Biological interpretation of genome-wide association studies using predicted gene functions

The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loc...

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Published in	Nature communications Vol. 6; no. 1; p. 5890
Main Authors	Pers, Tune H., Karjalainen, Juha M., Chan, Yingleong, Westra, Harm-Jan, Wood, Andrew R., Yang, Jian, Lui, Julian C., Vedantam, Sailaja, Gustafsson, Stefan, Esko, Tonu, Frayling, Tim, Speliotes, Elizabeth K., Boehnke, Michael, Raychaudhuri, Soumya, Fehrmann, Rudolf S. N., Hirschhorn, Joel N., Franke, Lude
Format	Journal Article
Language	English
Published	London Nature Publishing Group UK 19.01.2015 Nature Publishing Group
Subjects	38/39 631/114/2398 631/208/191 631/208/205/2138 Endocrinology Gene expression Genetics Genome-Wide Association Study - methods Genomes Hospitals Humanities and Social Sciences Medicin och hälsovetenskap multidisciplinary Proteins Science Science (multidisciplinary) Software Queensland Australia United Kingdom > UK United States > US Massachusetts Australia Ann Arbor Michigan Michigan
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Abstract	The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes. Identifying which genes and pathways explain genetic associations is challenging. Here, the authors present DEPICT, a tool for gene prioritization, pathway analysis and tissue/cell-type enrichment analysis that can be used to generate testable hypotheses from genetic association studies.
AbstractList	The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes. The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes. Identifying which genes and pathways explain genetic associations is challenging. Here, the authors present DEPICT, a tool for gene prioritization, pathway analysis and tissue/cell-type enrichment analysis that can be used to generate testable hypotheses from genetic association studies.
ArticleNumber	5890
Author	Boehnke, Michael Fehrmann, Rudolf S. N. Franke, Lude Wood, Andrew R. Speliotes, Elizabeth K. Karjalainen, Juha M. Pers, Tune H. Esko, Tonu Westra, Harm-Jan Yang, Jian Chan, Yingleong Vedantam, Sailaja Gustafsson, Stefan Raychaudhuri, Soumya Lui, Julian C. Frayling, Tim Hirschhorn, Joel N.
AuthorAffiliation	13 Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA 8 The University of Queensland Diamantina Institute, The Translation Research Institute, Brisbane, Queensland 4012, Australia 7 Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia 11 Estonian Genome Center, University of Tartu, Tartu 51010, Estonia 1 Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Boston, Massachusetts 02115, USA 3 Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen 9711, The Netherlands 6 Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK 5 Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts 02115, USA 2 Medical and Population Genetics Program, Broad Institute of MITand Harvard, Cambridge, Massachusetts 2142, USA 4 Department of Gene
AuthorAffiliation_xml	– name: 2 Medical and Population Genetics Program, Broad Institute of MITand Harvard, Cambridge, Massachusetts 2142, USA – name: 1 Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Boston, Massachusetts 02115, USA – name: 12 Department of Internal Medicine, Division of Gastroenterology, and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA – name: 13 Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA – name: 14 Partners HealthCare Center for Personalized Genetic Medicine, Boston, Massachusetts 02115, USA – name: 5 Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts 02115, USA – name: 7 Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia – name: 11 Estonian Genome Center, University of Tartu, Tartu 51010, Estonia – name: 8 The University of Queensland Diamantina Institute, The Translation Research Institute, Brisbane, Queensland 4012, Australia – name: 6 Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK – name: 4 Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA – name: 9 Section on Growth and Development, Program in Developmental Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892, USA – name: 16 Faculty of Medical and Human Sciences, University of Manchester, Manchester M13 9PL, UK – name: 15 Division of Rheumatology, Immunology and Allergy, Brigham and Women’s Hospital, Boston, Massachusetts 02115, USA – name: 3 Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen 9711, The Netherlands – name: 10 Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala 75185, Sweden
