Even with the proliferation of new genetic associations discovered in the past few years by GWA studies, only around 10 to 15% of the inherited risk for SLE and RA can be currently explained. This may be accounted for, in part, by a number of factors, some related to limitations of recent study design. As mentioned above, even the largest current GWA cohorts have limited power to detect associations with ORs < 1.3, potentially losing multiple risk genes. By definition, most genotyped SNPs are common, and so rare but causal variants have a tendency to be missed. These rarer SNPs may be either those with a low minor allele frequency (< 5%), or occur de novo, of which 200 to 500 non-synonymous SNPs are expected per individual. In many cases, it is far from certain if the associated SNP is functional, or in linkage disequilibrium with the true cause. Finally, the great majority of GWA studies have been conducted on European populations, thereby excluding carriers of many potential risk variants from analysis. However, it is unfortunately the case that current genotyping platforms often have poor coverage of tagging SNPs within populations that exhibit low levels of genomic linkage disequilibrium, such as those of African ancestry. For example, the latest high-density genotyping chips from Affymetrix (6.0) and Illumina (1 M) may capture fewer than half the SNPs identified through re-sequencing in Yoruban Nigerians. Given that clear differences exist in the risk of autoimmune disease according to ethnicity, and that not all disease risk alleles are in common, it is imperative that full account of this variation is made. Structural genetic differences have only recently begun to be assessed by modern genotyping platforms, and the contribution of, for example, CNV to inherited disease risk is largely unquantified. Even more difficult to appreciate is the influence of heritable epigenetic factors, and the exact relationship between genotype and phenotype. Nevertheless, although it will probably not be possible to explain all the observed genetic risk in the near future, we are rapidly moving towards the ability to quickly and cheaply fully sequence individual genomes, with all the advantages that brings. In the meantime, understanding the functional basis of the disease risk variants so far identified presents an outstanding challenge. Integration of genotypic with RNA and protein expression data in a systems biologic approach represents one potentially valuable methodology. Exploring and therapeutically utilizing the genetic differences between individuals is axiomatic to personalized medicine, and will undoubtedly lead to better outcomes in the management of autoimmune disease.
AS: ankylosing spondylitis; BCR: B cell receptor; CNV: copy number variation; GWA: genome-wide association; HLA: human leukocyte antigen; IFN: interferon; IL: interleukin; IRF: interferon regulatory factor; MHC: major histocompatibility complex; NF: nuclear factor; OR: odds ratio; RA: rheumatoid arthritis; SLE: systemic lupus erythematosus; SNP: single nucleotide polymorphism; STAT: signal transducer and activation of transcription factor; TLR: toll-like receptor; TNF: tumour necrosis factor; TNFAIP: TNFα-induced protein-3; TRAF: TNF receptor associated factor; WTCCC: Wellcome Trust Case Control Consortium.
The authors declare that they have no competing interests.
Arthritis Res Ther. 2009;11(5):248 © 2009 BioMed Central, Ltd.
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Cite this: Genetics of Rheumatic Disease - Medscape - Oct 14, 2009.