Rheumatoid arthritis (RA), which affects 1% of the world’s population, is an autoimmune disease characterized by chronic inflammation of the synovial tissue.

Events that occur within the synovial tissues of rheumatoid arthritis are responsible for the signs, symptoms and possible destruction of the joint structures that lead to dysfunction and motor disability.

There is increasing evidence that the current understanding of rheumatoid arthritis is moving beyond previous concepts that see this disease as the consequence of a single auto-antigen targeted autoimmune response.

Rather, a new view of rheumatoid arthritis is emerging, trying to understand this disease as the product of cell-cell interactions that occur within a unique and defined cellular environment, the synovium.

The three most abundant cell populations found in the synovium are: synovial macrophages (type A synovial cells), synovial fibroblasts (type B synoviocytes) and infiltrating T lymphocytes.

Before introducing you to this new vision, we want to explain what the difference is between a healthy synovium and a synovium affected by RA to underline the importance of a characterized cellular environment.

In a healthy condition, the synovial membrane contains relatively few cells.

It consists of: a layer of intimal coating, the thickness of which is comparable to ¼ of the thickness of a hair and, within this layer, we also identify cells like type B synoviocytes, type A synoviocytes and infiltrating T lymphocytes .

An underlying layer of well-vascularized connective tissue, containing collagen fibers and FLS (fibroblast-like synoviocytes, contribute to joint destruction through their production of cytokines) and MLS (macrophage-like synoviocytes, cells that can phagocyte and thus eliminate debris and cellular waste) dispersed uniformly and homogeneously (11).

The synovial membrane is essential as it controls the transport of cells and maintains the composition of the synovial fluid, promoting overall joint integrity.

In RA, the synovial tissue becomes inflamed, causing a noticeable increase in cellular infiltration.

The latter causes the intimal lining to expand up to 5-10 times its normal thickness.

A disorder of the previously mentioned cellular order is created. The harmony and interaction between cells is interrupted, the inflammatory signals are activated and released together with the main pro-inflammatory mediators, generating an environment that is anything but synchronous but a real inflammatory cascade.

The highly activated macrophages send pro-inflammatory signals to the intimal FLS inducing invasiveness. The proliferation of FLS is one of the main causes of synovial hyperplasia and with it, the cause of damage to cartilage and bones.

RA synovitis is highly heterogeneous, distinct patterns have been recognized in recent years, mainly based on the composition, organization and localization of cell infiltrates.

The most recent genetic studies have revealed synovial “pathotypes” of RA (7, 24), namely lymphoid, myeloid and fibroid variants.

The lymphoid pathotype is characterized by increased expression of genes associated with the activation and differentiation of B lymphocytes, as well as the Janus kinase JAK / STAT pathway and interleukin 17 (IL-17) signaling.

In the myeloid pathotype, the activation of genes of the NF-κB pathway (including TNFα, IL-1β, IL-1RA). In the fibroma pathotype, genes associated with the regulation of fibroblasts and osteoclasts / osteoblasts have been found, including fibroblast growth factor FGF2, FGF9, BMP6, and osteoprotegerin.

No distinct myeloid and lymphoid synovial histological subtypes have, however, been identified.

Recently, a machine learning algorithm was able to predict the synovial gene expression subtype of RA based on 20 histological characteristics.

The subtypes that have been pre-identified based on the RNA-seq grouping are: high inflammatory, low inflammatory and mixed.

The high inflammatory subtype identifiable with the lymphoid pathotype showed an enrichment of immune pathways, immune cell signaling (including SH2, SH3, JAK / STAT and TNF-mediated signaling), immunoglobulins, chemokines and cytokines. The low-inflammatory subtype was defined by enrichment of transforming growth factor β pathways, glycoprotein synthesis and cell adhesion genes (45).

Comparison of gene expression patterns with patients clinical characteristics revealed an important distinction: pain mechanisms may differ in patients with different synovial subtypes.

To conclude, the treatment of rheumatoid arthritis (RA) in recent years has been transformed both by the introduction of biological disease-modifying anti-rheumatic drugs and, more recently, by targeted synthetic therapies in the form of janus-inhibitors. kinase. However, the response to these agents varies in such a way as to take a trial and error approach; leading to poor patient quality of life and long-term results.

There is therefore an urgent need to identify effective biomarkers to guide treatment selection.

So, the importance of evaluating the synovial tissue, the primary site of RA, is increasingly recognized, where the knowledge of the cell phone dictated by the interactions of the same, represents an essential contribution in the pathological evaluation of the patient.

However, a new approach aimed at the precision and uniqueness of rheumatoid arthritis is emerging.

A method, which combines the enormous wealth of data collected so far combined with sophisticated analytical techniques, lays the foundations for entering the field of personalized medicine for the use of increasingly personal and precise AR therapy.


11. Lindblad S, Hedfors E. The synovial membrane of healthy individuals: immunohistochemistry overlaps with synovitis. Clin Exp Immunol. (1987) 69: 41-7.

7. Pitzalis C, Kelly S, Humby F. New teachings on the pathophysiology of RA from synovial biopsies. Curr Opin Rheumatol. (2013) 25: 334–44. 10.1097 / BOR.0b013e32835fd8eb

24. Dennis G, Holweg CT, Kummerfeld SK, Choy DF, Setiadi AF, Hackney JA, et al. . Synovial phenotypes in rheumatoid arthritis are correlated with the response to biological therapies. Therapy for the resolution of arthritis. (2014) 16: R90. 10.1186 / ar4555

45. Orange DE, Agius P, DiCarlo EF, Robine N, Geiger H, Szymonifka J, et al. . Identification of three rheumatoid arthritis disease subtypes by integrating machine learning of synovial histological features and RNA sequencing data. Rheumatoid arthritis. (2018) 70: 690–701. 10.1002 / art. 40428.

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