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Statistical false positive or true disease pathway?

John A Todd1

  • 1University of Cambridge, Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, Addenbrooke's Hospital Cambridge, Cambridgeshire CB2 2XY, UK. john.todd@cimr.cam.ac.uk

Nature Genetics
|June 29, 2006
PubMed
Summary
This summary is machine-generated.

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Recent genome-wide studies reveal strong statistical evidence linking common genetic variations to systemic lupus erythematosus, prostate cancer, and type 1 diabetes. This marks a significant shift towards reproducible genetic findings in common diseases.

Area of Science:

  • Genetics
  • Genomics
  • Disease Association Studies

Background:

  • Historically, genetic association studies have faced challenges with reproducibility.
  • Recent advancements have led to a surge in reliable findings.

Purpose of the Study:

  • To highlight recent, statistically robust evidence for common genetic polymorphisms associated with common diseases.
  • To discuss the implications of these findings in the context of past research challenges.

Main Methods:

  • Genome-wide association studies (GWAS) were employed.
  • Rigorous statistical analysis with genome-wide significance thresholds (P < 10(-8)) was applied.

Main Results:

  • Convincing evidence links specific polymorphisms to systemic lupus erythematosus (IRF5), prostate cancer, and type 1 diabetes (IFIH1 region).

Related Experiment Videos

  • Additional recent associations include age-related macular degeneration (CFH), type 1 diabetes (IL2RA/CD25), and type 2 diabetes (TCF7L2).

    • Conclusions:

    • The current wave of disease association results is highly unlikely to be false positives.
    • This indicates a significant improvement in the reliability and reproducibility of genetic association studies for common diseases.