Presymptomatic risk assessment for chronic non-communicable diseases

The prevalence of common chronic non-communicable diseases (CNCDs) far overshadows the prevalence of both monogenic and infectious diseases combined. All CNCDs, also called complex genetic diseases, have a heritable genetic component that can be used for pre-symptomatic risk assessment. Common single nucleotide polymorphisms (SNPs) that tag risk haplotypes across the genome currently account for a non-trivial portion of the germ-line genetic risk and we will likely continue to identify the remaining missing heritability in the form of rare variants, copy number variants and epigenetic modifications. Here, we describe a novel measure for calculating the lifetime risk of a disease, called the genetic composite index (GCI), and demonstrate its predictive value as a clinical classifier. The GCI only considers summary statistics of the effects of genetic variation and hence does not require the results of large-scale studies simultaneously assessing multiple risk factors. Combining GCI scores with environmental risk information provides an additional tool for clinical decision-making. The GCI can be populated with heritable risk information of any type, and thus represents a framework for CNCD pre-symptomatic risk assessment that can be populated as additional risk information is identified through next-generation technologies.Comment: Plos ONE paper. Previous version was withdrawn to be updated by the journal's pdf versio

iCanPlot: Visual Exploration of High-Throughput Omics Data Using Interactive Canvas Plotting

Increasing use of high throughput genomic scale assays requires effective visualization and analysis techniques to facilitate data interpretation. Moreover, existing tools often require programming skills, which discourages bench scientists from examining their own data. We have created iCanPlot, a compelling platform for visual data exploration based on the latest technologies. Using the recently adopted HTML5 Canvas element, we have developed a highly interactive tool to visualize tabular data and identify interesting patterns in an intuitive fashion without the need of any specialized computing skills. A module for geneset overlap analysis has been implemented on the Google App Engine platform: when the user selects a region of interest in the plot, the genes in the region are analyzed on the fly. The visualization and analysis are amalgamated for a seamless experience. Further, users can easily upload their data for analysis—which also makes it simple to share the analysis with collaborators. We illustrate the power of iCanPlot by showing an example of how it can be used to interpret histone modifications in the context of gene expression

Linkage disequilibrium in young genetically isolated Dutch population

The design and feasibility of genetic studies of complex diseases are critically dependent on the extent and distribution of linkage disequilibrium (LD) across the genome and between different populations. We have examined genomewide and region-specific LD in a young genetically isolated population identified in the Netherlands by genotyping approximately 800 Short Tandem Repeat markers distributed genomewide across 58 individuals. Several regions were an

Non-Overlapping Functions for Pyk2 and FAK in Osteoblasts during Fluid Shear Stress-Induced Mechanotransduction

Mechanotransduction, the process by which cells convert external mechanical stimuli such as fluid shear stress (FSS) into biochemical changes, plays a critical role in maintenance of the skeleton. We have proposed that mechanical stimulation by FSS across the surfaces of bone cells results in formation of unique signaling complexes called mechanosomes that are launched from sites of adhesion with the extracellular matrix and with other bone cells [1]. Deformation of adhesion complexes at the cell membrane ultimately results in alteration of target gene expression. Recently, we reported that focal adhesion kinase (FAK) functions as a part of a mechanosome complex that is required for FSS-induced mechanotransduction in bone cells. This study extends this work to examine the role of a second member of the FAK family of non-receptor protein tyrosine kinases, proline-rich tyrosine kinase 2 (Pyk2), and determine its role during osteoblast mechanotransduction. We use osteoblasts harvested from mice as our model system in this study and compared the contributions of Pyk2 and FAK during FSS induced mechanotransduction in osteoblasts. We exposed Pyk2+/+ and Pyk2−/− primary calvarial osteoblasts to short period of oscillatory fluid flow and analyzed downstream activation of ERK1/2, and expression of c-fos, cyclooxygenase-2 and osteopontin. Unlike FAK, Pyk2 was not required for fluid flow-induced mechanotransduction as there was no significant difference in the response of Pyk2+/+ and Pyk2−/− osteoblasts to short periods of fluid flow (FF). In contrast, and as predicted, FAK−/− osteoblasts were unable to respond to FF. These data indicate that FAK and Pyk2 have distinct, non-redundant functions in launching mechanical signals during osteoblast mechanotransduction. Additionally, we compared two methods of generating FF in both cell types, oscillatory pump method and another orbital platform method. We determined that both methods of generating FF induced similar responses in both primary calvarial osteoblasts and immortalized calvarial osteoblasts

PLCL1 rs7595412 variation is not associated with hip bone size variation in postmenopausal Danish women

