Identifying relationships among genomic disease regions

Predicting genes at pathogenic SNP associations and rare deletions

The International Schizophrenia Consortium (ISC)

Research output: Contribution to journalArticle

317 Citations (Scopus)

Abstract

Translating a set of disease regions into insight about pathogenic mechanisms requires not only the ability to identify the key disease genes within them, but also the biological relationships among those key genes. Here we describe a statistical method, Gene Relationships Among Implicated Loci (GRAIL), that takes a list of disease regions and automatically assesses the degree of relatedness of implicated genes using 250,000 PubMed abstracts. We first evaluated GRAIL by assessing its ability to identify subsets of highly related genes in common pathways from validated lipid and height SNP associations from recent genome-wide studies. We then tested GRAIL, by assessing its ability to separate true disease regions from many false positive disease regions in two separate practical applications in human genetics. First, we took 74 nominally associated Crohn's disease SNPs and applied GRAIL to identify a subset of 13 SNPs with highly related genes. Of these, ten convincingly validated in follow-up genotyping; genotyping results for the remaining three were inconclusive. Next, we applied GRAIL to 165 rare deletion events seen in schizophrenia cases (less than one-third of which are contributing to disease risk). We demonstrate that GRAIL is able to identify a subset of 16 deletions containing highly related genes; many of these genes are expressed in the central nervous system and play a role in neuronal synapses. GRAIL offers a statistically robust approach to identifying functionally related genes from across multiple disease regions-that likely represent key disease pathways. An online version of this method is available for public use (http://www.broad.mit. edu/mpg/grail/).

Original languageEnglish
Article numbere1000534
JournalPLoS Genetics
Volume5
Issue number6
DOIs
Publication statusPublished - 26 Jun 2009

Fingerprint

Single Nucleotide Polymorphism
genomics
gene
Genes
genes
loci
Aptitude
genotyping
Crohn disease
Genome-Wide Association Study
Medical Genetics
synapse
nervous system
relatedness
PubMed
Crohn Disease
Synapses
central nervous system
Schizophrenia
statistical analysis

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics
  • Genetics(clinical)
  • Cancer Research

Cite this

Identifying relationships among genomic disease regions : Predicting genes at pathogenic SNP associations and rare deletions. / The International Schizophrenia Consortium (ISC).

In: PLoS Genetics, Vol. 5, No. 6, e1000534, 26.06.2009.

Research output: Contribution to journalArticle

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abstract = "Translating a set of disease regions into insight about pathogenic mechanisms requires not only the ability to identify the key disease genes within them, but also the biological relationships among those key genes. Here we describe a statistical method, Gene Relationships Among Implicated Loci (GRAIL), that takes a list of disease regions and automatically assesses the degree of relatedness of implicated genes using 250,000 PubMed abstracts. We first evaluated GRAIL by assessing its ability to identify subsets of highly related genes in common pathways from validated lipid and height SNP associations from recent genome-wide studies. We then tested GRAIL, by assessing its ability to separate true disease regions from many false positive disease regions in two separate practical applications in human genetics. First, we took 74 nominally associated Crohn's disease SNPs and applied GRAIL to identify a subset of 13 SNPs with highly related genes. Of these, ten convincingly validated in follow-up genotyping; genotyping results for the remaining three were inconclusive. Next, we applied GRAIL to 165 rare deletion events seen in schizophrenia cases (less than one-third of which are contributing to disease risk). We demonstrate that GRAIL is able to identify a subset of 16 deletions containing highly related genes; many of these genes are expressed in the central nervous system and play a role in neuronal synapses. GRAIL offers a statistically robust approach to identifying functionally related genes from across multiple disease regions-that likely represent key disease pathways. An online version of this method is available for public use (http://www.broad.mit. edu/mpg/grail/).",
author = "Soumya Raychaudhuri and Plenge, {Robert M.} and Rossin, {Elizabeth J.} and Ng, {Aylwin C.Y.} and Purcell, {Shaun M.} and Pamela Sklar and Scolnick, {Edward M.} and Xavier, {Ramnik J.} and David Altshuler and Daly, {Mark J.} and Kristen Ardlie and Azevedo, {M. Helena} and Nicholas Bass and Blackwood, {Douglas H.R.} and Celia Carvalho and Kimberly Chambert and Khalid Choudhury and David Conti and Aiden Corvin and Craddock, {Nick J.} and Caroline Crombie and David Curtis and Susmita Datta and Gabrie, {Stacey B.} and Casey Gates and Lucy Georgieva and Michael Gill and Hugh Gurling and Holmans, {Peter A.} and Hultman, {Christina M.} and Ayman Fanous and Gillian Fraser and Elaine Kenny and Kirov, {George K.} and Knowles, {James A.} and Robert Krasucki and Joshua Korn and Soh, {Leh Kwan} and Jacob Lawrence and Paul Lichtenstein and Antonio Macedo and Stuart Macgregor and Maclean, {Alan W.} and Scott Mahon and Pat Malloy and McGhee, {Kevin A.} and Andrew McQuillin and Helena Medeiros and Frank Middleton and {St. Clair}, David and {The International Schizophrenia Consortium (ISC)}",
note = "We would like to thank Drs. Eric Lander, Russ Altman , Chris Cotsapas, Joerg Ermann, Elizabeth W. Karlson, Kasper Lage, Guillaume Lettre, Roland Nilsson, and Ayellet Segre for insightful feedback and comments. We also thank Jesse Ross for assistance in constructing the web server.",
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AU - Plenge, Robert M.

