ABSTRACT
High-throughput human genome sequencing has allowed genome-wide association studies (GWAS) to identify multiple genes and genetic variants involved in traits and diseases pathogenesis. However, these associations between genetic variants –mostly SNPs- and phenotype can explain only about 20-25% of traits or diseases. In addition, in all these studies have revealed common variants with very small effects and disease risk contribution that has no clinical implication. How could this missing heritability be explained? Small number of SNPs (<1 million), other than SNPs variants such as copy-number-variants (CNVs) not evaluated and small sample sizes not allow identification of rare mutations may explain the failure of these GWAS. For example, rare CNVs have most recently identified in a GWAS that showed that VIPR2 duplications are involved in schizophrenia and may have significant implications for the development of molecular diagnostics and treatments for this disorder. Here, I discuss the challenges and perspectives of the next-generation GWAS to provide molecular and genetic tools with clinical utility in diseases risk prediction and treatment.

(Citation: Gastric & Breast Cancer 2011; 10(2): 85-90)

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