Suchergebnisse

Insomnia is a worldwide problem with substantial deleterious health effects. Twin studies have shown a heritable basis for various sleep-related traits, including insomnia, but robust genetic risk variants have just recently begun to be identified. We conducted genome-wide association studies (GWAS) of soldiers in the Army Study To Assess Risk and Resilience in Servicemembers (STARRS). GWAS were carried out separately for each ancestral group (EUR, AFR, LAT) using logistic regression for each of the STARRS component studies (including 3,237 cases and 14,414 controls), and then meta-analysis was conducted across studies and ancestral groups. Heritability (SNP-based) for lifetime insomnia disorder was significant (h2g = 0.115, p = 1.78 × 10-4 in EUR). A meta-analysis including three ancestral groups and three study cohorts revealed a genome-wide significant locus on Chr 7 (q11.22) (top SNP rs186736700, OR = 0.607, p = 4.88 × 10-9) and a genome-wide significant gene-based association (p = 7.61 × 10-7) in EUR for RFX3 on Chr 9. Polygenic risk for sleeplessness/insomnia severity in UK Biobank was significantly positively associated with likelihood of insomnia disorder in STARRS. Genetic contributions to insomnia disorder in STARRS were significantly positively correlated with major depressive disorder (rg = 0.44, se = 0.22, p = 0.047) and type 2 diabetes (rg = 0.43, se = 0.20, p = 0.037), and negatively with morningness chronotype (rg = -0.34, se = 0.17, p = 0.039) and subjective well being (rg = -0.59, se = 0.23, p = 0.009) in external datasets. Insomnia associated loci may contribute to the genetic risk underlying a range of health conditions including psychiatric disorders and metabolic disease.

The results leading to this publication have received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 777394 for the project AIMS-2-TRIALS. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA and AUTISM SPEAKS, Autistica, SFARI. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Any views expressed are those of the author(s) and not necessarily those of the funders.

Recent advances in molecular genetics have provided social scientists with new tools with which to explore human behavior. By deploying genomic analysis, we can now explore long-term patterns of human migration and mating, explore the biological aspects of important sociological outcomes such as educational attainment, and, most importantly, model gene-by-environment interaction effects. The intuition motivating much socio-genomic research is that to have a more complete understanding of social life, scholars must take into consideration both nature and nurture as well as their interplay. Most promising is gene-by-environment research that deploys polygenic measures of genotype as a prism through which to refract and detect heterogenous treatment effects of plausibly exogenous environmental influences. This article reviews much recent work in this vein and argues for a broader integration of genomic data into social inquiry.

[Motivation] Although Genome Wide Association Studies (GWAS) genotype a very large number of single nucleotide polymorphisms (SNPs), the data are often analyzed one SNP at a time. The low predictive power of single SNPs, coupled with the high significance threshold needed to correct for multiple testing, greatly decreases the power of GWAS. ; [Results] We propose a procedure in which all the SNPs are analyzed in a multiple generalized linear model, and we show its use for extremely high-dimensional datasets. Our method yields P-values for assessing significance of single SNPs or groups of SNPs while controlling for all other SNPs and the family wise error rate (FWER). Thus, our method tests whether or not a SNP carries any additional information about the phenotype beyond that available by all the other SNPs. This rules out spurious correlations between phenotypes and SNPs that can arise from marginal methods because the 'spuriously correlated' SNP merely happens to be correlated with the 'truly causal' SNP. In addition, the method offers a data driven approach to identifying and refining groups of SNPs that jointly contain informative signals about the phenotype. We demonstrate the value of our method by applying it to the seven diseases analyzed by the Wellcome Trust Case Control Consortium (WTCCC). We show, in particular, that our method is also capable of finding significant SNPs that were not identified in the original WTCCC study, but were replicated in other independent studies. ; E.F. and L.B. gratefully acknowledge financial support from the European Research Council (grant 295642, The Foundations of Economic Preferences, FEP). D.S. gratefully acknowledges financial support from the German National Science Foundation (DFG, grant SCHU 2828/2-1, Inference statistical methods for behavioral genetics and neuroeconomics). A.N. gratefully acknowledges support from the Instituto de Salud Carlos III (grants RD12/0032/0011 and PT13/0001/0026) and the Spanish Government Grant (BFU2012-38236) and from FEDER. ; Peer reviewed

