A genome-wide homozygosity association study identifies runs of homozygosity associated with rheumatoid arthritis in the human major histocompatibility complex

Rheumatoid arthritis (RA) is a chronic inflammatory disorder with a polygenic mode of inheritance. This study examined the hypothesis that runs of homozygosity (ROHs) play a recessive-acting role in the underlying RA genetic mechanism and identified RA-associated ROHs. Ours is the first genome-wide homozygosity association study for RA and characterized the ROH patterns associated with RA in the genomes of 2,000 RA patients and 3,000 normal controls of the Wellcome Trust Case Control Consortium. Genome scans consistently pinpointed two regions within the human major histocompatibility complex region containing RA-associated ROHs. The first region is from 32,451,664 bp to 32,846,093 bp (-log10(p)>22.6591). RA-susceptibility genes, such as HLA-DRB1, are contained in this region. The second region ranges from 32,933,485 bp to 33,585,118 bp (-log10(p)>8.3644) and contains other HLA-DPA1 and HLA-DPB1 genes. These two regions are physically close but are located in different blocks of linkage disequilibrium, and ～40% of the RA patients' genomes carry these ROHs in the two regions. By analyzing homozygote intensities, an ROH that is anchored by the single nucleotide polymorphism rs2027852 and flanked by HLA-DRB6 and HLA-DRB1 was found associated with increased risk for RA. The presence of this risky ROH provides a 62% accuracy to predict RA disease status. An independent genomic dataset from 868 RA patients and 1,194 control subjects of the North American Rheumatoid Arthritis Consortium successfully validated the results obtained using the Wellcome Trust Case Control Consortium data. In conclusion, this genome-wide homozygosity association study provides an alternative to allelic association mapping for the identification of recessive variants responsible for RA. The identified RA-associated ROHs uncover recessive components and missing heritability associated with RA and other autoimmune diseases.     

Genetic and Molecular Basis of QTL of Diabetes in Mouse: Genes and Polymorphisms

A systematic study has been conducted of all available reports in PubMed and OMIM (Online Mendelian Inheritance in Man) to examine the genetic and molecular basis of quantitative genetic loci (QTL) of diabetes with the main focus on genes and polymorphisms. The major question is, What can the QTL tell us? Specifically, we want to know whether those genome regions differ from other regions in terms of genes relevant to diabetes. Which genes are within those QTL regions, and, among them, which genes have already been linked to diabetes? whether more polymorphisms have been associated with diabetes in the QTL regions than in the non-QTL regions.Our search revealed a total of 9038 genes from 26 type 1 diabetes QTL, which cover 667,096,006 bp of the mouse genomic sequence. On one hand, a large number of candidate genes are in each of these QTL; on the other hand, we found that some obvious candidate genes of QTL have not yet been investigated. Thus, the comprehensive search of candidate genes for known QTL may provide unexpected benefit for identifying QTL genes for diabetes. Key Words: Quantitative trait loci, type 1 diabetes, insulin-dependent diabetes mellitus (IDDM), candidate gene, polymorphism, mouse.     

Enrichment of Genetic Variants for Rheumatoid Arthritis within T-Cell and NK-Cell Enhancer Regions

To identify disease-causative variants, we intersected the published results of a metaanalysis of genome-wide association studies (GWAS) for rheumatoid arthritis (RA) with the set of enhancer regions for 71 primary cell types that was provided by the FANTOM consortium. We first retrieved all single nucleotide polymorphisms (SNPs) that are associated (P < 5 × 10⁸) with RA in the GWAS meta-analysis and that are located in any of these enhancer regions. After excluding the major histocompatibility complex (MHC) region, we identified 50 such RA-associated SNPs that are located in enhancer regions. Enhancer sets from different cell types were then compared with each other for their number of RA-associated SNPs by permutation analysis. This analysis showed that RA-associated SNPs are preferentially located in enhancers from several immunological cell types. In particular, we see a strong relative enrichment in enhancer regions that are active in T cells (P < 0.001) and NK cells (P < 0.001). Several loci display multiple RA-associated SNPs in tight linkage disequilibrium that are located within the same or neighboring enhancers. These haplotypes may have a greater likelihood to influence enhancer activity than any SNP on its own. Taken together, these results support the hypothesis that RA-causative variants often act through altering the activity of immune cell enhancers. The enrichment in T-cell and NK-cell enhancer regions indicates that expression changes in these cell types are particularly relevant for the pathogenesis of RA. The specific SNPs that account for this enrichment can be used as a basis for focused genotype-phenotype studies of these cell types.     

