Novel Association of HK1 with Glycated Hemoglobin in a Non-Diabetic Population: A Genome-Wide Evaluation of 14,618 Participants in the Women's Genome Health Study

Type 2 diabetes is a leading cause of morbidity and mortality. While genetic variants have been found to influence the risk of type 2 diabetes mellitus, relatively few studies have focused on genes associated with glycated hemoglobin, an index of the mean blood glucose concentration of the preceding 8–12 weeks. Epidemiologic studies and randomized clinical trials have documented the relationship between glycated hemoglobin levels and the development of long-term complications in diabetes; moreover, higher glycated hemoglobin levels in the subdiabetic range have been shown to predict type 2 diabetes risk and cardiovascular disease. To examine the common genetic determinants of glycated hemoglobin levels, we performed a genome-wide association study that evaluated 337,343 SNPs in 14,618 apparently healthy Caucasian women. The results show that glycated hemoglobin levels are associated with genetic variation at the GCK (rs730497; P = 2.8×10−12), SLC30A8 (rs13266634; P = 9.8×10−8), G6PC2 (rs1402837; P = 6.8×10−10), and HK1 (rs7072268; P = 6.4×10−9) loci. While associations at the GCK, SLC30A8, and G6PC2 loci are confirmatory, the findings at HK1 are novel. We were able to replicate this novel association in an independent validation sample of 455 additional non-diabetic men and women. HK1 encodes the enzyme hexokinase, the first step in glycolysis and a likely candidate for the control of glucose metabolism. This observed genetic association between glycated hemoglobin levels and HK1 polymorphisms paves the way for further studies of the role of HK1 in hemoglobin glycation, glucose metabolism, and diabetes

Habitual sleep disturbances and migraine: a Mendelian randomization study

Objective: Sleep disturbances are associated with increased risk of migraine, however the extent of shared underlying biology and the direction of causal relationships between these traits is unclear. Delineating causality between sleep patterns and migraine may offer new pathophysiologic insights and inform subsequent intervention studies. Here, we used genetic approaches to test for shared genetic influences between sleep patterns and migraine, and to test whether habitual sleep patterns may be causal risk factors for migraine and vice versa.Methods: To quantify genetic overlap, we performed genome-wide genetic correlation analyses using genome-wide association studies of nine sleep traits in the UK Biobank (n ≥ 237,627), and migraine from the International Headache Genetics Consortium (59,674 cases and 316,078 controls). We then tested for potential causal effects between sleep traits and migraine using bidirectional, two-sample Mendelian randomization.Results: Seven sleep traits demonstrated genetic overlap with migraine, including insomnia symptoms (rg = 0.29, P Interpretation: These data support a shared genetic basis between several sleep traits and migraine, and support potential causal effects of difficulty awakening and insomnia symptoms on migraine risk. Treatment of sleep disturbances may therefore be a promising clinical intervention in the management of migraine.</p

A genome-wide cross-phenotype meta-analysis of the association of blood pressure with migraine

Blood pressure (BP) was inconsistently associated with migraine and the mechanisms of BP-lowering medications in migraine prophylaxis are unknown. Leveraging large-scale summary statistics for migraine (Ncases/Ncontrols = 59,674/316,078) and BP (N = 757,601), we find positive genetic correlations of migraine with diastolic BP (DBP, rg = 0.11, P = 3.56 × 10-06) and systolic BP (SBP, rg = 0.06, P = 0.01), but not pulse pressure (PP, rg = -0.01, P = 0.75). Cross-trait meta-analysis reveals 14 shared loci (P ≤ 5 × 10-08), nine of which replicate (P < 0.05) in the UK Biobank. Five shared loci (ITGB5, SMG6, ADRA2B, ANKDD1B, and KIAA0040) are reinforced in gene-level analysis and highlight potential mechanisms involving vascular development, endothelial function and calcium homeostasis. Mendelian randomization reveals stronger instrumental estimates of DBP (OR [95% CI] = 1.20 [1.15-1.25]/10 mmHg; P = 5.57 × 10-25) on migraine than SBP (1.05 [1.03-1.07]/10 mmHg; P = 2.60 × 10-07) and a corresponding opposite effect for PP (0.92 [0.88-0.95]/10 mmHg; P = 3.65 × 10-07). These findings support a critical role of DBP in migraine susceptibility and shared biology underlying BP and migraine

