All polymorphisms studied in this paper [PMID: 17554300] , total : 11 polymorphisms

Title : Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls.

Abstract : There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined approximately 2,000 individuals for each of 7 major diseases and a shared set of approximately 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 x 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals (including 58 loci with single-point P values between 10(-5) and 5 x 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.

Author :

Source : Nature. 2007 Jun 7;447(7145):661-78.

No.	Polymorphism name	Gene Symbol	Entrez Gene ID
1	rs6679677	PHTF1	10745
2	rs6457617	NA	NA
3	rs6684865	MMEL1	79258
4	rs11162922	NA	NA
5	rs3816587	ANAPC4	29945
6	rs6920220	NA	NA
7	rs11761231	NA	NA
8	rs2104286	IL2RA	3559
9	rs9550642	NA	NA
10	rs2837960	NA	NA
11	rs743777	NA	NA