171 research outputs found

    Evaluation of hydrophobic chitosan-based particulate formulations of porcine reproductive and respiratory syndrome virus vaccine candidate T cell antigens

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    PRRS control is hampered by the inadequacies of existing vaccines to combat the extreme diversity of circulating viruses. Since immune clearance of PRRSV infection may not be dependent on the development of neutralising antibodies and the identification of broadly-neutralising antibody epitopes have proven elusive, we hypothesised that conserved T cell antigens represent potential candidates for development of a novel PRRS vaccine. Previously we had identified the M and NSP5 proteins as well-conserved targets of polyfunctional CD8 and CD4 T cells. To assess their vaccine potential, peptides representing M and NSP5 were encapsulated in hydrophobically-modified chitosan particles adjuvanted by incorporation of a synthetic multi-TLR2/TLR7 agonist and coated with a model B cell PRRSV antigen. For comparison, empty particles and adjuvanted particles encapsulating inactivated PRRSV-1 were prepared. Vaccination with the particulate formulations induced antigen-specific antibody responses, which were most pronounced following booster immunisation. M and NSP5-specific CD4, but not CD8, T cell IFN-Îł reactivity was measurable following the booster immunisation in a proportion of animals vaccinated with peptide-loaded particles. Upon challenge, CD4 and CD8 T cell reactivity was detected in all groups, with the greatest responses being detected in the peptide vaccinated group but with limited evidence of an enhanced control of viraemia. Analysis of the lungs during the resolution of infection showed significant M/NSP5 specific IFN-Îł responses from CD8 rather than CD4 T cells. Vaccine primed CD8 T cell responses may therefore be required for protection and future work should focus on enhancing the cross-presentation of M/NSP5 to CD8 T cells

    Gene transcripts associated with muscle strength: a CHARGE meta-analysis of 7,781 persons

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Background: Lower muscle strength in midlife predicts disability and mortality in later life. Bloodborne factors, including growth differentiation factor 11 (GDF11), have been linked to muscle regeneration in animal models. We aimed to identify gene transcripts associated with muscle strength in adults. Methods: Meta-analysis of whole blood gene expression (overall 17,534 unique genes measured by microarray) and hand-grip strength in four independent cohorts (n=7,781, ages: 20-104 years, weighted mean=56), adjusted for age, sex, height, weight, and leukocyte subtypes. Separate analyses were performed in subsets (older/younger than 60, male/female). Results: Expression levels of 221 genes were associated with strength after adjustment for cofactors and for multiple statistical testing, including ALAS2 (rate limiting enzyme in heme synthesis), PRF1 (perforin, a cytotoxic protein associated with inflammation), IGF1R and IGF2BP2 (both insulin like growth factor related). We identified statistical enrichment for hemoglobin biosynthesis, innate immune activation and the stress response. Ten genes were only associated in younger individuals, four in males only and one in females only. For example PIK3R2 (a negative regulator of PI3K/AKT growth pathway) was negatively associated with muscle strength in younger (=60 years). We also show that 115 genes (52%) have not previously been linked to muscle in NCBI PubMed abstracts Conclusions: This first large-scale transcriptome study of muscle strength in human adults confirmed associations with known pathways and provides new evidence for over half of the genes identified. There may be age and sex specific gene expression signatures in blood for muscle strength.Wellcome TrustFHS gene expression profiling was funded through the Division of Intramural Research (Principal Investigator, Daniel Levy), National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD. Dr. Murabito is supported by NIH grant R01AG029451. Dr. Kiel is supported by NIH R01 AR41398. The Framingham Heart Study is supported by National Heart, Lung, and Blood Institute contract N01-HC-25195.The InCHIANTI study was supported in part by the Intramural Research Program, National Institute on Aging, NIH, Baltimore MD USA. D.M. and L.W.H. were generously supported by a Wellcome Trust Institutional Strategic Support Award (WT097835MF). W.E.H. was funded by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) for the South West Peninsula. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health in EnglandThe infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10-000-1002) and is supported by participating universities and mental health care organizations (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen, Lentis, GGZ Friesland, GGZ Drenthe, Scientific Institute for Quality of Healthcare (IQ healthcare), Netherlands Institute for Health Services Research (NIVEL) and Netherlands Institute of Mental Health and Addiction (Trimbos Institute).The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012), the Research Institute for Diseases in the Elderly (014-93- 28 015; RIDE2), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. The generation and management of RNA-expression array data for the Rotterdam Study was executed and funded by the Human Genotyping Facility of the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, the Netherlands. We thank Marjolein Peters, MSc, Ms. Mila Jhamai, Ms. Jeannette M. Vergeer-Drop, Ms. Bernadette van Ast-Copier, Mr. Marijn Verkerk and Jeroen van Rooij, BSc for their help in creating the RNA array expression databaseSHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network ‘Greifswald Approach to Individualized Medicine (GANI_MED)’ funded by the Federal Ministry of Education and Research (grant 03IS2061A). The University of Greifswald is a member of the 'Center of Knowledge Interchange' program of the Siemens AG and the CachĂ© Campus program of the InterSystems GmbH