Measurement of the response of heat-and-ionization germanium detectors to nuclear recoils

The heat quenching factor Q' (the ratio of the heat signals produced by nuclear and electron recoils of equal energy) of the heat-and-ionization germanium bolometers used by the EDELWEISS collaboration has been measured. It is explained how this factor affects the energy scale and the effective quenching factor observed in calibrations with neutron sources. This effective quenching effect is found to be equal to Q/Q', where Q is the quenching factor of the ionization yield. To measure Q', a precise EDELWEISS measurement of Q/Q' is combined with values of Q obtained from a review of all available measurements of this quantity in tagged neutron beam experiments. The systematic uncertainties associated with this method to evaluate Q' are discussed in detail. For recoil energies between 20 and 100 keV, the resulting heat quenching factor is Q' = 0.91+-0.03+-0.04, where the two errors are the contributions from the Q and Q/Q' measurements, respectively. The present compilation of Q values and evaluation of Q' represent one of the most precise determinations of the absolute energy scale for any detector used in direct searches for dark matter.Comment: 28 pages, 7 figures. Submitted to Phys. Rev.

The Pharmacogenetics of Statin Therapy on Clinical Events: No Evidence that Genetic Variation Affects Statin Response on Myocardial Infarction

Background: The pharmacogenetic effect on cardiovascular disease reduction in response to statin treatment has only been assessed in small studies. In a pharmacogenetic genome wide association study (GWAS) analysis within the Genomic Investigation of Statin Therapy (GIST) consortium, we investigated whether genetic variation was associated with the response of statins on cardiovascular disease risk reduction. Methods: The investigated endpoint was incident myocardial infarction (MI) defined as coronary heart disease death and definite and suspect non-fatal MI. For imputed single nucleotide polymorphisms (SNPs), regression analysis was performed on expected allelic dosage and meta-analysed with a fixed-effects model, inverse variance weighted meta-analysis. All SNPs with p-values <5.0 × 10(−4) in stage 1 GWAS meta-analysis were selected for further investigation in stage-2. As a secondary analysis, we extracted SNPs from the Stage-1 GWAS meta-analysis results based on predefined hypotheses to possibly modifying the effect of statin therapy on MI. Results: In stage-1 meta-analysis (eight studies, n = 10,769, 4,212 cases), we observed no genome-wide significant results (p < 5.0 × 10(−8)). A total of 144 genetic variants were followed-up in the second stage (three studies, n = 1,525, 180 cases). In the combined meta-analysis, no genome-wide significant hits were identified. Moreover, none of the look-ups of SNPs known to be associated with either CHD or with statin response to cholesterol levels reached Bonferroni level of significance within our stage-1 meta-analysis. Conclusion: This GWAS analysis did not provide evidence that genetic variation affects statin response on cardiovascular risk reduction. It does not appear likely that genetic testing for predicting effects of statins on clinical events will become a useful tool in clinical practice

Rare coding SNP in DZIP1 gene associated with late-onset sporadic Parkinson's disease

We present the first application of the hypothesis-rich mathematical theory to genome-wide association data. The Hamza et al. late-onset sporadic Parkinson's disease genome-wide association study dataset was analyzed. We found a rare, coding, non-synonymous SNP variant in the gene DZIP1 that confers increased susceptibility to Parkinson's disease. The association of DZIP1 with Parkinson's disease is consistent with a Parkinson's disease stem-cell ageing theory.Comment: 14 page

Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque

Carotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 × 10 -8). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events

Association of rs780094 in GCKR with Metabolic Traits and Incident Diabetes and Cardiovascular Disease: The ARIC Study

