The functional "KL-VS" variant of KLOTHO is not associated with type 2 diabetes in 5028 UK Caucasians

BACKGROUND: Klotho has an important role in insulin signalling and the development of ageing-like phenotypes in mice. The common functional "KL-VS" variant in the KLOTHO (KL) gene is associated with longevity in humans but its role in type 2 diabetes is not known. We performed a large case-control and family-based study to test the hypothesis that KL-VS is associated with type 2 diabetes in a UK Caucasian population. METHODS: We genotyped 1793 cases, 1619 controls and 1616 subjects from 509 families for the single nucleotide polymorphism (SNP) F352V (rs9536314) that defines the KL-VS variant. Allele and genotype frequencies were compared between cases and controls. Family-based analysis was used to test for over- or under-transmission of V352 to affected offspring. RESULTS: Despite good power to detect odds ratios of 1.2, there were no significant associations between alleles or genotypes and type 2 diabetes (V352 allele: odds ratio = 0.96 (0.84–1.09)). Additional analysis of quantitative trait data in 1177 healthy control subjects showed no association of the variant with fasting insulin, glucose, triglycerides, HDL- or LDL-cholesterol (all P > 0.05). However, the HDL-cholesterol levels observed across the genotype groups showed a similar, but non-significant, pattern to previously reported data. CONCLUSION: This is the first large-scale study to examine the association between common functional variation in KL and type 2 diabetes risk. We have found no evidence that the functional KL-VS variant is a risk factor for type 2 diabetes in a large UK Caucasian case-control and family-based study

The fate of the homoctenids (Tentaculitoidea) during the Frasnian-Famennian mass extinction (Late Devonian)

The homoctenids (Tentaculitoidea) are small, conical-shelled marine animals which are amongst the most abundant and widespread of all Late Devonian fossils. They were a principal casualty of the Frasnian-Famennian (F-F, Late Devonian) mass extinction, and thus provide an insight into the extinction dynamics. Despite their abundance during the Late Devonian, they have been largely neglected by extinction studies. A number of Frasnian-Famennian boundary sections have been studied, in Poland, Germany, France, and the United States. These sections have yielded homoctenids, which allow precise recognition of the timing of the mass extinction. It is clear that the homoctenids almost disappear from the fossil record during the latest Frasnian “Upper Kellwasser Event”. The coincident extinction of this pelagic group, and the widespread development of intense marine anoxia within the water column, provides a causal link between anoxia and the F-F extinction. Most notable is the sudden demise of a group, which had been present in rock-forming densities, during this anoxic event. One new species, belonging to Homoctenus is described, but is not formally named here

Genetic Determinants of Variability in Glycated Hemoglobin (HbA1c) in Humans: Review of Recent Progress and Prospects for Use in Diabetes Care

Glycated hemoglobin A1c (HbA1c) 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. HbA1c 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. HbA1c 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 genome-wide analyses. Here I review current research aimed at discovering genetic determinants of HbA1c 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

TEAD and YAP regulate the enhancer network of human embryonic pancreatic progenitors.

The genomic regulatory programmes that underlie human organogenesis are poorly understood. Pancreas development, in particular, has pivotal implications for pancreatic regeneration, cancer and diabetes. We have now characterized the regulatory landscape of embryonic multipotent progenitor cells that give rise to all pancreatic epithelial lineages. Using human embryonic pancreas and embryonic-stem-cell-derived progenitors we identify stage-specific transcripts and associated enhancers, many of which are co-occupied by transcription factors that are essential for pancreas development. We further show that TEAD1, a Hippo signalling effector, is an integral component of the transcription factor combinatorial code of pancreatic progenitor enhancers. TEAD and its coactivator YAP activate key pancreatic signalling mediators and transcription factors, and regulate the expansion of pancreatic progenitors. This work therefore uncovers a central role for TEAD and YAP as signal-responsive regulators of multipotent pancreatic progenitors, and provides a resource for the study of embryonic development of the human pancreas

TCF7L2 variant genotypes and type 2 diabetes risk in Brazil: significant association, but not a significant tool for risk stratification in the general population

