Derived SNP alleles are used more frequently than ancestral alleles as risk-associated variants in common human diseases

Olga Y. Gorlova, Jun Ying, Christopher I. Amos, Margaret R. Spitz, Bo Peng, Ivan P. Gorlov

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Evolutionary aspects of the genetic architecture of common human diseases remain enigmatic. The results of more than 200 genome-wide association studies published to date were compiled in a catalog (http://www.genome.gov/26525384/). We used cataloged data to determine whether derived (mutant) alleles are associated with higher risk of human disease more frequently than ancestral alleles. We placed all allelic variants into ten categories of population frequency (0%-100%) in 10% increments. We then analyzed the relationship between allelic frequency, evolutionary status of the polymorphic site (ancestral versus derived), and disease risk status (risk versus protection). Given the same population frequency, derived alleles are more likely to be risk associated than ancestral alleles, as are rarer alleles. The common interpretation of this association is that negative selection prevents fixation of the risk variants. However, disease stratification as early or late onset suggests that weak selection against risk-associated alleles is unlikely a major factor shaping genetic architecture of common diseases. Our results clearly suggest that the duration of existence of an allele in a population is more important. Alleles existing longer tend to show weaker linkage disequilibrium with neighboring alleles, including the causal alleles, and are less likely to tag a SNP-disease association.

Original languageEnglish (US)
Article number1241008
JournalJournal of bioinformatics and computational biology
Volume10
Issue number2
DOIs
StatePublished - Apr 2012

Keywords

  • Genome-wide association studies
  • ancestral allele
  • derived allele
  • minor allele frequency

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications

MD Anderson CCSG core facilities

  • Bioinformatics Shared Resource

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