr10q21-22, a region containing 48 genes. Three novel noncoding variants were found in hexokinase 1 (HK1) and one missense variant in the coding region of DNA2.

CONCLUSION

Dominant, diazoxide-responsive HI in this family maps to a novel locus on Chr10q21-22. HK1 is the more attractive disease gene candidate since a mutation interfering with the normal suppression of HK1 expression in beta-cells could readily explain the hypoglycemia phenotype of this pedigree.

Ethnic disparity in hemoglobin A1c levels among normoglycemic offspring of parents with type 2 diabetes mellitus

OBJECTIVE

To investigate the racial/ethnic disparities in hemoglobin A1c levels among nondiabetic persons with similar parental history of type 2 diabetes mellitus.

METHODS

We studied a community-based sample of adult offspring of parents with type 2 diabetes mellitus. Measurements included anthropometry, hematology assessments, serial fasting plasma glucose, oral glucose tolerance testing, plasma insulin, hemoglobin A1c, insulin sensitivity, and β-cell function, using a homeostasis model assessment.

RESULTS

The study included 302 participants (135 white, 167 black). Compared with white participants, black participants had lower fasting plasma glucose levels (91.9 ± 0.51 mg/dL vs 93.6 ± 0.50 mg/dL, P = .015), lower area under the curve of plasma glucose during oral glucose tolerance testing (P = <.001), higher body mass index (31.1 ± 0.61 kg/m² vs 28.5 ± 0.57 kg/m², P = <.001), and similar insulin sensitivity and β-cell function. Hemoglobin A1c was higher in black participants than in white participants (5.68 ± 0.033% vs 5.45 ± 0.028%, P<.001). The absolute black-white difference in hemoglobin A1c level of approximately 0.22% persisted after adjusting for age, hemoglobin, hematocrit, body mass index, waist circumference, fasting plasma glucose, glucose area under the curve, and other covariates.

CONCLUSIONS

Among healthy offspring of parents with type 2 diabetes mellitus in this study, African American participants had higher hemoglobin A1c levels than white participants after adjusting for age, adiposity, blood glucose, and known variables. Thus, plasma glucose level is more valid than hemoglobin A1c for diagnosing prediabetes or diabetes in black persons.

Genetic determinants of variability in glycated hemoglobin (HbA(1c)) in humans: review of recent progress and prospects for use in diabetes care

Glycated hemoglobin A(1c) (HbA(1c)) indicates the percentage of total hemoglobin that is bound by glucose, produced from the nonenzymatic chemical modification by glucose of hemoglobin molecules carried in erythrocytes. HbA(1c) represents a surrogate marker of average blood glucose concentration over the previous 8 to 12 weeks, or the average lifespan of the erythrocyte, and thus represents a more stable indicator of glycemic status compared with fasting glucose. HbA(1c) levels are genetically determined, with heritability of 47% to 59%. Over the past few years, inroads into understanding genetic predisposition by glycemic and nonglycemic factors have been achieved through genomewide analyses. Here I review current research aimed at discovering genetic determinants of HbA(1c) levels, discussing insights into biologic factors influencing variability in the general and diabetic population, and across different ethnicities. Furthermore, I discuss briefly the relevance of findings for diabetes monitoring and diagnosis.

Genotype risk score of common susceptible variants for prediction of type 2 diabetes mellitus in Japanese: the Shimanami Health Promoting Program (J-SHIPP study). Development of type 2 diabetes mellitus and genotype risk score

Recent genomewide association studies have successfully identified several genotypes susceptible to type 2 diabetes mellitus (T2DM). However, only a few studies have investigated whether these variations confer a risk of the future development of T2DM. We conducted a longitudinal genetic epidemiological study to clarify the prognostic significance of the T2DM-associated variants. The sample population consisted of 2037 middle-aged to elderly community residents. Personal health records were obtained from a clinical database administered by the local government. Genotype risk score was calculated by the following variants, namely, KCNQ1, TCF7L2, CDKAL1, HHEX, IGF2BP2, CDKN2AB, SLC30A8, KCNJ11, PPARG, and GCKR. Susceptibility of these variants in Japanese has been confirmed by association analysis. Among the 1824 subjects who did not have T2DM at baseline, 95 cases of T2DM were newly diagnosed during the 9.4-year follow-up period. Mean genotype risk score in these subjects was significantly higher than that in the subjects who remained nondiabetic (9.5 ± 1.8 vs 9.1 ± 2.0, P = .042). Although the initial mean body mass index (24.7 ± 3.2 vs 23.0 ± 2.8, P < .001) and initial glucose (106 ± 18 vs 90 ± 13, P < .001) were also significantly higher in those subjects who developed T2DM, the genotype risk score remained an independent determinant of the development of T2DM even after adjustment for these parameters and possible confounding factors. Per-allele odds ratio for the development of T2DM was 1.12 (95% confidence interval, 1.00-1.25; P = .049). Type 2 diabetes mellitus-susceptible genetic variants identified by a cross-sectional genomewide association study were significantly associated with the future development of T2DM in a general population sample.

