DEMORA: DEep spatial characterization of synovial MacrOphages in Rheumatoid Arthritis

类风湿性关节炎（RA）是影响关节的最常见的自身免疫性疾病。疾病过程的主要部位是滑膜组织（ST），其中巨噬细胞在驱动炎症中起核心作用。在生理条件下，滑膜由薄衬里和含有少量常驻巨噬细胞的相对无细胞的下层组成，但在RA中，ST变化很大。根据细胞浸润的“数量/质量”，描述了三种不同的“病理类型”：淋巴-髓系、弥漫性髓系和少免疫型。虽然数量不同，但滑膜组织巨噬细胞（STM）存在于所有三种病理中。在过去的五年中，STM的单细胞分子分析揭示了表型和功能不同的集群的存在，从而定义了一个新的STM分类。在这里，我假设不同的STM簇塑造了RA的滑膜组织微环境，并影响组织病理和对治疗的反应。通过应用现有的独特生物资源bbb800 ST，尖端技术，如与单细胞RNA-seq和计算机反卷积相结合的数字空间分析，我的目标是：确定STM集群的位置/地形分布和特定“生态位”的存在（例如，异位内/异位周围淋巴结构，血管或神经周围）；识别与每种滑膜病理型相关的STM集群和驱动病理型转变；评估特定STM簇是否预测抗风湿药物的临床反应，它们在治疗后如何变化，以及在对多种药物难治性患者中出现哪些亚群。在RA ST中深入表征STM将增强我们对慢性关节炎和治疗无反应机制的理解，整合和改进基于ST细胞/分子特征的预测算法，并可能提出新的治疗靶点。

Rheumatoid Arthritis (RA) is the most common autoimmune disease affecting the joints. The primary site of the disease process is the synovial tissue (ST), where macrophages play a central role in driving inflammation. In physiologic conditions, the synovial membrane consists of a thin lining and a relatively acellular sublining containing a few resident macrophages, but in RA, the ST changes considerably. Three different "pathotypes" have been described depending on the "quantity/quality" of the cellular infiltrate: lympho-myeloid, diffuse-myeloid, and pauci-immune. Although in different amounts, synovial tissue macrophages (STM) are present in all three pathotypes. In the last five years, single-cell molecular profiling of STM has revealed the existence of phenotypically and functionally distinct clusters, leading to the definition of a new STM taxonomy. Here, I hypothesize that different STM clusters shape the synovial tissue micro-environment in RA and influence tissue pathology and response to treatment. By applying to an existing unique bioresource of >800 ST, cutting-edge technology such as digital spatial profiling integrated with single-cell RNA-seq and in silico deconvolution, I aim to: determine the location/topographical distribution of STM clusters and the existence of specific "niche" (e.g., intra/peri-ectopic lymphoid structures, peri-vascular or nerve); identify STM clusters associated with each synovial pathotype and driving pathotypes transition; assess if specific STM clusters predict clinical response to anti-rheumatic drugs, how they change post-treatment, and which subsets emerge in patients refractory to multiple medications. This in-depth STM characterization in RA ST will enhance our understanding of the mechanisms sustaining chronic arthritis and non-response to treatments, integrate and improve predictive algorithms based on ST cellular/molecular signatures, and may suggest new therapeutic targets.