Rheumatoid arthritis (RA), a common systemic inflammatory disease with autoimmune features, affects ∼1% of the adult population worldwide. The pathogenesis of RA involves an aberrant immune response to self antigens, which induces persistent synovial inflammation and subsequent cartilage destruction and bone erosions. Although the etiology of RA remains largely unknown, numerous epidemiologic studies have provided strong evidence of a major genetic component of RA susceptibility (1, 2). In twin studies, a higher concordance rate for RA in monozygotic than in dizygotic twins has been shown, with heritability approaching 60% (3). Family-based analyses have shown an increased risk of RA in siblings of affected probands compared with the general population (relative risk in siblings [λs] 2–17) (2).
An association between disease risk and the HLA locus has been well established in different ethnic groups. In particular, several HLA–DRB1 alleles (*0401, *0404, *0405, *0408, *0101, *0102, *1001, and *1402) are strongly associated with susceptibility to RA (4). These DRB1 alleles encode a conserved amino acid sequence (QKRAA, QRRAA, or RRRAA) in the third hypervariable region of the molecule, which is commonly called the shared epitope (5). The development of severe disease has also been associated with the HLA–DRB1 shared epitope (6). However, it is estimated that this association accounts for only one-third of the genetic component of RA (1), implying that several other non-HLA genes contribute to RA susceptibility.
To search for gene(s) underlying susceptibility to RA, genome-wide linkage screening in families with RA has been conducted by at least 4 independent research groups focusing on different ethnicities. The European Consortium on Rheumatoid Arthritis Families focused on Europeans (7, 8), Shiozawa et al focused on Japanese (9), the North American Rheumatoid Arthritis Consortium focused on Caucasians living in the US (10, 11), and the Arthritis Research Campaign: UK National Repository of Multicase RA Families focused on Caucasians living in the UK (12, 13). In these studies, linkage to the HLA locus on chromosome 6p was confirmed, and a number of potentially important non-HLA loci were identified. Several loci (e.g., 1p, 1q, 2q, 5q, 13q, 14q, 16p, 18p, and Xq) overlapped ≥2 genome screens (8); however, other than the HLA region, no obvious consensus regarding which chromosomal regions would be most likely to contain RA susceptibility genes was obtained. This is consistent with other complex genetic disorders such as type 1 diabetes mellitus (DM), and could be due to a number of factors, including the limited statistical power of individual studies (false-positive or false-negative findings), intra- and interpopulation differences in the effect size of each gene, and genetic heterogeneity.
One way to circumvent and minimize these problems is to use a meta-analysis, in which data across independent genome scans are combined. Indeed, Fisher et al (14) completed a meta-analysis using the rank-based genome scan meta-analysis method on the early genome scan data obtained in France, the US, the UK, and Japan, and reported linkage signals on 6p (HLA), 6q, 12p, and 16cen (P < 0.01), as well as 8 novel regions with suggestive evidence (P < 0.05). Choi et al (15) also applied the genome scan meta-analysis method to data obtained from European and Caucasian populations, and reported evidence of the involvement of 7 chromosomal regions, including the HLA region. More recently, Etzel et al (16) applied a novel meta-analytical method developed by Loesgen et al (17) to Caucasian-only populations, and reported overwhelming evidence of linkage in the HLA region, strong evidence of 8p and 16p (P < 0.01), and marginal evidence of 1q, 2q, 5q, and 18q (P < 0.05). Taken together, results of these meta-analyses highlight several regions of genetic linkage for RA, especially on chromosomes 1q, 6p, 12p, 16p, and 18q, that can be further studied in fine mapping and candidate gene analyses.
Chromosome 14q is one of the regions for which evidence of linkage to RA was found in the meta-analysis by Fisher et al (14), although the reported significance level was not overwhelming when compared with other possible linkage regions. We noticed that in this region, microsatellite markers showing at least some evidence of significance in each study were tightly clustered in a narrow genomic region of ∼3 Mb. These microsatellite markers were D14S587 (P = 0.037 for Caucasians living in the US by sibpair analysis with the SibPal program) (10), D14S276 (P = 0.03 for Caucasians living in the UK; logarithm of odds [LOD] 0.9 for Japanese) (9, 12), and D14S285 (P = 0.049 for Europeans by single-point analysis) (7). In addition, a recent whole-genome case–control association study in a Japanese population identified another closely located marker, D14S0452i, to be significantly associated with RA (P = 0.001 by Fisher's exact test) (18). These adjacent markers on chromosome 14q23 may be indicative of a common RA susceptibility gene across racial/ethnic groups.
