Meta-analysis of four rheumatoid arthritis genome-wide linkage studies: confirmation of a susceptibility locus on chromosome 16

Lack of association of -863C/A (rs1800630) polymorphism of tumor necrosis factor-a gene with rheumatoid arthritis

INTRODUCTION

Multifunctional pro-inflammatory cytokine tumor necrosis factor-α (TNF-α) has been implicated in a variety of inflammatory diseases including rheumatoid arthritis (RA). TNF-α polymorphisms are mostly located in its promoter region and play a significant role in disease susceptibility and severity. We therefore sought to investigate TNFA -863C/A (rs1800630) polymorphism association with RA activity in our Pakistani study group.

MATERIAL AND METHODS

A total of 268 human subjects were enrolled. Among them, 134 were RA patients and 134 were controls. In this study the physical parameters of RA patients were collected, and the disease activity was measured by DAS28. The genotypes were determined following the allele-specific PCR along with the pre-requisite internal amplification controls. Subsequently, data were analyzed statistically for any significant association including χ²/Fisher's exact test using GraphPad prism 6 software.

RESULTS

We found that the TNF-α -863 C/A (rs1800630) variant was not differentially segregated between cases and controls in either genotype frequency, with χ² of 2.771 and a p-value of 0.2502, or allele frequency, with χ² of 2.741 and a p-value of 0.0978, with an odds ratio (95% CI) of 0.7490 (0.5317-1.055).

CONCLUSIONS

The lack of positive association of TNF-α -863(rs1800630) polymorphism in our study group implies that TNF-α -863 polymorphism is not a susceptible marker to RA and cannot serve as a genetic factor for screening RA patients in Pakistan. There might be other factors that may influence disease susceptibility. However, further investigations on additional larger and multi-regional population samples are required to determine the consequences of genetic variations for disease prognosis.

Temporomandibular Disorders and Oral Features in Early Rheumatoid Arthritis Patients: An Observational Study

Aims: Temporomandibular disorders (TMD) represent a heterogeneous group of inflammatory or degenerative diseases of the stomatognatic system, with algic and/or dysfunctional clinical features involving temporomandibular joint (TMJ) and related masticatory muscles. Rheumatoid Arthritis (RA) is an autoimmune polyarthritis characterized by the chronic inflammation of synovial joints and oral implications such as hyposalivation, difficulty in swallowing and phoning, feeling of burning mouth, increased thirst, loss of taste or unpleasant taste and smell, dental sensitivity. The aim of this observational study was to investigate the prevalence of TMD symptoms and signs as well as oral implications in patients with Early Rheumatoid Arthritis (ERA), that is a RA diagnosed within 12 months, compared with a control group. Methods: The study group included 52 ERA patients (11 men, 41 women) diagnosed according to the 2010 ACR/EULAR Classification Criteria for Rheumatoid Arthritis. A randomly selected group of 52 patients not affected by this disease, matched by sex and age, served as the control group. The examination for TMD signs and symptoms was based on the standardized Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) by means of a questionnaire and through clinical examination. Results: Regarding the oral kinematics, the left lateral excursion of the mandible was restricted in statistically significant way in ERA patients (p=0.017). The endfeel values were significantly increased in ERA group (p=0.0017), thus showing the presence of a higher muscle contracture. On the other side, the study group complained less frequently (67.3%) of TDM symptoms (muscle pain on chewing, pain in the neck and shoulders muscles, difficulty in mouth opening, arthralgia of TMJ, tinnitus) than controls (90.4%) (χ²= 8.301 p=0.0039). The presence of TMJ noises was significantly lower in the study group (χ²= 3.869 p=0.0049), as well as presence of opening derangement (χ²= 14.014 p=0.0002). The salivary flow was significantly decreased in the study group respect to the control one (p<0.0001). Conclusions: The data collected show a weak TMJ kinematic impairment, a paucisymptomatic muscle contracture (positive endfeel) and a remarkable reduction of salivary flow in ERA patients. Myofacial pain (MP) evoked by palpation was more frequent and severe in the control group than in the study one, this result being highly significant.

Genetic studies of rheumatoid arthritis

Rheumatoid arthritis (RA) is a common autoimmune disease that results in significant morbidity. As with other complex disorders, genome-wide association studies (GWASs) have greatly contributed to the current understanding of RA etiology. In this review, we describe the genetic configuration of RA as revealed primarily through GWASs and their meta-analyses. In addition, we discuss the pathologic mechanisms of RA as suggested by the findings of genetic and functional studies of individual RA-associated genes, including HLA-DRB1, PADI4, PTPN22, CCR6 and FCRL3, and the potential use of genetic information for RA treatment in clinical practice.

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.

Comparison between the stochastic search variable selection and the least absolute shrinkage and selection operator for genome-wide association studies of rheumatoid arthritis

Background

Because multiple loci control complex diseases, there is great interest in testing markers simultaneously instead of one by one. In this paper, we applied two model selection algorithms: the stochastic search variable selection (SSVS) and the least absolute shrinkage and selection operator (LASSO) to two quantitative phenotypes related to rheumatoid arthritis (RA).

Results

The Genetic Analysis Workshop 16 data includes 2,062 unrelated individuals and 545,080 single-nucleotide polymorphism markers from the Illumina 550 k chip. We performed our analyses on the cases as the quantitative phenotype data was not provided for the controls. The performance of the two algorithms was compared. Using sure independence screening as the prescreening procedure, both SSVS and LASSO give small models. No markers are identified in the human leukocyte antigen region of chromosome 6 that was shown to be associated with RA. SSVS and LASSO identify seven common loci, and some of them are on genes LRRC8D, LRP1B, and COLEC12. These genes have not been reported to be associated with RA. LASSO also identified a common locus on gene KTCD21 for the two phenotypes (marker rs230662 and rs483731, respectively).

Conclusion

SSVS outperforms LASSO in simulation studies. Both SSVS and LASSO give small models on the RA data, however this depends on model parameters. We also demonstrate the ability of both LASSO and SSVS to handle more markers than the number of samples.

Vra4 congenic rats with allelic differences in the class II transactivator gene display altered susceptibility to experimental autoimmune encephalomyelitis

Presentation of Ag bound to MHC class II (MHC II) molecules to CD4+ T cells is a key event in adaptive immune responses. Genetic differences in MHC II expression in the rat CNS were recently positioned to allelic variability in the CIITA gene (Mhc2ta), located within the Vra4 locus on rat chromosome 10. In this study, we have examined reciprocal Vra4-congenic strains on the DA and PVGav1 backgrounds, respectively. After experimental nerve injury the strain-specific MHC II expression on microglia was reversed in the congenic strains. Similar findings were obtained after intraparenchymal injection of IFN-gamma in the brain. Expression of MHC class II was also lower on B cells and dendritic cells from the DA.PVGav1-Vra4- congenic strain compared with DA rats after in vitro stimulation with IFN-gamma. We next explored whether Vra4 may affect the outcome of experimental autoimmune disease. In experimental autoimmune encephalomyelitis induced by immunization with myelin oligodendrocyte glycoprotein, DA.PVGav1-Vra4 rats displayed a lower disease incidence and milder disease course compared with DA, whereas both PVGav1 and PVGav1.DA-Vra4 rats were completely protected. These results demonstrate that naturally occurring allelic differences in Mhc2ta have profound effects on the quantity of MHC II expression in the CNS and on immune cells and that this genetic variability also modulates susceptibility to autoimmune neuroinflammation.

