Genetics of joint inflammation problems and possibilities

Rikard Holmdahl

Medical Inflammation Research, BMC I11, Lund University, S-22184 Lund, Sweden

The search for the heredity of rheumatic diseases is not a new issue for medical science or for millions of people that are affected or have relatives that are affected. The presence of rheumatic diseases is impossible to avoid; they are easy to feel, to see and to diagnose. In addition, we nowadays have large resources of medical records and we know the genetic sequence of humans. So why have we not yet found the genetic basis of common diseases like rheumatic diseases? And, if we find the causative genes and the environmental factors, will we then be able to prevent these diseases? With these scientific tools and resources it should be appropriate today to aim for a zero tolerance for these diseases. Although, we have had only limited success so far we can now better identify the problems and see the possibilities and it should be within reach to completely eliminate many of these diseases.

This book is intended to update the state of the present knowledge of the genetic cause of rheumatic diseases. Maybe even more importantly we will describe some of the forthcoming tools, which will be used to build the bridge over the gap to fulfil the zero tolerance against rheumatic disease.

Rheumatic disease is indeed a heterogeneous group of diseases and in the book we will mainly discuss the rheumatic inflammatory diseases like rheumatoid arthritis (RA). Rheumatoid arthritis involves an inflammatory destructive attack on peripheral joints and is mainly classified using criteria reflecting signs and symptoms resulting in this attack. However, the disease starts years before this happens and the underlying factors triggering the disease or maintaining its chronicity are largely unknown. These disease pathways are likely to be quite diverse and could involve autoreactive T and B lymphocytes, activated macrophages, transformed fibroblasts and pathogenic production of cytokines. Many of these pathways are also likely to be shared with other inflammatory diseases, like ankylosing spondylitis, systemic lupus erythematosus (SLE) and type I diabetes.

To dissect the genetic causes and the disease pathways it is of critical importance to clinically define the specific subforms of these diseases, and to understand their occurrence in different populations.

The Hereditary Basis of Rheumatic Diseases, edited by Rikard Holmdahl © 2006 Birkhäuser Verlag Basel/Switzerland

In the first chapter Jane Worthington and co-authors review the epidemiology and genetics of rheumatoid arthritis (RA), discussing the different methods to closer define the genetic contribution. As they point out there are limitations in these approaches reflecting the genetic and population complexity as well as the heterogeneity on how the disease and disease pathways are defined. Cor Verweij and coauthors continue describing how it is possible to better define the disease using gene expression analysis in which they provide evidence for subdivision of the disease and ways to define the different disease pathways - information that will be of clear importance in the further work to define the involved genes. Clearly RA is a polygenic disease (caused by many genes) and is complex (interacting with environments and genes) and has proven to be a very difficult nut to crack for geneticists. There are a few indications of some of the genes associated with various rheumatic diseases and the scientists that identified the first genes describe their findings in the forthcoming chapters. Ryo Yamada and Kazuhiko Yamamoto describe the identification of the PADI4 and the SLC22A4/A5 genes as being associated with RA in the Japanese population. The PADI4 gene is of particular importance as this codes for the enzyme critical for formation of citrullinated amino acids, recently shown to be a common autoimmune target in RA. The function of the SLC22A4/A5 gene is still unclear but interesting it interacts with a gene coding for the transcription factor RUNX that may also be of importance in SLE, as is discussed by Marta Alarcon-Riquelme and Sergey Kozyrev. The latter authors also describe the importance of the PDCD1 gene in SLE and which may also play a role in RA, demonstrating shared pathways in the different rheumatic diseases. Deletion of the PDCD1 gene has previously been shown to cause lupus in mice, which opens the possibility of closer studying of the pathogenic mechanisms. Recently, a gene coding for an intracellular tyrosine phosphatase, PTPN22, was found by Peter Gregersen and co-workers to be associated not only with SLE but also with RA, again demonstrating the sharing of pathways between inflammatory diseases.

A demonstration of the difficulties in identifying and proving the role of specific genes, and thereby opening them for studies of their role in the pathogenesis, is the major histocompatibility region (MHC). Association with MHC occurs in basically all inflammatory rheumatic diseases and has been demonstrated to be possibly the strongest association than any other gene region. However, in no cases so far has the disease associated gene in the MHC region been conclusively identified, although there are strong circumstantial evidence for MHC Class II genes in RA, MHC Class I genes in psoriasis arthritis and the Class I gene HLA B27 in ankylosing spondylitis. Of these examples the strongest evidence for association is the B27 gene, yet we do not know its precise role. This is addressed by Joachim Sieper and Martin Rudwaleit who discuss ways to understand the function of B27 and of anky-losing spondylitis. This demonstrates that even with strong evidence for the involved genes we need tools to understand their function as well as for developing preventive and therapeutic therapies based on these findings.

