Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus

<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies (GWAS) have emerged as a powerful approach for identifying susceptibility loci associated with polygenetic diseases such as type 2 diabetes mellitus (T2DM). However, it is still a daunting task to prioritize single nucleotide polymorphisms (SNPs) from GWAS for further replication in different population. Several recent studies have shown that genetic variation often affects gene-expression at proximal (<it>cis</it>) as well as distal (<it>trans</it>) genomic locations by different mechanisms such as altering rate of transcription or splicing or transcript stability.</p> <p>Methods</p> <p>To prioritize SNPs from GWAS, we combined results from two GWAS related to T2DM, the Diabetes Genetics Initiative (DGI) and the Wellcome Trust Case Control Consortium (WTCCC), with genome-wide expression data from pancreas, adipose tissue, liver and skeletal muscle of individuals with or without T2DM or animal models thereof to identify T2DM susceptibility loci.</p> <p>Results</p> <p>We identified 1,170 SNPs associated with T2DM with <it>P </it>< 0.05 in both GWAS and 243 genes that were located in the vicinity of these SNPs. Out of these 243 genes, we identified 115 differentially expressed in publicly available gene expression profiling data. Notably five of them, <it>IGF2BP2</it>, <it>KCNJ11</it>, <it>NOTCH2</it>, <it>TCF7L2 </it>and <it>TSPAN8</it>, have subsequently been shown to be associated with T2DM in different populations. To provide further validation of our approach, we reversed the approach and started with 26 known SNPs associated with T2DM and related traits. We could show that 12 (57%) (<it>HHEX</it>, <it>HNF1B</it>, <it>IGF2BP2</it>, <it>IRS1</it>, <it>KCNJ11</it>, <it>KCNQ1</it>, <it>NOTCH2</it>, <it>PPARG</it>, <it>TCF7L2</it>, <it>THADA</it>, <it>TSPAN8 </it>and <it>WFS1</it>) out of 21 genes located in vicinity of these SNPs were showing aberrant expression in T2DM from the gene expression profiling studies.</p> <p>Conclusions</p> <p>Utilizing of gene expression profiling data from different tissues of individuals with or without T2DM or animal models thereof is a powerful tool for prioritizing SNPs from WGAS for further replication studies.</p

Previously Associated Type 2 Diabetes Variants May Interact With Physical Activity to Modify the Risk of Impaired Glucose Regulation and Type 2 Diabetes: A Study of 16,003 Swedish Adults

OBJECTIVE-Recent advances in type 2 diabetes genetics have culminated in the discovery and confirmation of multiple risk variants. Two important, and largely unanswered questions are whether this information can be used to identify individuals most susceptible to the adverse consequences of sedentary behavior and to predict their response to lifestyle intervention; such evidence Would be mechanistically informative and provide a rationale for targeting genetically susceptible subgroups of the population. RESEARCH DESIGN AND METHODS-Gene X physical activity interactions were assessed for 17 polymorphisms ill a prospective population-based cohort of initially nondiabetic middle-aged adults. Outcomes were 1) impaired glucose regulation (IGR) versus normal glucose regulation determined with either fasting or 2-h plasma glucose concentrations (n = 16,003), 2) glucose intolerance (in mmol/l, n = 8,860), or 3) incident, type 2 diabetes (n = 2,063 events). RESULTS-Tests of gene X physical activity interactions oil IGR risk for 3 of the 17 polymorphisms were nominally statistically significant: CDKNT2A/B rs10811661 (P-interaction = 0.015), HNF1B rs4430796 (P-interaction = 0.026), and PPARG rs1801282 (P-interaction = 0.04). Consistent interactions were observed for the CDKN2A/B (P-interaction = 0.013) and HNF1B (P-interaction = 0.0009) variants on 2-h glucose concentrations. Where type 2 diabetes was the outcome, only one statistically significant interaction effect was observed, and this was for the HNF1B rs4430796 variant, (P-interaction = 0.0004). The interaction effects for HNF1B on IGR risk and incident diabetes remained significant after correction for multiple testing (P-interaction = 0.015 and 0.0068, respectively). CONCLUSIONS-Our observations suggest that the genetic predisposition to hyperglycemia is partially dependent on a person's lifestyle. Diabetes 58:1411-1418, 200

