Myeloid precursors, osteoclastogenesis, and Spondyloarthropathies

Spondyloarthropathies (or Spondyloarthritides; SpAs) are a group of heterogeneous but genetically related inflammatory disorders in which ankylosing spondylitis (AS) is considered the prototypic form. Among the genes associated with AS, HLA-B27 allele has the strongest association although the cause is still not clear. Rats transgenic for the human HLA-B27 gene (B27 rats) develop a systemic inflammation mirroring the human SpA symptoms and thus provide a useful model to study the contribution of this MHC class I molecule in the disease development. Of particular interest was the observation of absence of arthritis in B27 rats grown in germ-free conditions and a recent theory suggests that microbial dysbiosis and gut inflammation might play a key role in initiating the HLA-B27-associated diseases. Studies in our laboratory have previously demonstrated that HLA-B27 expression alters the development of the myeloid compartment within the bone marrow (BM) in B27 rat and causes loss of a specific dendritic cell (DC) population involved in self-tolerance mechanisms within the gut. The aim of this thesis was to further analyse the myeloid compartment in B27 rats with a particular focus on the osteoclast progenitors and the bone phenotype and to link this to the gut inflammation. In addition, translational studies analysed peripheral monocyte/pre-osteoclasts in AS patients and teased apart the role of cytokines in in vitro human osteoclast differentiation. To understand the dynamics of the myeloid/monocyte compartment within the B27-associated inflammation, monocytes within the bloodstream and BM of B27 rats were characterised via flow cytometry and their ability to differentiate into osteoclast was assessed in vitro. Moreover, an antibiotic regime was used to reduce the B27 ileitis and to evaluate whether this could affect the migration, the phenotype, and the osteoclastogenic potential of B27 monocytes. B27 animals display a systemic and central increase of “inflammatory” CD43low MOs, which are the main contributors to osteoclastogenesis in vitro. Antibiotic treatment reduced ileitis and also reverted the B27 monocyte phenotype. This was also associated with the reduction of the previous described TNFα-enhancement of osteoclast differentiation from B27 BM precursors. These evidences support the idea that in genetically susceptible individuals inflammation in the gut might influence the myeloid compartment within the BM; in other terms, pre-emptively educate precursor cells to acquire specific phenotype end functions after being recruited into the tissue. This might explain the enhanced differentiation of osteoclast from B27 BM progenitors and thus the HLA-B27-associated bone loss. The data shown in this thesis suggest a link between the immunity within the gut and BM haematopoiesis. This provides an attractive and novel research prospective that could help not only to increase the understanding of the HLA-B27-associated aetiopathogenesis but also to unravel the cellular crosstalk that allows the mucosal immunity to program central cell differentiation. Human translational studies on monocyte subsets, cytokines and cytokine network in AS osteoclastogenesis evidenced altered osteoclast differentiation in the presence of IL-22 although no differences in the phenotype and functions of circulating CD14+ monocytes were observed. In addition, studies on the role of TNFα and TNFRs showed a dual role of this inflammatory cytokine in the human OC differentiation. In particular, the activation of TNFR1 in monocytes in early osteoclastogenesis inhibits OC differentiation while TNFα-biasing for TNFR2 on osteoclast precursors mediates the osteoclastogenic effect. Whether similar mechanisms are involved in the TNFα-mediated joint destruction in human rheumatic diseases needs further investigations. This could contribute to the development of novel and more specific anti-TNFα agents for the treatment of bone erosion. In conclusion, taken together my studies support the idea of a crosstalk between the periphery and the central system during the inflammatory response and provide new insights to the mechanisms behind the enhancement of osteoclastogenesis in B27-associated disorders.

Estimation of whole body muscle, adipose/fat mass, validation in health and during weight loss. Development of prediction equations using MRI as reference method

Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.