Prior evidence suggests that altered energy metabolism plays a crucial role in the development of fibrotic diseases. Recent research indicates that systemic sclerosis (SSc) patients have potentially benefited from energy management, implying that basal metabolic rate (BMR), a vital energy metabolic parameter, may be related to SSc. However, the causal effect of BMR on SSc remains unknown. Thus, we aimed to elucidate the causal links between BMR and SSc. Based on summary statistics from the genome-wide association studies (GWAS) database, two-sample Mendelian randomization (MR) was applied to explore causality between BMR and SSc. The causal relationships were assessed employing inverse variance weighted (IVW), MR-Egger, and weighted median (WM) methods. Meanwhile, several sensitivity analyses were carried out to ensure the robustness of the findings. There was an underlying genetic association of BMR on SSc (OR = 0.505, 95% CI: 0.272-0.936, P = 0.030). Moreover, no significant causal effect between SSc and BMR was observed in the reverse MR analysis (OR = 0.999, 95% CI: 0.997-1.001, P = 0.292). According to the sensitivity analysis, the presence of heterogeneity and genetic pleiotropy was not detected. Our findings, derived from a genetic perspective, provide robust evidence of a causal connection between BMR and SSc. To verify these results and clarify the potential mechanisms, further research is warranted.

UNASSIGNED: Systemic sclerosis (SSc) is a rare autoimmune disease with multiple organ involvement; however, the contribution of the nervous system (NS) remains relatively understudied. There are no specific data on the role of the autoimmune response and inflammation in the development of peripheral nerve system (PNS) damage in SSc and markers to assess this damage have yet to be identified.
UNASSIGNED: The primary objective of this study was to define the autoimmune mechanisms that lead to neuropathy by identifying antibodies (Abs) that target certain component of the NS or are associated with SSc. The secondary objective was to identify markers of NS damage that correlate with the detection and progression of polyneuropathy (PNP).
UNASSIGNED: This study included patients diagnosed with SSc who met ACR/EULAR 2013 classification criteria at two leading Latvian hospitals between January 2016 and December 2021. Patients underwent a nerve conduction study (NCS). The SSc-associated Abs, Abs against myelin-associated glycoprotein (MAG) and anti-ganglioside Abs (GM1, GM2, GD1a, GD1b and GQ1b) were analysed. Potential serum PNS biomarkers-neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), fibroblast growth factor 21 (FGF21) and growth/differentiation factor 15 (GDF15)-were measured.
UNASSIGNED: We recruited 103 Caucasian patients diagnosed with SSc. SSc-associated Abs did not differ significantly between patients with and without PNP (p > 0.05). Anti-MAG and anti-ganglioside Abs in patients with PNP did not present a significant increase above the reference range. NfL, GFAP and GDF15 were significantly elevated in the presence of PNP (p < 0.05), with a moderate to high effect size (r = 0.36-0.65). Our regression analysis revealed a strong association between the HAQ-DI score, older age, male gender and the risk of developing PNP.
UNASSIGNED: The development of PNP in patients with SSc is most likely due to ageing, natural progression and the sequelae of the disease. Several serum biomarkers-NfL, GFAP and GDF15-could be used as relevant diagnostic biomarkers for PNP in patients with SSc. Future studies are warranted to validate the diagnostic efficacy of these biomarkers and to unravel the complex interplay of factors leading to PNP in patients with SSc.

Fibroblasts are crucial components of the skin structure. They were traditionally believed to maintain the skin\'s structure by producing extracellular matrix and other elements. Recent research illuminated that fibroblasts can respond to external stimuli and exhibit diverse functions, such as the secretion of pro-inflammatory factors, adipogenesis, and antigen presentation, exhibiting remarkable heterogeneity and plasticity. This revelation positions fibroblasts as active contributors to the pathogenesis of skin diseases, challenging the traditional perspective that views fibroblasts solely as structural entities. Based on their diverse functions, fibroblasts can be categorized into six subtypes: pro-inflammatory fibroblasts, myofibroblasts, adipogenic fibroblasts, angiogenic fibroblasts, mesenchymal fibroblasts, and antigen-presenting fibroblasts. Cytokines, metabolism, and epigenetics regulate functional abnormalities in fibroblasts. The dynamic changes fibroblasts exhibit in different diseases and disease states warrant a comprehensive discussion. We focus on dermal fibroblasts\' aberrant manifestations and pivotal roles in inflammatory and autoimmune skin diseases, including psoriasis, vitiligo, lupus erythematosus, scleroderma, and atopic dermatitis, and propose targeting aberrantly activated fibroblasts as a potential therapeutic strategy for inflammatory and autoimmune skin diseases.

