119 research outputs found

    Association study in African-admixed populations across the Americas recapitulates asthma risk loci in non-African populations

    Get PDF
    Publisher's version (útgefin grein)Asthma is a complex disease with striking disparities across racial and ethnic groups. Despite its relatively high burden, representation of individuals of African ancestry in asthma genome-wide association studies (GWAS) has been inadequate, and true associations in these underrepresented minority groups have been inconclusive. We report the results of a genome-wide meta-analysis from the Consortium on Asthma among African Ancestry Populations (CAAPA; 7009 asthma cases, 7645 controls). We find strong evidence for association at four previously reported asthma loci whose discovery was driven largely by non-African populations, including the chromosome 17q12–q21 locus and the chr12q13 region, a novel (and not previously replicated) asthma locus recently identified by the Trans-National Asthma Genetic Consortium (TAGC). An additional seven loci reported by TAGC show marginal evidence for association in CAAPA. We also identify two novel loci (8p23 and 8q24) that may be specific to asthma risk in African ancestry populations.We thank Goncalo Abecasis for coordinating inclusion of the CAAPA reference panel on the Michigan Imputation Server, Todd Deppe, Estelle Giraud, Cindy Lawley from Illumina for genotyping services, and Pat Oldewurtel for administrative and technical support.Peer Reviewe

    On Robustness of Deep Neural Networks: A Comprehensive Study on the Effect of Architecture and Weight Initialization to Susceptibility and Transferability of Adversarial Attacks

    Get PDF
    Neural network models have shown state of the art performance inseveral applications. However it has been observed that they aresusceptible to adversarial attacks: small perturbations to the inputthat fool a network model into mislabelling the input data. Theseattacks can also transfer from one network model to another, whichraises concerns over their applicability, particularly when there areprivacy and security risks involved. In this work, we conduct a studyto analyze the effect of network architectures and weight initial-ization on the robustness of individual network models as well astransferability of adversarial attacks. Experimental results demon-strate that while weight initialization has no affect on the robustnessof a network model, it does have an affect on attack transferabilityto a network model. Results also show that the complexity of anetwork model as indicated by the total number of parameters andMAC number is not indicative of a network’s robustness to attackor transferability, but accuracy can be; within the same architec-ture, higher accuracy usually indicates a more robust network, butacross architectures there is no strong link between accuracy androbustness

    Determining ancestry proportions in complex admixture scenarios in South Africa using a novel proxy ancestry selection method

    Get PDF
    Admixed populations can make an important contribution to the discovery of disease susceptibility genes if the parental populations exhibit substantial variation in susceptibility. Admixture mapping has been used successfully, but is not designed to cope with populations that have more than two or three ancestral populations. The inference of admixture proportions and local ancestry and the imputation of missing genotypes in admixed populations are crucial in both understanding variation in disease and identifying novel disease loci. These inferences make use of reference populations, and accuracy depends on the choice of ancestral populations. Using an insufficient or inaccurate ancestral panel can result in erroneously inferred ancestry and affect the detection power of GWAS and meta-analysis when using imputation. Current algorithms are inadequate for multi-way admixed populations. To address these challenges we developed PROXYANC, an approach to select the best proxy ancestral populations. From the simulation of a multi-way admixed population we demonstrate the capability and accuracy of PROXYANC and illustrate the importance of the choice of ancestry in both estimating admixture proportions and imputing missing genotypes

    A Panel of Ancestry Informative Markers for the Complex Five-Way Admixed South African Coloured Population

    Get PDF
    Admixture is a well known confounder in genetic association studies. If genome-wide data is not available, as would be the case for candidate gene studies, ancestry informative markers (AIMs) are required in order to adjust for admixture. The predominant population group in the Western Cape, South Africa, is the admixed group known as the South African Coloured (SAC). A small set of AIMs that is optimized to distinguish between the five source populations of this population (African San, African non-San, European, South Asian, and East Asian) will enable researchers to cost-effectively reduce false-positive findings resulting from ignoring admixture in genetic association studies of the population. Using genome-wide data to find SNPs with large allele frequency differences between the source populations of the SAC, as quantified by Rosenberg et. al's -statistic, we developed a panel of AIMs by experimenting with various selection strategies. Subsets of different sizes were evaluated by measuring the correlation between ancestry proportions estimated by each AIM subset with ancestry proportions estimated using genome-wide data. We show that a panel of 96 AIMs can be used to assess ancestry proportions and to adjust for the confounding effect of the complex five-way admixture that occurred in the South African Coloured population.Department of HE and Training approved lis

    Determining ancestry proportions in complex admixture scenarios in South Africa using a novel proxy ancestry selection method

