The adaptive immune system is equipped to eliminate both tumors and pathogenic microorganisms. It requires a series of complex and coordinated signals to drive the activation, proliferation, and differentiation of appropriate T cell subsets. It is now established that changes in cellular activation are coupled to profound changes in cellular metabolism. In addition, emerging evidence now suggest that specific metabolic alterations associated with distinct T cell subsets may be ancillary to their differentiation and influential in their immune functions. The “Warburg effect” originally used to describe a phenomenon in which most cancer cells relied on aerobic glycolysis for their growth is a key process that sustain T cell activation and differentiation. Here, we review how different aspects of metabolism in T cells influence their functions, focusing on the emerging role of key regulators of glucose metabolism such as HIF-1α. A thorough understanding of the role of metabolism in T cell function could provide insights into mechanisms involved in inflammatory-mediated conditions, with the potential for developing novel therapeutic approaches to treat these diseases.

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Glucose Metabolism Regulates T Cell Activation, Differentiation, and Functions

Optimal fracture treatment requires knowledge of the complex physiological process of bone healing. The course of bone healing is mainly influenced by fracture fixation stability (biomechanics) and the blood supply to the healing site (revascularization after trauma). The repair process proceeds via a characteristic sequence of events, described as the inflammatory, repair and remodeling phases. An inflammatory reaction involving immune cells and molecular factors is activated immediately in response to tissue damage and is thought to initiate the repair cascade. Immune cells also have a major role in the repair phase, exhibiting important crosstalk with bone cells. After bony bridging of the fragments, a slow remodeling process eventually leads to the reconstitution of the original bone structure. Systemic inflammation, as observed in patients with rheumatoid arthritis, diabetes mellitus, multiple trauma or sepsis, can increase fracture healing time and the rate of complications, including non-unions. In addition, evidence suggests that insufficient biomechanical conditions within the fracture zone can influence early local inflammation and impair bone healing. In this Review, we discuss the main factors that influence fracture healing, with particular emphasis on the role of inflammation.

Fracture healing under healthy and inflammatory conditions

Oxygen-derived free radicals, collectively termed reactive oxygen species (ROS), play important roles in immunity, cell growth, and cell signaling. In excess, however, ROS are lethal to cells, and the overproduction of these molecules leads to a myriad of devastating diseases. The key producers of ROS in many cells are the NOX family of NADPH oxidases, of which there are seven members, with various tissue distributions and activation mechanisms. NADPH oxidase is a multisubunit enzyme comprising membrane and cytosolic components, which actively communicate during the host responses to a wide variety of stimuli, including viral and bacterial infections. This enzymatic complex has been implicated in many functions ranging from host defense to cellular signaling and the regulation of gene expression. NOX deficiency might lead to immunosuppression, while the intracellular accumulation of ROS results in the inhibition of viral propagation and apoptosis. However, excess ROS production causes cellular stress, leading to various lethal diseases, including autoimmune diseases and cancer. During the later stages of injury, NOX promotes tissue repair through the induction of angiogenesis and cell proliferation. Therefore, a complete understanding of the function of NOX is important to direct the role of this enzyme towards host defense and tissue repair or increase resistance to stress in a timely and disease-specific manner.

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NADPH oxidases: an overview from structure to innate immunity-associated pathologies

Sleep and immunity are bidirectionally linked. Immune system activation alters sleep, and sleep in turn affects the innate and adaptive arm of our body’s defense system. Stimulation of the immune s...

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The Sleep-Immune Crosstalk in Health and Disease

Sequential delivery of immunomodulatory cytokines to facilitate the M1-to-M2 transition of macrophages and enhance vascularization of bone scaffolds