Quantitative trait loci,genes, and polymorphisms that regulate bone mineral density in mouse

This is an in silico analysis of data available from genome-wide scans. Through analysis of QTL, genes and polymorphisms that regulate BMD, we identified 82 BMD QTL, 191 BMD-associated (BMDA) genes, and 83 genes containing known BMD-associated polymorphisms (BMDAP). The catalogue of all BMDA/BMDAP genes and relevant literatures are provided. In total, there are substantially more BMDA/BMDAP genes in regions of the genome where QTL have been identified than in non-QTL regions. Among 191 BMDA genes and 83 BMDAP genes, 133 and 58 are localized in QTL regions, respectively. The difference was still noticeable for the chromosome distribution of these genes between QTL and non-QTL regions. These results have allowed us to generate an integrative profile of QTL, genes, polymorphisms that determine BMD. These data could facilitate more rapid and comprehensive identification of causal genes underlying the determination of BMD in mouse and provide new insights into how BMD is regulated in humans.     

A systems genetics approach provides a bridge from discovered genetic variants to biological pathways in rheumatoid arthritis

Genome-wide association studies (GWAS) have yielded novel genetic loci underlying common diseases. We propose a systems genetics approach to utilize these discoveries for better understanding of the genetic architecture of rheumatoid arthritis (RA). Current evidence of genetic associations with RA was sought through PubMed and the NHGRI GWAS catalog. The associations of 15 single nucleotide polymorphisms and HLA-DRB1 alleles were confirmed in 1,287 cases and 1,500 controls of Japanese subjects. Among these, HLA-DRB1 alleles and eight SNPs showed significant associations and all but one of the variants had the same direction of effect as identified in the previous studies, indicating that the genetic risk factors underlying RA are shared across populations. By receiver operating characteristic curve analysis, the area under the curve (AUC) for the genetic risk score based on the selected variants was 68.4%. For seropositive RA patients only, the AUC improved to 70.9%, indicating good but suboptimal predictive ability. A simulation study shows that more than 200 additional loci with similar effect size as recent GWAS findings or 20 rare variants with intermediate effects are needed to achieve AUC = 80.0%. We performed the random walk with restart (RWR) algorithm to prioritize genes for future mapping studies. The performance of the algorithm was confirmed by leave-one-out cross-validation. The RWR algorithm pointed to ZAP70 in the first rank, in which mutation causes RA-like autoimmune arthritis in mice. By applying the hierarchical clustering method to a subnetwork comprising RA-associated genes and top-ranked genes by the RWR, we found three functional modules relevant to RA etiology: “leukocyte activation and differentiation”, “pattern-recognition receptor signaling pathway”, and “chemokines and their receptors”.These results suggest that the systems genetics approach is useful to find directions of future mapping strategies to illuminate biological pathways.     

Genetic basis of rheumatoid arthritis: A current review

Rheumatoid arthritis (RA) is one of the most common autoimmune diseases. As with other complex traits, genome-wide association studies (GWASs) have tremendously enhanced our understanding of the complex etiology of RA. In this review, we describe the genetic architecture of RA as determined through GWASs and meta-analyses. In addition, we discuss the pathologic mechanism of the disease by examining the combined findings of genetic and functional studies of individual RA-associated genes, including HLA-DRB1, PADI4, PTPN22, TNFAIP3, STAT4, and CCR6. Moreover, we briefly examine the potential use of genetic data in clinical practice in RA treatment, which represents a challenge in medical genetics in the post-GWAS era.     

