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  • 1
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    Human metabolic individuality in biomedical and pharmaceutical research (2011)
    Nature Publishing Group (NPG)
    Details
    Publication Date: 2011-09-03
    Description: Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3832838/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3832838/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Suhre, Karsten -- Shin, So-Youn -- Petersen, Ann-Kristin -- Mohney, Robert P -- Meredith, David -- Wagele, Brigitte -- Altmaier, Elisabeth -- CARDIoGRAM -- Deloukas, Panos -- Erdmann, Jeanette -- Grundberg, Elin -- Hammond, Christopher J -- de Angelis, Martin Hrabe -- Kastenmuller, Gabi -- Kottgen, Anna -- Kronenberg, Florian -- Mangino, Massimo -- Meisinger, Christa -- Meitinger, Thomas -- Mewes, Hans-Werner -- Milburn, Michael V -- Prehn, Cornelia -- Raffler, Johannes -- Ried, Janina S -- Romisch-Margl, Werner -- Samani, Nilesh J -- Small, Kerrin S -- Wichmann, H-Erich -- Zhai, Guangju -- Illig, Thomas -- Spector, Tim D -- Adamski, Jerzy -- Soranzo, Nicole -- Gieger, Christian -- 091746/Wellcome Trust/United Kingdom -- 091746/Z/10/Z/Wellcome Trust/United Kingdom -- 1R01HL103931-01/HL/NHLBI NIH HHS/ -- HL087647/HL/NHLBI NIH HHS/ -- MOP172605/Canadian Institutes of Health Research/Canada -- MOP77682/Canadian Institutes of Health Research/Canada -- MOP-82810/Canadian Institutes of Health Research/Canada -- N01-AG-12100/AG/NIA NIH HHS/ -- N01-HC-55015/HC/NHLBI NIH HHS/ -- N01-HC-55016/HC/NHLBI NIH HHS/ -- N01-HC-55018/HC/NHLBI NIH HHS/ -- N01-HC-55019/HC/NHLBI NIH HHS/ -- N01-HC-55020/HC/NHLBI NIH HHS/ -- N01-HC-55021/HC/NHLBI NIH HHS/ -- N01-HC-55022/HC/NHLBI NIH HHS/ -- P01 HL098055/HL/NHLBI NIH HHS/ -- P01HL076491-06/HL/NHLBI NIH HHS/ -- P01HL087018/HL/NHLBI NIH HHS/ -- R01 HL087647/HL/NHLBI NIH HHS/ -- R01 HL087676/HL/NHLBI NIH HHS/ -- R01DK080732/DK/NIDDK NIH HHS/ -- R01HL089650-02/HL/NHLBI NIH HHS/ -- Biotechnology and Biological Sciences Research Council/United Kingdom -- British Heart Foundation/United Kingdom -- Cancer Research UK/United Kingdom -- Intramural NIH HHS/ -- Medical Research Council/United Kingdom -- England -- Nature. 2011 Aug 31;477(7362):54-60. doi: 10.1038/nature10354.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany. karsten@suhre.fr〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/21886157" target="_blank"〉PubMed〈/a〉
    Keywords: Adolescent ; Adult ; Aged ; Aged, 80 and over ; *Biomedical Research ; Blood/metabolism ; Child ; Chronic Disease ; Coronary Artery Disease/genetics ; Diabetes Mellitus/genetics ; *Drug Industry ; Female ; Genetic Loci/genetics ; *Genetic Variation ; *Genome-Wide Association Study ; Genotype ; Humans ; Male ; Metabolism/*genetics ; Metabolomics ; Middle Aged ; Pharmacogenetics ; Renal Insufficiency/genetics ; Risk Factors ; Venous Thromboembolism/genetics ; Young Adult
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Published by Nature Publishing Group (NPG)
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  • 2
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    SNiPA: an interactive, genetic variant-centered annotation browser (2015)
    Oxford University Press
    Details
    Publication Date: 2015-04-12
    Description: Motivation: Linking genes and functional information to genetic variants identified by association studies remains difficult. Resources containing extensive genomic annotations are available but often not fully utilized due to heterogeneous data formats. To enhance their accessibility, we integrated many annotation datasets into a user-friendly webserver. Availability and implementation: http://www.snipa.org/ Contact: g.kastenmueller@helmholtz-muenchen.de Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 3
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    Genetics of human metabolism: an update (2015)
    Oxford University Press
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    Publication Date: 2015-09-17
    Description: Genome-wide association studies with metabolomics (mGWAS) identify genetically influenced metabotypes (GIMs), their ensemble defining the heritable part of every human's metabolic individuality. Knowledge of genetic variation in metabolism has many applications of biomedical and pharmaceutical interests, including the functional understanding of genetic associations with clinical end points, design of strategies to correct dysregulations in metabolic disorders and the identification of genetic effect modifiers of metabolic disease biomarkers. Furthermore, it has been shown that GIMs provide testable hypotheses for functional genomics and metabolomics and for the identification of novel gene functions and metabolite identities. mGWAS with growing sample sizes and increasingly complex metabolic trait panels are being conducted, allowing for more comprehensive and systems-based downstream analyses. The generated large datasets of genetic associations can now be mined by the biomedical research community and provide valuable resources for hypothesis-driven studies. In this review, we provide a brief summary of the key aspects of mGWAS, followed by an update of recently published mGWAS. We then discuss new approaches of integrating and exploring mGWAS results and finish by presenting selected applications of GIMs in recent studies.
