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PMID: 20463879 Published · epublish English Journal Article Research Support, Non-U.S. Gov't

Liver and adipose expression associated SNPs are enriched for association to type 2 diabetes.

PLoS genetics ·Vol. 6 ·No. 5 ·2010-05-06 ·Pages e1000932

Zhong H, Beaulaurier J, Lum PY, Molony C, Yang X, Macneil DJ, Weingarth DT, Zhang B, Greenawalt D, Dobrin R, Hao K, Woo S, Fabre-Suver C, Qian S, Tota MR, Keller MP, Kendziorski CM, Yandell BS, Castro V, Attie AD, Kaplan LM, Schadt EE

Abstract

Genome-wide association studies (GWAS) have demonstrated the ability to identify the strongest causal common variants in complex human diseases. However, to date, the massive data generated from GWAS have not been maximally explored to identify true associations that fail to meet the stringent level of association required to achieve genome-wide significance. Genetics of gene expression (GGE) studies have shown promise towards identifying DNA variations associated with disease and providing a path to functionally characterize findings from GWAS. Here, we present the first empiric study to systematically characterize the set of single nucleotide polymorphisms associated with expression (eSNPs) in liver, subcutaneous fat, and omental fat tissues, demonstrating these eSNPs are significantly more enriched for SNPs that associate with type 2 diabetes (T2D) in three large-scale GWAS than a matched set of randomly selected SNPs. This enrichment for T2D association increases as we restrict to eSNPs that correspond to genes comprising gene networks constructed from adipose gene expression data isolated from a mouse population segregating a T2D phenotype. Finally, by restricting to eSNPs corresponding to genes comprising an adipose subnetwork strongly predicted as causal for T2D, we dramatically increased the enrichment for SNPs associated with T2D and were able to identify a functionally related set of diabetes susceptibility genes. We identified and validated malic enzyme 1 (Me1) as a key regulator of this T2D subnetwork in mouse and provided support for the association of this gene to T2D in humans. This integration of eSNPs and networks provides a novel approach to identify disease susceptibility networks rather than the single SNPs or genes traditionally identified through GWAS, thereby extracting additional value from the wealth of data currently being generated by GWAS.

MeSH Terms
Adipose Tissue/metabolism Animals Cohort Studies DNA-Binding Proteins/genetics,metabolism Diabetes Mellitus, Type 2/genetics,metabolism Female Gene Expression Genome-Wide Association Study Humans Liver/metabolism Male Mice Mice, Inbred C57BL Mice, Knockout Mice, Obese Polymorphism, Single Nucleotide Transcription Factors/genetics,metabolism
Chemicals
DNA-Binding Proteins PRDM16 protein, human Prdm16 protein, mouse Transcription Factors
Authors & Affiliations
22 authors, click to expand affiliations / ORCID
Zhong Hua
Department of Genetics, Rosetta Inpharmatics, Seattle, Washington, United States of America.
Beaulaurier John
Lum Pek Yee
Molony Cliona
Yang Xia
Macneil Douglas J
Weingarth Drew T
Zhang Bin
Greenawalt Danielle
Dobrin Radu
Hao Ke
Woo Sangsoon
Fabre-Suver Christine
Qian Su
Tota Michael R
Keller Mark P
Kendziorski Christina M
Yandell Brian S
Castro Victor
Attie Alan D
Kaplan Lee M
Schadt Eric E
Conflict of Interest

The senior author (EES) is the Chief Scientific Officer of Pacific Biosciences and owns stock in that company. A number of the other authors were employees of Merck when the work presented in this manuscript was carried out.

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Article Info
Journal
PLoS genetics
Abbr.
PLoS Genet
ISSN
1553-7404
DOI
10.1371/journal.pgen.1000932
Published
2010-05-06
Epub
2010-00-06
Pages
e1000932
Language
English
Region
United States
NLM ID
101239074
PMCID
PMC2865508
Subset
IM
Grants
NIDDK NIH HHS · R01 DK066369 · United States
Databases
GEO
GSE9588
External Links
PubMed source DOI: 10.1371/journal.pgen.1000932 PMC Full Text View journal details
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