Genomic dissection and prioritizing of candidate genes of QTL for regulating spontaneous arthritis on chromosome 1 in mice deficient for interleukin-1 receptor antagonist

Rheumatoid arthritis is a heterogeneous disease with clinical and biological polymorphisms. IL-1RN is a protein that binds to interleukin-1 (IL-1) receptors and inhibits the binding of IL-1-alpha and IL-1-beta. IL-1RN levels are elevated in the blood of patients with a variety of infectious, immune, and traumatic conditions. Balb/c mice deficient in IL-1ra (mouse gene of IL-1RN) develop spontaneous autoimmune arthritis while DBA/1 mice deficient in IL-1ra do not. Previously, we identified a major QTL that regulates the susceptibility to arthritis in Balb/c mice with IL-1ra deficiency. In this study, we found that the QTL may contain two peaks that are regulated by two sets of candidate genes. By haplotype analysis, the total genomic regions of candidate genes were reduced from about 19 Mbp to approximately 9 Mbp. The total number of candidate genes was reduced from 208 to 21.     

Genetic architecture of the dog: sexual size dimorphism and functional morphology

Purebred dogs are a valuable resource for genetic analysis of quantitative traits. Quantitative traits are complex, controlled by many genes that are contained within regions of the genome known as quantitative trait loci (QTL). The genetic architecture of quantitative traits is defined by the characteristics of these genes: their number, the magnitude of their effects, their positions in the genome and their interactions with each other. QTL analysis is a valuable tool for exploring genetic architecture, and highlighting regions of the genome that contribute to the variation of a trait within a population.     

Association of MHC and rheumatoid arthritis. HLA polymorphisms in phenotypic variants of rheumatoid arthritis

Genes in the human leukocyte antigen (HLA) region remain the most powerful disease risk genes in rheumatoid arthritis (RA). Several allelic variants of HLA-DRB1 genes have been associated with RA, supporting a role for T-cell receptor-HLA-antigen interactions in the pathologic process. Disease-associated HLA-DRB1 alleles are similar but not identical and certain allelic variants are preferentially enriched in patient populations with defined clinical characteristics. Also, a gene dosing effect of HLA-DRB1 alleles has been suggested by the accumulation of patients with two RA-associated alleles, especially in patient subsets with a severe disease course. Therefore, polymorphisms in HLA genes are being explored as tools to dissect the clinical heterogeneity of the rheumatoid syndrome. Besides HLA polymorphisms, other risk genes will be helpful in defining genotypic profiles correlating with disease phenotypes. One such phenotype is the type of synovial lesion generated by the patient. HLA genes in conjunction with other genetic determinants may predispose patients to a certain pathway of synovial inflammation. Also, patients may or may not develop extraarticular manifestations, which are critical in determining morbidity and mortality. HLA genes, complemented by other RA risk genes, are likely involved in shaping the T-cell repertoire, including the emergence of an unusual T-cell population characterized by the potential of vascular injury, such as seen in extraarticular RA.     

Association of MHC and rheumatoid arthritis: HLA polymorphisms in phenotypic variants of rheumatoid arthritis

Genes in the human leukocyte antigen (HLA) region remain the most powerful disease risk genes in rheumatoid arthritis (RA). Several allelic variants of HLA-DRB1 genes have been associated with RA, supporting a role for T-cell receptor-HLA-antigen interactions in the pathologic process. Disease-associated HLA-DRB1 alleles are similar but not identical and certain allelic variants are preferentially enriched in patient populations with defined clinical characteristics. Also, a gene dosing effect of HLA-DRB1 alleles has been suggested by the accumulation of patients with two RA-associated alleles, especially in patient subsets with a severe disease course. Therefore, polymorphisms in HLA genes are being explored as tools to dissect the clinical heterogeneity of the rheumatoid syndrome. Besides HLA polymorphisms, other risk genes will be helpful in defining genotypic profiles correlating with disease phenotypes. One such phenotype is the type of synovial lesion generated by the patient. HLA genes in conjunction with other genetic determinants may predispose patients to a certain pathway of synovial inflammation. Also, patients may or may not develop extraarticular manifestations, which are critical in determining morbidity and mortality. HLA genes, complemented by other RA risk genes, are likely involved in shaping the T-cell repertoire, including the emergence of an unusual T-cell population characterized by the potential of vascular injury, such as seen in extraarticular RA.     

