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PLoS Genet DOI:10.1371/journal.pgen.1000534

Identifying relationships among genomic disease regions: predicting genes at pathogenic SNP associations and rare deletions.

Publication TypeJournal Article
Year of Publication2009
AuthorsRaychaudhuri, S, Plenge, RM, Rossin, EJ, C Y Ng, A, Purcell, SM, Sklar, P, Scolnick, EM, Xavier, RJ, Altshuler, D, Daly, MJ
Corporate AuthorsInternational Schizophrenia Consortium
JournalPLoS Genet
Volume5
Issue6
Pagese1000534
Date Published2009 Jun
ISSN1553-7404
KeywordsCrohn Disease, Databases, Genetic, Gene Deletion, Genome, Human, Genome-Wide Association Study, Genomics, Humans, Meta-Analysis as Topic, Polymorphism, Single Nucleotide, Schizophrenia
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/).

URLhttp://dx.plos.org/10.1371/journal.pgen.1000534
DOI10.1371/journal.pgen.1000534
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/19557189?dopt=Abstract

Alternate JournalPLoS Genet.
PubMed ID19557189
PubMed Central IDPMC2694358
Grant ListP30 DK040561 / DK / NIDDK NIH HHS / United States
U01 HG004171 / HG / NHGRI NIH HHS / United States
K08 AR055688-01A1 / AR / NIAMS NIH HHS / United States
1K08AR055688-01A1 / AR / NIAMS NIH HHS / United States
T32 GM007753 / GM / NIGMS NIH HHS / United States
T32 AR007530 / AR / NIAMS NIH HHS / United States
P30 DK040561-14 / DK / NIDDK NIH HHS / United States
R01 DK083759 / DK / NIDDK NIH HHS / United States
U01HG004171 / HG / NHGRI NIH HHS / United States
T32AR007530-23 / AR / NIAMS NIH HHS / United States
K08 AR055688 / AR / NIAMS NIH HHS / United States