Genetically determined height and coronary artery disease.

BACKGROUND: The nature and underlying mechanisms of an inverse association between adult height and the risk of coronary artery disease (CAD) are unclear. METHODS: We used a genetic approach to investigate the association between height and CAD, using 180 height-associated genetic variants. We tested the association between a change in genetically determined height of 1 SD (6.5 cm) with the risk of CAD in 65,066 cases and 128,383 controls. Using individual-level genotype data from 18,249 persons, we also examined the risk of CAD associated with the presence of various numbers of height-associated alleles. To identify putative mechanisms, we analyzed whether genetically determined height was associated with known cardiovascular risk factors and performed a pathway analysis of the height-associated genes. RESULTS: We observed a relative increase of 13.5% (95% confidence interval [CI], 5.4 to 22.1; P<0.001) in the risk of CAD per 1-SD decrease in genetically determined height. There was a graded relationship between the presence of an increased number of height-raising variants and a reduced risk of CAD (odds ratio for height quartile 4 versus quartile 1, 0.74; 95% CI, 0.68 to 0.84; P<0.001). Of the 12 risk factors that we studied, we observed significant associations only with levels of low-density lipoprotein cholesterol and triglycerides (accounting for approximately 30% of the association). We identified several overlapping pathways involving genes associated with both development and atherosclerosis. CONCLUSIONS: There is a primary association between a genetically determined shorter height and an increased risk of CAD, a link that is partly explained by the association between shorter height and an adverse lipid profile. Shared biologic processes that determine achieved height and the development of atherosclerosis may explain some of the association. (Funded by the British Heart Foundation and others.)

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE Glycated hemoglobin (HbA1c), 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 HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c 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 HbA1c 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 HbA1c, 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 HbA1c 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 HbA1c 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 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. 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 HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c

The ac magnetic response of mesoscopic type II superconductors

The response of mesoscopic superconductors to an ac magnetic field is numerically investigated on the basis of the time-dependent Ginzburg-Landau equations (TDGL). We study the dependence with frequency $\omega$ and dc magnetic field $H_{dc}$ of the linear ac susceptibility $\chi(H_{dc}, \omega)$ in square samples with dimensions of the order of the London penetration depth. At $H_{dc}=0$ the behavior of $\chi$ as a function of $\omega$ agrees very well with the two fluid model, and the imaginary part of the ac susceptibility, $\chi"(\omega)$, shows a dissipative a maximum at the frequency $\nu_o=c^2/(4\pi \sigma\lambda^2)$. In the presence of a magnetic field a second dissipation maximum appears at a frequency $\omega_p\ll\nu_0$. The most interesting behavior of mesoscopic superconductors can be observed in the $\chi(H_{dc})$ curves obtained at a fixed frequency. At a fixed number of vortices, $\chi"(H_{dc})$ continuously increases with increasing $H_{dc}$. We observe that the dissipation reaches a maximum for magnetic fields right below the vortex penetration fields. Then, after each vortex penetration event, there is a sudden suppression of the ac losses, showing discontinuities in $\chi"(H_{dc})$ at several values of $H_{dc}$. We show that these discontinuities are typical of the mesoscopic scale and disappear in macroscopic samples, which have a continuos behavior of $\chi(H_{dc})$. We argue that these discontinuities in $\chi(H_{dc})$ are due to the effect of {\it nascent vortices} which cause a large variation of the amplitude of the order parameter near the surface before the entrance of vortices.Comment: 12 pages, 9 figures, RevTex

Comparative effectiveness of dipeptidyl peptidase-4 (DPP-4) inhibitors and human glucagon-like peptide-1 (GLP-1) analogue as add-on therapies to sulphonylurea among diabetes patients in the Asia-Pacific region: a systematic review

The prevalence of diabetes mellitus is rising globally, and it induces a substantial public health burden to the healthcare systems. Its optimal control is one of the most significant challenges faced by physicians and policy-makers. Whereas some of the established oral hypoglycaemic drug classes like biguanide, sulphonylureas, thiazolidinediones have been extensively used, the newer agents like dipeptidyl peptidase-4 (DPP-4) inhibitors and the human glucagon-like peptide-1 (GLP-1) analogues have recently emerged as suitable options due to their similar efficacy and favorable side effect profiles. These agents are widely recognized alternatives to the traditional oral hypoglycaemic agents or insulin, especially in conditions where they are contraindicated or unacceptable to patients. Many studies which evaluated their clinical effects, either alone or as add-on agents, were conducted in Western countries. There exist few reviews on their effectiveness in the Asia-Pacific region. The purpose of this systematic review is to address the comparative effectiveness of these new classes of medications as add-on therapies to sulphonylurea drugs among diabetic patients in the Asia-Pacific countries. We conducted a thorough literature search of the MEDLINE and EMBASE from the inception of these databases to August 2013, supplemented by an additional manual search using reference lists from research studies, meta-analyses and review articles as retrieved by the electronic databases. A total of nine randomized controlled trials were identified and described in this article. It was found that DPP-4 inhibitors and GLP-1 analogues were in general effective as add-on therapies to existing sulphonylurea therapies, achieving HbA1c reductions by a magnitude of 0.59–0.90% and 0.77–1.62%, respectively. Few adverse events including hypoglycaemic attacks were reported. Therefore, these two new drug classes represent novel therapies with great potential to be major therapeutic options. Future larger-scale research should be conducted among other Asia-Pacific region to evaluate their efficacy in other ethnic groups

Role of the FOXC2 -512C&gt;T polymorphism in type 2 diabetes: possible association with the dysmetabolic syndrome.