Constructing gene association networks for rheumatoid arthritis using the backward genotype-trait association (BGTA) algorithm

BACKGROUND

Rheumatoid arthritis (RA, MIM 180300) is a common and complex inflammatory disorder. The North American Rheumatoid Arthritis Consortium (NARAC) data, as part of the Genetic Analysis Workshop 15 data, consists of both genome scan and candidate gene studies on RA patients.

RESULTS

We applied the backward genotype-trait association (BGTA) algorithm to capture marginal and gene x gene interaction effects of multiple susceptibility loci on RA disease status. A two-stage screening approach was used for the genome scan, whereas a comprehensive study of all possible subsets was conducted for the candidate genes. For the genome scan, we constructed an association network among 39 genetic loci that demonstrated strong signals, 19 of which have been reported in the RA literature. For the candidate genes, we found strong signals for PTPN22 and SUMO4. Based on significant association evidence, we built an association network among the loci of PTPN22, PADI4, DLG5, SLC22A4, SUMO4, and CARD15. To control for false positives, we used permutation tests to constrain the family-wise type I error rate to 1%.

CONCLUSION

Using the BGTA algorithm, we identified genetic loci and candidate genes that were associated with RA susceptibility and association networks among them. For the first time, we report possible interactions between single-nucleotide polymorphisms/genes, which may be useful for biological interpretation.

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.

The sodium-dependent glucose cotransporter SLC5A11 as an autoimmune modifier gene in SLE

Genetic studies in several human autoimmune diseases suggest that the pericentromeric region of chromosome 16 might harbor an autoimmune modifier gene. We hypothesized that the sodium-dependent glucose cotransporter gene SLC5A11 is such a gene, and so might interact with immune-related genes. Herein, this hypothesis was tested in a genetic evaluation of the multiple gene effect in systemic lupus erythematosus (SLE). We used the case-control candidate gene association approach. Eight immune-related genes involved in inflammation and autoantibody generation and clear-up [interleukin 1 receptor antagonist (IL1RN), interleukin 1-beta (IL1-beta), tumor necrosis factor-alpha (TNF-alpha), lymphotoxin-alpha (LTA), tumor necrosis factor ligand superfamily, member 6 (TNFSF6), programmed cell death 1 (PDCD1), C2, and complement component 4 (C4)] were selected for study. Frequency of each candidate's genotype and allele between case and control were compared. Results were stratified by reanalyzing genotype data with relevant symptoms. Finally, improved computational data mining was used to analyze the phenotypes in a large data set. In the frequency analysis, only IL1-beta was significantly associated with SLE. Stratification analysis showed a significant association with SLE symptoms between SLC5A11 and the other immune-related genes, with the exceptions of TNFSF6 and C4. SLC5A11 was significantly associated with low C4 (as was TNF-alpha), anti-Smith antibody (anti-Sm) (as was C2), serositis, and alopecia. Finally, SLC5A11 interacted with PDCD1, TNF-alpha, LTA, and C4. After our study, we concluded that SLC5A11 is involved with some immune effects and interacts with immune-related gene(s), consistent with its function as an autoimmune modifier gene. Furthermore, SLC5A11 might induce apoptosis through the TNF-alpha, PDCD1 pathway. The present genotype-phenotype mapping approach should be applicable to genetic study of other complex diseases.

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.

Association of arthritis with a gene complex encoding C-type lectin-like receptors

OBJECTIVE

To identify susceptibility genes in a rat model of rheumatoid arthritis (RA) and to determine whether the corresponding human genes are associated with RA.

METHODS

Genes influencing oil-induced arthritis (OIA) were position mapped by comparing the susceptibility of inbred DA rats with that of DA rats carrying alleles derived from the arthritis-resistant PVG strain in chromosomal fragments overlapping the quantitative trait locus Oia2. Sequencing of gene complementary DNA (cDNA) and analysis of gene messenger RNA (mRNA) expression were performed to attempt to clone a causal gene. Associations with human RA were evaluated by genotyping single-nucleotide polymorphisms (SNPs) in the corresponding human genes and by analyzing frequencies of alleles and haplotypes in RA patients and age-, sex-, and area-matched healthy control subjects.

RESULTS

Congenic DA rats were resistant to OIA when they carried PVG alleles for the antigen-presenting lectin-like receptor gene complex (APLEC), which encodes immunoregulatory C-type lectin-like receptors. Multiple differences in cDNA sequence and mRNA expression precluded cloning of a single causal gene. Five corresponding human APLEC genes were identified and targeted. The SNP rs1133104 in the dendritic cell immunoreceptor gene (DCIR), and a haplotype including that marker and 4 other SNPs in DCIR and its vicinity showed an indication of allelic association with susceptibility to RA in patients who were negative for antibodies to cyclic citrullinated peptide (anti-CCP), with respective odds ratios of 1.27 (95% confidence interval [95% CI] 1.06-1.52; uncorrected P = 0.0073) and 1.37 (95% CI 1.12-1.67; uncorrected P = 0.0019). Results of permutation testing supported this association of the haplotype with RA.

CONCLUSION

Rat APLEC is associated with susceptibility to polyarthritis, and human APLEC and DCIR may be associated with susceptibility to anti-CCP-negative RA.

Meta-analysis of genome-wide linkage studies in BMI and obesity

OBJECTIVE

The objective was to provide an overall assessment of genetic linkage data of BMI and BMI-defined obesity using a nonparametric genome scan meta-analysis.

RESEARCH METHODS AND PROCEDURES

We identified 37 published studies containing data on over 31,000 individuals from more than >10,000 families and obtained genome-wide logarithm of the odds (LOD) scores, non-parametric linkage (NPL) scores, or maximum likelihood scores (MLS). BMI was analyzed in a pooled set of all studies, as a subgroup of 10 studies that used BMI-defined obesity, and for subgroups ascertained through type 2 diabetes, hypertension, or subjects of European ancestry.

RESULTS

Bins at chromosome 13q13.2- q33.1, 12q23-q24.3 achieved suggestive evidence of linkage to BMI in the pooled analysis and samples ascertained for hypertension. Nominal evidence of linkage to these regions and suggestive evidence for 11q13.3-22.3 were also observed for BMI-defined obesity. The FTO obesity gene locus at 16q12.2 also showed nominal evidence for linkage. However, overall distribution of summed rank p values <0.05 is not different from that expected by chance. The strongest evidence was obtained in the families ascertained for hypertension at 9q31.1-qter and 12p11.21-q23 (p < 0.01).

CONCLUSION

Despite having substantial statistical power, we did not unequivocally implicate specific loci for BMI or obesity. This may be because genes influencing adiposity are of very small effect, with substantial genetic heterogeneity and variable dependence on environmental factors. However, the observation that the FTO gene maps to one of the highest ranking bins for obesity is interesting and, while not a validation of this approach, indicates that other potential loci identified in this study should be investigated further.