OBJECTIVE: To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.
METHODS: The GSE95065 and GSE59785 datasets of scleroderma from GEO database were used for analyzing expressions of mitochondria-related genes, and the differential genes were identified by Random forest, LASSO regression and SVM algorithms. Based on these differential genes, an artificial neural network model was constructed, and its diagnostic accuracy was evaluated by 10-fold crossover verification and ROC curve analysis using the verification dataset GSE76807. The mRNA expressions of the key genes were verified by RT-qPCR in a mouse model of scleroderma. The CIBERSORT algorithm was used to estimate the bioinformatic association between scleroderma and the screened biomarkers.
RESULTS: A total of 24 differential genes were obtained, including 11 up-regulated and 13 down-regulated genes. Seven most relevant mitochondria-related genes (POLB, GSR, KRAS, NT5DC2, NOX4, IGF1, and TGM2) were screened using 3 machine learning algorithms, and the artificial neural network diagnostic model was constructed. The model showed an area under the ROC curves of 0.984 for scleroderma diagnosis (0.740 for the verification dataset and 0.980 for cross-over validation). RT-qPCR detected significant up-regulation of POLB, GSR, KRAS, NOX4, IGF1 and TGM2 mRNAs and significant down-regulation of NT5DC2 in the mouse models of scleroderma. Immune cell infiltration analysis showed that the differential genes in scleroderma were associated with follicular helper T cells, immature B cells, resting dendritic cells, memory activated CD4+T cells, M0 macrophages, monocytes, resting memory CD4+T cells and mast cell activation.
CONCLUSIONS: The artificial neural network diagnostic model for scleroderma established in this study provides a new perspective for exploring the pathogenesis of scleroderma.

OBJECTIVE: To investigate microvascular changes in juvenile localised scleroderma (JLS) lesions using superb microvascular imaging (SMI) and assess SMI\'s utility in evaluating disease activity.
METHODS: This prospective study enroled 16 children (7 males) with pathologically diagnosed JLS between January 2021 and June 2023. Lesions were assessed using Localised Scleroderma Cutaneous Assessment Tools, including the localised scleroderma skin activity index (LoSAI) and localised scleroderma skin damage index (LoSDI). Lesions with LoSAI scores > 0 were classified as active. The thickness and blood flow of the lesions and healthy skin layers of the contralateral site were evaluated using ultrasound. SMI was used to detect microvascular blood flow in the lesions and healthy skin, and the vascular index (VI) was calculated. The difference in VI between active lesions and healthy skin was correlated with LoSAI and total scores.
RESULTS: Of 46 lesions, 23 were active and 23 inactive. The skin thickness of the lesion was 0.094 ± 0.024 cm, and that of the healthy site was 0.108 ± 0.026 cm (p < 0.001). The VI of the active lesions and healthy skin were 7.60 (3.60, 12.80)% and 1.10 (0.50, 2.10)%, respectively (p < 0.001). The VI of the inactive lesions and the healthy skin were 0.85 (0.00, 2.20)% and 1.60 (1.00, 3.10)%, respectively (p = 0.011). VI differences between active lesions and healthy skin positively correlated with the LoSAI clinical score (r = 0.625, p = 0.001) and total score (r = 0.842, p < 0.001).
CONCLUSIONS: SMI can quantitatively detect microvascular blood flow changes in JLS skin, indicating lesion activity and severity.
CONCLUSIONS: SMI is a convenient, non-invasive, technique for detecting active JLS lesions and can provide valuable information to guide treatment options.
CONCLUSIONS: Current grading systems of juvenile localised scleroderma rely on subjective clinical information. Superb Microvascular Imaging identified that vascular indexes between active lesions and healthy skin positively correlated with clinical scores. Superb Microvascular Imaging effectively assesses microvascular blood flow, aiding juvenile localised scleroderma lesion activity evaluation.

