iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: http://www.ncbi.nlm.nih.gov/pubmed/20659789
Common variants conferring risk of schizophrenia: a pathway analysis of GWAS data - PubMed Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2010 Sep;122(1-3):38-42.
doi: 10.1016/j.schres.2010.07.001. Epub 2010 Jul 24.

Common variants conferring risk of schizophrenia: a pathway analysis of GWAS data

Peilin Jia  1 , Lily Wang, Herbert Y Meltzer, Zhongming Zhao
Affiliations

Common variants conferring risk of schizophrenia: a pathway analysis of GWAS data

Peilin Jia et al. Schizophr Res. 2010 Sep.

Abstract

Unlike the typical analysis of single markers in genome-wide association studies (GWAS), we incorporated Gene Set Enrichment Analysis (GSEA) and hypergeometric test and combined them using Fisher's combined method to perform pathway-based analysis in order to detect genes' combined effects on mediating schizophrenia. A few pathways were consistently found to be top ranked and likely associated with schizophrenia by these methods; they are related to metabolism of glutamate, the process of apoptosis, inflammation, and immune system (e.g., glutamate metabolism pathway, TGF-beta signaling pathway, and TNFR1 pathway). The genes involved in these pathways had not been detected by single marker analysis, suggesting this approach may complement the original analysis of GWAS dataset.

PubMed Disclaimer

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Beattie EC, Stellwagen D, Morishita W, Bresnahan JC, Ha BK, Von Zastrow M, Beattie MS, Malenka RC. Control of synaptic strength by glial TNFalpha. Science. 2002;295:2282–2285. - PubMed
    1. Benjamini Y, Hochberg Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Stat. Methodol. 1995;57:289–300.
    1. Dinu I, Potter JD, Mueller T, Liu Q, Adewale AJ, Jhangri GS, Einecke G, Famulski KS, Halloran P, Yasui Y. Improving gene set analysis of microarray data by SAM-GS. BMC Bioinformatics. 2007;8:242. - PMC - PubMed
    1. Efron B, Tibshirani R. On testing the significance of sets of genes. Ann. Appl. Stat. 2007;1:107–129.
    1. Fisher RA. Statistical methods for research workers. London: Oliver and Boyd; 1932.

Publication types

MeSH terms