Trans-eQTLs Reveal That Independent Genetic Variants Associated with a Complex Phenotype Converge on Intermediate Genes, with a Major Role for the HLA

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Transmission and Control of African Horse Sickness in The Netherlands: A Model Analysis

African horse sickness (AHS) is an equine viral disease that is spread by Culicoides spp. Since the closely related disease bluetongue established itself in The Netherlands in 2006, AHS is considered a potential threat for the Dutch horse population. A vector-host model that incorporates the current knowledge of the infection biology is used to explore the effect of different parameters on whether and how the disease will spread, and to assess the effect of control measures. The time of introduction is an important determinant whether and how the disease will spread, depending on temperature and vector season. Given an introduction in the most favourable and constant circumstances, our results identify the vector-to-host ratio as the most important factor, because of its high variability over the country. Furthermore, a higher temperature accelerates the epidemic, while a higher horse density increases the extent of the epidemic. Due to the short infectious period in horses, the obvious clinical signs and the presence of non-susceptible hosts, AHS is expected to invade and spread less easily than bluetongue. Moreover, detection is presumed to be earlier, which allows control measures to be targeted towards elimination of infection sources. We argue that recommended control measures are euthanasia of infected horses with severe clinical signs and vector control in infected herds, protecting horses from midge bites in neighbouring herds, and (prioritized) vaccination of herds farther away, provided that transport regulations are strictly applied. The largest lack of knowledge is the competence and host preference of the different Culicoides species present in temperate regions

Mapping genetic determinants of host susceptibility to Pseudomonas aeruginosa lung infection in mice.

Background: P. aeruginosa is one of the top three causes of opportunistic human bacterial infections. The remarkable variability in the clinical outcomes of this infection is thought to be associated with genetic predisposition. However, the genes underlying host susceptibility to P. aeruginosa infection are still largely unknown. Results: As a step towards mapping these genes, we applied a genome wide linkage analysis approach to a mouse model. A large F2 intercross population, obtained by mating P. aeruginosa-resistant C3H/HeOuJ, and susceptible A/J mice, was used for quantitative trait locus (QTL) mapping. The F2 progenies were challenged with a P. aeruginosa clinical strain and monitored for the survival time up to 7 days post-infection, as a disease phenotype associated trait. Selected phenotypic extremes of the F2 distribution were genotyped with high-density single nucleotide polymorphic (SNP) markers, and subsequently QTL analysis was performed. A significant locus was mapped on chromosome 6 and was named P. aeruginosa infection resistance locus 1 (Pairl1). The most promising candidate genes, including Dok1, Tacr1, Cd207, Clec4f, Gp9, Gata2, Foxp1, are related to pathogen sensing, neutrophils and macrophages recruitment and inflammatory processes. Conclusions: We propose a set of genes involved in the pathogenesis of P. aeruginosa infection that may be explored to complement human studie

Pathway analysis comparison using Crohn's disease genome wide association studies

<p>Abstract</p> <p>Background</p> <p>The use of biological annotation such as genes and pathways in the analysis of gene expression data has aided the identification of genes for follow-up studies and suggested functional information to uncharacterized genes. Several studies have applied similar methods to genome wide association studies and identified a number of disease related pathways. However, many questions remain on how to best approach this problem, such as whether there is a need to obtain a score to summarize association evidence at the gene level, and whether a pathway, dominated by just a few highly significant genes, is of interest.</p> <p>Methods</p> <p>We evaluated the performance of two pathway-based methods (Random Set, and Binomial approximation to the hypergeometric test) based on their applications to three data sets of Crohn's disease. We consider both the disease status as a phenotype as well as the residuals after conditioning on IL23R, a known Crohn's related gene, as a phenotype.</p> <p>Results</p> <p>Our results show that Random Set method has the most power to identify disease related pathways. We confirm previously reported disease related pathways and provide evidence for IL-2 Receptor Beta Chain in T cell Activation and IL-9 signaling as Crohn's disease associated pathways.</p> <p>Conclusions</p> <p>Our results highlight the need to apply powerful gene score methods prior to pathway enrichment tests, and that controlling for genes that attain genome wide significance enable further biological insight.</p

Variants in Neuropeptide Y Receptor 1 and 5 Are Associated with Nutrient-Specific Food Intake and Are Under Recent Selection in Europeans

There is a large variation in caloric intake and macronutrient preference between individuals and between ethnic groups, and these food intake patterns show a strong heritability. The transition to new food sources during the agriculture revolution around 11,000 years ago probably created selective pressure and shaped the genome of modern humans. One major player in energy homeostasis is the appetite-stimulating hormone neuropeptide Y, in which the stimulatory capacity may be mediated by the neuropeptide Y receptors 1, 2 and 5 (NPY1R, NPY2R and NPY5R). We assess association between variants in the NPY1R, NPY2R and NPY5R genes and nutrient intake in a cross-sectional, single-center study of 400 men aged 40 to 80 years, and we examine whether genomic regions containing these genes show signatures of recent selection in 270 HapMap individuals (90 Africans, 90 Asians, and 90 Caucasians) and in 846 Dutch bloodbank controls. Our results show that derived alleles in NPY1R and NPY5R are associated with lower carbohydrate intake, mainly because of a lower consumption of mono- and disaccharides. We also show that carriers of these derived alleles, on average, consume meals with a lower glycemic index and glycemic load and have higher alcohol consumption. One of these variants shows the hallmark of recent selection in Europe. Our data suggest that lower carbohydrate intake, consuming meals with a low glycemic index and glycemic load, and/or higher alcohol consumption, gave a survival advantage in Europeans since the agricultural revolution. This advantage could lie in overall health benefits, because lower carbohydrate intake, consuming meals with a low GI and GL, and/or higher alcohol consumption, are known to be associated with a lower risk of chronic diseases

