Genetic epidemiology: Approaches to the genetic analysis of rheumatoid arthritis

The basis of susceptibility to rheumatoid arthritis (RA) is complex, comprising genetic and environmental susceptibility factors. We have reviewed the available approaches to the investigation of the genetic basis of complex diseases and how these are being applied to RA. Affected-sibling-pair methods for nonparametric linkage analysis, linkage-disequilibrium-based approaches, transmission disequilibrium testing, and disease-association studies are discussed. The pros, cons, and limitations of the approaches are considered and are illustrated by examples from the literature about rheumatoid arthritis

Commentary on "Genetic linkage and transmission disequilibrium of marker haplotypes at chromosome 1q41 in human systemic lupus erythematosus", by RR Graham et al.

Genome-wide linkage analysis studies in families with systemic lupus erythematosus (SLE) have revealed consistent evidence of linkage to several regions of the genome. In a previous issue of this journal, Graham and colleagues described their approach to following up the linkage data for one of these regions, 1q41–42. Using methods based on the transmission disequilibrium test, the region likely to harbour a SLE disease gene was refined to 2.3 Mb. This commentary discusses their approach and identifies lessons that may be applicable to the investigation of other complex diseases

Genetic epidemiology: Systemic sclerosis

Systemic sclerosis (SSc) is a multisystem connective tissue disease characterised phenotypically by fibrosis and ischaemic atrophy. Its aetiology is most likely multifactorial. A genetic predisposition to the condition is suggested by reports of familial SSc (a positive family history is the strongest risk factor yet identified), by animal models, and by disease-association studies, in which researchers have examined a wide variety of genes including those involved in fibrosis, in vascular function and structure, and in autoimmunity – the relative rarity of SSc has precluded linkage studies, except in the Choctaw Indians. Recent advances in genetic methodologies should further our understanding of this complex disease process

Characterisation of the genomic architecture of human chromosome 17q and evaluation of different methods for haplotype block definition

BACKGROUND: The selection of markers in association studies can be informed through the use of haplotype blocks. Recent reports have determined the genomic architecture of chromosomal segments through different haplotype block definitions based on linkage disequilibrium (LD) measures or haplotype diversity criteria. The relative applicability of distinct block definitions to association studies, however, remains unclear. We compared different block definitions in 6.1 Mb of chromosome 17q in 189 unrelated healthy individuals. Using 137 single nucleotide polymorphisms (SNPs), at a median spacing of 15.5 kb, we constructed haplotype block maps using published methods and additional methods we have developed. Haplotype tagging SNPs (htSNPs) were identified for each map. RESULTS: Blocks were found to be shorter and coverage of the region limited with methods based on LD measures, compared to the method based on haplotype diversity. Although the distribution of blocks was highly variable, the number of SNPs that needed to be typed in order to capture the maximum number of haplotypes was consistent. CONCLUSION: For the marker spacing used in this study, choice of block definition is not important when used as an initial screen of the region to identify htSNPs. However, choice of block definition has consequences for the downstream interpretation of association study results

Fine mapping of genes within the IDDM8 region in rheumatoid arthritis

The IDDM8 region on chromosome 6q27, first identified as a susceptibility locus for type 1 diabetes, has previously been linked and associated with rheumatoid arthritis (RA). The region contains a number of potential candidate genes, including programmed cell death 2 (PDCD2), the proteosome subunit beta type 1 (PSMB1), delta-like ligand 1 (DLL-1) and TATA box-binding protein (TBP) amongst others. The aim of this study was to fine map the IDDM8 region on chromosome 6q27, focusing on the genes in the region, to identify polymorphisms that may contribute to susceptibility to RA and potentially to other autoimmune diseases. Validated single nucleotide polymorphisms (SNPs; n = 65) were selected from public databases from the 330 kb region of IDDM8. These were genotyped using Sequenom MassArray genotyping technology in two datasets; the test dataset comprised 180 RA cases and 180 controls. We tested 50 SNPs for association with RA and any significant associations were genotyped in a second dataset of 174 RA cases and 192 controls, and the datasets were combined before analysis. Association analysis was performed by chi-square test implemented in Stata software and linkage disequilibrium and haplotype analysis was performed using Helix tree version 4.1. There was initial weak evidence of association, with RA, of a number of SNPs around the loc154449 putative gene and within the KIAA1838 gene; however, these associations were not significant in the combined dataset. Our study has failed to detect evidence of association with any of the known genes mapping to the IDDM8 locus with RA

Association of the FCRL3 gene with rheumatoid arthritis: a further example of population specificity?

