B cells play a significant role in established Rheumatoid Arthritis (RA). However, it is unclear to what extent differentiated B cells are present in joint tissue already at the onset of disease. Here, we studied synovial biopsies (n = 8) captured from untreated patients at time of diagnosis. 3414 index-sorted B cells underwent RNA sequencing and paired tissue pieces were subjected to spatial transcriptomics (n = 4). We performed extensive bioinformatics analyses to dissect the local B cell composition. Select plasma cell immunoglobulin sequences were expressed as monoclonal antibodies and tested by ELISA. Memory and plasma cells were found irrespective of autoantibody status of the patients. Double negative memory B cells were prominent, but did not display a distinct transcriptional profile. The tissue architecture implicate both local B cell maturation via T cell help and plasma cell survival niches with a strong CXCL12-CXCR4 axis. The immunoglobulin sequence analyses revealed clonality between the memory B and plasma cell pools further supporting local maturation. One of the plasma cell-derived antibodies displayed citrulline autoreactivity, demonstrating local autoreactive plasma cell differentiation in joint biopsies captured from untreated early RA. Hence, plasma cell niches are not a consequence of chronic inflammation, but are already present at the time of diagnosis.

The inflamed rheumatic joint is a highly heterogeneous and complex tissue with dynamic recruitment and expansion of multiple cell types that interact in multifaceted ways within a localized area. Rheumatoid arthritis synovium has primarily been studied either by immunostaining or by molecular profiling after tissue homogenization. Here, we use Spatial Transcriptomics, where tissue-resident RNA is spatially labeled in situ with barcodes in a transcriptome-wide fashion, to study local tissue interactions at the site of chronic synovial inflammation. We report comprehensive spatial RNA-Seq data coupled to cell type-specific localization patterns at and around organized structures of infiltrating leukocyte cells in the synovium. Combining morphological features and high-throughput spatially resolved transcriptomics may be able to provide higher statistical power and more insights into monitoring disease severity and treatment-specific responses in seropositive and seronegative rheumatoid arthritis. Sanja Vickovic et al. use spatial transcriptomics to probe the local synovial tissue interactions in rheumatoid arthritis (RA) patients. Their results provide a valuable resource to understand the spatial organisation of cell populations in the synovium in the context of RA-associated inflammation.

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.

Reumatoid artrit (RA) är en kronisk inflammatorisk autoimmun sjukdom som främst drabbar leder och orsakar obehag såsom smärta, varpå livskvaliteten hos den drabbade individen avsevärt försämras. Etiologin bakom RA är mestadels okänd trots att några patofysiologiska mekanismer såsom bildandet av anti-citrullinated protein antibodies (ACPAs), Rheumatic factors (RFs), lokal prolifiering av mesenchymala celler och rekrytering av T- och B-celler till de drabbade lederna har identifierats. Lymphocytinfiltration resulterar i kronisk sjukdom med förhöjda nivåer av cytokiner (såsom Tumor necrosis factor alpha; TNF-α) och interleukinsignalering vilket triggar proteasaktivering som gradvis bryter ned synovium och det underliggande skelettet. I många fall kan RA effektivt behandlas med hjälp av de nyare disease-modifying anti-rheumatic drugs (DMARDs) och tidigare diagnos av patienten. Detta fungerar dock inte för alla patienter och en bot for RA existerar ännu inte. 

Synoviala skador i RA visar på komplexa histopatologiska manifestationer vilka inkluderar bildandet av lymfoida folliklar men även Ectopic Lymphoid Structures (ELS) vilka har blivit noggrant studerade med immuninfärgning och andra cytologiska metoder. Dessa metoder saknar antingen omfattande detektion av målmolekyler eller saknar information om den spatiala kontexten av dessa målmolekyler. 

I denna avhandling har vi tillämpat Spatial Transcriptomics (ST), en metod som tillåter genexpressionstudier med bevarad spatial information. Denna metod används på RA biopsier från tidigt obehandlad RA till långtgående etablerad sjukdom med ödem. Med andra ord täcker avhandlingen hela den spatio-temporala dynamiken i inflammerade leder. Arikel I beskriver en ny metod för att bestämma kvaliteten av RNA likt RNA Integrity Number (RIN) i bulk, men med singelcellupplösning på vävnadssnitt. Målet är att studera kliniskt sällsynta prover för vidare bearbetning med ST. Artikel II undersöker långtgående inflammerade RA-leder med Spondyloartrit (SpA) som sjukdomskontroll med hjälp av ST. Här utförde vi immuncellprediktion in silico från det omfattande transkriptomdata vi tillhandahöll och kunde se skillnaderna i infiltrat i RA jämfört med SpA med större detaljrikedom än vad traditionell patologi tidigare gjort. Som en uppföljning undersöker Artikel III RA-vävnader med ännu större detaljrikedom genom användandet av exakt intilliggande vävnadssnitt från RA-patienter för att bygga en tredimensionell atlas över presumtiva ELS i inflammerade vävnader. Slutligen använder Artikel IV fyra olika teknologier för att studera tidig obehandlad RA. Vi använde ST för vävnadsanalys i kombination med singelcell RNA-sekvensering (scRNA-Seq) från Fluorescence-activated cell sorted (FACS) B-celler. Dessa två metoder kompletterades med immunohistochemistry (IHC) för validering och sRIN så vi kunde bestämma kvaliteten på de kliniska proverna. Här fann vi bevis för B-cellsmognad och ELS-bildande redan i tidig RA och mekanismer som kan vara kopplade till så kallad ”survival niche”. Dessa studier syftar till att täcka det komplexa RA och karaktärisera sjukdomen med högre upplösning än tidigare och även föreslå nya sjukdomsmönster som kan komma att bli värdefulla i studier med klinisk innebörd.  