    Print ISSN: 0964-6906
    Electronic ISSN: 1460-2083
    Topics: Biology , Medicine
    Published by Oxford University Press
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  • 4
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    Epigenetics meets metabolomics: an epigenome-wide association study with blood serum metabolic traits (2013)
    Oxford University Press
    Details
    Publication Date: 2013-12-21
    Description: Previously, we reported strong influences of genetic variants on metabolic phenotypes, some of them with clinical relevance. Here, we hypothesize that DNA methylation may have an important and potentially independent effect on human metabolism. To test this hypothesis, we conducted what is to the best of our knowledge the first epigenome-wide association study (EWAS) between DNA methylation and metabolic traits (metabotypes) in human blood. We assess 649 blood metabolic traits from 1814 participants of the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) population study for association with methylation of 457 004 CpG sites, determined on the Infinium HumanMethylation450 BeadChip platform. Using the EWAS approach, we identified two types of methylome–metabotype associations. One type is driven by an underlying genetic effect; the other type is independent of genetic variation and potentially driven by common environmental and life-style-dependent factors. We report eight CpG loci at genome-wide significance that have a genetic variant as confounder ( P = 3.9 x 10 –20 to 2.0 x 10 –108 , r 2 = 0.036 to 0.221). Seven loci display CpG site-specific associations to metabotypes, but do not exhibit any underlying genetic signals ( P = 9.2 x 10 –14 to 2.7 x 10 –27 , r 2 = 0.008 to 0.107). We further identify several groups of CpG loci that associate with a same metabotype, such as 4-vinylphenol sulfate and 4-androsten-3-beta,17-beta-diol disulfate. In these cases, the association between CpG-methylation and metabotype is likely the result of a common external environmental factor, including smoking. Our study shows that analysis of EWAS with large numbers of metabolic traits in large population cohorts are, in principle, feasible. Taken together, our data suggest that DNA methylation plays an important role in regulating human metabolism.
    Print ISSN: 0964-6906
    Electronic ISSN: 1460-2083
    Topics: Biology , Medicine
    Published by Oxford University Press
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  • 5
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    HoPaCI-DB: host-Pseudomonas and Coxiella interaction database (2013)
    Oxford University Press
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    Publication Date: 2013-12-29
    Description: Bacterial infectious diseases are the result of multifactorial processes affected by the interplay between virulence factors and host targets. The host- Pseudomonas and Coxiella interaction database (HoPaCI-DB) is a publicly available manually curated integrative database ( http://mips.helmholtz-muenchen.de/HoPaCI/ ) of host–pathogen interaction data from Pseudomonas aeruginosa and Coxiella burnetii . The resource provides structured information on 3585 experimentally validated interactions between molecules, bioprocesses and cellular structures extracted from the scientific literature. Systematic annotation and interactive graphical representation of disease networks make HoPaCI-DB a versatile knowledge base for biologists and network biology approaches.
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 6
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    The HIB database of annotated UniGene clusters (2001)
    Oxford University Press
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    Publication Date: 2001-06-01
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 7
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    PEDANT covers all complete RefSeq genomes (2009)
    Oxford University Press
    Details
    Publication Date: 2009-01-01
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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