    A whole-blood transcriptome meta-analysis identifies gene expression signatures of cigarette smoking

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    Cigarette smoking is a leading modifiable cause of death worldwide. We hypothesized that cigarette smoking induces extensive transcriptomic changes that lead to target-organ damage and smoking-related diseases. We performed a metaanalysis of transcriptome-wide gene expression using whole blood-derived RNA from 10,233 participants of European ancestry in six cohorts (including 1421 current and 3955 former smokers) to identify associations between smoking and altered gene expression levels. At a false discovery rate (FDR) < 0.1, we identified 1270 differentially expressed genes in current vs. never smokers, and 39 genes in former vs. never smokers. Expression levels of 12 genes remained elevated up to 30 years after smoking cessation, suggesting that the molecular consequence of smoking may persist for decades. Gene ontology analysis revealed enrichment of smoking-related genes for activation of platelets and lymphocytes, immune response, and apoptosis. Many of the top smoking-related differentially expressed genes, including LRRN3 and GPR15, have DNA methylation loci in promoter regions that were recently reported to be hypomethylated among smokers. By linking differential gene expression with smoking-related disease phenotypes, we demonstrated that stroke and pulmonary function show enrichment for smoking-related gene expression signatures. Mediation analysis revealed the expression of several genes (e.g. ALAS2) to be putative mediators of the associations between smoking and inflammatory biomarkers (IL6 and C-re

    A genome-wide association study of aging

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    AbstractHuman longevity and healthy aging show moderate heritability (20%–50%). We conducted a meta-analysis of genome-wide association studies from 9 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium for 2 outcomes: (1) all-cause mortality, and (2) survival free of major disease or death. No single nucleotide polymorphism (SNP) was a genome-wide significant predictor of either outcome (p < 5 × 10−8). We found 14 independent SNPs that predicted risk of death, and 8 SNPs that predicted event-free survival (p < 10−5). These SNPs are in or near genes that are highly expressed in the brain (HECW2, HIP1, BIN2, GRIA1), genes involved in neural development and function (KCNQ4, LMO4, GRIA1, NETO1) and autophagy (ATG4C), and genes that are associated with risk of various diseases including cancer and Alzheimer's disease. In addition to considerable overlap between the traits, pathway and network analysis corroborated these findings. These findings indicate that variation in genes involved in neurological processes may be an important factor in regulating aging free of major disease and achieving longevity

    The Molecular Genetic Architecture of Self-Employment

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    Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable-entrepreneurship-that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg2/σP2= 25%, h2= 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10-5were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≄0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases

    1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function.

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    HapMap imputed genome-wide association studies (GWAS) have revealed &gt;50 loci at which common variants with minor allele frequency &gt;5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value &lt; 5 × 10(-8) previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR &lt; 0.05) genes and 127 significantly (FDR &lt; 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples

    Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption.

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    Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to 91 462 coffee consumers of European ancestry with top single-nucleotide polymorphisms (SNPs) followed-up in ~30 062 and 7964 coffee consumers of European and African-American ancestry, respectively. Studies from both stages were combined in a trans-ethnic meta-analysis. Confirmed loci were examined for putative functional and biological relevance. Eight loci, including six novel loci, met GW significance (log10Bayes factor (BF)&gt;5.64) with per-allele effect sizes of 0.03-0.14 cups per day. Six are located in or near genes potentially involved in pharmacokinetics (ABCG2, AHR, POR and CYP1A2) and pharmacodynamics (BDNF and SLC6A4) of caffeine. Two map to GCKR and MLXIPL genes related to metabolic traits but lacking known roles in coffee consumption. Enhancer and promoter histone marks populate the regions of many confirmed loci and several potential regulatory SNPs are highly correlated with the lead SNP of each. SNP alleles near GCKR, MLXIPL, BDNF and CYP1A2 that were associated with higher coffee consumption have previously been associated with smoking initiation, higher adiposity and fasting insulin and glucose but lower blood pressure and favorable lipid, inflammatory and liver enzyme profiles (P&lt;5 × 10-8).Our genetic findings among European and African-American adults reinforce the role of caffeine in mediating habitual coffee consumption and may point to molecular mechanisms underlying inter-individual variability in pharmacological and health effects of coffee

    Genome-wide meta-analysis of common variant differences between men and women

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    The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 × 10−8) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ∌115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased trait

    Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function

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    In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10−9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10−4-2.2 × 10−7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in genera

    1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function

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    HapMap imputed genome-wide association studies (GWAS) have revealed &gt;50 loci at which common variants with minor allele frequency &gt;5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value &lt; 5 × 10(-8) previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR &lt; 0.05) genes and 127 significantly (FDR &lt; 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples
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