<p>Abstract</p> <p>Background</p> <p>Genetic polymorphisms of the <it>TCF7L2 </it>gene are strongly associated with large increments in type 2 diabetes risk in different populations worldwide. In this study, we aimed to confirm the effect of the <it>TCF7L2 </it>polymorphism <it>rs7903146 </it>on diabetes risk in a Brazilian population and to assess the use of this genetic marker in improving diabetes risk prediction in the general population.</p> <p>Methods</p> <p>We genotyped the single nucleotide polymorphisms (SNP) rs7903146 of the <it>TCF7L2 </it>gene in 560 patients with known coronary disease enrolled in the MASS II (Medicine, Angioplasty, or Surgery Study) Trial and in 1,449 residents of Vitoria, in Southeast Brazil. The associations of this gene variant to diabetes risk and metabolic characteristics in these two different populations were analyzed. To access the potential benefit of using this marker for diabetes risk prediction in the general population we analyzed the impact of this genetic variant on a validated diabetes risk prediction tool based on clinical characteristics developed for the Brazilian general population.</p> <p>Results</p> <p>SNP rs7903146 of the <it>TCF7L2 </it>gene was significantly associated with type 2 diabetes in the MASS-II population (OR = 1.57 per T allele, p = 0.0032), confirming, in the Brazilian population, previous reports of the literature. Addition of this polymorphism to an established clinical risk prediction score did not increased model accuracy (both area under ROC curve equal to 0.776).</p> <p>Conclusion</p> <p><it>TCF7L2 </it>rs7903146 T allele is associated with a 1.57 increased risk for type 2 diabetes in a Brazilian cohort of patients with known coronary heart disease. However, the inclusion of this polymorphism in a risk prediction tool developed for the general population resulted in no improvement of performance. This is the first study, to our knowledge, that has confirmed this recent association in a South American population and adds to the great consistency of this finding in studies around the world. Finally, confirming the biological association of a genetic marker does not guarantee improvement on already established screening tools based solely on demographic variables.</p

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

A Stratified Transcriptomics Analysis of Polygenic Fat and Lean Mouse Adipose Tissues Identifies Novel Candidate Obesity Genes

Obesity and metabolic syndrome results from a complex interaction between genetic and environmetal factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator lean (L) strain. To enrich for adipose tissue obesity genes a ˝snap-shot˝ pooled-sample transcriptome comparison of key fat depots and non adipose tissue (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue.A number of novel obesity candidate genes were also identified (Thbs1, Ppp1rd, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred rolesin fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a dictinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathaways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity. A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity

Association between TCF7L2 gene polymorphisms and susceptibility to Type 2 Diabetes Mellitus: a large Human Genome Epidemiology (HuGE) review and meta-analysis

<p>Abstract</p> <p>Background</p> <p>Transcription factor 7-like 2 (<it>TCF7L2</it>) has been shown to be associated with type 2 diabetes mellitus (T2MD) in multiple ethnic groups in the past two years, but, contradictory results were reported for Chinese and Pima Indian populations. The authors then performed a large meta-analysis of 36 studies examining the association of type 2 diabetes mellitus (T2DM) with polymorphisms in the <it>TCF7L2 </it>gene in various ethnicities, containing rs7903146 C-to-T (IVS3C>T), rs7901695 T-to-C (IVS3T>C), a rs12255372 G-to-T (IVS4G>T), and rs11196205 G-to-C (IVS4G>C) polymorphisms and to evaluate the size of gene effect and the possible genetic mode of action.</p> <p>Methods</p> <p>Literature-based searching was conducted to collect data and three methods, that is, fixed-effects, random-effects and Bayesian multivariate mete-analysis, were performed to pool the odds ratio (<it>OR</it>). Publication bias and study-between heterogeneity were also examined.</p> <p>Results</p> <p>The studies included 35,843 cases of T2DM and 39,123 controls, using mainly primary data. For T2DM and IVS3C>T polymorphism, the Bayesian <it>OR </it>for TT homozygotes and TC heterozygotes versus CC homozygote was 1.968 (95% credible interval (<it>CrI</it>): 1.790, 2.157), 1.406 (95% <it>CrI</it>: 1.341, 1.476), respectively, and the population attributable risk (PAR) for the TT/TC genotypes of this variant is 16.9% for overall. For T2DM and IVS4G>T polymorphism, TT homozygotes and TG heterozygotes versus GG homozygote was 1.885 (95%<it>CrI</it>: 1.698, 2.088), 1.360 (95% <it>CrI</it>: 1.291, 1.433), respectively. Four <it>OR</it>s among these two polymorphisms all yielded significant between-study heterogeneity (P < 0.05) and the main source of heterogeneity was ethnic differences. Data also showed significant associations between T2DM and the other two polymorphisms, but with low heterogeneity (<it>P </it>> 0.10). Pooled <it>OR</it>s fit a codominant, multiplicative genetic model for all the four polymorphisms of <it>TCF7L2 </it>gene, and this model was also confirmed in different ethnic populations when stratification of IVS3C>T and IVS4G>T polymorphisms except for Africans, where a dominant, additive genetic mode is suggested for IVS3C>T polymorphism.</p> <p>Conclusion</p> <p>This meta-analysis demonstrates that four variants of <it>TCF7L2 </it>gene are all associated with T2DM, and indicates a multiplicative genetic model for all the four polymorphisms, as well as suggests the <it>TCF7L2 </it>gene involved in near 1/5 of all T2MD. Potential gene-gene and gene-environmental interactions by which common variants in the <it>TCF7L2 </it>gene influence the risk of T2MD need further exploration.</p

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives