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- Abstract: found
- Article: found
Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics
research-article
Author(s):
Alvaro N. Barbeira
1 ,
Scott P. Dickinson
1 ,
Rodrigo Bonazzola
1 ,
Jiamao Zheng
1 ,
Heather E. Wheeler
2
,
3 ,
Jason M. Torres
4 ,
Eric S. Torstenson
5 ,
Kaanan P. Shah
1 ,
Tzintzuni Garcia
6 ,
Todd L. Edwards
7 ,
Eli A. Stahl
8
,
9 ,
Laura M. Huckins
8
,
9 ,
GTEx Consortium,
Dan L. Nicolae
1 ,
Nancy J. Cox
5 ,
Hae Kyung Im
1
,
Publication date (Electronic):
8 May 2018
Journal:
Nature Communications
Publisher:
Nature Publishing Group UK
Read this article at
There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.
Abstract
Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.
Abstract
Phenotypic variation and diseases are influenced by factors such as genetic variants and gene expression. Here, Barbeira et al. develop S-PrediXcan to compute PrediXcan results using summary data, and investigate the effects of gene expression variation on human phenotypes in 44 GTEx tissues and >100 phenotypes.
Related collections
Most cited references44
- Record: found
- Abstract: found
- Article: found
A global reference for human genetic variation
Lachlan Coin, Robert Garry, Oleksyk Taras (2018)
The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
- Record: found
- Abstract: found
- Article: found
Second-generation PLINK: rising to the challenge of larger and richer datasets
Christopher Chang, Carson Chow, Laurent Tellier … (2015)
PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for even faster and more scalable implementations of key functions. In addition, GWAS and population-genetic data now frequently contain probabilistic calls, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1's primary data format. To address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, O(sqrt(n))-time/constant-space Hardy-Weinberg equilibrium and Fisher's exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. This will be followed by PLINK 2.0, which will introduce (a) a new data format capable of efficiently representing probabilities, phase, and multiallelic variants, and (b) extensions of many functions to account for the new types of information. The second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.
- Record: found
- Abstract: found
- Article: not found
The Genotype-Tissue Expression (GTEx) project.
John M. Lonsdale, Jeffrey Thomas, Mike Salvatore … (2014)
Genome-wide association studies have identified thousands of loci for common diseases, but, for the majority of these, the mechanisms underlying disease susceptibility remain unknown. Most associated variants are not correlated with protein-coding changes, suggesting that polymorphisms in regulatory regions probably contribute to many disease phenotypes. Here we describe the Genotype-Tissue Expression (GTEx) project, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.
Author and article information
Contributors
Hae Kyung Im:
ORCID: http://orcid.org/0000-0003-0333-5685
haky@uchicago.edu
Journal
Journal ID (nlm-ta): Nat Commun
Journal ID (iso-abbrev): Nat Commun
Title:
Nature Communications
Publisher:
Nature Publishing Group UK
(London
)
ISSN
(Electronic):
2041-1723
Publication date
(Electronic):
8
May
2018
Publication date PMC-release: 8
May
2018
Publication date Collection: 2018
Volume: 9
Electronic Location Identifier: 1825
Affiliations
[1
]ISNI 0000 0004 1936 7822, GRID grid.170205.1, Section of Genetic Medicine, , The University of Chicago, ; Chicago, IL 60637 USA
[2
]ISNI 0000 0001 1089 6558, GRID grid.164971.c, Department of Biology, , Loyola University Chicago, ; Chicago, IL 60660 USA
[3
]ISNI 0000 0001 1089 6558, GRID grid.164971.c, Department of Computer Science, , Loyola University Chicago, ; Chicago, IL 60660 USA
[4
]ISNI 0000 0004 1936 7822, GRID grid.170205.1, Committee on Molecular Metabolism and Nutrition, , The University of Chicago, ; Chicago, IL 60637 USA
[5
]ISNI 0000 0004 1936 9916, GRID grid.412807.8, Vanderbilt Genetic Institute, , Vanderbilt University Medical Center, ; Nashville, TN 37232 USA
[6
]ISNI 0000 0004 1936 7822, GRID grid.170205.1, Center for Research Informatics, , The University of Chicago, ; Chicago, IL 60615 USA
[7
]ISNI 0000 0004 1936 9916, GRID grid.412807.8, Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, , Vanderbilt University Medical Center, ; Nashville, TN 37232 USA
[8
]ISNI 0000 0001 0670 2351, GRID grid.59734.3c, Division of Psychiatric Genomics, , Icahn School of Medicine at Mount Sinai, ; NYC, NY 10029 USA
[9
]ISNI 0000 0001 0670 2351, GRID grid.59734.3c, Department of Genetics and Genomics, , Icahn School of Medicine at Mount Sinai, ; NYC, NY 10029 USA
[10
]GRID grid.66859.34, The Broad Institute of Massachusetts Institute of Technology and Harvard University,
; Cambridge, MA 02142 USA
[11
]ISNI 0000 0004 0386 9924, GRID grid.32224.35, Analytic and Translational Genetics Unit, , Massachusetts General Hospital, ; Boston, MA 02114 USA
[12
]ISNI 0000 0004 0386 9924, GRID grid.32224.35, Massachusetts General Hospital Cancer Center, Department of Pathology, , Massachusetts General Hospital, ; Boston, MA 02114 USA
[13
]ISNI 000000041936754X, GRID grid.38142.3c, Department of Genetics, , Harvard Medical School, ; Boston, MA 02114 USA
[14
]ISNI 0000000419368956, GRID grid.168010.e, Department of Genetics, , Stanford University, ; Stanford, CA 94305 USA
[15
]ISNI 0000000419368956, GRID grid.168010.e, Department of Pathology, , Stanford University, ; Stanford, CA 94305 USA
[16
]ISNI 0000 0004 1937 0511, GRID grid.7489.2, Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences,
, BenGurion University of the Negev, ; Beer-Sheva, 84105 Israel
[17
]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Computer Science, , Johns Hopkins University, ; Baltimore, MD 21218 USA
[18
]GRID grid.473715.3, Centre for Genomic Regulation (CRG), , The Barcelona Institute for Science and Technology, ; 08003 Barcelona, Spain
[19
]ISNI 0000 0001 2172 2676, GRID grid.5612.0, Universitat Pompeu Fabra (UPF), ; 08002 Barcelona, Spain
[20
]ISNI 0000 0001 2322 4988, GRID grid.8591.5, Department of Genetic Medicine and Development, , University of Geneva Medical School, ; 1211 Geneva, Switzerland
[21
]ISNI 0000 0001 2322 4988, GRID grid.8591.5, Institute for Genetics and Genomics in Geneva (iG3), , University of Geneva, ; 1211 Geneva, Switzerland
[22
]ISNI 0000 0001 2223 3006, GRID grid.419765.8, Swiss Institute of Bioinformatics, ; 1211 Geneva, Switzerland
[23
]ISNI 0000 0004 1936 8972, GRID grid.25879.31, Department of Genetics, Perelman School of Medicine, , University of Pennsylvania, ; Philadelphia, PA 19104 USA
[25
]ISNI 0000 0001 2285 2675, GRID grid.239585.0, Department of Systems Biology, , Columbia University Medical Center, ; New York, NY 10032 USA
[26
]ISNI 0000 0004 1936 7822, GRID grid.170205.1, Department of Public Health Sciences, , The University of Chicago, ; Chicago, IL 60637 USA
[27
]ISNI 0000 0001 2355 7002, GRID grid.4367.6, McDonnell Genome Institute, , Washington University School of Medicine, ; St. Louis, MO 63108 USA
[28
]ISNI 0000 0001 2355 7002, GRID grid.4367.6, Department of Genetics, , Washington University School of Medicine, ; St. Louis, MO 63108 USA
[29
]ISNI 0000 0001 2355 7002, GRID grid.4367.6, Department of Pathology & Immunology, , Washington University School of Medicine, ; St. Louis, MO 63108 USA
[30
]ISNI 0000 0001 2097 5006, GRID grid.16750.35, Department of Computer Science, Center for Statistics and Machine Learning, , Princeton University, ; Princeton, NJ 08540 USA
[31
]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Department of Computer Science, , University of California, ; Los Angeles, CA 90095 USA
[32
]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Department of Human Genetics, , University of California, ; Los Angeles, CA 90095 USA
[33
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[34
]ISNI 0000 0001 1503 7226, GRID grid.5808.5, Institute of Molecular Pathology and Immunology (IPATIMUP), , University of Porto, ; 4200-625 Porto, Portugal
[35
]ISNI 0000 0004 1936 9916, GRID grid.412807.8, Division of Genetic Medicine, Department of Medicine, , Vanderbilt University Medical Center, ; Nashville, Tennessee 37232 USA
[36
]ISNI 0000000084992262, GRID grid.7177.6, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical
Center, , University of Amsterdam, ; 1105 AZ Amsterdam, The Netherlands
[37
]ISNI 0000000084992262, GRID grid.7177.6, Department of Psychiatry, Academic Medical Center, , University of Amsterdam, ; 1105 AZ Amsterdam, The Netherlands
[38
]ISNI 0000 0001 2097 5006, GRID grid.16750.35, Lewis Sigler Institute, , Princeton University, ; Princeton, NJ 08540 USA
[39
]ISNI 0000 0001 2097 5006, GRID grid.16750.35, Department of Operations Research and Financial Engineering, , Princeton University, ; Princeton, NJ 08540 USA
[40
]ISNI 0000000419368956, GRID grid.168010.e, Biomedical Informatics Program, , Stanford University, ; Stanford, CA 94305 USA
[41
]ISNI 0000 0004 1767 9005, GRID grid.20522.37, Institut Hospital del Mar d’Investigacions Mèdiques (IMIM), ; 08003 Barcelona, Spain
[42
]ISNI 0000 0001 2355 7002, GRID grid.4367.6, Department of Medicine, , Washington University School of Medicine, ; St. Louis, MO 63108 USA
[43
]ISNI 0000 0001 0842 2126, GRID grid.413967.e, Department of Convergence Medicine, , University of Ulsan College of Medicine, Asan Medical Center, ; Seoul, 138-736 South Korea
[44
]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Biomedical Engineering, , Johns Hopkins University, ; Baltimore, MD 21218 USA
[45
]ISNI 0000000419368729, GRID grid.21729.3f, Department of Biostatistics, Mailman School of Public Health, , Columbia University, ; New York, NY 10032 USA
[46
]ISNI 0000000419368956, GRID grid.168010.e, Department of Biology, , Stanford University, ; Stanford, CA 94305 USA
[47
]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, , University of Oxford, ; Oxford, OX3 7BN UK
[48
]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Oxford Centre for Diabetes, Endocrinology and Metabolism, , University of Oxford, Churchill Hospital, ; Oxford, OX3 7LE UK
[49
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[50
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[51
]ISNI 0000 0004 1936 8649, GRID grid.14709.3b, Human Genetics Department, , McGill University, ; Montreal, QC H3A 0G1 Canada
[52
]GRID grid.6835.8, Departament d’Estadística i Investigació Operativa, , Universitat Politècnica de Catalunya, ; 08034 Barcelona, Spain
[53
]ISNI 0000 0001 1034 1720, GRID grid.410711.2, Department of Statistics and Operations Research, , University of North Carolina, ; Chapel Hill, NC 27599 USA
[54
]ISNI 0000 0001 1034 1720, GRID grid.410711.2, Department of Biostatistics, , University of North Carolina, ; Chapel Hill, NC 27599 USA
[55
]ISNI 0000 0004 1936 7822, GRID grid.170205.1, Section of Genetic Medicine, Department of Medicine, , The University of Chicago, ; Chicago, IL 60637 USA
[56
]ISNI 0000 0004 1936 7822, GRID grid.170205.1, Institute for Genomics and Systems Biology, , The University of Chicago, ; Chicago, IL 60637 USA
[57
]ISNI 0000 0001 2291 4776, GRID grid.240145.6, Department of Biostatistics, , The University of Texas MD Anderson Cancer Center, ; Houston, TX 77030 USA
[58
]ISNI 0000 0000 8800 7493, GRID grid.410513.2, Computational Sciences, , Pfizer Inc, ; Cambridge, MA 02139 USA
[60
]ISNI 0000000419368956, GRID grid.168010.e, Department of Biomedical Data Science, , Stanford University, ; Stanford, CA 94305 USA
[61
]ISNI 0000000419368956, GRID grid.168010.e, Department of Statistics, , Stanford University, ; Stanford, CA 94305 USA
[62
]ISNI 0000 0001 2294 473X, GRID grid.8536.8, Institute of Biophysics Carlos Chagas Filho (IBCCF), , Federal University of Rio de Janeiro (UFRJ), ; 21941902 Rio de Janeiro, Brazil
[63
]ISNI 0000 0001 2193 0096, GRID grid.223827.e, Department of Psychiatry, , University of Utah, ; Salt Lake City, UT 84108 USA
[64
]ISNI 0000 0004 1936 7822, GRID grid.170205.1, Department of Statistics, , The University of Chicago, ; Chicago, IL 60637 USA
[65
]ISNI 0000 0004 1936 7822, GRID grid.170205.1, Department of Human Genetics, , The University of Chicago, ; Chicago, IL 60637 USA
[66
]ISNI 0000 0004 1936 7822, GRID grid.170205.1, Center for Data Intensive Science, , The University of Chicago, ; Chicago, IL 60637 USA
[67
]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Department of Psychiatry and Biobehavioral Sciences, , University of California, ; Los Angeles, CA 90095 USA
[68
]ISNI 0000000086837370, GRID grid.214458.e, Department of Biostatistics, , University of Michigan, ; Ann Arbor, MI 48109 USA
[69
]ISNI 0000 0001 2173 6074, GRID grid.40803.3f, Bioinformatics Research Center and Departments of Statistics and Biological Sciences,
, North Carolina State University, ; Raleigh, NC 27695 USA
[70
]ISNI 0000 0004 1937 0511, GRID grid.7489.2, National Institute for Biotechnology in the Negev, ; Beer-Sheva, 84105 Israel
[71
]ISNI 0000 0004 0495 846X, GRID grid.4709.a, European Molecular Biology Laboratory, ; 69117 Heidelberg, Germany
[72
]ISNI 0000 0001 2097 5006, GRID grid.16750.35, Department of Ecology and Evolutionary Biology, , Princeton University, ; Princeton, NJ 08540 USA
[74
]ISNI 000000041936754X, GRID grid.38142.3c, Beth Israel Deaconess Medical Center, , Harvard Medical School, ; Boston, MA 02215 USA
[75
]ISNI 0000 0001 2290 1502, GRID grid.9464.f, University of Hohenheim, ; 70599 Stuttgart, Germany
[76
]ISNI 0000 0001 2193 0096, GRID grid.223827.e, Huntsman Cancer Institute, Department of Population Health Sciences, , University of Utah, ; Salt Lake City, UT 84112 USA
[77
]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Center for Epigenetics, , Johns Hopkins University School of Medicine, ; Baltimore, MD 21205 USA
[78
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[79
]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Mental Health, , Johns Hopkins University School of Public Health, ; Baltimore, MD 21205 USA
[80
]ISNI 0000 0001 2171 9311, GRID grid.21107.35, McKusick-Nathans Institute of Genetic Medicine, , Johns Hopkins School of Medicine, ; Baltimore, MD 21205 USA
[81
]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Biostatistics, , Johns Hopkins University, ; Baltimore, MD 21205 USA
[82
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[83
]ISNI 0000000122986657, GRID grid.34477.33, Department of Medicine, , University of Washington, Seattle, ; Washington, 98195 USA
[84
]ISNI 0000000122986657, GRID grid.34477.33, Division of Cardiology, , University of Washington, Seattle, ; Washington, 98195 USA
[85
]ISNI 0000 0001 2109 4251, GRID grid.240324.3, Institute for Systems Genetics, , New York University Langone Medical Center, ; New York, NY 10016 USA
[86
]ISNI 0000000122986657, GRID grid.34477.33, Department of Genome Sciences, , University of Washington, ; Seattle, WA 98195 USA
[87
]GRID grid.453125.4, Office of Strategic Coordination, Division of Program Coordination, Planning and Strategic
Initiatives, , Office of the Director, NIH, ; Rockville, MD 20852 USA
[88
]ISNI 0000 0004 1936 8075, GRID grid.48336.3a, Biorepositories and Biospecimen Research Branch, Division of Cancer Treatment and
Diagnosis, , National Cancer Institute, ; Bethesda, MD 20892 USA
[89
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[90
]ISNI 0000 0001 2233 9230, GRID grid.280128.1, Division of Genomic Medicine, , National Human Genome Research Institute, ; Rockville, MD 20852 USA
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[104
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[107
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Author information
Alvaro N. Barbeira
http://orcid.org/0000-0002-9153-6120
Heather E. Wheeler
http://orcid.org/0000-0001-6955-6021
Todd L. Edwards
http://orcid.org/0000-0003-4318-6119
Hae Kyung Im
http://orcid.org/0000-0003-0333-5685
Article
Publisher ID: 3621DOI: 10.1038/s41467-018-03621-1
PMC ID: 5940825
PubMed ID: 29739930
SO-VID: 3167b745-e5ee-4455-8daf-f8440818badc
Copyright © © The Author(s) 2018
License:
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
History
Date
received
: 22
June
2017
Date
accepted
: 27
December
2017
Categories
Subject:
Article
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