Background Rheumatoid arthritis (RA) patients are reported to be often affected by fracture-healing complications not only as a result of osteoporosis. The inflammatory disease itself and anti-rheumatic drugs (e.g. glucocorticoids, GC) are supposed to interfere with the healing process. However, current literature studies reporting the number of afflicted patients and/or indicating the negative impact of comorbidities or even standard medications on the fracture healing are scarce. Objectives The aim of this study is to evaluate the clinical relevance of especially RA and GC treatment as well as other comorbidities as potential risk factors for fracture healing disorders in a single-center retrospective study at the Center of Musculoskeletal Surgery (Charite University Hospital Berlin). According to our preliminary data, we now included an enhanced patient cohort as well as a control group that fulfills the required criteria. Methods Based on the database of the Center for Musculoskeletal Surgery at Charite University Hospital Berlin patients were selected who underwent surgery at this institution to treat fracture healing complications in 2012. Exclusion criteria were age below 18 years at initial fracture, open fracture, and metastases close to fracture location. Our data were compared with a control group matched for age and type of fracture at the ratio of two. Descriptive and explorative data analysis as well as statistical evaluation of logistic regression were performed. The latter method starts with a univariable regression (Omnibus-Test p≤0.15) to identify co-variables for further investigations. The identified co-variables were subsequently tested with multivariable regression using regression elimination to determine interfering factors. Results 266 patients were included in the study whereas 79 cases and 178 controls were compared. The mean age was 52.6 years and 140 females and 126 males could be identified. The descriptive analysis showed higher frequencies of GC (6.3% vs. 1.6%) and NASAID (7.6% vs. 2.7%) administration in patients with fracture healing disorders. Additionaly, patients suffering from rheumatoid arthritis (6.3% vs. 0.5%), arterial hypertonia (43.0% vs. 33.5%) and smokers (37.8% vs. 28.1%) more frequently exhibited delayed fracture healing. Statistical analysis using logistic regression showed high significance for rheumatoid arthritis patients (p=0.028, odds ratio 12.1) and a trend for smokers (p=0.075, odds ratio 1.7) as interfering factors favoring bone healing disorders. Conclusions Taken together, the results we have obtained so far support the hypothesis that especially RA has a negative impact on the outcome of fracture healing as well as smoking. To our knowledge, this is the first retrospective study focusing on risk factors for bone healing complications in Germany. Furthermore, the results confirm observations known from in vitro and in vivo studies in humans. Acknowledgements We thank Prof. Schlattmann for his support. Disclosure of Interest None declared

https://ard.bmj.com/content/annrheumdis/74/Suppl_2/254.1.full.pdf

THU0166 Logistic Regression Method Identifies RA as Risk Factors for Delayed Fracture-Healing – an Update of a Single-Center Retrospective Study

Cellular metabolism modulates effector functions in human CD4+ T (Th) cells by providing energy and building blocks. Conversely, cellular metabolic responses are modulated by various influences, e.g., age. Thus, we hypothesized that metabolic reprogramming in human Th cells during aging modulates effector functions and contributes to “inflammaging”, an aging-related, chronic, sterile, low-grade inflammatory state characterized by specific proinflammatory cytokines. Analyzing the metabolic response of human naive and memory Th cells from young and aged individuals, we observed that memory Th cells exhibit higher glycolytic and mitochondrial fluxes than naive Th cells. In contrast, the metabolism of the latter was not affected by donor age. Memory Th cells from aged donors showed a higher respiratory capacity, mitochondrial content, and intracellular ROS production than those from young donors without altering glucose uptake and cellular ATP levels, which finally resulted in higher secreted amounts of proinflammatory cytokines, e.g., IFN-γ, IP-10 from memory Th cells taken from aged donors after TCR-stimulation which were sensitive to ROS inhibition. These findings suggest that metabolic reprogramming in human memory Th cells during aging results in an increased expression of proinflammatory cytokines through enhanced ROS production, which may contribute to the pathogenesis of inflammaging.

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Age-related increase of mitochondrial content in human memory CD4+ T cells contributes to ROS-mediated increased expression of proinflammatory cytokines

OBJECTIVES
The coronavirus disease 19 (COVID-19) pandemic concerns the field of rheumatology in many ways. Arthritis in conjunction with COVID-19 is increasingly reported. However, clinical data are still limited and there is lack of a detailed characterisation of COVID-19 associated arthritis by musculoskeletal ultrasound (MSUS). This case series reports different forms of COVID-19 associated arthritis supported by MSUS in patients with or without underlying rheumatic and musculoskeletal disease (RMD).


METHODS
From March 2020 to July 2021, adult patients (n=10) with arthritis timely related to COVID-19 were assessed in three European centres by clinical and laboratory values and additionally MSUS.


RESULTS
In the group without underlying RMD (n=6), two patients presented with polyarticular arthralgia during severe COVID-19, swelling was rarely seen and MSUS demonstrated arthritis only in a few joints affected. The other four patients showed arthritis four to 16 weeks after mild or moderate COVID-19 (without hospitalisation): polyarthritis (n=1), oligoarthritis of the upper and lower limb (n=2), and in one case, late-onset rheumatoid arthritis (LORA) was newly diagnosed. In the group with an underlying RMD (n=4), an increase of disease activity was reported by MSUS during mild and mild-moderate COVID-19. In general, MSUS often presented power Doppler (PD) positive synovitis and tenosynovitis.


CONCLUSIONS
In our patients without underlying RMD, arthritides associated with COVID-19 are comparable to the clinical picture of a reactive arthritis (ReA) or other virus-related arthritides (e.g. parvovirus B19). New onset or flares of RMD possibly triggered by COVID-19 are noteworthy.

Diagnosis of COVID-19 associated arthritis in patients with or without underlying rheumatic and musculoskeletal disease supported by musculoskeletal ultrasound: a case series from three European centres.