Genetics of osteoporosis

Osteoporosis is a common disease with a strong genetic component characterised by reduced bone mass and an increased risk of fragility fractures. Twin and family studies have shown that genetic factors contribute to osteoporosis by influencing bone mineral density (BMD), and other phenotypes that are associated with fracture risk, although the heritability of fracture itself is modest. Linkage studies have identified several quantitative trait loci that regulate BMD but most causal genes remain to be identified. In contrast, linkage studies in monogenic bone diseases have been successful in gene identification, and polymorphisms in many of these genes have been found to contribute to the regulation of bone mass in the normal population. Population-based studies have identified polymorphisms in several candidate genes that have been associated with bone mass or osteoporotic fracture, although individually these polymorphisms only account for a small amount of the genetic contribution to BMD regulation. Environmental factors such as diet and physical activity are also important determinants of BMD, and in some cases specific nutrients have been found to interact with genetic polymorphisms to regulate BMD. From a clinical standpoint, advances in knowledge about the genetic basis of osteoporosis are likely to be important in increasing the understanding of the pathophysiology of the disease; providing new genetic markers with which to assess fracture risk and in identifying genes and pathways that form molecular targets for the design of the next generation of drug treatments.

Meta-analysis of HLA-DRB1 polymorphism in Latin American patients with rheumatoid arthritis

OBJECTIVES

To estimate the common effect size of HLA-DRB1 alleles on rheumatoid arthritis (RA) susceptibility across Latin America populations through a meta-analysis combining the results of published data.

METHODS

Case-control studies on HLA-DRB1 association with RA in Latin America were searched up to October 2006. Genotype frequencies were extracted according to both shared epitope (SE) and HLA-DR4 positive or negative alleles. The effect summary odds ratio (OR) and 95% confidence intervals was obtained. Heterogeneity and publication bias were assessed.

RESULTS

Eight studies containing 684 cases and 1015 controls were included. Under the random effects model, the common OR was 3.28 (1.93, 5.60) (p<0.0001) and 3.54 (2.47, 5.05) (p=4.22 x 10(-12)) for HLA-DR4 and SE, respectively. There was no evidence of publication bias according to Funnel plot and Egger's regression test (p=0,445 for DR4 and p=0,464 for SE meta-analysis). Significant heterogeneity was observed for HLA-DR4 (I2=81.06%, Q=36.96, p=0.000005) but not for the SE meta-analysis.

CONCLUSIONS

HLA-DR4 and SE positive HLA-DRB1 alleles (mainly HLA-DRB10404) are associated with RA in Latin Americans. Heterogeneity is expected owing to the diverse degree of admixture between the examined populations. Our findings support the HLA as a major susceptibility locus for RA and validate the SE hypothesis in Latin America.

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

OBJECTIVE

To dissect the heterogeneity of rheumatoid arthritis (RA) through linkage analysis of quantitative traits, specifically, IgM rheumatoid factor (IgM-RF) and anti-cyclic citrullinated peptide (anti-CCP) autoantibody titers.

METHODS

Subjects, 1,002 RA patients from 491 multiplex families recruited by the North American RA Consortium, were typed for 379 microsatellite markers. Anti-CCP titers were determined based on a second-generation enzyme-linked immunosorbent assay, and IgM-RF levels were quantified by immunonephelometry. We used the Merlin statistical package to perform nonparametric quantitative trait linkage analysis.

RESULTS

For each of the quantitative traits, evidence of linkage, with logarithm of odds (LOD) scores of >1.0, was found in 9 regions. For both traits, the strongest evidence of linkage was for marker D6S1629 on chromosome 6p (LOD 14.02 for anti-CCP and LOD 12.09 for RF). Six other regions with LOD scores of >1.0 overlapped between the 2 traits, on chromosomes 1p21.1, 5q15, 8p23.1, 16p12.1, 16q23.1, and 18q21.31. Evidence of linkage to anti-CCP titer but not to RF titer was found in 2 regions (chromosomes 9p21.3 and 10q21.1), and evidence of linkage to RF titer but not to anti-CCP titer was found in 2 regions (chromosomes 5p15.2 and 1q42.3). Several covariates were significantly associated with 1 or both traits, and linkage analysis exploring the covariate effects revealed striking effects of sex in modulating linkage signals for several chromosomal regions. For example, sex had a striking impact on the linkage results for both quantitative traits on chromosome 6p (P = 0.0007 for anti-CCP titer and P = 0.0012 for RF titer), suggesting a sex-HLA region interaction.

CONCLUSION

Analysis of quantitative components of RA is a promising approach for dissecting the genetic heterogeneity of this complex disorder. These results highlight the potential importance of sex or other covariates that may modulate some of the genetic effects that influence the risk of specific disease manifestations.

Genetic association between the PRKCH gene encoding protein kinase Ceta isozyme and rheumatoid arthritis in the Japanese population

OBJECTIVE

Analyses of families with rheumatoid arthritis (RA) have suggested the presence of a putative susceptibility locus on chromosome 14q21-23. This large population-based genetic association study was undertaken to examine this region.

METHODS

A 2-stage case-control association study of 950 unrelated Japanese patients with RA and 950 healthy controls was performed using >400 gene-based common single-nucleotide polymorphisms (SNPs).

RESULTS

Multiple SNPs in the PRKCH gene encoding the eta isozyme of protein kinase C (PKCeta) showed significant single-locus disease associations, the most significant being SNP c.427+8134C>T (odds ratio 0.72, 95% confidence interval 0.62-0.83, P = 5.9 x 10(-5)). Each RA-associated SNP was consistently mapped to 3 distinct regions of strong linkage disequilibrium (i.e., linkage disequilibrium or haplotype blocks) in the PRKCH gene locus, suggesting that multiple causal variants influence disease susceptibility. Significant SNPs included a novel common missense polymorphism of the PRKCH gene, V374I (rs2230500), which lies within the ATP-binding site that is highly conserved among PKC superfamily members. In circulating lymphocytes, PRKCH messenger RNA was expressed at higher levels in resting T cells (CD4(+) or CD8(+)) than in B cells (CD19(+)) or monocytes (CD14(+)) and was significantly down-regulated through immune responses.

CONCLUSION

Our results provide evidence of the involvement of PRKCH as a susceptibility gene for RA in the Japanese population. Dysregulation of PKCeta signal transduction pathway(s) may confer increased risk of RA through aberrant T cell-mediated autoimmune responses.

Recent advances in the genetics of rheumatoid arthritis

Recent progress in defining the role of genetic factors in rheumatoid arthritis (RA) has been remarkable. Anticyclic citrullinated peptide (anti-CCP) antibody-positive disease appears to be immunogenetically distinct from anti-CCP-negative disease, with the former subgroup primarily responsible for association and linkage with the HLA-DRB1 shared epitope (SE). There is preliminary evidence that non-HLA genes contribute differentially to anti-CCP-positive and negative disease. The phenotypic differences evident in anti-CCP-positive and negative disease suggest a need to reclassify RA based on the presence or absence of this autoantibody. Some recent work also suggests marked interactions between cigarette smoking, anti-CCP antibodies, and the SE, though these relationships may vary across populations. Lastly, a recent single nucleotide polymorphism-based genome-wide linkage analysis of multicase RA families revealed novel genomic regions that likely contain genes that predispose to RA or more specific phenotypes.