Re-Sequencing Data for Refining Candidate Genes and Polymorphisms in QTL Regions Affecting Adiposity in Chicken

In this study, we propose an approach aiming at fine-mapping adiposity QTL in chicken, integrating whole genome re-sequencing data. First, two QTL regions for adiposity were identified by performing a classical linkage analysis on 1362 offspring in 11 sire families obtained by crossing two meat-type chicken lines divergently selected for abdominal fat weight. Those regions, located on chromosome 7 and 19, contained a total of 77 and 84 genes, respectively. Then, SNPs and indels in these regions were identified by re-sequencing sires. Considering issues related to polymorphism annotations for regulatory regions, we focused on the 120 and 104 polymorphisms having an impact on protein sequence, and located in coding regions of 35 and 42 genes situated in the two QTL regions. Subsequently, a filter was applied on SNPs considering their potential impact on the protein function based on conservation criteria. For the two regions, we identified 42 and 34 functional polymorphisms carried by 18 and 24 genes, and likely to deeply impact protein, including 3 coding indels and 4 nonsense SNPs. Finally, using gene functional annotation, a short list of 17 and 4 polymorphisms in 6 and 4 functional genes has been defined. Even if we cannot exclude that the causal polymorphisms may be located in regulatory regions, this strategy gives a complete overview of the candidate polymorphisms in coding regions and prioritize them on conservation- and functional-based arguments.     

Identification of a novel inflammation-protective locus in the Fischer rat

Inbred LEW/N rats are relatively susceptible, while histocompatible inbred F344/N rats are relatively resistant to development of a wide variety of inflammatory diseases in response to a range of pro-inflammatory stimuli. In a LEW/N vs. F344/N F2 intercross, we identified a quantitative trait locus (QTL) on Chr 10 that protects in a dominant fashion against the exudate volume component of innate inflammation in the F344/N rat, as well as a suggestive QTL on Chr 2 near the Fibrinogen cluster region. The exudate volume linkage region on Chr 10 may be similar to one of the multiple regions found to link to inflammatory arthritis phenotypes in other crosses. The suggestive linkage on Chr 2 has not been previously reported and does not seem to contribute to this phenotype in the same manner as the QTL on Chr 10. These findings are consistent with the hypothesis that the innate exudate volume trait is a sub-phenotype of more complex inflammatory phenotypes, such as arthritis, and genes within the Chr 10 linkage region could account for differences in this non-specific acute phase component of the inflammatory response. Since the rat Chr 10 exudate volume linkage region we have identified is syntenic with a region of human Chr 17 that has been shown to link to a variety of autoimmune/inflammatory diseases, including insulin-dependent diabetes mellitus, multiple sclerosis, and psoriasis, identification of genes within this linkage region will shed light on genes relevant to the earliest inflammatory component and to susceptibility and resistance to such human autoimmune/inflammatory diseases. Received: 4 August 1998 / Accepted: 4 December 1998     

Detection of selection signatures within candidate regions underlying trypanotolerance in outbred cattle populations