Effects of Male Hypogonadism on Regional Adipose Tissue Fatty Acid Storage and Lipogenic Proteins

Testosterone has long been known to affect body fat distribution, although the underlying mechanisms remain elusive. We investigated the effects of chronic hypogonadism in men on adipose tissue fatty acid (FA) storage and FA storage factors. Twelve men with chronic hypogonadism and 13 control men matched for age and body composition: 1) underwent measures of body composition with dual energy x-ray absorptiometry and an abdominal CT scan; 2) consumed an experimental meal containing [3H]triolein to determine the fate of meal FA (biopsy-measured adipose storage vs. oxidation); 3) received infusions of [U-13C]palmitate and [1-14C]palmitate to measure rates of direct free (F)FA storage (adipose biopsies). Adipose tissue lipoprotein lipase, acyl-CoA synthetase (ACS), and diacylglycerol acetyl-transferase (DGAT) activities, as well as, CD36 content were measured to understand the mechanism by which alterations in fat storage occur in response to testosterone deficiency. Results of the study showed that hypogonadal men stored a greater proportion of both dietary FA and FFA in lower body subcutaneous fat than did eugonadal men (both p<0.05). Femoral adipose tissue ACS activity was significantly greater in hypogonadal than eugonadal men, whereas CD36 and DGAT were not different between the two groups. The relationships between these proteins and FA storage varied somewhat between the two groups. We conclude that chronic effects of testosterone deficiency has effects on leg adipose tissue ACS activity which may relate to greater lower body FA storage. These results provide further insight into the role of androgens in body fat distribution and adipose tissue metabolism in humans

Lack of association of genetic variation in chromosome region 15q14-22.1 with type 2 diabetes in a Japanese population

<p>Abstract</p> <p>Background</p> <p>Chromosome 15q14-22.1 has been linked to type 2 diabetes (T2D) and its related traits in Japanese and other populations. The presence of T2D disease susceptibility variant(s) was assessed in the 21.8 Mb region between <it>D15S118 </it>and <it>D15S117 </it>in a Japanese population using a region-wide case-control association test.</p> <p>Methods</p> <p>A two-stage association test was performed using Japanese subjects: The discovery panel (Stage 1) used 372 cases and 360 controls, while an independent replication panel (Stage 2) used 532 cases and 530 controls. A total of 1,317 evenly-spaced, common SNP markers with minor allele frequencies > 0.10 were typed for each stage. Captured genetic variation was examined in HapMap JPT SNPs, and a haplotype-based association test was performed.</p> <p>Results</p> <p>SNP2140 (rs2412747) (<it>C/T</it>) in intron 33 of the ubiquitin protein ligase E3 component n-recognin 1 (<it>UBR1</it>) gene was selected as a landmark SNP based on repeated significant associations in Stage 1 and Stage 2. However, the marginal <it>p </it>value (<it>p </it>= 0.0043 in the allelic test, OR = 1.26, 95% CI = 1.07–1.48 for combined samples) was weak in a single locus or haplotype-based association test. We failed to find any significant SNPs after correcting for multiple testing.</p> <p>Conclusion</p> <p>The two-stage association test did not reveal a strong association between T2D and any common variants on chromosome 15q14-22.1 in 1,794 Japanese subjects. A further association test with a larger sample size and denser SNP markers is required to confirm these observations.</p

Comparisons of seven algorithms for pathway analysis using the WTCCC Crohn's Disease dataset

<p>Abstract</p> <p>Background</p> <p>Though rooted in genomic expression studies, pathway analysis for genome-wide association studies (GWAS) has gained increasing popularity, since it has the potential to discover hidden disease pathogenic mechanisms by combining statistical methods with biological knowledge. Generally, algorithms or programs proposed recently can be categorized by different types of input data, null hypothesis or counts of analysis stages. Due to complexity caused by SNP, gene and pathway relationships, re-sampling strategies like permutation are always utilized to derive an empirical distribution for test statistics for evaluating the significance of candidate pathways. However, evaluation of these algorithms on real GWAS datasets and real biological pathway databases needs to be addressed before we apply them widely with confidence.</p> <p>Findings</p> <p>Two algorithms which use summary statistics from GWAS as input were implemented in KGG, a novel and user-friendly software tool for GWAS pathway analysis. Comparisons of these two algorithms as well as the other five selected algorithms were conducted by analyzing the WTCCC Crohn's Disease dataset utilizing the MsigDB canonical pathways. As a result of using permutation to obtain empirical p-value, most of these methods could control Type I error rate well, although some are conservative. However, the methods varied greatly in terms of power and running time, with the PLINK truncated set-based test being the most powerful and KGG being the fastest.</p> <p>Conclusions</p> <p>Raw data-based algorithms, such as those implemented in PLINK, are preferable for GWAS pathway analysis as long as computational capacity is available. It may be worthwhile to apply two or more pathway analysis algorithms on the same GWAS dataset, since the methods differ greatly in their outputs and might provide complementary findings for the studied complex disease.</p