Dissecting the heterogeneity of rheumatoid arthritis through linkage analysis of quantitative traits

Identification of IRX1 as a Risk Locus for Rheumatoid Factor Positivity in Rheumatoid Arthritis in a Genome-Wide Association Study

OBJECTIVE

Rheumatoid factor (RF) is a well-established diagnostic and prognostic biomarker in rheumatoid arthritis (RA). However, ∼20% of RA patients are negative for this anti-IgG antibody. To date, only variation at the HLA-DRB1 gene has been associated with the presence of RF. This study was undertaken to identify additional genetic variants associated with RF positivity.

METHODS

A genome-wide association study (GWAS) for RF positivity was performed using an Illumina Quad610 genotyping platform. A total of 937 RF-positive and 323 RF-negative RA patients were genotyped for >550,000 single-nucleotide polymorphisms (SNPs). Association testing was performed using an allelic chi-square test implemented in Plink software. An independent cohort of 472 RF-positive and 190 RF-negative RA patients was used to validate the most significant findings.

RESULTS

In the discovery stage, a SNP in the IRX1 locus on chromosome 5p15.3 (SNP rs1502644) showed a genome-wide significant association with RF positivity (P = 4.13 × 10(-8) , odds ratio [OR] 0.37 [95% confidence interval (95% CI) 0.26-0.53]). In the validation stage, the association of IRX1 with RF was replicated in an independent group of RA patients (P = 0.034, OR 0.58 [95% CI 0.35-0.97] and combined P = 1.14 × 10(-8) , OR 0.43 [95% CI 0.32-0.58]).

CONCLUSION

To our knowledge, this is the first GWAS of RF positivity in RA. Variation at the IRX1 locus on chromosome 5p15.3 is associated with the presence of RF. Our findings indicate that IRX1 and HLA-DRB1 are the strongest genetic factors for RF production in RA.

TDT-HET: a new transmission disequilibrium test that incorporates locus heterogeneity into the analysis of family-based association data

BACKGROUND

Locus heterogeneity is one of the most documented phenomena in genetics. To date, relatively little work had been done on the development of methods to address locus heterogeneity in genetic association analysis. Motivated by Zhou and Pan's work, we present a mixture model of linked and unlinked trios and develop a statistical method to estimate the probability that a heterozygous parent transmits the disease allele at a di-allelic locus, and the probability that any trio is in the linked group. The purpose here is the development of a test that extends the classic transmission disequilibrium test (TDT) to one that accounts for locus heterogeneity.

RESULTS

Our simulations suggest that, for sufficiently large sample size (1000 trios) our method has good power to detect association even the proportion of unlinked trios is high (75%). While the median difference (TDT-HET empirical power - TDT empirical power) is approximately 0 for all MOI, there are parameter settings for which the power difference can be substantial. Our multi-locus simulations suggest that our method has good power to detect association as long as the markers are reasonably well-correlated and the genotype relative risk are larger. Results of both single-locus and multi-locus simulations suggest our method maintains the correct type I error rate.Finally, the TDT-HET statistic shows highly significant p-values for most of the idiopathic scoliosis candidate loci, and for some loci, the estimated proportion of unlinked trios approaches or exceeds 50%, suggesting the presence of locus heterogeneity.

CONCLUSIONS

We have developed an extension of the TDT statistic (TDT-HET) that allows for locus heterogeneity among coded trios. Benefits of our method include: estimates of parameters in the presence of heterogeneity, and reasonable power even when the proportion of linked trios is small. Also, we have extended multi-locus methods to TDT-HET and have demonstrated that the empirical power may be high to detect linkage. Last, given that we obtain PPBs, we conjecture that the TDT-HET may be a useful method for correctly identifying linked trios. We anticipate that researchers will find this property increasingly useful as they apply next-generation sequencing data in family based studies.

Genome-wide association analyses of quantitative traits: the GAW16 experience

The group that formed on the theme of genome-wide association analyses of quantitative traits (Group 2) in the Genetic Analysis Workshop 16 comprised eight sets of investigators. Three data sets were available: one on autoantibodies related to rheumatoid arthritis provided by the North American Rheumatoid Arthritis Consortium; the second on anthropometric, lipid, and biochemical measures provided by the Framingham Heart Study (FHS); and the third a simulated data set modeled after FHS. The different investigators in the group addressed a large set of statistical challenges and applied a wide spectrum of association methods in analyzing quantitative traits at the genome-wide level. While some previously reported genes were validated, some novel chromosomal regions provided significant evidence of association in multiple contributions in the group. In this report, we discuss the different strategies explored by the different investigators with the common goal of improving the power to detect association.

Linkage and association studies of joint morbidity from rheumatoid arthritis

OBJECTIVE

To investigate the relationship between genetic variations of rheumatoid arthritis (RA) susceptibility in terms of joint morbidity.