    Get PDF
    Publication of this article was funded by the Stellenbosch University Open Access Fund.The original publication is available at http://www.plosone.org/Admixed populations can make an important contribution to the discovery of disease susceptibility genes if the parental populations exhibit substantial variation in susceptibility. Admixture mapping has been used successfully, but is not designed to cope with populations that have more than two or three ancestral populations. The inference of admixture proportions and local ancestry and the imputation of missing genotypes in admixed populations are crucial in both understanding variation in disease and identifying novel disease loci. These inferences make use of reference populations, and accuracy depends on the choice of ancestral populations. Using an insufficient or inaccurate ancestral panel can result in erroneously inferred ancestry and affect the detection power of GWAS and meta-analysis when using imputation. Current algorithms are inadequate for multi-way admixed populations. To address these challenges we developed PROXYANC, an approach to select the best proxy ancestral populations. From the simulation of a multi-way admixed population we demonstrate the capability and accuracy of PROXYANC and illustrate the importance of the choice of ancestry in both estimating admixture proportions and imputing missing genotypes. We applied this approach to a complex, uniquely admixed South African population. Using genome-wide SNP data from over 764 individuals, we accurately estimate the genetic contributions from the best ancestral populations: isiXhosa (33%±0:226), {Khomani SAN (31%±0:195), European (16%±0:118), Indian (13%±0:094), and Chinese (7%±0:0488). We also demonstrate that the ancestral allele frequency differences correlate with increased linkage disequilibrium in the South African population, which originates from admixture events rather than population bottlenecks.Stellenbosch UniversityMRC Centre for Molecular and Cellular Biology and the DST/NRF Centre of Excellence for Biomedical TB ResearchCarnegie Corporation Grant and by the Department of Clinical Laboratory Sciences, University of Cape TownPublishers' versio

    Associations between human leukocyte antigen class I variants and the Mycobacterium tuberculosis subtypes causing disease

    Get PDF
    BACKGROUND. The development of active tuberculosis disease has been shown to be multifactorial. Interactions between host and bacterial genotype may influence disease outcome, with some studies indicating the adaptation of M. tuberculosis strains to specific human populations. Here we investigate the role of the human leukocyte antigen (HLA) class I genes in this biological process. METHODS. Three hundred patients with tuberculosis from South Africa were typed for their HLA class I alleles by direct sequencing. Mycobacterium tuberculosis genotype classification was done by IS6110 restriction fragment length polymorphism genotyping and spoligotyping. RESULTS. We showed that Beijing strain occurred more frequently in individuals with multiple disease episodes (P < .001) with the HLA-B27 allele lowering the odds of having an additional episode (odds ratio, 0.21; P = .006). Associations were also identified for specific HLA types and disease caused by the Beijing, LAM, LCC, and Quebec strains. HLA types were also associated with disease caused by strains from the Euro-American or East Asian lineages, and the frequencies of these alleles in their sympatric human populations identified potential coevolutionary events between host and pathogen. CONCLUSIONS. This is the first report of the association of human HLA types and M. tuberculosis strain genotype, highlighting that both host and pathogen genetics need to be taken into consideration when studying tuberculosis disease development.Web of Scienc