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AU - Ng, Aylwin C.Y.

AU - Purcell, Shaun M.

AU - Sklar, Pamela

AU - Scolnick, Edward M.

AU - Xavier, Ramnik J.

AU - Altshuler, David

AU - Daly, Mark J.

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AU - Bass, Nicholas

AU - Blackwood, Douglas H.R.

AU - Carvalho, Celia

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AU - Choudhury, Khalid

AU - Conti, David

AU - Corvin, Aiden

AU - Craddock, Nick J.

AU - Crombie, Caroline

AU - Curtis, David

AU - Datta, Susmita

AU - Gabrie, Stacey B.

AU - Gates, Casey

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AU - Gurling, Hugh

AU - Holmans, Peter A.

AU - Hultman, Christina M.

AU - Fanous, Ayman

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AU - Kenny, Elaine

AU - Kirov, George K.

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AU - Korn, Joshua

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AU - Lawrence, Jacob

AU - Lichtenstein, Paul

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AU - Maclean, Alan W.

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AU - Malloy, Pat

AU - McGhee, Kevin A.

AU - McQuillin, Andrew

AU - Medeiros, Helena

AU - Middleton, Frank

AU - St. Clair, David

AU - The International Schizophrenia Consortium (ISC)

N1 - We would like to thank Drs. Eric Lander, Russ Altman , Chris Cotsapas, Joerg Ermann, Elizabeth W. Karlson, Kasper Lage, Guillaume Lettre, Roland Nilsson, and Ayellet Segre for insightful feedback and comments. We also thank Jesse Ross for assistance in constructing the web server.

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N2 - Translating a set of disease regions into insight about pathogenic mechanisms requires not only the ability to identify the key disease genes within them, but also the biological relationships among those key genes. Here we describe a statistical method, Gene Relationships Among Implicated Loci (GRAIL), that takes a list of disease regions and automatically assesses the degree of relatedness of implicated genes using 250,000 PubMed abstracts. We first evaluated GRAIL by assessing its ability to identify subsets of highly related genes in common pathways from validated lipid and height SNP associations from recent genome-wide studies. We then tested GRAIL, by assessing its ability to separate true disease regions from many false positive disease regions in two separate practical applications in human genetics. First, we took 74 nominally associated Crohn's disease SNPs and applied GRAIL to identify a subset of 13 SNPs with highly related genes. Of these, ten convincingly validated in follow-up genotyping; genotyping results for the remaining three were inconclusive. Next, we applied GRAIL to 165 rare deletion events seen in schizophrenia cases (less than one-third of which are contributing to disease risk). We demonstrate that GRAIL is able to identify a subset of 16 deletions containing highly related genes; many of these genes are expressed in the central nervous system and play a role in neuronal synapses. GRAIL offers a statistically robust approach to identifying functionally related genes from across multiple disease regions-that likely represent key disease pathways. An online version of this method is available for public use (http://www.broad.mit. edu/mpg/grail/).

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