METHODS

We used data from Genetic Analysis Workshop 15. The Illumina linkage panel IV included 5858 single-nucleotide polymorphisms (SNP), with 5744 SNP passing quality control filters. The phenotypic variables analyzed were the level of rheumatoid factor (RF) and score on the Joint Alignment and Motion (JAM) scale. We modified the scale, dividing by RF values relevant to disease severity. Linkage analysis for affected sibling pairs was done using the MERLIN program, and family-based association tests were carried out using PLINK and FBAT software.

RESULTS

We found a high peak (LOD = 3.29; NPL Z = 4.07) near the HLA-DRB1 region on chromosome 6. The linkage at 6p24 at rs1410766 [LOD = 2.66; nonparametric linkage (NPL) Z = 3.23] was statistically significant. Two other regions also showed possible linkage peaks: chromosome 7q30 at rs322812 (LOD = 2.47; NPL Z = 3.39) and chromosome 15p34 at rs347117 (LOD = 1.95; NPL Z = 2.80). For the family-based association study, 7 SNP related to clinical RA severity were detected.

CONCLUSION

Genetic variations may lead to an enhanced risk of joint damage and increased levels of RF. Further studies are needed to elucidate the roles of other genes involved in RA and to explore whether the clinical signs of RA are associated with particular genetic variations.

The 6-minute walk test in scleroderma--how measuring everything measures nothing

The 6-min walk test (6MWT) is a standardized measure of submaximal exercise capacity that has served as the primary measure of outcome in studies of pulmonary arterial hypertension. Never fully validated in scleroderma, a variety of data suggest that many non-pulmonary aspects of scleroderma contribute to its results thereby blunting the ability of the 6MWT to measure change in lung function. Although reproducible, the lack of correlation with measures of parenchymal lung disease demonstrates an insurmountable lack of both construct and content validity. The 6MWT should be abandoned as an outcome measure in lung disease complicating scleroderma.

A large-scale rheumatoid arthritis genetic study identifies association at chromosome 9q33.2

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease affecting both joints and extra-articular tissues. Although some genetic risk factors for RA are well-established, most notably HLA-DRB1 and PTPN22, these markers do not fully account for the observed heritability. To identify additional susceptibility loci, we carried out a multi-tiered, case-control association study, genotyping 25,966 putative functional SNPs in 475 white North American RA patients and 475 matched controls. Significant markers were genotyped in two additional, independent, white case-control sample sets (661 cases/1322 controls from North America and 596 cases/705 controls from The Netherlands) identifying a SNP, rs1953126, on chromosome 9q33.2 that was significantly associated with RA (OR(common) = 1.28, trend P(comb) = 1.45E-06). Through a comprehensive fine-scale-mapping SNP-selection procedure, 137 additional SNPs in a 668 kb region from MEGF9 to STOM on 9q33.2 were chosen for follow-up genotyping in a staged-approach. Significant single marker results (P(comb)<0.01) spanned a large 525 kb region from FBXW2 to GSN. However, a variety of analyses identified SNPs in a 70 kb region extending from the third intron of PHF19 across TRAF1 into the TRAF1-C5 intergenic region, but excluding the C5 coding region, as the most interesting (trend P(comb): 1.45E-06 --> 5.41E-09). The observed association patterns for these SNPs had heightened statistical significance and a higher degree of consistency across sample sets. In addition, the allele frequencies for these SNPs displayed reduced variability between control groups when compared to other SNPs. Lastly, in combination with the other two known genetic risk factors, HLA-DRB1 and PTPN22, the variants reported here generate more than a 45-fold RA-risk differential.

Data for Genetic Analysis Workshop (GAW) 15 Problem 2, genetic causes of rheumatoid arthritis and associated traits

For Genetic Analysis Workshop 15 Problem 2, we organized data from several ongoing studies designed to identify genetic and environmental risk factors for rheumatoid arthritis. Data were derived from the North American Rheumatoid Arthritis Consortium (NARAC), collaboration among Canadian researchers, the European Consortium on Rheumatoid Arthritis Families (ECRAF), and investigators from Manchester, England. All groups used a common standard for defining rheumatoid arthritis, but NARAC also further selected for a more severe phenotype in the probands. Genotyping and family structures for microsatellite-based linkage analysis were provided from all centers. In addition, all centers but ECRAF have genotyped families for linkage analysis using SNPs and these data were additionally provided. NARAC also had additional data from a dense genotyping analysis of a region of chromosome 18 and results from candidate gene studies, which were provided. Finally, smoking influences risk for rheumatoid arthritis, and data were provided from the NARAC study on this behavior as well as some additional phenotypes measuring severity. Several questions could be evaluated using the data that were provided. These include comparing linkage analysis using single-nucleotide polymorphisms versus microsatellites and identifying credible regions of linkage outside the HLA region on chromosome 6p13, which has been extensively documented; evaluating the joint effects of smoking with genetic factors; and identifying more homogenous subsets of families for whom genetic susceptibility might be stronger, so that linkage and association studies may be more efficiently conducted.