OBJECTIVE: Overexpression of the human transcription factor FOXC2 gene ( FOXC2) protects against insulin resistance in mice and a common FOXC2 polymorphism (-512C > T) has been suggested to be associated with insulin resistance in humans. Here, we addressed the potential role for FOXC2 as a candidate gene for type 2 diabetes and associated phenotypes. MATERIALS AND METHODS: A case-control study was performed in 390 type 2 diabetic patients and 307 control subjects. The number of patients was increased to a total of 768 subjects for further study of phenotypic differences relating to the dysmetabolic syndrome relative to genetic variation. The FOXC2 -512C > T polymorphism was genotyped by a restriction fragment length polymorphism PCR assay. RESULTS: FOXC2 -512C > T allele and genotype distribution did not differ between patients with type 2 diabetes and control subjects, but the C/C genotype was associated with increased body mass index (BMI, kg/m(2)) (P-a = 0.03) among type 2 diabetic patients. The FOXC2 -512C > T polymorphism was a significant independent predictor of BMI (P = 0.001) in a multiple regression model including age, gender and affection status. We found no significant association with type 2 diabetes-related metabolic parameters but that the C-allele (P = 0.01) and C/C and C/T genotypes (P = 0.03) were significantly over-represented in type 2 diabetic males with a concomitant diagnosis of dysmetabolic syndrome. CONCLUSION: We conclude that FOXC2 is associated with obesity and metabolic deterioration but does not contribute to an increased risk for type 2 diabetes

Adherence to special diets and its association with meeting the nutrient recommendations in individuals with type 1 diabetes

Not much is known about adherence to special diets in type 1 diabetes, characteristics of individuals with special diets, and whether such practices should raise concerns with respect to meeting the dietary recommendations. In this study, we assessed the frequencies of adherence to special diets, in a population of individuals with type 1 diabetes, and investigated the association between special diet adherence and dietary intake, measured as dietary patterns and nutrient intakes. During the Finnish Diabetic Nephropathy Study visit, participants with type 1 diabetes (n = 1429) were instructed to complete a diet questionnaire inquiring about the adherence to special diets. The participants also completed a food record, from which energy and nutrient intakes were calculated. In all, 36.6% participants reported adhering to some special diet. Most commonly reported special diets were lactose-free (17.1%), protein restriction (10.0%), vegetarian (7.0%), and gluten-free (5.6%) diet. Special diet adherents were more frequently women, older, had longer diabetes duration, and more frequently had various diabetes complications. Mean carbohydrate intakes were close to the lower levels of the recommendation in all diet groups, which was reflected in low mean fibre intakes but high frequencies of meeting the sucrose recommendations. The recommendation for saturated fatty acid intake was frequently unmet, with the highest frequencies observed in vegetarians. Of the micronutrients, vitamin D, folate, and iron recommendations were most frequently unmet, with some differences between the diet groups. Special diets are frequently followed by individuals with type 1 diabetes. The adherents are more frequently women, and have longer diabetes duration and more diabetes complications. Achieving the dietary recommendations differed between diets, and depended on the nutrient in question. Overall, intakes of fibre, vitamin D, folate, and iron fell short of the recommendations.Peer reviewe

Analysis of case-control association studies with known risk variants

Motivation: The question of how to best use information from known associated variants when conducting disease association studies has yet to be answered. Some studies compute a marginal P-value for each Several Nucleotide Polymorphisms independently, ignoring previously discovered variants. Other studies include known variants as covariates in logistic regression, but a weakness of this standard conditioning strategy is that it does not account for disease prevalence and non-random ascertainment, which can induce a correlation structure between candidate variants and known associated variants even if the variants lie on different chromosomes. Here, we propose a new conditioning approach, which is based in part on the classical technique of liability threshold modeling. Roughly, this method estimates model parameters for each known variant while accounting for the published disease prevalence from the epidemiological literature. Results: We show via simulation and application to empirical datasets that our approach outperforms both the no conditioning strategy and the standard conditioning strategy, with a properly controlled false-positive rate. Furthermore, in multiple data sets involving diseases of low prevalence, standard conditioning produces a severe drop in test statistics whereas our approach generally performs as well or better than no conditioning. Our approach may substantially improve disease gene discovery for diseases with many known risk variants. Availability: LTSOFT software is available online http://www.hsph.harvard.edu/faculty/alkes-price/software/ Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research

A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate global searching of available samples for research. The use cases include the ENGAGE (European Network for Genetic and Genomic Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate markers for micro- and macro-vascular hard endpoints for innovative diabetes tools) consortium and a pilot for data integration between a Swedish clinical health registry and a biobank. We used the Sample avAILability (SAIL) method for data linking: first, created harmonised variables and then annotated and made searchable information on the number of specimens available in individual biobanks for various phenotypic categories. By operating on this categorised availability data we sidestep many obstacles related to privacy that arise when handling real values and show that harmonised and annotated records about data availability across disparate biomedical archives provide a key methodological advance in pre-analysis exchange of information between biobanks, that is, during the project planning phase