The RNA integrity number (RIN) is a frequently used quality metric to assess the completeness of rRNA, as a proxy for the corresponding mRNA in a tissue. Current methods operate at bulk resolution and provide a single average estimate for the whole sample. Spatial transcriptomics technologies have emerged and shown their value by placing gene expression into a tissue context, resulting in transcriptional information from all tissue regions. Thus, the ability to estimate RNA quality in situ has become of utmost importance to overcome the limitation with a bulk rRNA measurement. Here we show a new tool, the spatial RNA integrity number (sRIN) assay, to assess the rRNA completeness in a tissue wide manner at cellular resolution. We demonstrate the use of sRIN to identify spatial variation in tissue quality prior to more comprehensive spatial transcriptomics workflows. Kvastad et al. develop the spatial RNA Integrity Number (sRIN) assay that evaluates the RNA integrity at cellular resolution. This method improves the resolution of a similar method called the RNA Integrity Number (RIN), demonstrating spatial variation in the quality of RNA samples.

Lately it has become possible to analyze transcriptomic profiles in tissue sections with retained cellular context. We aimed to explore synovial biopsies from rheumatoid arthritis (RA) and spondyloarthritis (SpA) patients, using Spatial Transcriptomics (ST) as a proof of principle approach for unbiased mRNA studies at the site of inflammation in these chronic inflammatory diseases. Synovial tissue biopsies from affected joints were studied with ST. The transcriptome data was subjected to differential gene expression analysis (DEA), pathway analysis, immune cell type identification using Xcell analysis and validation with immunohistochemistry (IHC). The ST technology allows selective analyses on areas of interest, thus we analyzed morphologically distinct areas of mononuclear cell infiltrates. The top differentially expressed genes revealed an adaptive immune response profile and T-B cell interactions in RA, while in SpA, the profiles implicate functions associated with tissue repair. With spatially resolved gene expression data, overlaid on high-resolution histological images, we digitally portrayed pre-selected cell types in silico. The RA displayed an overrepresentation of central memory T cells, while in SpA effector memory T cells were most prominent. Consequently, ST allows for deeper understanding of cellular mechanisms and diversity in tissues from chronic inflammatory diseases.

Rheumatoid Arthritis (RA) is a prevalent autoimmune disease characterized by inflammation of peripheral joints. Patients can be subdivided by the presence or absence of Rheumatoid Factor and anti-citrullinated protein antibodies (ACPA) in their circulation. Inflammation of the joint tissue is associated with infiltration of leukocytes from the blood, which can result in generation of lymphoid structures composed of B and T cells. Previous studies have shown that both memory B cells and antibody-secreting plasma cells populate the rheumatic joint tissue when captured from established and often long-standing disease. However, it has remained unclear, whether these cells are autoreactive and whether the associated lymphoid structures are present at the site of inflammation already at the time of diagnosis. Here, we used an integrated single cell and spatial transcriptomic approach to study B and plasma cells in synovial tissue of ACPA- and ACPA+ RA patients at this early time point. We found evidence for T cell help to B cells and presence of memory B and plasma cell pools in ACPA- as well as in ACPA+ RA. Our results demonstrated common supportive microenvironments in both patient subgroups, clonal relationships between the memory B and plasma cell pools and autoreactivity within the plasma cell compartment. These findings challenge our understanding of the dynamics of local adaptive immune responses in the RA joint of ACPA- and ACPA+ patients at the time of diagnosis, with direct implications for B and T cell targeting therapies for both patient subgroups. 

Spatial Transcriptomics has been shown to be a persuasive RNA sequencing

technology for analyzing cellular heterogeneity within tissue sections. The

technology efficiently captures and barcodes 3’ tags of all polyadenylated

transcripts from a tissue section, and thus provides a powerful platform when

performing quantitative spatial gene expression studies. However, the current

protocol does not recover the full-length information of transcripts, and

consequently lack information regarding alternative splice variants. Here, we

introduce a novel protocol for spatial isoform profiling, using Spatial

Transcriptomics barcoded arrays.

The inflamed rheumatic joint is a highly heterogeneous and complex tissue with dynamic recruitment and expansion of multiple cell types that interact in multifaceted ways within a localized area. Rheumatoid arthritis synovium has primarily been studied either by immunostaining or by molecular profiling after tissue homogenization. Here, we use Spatial Transcriptomics to study local cellular interactions at the site of chronic synovial inflammation. We report comprehensive spatial RNA-seq data coupled to quantitative and cell type-specific chemokine-driven dynamics at and around organized structures of infiltrating leukocyte cells in the synovium.