Genome-wide association studies: hypothesis-"free" or "engaged"?

Area of Science:

• Genetics
• Genomics
• Human Variation

Background:

• Genome-wide association studies (GWAS) revolutionized common disease research by enabling hypothesis-free genomic scans.
• Despite successes, GWAS explain only a fraction of disease heritability, suggesting inherent limitations.
• The

Purpose of the Study:

• To summarize the implicit hypotheses underlying genome-wide association studies (GWAS).
• To discuss the limitations imposed by these assumptions on the interpretation of GWAS results.
• To highlight the implications for future genetic research strategies.

Main Methods:

• Review and commentary on the inherent assumptions in GWAS design and analysis.
• Analysis of how genotyping platforms and statistical methodologies introduce implicit hypotheses.
• Discussion of the consequences of these assumptions for interpreting genetic findings.

Main Results:

• GWAS, while appearing hypothesis-free, are guided by implicit assumptions embedded in their design and analytical methods.
• These underlying assumptions, often dictated by technology and methodology, limit the scope and interpretation of findings.
• Failure to acknowledge these presumptions can lead to an incomplete understanding of disease heritability.

Conclusions:

• The effectiveness of GWAS is constrained by unacknowledged, implicit hypotheses.
• Recognizing and addressing these assumptions is crucial for advancing genomic research.
• Complementary genetic analysis methods are necessary to fully leverage genomic scans of human variation.