Gene prioritization based on biological plausibility over genome wide association studies renders new loci associated with type 2 diabetes

Purpose: We present an approach to prioritize single nucleotide polymorphisms for further follow-up in genome-wide association studies of type 2 diabetes. Method: The proposed method combines both the use of open data access from two type 2 diabetes-genome-wide association. P studies (granted by the Diabetes Genetics Initiative and the Welcome Trust Case Control Consortium) and the comprehensive analysis of candidate regions generated by the freely accessible ENDEAVOUR software. Results: The algorithm prioritized all genes of the whole genome in relation to type 2 diabetes. There were six of 1096 single nucleotide polymorphisms in five genes potentially associated with type 2 diabetes: tachykinin receptor 3 (rs1384401), anaplastic lymphoma receptor tyrosine kinase (rs4319896), calcium channel, voltage-dependent, L type, alpha ID subunit (rs12487452), FOXO1A (rs10507486 and rs7323267), and v-akt murine thymoma viral oncogene homolog 3 (rs897959). We estimated the fixed effect and P values of each single nucleotide polymorphism in the combined dataset by Mantel-Haenszel meta-analysis and we observed significant P values for all single nucleotide polymorphisms except for rs897959 at v-akt murine thymoma viral oncogene homolog 3. Conclusion: The proposed strategy may be used as an alternative toot for optimizing the information of the nearly 500,000 gene variants in which markers with modest significant P value for disease association are currently disregarded. Additionally, the said single nucleotide polymorphisms may be incorporated into the replication of the multistage design involved in the genome-wide association studies. Genet Med 2009:11(5):338-343.