Possibly the greatest success of medical science during the last one or two decades has been the identification of causative genes in monogenic diseases. There are many such diseases but each of them affects a very limited number of individuals in the population. This has led, at least in some cases, to the possibility for treatment and prevention. However, maybe the most important benefit from these studies have been an increased understanding of basic biology and disease pathways, which helps us to understand the more common complex diseases. The difficulties in making similar progress in complex disease related to the fact that each contributing gene is not fully penetrant and that the genetic contribution operates in patterns of genes rather than by single genes. A way to overcome these difficulties will be to increase statistical power, i.e., to include thousands or millions of individuals in the analysis and to compare their genomes with their diseases. The technologies for such approaches are emerging but there are also ethical, logistic and analytic problems. A simplifying factor is that each individual of the human population of today consists of a mosaic of genetic fragments derived from the bottleneck of human speciation, occurring some 150-200,000 years ago. Keeping track of these genetic fragments, or haplotypes, could open the possibility to analyse which set of haplotypes are associated with specified diseases. The technology for such analysis might seem to be science fiction but is in fact already present as emerging tools, which is described by Ulf Landegren who is inventor of many of such tools and who describes the possibilities to use them in the future. Although genetics seem to be complex the advantage is that it consists of definite letter codes, just as computers, which simplifies the analysis. Obviously, from our limited success so far in cracking the genetic codes for complex diseases like rheumatic disease, it still contains considerable complexity. However, the complexity increases one step further when we analyse the expression of these genes. The expression of the genes is clearly a level between the genes and disease expression and methods to describe gene expression and relating this to diseases are also recently and rapidly developing technologies. This will clearly be useful for both diagnosis and understanding of the diseases but are still, as the genomic tools, difficult to analyse as is discussed by Thomas Haupl and co-authors.

Another, but classical, way to handle complex problems in medical science is the use of experimental animal models. Animal models, from worms to chimpanzees, have proven very relevant in studies of critical biological pathways, which is best exemplified by the discovery of cellular apoptosis in humans through studies on the microscopic worm Caenorhabditis elegans. Rodents have proven to be a very useful compromise between relevance and possibilities for studies of human diseases and much of the fundament of medical knowledge is today based on inbred mouse strains. Also, models for rheumatoid diseases have proven to be useful and mouse models are today required by FDA (Food and Drug Administration) in the US for the development of new therapies for RA. There has been a rapid development in developing technologies in using such animal models. One of these tools is the pos sibility to genetically manipulate the animal genome, allowing the possibility to make controlled genetic changes in the genome and study its effect on the complex in vivo situation. One example on how this can be used is discussed by Kary Latham, Edward Rosloniec and colleagues who describe how mice can be 'humanised' by inserting relevant human MHC Class II genes and study their impact on models for rheumatoid arthritis. This enables possibilities to confirm the role of human genes and to study their function and therapeutic possibilities in vivo. These studies are based on the strikingly similar results using the corresponding mouse genes and will be a powerful tool for further studies. There is, however, also a raising awareness that genetic manipulation of mice may also introduce abnormalities that divert the results from reality. Introduction of deletions or the introduction of foreign genes may not cooperate well with the rest of the mouse genome. An alternative look at this problem would be to use the mice as we use the humans, to search for the naturally polymorphic DNA sequences that cause disease, with the assumption that mice and humans are close enough to share some of the major disease pathways. Shimon Sakaguchi and co-authors give one example in which they describe the search for genes causing a spontaneous development of arthritis in mice. The major causative gene was identified to be ZAP70, in which the arthritis-prone mice had an amino acid replacement mutation. This clearly points out the threshold for T cell receptor signalling as being critical for development of arthritis and the model is now open for further analysis of the pathways as well as translating the results into the corresponding pathway affecting human arthritis. Another way to identify relevant genes is described by Peter Olofsson who describe the use of crosses of inbred rat strains that are susceptible versus resistant to arthritis. Using such crosses it is possible to make linkage analysis with a power thousand-fold larger than the human studies, since the strains are inbred, the disease more precisely characterised and the environment better controlled. They could identify one of the genes of importance for development of arthritis severity, Ncfl, which controls a pathway regulating oxidative burst. In fact, lower oxidative burst led to increased arthritis severity. He also shows that this finding could be utilised to develop a new therapeutic strategy that could have potential for treatment of human disease. Thus, identification of the genes in the animal models may not only enable identification of genes in complex disease, but also provides a tool to shorten the time to develop the findings into therapy for human disease. Obviously, it will in most cases not be the genetic polymorphism per se that is the critical target for prevention or therapy but rather the critical pathways leading to disease.

B. Genetic studies on rheumatic diseases

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