The minor T-allele of rs780094 in the glucokinase regulator gene (GCKR) associates with a number of metabolic traits including higher triglyceride levels and improved glycemic regulation in study populations of mostly European ancestry. Using data from the Atherosclerosis Risk in Communities (ARIC) Study, we sought to replicate these findings, examine them in a large population-based sample of African American study participants, and to investigate independent associations with other metabolic traits in order to determine if variation in GKCR contributes to their observed clustering. In addition, we examined the association of rs780094 with incident diabetes, coronary heart disease (CHD), and stroke over up mean follow-up times of 8, 15, and 15 years, respectively.Race-stratified analyses were conducted among 10,929 white and 3,960 black participants aged 45-64 at baseline assuming an additive genetic model and using linear and logistic regression and Cox proportional hazards models.Previous findings replicated among white participants in multivariable adjusted models: the T-allele of rs780094 was associated with lower fasting glucose (p = 10(-7)) and insulin levels (p = 10(-6)), lower insulin resistance (HOMA-IR, p = 10(-9)), less prevalent diabetes (p = 10(-6)), and higher CRP (p = 10(-8)), 2-h postprandial glucose (OGTT, p = 10(-6)), and triglyceride levels (p = 10(-31)). Moreover, the T-allele was independently associated with higher HDL cholesterol levels (p = 0.022), metabolic syndrome prevalence (p = 0.043), and lower beta-cell function measured as HOMA-B (p = 0.011). Among black participants, the T-allele was associated only with higher triglyceride levels (p = 0.004) and lower insulin levels (p = 0.002) and HOMA-IR (p = 0.013). Prospectively, the T-allele was associated with reduced incidence of diabetes (p = 10(-4)) among white participants, but not with incidence of CHD or stroke.Our findings indicate rs780094 has independent associations with multiple metabolic traits as well as incident diabetes, but not incident CHD or stroke. The magnitude of association between the SNP and most traits was of lower magnitude among African American compared to white participants

QTL/microarray approach using pathway information

<p>Abstract</p> <p>Background</p> <p>A combined quantitative trait loci (QTL) and microarray-based approach is commonly used to find differentially expressed genes which are then identified based on the known function of a gene in the biological process governing the trait of interest. However, a low cutoff value in individual gene analyses may result in many genes with moderate but meaningful changes in expression being missed.</p> <p>Results</p> <p>We modified a gene set analysis to identify intersection sets with significantly affected expression for which the changes in the individual gene sets are less significant. The gene expression profiles in liver tissues of four strains of mice from publicly available microarray sources were analyzed to detect trait-associated pathways using information on the QTL regions of blood concentrations of high density lipoproteins (HDL) cholesterol and insulin-like growth factor 1 (IGF-1). Several metabolic pathways related to HDL levels, including lipid metabolism, ABC transporters and cytochrome P450 pathways were detected for HDL QTL regions. Most of the pathways identified for the IGF-1 phenotype were signal transduction pathways associated with biological processes for IGF-1's regulation.</p> <p>Conclusion</p> <p>We have developed a method of identifying pathways associated with a quantitative trait using information on QTL. Our approach provides insights into genotype-phenotype relations at the level of biological pathways which may help to elucidate the genetic architecture underlying variation in phenotypic traits.</p

Genetic correlations between diabetes and glaucoma: an analysis of continuous and dichotomous phenotypes

Purpose: A genetic correlation is the proportion of phenotypic variance between traits that is shared on a genetic basis. Here we explore genetic correlations between diabetes- and glaucoma-related traits.Design: Cross-sectional study.Methods: We assembled genome-wide association study summary statistics from European-derived participants regarding diabetes-related traits like fasting blood sugar (FBS) and type 2 diabetes (T2D) and glaucoma-related traits (intraocular pressure (IOP), central corneal thickness (CCT), corneal hysteresis (CH), corneal resistance factor (CRF), cup-disc ratio (CDR), and primary open-angle glaucoma (POAG)). We included data from the National Eye Institute Glaucoma Human Genetics Collaboration Heritable Overall Operational Database, the UK Biobank and the International Glaucoma Genetics Consortium. We calculated genetic correlation (rg) between traits using linkage disequilibrium score regression. We also calculated genetic correlations between IOP, CCT and selected diabetes-related traits based on individual level phenotype data in two Northern European population-based samples using pedigree information and Sequential Oligogenic Linkage Analysis Routines (SOLAR).Results: Overall, there was little rg between diabetes- and glaucoma-related traits. Specifically, we found a non-significant negative correlation between T2D and POAG (rg=-0.14; p=0.16). Using SOLAR, the genetic correlations between measured IOP, CCT, FBS, fasting insulin and hemoglobin A1c, were null. In contrast, genetic correlations between IOP and POAG (rg ≥0.45; p≤3.0E-04) and between CDR and POAG were high (rg =0.57; p=2.8E-10). However, genetic correlations between corneal properties (CCT, CRF and CH) and POAG were low (rg range: -0.18 - 0.11) and non-significant (p≥0.07).Conclusion: These analyses suggest there is limited genetic correlation between diabetes- and glaucoma-related traits