Genetic basis of rheumatoid arthritis

Rheumatoid arthritis (RA) is a clinically heterogeneous condition with a complex aetiology in which environmental and genetic factors are implicated. The contribution of human leukocyte antigen (HLA) genes, particularly the HLA-DRB1 gene, to RA genetic predisposition was the first described, and remains as the best characterised single genetic risk factor contributing to RA. However, it has been estimated that only 30% of the genetic contribution to RA can be attributed to HLA genes and it is suggested that other non-HLA genes may play a relevant role in RA susceptibility. Linkage studies and association studies are the two main strategies used in the investigation of genetic factors contributing to complex genetic traits. In this work we review the progress made in the field of RA genetics, focusing mainly on the contribution of candidate gene association studies to the dissection of RA genetic risk factors.

Meta-analysis of genome-wide linkage studies of systemic lupus erythematosus

A genetic contribution to the development of systemic lupus erythematosus (SLE) is well established. Several genome-wide linkage scans have identified a number of putative susceptibility loci for SLE, some of which have been replicated in independent samples. This study aimed to identify the regions showing the most consistent evidence for linkage by applying the genome scan meta-analysis (GSMA) method. The study identified two genome-wide suggestive regions on 6p21.1-q15 and 20p11-q13.13 (P-value=0.0056 and P-value=0.0044, respectively) and a region with P-value<0.01 on 16p13-q12.2. The region on chromosome 6 contains the human leukocyte antigen cluster, and the chromosome 16 and 20 regions have been replicated in several cohorts. The potential importance of the identified genomic regions are also highlighted. These results, in conjunction with data emerging from dense single nucleotide polymorphism typing of specific regions or future genome-wide association studies will help guide efforts to identify the actual predisposing genetic variation contributing to this complex genetic disease.

Linkage analysis of rheumatoid arthritis in US and UK families reveals interactions between HLA-DRB1 and loci on chromosomes 6q and 16p

OBJECTIVE

HLA is the most strongly associated locus in rheumatoid arthritis (RA), accounting for up to one-third of the genetic contribution. Conditioning on the effect of true disease loci such as HLA can lead to increased power to detect effects at other loci and, in addition, allows investigation of the underlying disease models, including interactions. The aim of this study was to detect susceptibility loci for RA by conditioning on HLA in a large sample of affected sibling pairs (ASPs) and to test for evidence of interaction between novel loci and HLA.

METHODS

Genotype data from 3 whole-genome linkage scans for RA in a US population and a UK population were pooled, resulting in a combined data set of 886 ASPs. This pooling of data increased the power to detect loci showing low levels of heterogeneity. Nonparametric linkage analysis was performed to identify regions of interest. Joint 2-locus analysis was then performed for HLA and each of the loci that demonstrated evidence of linkage in the 886 ASPs.

RESULTS

Evidence for linkage was most significant at HLA (P = 4 x 10(-16)), with 7 non-HLA loci showing some evidence for linkage (P = 0.05-0.003). Joint modeling of these loci with HLA provided evidence for linkage at a genome-wide significance level for loci on 6q (P = 2.7 x 10(-6)) and 16p (P = 2 x 10(-4)).

CONCLUSION

These data provide the most convincing evidence to date that 6q and 16p harbor susceptibility genes. In addition, these loci may interact with HLA, facilitating the search for candidate genes within this region.

Heterogeneity-based genome search meta-analysis for preeclampsia

Preeclampsia is a pregnancy-related disorder that causes maternal and fetal morbidity and mortality. Its exact inheritance pattern is still unknown, and genome searches for identifying susceptibility loci for preeclampsia have thus far produced inconclusive or inconsistent results. We performed a heterogeneity-based genome search meta-analysis (HEGESMA) that synthesized the available genome scan data on preeclampsia. HEGESMA identifies genetic regions (bins) that rank highly on average in terms of linkage statistics across genome scans (searches). The significance of each bin's average rank and heterogeneity across scans was calculated using Monte Carlo tests. The meta-analysis involved four genome-scans on general preeclampsia and five scans on severe preeclampsia. In general preeclampsia, 13 bins had significantly high average rank (Prank< 0.05) by either unweighted or weighted analyses, while four of them (2p11.2-2q21.1, 9q21.32-9q31.2, 2p15-2p11.2, 2q32.1-2q35) were formally significant by both analyses. Heterogeneity of bin 2.8 (2q32.1-2q35) was significantly low in both unweighted and weighted analysis (PQ< 0.01). In severe preeclampsia, 10 bins had significantly high average rank by either unweighted or weighted analyses and five of them (3q11.1-3q21.2, 2q37.1-2q37.3, 18p11.32-18p11.22, 2p15-2p11.2, 7q34-7q36.3) were significant by both analyses. Bin 2q37.1-2q37.3 showed marginal low heterogeneity in unweighted and weighted analysis (PQ= 0.06). Results should be interpreted with caution as the p values were modest. Further investigation of these regions by genotyping with additional markers and families may help to direct the identification of candidate genes for preeclampsia.

High-density SNP analysis of 642 Caucasian families with rheumatoid arthritis identifies two new linkage regions on 11p12 and 2q33

We have completed a genome wide linkage scan using >5700 informative single-nucleotide polymorphism (SNP) markers (Illumina IV SNP linkage panel) in 642 Caucasian families containing affected sibling pairs with rheumatoid arthritis (RA), ascertained by the North American Rheumatoid Arthritis Consortium. The results show striking new evidence of linkage at chromosomes 2q33 and 11p12 with logarithm of odds (LOD) scores of 3.52 and 3.09, respectively. In addition to a strong and broad linkage interval surrounding the major histocompatibility complex (LOD>16), regions with LOD>2.5 were observed on chromosomes 5 and 10. Additional linkage evidence (LOD scores between 1.46 and 2.35) was also observed on chromosomes 4, 7, 12, 16 and 18. This new evidence for multiple regions of genetic linkage is partly explained by the significantly increased information content of the Illumina IV SNP linkage panel (75.6%) compared with a standard microsatellite linkage panel utilized previously (mean 52.6%). Stratified analyses according to whether or not the sibling pair members showed elevated anticyclic citrullinated peptide titers indicates significant variation in evidence for linkage among strata on chromosomes 4, 5, 6 and 7. Overall, these new linkage data should reinvigorate efforts to utilize positional information to identify susceptibility genes for RA.

Testing for genetic heterogeneity in the genome search meta-analysis method

The Genome Search Meta-Analysis (GSMA) method is widely used to detect linkage by pooling results of previously published genome-wide linkage studies. The GSMA uses a non-parametric summed rank statistic in 30 cM bins of the genome. Zintzaras and Ioannidis ([2005] Genet. Epidemiol. 28:123-137) developed a method of testing for heterogeneity of evidence for linkage in the GSMA, with three heterogeneity statistics (Q, Ha, B). They implement two testing procedures, restricted versus unrestricted for the summed rank within the bin. We show here that the rank-unrestricted test provides a conservative test for high heterogeneity and liberal test for low heterogeneity in linked regions. The rank-restricted test should therefore be used, despite the extensive simulations needed. In a simulation study, we show that the power to detect heterogeneity is low. For 20 studies of affected sib pairs, simulated assuming linkage in all studies to a gene with sibling relative risk of 1.3, the power to detect low heterogeneity using the Q statistic was 14%. With linkage present in 50% of the studies (to a gene with sibling relative risk of 1.4), the Q heterogeneity statistic had power of 29% to detect high heterogeneity. The power to detect linkage using the summed rank was high in both of these situations, at 98% and 79%, respectively. Although testing for heterogeneity in the GSMA is of interest, the currently available method provides little additional information to that provided by the summed rank statistic.