Associations of Common Genetic Variants With Age-Related Changes in Fasting and Postload Glucose: Evidence From 18 Years of Follow-Up of the Whitehall II Cohort

OBJECTIVE In the general, nondiabetic population, fasting glucose increases only slightly over time, whereas 2-h postload glucose shows a much steeper age-related rise. The reasons underlying these different age trajectories are unknown. We investigated whether common genetic variants associated with fasting and 2-h glucose contribute to age-related changes of these traits.RESEARCH DESIGN AND METHODS We studied 5,196 nondiabetic participants of the Whitehall 11 cohort (aged 40-78 years) attending up to four 5-yearly oral glucose tolerance tests. A genetic score was calculated separately for fasting and 2-h glucose, including 16 and 5 single nucleotide polymorphisms, respectively. Longitudinal modeling with age centered at 55 years was used to study the effects of each genotype and genetic score on fasting and 2-h glucose and their interactions with age, adjusting for sex and time-varying BMI.RESULTS The fasting glucose genetic score was significantly associated with fasting glucose with a 0,029 mmol/L (95% CI 0.023-0.034) difference (P = 2.76 x 10(-21)) per genetic score point, an association that remained constant over time (age interaction P = 0.17). Two-hour glucose levels differed by 0.076 mmol/L (0.047-0.105) per genetic score point (P = 3.1 x 10(-7)); notably, this effect became stronger with increasing age by 0.006 mmol/L (0.003-0.009) per genetic score point per year (age interaction P = 3.0 x 10(-5)), resulting in diverging age trajectories by genetic score.CONCLUSIONS Common genetic variants contribute to the age-related rise of 2-h glucose levels, whereas associations of variants for fasting glucose are constant over time, in line with stable age trajectories of fasting glucose. Diabetes 60:16171623, 201

Effects of impurity scattering on electron-phonon resonances in semiconductor superlattice high-field transport

A non-equilibrium Green's function method is applied to model high-field quantum transport and electron-phonon resonances in semiconductor superlattices. The field-dependent density of states for elastic (impurity) scattering is found non-perturbatively in an approach which can be applied to both high and low electric fields. I-V curves, and specifically electron-phonon resonances, are calculated by treating the inelastic (LO phonon) scattering perturbatively. Calculations show how strong impurity scattering suppresses the electron-phonon resonance peaks in I-V curves, and their detailed sensitivity to the size, strength and concentration of impurities.Comment: 7 figures, 1 tabl

A Variant of GJD2, Encoding for Connexin 36, Alters the Function of Insulin Producing β-Cells.

Signalling through gap junctions contributes to control insulin secretion and, thus, blood glucose levels. Gap junctions of the insulin-producing β-cells are made of connexin 36 (Cx36), which is encoded by the GJD2 gene. Cx36-null mice feature alterations mimicking those observed in type 2 diabetes (T2D). GJD2 is also expressed in neurons, which share a number of common features with pancreatic β-cells. Given that a synonymous exonic single nucleotide polymorphism of human Cx36 (SNP rs3743123) associates with altered function of central neurons in a subset of epileptic patients, we investigated whether this SNP also caused alterations of β-cell function. Transfection of rs3743123 cDNA in connexin-lacking HeLa cells resulted in altered formation of gap junction plaques and cell coupling, as compared to those induced by wild type (WT) GJD2 cDNA. Transgenic mice expressing the very same cDNAs under an insulin promoter revealed that SNP rs3743123 expression consistently lead to a post-natal reduction of islet Cx36 levels and β-cell survival, resulting in hyperglycemia in selected lines. These changes were not observed in sex- and age-matched controls expressing WT hCx36. The variant GJD2 only marginally associated to heterogeneous populations of diabetic patients. The data document that a silent polymorphism of GJD2 is associated with altered β-cell function, presumably contributing to T2D pathogenesis

