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To better understand the systemic response to naturally acquired acute respiratory viral infections, we prospectively enrolled 1610 healthy adults in 2009 and 2010. Of these, 142 subjects were followed for detailed evaluation of acute viral respiratory illness. We examined peripheral blood gene expression at 7 timepoints: enrollment, 5 illness visits and the end of each year of the study. 133 completed all study visits and yielded technically adequate peripheral blood microarray gene expression data. Seventy-three (55%) had an influenza virus infection, 64 influenza A and 9 influenza B. The remaining subjects had a rhinovirus infection (N = 32), other viral infections (N = 4), or no viral agent identified (N = 24). The results, which were replicated between two seasons, showed a dramatic upregulation of interferon pathway and innate immunity genes. This persisted for 2-4 days. The data show a recovery phase at days 4 and 6 with differentially expressed transcripts implicated in cell proliferation and repair. By day 21 the gene expression pattern was indistinguishable from baseline (enrollment). Influenza virus infection induced a higher magnitude and longer duration of the shared expression signature of illness compared to the other viral infections. Using lineage and activation state-specific transcripts to produce cell composition scores, patterns of B and T lymphocyte depressions accompanied by a major activation of NK cells were detected in the acute phase of illness. The data also demonstrate multiple dynamic gene modules that are reorganized and strengthened following infection. Finally, we examined pre- and post-infection anti-influenza antibody titers defining novel gene expression correlates.

Identification of the host genetic factors that contribute to variation in vaccine responsiveness may uncover important mechanisms affecting vaccine efficacy. We carried out an integrative, longitudinal study combining genetic, transcriptional, and immunologic data in humans given seasonal influenza vaccine. We identified 20 genes exhibiting a transcriptional response to vaccination, significant genotype effects on gene expression, and correlation between the transcriptional and antibody responses. The results show that variation at the level of genes involved in membrane trafficking and antigen processing significantly influences the human response to influenza vaccination. More broadly, we demonstrate that an integrative study design is an efficient alternative to existing methods for the identification of genes involved in complex traits. Vaccines increase resistance to disease by priming the immune system to respond to specific viruses or microorganisms. By presenting a weakened (or dead) form of a pathogen, or its toxins or surface proteins, to the immune system, vaccines trigger the production of antibodies against the virus or microorganism. If a vaccinated individual then encounters the pathogen, their immune system should be able to recognize and destroy it. Many vaccines also include a secondary agent, known as an adjuvant, to further stimulate the immune response. Influenza, an RNA virus commonly referred to as the ‘flu’, is an infectious disease that affects both birds and mammals. Seasonal epidemics occur each year affecting 2–7% of the population. According to the World Health Organization, influenza leads to nearly 5 million hospitalizations each year and causes up to half a million deaths. Vaccination is a primary strategy for the prevention of seasonal influenza, but responses to the vaccine vary markedly, partly because of variation in the genetic makeup or genotype of individuals. However, the details of how genes influence response to vaccination, and indeed susceptibility to influenza, remain unclear. To investigate the genetic basis of variation in the immune response of healthy adults to the seasonal influenza vaccine, Franco et al. combined information about the genotypes of individuals with measurements of their gene transcription and antibody response to vaccination. They identified 20 genes that contributed to differential immune responses to the vaccine. Almost half of these encode proteins that are not specifically associated with the immune system, but have more general roles in processes such as membrane trafficking and intracellular transport. Focusing on these genes may enable researchers to spot those individuals who are less likely to respond to a vaccine. It could also open up new avenues of research for vaccine development: rather than designing adjuvants that target known immune mechanisms, researchers should develop adjuvants that target the proteins encoded by these 20 genes.

Background. Annual vaccination is the primary means for preventing influenza. However, great interindividual variability exists in vaccine responses, the cellular events that take place in vivo after vaccination are poorly understood, and appropriate biomarkers for vaccine responsiveness have not been developed. Methods. We immunized a cohort of healthy male adults with a licensed trivalent influenza vaccine and performed a timed assessment of global gene expression before and after vaccination. We analyzed the relationship between gene expression patterns and the humoral immune response to vaccination. Results. Marked up regulation of expression of genes involved in interferon signaling, positive IL-6 regulation, and antigen processing and presentation, were detected within 24 hours of immunization. The late vaccine response showed a transcriptional pattern suggestive of increased protein biosynthesis and cellular proliferation. Integrative analyses revealed a 494-gene expression signature—including STATI, CD74, and E2F2— which strongly correlates with the magnitude of the antibody response. High vaccine responder status correlates with increased early expression of interferon signaling and antigen processing and presentation genes. Conclusions. The results highlight the role of a systems biology approach in understanding the molecular events that take place in vivo after influenza vaccination and in the development of better predictors of vaccine responsiveness.