    Crop Updates 2006 - Weeds

    Get PDF
    This session covers thirty seven papers from different authors: 1. ACKNOWLEDGEMENTS, Alexandra Douglas, CONVENOR – WEEDS DEPARTMENT OF AGRICULTURE SPRAY TECHNOLOGY 2. Meeting the variable application goals with new application technology, Thomas M. Wolf, Agriculture and Agri-Food Canada, Saskatoon Research Centre 3. Spray nozzles for grass weed control, Harm van Rees, BCG (Birchip Cropping Group) 4. Boom sprayer setups – achieving coarse droplets with different operating parameters, Bill Gordon, Bill Gordon Consulting 5. Complying with product label requirements, Bill Gordon, Bill Gordon Consulting 6. IWM a proven performer over 5 years in 33 focus paddocks, Peter Newman and Glenn Adam, Department of Agriculture 7. Crop topping of wild radish in lupins and barley, how long is a piece of string? Peter Newman and Glenn Adam, Department of Agriculture 8. Determining the right timing to maximise seed set control of wild radish, Aik Cheam and Siew Lee, Department of Agriculture 9. Why weed wiping varies in success rates in broadacre crops? Aik Cheam1, Katherine Hollaway2, Siew Lee1, Brad Rayner1 and John Peirce1,1Department of Agriculture, 2Department of Primary Industries, Victoria 10. Are WA growers successfully managing herbicide resistant annual ryegrass? Rick Llewellynabc, Frank D’Emdena, Mechelle Owenb and Stephen Powlesb aCRC Australian Weed Management, School of Agricultural and Resource Economics, University of Western Australia; bWA Herbicide Resistance Initiative, University of Western Australia. cCurrent address: CSIRO Sustainable Ecosystems 11. Do herbicide resistant wild radish populations look different? Michael Walsh, Western Australian Herbicide Resistance Initiative, University of Western Australia 12. Can glyphosate and paraquat annual ryegrass reduce crop topping efficacy? Emma Glasfurd, Michael Walsh and Kathryn Steadman, Western Australian Herbicide Resistance Initiative, University of Western Australia 13. Tetraploid ryegrass for WA. Productive pasture phase AND defeating herbicide resistant ryegrass, Stephen Powlesa, David Ferrisab and Bevan Addisonc, aWA Herbicide Resistance Initiative, University of Western Australia; bDepartment of Agriculture, and cElders Limited 14. Long-term management impact on seedbank of wild radish with multiple resistance to diflufenican and triazines, Aik Cheam, Siew Lee, Dave Nicholson and Ruben Vargas, Department of Agriculture 15. East-west crop row orientation improves wheat and barley yields, Dr Shahab Pathan, Dr Abul Hashem, Nerys Wilkins and Catherine Borger3, Department of Agriculture, 3WAHRI, The University ofWestern Australia 16. Competitiveness of different lupin cultivars with wild radish, Dr Shahab Pathan, Dr Bob French and Dr Abul Hashem, Department of Agriculture 17. Managing herbicide resistant weeds through farming systems, Kari-Lee Falconer, Martin Harries and Chris Matthews, Department of Agriculture 18. Lupins tolerate in-row herbicides well, Peter Newman and Martin Harries, Department of Agriculture 19. Summer weeds can reduce wheat grain yield and protein, Dr Abul Hashem1, Dr Shahab Pathan1 and Vikki Osten3, 1Department Agriculture, 3Senior Agronomist, CRC for Australian Weed Management, Queensland Department of Primary Industries and Fisheries 20. Diuron post-emergent in lupins, the full story, Peter Newman and Glenn Adam, Department of Agriculture 21. Double incorporation of trifluralin, Peter Newman and Glenn Adam, Department of Agriculture 22. Herbicide tolerance of narrow leafed and yellow lupins, Harmohinder Dhammu, David Nicholson, Department of Agriculture 23. MIG narrow leaf lupin herbicide tolerance trial, Richard Quinlan, Planfarm Pty Ltd, Trials Coordinator MIG; Debbie Allen, Research Agronomist – MIG 24. Herbicide tolerance of new albus lupins, Harmohinder Dhammu, David Nicholson, Department of Agriculture 25. Field pea x herbicide tolerance, Mark Seymour and Harmohinder Dhammu, Research Officers, and Pam Burgess, Department of Agriculture 26. Faba bean variety x herbicide tolerance, Mark Seymour and Harmohinder Dhammu, Research Officers, and Pam Burgess, Department of Agriculture 27. Herbicide tolerance of new Kabili chickpeas, Harmohinder Dhammu, Owen Coppen and Chris Roberts, Department of Agriculture 28. Timing of phenoxys application in EAG Eagle Rock, Harmohinder Dhammu, David Nicholson, Department of Agriculture 29. Herbicide tolerance of new wheat varieties, Harmohinder Dhammu, David Nicholson, Department of Agriculture 30. Lathyrus sativus x herbicide tolerance, Mark Seymour, Department of Agriculture 31. Tolerance of annual pasture species to herbicides and mixtures containing diuron, Christiaan Valentine and David Ferris, Department of Agriculture 32. The impact of herbicides on pasture legume species – a summary of scientific trial results across 8 years, Christiaan Valentine and David Ferris, Department of Agriculture 33. The impact of spraytopping on pasture legume seed set, Christiaan Valentine and David Ferris, Department of Agriculture 34. Ascochyta interaction with Broadstrike in chickpeas, H.S. Dhammu1, A.K. Basandrai2,3, W.J. MacLeod1, 3 and C. Roberts1, 1Department of Agriculture, 2CSKHPAU, Dhaulakuan, Sirmour (HP), India and 3CLIMA 35. Best management practices for atrazine in broadacre crops, John Moore, Department of Agriculture, Neil Rothnie, Chemistry Centre of WA, Russell Speed, Department of Agriculture, John Simons, Department of Agriculture, and Ted Spadek, Chemistry Centre of WA 36. Biology and management of red dodder (Cuscuta planiflolia) – a new threat to the grains industry, Abul Hashem, Daya Patabendige and Chris Roberts, Department Agriculture 37. Help the wizard stop the green invaders! Michael Renton, Sally Peltzer and Art Diggle, Department of Agricultur

    Global Biobank Meta-analysis Initiative:Powering genetic discovery across human disease

    Get PDF
    Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)—a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.</p
    corecore