Motivation: Although Genome Wide Association Studies (GWAS) genotype a very large number of single nucleotide polymorphisms (SNPs), the data are often analyzed one SNP at a time. The low predictive power of single SNPs, coupled with the high significance threshold needed to correct for multiple testing, greatly decreases the power of GWAS. Results: We propose a procedure in which all the SNPs are analyzed in a multiple generalized linear model, and we show its use for extremely high-dimensional datasets. Our method yields P -values for assessing significance of single SNPs or groups of SNPs while controlling for all other SNPs and the family wise error rate (FWER). Thus, our method tests whether or not a SNP carries any additional information about the phenotype beyond that available by all the other SNPs. This rules out spurious correlations between phenotypes and SNPs that can arise from marginal methods because the 'spuriously correlated' SNP merely happens to be correlated with the 'truly causal' SNP. In addition, the method offers a data driven approach to identifying and refining groups of SNPs that jointly contain informative signals about the phenotype. We demonstrate the value of our method by applying it to the seven diseases analyzed by the Wellcome Trust Case Control Consortium (WTCCC). We show, in particular, that our method is also capable of finding significant SNPs that were not identified in the original WTCCC study, but were replicated in other independent studies. Availability and implementation: Reproducibility of our research is supported by the open-source Bioconductor package hierGWAS. Contact:peter.buehlmann@stat.math.ethz.ch Supplementary information:Supplementary data are available at Bioinformatics online. ; E.F. and L.B. gratefully acknowledge financial support from the European Research Council (grant 295642, The Foundations of Economic Preferences, FEP). D.S. gratefully acknowledges financial support from the German National Science Foundation (DFG, grant SCHU 2828/2-1, Inference statistical methods for behavioral genetics and neuroeconomics). A.N. gratefully acknowledges support from the Instituto de Salud Carlos III (grants RD12/0032/0011 and PT13/0001/0026) and the Spanish Government Grant (BFU2012-38236) and from FEDER.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. ; Most people in theworld (∼90%) are infected by the Epstein-Barr virus (EBV), which establishes itself permanently in B cells. Infection by EBV is related to a number of diseases including infectious mononucleosis, multiple sclerosis, and different types of cancer. So far, only seven complete EBV strains have been described, all of themcoming from donors presenting EBV-related diseases. To perform a detailed comparative genomic analysis of EBV including, for the first time, EBV strains derived from healthy individuals, we reconstructed EBV sequences infecting lymphoblastoid cell lines (LCLs) from the 1000 Genomes Project. As strain B95-8 was used to transform B cells to obtain LCLs, it is always present, but a specific deletion in its genome sets it apart from natural EBV strains. After studying hundreds of individuals, we determined the presence of natural EBV in at least 10 of them and obtained a set of variants specific to wild-type EBV. By mapping the natural EBV reads into the EBV reference genome (NC007605), we constructed nearly complete wild-type viralgenomesfrom three individuals.Adding themtothefivedisease-derived EBVgenomicsequences available in the literature, we performed an in-depth comparative genomic analysis. We found that latency genes harbor more nucleotide diversity than lytic genes and that six out of nine latency-related genes, as well as other genes involved in viral attachment and entry into host cells, packaging, and the capsid, present the molecular signature of accelerated protein evolution rates, suggesting rapid host-parasite coevolution. © 2014 The Author(s). ; This work was supported by the Spanish Multiple Sclerosis Network (REEM), of the Instituto de Salud Carlos III (RD07/0060 and RD12/0032/0011) to A.N., A.A., and P.V.; by the Spanish Government Grants BFU2009-13409-C02-02 and BFU2012-38236 to A.N.; and by FEDER. ; Peer Reviewed

