Spatial Tissue Mapping on Joint Biopsies from Arthritis Patients
Time: Fri 2021-04-16 10.00
Location: https://kth-se.zoom.us/webinar/register/WN_apN_zgDTQHizMT3m4MJ7CA, Solna (English)
Subject area: Biotechnology
Doctoral student: Konstantin Carlberg , Genteknologi, Science for Life Laboratory, SciLifeLab
Opponent: Docent Anna-Karin Hultgård Ekwall, Göreborgs Universitet
Supervisor: Universitetslektor Patrik Ståhl, Genteknologi, Science for Life Laboratory, SciLifeLab; Professor Vivianne Malmström, Karolinska Institutet
Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease that mainly affects joints, causing discomfort and pain that severely reduces the life quality of affected individuals. Its etiology is largely unknown, but some pathophysiological mechanisms have been identified. These include formation of anti-citrullinated protein antibodies (ACPAs) and rheumatic factors (RFs), local proliferation of mesenchymal cells, and recruitment of T- and B cells to the affected synovium. Lymphocyte infiltration results in elevated levels of cytokines such as Tumor Necrosis Factor alpha (TNF-α) and interleukin signaling, which in turn triggers protease activation that gradually degrades the synovium and underlying bone.
In many cases RA can be effectively managed by early diagnosis followed by treatment with disease-modifying anti-rheumatic drugs (DMARDs). However, this is not true for all patients and there is currently no cure for RA. Synovial lesions in RA patients exhibit complex histopathological manifestations involving the formation of lymphoid follicles with highly organized Ectopic Lymphoid Structures (ELS). These have been extensively studied using immunostaining and other cytological methods, either by targeting a few specific molecular markers in tissue sections or by examining homogenized suspensions of complex samples, which causes a loss of local and spatial tissue information.
This thesis reports the use of Spatial Transcriptomics (ST) to study gene expression in tissue samples from RA patients while preserving spatial information. The method was applied to RA biopsies from early onset and untreated RA to late-stage established disease with edema, providing comprehensive coverage of the spatio-temporal dynamics of the inflamed joints.
Paper I introduces sRIN, a novel method of assessing the quality of RNA in tissue sections that is similar to RNA Integrity Number (RIN) analysis for bulk RNA but with single-cell resolution. The aim was to find ways of analyzing clinically rare samples for further processing with ST. Paper II uses ST to study tissue samples from RA joints with long-standing disease, using Spondyloarthritis (SpA) as a disease control. The resulting comprehensive transcriptomic data were used to perform in silico immune cell prediction and revealed how immune cell infiltration in RA differs from that in SpA in more detail than was previously possible using traditional pathological methods. As a follow up, Paper III investigates inflamed RA joints in even greater detail by using several adjacent tissue sections to build a three-dimensional atlas of assumed ELS areas. Finally, Paper IV uses four distinct technologies to study untreated early onset RA patients. Spatial tissue analysis with ST was combined with single cell RNA sequencing (scRNA-Seq) of fluorescence-activated cell sorted (FACS) B cells. These two methods were complemented with immunohistochemistry (IHC) for validation and sRIN to assess the quality of the clinical samples. B cells are known to play a key role in RA by producing self-reactive antibodies. This work showed that B cell maturation and ELS formation are detectable even in early onset RA, and revealed mechanisms supporting survival niches in hyperplastic joints. Overall, these studies shed new light on the complex nature of Rheumatoid arthritis, characterize the site of infection with greater granularity than was previously possible, and reveal novel disease patterns with clinical implications that warrant further study.