Association of a functional promoter polymorphism mapping to the Fc receptor-like 3 (FCRL3) gene has recently been reported and replicated with rheumatoid arthritis (RA) in Japanese populations. The aim of this study was to investigate association of the FCRL3 gene with RA in UK subjects. DNA was available from 1065 patients with RA and 2073 population controls from the UK. Four single nucleotide polymorphism (SNP) markers (FCRL3-169*C/T (fclr3_3, rs7528684), fclr3_4 (rs11264799), fclr3_5 (rs945635), fclr3_6 (rs3761959)) all previously associated with RA in a Japanese population were genotyped in 761 RA samples and 484 controls. In the remaining samples, only the putative disease causal polymorphism, FCRL3-169*C/T, was tested. Genotyping was performed using either the Sequenom MassArray iPlex platform or a 5' Allelic discrimination assay (Taqman, ABI). Extensive linkage disequilibrium was present across the promoter SNPs genotyped (r(2) values = 0.60-0.98). Allele frequencies did not differ between RA cases and controls either for the putative disease causal polymorphism (odds ratio FCRL3-169*C allele = 0.97 (0.87-1.07), p = 0.51) or for the other SNPs tested. Similarly, no association was detected with RA using haplotype analysis or when stratification by shared epitope carriage or by presence of rheumatoid factor was undertaken. This study was powered to detect an effect size of 1.24 or greater for the FCRL3-169*C/T functional promoter polymorphism but no evidence for association was detected, suggesting that this gene will not have a substantial effect in determining susceptibility to RA in populations of Northern European descent

Genetic susceptibility to psoriasis: an emerging picture

Psoriasis is recognized as a complex disease for which multiple genetic and non-genetic factors influence susceptibility. The major susceptibility locus resides in the MHC class I region and, until relatively recently, evidence for non-MHC loci was inconsistent. Like many common diseases, knowledge of the genetic basis of this condition has been advanced dramatically in recent times with the advent of genome-wide association studies using single nucleotide polymorphisms. Here, we give an overview of current knowledge of genetic risk factors for psoriasis and consider emerging studies that may further add to our understanding of the genetic basis of the disease

Linkage analysis of cross-sectional and longitudinally derived phenotypic measures to identify loci influencing blood pressure

BACKGROUND: The design of appropriate strategies to analyze and interpret linkage results for complex human diseases constitutes a challenge. Parameters such as power, definition of phenotype, and replicability have to be taken into account in order to reach meaningful conclusions. Incorporating data on repeated phenotypic measures may increase the power to detect linkage but requires sophisticated analysis methods. Using the simulated Genetic Analysis Workshop 13 data set, we have estimated a variety of systolic blood pressure (SBP) phenotypic measures and examined their performance with respect to consistency among replicates and to true and false positive linkage signals. RESULTS: The whole-genome scan conducted on a dichotomous hypertension phenotype indicated the involvement of few true loci with nominal significance and gave rise to a high rate of false positives. Analysis of a cross-sectional quantitative SBP measure performed better, although genome-wide significance was again not reached. Additional phenotypic measures were derived from the longitudinal data using random effects modelling for censored data with varying levels of covariate adjustment. These models provided evidence for significant linkage to most genes influencing SBP and produced few false positive results. Overall, replicability of results was poor for loci, representing weak effects. CONCLUSION: Longitudinally derived phenotypes performed better than cross-sectional measures in linkage analyses. Bearing in mind the sample design and size of these data, linkage results that fail to replicate should not be dismissed; instead, different lines of evidence derived from complementary analysis methods should be combined to prioritize follow up