<p>Abstract</p> <p>Background</p> <p>Bone size (BS) variation is under strong genetic control and plays an important role in determining bone strength and fracture risk. Recently, a genome-wide association study identified polymorphisms associated with hip BS variation in the <it>PLCL1 </it>(phospholipase c-like 1) locus. Carriers of the major A allele of the most significant polymorphism, rs7595412, have around 17% larger hip BS than non-carriers. We therefore hypothesized that this polymorphism may also influence postmenopausal complications.</p> <p>Methods</p> <p>The effects of rs7595412 on hip BS, bone mineral density (BMD), vertebral fractures, serum Crosslaps and osteocalcin levels were analyzed in 1,191 postmenopausal Danish women.</p> <p>Results</p> <p>This polymorphism had no influence on hip and spine BS as well as on femur and spine BMD. Women carrying at least one copy of the A allele had lower levels of serum osteocalcin as compared with those homozygous for the G allele (p = 0.03) whereas no effect on serum Crosslaps was detected. Furthermore, women homozygous for the A allele were more affected by vertebral fractures than those carrying at least one copy of the G allele (p = 0.04).</p> <p>Conclusions</p> <p>In postmenopausal women, our results suggest that the <it>PLCL1 </it>rs7595412 polymorphism has no obvious effect on hip BS or BMD but may be nominally associated with increased proportion of vertebral fracture and increased levels of osteocalcin.</p

Engineering Genetically Encoded Nanosensors for Real-Time In Vivo Measurements of Citrate Concentrations

Citrate is an intermediate in catabolic as well as biosynthetic pathways and is an important regulatory molecule in the control of glycolysis and lipid metabolism. Mass spectrometric and NMR based metabolomics allow measuring citrate concentrations, but only with limited spatial and temporal resolution. Methods are so far lacking to monitor citrate levels in real-time in-vivo. Here, we present a series of genetically encoded citrate sensors based on Förster resonance energy transfer (FRET). We screened databases for citrate-binding proteins and tested three candidates in vitro. The citrate binding domain of the Klebsiella pneumoniae histidine sensor kinase CitA, inserted between the FRET pair Venus/CFP, yielded a sensor highly specific for citrate. We optimized the peptide linkers to achieve maximal FRET change upon citrate binding. By modifying residues in the citrate binding pocket, we were able to construct seven sensors with different affinities spanning a concentration range of three orders of magnitude without losing specificity. In a first in vivo application we show that E. coli maintains the capacity to take up glucose or acetate within seconds even after long-term starvation

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

Fine-scale detection of population-specific linkage disequilibrium using haplotype entropy in the human genome

<p>Abstract</p> <p>Background</p> <p>The creation of a coherent genomic map of recent selection is one of the greatest challenges towards a better understanding of human evolution and the identification of functional genetic variants. Several methods have been proposed to detect linkage disequilibrium (LD), which is indicative of natural selection, from genome-wide profiles of common genetic variations but are designed for large regions.</p> <p>Results</p> <p>To find population-specific LD within small regions, we have devised an entropy-based method that utilizes differences in haplotype frequency between populations. The method has the advantages of incorporating multilocus association, conciliation with low allele frequencies, and independence from allele polarity, which are ideal for short haplotype analysis. The comparison of HapMap SNPs data from African and Caucasian populations with a median resolution size of ~23 kb gave us novel candidates as well as known selection targets. Enrichment analysis for the yielded genes showed associations with diverse diseases such as cardiovascular, immunological, neurological, and skeletal and muscular diseases. A possible scenario for a selective force is discussed. In addition, we have developed a web interface (ENIGMA, available at <url>http://gibk21.bse.kyutech.ac.jp/ENIGMA/index.html</url>), which allows researchers to query their regions of interest for population-specific LD.</p> <p>Conclusion</p> <p>The haplotype entropy method is powerful for detecting population-specific LD embedded in short regions and should contribute to further studies aiming to decipher the evolutionary histories of modern humans.</p

An in vivo cis-Regulatory Screen at the Type 2 Diabetes Associated TCF7L2 Locus Identifies Multiple Tissue-Specific Enhancers

Genome-wide association studies (GWAS) have repeatedly shown an association between non-coding variants in the TCF7L2 locus and risk for type 2 diabetes (T2D), implicating a role for cis-regulatory variation within this locus in disease etiology. Supporting this hypothesis, we previously localized complex regulatory activity to the TCF7L2 T2D-associated interval using an in vivo bacterial artificial chromosome (BAC) enhancer-trapping reporter strategy. To follow-up on this broad initial survey of the TCF7L2 regulatory landscape, we performed a fine-mapping enhancer scan using in vivo mouse transgenic reporter assays. We functionally interrogated approximately 50% of the sequences within the T2D-associated interval, utilizing sequence conservation within this 92-kb interval to determine the regulatory potential of all evolutionary conserved sequences that exhibited conservation to the non-eutherian mammal opossum. Included in this study was a detailed functional interrogation of sequences spanning both protective and risk alleles of single nucleotide polymorphism (SNP) rs7903146, which has exhibited allele-specific enhancer function in pancreatic beta cells. Using these assays, we identified nine segments regulating various aspects of the TCF7L2 expression profile and that constitute nearly 70% of the sequences tested. These results highlight the regulatory complexity of this interval and support the notion that a TCF7L2 cis-regulatory disruption leads to T2D predisposition