• Georgios D Kitsios and Elias Zintzaras.
• Institute for Clinical Research and Health Policy Studies, Department of Medicine, Tufts Medical Center, Boston, MA, USA; Department of Biomathematics, University of Thessaly School of Medicine, Larissa, Greece. GKitsios@tuftsmedicalcenter.org
• Transl Res. 2009 Oct 1; 154 (4): 161-4.

AbstractThe advent of the first wave of genome-wide association studies (GWAS) provided a new conceptual framework in the search for variants underlying common disorders: a massive scan of the genome, free from underlying assumptions for biological or positional candidate loci, genes, and variants. Thus, GWAS have been labeled as a "hypothesis-free" or "agnostic" approach, overcoming the obstacles imposed by the incomplete understanding of disease pathophysiology. Despite undisputable successes of the genome-wide approach, the available output from GWAS explains only a fraction of disease heritability. Although strategies for tuning up the design and conduct of these studies have been proposed, it is probably under-appreciated that GWAS are dependent on underlying assumptions, which account for important limitations of the so-called "hypothesis-free" studies. Dictated by the design of genotyping platforms or the analysis methodologies, the implicit hypotheses of GWAS and their related implications for future research are summarized in this commentary. Since the result of any biological experiment is primarily determined by the extent to which the hypotheses tested truly hold, unless the presumptions of GWAS are acknowledged and complementary genetic analysis methods are implemented, the full advantage of genomic scans of human variation will not be realized.

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