Genome-wide meta-analysis for rheumatoid arthritis

Meta-analysis is being increasingly used as a tool for integrating data from different studies of complex phenotypes, because the power of any one study to identify causal loci is limited. We applied a novel meta-analytical approach (Loesgen et al. in Genet Epidemiol 21(Suppl 1):S142-S147, 2001) in compiling results from four studies of rheumatoid arthritis in Caucasians including two studies from NARAC (Jawaheer et al. in Am J Hum Genet 68:927-936, 2001; Jawaheer et al. in Arthritis Rheum 48:906-916, 2003), one study from the UK (MacKay et al. in Arthritis Rheum 46:632-639, 2001) and one from France (Cornelis et al. in Proc Natl Acad Sci USA 95:10746-10750, 1998). For each study, we obtained NPL scores by performing interval mapping (2 cM intervals) using GeneHunter2 (Kruglyak et al. in Am J Hum Genet 58:1347-1363, 1996; Markianos et al. in Am J Hum Genet 68:963-977, 2001). The marker maps differed among the three consortium groups, therefore, the marker maps were aligned after the interval mapping was completed and the NPL scores that were within 1 cM of each other were combined using the method of Loesgen et al. (Genet Epidemiol 21(Suppl 1):S142-S147, 2001) by calculating the weighted average of the NPL score. This approach avoids some problems in analysis encountered by using GeneHunter2 when some markers in the sample are not genotyped. This procedure provided marginal evidence (P<0.05) of linkage on chromosome 1, 2, 5 and 18, strong evidence (P<0.01) on chromosomes 8 and 16, and overwhelming evidence in the HLA region of chromosome 6.

A two-step procedure for constructing confidence intervals of trait loci with application to a rheumatoid arthritis dataset

Preliminary genome screens are usually succeeded by fine mapping analyses focusing on the regions that signal linkage. It is advantageous to reduce the size of the regions where follow-up studies are performed, since this will help better tackle, among other things, the multiplicity adjustment issue associated with them. We describe a two-step approach that uses a confidence set inference procedure as a tool for intermediate mapping (between preliminary genome screening and fine mapping) to further localize disease loci. Apart from the usual Hardy-Weiberg and linkage equilibrium assumptions, the only other assumption of the proposed approach is that each region of interest houses at most one of the disease-contributing loci. Through a simulation study with several two-locus disease models, we demonstrate that our method can isolate the position of trait loci with high accuracy. Application of this two-step procedure to the data from the Arthritis Research Campaign National Repository also led to highly encouraging results. The method not only successfully localized a well-characterized trait contributing locus on chromosome 6, but also placed its position to narrower regions when compared to their LOD support interval counterparts based on the same data.

A comparison of methods for intermediate fine mapping

The arrival of highly dense genetic maps at low cost has geared the focus of linkage analysis studies toward developing methods for placing putative trait loci in narrow regions with high confidence. This shift has led to a new analytic scheme that expands the traditional two-stage protocol of preliminary genome scan followed by fine mapping through inserting a new stage in between the two. The goal of this new "intermediate" fine mapping stage is to isolate disease loci to narrow intervals with high confidence so that association studies can be more focused, efficient, and cost-effective. In this paper, we compared and contrasted five methods that can be used for performing this intermediate step. These methods are: the lod support approach, the generalized estimating equations (GEE) method, the confidence set inference (CSI) procedure, and two bootstrap methods. We compared these methods in terms of the coverage probability and precision of localization of the resulting intervals. Results from a simulation study considering several two-locus models demonstrated that the two bootstrap methods yield intervals with approximately correct coverage. On the other hand, the 1-lod support intervals, and those produced by the GEE method, tend to significantly undercover the trait locus, while the regions obtained by the CSI incline to overcover the gene position. When the observed coverage of the confidence intervals produced by all the methods was held to be the same, those obtained through the CSI procedure displayed a higher ability to localize loci, especially when these loci have a minor contribution to the trait and when the amount of data available for the analysis is relatively small. However, with very large sample sizes, lod support intervals emerged as a winner. Application of the methods to the data from the Arthritis Research Campaign National Repository led to intervals containing the position of a known trait locus for all methods, with the greatest precision achieved by the CSI.

Genetics of rheumatoid arthritis

Rheumatoid arthritis (RA) is a heterogeneous autoimmune disorder of unknown cause with variable clinical expression. About 70% of patients are women. Genetic factors play an important role and likely account for about 60% of disease susceptibility and expression. The association with the HLA-DRB1 gene is the best understood, although several non-HLA loci have been linked to RA, including the 18q21 region of the TNFRSR11A gene, which encodes the receptor activator of nuclear factor kappaB, important in bone resorption in RA. Genetic factors are also important in the treatment of RA because the activity of enzymes relevant in the metabolism of drugs such as methotrexate and azathioprine, including methylenetetrahydrofolate reductase and thiopurine methyltransferase, are in part genetically determined.

Genetic basis of rheumatoid arthritis

Rheumatoid arthritis (RA) is a multifactorial disease due to a combination of genetic and environmental factors. Identification of the genetic factors involved in the pathogenesis of RA should open up avenues for developing radical treatment strategies directed at the cause of the disease. The Association de Recherche sur la Polyarthrite (ARP) supports research in this field, in which our group has been involved since 1993. Thanks to this support, considerable progress has been made. Several combinations of susceptibility alleles of various genes are probably involved in the development of RA. Although HLA-DRB1 is the main RA gene, it accounts for only part of the familial risk for RA. HLA-DRB1 alleles are neither necessary nor sufficient to cause the development of RA in a given individual. Several genome scans conducted in populations from France, Japan, North America and UK have confirmed the role of the HLA region and suggested several other susceptibility loci. Association studies support a role for several genes, including TNFR2, PADI4, SLC22A4, RUNX1, and PTPN22. However, the imperfect matching of cases and controls requires that confirmation of these results be obtained. To confirm that a gene confers susceptibility to RA, the association must be replicated in several independent studies and, more importantly, evidence of genetic linkage must be obtained in family studies. The identification of genetic factors conferring susceptibility to RA will open up new avenues toward radical treatments for RA and may help to optimize the diagnostic, prognostic, and pharmacogenetic management of today's patients with RA.

Genome scan meta-analysis of rheumatoid arthritis

OBJECTIVE

Genome scans for rheumatoid arthritis (RA) have yielded inconsistent results. The absence of replication of linkage might be due to lack of power of individual studies. We performed a genome scan meta-analysis of published data to increase statistical power and to assess evidence for linkage of RA across genome scan studies.

METHODS

Four RA whole-genome scans containing 767 families with 964 sibling pairs were included for the genome scan meta-analysis (GSMA). The GSMA method was applied to pool the results obtained from four genome scans. For each study, 120 genomic bins of approximately 30 centimorgans were defined and ranked according to maximum evidence for linkage within each bin. Bin ranks were weighted and summed across all studies. The summed rank for each bin was assessed empirically for significance using permutation methods.

RESULTS

A total of nine bins lay above the 95% confidence level (P=0.05) and four bins were above the 99% confidence level (P=0.01) in the RA GSMA, suggesting that these bins contain RA-linked loci: bins 6.2, 6.4, 8.1, 18.3, 12.3, 12.2, 1.5, 6.3 and 16.2. The strongest evidence for linkage occurred on chromosome 6p22.3-6p21.1 (bin 6.2), containing the HLA region (P(sumrnk)=0.0000008).