Most people in the world (∼90%) are infected by the Epstein–Barr virus (EBV), which establishes itself permanently in B cells. Infection by EBV is related to a number of diseases including infectious mononucleosis, multiple sclerosis, and different types of cancer. So far, only seven complete EBV strains have been described, all of them coming from donors presenting EBV-related diseases. To perform a detailed comparative genomic analysis of EBV including, for the first time, EBV strains derived from healthy individuals, we reconstructed EBV sequences infecting lymphoblastoid cell lines (LCLs) from the 1000 Genomes Project. As strain B95-8 was used to transform B cells to obtain LCLs, it is always present, but a specific deletion in its genome sets it apart from natural EBV strains. After studying hundreds of individuals, we determined the presence of natural EBV in at least 10 of them and obtained a set of variants specific to wild-type EBV. By mapping the natural EBV reads into the EBV reference genome (NC007605), we constructed nearly complete wild-type viral genomes from three individuals. Adding them to the five disease-derived EBV genomic sequences available in the literature, we performed an in-depth comparative genomic analysis. We found that latency genes harbor more nucleotide diversity than lytic genes and that six out of nine latency-related genes, as well as other genes involved in viral attachment and entry into host cells, packaging, and the capsid, present the molecular signature of accelerated protein evolution rates, suggesting rapid host–parasite coevolution. ; This work was supported by the Spanish Multiple Sclerosis Network (REEM), of the Instituto de Salud Carlos III (RD07/0060 and RD12/0032/0011) to A.N., A.A., and P.V. ; by the Spanish Government Grants BFU2009-13409-C02-02 and BFU2012-38236 to A.N.; and by FEDER

The popularization of large-scale federated Genome-Wide Association Study (GWAS) where multiple data owners share their genome data to conduct federated analytics uncovers new privacy issues that have remained unnoticed or not given proper attention. Indeed, as soon as a diverse type of interested parties (e.g., private or public biocenters and governmental institutions from around the globe) and individuals from heterogeneous populations are participating in cooperative studies, interdependent and multi-party privacy appear as crucial issues that are currently not adequately assessed. In fact, in federated GWAS environments, the privacy of individuals and parties does not depend solely on their own behavior anymore but also on others, because a collaborative environment opens new credible adversary models. For instance, one might want to tailor the privacy guarantees to withstand the presence of potentially colluding federation members aiming to violate other members' data privacy and the privacy deterioration that might occur in the presence of interdependent genomic data (e.g., due to the presence of relatives in studies or the perpetuation of previous genomic privacy leaks in future studies). In this work, we catalog and discuss the features, unsolved problems, and challenges to tackle toward truly end-to-end private and practical federated GWAS.

[Background] Plant breeding has been proposed as one of the most effective and environmentally safe methods to control fungal infection and to reduce fumonisin accumulation. However, conventional breeding can be hampered by the complex genetic architecture of resistance to fumonisin accumulation and marker-assisted selection is proposed as an efficient alternative. In the current study, GWAS has been performed for the first time for detecting high-resolution QTL for resistance to fumonisin accumulation in maize kernels complementing published GWAS results for Fusarium ear rot. ; [Results] Thirty-nine SNPs significantly associated with resistance to fumonisin accumulation in maize kernels were found and clustered into 17 QTL. Novel QTLs for fumonisin content would be at bins 3.02, 5.02, 7.05 and 8.07. Genes with annotated functions probably implicated in resistance to pathogens based on previous studies have been highlighted. ; [Conclusions] Breeding approaches to fix favorable functional variants for genes implicated in maize immune response signaling may be especially useful to reduce kernel contamination with fumonisins without significantly interfering in mycelia development and growth and, consequently, in the beneficial endophytic behavior of Fusarium verticillioides. ; This research was funded by the Autonomous Government of Galicia, Spain (project IN607A/013), and by the "Secretaría de Estado de Investigación, Desarrollo e Innovación", Spain, within the projects AGL2015–67313-C2–1-R and AGL2015–67313-C2–2-R, which were co-financed with European Social Funds. R. Santiago acknowledges postdoctoral contract "Ramón y Cajal" financed by the "Secretaría de Estado de Investigación, Desarrollo e Innovación" and co-financed by the "Universidad de Vigo", Spain, and the European Social Funds.