Studies of a genetic variant in HK1 in relation to quantitative metabolic traits and to the prevalence of type 2 diabetes

BACKGROUND

Single nucleotide polymorphisms (SNPs) within the gene encoding Hexokinase 1 (HK1) are associated with changes in glycated haemoglobin (HbA1c) levels. Our aim was to investigate the effect of HK1 rs7072268 on measures of glucose- and lipid-metabolism in a Danish non-diabetic population and combine the outcome of these analyses in a meta-analysis with previously published results. Furthermore, our aim was to perform a type 2 diabetes case-control analysis and meta-analysis with two previous case-control studies.

METHODS

SNP rs7072268 was genotyped in 9,724 Danes. The quantitative trait study included 5,604 non-diabetic individuals from the Inter99 cohort. The case-control study included 4,449 glucose tolerant individuals and 3,398 patients with type 2 diabetes. Meta-analyses on quantitative traits included 24,560 Caucasian individuals and 30,802 individuals were included in the combined analysis of present and previous type 2 diabetes case-control studies.

RESULTS

Using an additive model, we confirmed that the T-allele of rs7072268 associates with increased HbA1c of 0.6% (CI: 0.4-0.9), p = 3*10-7 per allele. The same allele associated with an increased area under the curve (AUC) for glucose of 5.0 mmol/l*min (0.1-10.0), p = 0.045 following an oral glucose tolerance test (OGTT) and increased fasting levels of cholesterol of 0.06 mmol/l (0.03-1.0), p = 0.001 and triglycerides of 2.0% (0.2-3.8), p = 0.03 per allele in the same study sample of non-diabetic individuals from the Inter99 cohort. However, the T-allele did not show any association with estimates of insulin release or insulin sensitivity neither in Inter99 nor in combined analyses. The prevalence of type 2 diabetes was increased among carriers of the rs7072268 T-allele both in the Danish study-population with an OR of 1.11 (1.02-1.21) and in a meta-analysis including the two additional sample sets with an OR of 1.06 (1.02-1.11). However, after Bonferroni correction the T-allele only remained associated to HbA1c and fasting cholesterol.

CONCLUSIONS

The present study provides suggestive evidence of an association of the rs7072268 T-allele in HK1 with increased AUC glucose following an OGTT in non-diabetic individuals and a nominal association with type 2 diabetes prior to Bonferroni correction. The latter was confirmed in combined analyses involving 16,445 cases and 14,357 control subjects.

Evaluation of four novel genetic variants affecting hemoglobin A1c levels in a population-based type 2 diabetes cohort (the HUNT2 study)

BACKGROUND

Chronic hyperglycemia confers increased risk for long-term diabetes-associated complications and repeated hemoglobin A1c (HbA1c) measures are a widely used marker for glycemic control in diabetes treatment and follow-up. A recent genome-wide association study revealed four genetic loci, which were associated with HbA1c levels in adults with type 1 diabetes. We aimed to evaluate the effect of these loci on glycemic control in type 2 diabetes.

METHODS

We genotyped 1,486 subjects with type 2 diabetes from a Norwegian population-based cohort (HUNT2) for single-nucleotide polymorphisms (SNPs) located near the BNC2, SORCS1, GSC and WDR72 loci. Through regression models, we examined their effects on HbA1c and non-fasting glucose levels individually and in a combined genetic score model.

RESULTS

No significant associations with HbA1c or glucose levels were found for the SORCS1, BNC2, GSC or WDR72 variants (all P-values > 0.05). Although the observed effects were non-significant and of much smaller magnitude than previously reported in type 1 diabetes, the SORCS1 risk variant showed a direction consistent with increased HbA1c and glucose levels, with an observed effect of 0.11% (P = 0.13) and 0.13 mmol/l (P = 0.43) increase per risk allele for HbA1c and glucose, respectively. In contrast, the WDR72 risk variant showed a borderline association with reduced HbA1c levels (β = -0.21, P = 0.06), and direction consistent with decreased glucose levels (β = -0.29, P = 0.29). The allele count model gave no evidence for a relationship between increasing number of risk alleles and increasing HbA1c levels (β = 0.04, P = 0.38).

CONCLUSIONS

The four recently reported SNPs affecting glycemic control in type 1 diabetes had no apparent effect on HbA1c in type 2 diabetes individually or by using a combined genetic score model. However, for the SORCS1 SNP, our findings do not rule out a possible relationship with HbA1c levels. Hence, further studies in other populations are needed to elucidate whether these novel sequence variants, especially rs1358030 near the SORCS1 locus, affect glycemic control in type 2 diabetes.

Genetics of type 2 diabetes: the GWAS era and future perspectives [Review]

Genome-wide association studies (GWAS) have facilitated a substantial and rapid rise in the number of confirmed genetic susceptibility variants for type 2 diabetes (T2D). Approximately 40 variants have been identified so far, many of which were discovered through GWAS. This success has led to widespread hope that the findings will translate into improved clinical care for the increasing numbers of patients with diabetes. Potential areas or clinical translation include risk prediction and subsequent disease prevention, pharmacogenetics, and the development of novel therapeutics. However, the genetic loci so far identified account for only a small fraction (approximately 10%) of the overall heritable risk for T2D. Uncovering the missing heritability is essential to the progress of T2D genetic studies and to the translation of genetic information into clinical practice.