Tofacitinib promotes fundamental processes of bone healing

As outlined in previous studies, different rheumatic joint diseases present specific characteristic patterns and features in fluorescence optical imaging (FOI) (1-4).We tested different features in FOI for their ability to differentiate various rheumatic joint diseases such as rheumatoid arthritis (RA), osteoarthritis (OA) and psoriatic arthritis (PsA) with the aim to identify clear FOI criteria for the diseases.FOI images from patients with RA, OA, PsA and healthy volunteers were evaluated by two readers blinded for diagnosis and calibrated against each other, using the prima vista mode (PVM) and the 5-phase model. For the latter, the overall time course of FOI in each hand was divided into 5 phases with a computational algorithm. Phases 1 and 2 describe the inflow (start to 15% and 15%-90% on rising edge), phase 3 is the peak phase and phases 4 and 5 comprise the outflow (90%-36.8% and 36.8% to end on falling edge). Twenty-six different features were defined by an atlas, for example the streaky pattern feature (T) as a signal enhancement around the PIP area that appears streaky, whereby the stripes are orthogonal to the finger axis (Figure 1a). The cloudy pattern (W) is visible during the inflow on the back of the hand (Figure 1b). The enthesis feature (E) depicts a V shaped and filled pattern between nail and DIP (Figure 1c). The feature frequency in each patient and phase (PVM, 5-phase) was counted and statistically analysed.Figure 1.Examples for FOI patterns and features: a) (T) Streaky pattern in PVM image (OA); b) (W) Cloudy pattern on the back of the hand in phase 1 (PsA); c) (E) Enthesis pattern in phase 3.In total, 128 patients (RA (age mean 54.2; SD 10.6; median 52.4), OA (58.0; 14.3; 60.1), and PsA (47.9; 12.7; 46.8)) and healthy volunteers (32 in each group) were included in the feature reading. In our analysis, OA can be differentiated from RA on the basis of the feature T. Feature T is found in phase 3 (χ2: 4.61; diagnostic odds ratio (DOR): 7.49; sensitivity (TPR) 0.11; specificity (TNR): 0.98; positive predictive value (PPV): 0.87; negative predictive value (NPV): 0.52), phase 5 (χ2: 18.5; DOR: 5.60; TPR 0.55; TNR: 0.82; PPV: 0.76; NPV: 0.64 and PVM (28.3; 12.1; 52%; 92% 87%; 65%). By means of the feature E, a distinction between RA and PsA is only limited possible (χ2: 9.58; DOR: 3.65; TPR 0.40; TNR: 0.84; PPV: 0.71; NPV: 0.59). But PsA can well be distinguished from RA by the appearance of pattern W in phase 1 (χ2: 7.68; DOR: 6.92; TPR 0.19; TNR: 0.97; PPV: 0.86; NPV: 0.54).Other significant features yield high specificity (70%-98%) while having low sensitivity (12%-52%).This work demonstrates that FOI feature analysis has the potential for differential diagnosis with FOI, which could optimize the (early) diagnostic process of rheumatic joint diseases. A majority of features yield high specificity, but only low sensitivity. The combination of different features using artificial intelligence might lead to improved diagnostic accuracy.[1]Werner SG, et al. Inflammation assessment in patients with arthritis using a novel in vivo fluorescence optical imaging technology. Ann Rheum Dis. 2012; 71(4):504-510.[2]Glimm AM, et al. Analysis of distribution and severity of inflammation in patients with osteoarthitis compared to rheumatoid arthritis by ICG-enhanced fluorescence optical imaging and musculoskeletal ultrasound: a pilot study. Ann Rheum Dis. 2016; 75(3):566-570.[3]Wiemann O, et al. The “green nail” phenomenon in ICG-enhanced fluorescence optical imaging - a potential tool for the differential diagnosis of psoriatic arthritis. J Dtsch Dermatol Ges. 2019;17(2):138-147.[4]Schmidt A, et al. Detection of subclinical skin manifestation in patients with psoriasis and psoriatic arthritis by fluorescence optical imaging. Arthritis Res Ther. 2020; 22(1):192.None declared

https://ard.bmj.com/content/annrheumdis/81/Suppl_1/1787.1.full.pdf

Paula Hoff

Papers

THU0166 Logistic Regression Method Identifies RA as Risk Factors for Delayed Fracture-Healing – an Update of a Single-Center Retrospective Study

Age-related increase of mitochondrial content in human memory CD4+ T cells contributes to ROS-mediated increased expression of proinflammatory cytokines

Diagnosis of COVID-19 associated arthritis in patients with or without underlying rheumatic and musculoskeletal disease supported by musculoskeletal ultrasound: a case series from three European centres.

Tofacitinib promotes fundamental processes of bone healing

Ab1363 image pattern analysis in fluorescence optical imaging for differential diagnosis in rheumatic joint diseases