IMPORTANCE OF TRABECULAR BONE SCORE IN FRACTURE RISK PREDICTION IN RHEUMATOID ARTHRITIS AND ANKYLOSING SPONDYLITIS.

One of the most deleterious eff ectsinduced by the chronic inflammation is bone loss.Fracture is one of the most common comorbidities in rheumatoid arthritis (RA) patients, especially patients using glucocorticoids. Bone mineral density (BMD) by dual-energy x-ray absorptiometry (DXA) is the gold standard of diagnosing and monitoring osteoporosis but does not entirely explain the fracture risk in patients suffering from systemic inflammatory diseases. A number of fractures are observed in patients with T-scores, which are not in the osteoporotic range. Th is discrepancy may be related to alterations of bone quality and measurements of bone mineral density are overestimated. A challenge in clinical practice is to detect patients with a risk of having fractures although their BMD is in osteopenia. The trabecular bone score (TBS), novel texture parameter reflects degradation of trabecular bone and therefore could be used as another bone measure to predict the risk of fragility fracture. Little is known about the importance of TBS in fracture risk prediction in systemic inflammatory disease and about the influence of biologic treatment on TBS changes. Because the same cytokines are involved in local and systemic bone loss, it is rational to assume that biologics may influence bone turnover and systemic bone loss. Several new studies showed that therapies targeting specific cytokines and its signaling pathways with biologic DMARDs may protect the skeleton but outcomes in these clinical studies were based mostly on bone turnover markers and BMD changes. We compared the effects of biological disease-modifying antirheumatic drugs (bDMARDs) and conventional synthetic (cs) DMARDs (methotrexate) on BMD, bone turnover markers (BTM) and trabecular bone score (TBS) in patients suffering from active RA. Methods: A 12-month prospective trial in 105 active RA patients. Results: Treatment with bDMARDS led to increase of 1.7 % (p<0.05) in TBS but not on BMD. The greatest TBS increase (2.7%, p<0.05) was observed in premenopausal females treates with bDMARDs. No effect of csDMARDS on measured parameters was observed. Based on our observation and literature data TBS could contribute to fracture risk prediction especially in RA patients with osteopenia. Although several studies reported favorable actions of biologic therapies on bone protection, there are still unmet needs for studies regarding their actions on the risk of bone fractures

Osteoarticular Changes in Acromegaly

Acromegaly is caused by hypersecretion of growth hormone (GH) and consequently of insulin-like growth factor-I (IGF-1) due to pituitary tumor. Other causes, such as increased growth-hormone releasing hormone (GHRH) production, ectopic GHRH production, and ectopic GH secretion, are rare. Growth hormone and IGF-1 play a role in the regulation of bone metabolism, but accurate effect of growth hormone excess on bone is not fully explained. The issue of osteoarticular manifestations is still very actual, due to development of complications in the majority of patients with acromegaly. Traditionally, acromegaly is considered as a cause of secondary osteoporosis. Nowadays, it is discussed if BMD as predictor of osteoporotic fractures in acromegalic patient is decreased or even normal. Thus, bone quality remains to be more important in assessment of fracture risk. GH excess leads to increased bone turnover, defined by changes of bone markers. The articular manifestations are frequent clinical complications and may be present as the earliest symptom in a significant proportion of acromegalic patients. Articular manifestations are the main causes of morbidity and immobility of these patients, and they are persistent even after successful treatment. Quick recognition of osteoarticular changes and aiming the therapy lead to decrease in complication number

McCune-Albright syndrome

McCune-Albright syndrome (MAS) is a very rare disease characterizedby the triad of bone defects, skin hyperpigmentation, andvarious types of endocrine and non-endocrine manifestations. Itfalls into the category of sporadic genetic disorders and its exactincidence is unknown. In its more severe forms, the disease manifestsitself already in early childhood and can gradually affectmore and more organs throughout life. The extent and degree ofinvolvement of affected tissues are heterogeneous due to themosaicism of the genetic mutation. The disease is the subject ofextensive research and new pathogenetic mechanisms are beingelucidated, leading to new diagnostic and therapeutic choices. Inaddition, the authors present a case report of an adult femalepatient with McCune-Albright syndrome. The clinical picture isdominated by bone involvement, thyroid hyperfunction and persistenthyperestrogenism. The case report underlines the fact thatmanagement of patients with McCune-Albright syndrome continuesto be a challenge

A Combination of CD28 (rs1980422) and IRF5 (rs10488631) Polymorphisms Is Associated with Seropositivity in Rheumatoid Arthritis: A Case Control Study.