Comparison of genome-wide single-nucleotide polymorphism linkage analyses in Caucasian and Hispanic NARAC families

We performed linkage analysis on families with rheumatoid arthritis, stratifying by ethnic origin. We compared results using either Kong and Cox nonparametric LOD scores or MOD score analysis using the software GeneHunter MODSCORE. We first applied SNPLINK to remove markers showing excess linkage disequilibrium from the SNPs in the Illumina IV SNP Linkage panel. In this analysis there were 659 self-reported Caucasian families and 29 self-reported Hispanic families in the NARAC collection. Chromosome 19 yielded MOD scores > 3.00 in the Hispanic group, while chromosomes 2, 6, 7, 11, and XY had MOD scores > 3.00 in the Caucasian group. We performed simulation studies to evaluate the empirical distribution of the MOD score for autosomal loci separately in Hispanics and Caucasians. Results showed genome-wide significant evidence for linkage in Caucasians for chromosomes 2q and 6p, but no significant evidence for any linkages in the Hispanics, including little evidence for linkage to chromosome 6p in this group. An examination of the difference of phenotypes in two ethnic groups suggested significantly earlier mean age of onset, higher percentage of anti-cyclic citrullinated peptide positive people, and lower percentage of affected people carrying shared epitopes in Hispanics than those in Caucasians. A larger sample size of the Hispanic group is needed to identify linkage regions.

Two-dimensional linkage analyses of rheumatoid arthritis

Rheumatoid arthritis (RA) is a multifactorial disease with complex genetic etiology, about which little is known. Here, we apply a two-stage procedure in which a quick first-stage analysis was used to narrow down targets for a more thorough and detailed testing for gene x gene interaction. Potentially interesting regions were first identified by testing for major gene effects using non-parametric linkage methods. To select regions of interest, we first tested for linkage to three different RA-related traits one at a time: RA affection status and the quantitative phenotypes rheumatoid factor IgM and anti-cyclic citrullinated peptide levels. These linkage analyses identified regions on chromosomes 3, 5, 6, 8, 16, 18, 19, and 20. We subsequently analyzed the selected regions in a pairwise manner to detect gene x gene interactions influencing RA using a recently developed two-dimensional linkage method. We found evidence of interacting loci on chromosomes 5, 6, and 18.

Genome-wide single-nucleotide polymorphism linkage analyses of quantitative rheumatoid arthritis phenotypes in Caucasian NARAC families

We applied nonparametric quantitative trait linkage analysis to two rheumatoid arthritis quantitative phenotypes, IgM rheumatoid factor (RF) and anti-cyclic citrullinated peptide autoantibody titer measurements, using 5700 genome-wide Illumina single-nucleotide polymorphism genotypes on 658 Caucasian North American Rheumatoid Arthritis Consortium families. Peak LOD scores for both quantitative traits were located in the human leukocyte antigen region 6p21 (15.8 and 13.8 for RF and anti-cyclic citrullinated peptide, respectively) followed by 11p12 (3.2 and 3.6). In addition, there were LOD scores of 3.2 on 2q32 for RF and 3.6 on 4q24 for anti-cyclic citrullinated peptide. The resulting linkage signals for both phenotypes are very similar to previous results for rheumatoid arthritis as a qualitative variable, with rheumatoid factor measurements being most closely aligned. Interestingly, anti-cyclic citrullinated peptide exhibits a stronger linkage peak on 2p14 than rheumatoid factor and rheumatoid arthritis, and stronger linkage on 4q24. Finally, we used ordered subset analyses to determine if sub-ranges of these two traits increased rheumatoid arthritis linkage signals; however, our analyses did not reveal significant effects of the quantitative traits on rheumatoid arthritis linkage signals in this population.

Linkage analyses of rheumatoid arthritis and related quantitative phenotypes: the GAW15 experience

The group that formed on the theme of linkage analyses of rheumatoid arthritis RA and related phenotypes (Group 10) in the Genetic Analysis Workshop 15 comprised 18 sets of investigators. Two data sets were available: one was a real set provided by the North American Rheumatoid Arthritis Consortium and collaborators in Canada, France (European Consortium Of Rheumatoid Arthritis Families) and the UK; the other was a simulated data set modelled after the real data set. Whereas a majority of the investigators analyzed the RA affection status as a binary phenotype, a few contributions considered data on correlated quantitative traits such as anti-cyclic citrullinated peptide and rheumatoid factor-immunoglobulin M. The different investigators applied a wide spectrum of linkage methods. As expected, most methods could identify the human leukocyfeantigen region on chromosome 6 as a major genetic factor for RA. In addition, some novel chromosomal regions provided significant evidence of linkage in multiple contributions in the group. In this report, we discuss the different strategies explored by the different investigators with the common goal of improving the power to detect linkage.