CONCLUSION

This RA GSMA confirmed the evidence for HLA loci as the greatest susceptibility factor to RA and showed evidence for linkage at non-HLA loci, such as chromosomes 1p, 6, 8p, 12, 16 and 18q, across studies. These data may provide a basis to carry out targeted linkage and candidate gene studies, particularly in the regions.

Investigating the genetic basis of susceptibility to rheumatoid arthritis

The challenges in identifying genetic polymorphisms that influence the susceptibility to rheumatoid arthritis are the same as those faced in most complex diseases; genetic and phenotypic heterogeneity, an unknown number of loci presumed to have small genetic effects, non-genetic modifying effects that have yet to be fully characterised and a history of unconfirmed genetic associations. Despite the difficulties, the chronic nature of the disease, incomplete efficacy of existing therapies and resultant heavy healthcare burden for the developed world in managing patients with this condition, mean that an understanding of the genetic basis of disease susceptibility, severity and response to therapy is keenly sought. Many linkage and association studies have been carried out and in this article the results of linkage studies are summarised. Recently a number of convincing candidate genes have begun to emerge and an update has been provided for three of these: PTPN22, CTLA-4 and MIF.

GSMA: software implementation of the genome search meta-analysis method

Meta-analysis can be used to pool results of genome-wide linkage scans. This is of great value in complex diseases, where replication of linked regions occurs infrequently. The genome search meta-analysis (GSMA) method is widely used for this analysis, and a computer program is now available to implement the GSMA.

Systemic lupus erythematosus susceptibility loci defined by genome scan meta-analysis

To date, several susceptibility loci for systemic lupus erythematosus (SLE) have been identified by individual genome-wide scans, but many of these loci have shown inconsistent results across studies. Additionally, many individual studies are at the lower limit of acceptable power recommended for declaring significant linkage. The genome search meta-analysis (GSMA) has been proposed as a valid and robust method for combining several genome scan results. The aim of this study is to investigate whether there is any consistent evidence of linkage across multiple studies, and to identify novel SLE susceptibility loci by using GSMA method. Twelve genome scan results generated from nine independent studies have been used for the present GSMA. All together, the data consists of 605 families with 1,355 SLE affected individuals from three self-reported ethnicities; Caucasian, African-American, and Hispanic. For each study, the genome was divided into 120 bins (30 cM) and ranked according to the maximum evidence of linkage within each bin. The ranks were summed and averaged across studies following which the significance was assessed by the permutation tests. The present study identified two genomic locations at 6p22.3-6p21.1 and 16p12.3-16q12.2 that met genome-wide significance (p<0.000417). The identified region at 6p22.3-6p21.1 contains the HLA region. The combined p-values using Fisher's method also supported the significance in these regions. Clustering of significant adjacent bins was observed for chromosomes 6 and 16. Additionally, there are 12 other bins with two point-wise p-values (Psumrnk and Pord) <0.05, suggesting that these bin regions are highly likely to contain SLE susceptibility loci. Among them, present GSMA also identified two novel regions at 4q32.1-4q34.3 and 13q13.2-13q22.2. However, separate analysis using only Caucasian populations identified the strongest evidence for linkage at chromosome 6p21.1-6q15 (Psumrnk=0.00021). One interesting novel region suggests that 3q22.1-3q25.33 (Psumrnk=0.01376) may be an ethnicity-specific SLE linkage. In summary, the present GSMA have identified two statistically significant genomic regions that reconfirmed the SLE linkage at chromosomes 6 and 16.

Genetic determinants of osteoporosis

PURPOSE OF REVIEW

Osteoporosis is a common disease with a strong genetic component characterised by reduced bone mass and an increased risk of fragility fractures. Several advances have been made over recent years in understanding the genetic basis of susceptibility to osteoporosis. This paper will review recent developments in this area.

RECENT FINDINGS

Twin studies have shown that genetic factors contribute to osteoporosis by influencing bone mineral density and other determinants of fracture risk such as ultrasound properties of bone, skeletal geometry, and bone turnover. In the normal population, many different genes contribute to the regulation of these phenotypes by interacting with environmental factors such as diet and exercise. Whereas the effect size of individual genes is small, meta-analysis has been successfully used in many cases to define the role of individual polymorphisms in predisposing to osteoporosis. Linkage studies in humans and experimental animals have identified several quantitative trait loci that regulate osteoporosis-related phenotypes, and many genes that cause monogenic bone diseases have been identified by use of this approach. It has been found that subtle polymorphisms in some of these genes also contribute to regulation of bone mass in the normal population.

SUMMARY

Research has recently begun to clarify the genes and genetic variants that predispose to osteoporosis and regulation of bone mass. Clinical applications of this research include the identification of genetic markers for assessment of fracture risk and the identification of novel molecular targets for the design of drugs that can be used to treat bone disease.

Type 1 diabetes: evidence for susceptibility loci from four genome-wide linkage scans in 1,435 multiplex families

Type 1 diabetes is a common, multifactorial disease with strong familial clustering (genetic risk ratio [lambda(S)] approximately 15). Approximately 40% of the familial aggregation of type 1 diabetes can be attributed to allelic variation of HLA loci in the major histocompatibility complex on chromosome 6p21 (locus-specific lambda(S) approximately 3). Three other disease susceptibility loci have been clearly demonstrated based on their direct effect on risk, INS (chromosome 11p15, allelic odds ratio [OR] approximately 1.9), CTLA4 (chromosome 2q33, allelic OR approximately 1.2), and PTPN22 (chromosome 1p13, allelic OR approximately 1.7). However, a large proportion of type 1 diabetes clustering remains unexplained. We report here on a combined linkage analysis of four datasets, three previously published genome scans, and one new genome scan of 254 families, which were consolidated through an international consortium for type 1 diabetes genetic studies (www.t1dgc.org) and provided a total sample of 1,435 families with 1,636 affected sibpairs. In addition to the HLA region (nominal P = 2.0 x 10(-52)), nine non-HLA-linked regions showed some evidence of linkage to type 1 diabetes (nominal P < 0.01), including three at (or near) genome-wide significance (P < 0.05): 2q31-q33, 10p14-q11, and 16q22-q24. In addition, after taking into account the linkage at the 6p21 (HLA) region, there was evidence supporting linkage for the 6q21 region (empiric P < 10(-4)). More than 80% of the genome could be excluded as harboring type 1 diabetes susceptibility genes of modest effect (lambda(S) > or = 1.3) that could be detected by linkage. This study represents one of the largest linkage studies ever performed for any common disease. The results demonstrate some consistency emerging for the existence of susceptibility loci on chromosomes 2q31-q33, 6q21, 10p14-q11, and 16q22-q24 but diminished support for some previously reported locations.

