Analysis of synovitis patterns in early RA supports the importance of joint-specific factors.

Semin Arthritis Rheum

Service de Rhumatologie, Cliniques Universitaires Saint-Luc, Brussels, Belgium; Pôle de pathologies rhumatismales systémiques et inflammatoires, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Brussels, Belgium. Electronic address:

Published: October 2024


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Background: Rheumatoid arthritis (RA) is classically considered a systemic disorder, but the role of local factors in driving synovial inflammation is increasingly being recognized. These joint-specific factors may consequently modulate disease phenotype.

Objectives: Our goal was to study the spatial distribution of swelling, tenderness and erosions in a large cohort of early RA (ERA) patients, to assess for patterns of simultaneously-involved joint clusters. We also aimed to investigate the link between arthritis localization and phenotypic features such as bone erosions and response to methotrexate therapy.

Methods: DMARD-naive patients from the ERA UCLouvain Brussels cohort were included. Forty-four joints were clinically assessed for swelling and tenderness before treatment, and 6 months later for methotrexate-treated patients. Clusters of joints were identified using Principal component analysis and Cramer's correlation coefficients. Frequency of bone erosions and joint-specific response to methotrexate were compared across different clusters.

Results: 452 ERA patients were included. Analysis of the spatial distribution of swelling and tenderness allowed for the identification of 3 joint clusters that showed significant simultaneous involvement: (i) MTP1-5 joints, (ii) hand joints (MCPs and PIPs), and (iii) larger joints. These clusters were associated with different susceptibility to bone erosions and distinct clinical features, but similar local response (joint swelling resolution) to methotrexate.

Conclusion: This is the first study investigating the spatial distribution of arthritis in a large cohort of early RA using an unbiased approach. We identify clusters of simultaneously involved joints, supporting the importance of local factors in driving synovitis in RA.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.semarthrit.2024.152524DOI Listing

Publication Analysis

Top Keywords

spatial distribution
12
swelling tenderness
12
bone erosions
12
joint-specific factors
8
local factors
8
factors driving
8
distribution swelling
8
large cohort
8
cohort early
8
era patients
8

Similar Publications

Immunoelectron microscopy: a comprehensive guide from sample preparation to high-resolution imaging.

Discov Nano

September 2025

Department of Rehabilitation Medicine, Rehabilitation Medical Center, Key Laboratory of Rehabilitation Medicine in Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.

Immunoelectron Microscopy (IEM) is a technique that combines specific immunolabeling with high-resolution electron microscopic imaging to achieve precise spatial localization of biomolecules at the subcellular scale (< 10 nm) by using high-electron-density markers such as colloidal gold and quantum dots. As a core tool for analyzing the distribution of proteins, organelle interactions, and localization of disease pathology markers, it has irreplaceable value, especially in synapse research, pathogen-host interaction mechanism, and tumor microenvironment analysis. According to the differences in labeling sequence and sample processing, the IEM technology system can be divided into two categories: the first is pre-embedding labeling, which optimizes the labeling efficiency through the pre-exposure of antigenic epitopes and is especially suitable for the detection of low-abundance and sensitive antigens; the second is post-embedding labeling, which relies on the low-temperature resin embedding (e.

View Article and Find Full Text PDF

Genomes are composed of a mosaic of segments inherited from different ancestors, each separated by past recombination events. Consequently, genealogical relationships among multiple genomes vary spatially across different genomic regions. Genealogical variation among unlinked (uncorrelated) genomic regions is well described for either a single population (coalescent) or multiple structured populations (multispecies coalescent).

View Article and Find Full Text PDF

Spatial transcriptomics (ST) reveals gene expression distributions within tissues. Yet, predicting spatial gene expression from histological images still faces the challenges of limited ST data that lack prior knowledge, and insufficient capturing of inter-slice heterogeneity and intra-slice complexity. To tackle these challenges, we introduce FmH2ST, a foundation model-based method for spatial gene expression prediction.

View Article and Find Full Text PDF

Desert plant communities play an irreplaceable role in maintaining the ecological balance of arid areas. Understanding the spatial distribution pattern of desert plant diversity and its environmental response mechanism is particularly important for the protection of regional biodiversity, and combining phylogenetic information can provide more in-depth insights. To this end, this study conducted a survey of desert plant communities along the southeast to northwest direction of the Hexi Corridor, revealing the variation patterns of species and phylogenetic diversity (PD) indicators along longitude, latitude, and altitude, and explored the driving factors of these patterns in combination with geographical, climatic, and soil factors.

View Article and Find Full Text PDF

Understanding the spatial distribution of rare species is fundamental to biodiversity conservation. The black-necked crane (), a flagship species of alpine wetlands and a first-class nationally protected species in China, serves as an important indicator for ecosystem health. Based on the had data and ecological environment data, this study used the Maximum Entropy model (MaxEnt) and Random Forest model (RF) to predict the suitable distribution area of the black-necked crane.

View Article and Find Full Text PDF