Primer: comparative genetics of animal models of arthritis--a tool to resolve complexity.

Research output: Contribution to journalReview article


Complex traits, including inflammatory rheumatic diseases, have important genetic features, but most of the responsible genes have not been conclusively identified. Genetic analysis of inbred animal models and comparative genetics - the comparison of genes between different species - might help to identify the crucial genes and to investigate more directly the biology involved. Genome-wide linkage analysis of particular genes can be assessed by genetic segregation studies, whereas disease pathways can be delineated by the use of congenic strains. To clone disease genes, the traits need to be transformed so that they are inherited in a more Mendelian manner: achieving this pattern requires isolation of the locus on a genetic background that allows high penetrance by minimization of the size of congenic fragments, genetic manipulations without associated artifacts, or identification of highly penetrant mutations by phenotypic selection. Although almost one hundred quantitative trait loci for arthritis have been identified, only a few genes have so far been positionally cloned. In this Review we highlight the possibilities of using animal models to identify genes associated with complex diseases like arthritis, illustrated with available findings for genes such as those encoding major histocompatibility complex class II, neutrophil cytosolic factor 1 (Ncf1/p47(phox)) and ZAP70.


  • Rikard Holmdahl
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Immunology in the medical area


  • disease, polygenic, autoimmunity, experimental animal models, major histocompatibility complex, linkage analysis
Original languageEnglish
Pages (from-to)104-111
JournalNature Clinical Practice Rheumatology
Issue number2
Publication statusPublished - 2007
Publication categoryResearch

Bibliographic note

The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Medical Inflammation Research (013212019)