Non-HLA associations with autoimmune diseases

Susceptibility to autoimmune diseases (AID) has been associated with multiple combinations of genes and environmental or stochastic factors. The strongest influence on susceptibility to autoimmunity is the major histocompatibility complex (MHC), in particular HLA; however, linkage analyses among multiple affected family members have established that non-MHC chromosomal susceptibility regions also influence the susceptibility towards AID. Besides HLA, three non-HLA genes have been convincingly associated with different AID: Citotoxic T lymphocyte-associated antigen 4 (CTLA4), Protein Tyrosine Phosphatase (PTPN22) and Tumor Necrosis Factor-alpha (TNF), indicating that autoimmune phenotypes could represent pleiotropic outcomes of non-specific diseases' genes that underline similar immunogenetic mechanisms. Identification of genes that generate susceptibility will enhance our understanding of the mechanisms that mediate these complex diseases and will allow us to predict and/or prevent them as well as to discover new therapeutic interventions.

Severe disease in patients with rheumatoid arthritis carrying a mutation in the Mediterranean fever gene

BACKGROUND

Pyrin is a newly recognised intracellular regulator of inflammation, and mutations in MEFV, the gene encoding pyrin, are the cause of familial Mediterranean fever.

OBJECTIVE

To determine if known mutations of MEFV are associated with rheumatoid arthritis (RA) morbidity or can modify RA severity.

METHODS

The frequency of the three most common MEFV mutations: M694V, V726A, and E148Q, was determined in 98 Israeli patients with RA (74 women, 24 men) and compared with that in 100 healthy subjects matched for origin. RA severity was determined using a new clinical score of 126 grades. The median severity score of mutation carrier and non-carrier groups was compared after confounding measures were eliminated by logistic regression.

RESULTS

17/98 (17%) patients with RA (all women) were heterozygous for common MEFV mutations, predominantly E148Q (12 patients), and one patient was homozygous for the V726A mutation. The overall mutation rate was comparable between patients with RA and healthy subjects. Patients carrying a mutation had a higher median severity score than the non-carrier group (42 v 29, p = 0.0005). The logistic regression model assigned a 15-fold odds ratio for severe RA in carriers, after adjusting for sex, presence of rheumatoid factor, age at onset, and disease duration (n = 97, p = 0.01, 95% CI 1.74 to 128).

CONCLUSION

MEFV, and particularly the E148Q mutation, is an independent modifier of the clinical manifestations of RA. This is the second Th1-type autoimmune disease in which MEFV mutations have been shown to aggravate the clinical status.

PADI4 polymorphisms are not associated with rheumatoid arthritis in the Spanish population

OBJECTIVES

The presence of anti-citrullinated peptide antibodies is the most specific serological marker known of rheumatoid arthritis (RA). The PADI4 gene, encoding a haematopoietic isoform of the peptidylarginine deiminase citrullinating enzyme, has recently been associated with susceptibility to RA in the Japanese population. A subsequent UK report could not confirm this association, and a later French study also yielded a negative result. Given this discrepancy and the importance of antibodies against citrullinated peptides in the early course of the disease, we performed a replication study.

METHODS

Three hundred and fifty-four Spanish RA patients and 498 Spanish controls were recruited from two Madrid hospitals. The padi4_104 and padi4_94 single-nucleotide polymorphisms (SNP) were analysed by TaqMan assays.

RESULTS

Similarly to what was described in the British and French population, the less frequent allele of this SNP was not associated with the disease (genotype TT, 16.1% in RA patients vs 14.3% in controls; P = 0.46, odds ratio 1.15, 95% confidence interval 0.78-1.71). A confirmatory negative result was obtained on analysing another SNP in the same gene, padi4_94, in 248 RA patients and 394 controls.

CONCLUSIONS

The results of our group and from the British and French studies strongly suggest that polymorphisms of the PADI4 gene do not play a role in susceptibility to RA in European populations.

Meta-analysis of genome scans of age-related macular degeneration

A genetic contribution to the development of age-related macular degeneration (AMD) is well established. Several genome-wide linkage studies have identified a number of putative susceptibility loci for AMD but only a few of these regions have been replicated in independent studies. Here, we perform a meta-analysis of six AMD genome screens using the genome-scan meta-analysis method, which allows linkage results from several studies to be combined, providing greater power to identify regions that show only weak evidence for linkage in individual studies. Results from non-parametric analysis for a broad AMD clinical phenotype (including two studies with quantitative traits) were extracted. For each study, 120 genomic bins of approximately 30 cM were defined and ranked according to maximum evidence for linkage within each bin. Bin ranks were weighted according to study size and summed across all studies; the summed rank (SR) for each bin was assessed empirically for significance using permutation methods. A high SR indicates a region with consistent evidence for linkage across studies. The strongest evidence for an AMD susceptibility locus was found on chromosome 10q26 where genome-wide significant linkage was observed (P=0.00025). Several other regions met the empirical significance criteria for bins likely to contain linked loci including adjacent pairs of bins on chromosomes 1q, 2p, 3p and 16. Several of the regions identified here showed only weak evidence for linkage in the individual studies. These results will help prioritize regions for future positional and functional candidate gene studies in AMD.

HEGESMA: genome search meta-analysis and heterogeneity testing

SUMMARY

Heterogeneity and genome search meta-analysis (HEGESMA) is a comprehensive software for performing genome scan meta-analysis, a quantitative method to identify genetic regions (bins) with consistently increased linkage score across multiple genome scans, and for testing the heterogeneity of the results of each bin across scans. The program provides as an output the average of ranks and three heterogeneity statistics, as well as corresponding significance levels. Statistical inferences are based on Monte Carlo permutation tests. The program allows both unweighted and weighted analysis, with the weights for each study as specified by the user. Furthermore, the program performs heterogeneity analyses restricted to the bins with similar average ranks.

AVAILABILITY

http://biomath.med.uth.gr.

Disease association of two distinct interleukin-18 promoter polymorphisms in Caucasian rheumatoid arthritis patients

Interleukin (IL)-18 is an important mediator of innate and adaptive immunity. We searched for an association of IL-18 promoter single-nucleotide polymorphisms (SNP) with rheumatoid arthritis (RA) in Caucasians. The entire study population was composed of two independent cohorts from Germany (n=200) and Scotland (n=410). Presence of IL-18 SNP at positions -607 and -137 was determined by allele-specific PCR in 327 RA patients and 283 healthy donors (HD). Diplotype distributions of both loci were in Hardy-Weinberg equilibrium (HWE) in the German and Scottish HD cohorts. In contrast, locus -607 was in HW disequilibrium in German, and locus -137 in Scottish RA patients. Diplotypic exact chi(2) tests suggested that -607CC was overrepresented in German, and -137CC in Scottish RA patients, but conservative chi(2) trend analyses could not prove any significant disease association of these single loci. SNP -607 and -137 were in strong linkage disequilibrium. The -607C(*)-137C haplotype was more prevalent in German RA (3.2 vs 1.2%) and in Scottish RA patients (4.1 vs 0.9%) than in the respective HD cohorts. These observations suggest that SNP of both positions contribute to the genetic background of RA pathogenesis.