Combined Risk Allele Score of Eight Type 2 Diabetes Genes Is Associated With Reduced First-Phase Glucose-Stimulated Insulin Secretion During Hyperglycemic Clamps

OBJECTIVE - At least 20 type 2 diabetes loci have now been identified, and several of these are associated with altered β-cell function. In this study, we have investigated the combined effects of eight known β-cell loci on insulin secretion stimulated by three different secretagogues during hyperglycemic clamps. RESEARCH DESIGN AND METHODS - A total of 447 subjects originating from four independent studies in the Netherlands and Germany (256 with normal glucose tolerance [NGT]/ 191 with impaired glucose tolerance [IGT]) underwent a hyperglycemic clamp. A subset had an extended clamp with additional glucagon-like peptide (GLP)-1 and arginine (n = 224). We next genotyped single nucleotide polymorphisms in TCF7L2, KCNJ11, CDKAL1, IGF2BP2, HHEX/IDE, CDKN2A/B, SLC30A8, and MTNR1B and calculated a risk allele score by risk allele counting. RESULTS - The risk allele score was associated with lower first-phase glucose-stimulated insulin secretion (GSIS) (P = 7.1 × 1

Genetic Architecture of Type 2 Diabetes: Recent Progress and Clinical Implications

Review. Introductory paragraph: With the exception of rare monogenic disorders, most type 2 diabetes results from the interaction of genetic variation at multiple different chromosomal sites with environmental exposures experienced throughout the lifespan (1). This complex genetic architecture has important consequences for understanding the pathophysiology of type 2 diabetes, both for researchers seeking mechanistic insight into disease progression and for clinicians hoping to translate this new genetic information into more effective patient management. With nearly two dozen genes associated with type 2 diabetes, including some genetic variants that appear to modify responses to commonly prescribed diabetes medications and lifestyle interventions, we may be on the verge of a new era in which a patient’s individual genetic profile can add useful information to clinical care. Indeed, commercial companies are already offering genome-wide genetic profiling that includes information related to diabetes risk (2). Further advances in type 2 diabetes genetic discovery hold the promise, as yet unrealized, of enabling clinicians to individualize care for their patients by basing their clinical decisions on patient risk for disease progression, propensity to develop specific complications, and likely response to different medication classes. At present it is unknown whether individual genetic information may also serve to effectively motivate patient behavior change, a cornerstone of diabetes and pre-diabetes management. In this review of polygenic type 2 diabetes, we focus on recent discoveries made via linkage analyses, candidate gene association studies and genome-wide association (GWA) scans and highlight potential clinical applications of new genetic knowledge to risk prediction, pharmacologic management, and patient behavior. Monogenic diabetes has recently been reviewed elsewhere (3)

Bloch oscillations of magnetic solitons in anisotropic spin-1/2 chains

We study the quantum dynamics of soliton-like domain walls in anisotropic spin-1/2 chains in the presence of magnetic fields. In the absence of fields, domain walls form a Bloch band of delocalized quantum states while a static field applied along the easy axis localizes them into Wannier wave packets and causes them to execute Bloch oscillations, i.e. the domain walls oscillate along the chain with a finite Bloch frequency and amplitude. In the presence of the field, the Bloch band, with a continuum of extended states, breaks up into the Wannier-Zeeman ladder -- a discrete set of equally spaced energy levels. We calculate the dynamical structure factor in the one-soliton sector at finite frequency, wave vector, and temperature, and find sharp peaks at frequencies which are integer multiples of the Bloch frequency. We further calculate the uniform magnetic susceptibility and find that it too exhibits peaks at the Bloch frequency. We identify several candidate materials where these Bloch oscillations should be observable, for example, via neutron scattering measurements. For the particular compound CoCl_2.2H_2O we estimate the Bloch amplitude to be on the order of a few lattice constants, and the Bloch frequency on the order of 100 GHz for magnetic fields in the Tesla range and at temperatures of about 18 Kelvin.Comment: 31 single-spaced REVTeX pages, including 7 figures embedded with eps