Waist-to-hip ratio (WHR), a relative comparison of waist and hip circumferences, is an easily accessible measurement of body fat distribution, in particular central abdominal fat. A high WHR indicates more intra-abdominal fat deposition and is an established risk factor for cardiovascular disease and type 2 diabetes. Recent genome-wide association studies have identified numerous common genetic loci influencing WHR, but the contributions of rare variants have not been previously reported. We investigated rare variant associations with WHR in 1510 European-American and 1186 African-American women from the National Heart, Lung, and Blood Institute-Exome Sequencing Project. Association analysis was performed on the gene level using several rare variant association methods. The strongest association was observed for rare variants in IKBKB (P=4.0 × 10(-8)) in European-Americans, where rare variants in this gene are predicted to decrease WHRs. The activation of the IKBKB gene is involved in inflammatory processes and insulin resistance, which may affect normal food intake and body weight and shape. Meanwhile, aggregation of rare variants in COBLL1, previously found to harbor common variants associated with WHR and fasting insulin, were nominally associated (P=2.23 × 10(-4)) with higher WHR in European-Americans. However, these significant results are not shared between African-Americans and European-Americans that may be due to differences in the allelic architecture of the two populations and the small sample sizes. Our study indicates that the combined effect of rare variants contribute to the inter-individual variation in fat distribution through the regulation of insulin response.

Doc number: 85 Abstract Background: Whole genome amplification (WGA) offers new possibilities for genome-wide association studies where limited DNA samples have been collected. This study provides a realistic and high-precision assessment of WGA DNA genotyping performance from 20-year old archived serum samples using the Affymetrix Genome-Wide Human SNP Array 6.0 (SNP6.0) platform. Results: Whole-genome amplified (WGA) DNA samples from 45 archived serum replicates and 5 fresh sera paired with non-amplified genomic DNA were genotyped in duplicate. All genotyped samples passed the imposed QC thresholds for quantity and quality. In general, WGA serum DNA samples produced low call rates (45.00 +/- 2.69%), although reproducibility for successfully called markers was favorable (concordance = 95.61 +/- 4.39%). Heterozygote dropouts explained the majority (>85% in technical replicates, 50% in paired genomic/serum samples) of discordant results. Genotyping performance on WGA serum DNA samples was improved by implementation of Corrected Robust Linear Model with Maximum Likelihood Classification (CRLMM) algorithm but at the loss of many samples which failed to pass its quality threshold. Poor genotype clustering was evident in the samples that failed the CRLMM confidence threshold. Conclusions: We conclude that while it is possible to extract genomic DNA and subsequently perform whole-genome amplification from archived serum samples, WGA serum DNA did not perform well and appeared unsuitable for high-resolution genotyping on these arrays.

To better understand the systemic response to naturally acquired acute respiratory viral infections, we prospectively enrolled 1610 healthy adults in 2009 and 2010. Of these, 142 subjects were followed for detailed evaluation of acute viral respiratory illness. We examined peripheral blood gene expression at 7 timepoints: enrollment, 5 illness visits and the end of each year of the study. 133 completed all study visits and yielded technically adequate peripheral blood microarray gene expression data. Seventy-three (55%) had an influenza virus infection, 64 influenza A and 9 influenza B. The remaining subjects had a rhinovirus infection (N = 32), other viral infections (N = 4), or no viral agent identified (N = 24). The results, which were replicated between two seasons, showed a dramatic upregulation of interferon pathway and innate immunity genes. This persisted for 2-4 days. The data show a recovery phase at days 4 and 6 with differentially expressed transcripts implicated in cell proliferation and repair. By day 21 the gene expression pattern was indistinguishable from baseline (enrollment). Influenza virus infection induced a higher magnitude and longer duration of the shared expression signature of illness compared to the other viral infections. Using lineage and activation state-specific transcripts to produce cell composition scores, patterns of B and T lymphocyte depressions accompanied by a major activation of NK cells were detected in the acute phase of illness. The data also demonstrate multiple dynamic gene modules that are reorganized and strengthened following infection. Finally, we examined pre- and post-infection anti-influenza antibody titers defining novel gene expression correlates.