Resolution of a 16.8-Mb Autoimmunity-Regulating Rat Chromosome 4 Region into Multiple Encephalomyelitis Quantitative Trait Loci and Evidence for Epistasis

To investigate effects of a 16.8-Mb region on rat chromosome 4q42-43 on encephalomyelitis, we performed a high-resolution mapping using a 10th generation advanced intercross line between the susceptible DA strain and the MHC identical but resistant PVG.1AV1 strain. Clinical signs of myelin oligodendrocyte glycoprotein-induced experimental autoimmune encephalomyelitis (EAE) developed in 29% of 772 F(10) rats. Three regions controlling disease, Eae20, Eae21, and Eae22, were mapped using 15 microsatellite markers spanning 16.8 Mb. Eae20 was a major genetic determinant within the region whereas Eae21 modified disease severity. Eae22 was identified as an epistatic region because it only displayed an effect together with Piebald Virol Glaxo (PVG) alleles on Eae20. Disease down-regulation by PVG alleles in the telomeric part of Eae20 was also demonstrated in DA rats made congenic for a approximately 1.44-Mb chromosomal region from PVG. As the region containing Eae20-Eae22 also regulates arthritis, together with the fact that the syntenic mouse 6F(2)-F(3) region regulates experimental lupus and diabetes, and the syntenic human 12p13.31-13.2 region regulates multiple sclerosis and rheumatoid arthritis, the present data point to genes that control several inflammatory diseases. The pairscan analyses of interaction, which here identified Eae22, are novel in the encephalomyelitis field and of importance in the design of further studies of this region in other diseases and species. The limited number of genes identified in Eae20, Eae21, and Eae22 enables focused examination of their relevance in mechanistic animal studies and screening of their association to human diseases.

Heterogeneity testing in meta-analysis of genome searches

Genome searches for identifying susceptibility loci for the same complex disease often give inconclusive or inconsistent results. Genome Search Meta-analysis (GSMA) is an established non-parametric method to identify genetic regions that rank high on average in terms of linkage statistics (e.g., lod scores) across studies. Meta-analysis typically aims not only to obtain average estimates, but also to quantify heterogeneity. However, heterogeneity testing between studies included in GSMA has not been developed yet. Heterogeneity may be produced by differences in study designs, study populations, and chance, and the extent of heterogeneity might influence the conclusions of a meta-analysis. Here, we propose and explore metrics that indicate the extent of heterogeneity for specific loci in GSMA based on Monte Carlo permutation tests. We have also developed software that performs both the GSMA and the heterogeneity testing. To illustrate the concept, the proposed methodology was applied to published data from meta-analyses of rheumatoid arthritis (4 scans) and schizophrenia (20 scans). In the first meta-analysis, we identified 11 bins with statistically low heterogeneity and 8 with statistically high heterogeneity. The respective numbers were 9 and 6 for the schizophrenia meta-analysis. For rheumatoid arthritis, bins 6.2 (the HLA region that is a well-documented susceptibility locus for the disease) and 16.3 (16q12.2-q23.1) had both high average ranks and low between-study heterogeneity. For schizophrenia, this was seen for bin 3.2 (3p25.3-p22.1) and heterogeneity was still significantly low after adjusting for its high average rank. Concordance was high between the proposed metrics and between weighted and unweighted analyses. Data from genome searches should be synthesized and interpreted considering both average ranks and heterogeneity between studies.

Association of a functionalCD19 polymorphism with susceptibility to systemic sclerosis

OBJECTIVE

CD19 is overexpressed in B cells from patients with systemic sclerosis (SSc), and plays a crucial role not only for autoantibody production, but also for skin fibrosis in mouse models. We previously reported the association of a GT repeat polymorphism in the 3'-untranslated region (3'-UTR) of CD19 with human systemic lupus erythematosus. In this study, we examined whether CD19 polymorphisms are associated with genetic susceptibility to SSc.

METHODS

A case-control association study was performed for CD19 polymorphisms, -499G>T in the promoter region and a GT repeat polymorphism in the 3'-UTR, in 134 patients with SSc and 96 healthy individuals recruited at Kanazawa University. CD19 expression levels in the peripheral blood naive and memory B cells from SSc patients were examined by 2-color flow cytometry.

RESULTS

Carrier frequencies of the -499T allele in the promoter (odds ratio [OR] 2.18, 95% confidence interval [95% CI] 1.31-3.86, P = 0.003) and of the (GT)(14) allele in the 3'-UTR (OR 1.86, 95% CI 1.05-3.28, P = 0.03) were significantly increased in SSc patients compared with healthy controls. Association was particularly evident in patients with limited cutaneous SSc with anticentromere antibodies. These alleles were in linkage disequilibrium, but the -499T allele seemed to play a primary role. CD19 expression levels in peripheral blood B cells were significantly elevated in both naive (P = 0.0029) and memory (P = 0.0022) B cells from patients with SSc who had the -499T allele as compared with those without the -499T allele.

CONCLUSION

The CD19 -499G>T polymorphism is associated with higher CD19 expression in B cells, and with susceptibility to SSc.

Dense genome-wide linkage analysis of rheumatoid arthritis, including covariates

OBJECTIVE

Rheumatoid arthritis (RA) is a heterogeneous disease that exhibits a complex genetic component. Previous RA genome scans confirmed the involvement of the HLA region and generated data on suggestive signals at non-HLA regions, albeit with few overlaps in findings between studies. The present study was undertaken to detect potential RA gene regions and to estimate the number of true RA gene regions, taking into account the heterogeneity of RA, through performance of a dense genome scan.

METHODS

In a study of 88 French Caucasian families (105 RA sibpairs), 1,088 microsatellite markers were genotyped (3.3-cM genome scan), and a multipoint model-free linkage analysis was performed. The statistical assessment of the results relied on 10,000 computer simulations. A covariate-based multipoint model-free linkage analysis was performed on the locations of regions with suggestive evidence for linkage.

RESULTS

Involvement of the HLA region was strongly confirmed (P = 6 x 10(-5)), and 19 non-HLA regions showed suggestive evidence for linkage (P < 0.05); 9 of these overlapped with regions suggested in other published RA genome scans. A routine 12-cM genome scan with the same families would have detected only 7 of the 19 regions, including only 4 of the 9 overlapping regions. From the 10,000 computer simulations, we estimated that 8 +/- 4 regions (mean +/- SD) were true-positives. RA covariate-based analysis provided additional linkage evidence for 3 regions, with age at disease onset, erosions, and HLA-DRB1 shared epitope as covariates.

CONCLUSION

The results of this study provide evidence of 19 non-HLA RA gene regions, with an estimate of 8 +/- 4 as true-positives, and provide additional evidence for 3 regions from covariate-based analysis.

A missense single-nucleotide polymorphism in a gene encoding a protein tyrosine phosphatase (PTPN22) is associated with rheumatoid arthritis

Rheumatoid arthritis (RA) is the most common systemic autoimmune disease, affecting approximately 1% of the adult population worldwide, with an estimated heritability of 60%. To identify genes involved in RA susceptibility, we investigated the association between putative functional single-nucleotide polymorphisms (SNPs) and RA among white individuals by use of a case-control study design; a second sample was tested for replication. Here we report the association of RA susceptibility with the minor allele of a missense SNP in PTPN22 (discovery-study allelic P=6.6 x 10(-4); replication-study allelic P=5.6 x 10(-8)), which encodes a hematopoietic-specific protein tyrosine phosphatase also known as "Lyp." We show that the risk allele, which is present in approximately 17% of white individuals from the general population and in approximately 28% of white individuals with RA, disrupts the P1 proline-rich motif that is important for interaction with Csk, potentially altering these proteins' normal function as negative regulators of T-cell activation. The minor allele of this SNP recently was implicated in type 1 diabetes, suggesting that the variant phosphatase may increase overall reactivity of the immune system and may heighten an individual carrier's risk for autoimmune disease.