Traditional statistical methods for confidentiality protection of statistical databases do not scale well to deal with GWAS databases especially in terms of guarantees regarding protection from linkage to external information. The more recent concept of differential privacy, introduced by the cryptographic community, is an approach which provides a rigorous definition of privacy with meaningful privacy guarantees in the presence of arbitrary external information, although the guarantees may come at a serious price in terms of data utility. Building on such notions, we propose new methods to release aggregate GWAS data without compromising an individual's privacy. We present methods for releasing differentially private minor allele frequencies, chi-square statistics and p-values. We compare these approaches on simulated data and on a GWAS study of canine hair length involving 685 dogs. We also propose a privacy-preserving method for finding genome-wide associations based on a differentially-private approach to penalized logistic regression.

AbstractSelf-rated health questions have been proven to be a highly reliable and valid measure of overall health as measured by other indicators in many population groups. It also has been shown to be a very good predictor of mortality, chronic or severe diseases, and the need for services, and is positively correlated with clinical assessments. Genetic factors have been estimated to account for 25–64% of the variance in the liability of self-rated health. The aim of the present study was to identify Single Nucleotide Polymorphisms (SNPs) underlying the heritability of self-rated health by conducting a genome-wide association analysis in a large sample of 6,706 Australian individuals aged 18–92. No genome wide significant SNPs associated with self-rated health could be identified, indicating that self-rated health may be influenced by a large number of SNPs with very small effect size. A very large sample will be needed to identify these SNPs.

Background There is a growing interest to decipher the genetic background of resilience and its possible improvement through selective breeding. The objective of the present study was to provide new insights into the genetic make-up of resilience in growing pigs by identifying genomic regions and candidate genes associated with resilience indicators. Commercial Duroc pigs were challenged with an attenuated Aujeszky vaccine at 12 weeks of age. Two resilience indicators were used: deviation from the expected body weight at 16 weeks of age given the growth curve of non-vaccinated pigs (∆BW) and the increase in acute-phase protein haptoglobin at four days post-vaccination (∆HP). Genome-wide association analyses were carried out on 445 pigs, using genotypes at 41,165 single nucleotide polymorphisms (SNPs) and single-marker and Bayesian multiple-marker regression approaches. Results Genomic regions on pig chromosomes 2, 8, 9, 11 (∆BW) and 8, 9, 13 (∆HP) were found to be associated with the resilience indicators and explained high proportions of their genetic variance. The genomic regions that were associated explained 27 and 5% of the genetic variance of ∆BW and ∆HP, respectively. These genomic regions harbour promising candidate genes that are involved in pathways related to immune response, response to stress, or signal transduction ( CD6 , PTGDR2 , IKZF1 , RNASEL and MYD88 ), and growth ( GRB10 and LCORL ). Conclusions Our study identified novel genomic regions that are associated with two resilience indicators (∆BW and ∆HP) in pigs. These associated genomic regions harbour potential candidate genes involved in immune response and growth pathways, which emphasise the strong relationship between resilience and immune response. ; The research was funded by the Spanish Ministry of Science, Innovation and Universities and the European Union Regional Development Funds (Grant RTI2018-097700-B-I00). HL is a recipient of a PhD scholarship from the Department of Research and Universities of the Government of Catalonia.