Interestingly, the chromosome 14q21–q23 region has also been implicated repeatedly in susceptibility to systemic lupus erythematosus (SLE). Suggestive evidence of linkage to this region was reported in Caucasian populations in the US and Canada (D14S276; LOD 2.81, P = 0.00016) (19), in Mexican Americans and Caucasians in the US (D14S63; nonparametric linkage [NPL] 1.70, P = 0.04 and D14S258; NPL 2.02, P = 0.02) (20), in the Swedish population (D14S592; LOD 1.15) (21), and in the Finnish population (D14S587; NPL 2.20, P = 0.02) (22), although no single study has obtained significant linkage results. It is well known that different autoimmune diseases share susceptibility loci (23), and there are numerous reports describing concurrence of RA and SLE in individuals (24) or in families (25, 26). In this study, therefore, we hypothesized that a gene predisposing to RA and/or SLE may exist in chromosome 14q21–q23, and we investigated this region in a large-scale association study with a set of >400 single-nucleotide polymorphism (SNP) markers in 950 unrelated Japanese patients with RA and 950 controls. A similar approach was recently used to identify the SEC8L1 gene, located on chromosome 7q31, as a putative RA susceptibility gene in Japanese individuals (27). Our approach was useful in demonstrating an association between RA and multiple variants of the PRKCH gene, which encodes the η isozyme of protein kinase C (PKCη).
- Top of page
- PATIENTS AND METHODS
- AUTHOR CONTRIBUTIONS
- Supporting Information
The current study was designed to determine whether gene(s) located on chromosome 14q are associated with susceptibility to RA in the Japanese population. Our SNP association scan covers an ∼20-Mb genomic region on chromosome 14q21–23. We focused on the gene-coding region of this area, and chose SNPs yielding priorities in their allele frequencies, rather than relying on linkage disequilibrium information and resources that recently became publicly available (e.g., the International HapMap Project), since a high-density SNP map of the region was not available when we started this study. In addition, to reduce the time and cost of genotyping, we adopted a 2-stage strategy, in which we proceeded to the validation stage of genotyping only if the results from the exploratory stage offered some possibility of overall significance. To test associations, we used the so-called “joint analysis” strategy (32), in which we analyzed the pooled data from both exploratory and validation stages, using a P value of 0.05 with Bonferroni correction for 378 comparisons (the total number of SNP loci used for analysis). A recent report indicated that joint analysis is more efficient and powerful than the standard 2-stage strategy, which considers the second cohort to be a completely independent replication panel and tests statistics for the second stage data alone (32).
Our association study strategy was successful in identifying a significant association for 1 landmark SNP (rs767755), located in intron 2 of the PRKCH gene encoding PKCη. Subsequent analysis of additional SNPs within this gene revealed multiple SNPs scattered in the 3 distinct linkage disequilibrium blocks (blocks A, B, and D) to be significantly associated with RA. Associations were observed in a linkage disequilibrium block–dependent manner. Moreover, the results of genotype combination analysis using SNPs residing in different linkage disequilibrium blocks suggest that 2- or 3-way combinations of “at risk” genotypes increase the risk of RA additively or synergistically. Significant SNPs included a novel missense SNP substituting V for I at residue 374 of the PKCη (V374I). Of note, the V374 residue is located within the conserved ATP-binding site with the consensus sequence GXGXXGX16K, and mutations in this motif reportedly result in abolished functional activities for other PKC isozymes (38, 39). An investigation is now under way in our laboratory to determine whether this variant has functional consequences.
Other significant SNPs were noncoding SNPs, located in intron 2, 5, or 9; these observations are not surprising given the recent reports of similar findings in RA (40) and also in other common diseases with genetic associations, such as type 2 DM (41) and asthma (42). Although the exact causal connection between these intronic SNPs and RA risk is not known, they may alter PKCη expression or function by affecting splicing. In this regard, we searched for potential DNA regulatory sites and protein-binding sites in SNPs but identified no such motifs (TRANSFAC database ; data not shown).
One limitation of this genetic association study is that our controls were not matched for age. With respect to age at the time of the interview and subsequent blood sampling, the control subjects were significantly younger than the patients (mean ± SD age 39.1 ± 15.2 years versus 61.7 ± 12.4 years, respectively; P < 0.001). Owing to the late onset of RA, it is possible that at least some of the controls who were included in this study will develop RA in the future. This potential misclassification in the control group due to the inclusion of undiagnosed cases, as well as inappropriate case definition, would bias and weaken any association between PRKCH and RA.