INTRODUCTION:The aim of the study was to analyse genetic architecture of RA by utilizing multiparametric statistical methods such as linear discriminant analysis (LDA) and redundancy analysis (RDA). METHODS:A total of 1393 volunteers, 499 patients with RA and 894 healthy controls were included in the study. The presence of shared epitope (SE) in HLA-DRB1 and 11 SNPs (PTPN22 C/T (rs2476601), STAT4 G/T (rs7574865), CTLA4 A/G (rs3087243), TRAF1/C5 A/G (rs3761847), IRF5 T/C (rs10488631), TNFAIP3 C/T (rs5029937), AFF3 A/T (rs11676922), PADI4 C/T (rs2240340), CD28 T/C (rs1980422), CSK G/A (rs34933034) and FCGR3A A/C (rs396991), rheumatoid factor (RF), anti-citrullinated protein antibodies (ACPA) and clinical status was analysed using the LDA and RDA. RESULTS:HLA-DRB1, PTPN22, STAT4, IRF5 and PADI4 significantly discriminated between RA patients and healthy controls in LDA. The correlation between RA diagnosis and the explanatory variables in the model was 0.328 (Trace = 0.107; F = 13.715; P = 0.0002). The risk variants of IRF5 and CD28 genes were found to be common determinants for seropositivity in RDA, while positivity of RF alone was associated with the CTLA4 risk variant in heterozygous form. The correlation between serologic status and genetic determinants on the 1st ordinal axis was 0.468, and 0.145 on the 2nd one (Trace = 0.179; F = 6.135; P = 0.001). The risk alleles in AFF3 gene together with the presence of ACPA were associated with higher clinical severity of RA. CONCLUSIONS:The association among multiple risk variants related to T cell receptor signalling with seropositivity may play an important role in distinct clinical phenotypes of RA. Our study demonstrates that multiparametric analyses represent a powerful tool for investigation of mutual relationships of potential risk factors in complex diseases such as RA

SNPs associated with seropositivity in RA.

<p>Redundancy discrimination analysis plot showing that IRF5, CD28 and CTLA4 are associated with seropositivity in RA patients. RF+–rheumatoid factor positive RA patients; RF-–rheumatoid factor negative RA patients; ACPA+–anti-citrullinated peptides antibodies positive RA patients; ACPA-–anti-citrullinated peptides antibodies negative RA patients; SE (0,1,2)—number of shared epitope coding alleles in HLA-DRB1 gene (✧); IRF5 (CC, CT, TT)—genotypes in IRF5 gene (C risk allele) (▷); CD28 (CC, CT, TT)–genotypes in CD28 gene (C risk allele) (◁); CTLA4 (AG, GG, AA)–genotypes in CTLA4 gene (G risk allele) (◊). Diagram reading clue: Symbols are genetic factors. Large bold symbols represent genotypes significantly influencing the presence of RF and ACPA. Small empty symbols represent other genotypes of selected genes. Direction of arrow indicates which serologic status is associated with the genetic parameters and the length of the arrow indicates the magnitude of the association.</p

Factors associated with clinical severity in RA.

<p>Redundancy analysis plot showing that risk alleles in AFF3 gene, together with ACPA positivity are associated with higher clinical severity of RA. ACPA—anti-citrullinated peptides antibodies (□); <i>AFF3</i> (TT, AT, AA)–genotypes in <i>AFF3</i> gene (T risk allele) (▽). Diagram reading clue: Symbols are genetic and serologic factors. Large bold symbols represent genotypes and antibody presence significantly influencing the clinical parameters of disease severity (DAS28, CRP, ESR, TJC, SJC, HAQ-DI). Small empty symbols represent other factors and genotypes of selected genes. Direction of arrow indicates which of the clinical factors are associated with the genetic and serologic parameters and the length of the arrow indicates the magnitude of the association.</p

The genetic discrimination of RA patients and controls.

<p>Linear discrimination analysis diagram shows that shared epitope and single nucleotide polymorphisms in PTPN22, STAT4, IRF5 and PADI4 genes significantly discriminated between RA patients and healthy controls. RA—RA patients; C—control group; SE (0,1,2)—number of SE coding allele in HLA-DRB1 gene (✧); IRF5 (CC, CT, TT)—genotypes in IRF5 gene (C risk allele) (◁); PADI4 (TT, CT, CC)–genotypes in PADI4 gene (T risk allele) (▽); PTPN22 (CC, CT, TT)–genotypes in PTPN22 gene (A risk allele) (△); STAT4 (GG, GT, TT)–genotypes in STAT4 gene (T risk allele) (☐). Diagram reading clue: Small circles represent individual cases. Large grey circles—centroids—represent subject groups (RA patients and controls). Symbols are genetic factors. Large bold symbols represent genotypes significantly influencing the distribution of subjects. Small empty symbols represent other genotypes of selected genes. The closer to the group centroid the gene symbol lies, the stronger is its impact on the classification of subjects to particular group.</p