Author_xml	– sequence: 1 givenname: Tune H. surname: Pers fullname: Pers, Tune H. email: tunepers@broadinstitute.org organization: Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Medical and Population Genetics Program, Broad Institute of MIT and Harvard – sequence: 2 givenname: Juha M. surname: Karjalainen fullname: Karjalainen, Juha M. organization: Department of Genetics, University of Groningen, University Medical Centre Groningen – sequence: 3 givenname: Yingleong surname: Chan fullname: Chan, Yingleong organization: Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Department of Genetics, Harvard Medical School – sequence: 4 givenname: Harm-Jan surname: Westra fullname: Westra, Harm-Jan organization: Division of Genetics, Brigham and Women’s Hospital – sequence: 5 givenname: Andrew R. surname: Wood fullname: Wood, Andrew R. organization: Genetics of Complex Traits, University of Exeter Medical School, University of Exeter – sequence: 6 givenname: Jian surname: Yang fullname: Yang, Jian organization: Queensland Brain Institute, The University of Queensland, The University of Queensland Diamantina Institute, The Translation Research Institute – sequence: 7 givenname: Julian C. surname: Lui fullname: Lui, Julian C. organization: Section on Growth and Development, Program in Developmental Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health – sequence: 8 givenname: Sailaja surname: Vedantam fullname: Vedantam, Sailaja organization: Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Medical and Population Genetics Program, Broad Institute of MIT and Harvard – sequence: 9 givenname: Stefan surname: Gustafsson fullname: Gustafsson, Stefan organization: Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University – sequence: 10 givenname: Tonu surname: Esko fullname: Esko, Tonu organization: Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Estonian Genome Center, University of Tartu – sequence: 11 givenname: Tim surname: Frayling fullname: Frayling, Tim organization: Genetics of Complex Traits, University of Exeter Medical School, University of Exeter – sequence: 12 givenname: Elizabeth K. surname: Speliotes fullname: Speliotes, Elizabeth K. organization: Department of Internal Medicine, Division of Gastroenterology, and Department of Computational Medicine and Bioinformatics, University of Michigan – sequence: 14 givenname: Michael surname: Boehnke fullname: Boehnke, Michael organization: Department of Biostatistics and Center for Statistical Genetics, University of Michigan – sequence: 15 givenname: Soumya surname: Raychaudhuri fullname: Raychaudhuri, Soumya organization: Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Division of Genetics, Brigham and Women’s Hospital, Partners HealthCare Center for Personalized Genetic Medicine, Division of Rheumatology, Immunology and Allergy, Brigham and Women’s Hospital, Faculty of Medical and Human Sciences, University of Manchester – sequence: 16 givenname: Rudolf S. N. surname: Fehrmann fullname: Fehrmann, Rudolf S. N. organization: Department of Genetics, University of Groningen, University Medical Centre Groningen – sequence: 17 givenname: Joel N. surname: Hirschhorn fullname: Hirschhorn, Joel N. email: joelh@broadinstitute.org organization: Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Department of Genetics, Harvard Medical School – sequence: 18 givenname: Lude surname: Franke fullname: Franke, Lude email: lude@ludesign.nl organization: Department of Genetics, University of Groningen, University Medical Centre Groningen
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/25597830$$D View this record in MEDLINE/PubMed https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-245522$$DView record from Swedish Publication Index http://kipublications.ki.se/Default.aspx?queryparsed=id:130533310$$DView record from Swedish Publication Index
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ContentType	Journal Article
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Copyright	Springer Nature Limited 2015 Copyright Nature Publishing Group Jan 2015 2015 Macmillan Publishers Limited. All rights reserved. 2015
Copyright_xml	– notice: Springer Nature Limited 2015 – notice: Copyright Nature Publishing Group Jan 2015 – notice: 2015 Macmillan Publishers Limited. All rights reserved. 2015
CorporateAuthor	Genetic Investigation of ANthropometric Traits (GIANT) Consortium
CorporateAuthor_xml	– name: Genetic Investigation of ANthropometric Traits (GIANT) Consortium
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DOI	10.1038/ncomms6890
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Snippet	The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present...
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SubjectTerms	38/39 631/114/2398 631/208/191 631/208/205/2138 Endocrinology Gene expression Genetics Genome-Wide Association Study - methods Genomes Hospitals Humanities and Social Sciences Medicin och hälsovetenskap multidisciplinary Proteins Science Science (multidisciplinary) Software
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Title	Biological interpretation of genome-wide association studies using predicted gene functions
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