Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies

A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.     

Preserving Insulin Secretion in Diabetes by Inhibiting VDAC1 Overexpression and Surface Translocation in β Cells

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Maize endosperm ADP-glucose pyrophosphorylase SHRUNKEN2 and BRITTLE2 subunit interactions

ADP-glucose pyrophosphorylase (AGP) represents a key regulatory step in polysaccharide synthesis in organisms ranging from bacteria to plants. Higher plant AGPs are complex in nature and are heterotetramers consisting of two similar but distinct subunits. How the subunits are assembled into enzymatically active polymers is not yet understood. Here, we address this issue by using naturally occurring null mutants of the Shrunken2 (Sh2) and Brittle2 (Bt2) loci of maize as well as the yeast two-hybrid expression system. In the absence of the maize endosperm large AGP subunit (SH2), the BT2 subunit remains as a monomer in the developing endosperm. In contrast, the SH2 protein, in the absence of BT2, is found in a complex of 100 kD. A direct interaction between SH2 and BT2 was proven when they were both expressed in yeast. Several motifs are essential for SH2:BT2 interaction because truncations removing the N or C terminus of either subunit eliminate SH2:BT2 interactions. Analysis of subunit interaction mutants (sim) also identified motifs essential for protein interactions.     

Telomere length in blood and skeletal muscle in relation to measures of glycaemia and insulinaemia

Diabet. Med. 29, e377-e381 (2012) ABSTRACT: Aims Skeletal muscle is a major metabolic organ and plays important roles in glucose metabolism, insulin sensitivity and insulin action. Muscle telomere length reflects the myocyte's exposure to harmful environmental factors. Leukocyte telomere length is considered a marker of muscle telomere length and is used in epidemiologic studies to assess associations with ageing-related diseases where muscle physiology is important. However, the extent to which leucocyte and muscle telomere length are correlated is unknown, as are their relative correlations with glucose and insulin concentrations. The purpose of this study was to determine the extent of these relationships. Methods Leucocyte and muscle telomere length were measured by quantitative real-time polymerase chain reaction in participants from the Malm? Exercise Intervention (n?=?27) and the Prevalence, Prediction and Prevention of Diabetes-Botnia studies (n?=?31). Participants in both studies were free from Type?2 diabetes. We assessed the association between leucocyte telomere length, muscle telomere length and metabolic traits using Spearmen correlations and multivariate linear regression. Bland-Altman analysis was used to assess agreement between leucocyte and muscle telomere length. Results In age-, study-, diabetes family history- and sex-adjusted models, leucocyte and muscle telomere length were positively correlated (r?=?0.39, 95%?CI 0.15-0.59). Leucocyte telomere length was inversely associated with 2-h glucose concentrations (r?=?-0.58, 95%?CI -1.0 to -0.16), but there was no correlation between muscle telomere length and 2-h glucose concentrations (r?=?0.05, 95%?CI -0.35 to 0.46) or between leucocyte or muscle telomere length with other metabolic traits. Conclusions In summary, the current study supports the use of leucocyte telomere length as a proxy for muscle telomere length in epidemiological studies of Type?2 diabetes aetiology.     

Characterization of systemic metabolic phenotypes associated with subclinical atherosclerosis

Detailed molecular phenotyping gives insight into disease mechanisms and can individualize medical practice for improved risk assessment and treatment. We show in an epidemiological study (n = 4309) that the multi-metabolic profiles obtained by serum NMR metabonomics inherently associate with the extent of atherosclerosis already in preclinical stages. Data-driven analysis of the spectral profiles of healthy, young adults revealed three distinct metabolic phenotypes associated with high carotid intima-media thickness (IMT), a surrogate marker of cardiovascular disease. The phenotypes were characterized by varying combinations of well-known metabolic disturbances like elevated VLDL and LDL and low HDL levels. Low IMT was also associated with distinct metabolic phenotypes with lipoprotein as well as other biochemical characteristics partly opposing those found for the high IMT phenotypes. Profiles of low-molecular-weight metabolites quantified from the experimentation were also characteristic for the metabolic phenotypes and substantiate developments toward the use of multi-metabolic risk phenotypes. The methodology can be taken as a direct extension for the routine analytics used for the risk assessment of atherosclerosis; quantification of metabolites will complement and might even replace conventional lipid measurements. Serum NMR metabonomics is therefore anticipated as a rational option for comprehensive cardiovascular risk assessment.     

Metabolic diversity of progressive kidney disease in 325 patients with type 1 diabetes (the FinnDiane Study)

Type 1 diabetic patients with varying severity of kidney disease were investigated to create multimetabolite models of the disease process. Urinary albumin excretion rate was measured for 3358 patients with type 1 diabetes. Prospective records were available for 1051 patients, of whom 163 showed progression of albuminuria (8.3-year follow-up), and 162 were selected as stable controls. At baseline, serum lipids, lipoprotein subclasses, and low-molecular weight metabolites were quantified by NMR spectroscopy (325 samples). The data were analyzed by the self-organizing map. In cross-sectional analyses, patients with no complications had low serum lipids, less inflammation, and better glycemic control, whereas patients with advanced kidney disease had high serum cystatin-C and sphingomyelin. These phenotype extremes shared low unsaturated fatty acids (UFAs) and phospholipids. Prospectively, progressive albuminuria was associated with high UFAs, phospholipids, and IDL and LDL lipids. Progression at longer duration was associated with high HDL lipids, whereas earlier progression was associated with poor glycemic control, increased saturated fatty acids (SFAs), and inflammation. Diabetic kidney disease consists of diverse metabolic phenotypes: UFAs, phospholipids, IDL, and LDL may be important in the subclinical phase, high SFAs and low HDL suggest accelerated progression, and the sphingolipid pathway in advanced kidney injury deserves further research.