Common variants at 10 genomic loci influence hemoglobin A₁(C) levels via glycemic and nonglycemic pathways

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).

The emerging genetics of type 2 diabetes

The elucidation of several genetic etiologies of both monogenic and polygenic type 2 diabetes (T2D) has revealed several key regulators of glucose homeostasis and insulin secretion in humans. Genome-wide association studies (GWAS) have been instrumental in most of these recent discoveries. The T2D susceptibility genes identified so far are mainly involved in pancreatic beta-cell maturation or function. However, common DNA variants in those genes only explain approximately 10% of T2D heritability. The resequencing of whole exomes and whole genomes with next-generation technologies should identify additional genetic changes that contribute to the monogenic forms of diabetes and possibly provide novel clues to the genetic architecture of common adult T2D.

ITPA gene variants protect against anaemia in patients treated for chronic hepatitis C

Chronic infection with the hepatitis C virus (HCV) affects 170 million people worldwide and is an important cause of liver-related morbidity and mortality. The standard of care therapy combines pegylated interferon (pegIFN) alpha and ribavirin (RBV), and is associated with a range of treatment-limiting adverse effects. One of the most important of these is RBV-induced haemolytic anaemia, which affects most patients and is severe enough to require dose modification in up to 15% of patients. Here we show that genetic variants leading to inosine triphosphatase deficiency, a condition not thought to be clinically important, protect against haemolytic anaemia in hepatitis-C-infected patients receiving RBV.

A genome-wide association study identifies a novel major locus for glycemic control in type 1 diabetes, as measured by both A1C and glucose

OBJECTIVE

Glycemia is a major risk factor for the development of long-term complications in type 1 diabetes; however, no specific genetic loci have been identified for glycemic control in individuals with type 1 diabetes. To identify such loci in type 1 diabetes, we analyzed longitudinal repeated measures of A1C from the Diabetes Control and Complications Trial.

RESEARCH DESIGN AND METHODS

We performed a genome-wide association study using the mean of quarterly A1C values measured over 6.5 years, separately in the conventional (n = 667) and intensive (n = 637) treatment groups of the DCCT. At loci of interest, linear mixed models were used to take advantage of all the repeated measures. We then assessed the association of these loci with capillary glucose and repeated measures of multiple complications of diabetes.

RESULTS

We identified a major locus for A1C levels in the conventional treatment group near SORCS1 (10q25.1, P = 7 x 10(-10)), which was also associated with mean glucose (P = 2 x 10(-5)). This was confirmed using A1C in the intensive treatment group (P = 0.01). Other loci achieved evidence close to genome-wide significance: 14q32.13 (GSC) and 9p22 (BNC2) in the combined treatment groups and 15q21.3 (WDR72) in the intensive group. Further, these loci gave evidence for association with diabetic complications, specifically SORCS1 with hypoglycemia and BNC2 with renal and retinal complications. We replicated the SORCS1 association in Genetics of Diabetes in Kidneys (GoKinD) study control subjects (P = 0.01) and the BNC2 association with A1C in nondiabetic individuals.

CONCLUSIONS

A major locus for A1C and glucose in individuals with diabetes is near SORCS1. This may influence the design and analysis of genetic studies attempting to identify risk factors for long-term diabetic complications.

Sequence variants in three loci influence monocyte counts and erythrocyte volume

Blood cells participate in vital physiological processes, and their numbers are tightly regulated so that homeostasis is maintained. Disruption of key regulatory mechanisms underlies many blood-related Mendelian diseases but also contributes to more common disorders, including atherosclerosis. We searched for quantitative trait loci (QTL) for hematology traits through a whole-genome association study, because these could provide new insights into both hemopoeitic and disease mechanisms. We tested 1.8 million variants for association with 13 hematology traits measured in 6015 individuals from the Australian and Dutch populations. These traits included hemoglobin composition, platelet counts, and red blood cell and white blood cell indices. We identified three regions of strong association that, to our knowledge, have not been previously reported in the literature. The first was located in an intergenic region of chromosome 9q31 near LPAR1, explaining 1.5% of the variation in monocyte counts (best SNP rs7023923, p=8.9x10(-14)). The second locus was located on chromosome 6p21 and associated with mean cell erythrocyte volume (rs12661667, p=1.2x10(-9), 0.7% variance explained) in a region that spanned five genes, including CCND3, a member of the D-cyclin gene family that is involved in hematopoietic stem cell expansion. The third region was also associated with erythrocyte volume and was located in an intergenic region on chromosome 6q24 (rs592423, p=5.3x10(-9), 0.6% variance explained). All three loci replicated in an independent panel of 1543 individuals (p values=0.001, 9.9x10(-5), and 7x10(-5), respectively). The identification of these QTL provides new opportunities for furthering our understanding of the mechanisms regulating hemopoietic cell fate.