Selecting SNPs for association studies based on population frequencies: A novel interactive tool and its application to polygenic diseases

Steffen Möller, Dirk Koczan, Pablo Serrano-Fernandez, Uwe K. Zettl, Jans Jürgen Thiesen, Saleh M. Ibrahim

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Common complex polygenic diseases as autoimmune diseases have not been completely understood on a molecular level. While many genes are known to be involved in the pathways responsible for the phenotype, explicit causes for the susceptibility of the disease remain to be elucidated. The susceptibility to disease is thought to be the result of genetic epistatic interactions between common polymorphic genes. This polymorphism is mostly caused by single nucleotide polymorphisms (SNPs). Human subpopulations are known to differ in the susceptibility to the diseases and generally in the distribution of single nucleotide polymorphisms. The here presented approach retrieves SNPs with the most divergent frequencies for selected human subpopulations to help defining properties for the experimental verification of SNPs within defined regions. A web-accessible program implementing this approach was evaluated for multiple sclerosis (MS), a common human polygenic disease. A link to a summary of data from "The SNP Consortium" (TSC) with sex-dependencies of SNPs is available. Associations of SNPs to genes, genetic markers and chromosomal loci are retrieved from the Ensembl project. This tool is recommended to be used in conjunction with microarray analyses or marker association studies that link genes or chromosomal loci to particular diseases.

Original languageBritish English
Pages (from-to)417-427
Number of pages11
JournalIn Silico Biology
Volume4
Issue number4
StatePublished - 2004

Keywords

  • Association studies
  • Ensembl
  • Multiple sclerosis
  • SNP selection by population frequencies

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