Breeding indigenous African taurine cattle tolerant to trypanosomosis is a straightforward approach to control costs generated by this disease. A recent study identified quantitative trait loci (QTL) underlying trypanotolerance traits in experimental crosses between tolerant N'Dama and susceptible Boran zebu cattle. As trypanotolerance is thought to result from local adaptation of indigenous cattle breeds, we propose an alternative and complementary approach to study the genetic architecture of this trait, based on the identification of selection signatures within QTL or candidate genes. A panel of 92 microsatellite markers was genotyped on 509 cattle belonging to four West African trypanotolerant taurine breeds and 10 trypanosusceptible European or African cattle breeds. Some of these markers were located within previously identified QTL regions or candidate genes, while others were chosen in regions assumed to be neutral. A detailed analysis of the genetic structure of these different breeds was carried out to confirm a priori grouping of populations based on previous data. Tests based on the comparison of the observed heterozygosities and variances in microsatellite allelic size among trypanotolerant and trypanosusceptible breeds led to the identification of two significantly less variable microsatellite markers. BM4440, one of these two outlier loci, is located within the confidence interval of a previously described QTL underlying a trypanotolerance-related trait.
Detection of selection signatures appears to be a straightforward approach for unravelling the molecular determinism of trypanosomosis pathogenesis. We expect that a whole genome approach will help confirm these results and achieve a higher resolving power.     

Genes and environment in arthritis: can RA be prevented?

Understanding of how interactions between genes and environment contribute to the development of arthritis is a central issue in understanding the etiology of rheumatoid arthritis (RA), as well as for eventual subsequent efforts to prevent the disease. In this paper, we review current published data on genes and environment in RA as well as in certain induced animal models of disease, mainly those in which adjuvants only or adjuvants plus organ-specific autoantigens are used to induce arthritis. We refer to some new data on environmental and genetic factors of importance for RA generated from a large case-control study in Sweden (1200 patients, 1200 matched controls). We found an increased risk of seropositive but not of seronegative RA in smokers, and there are indications that this effect may be due to a gene-environment interaction involving MHC class II genes. We also found an increased risk of RA in individuals heavily exposed to mineral oils. This was of particular interest because mineral oils are strong inducers of arthritis in certain rodent strains and because polymorphisms in human genetic regions syntenic with genes predisposing for oil-induced arthritis in rats have now been shown to associate with RA in humans. Taken together, our data support the notion that concepts and data on gene-environment interactions in arthritis can now be taken from induced animal models of arthritis to generate new etiological hypotheses for RA.     

Precision and high-resolution mapping of quantitative trait loci by use of recurrent selection,backcross or intercross schemes

Dissecting quantitative genetic variation into genes at the molecular level has been recognized as the greatest challenge facing geneticists in the twenty-first century. Tremendous efforts in the last two decades were invested to map a wide spectrum of quantitative genetic variation in nearly all important organisms onto their genome regions that may contain genes underlying the variation, but the candidate regions predicted so far are too coarse for accurate gene targeting. In this article, the recurrent selection and backcross (RSB) schemes were investigated theoretically and by simulation for their potential in mapping quantitative trait loci (QTL). In the RSB schemes, selection plays the role of maintaining the recipient genome in the vicinity of the QTL, which, at the same time, are rapidly narrowed down over multiple generations of backcrossing. With a high-density linkage map of DNA polymorphisms, the RSB approach has the potential of dissecting the complex genetic architecture of quantitative traits and enabling the underlying QTL to be mapped with the precision and resolution needed for their map-based cloning to be attempted. The factors affecting efficiency of the mapping method were investigated, suggesting guidelines under which experimental designs of the RSB schemes can be optimized. Comparison was made between the RSB schemes and the two popular QTL mapping methods, interval mapping and composite interval mapping, and showed that the scenario of genomic distribution of QTL that was unlocked by the RSB-based mapping method is qualitatively distinguished from those unlocked by the interval mapping-based methods.     

Insight from genome-wide association studies in rheumatoid arthritis and multiple sclerosis

Autoimmune diseases are caused by multiple genes and environmental effects. In addition, genetic contributions and the number of associated genes differ among different diseases and ethnic populations. Genome-wide association studies (GWAS) on rheumatoid arthritis (RA) and multiple sclerosis (MS) show that these diseases share many genetic factors. Recently, in addition to the major histocompatibility complex (MHC) gene, other genetic loci have been found to be associated with the risk for autoimmune diseases. This review focuses on the search for genetic variants that influence the susceptibility to RA and MS as typical autoimmune diseases and discusses the future of GWAS.