There are, however, several arguments against such bias. First, the mean ± SD age at RA diagnosis in the patients was 48.7 ± 13.4 years, rather similar to the mean age of controls, although the difference was still statistically significant (P < 0.0001), Second, our controls were interviewed extensively about their health and reported no family history of any autoimmune diseases. Therefore, they would have only a low risk of developing RA, and the overall population incidence is estimated to be <0.5–1%. Thus, the sample size of our association study should still provide adequate power to detect an association. Finally, there was no significant difference in PRKCH genotype distribution between our controls and a group of Japanese individuals from the same geographic area who had type 2 DM (n = 711), from whom samples were collected for a different genetic association study (ref.30 and Takata Y: unpublished observations). The mean ± SD age of the type 2 DM group was 62.6 ± 11.4 years, which was not significantly different from that of RA patients in this study. We thus believe our comparison to be acceptable. However, due to the cross-sectional, population-based nature of this study, our findings need to be confirmed in other independent populations and/or by family-based tests of association. In the first instance, the use of populations collected for large prospective cohort studies would be one obvious approach.
The PRKCH gene is an excellent functional candidate for susceptibility to RA, since the disease is believed to be the result of misdirected immune responses by autoreactive T cells, and PKC plays a critical role in signal transduction controlling T cell activation. The PKC gene family consists of ≥11 members, including PRKCH/PKCη, and their gene products (isozymes) are usually categorized into the following 3 groups based on structure and cofactor/activator requirements: conventional (PKCα, PKCβ1, PKCβ2, and PKCγ), novel (PKCδ, PKCε, PKCη, PKCθ, and PKCμ), and atypical (PKCζ and PKCλ/ι). Conventional PKCs are dependent on calcium and diacylglycerol for their functional activity, whereas novel PKCs are calcium independent, and atypical PKCs are calcium and diacylglycerol independent.
Individual PKC isozymes have been shown to exhibit biologically distinct and even opposing cellular functions in different cell types (44), and recent data suggest that at least some isozymes of PKC are involved in critical function(s) of T cells. For example, PKCθ, which is highly expressed in T cells, has been extensively documented to play essential roles in T cell activation, signaling, and gene transcription regulation (45). In addition, PKCβ has been suggested to be a key element in proper T cell migration (46), while PKCζ has been described as maintaining the integrity of the actin cytoskeleton and mediating interleukin-induced T cell proliferation (47). It is also noteworthy that gold sodium thiomalate, which has been used as a therapeutic agent for RA for many years, is now recognized as a PKC inhibitor, suppressing mitogen-induced T cell proliferation (48).
Unfortunately, the physiologic function of PKCη in T cells has not yet been documented, and the pathophysiologic mechanism (or pathway) by which PRKCH gene polymorphisms may influence RA risk remains unknown. However, this study is the first to show that the PRKCH gene is expressed at high levels in helper/inducer (CD4+) or suppressor/cytotoxic (CD8+) T cells, in a manner analogous to that of PKCθ, and that its expression is down-regulated through immune responses. These observations suggest that PKCη functions, at least in part, in signaling pathways unique to T cells, and, therefore, that dysregulation of its gene expression and/or function might be associated with an increased risk of RA.
Another possibility is that PKCη may function as a regulator in both the pathogenic pathway and certain aspects of the cytokine signaling cascade in monocytes and macrophages, although, in our experiments, the PRKCH gene expression level in monocytes (CD14+ cells) was low compared with that in T cells. Interestingly, plasma levels of nitric oxide, a mediator of inflammation, were shown to be elevated in patients with severe RA, and a positive correlation between PKCη and inducible nitric oxide synthase expression was observed in peripheral blood monocyte–derived macrophages from RA patients (49). Although these findings provide evidence supporting the possible involvement of PKCη in immunologic activities of monocytes and macrophages, further investigation is obviously required before firm conclusions can be drawn.
In conclusion, we have identified the PRKCH gene encoding PKCη as a putative candidate gene conferring genetic susceptibility to RA in a Japanese population. Although PKCη certainly has biologic plausibility as an RA gene, replication studies in other independent populations and/or by family-based tests of association are essential for determining whether our observations are consistent. Further investigations into the molecular mechanisms by which PKCη alters RA susceptibility are also required. These studies may ultimately lead to the development of novel therapies that modulate the PKCη pathway in patients with RA and other autoimmune disorders.
- Top of page
- PATIENTS AND METHODS
- AUTHOR CONTRIBUTIONS
- Supporting Information
Dr. Itakura had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study design. Drs. Takata, Hamada, and Itakura.
Acquisition of data. Drs. Takata, Hamada, Miyatake, Nakano, and Shinomiya, Mr. Scafe, Mr. Reeve, and Mr. Osabe, and Drs. Moritani, Kunika, and Yasui.
Analysis and interpretation of data. Drs. Takata and Hamada.
Manuscript preparation. Drs. Takata, Inoue, and Itakura.
Statistical analysis. Drs. Takata, Kamatani, Inoue, and Itakura.