Chimeric antigen receptor T cell (CAR-T) therapy, an innovative immune cell therapy, has revolutionized the treatment landscape of haematological malignancies. The past 2 years has witnessed the successful application of CD19-targeting CAR constructs in refractory cases of autoimmune rheumatic diseases, including systemic lupus erythematosus, systemic sclerosis and anti-synthetase syndrome. In comparison with existing B cell depletion therapies, targeting CD19 has demonstrated a more rapid and profound therapeutic effect, enabling drug-free remission with manageable adverse events. These promising results necessitate validation through long-term, large-sample randomized controlled studies. Corroborating the role of CAR-T therapy in refractory rheumatological disorders and affirming safety, efficacy and durability of responses are the aims of future clinical studies. Optimizing the engineering strategies and better patient selection are also critical to further refining the successful clinical implementation of CAR-T therapy.

BACKGROUND: m6A regulators have important roles in a variety of autoimmune diseases, but their potential function in scleroderma, a refractory connective tissue disease, remains unclear. Tenascin C (TNC) is known to be a factor promoting collagen deposition in the development of scleroderma, but the regulatory relationship between TNC and m6A regulators is unknown.
METHODS: We extracted GSE33463 data consisting of forty-one healthy controls and sixty-one patients with scleroderma, and we analyzed the expression levels of twenty-one m6A regulators as well as the associations between them. In addition, we obtained random forest (RF) and nomogram models to predict the likehood of scleroderma. Next, we categorized the m6Aclusters and geneclusters by consensus clustering, and we performed an immune cell infiltration analysis for each cluster. Finally, we injected adenoviruses into a bleomycin (BLM)-induced mouse model of scleroderma, which was used to overexpress FTO and TNC. We assess the extent of skin fibrosis in the mice samples using pathology stains and measuring their hydroxyproline content and collagen mRNA.
RESULTS: We initially identified fourteen differentially expressed m6A regulators (WTAP, RBM15, CBLL1, FTO, ALKBH5, YTHDC1, YTHDC2, YTHDF1, YTHDF2, YTHDF3, RBMX, HNRNPC, IGFBP1 and IGFBP2). We found ALKBH5 to be positively associated with CBLL1 and RBM15, and FTO to be negatively associated with WTAP. In addition, we identified four m6A regulators (CBLL1, IGFBP1, YTHDF2 and IGFBP2) using a RF model, and we designed a nomogram model with those variables that proved reliable according to the calibration curve and clinical impact curve. We found that the m6Acluster A was correlated with Type 1 T helper cell infiltration and the genecluster A was correlated with regulatory T cell infiltration. Finally, we showed that FTO overexpression downregulated the m6A and mRNA levels of TNC, and alleviated skin fibrosis in the mouse model of scleroderma. Thus, our overexpression experiments provide preliminary evidence suggesting that TNC is an adverse factor in scleroderma.
CONCLUSIONS: Our approach might be useful as a new and accurate scleroderma diagnosis method. Moreover, our results suggested that FTO/TNC might be a novel scleroderma therapeutic target.

BACKGROUND: Eosinophilic fasciitis (EF) is a rare connective tissue disease that can cause swelling and sclerosis of the extremities, and special attention is needed to differentiate EF from systemic sclerosis. Misdiagnosis or omission markedly delays treatment of EF, and severe skin sclerosis in advanced stages can cause joint contracture and tendon retraction, worsening the patient\'s prognosis and quality of life.
METHODS: We report a case of EF in a young woman diagnosed by tissue biopsy, confirming the difficulty of differential diagnosis with scleroderma.
CONCLUSIONS: Focusing on skin manifestations, completing tissue biopsy and radiography can help diagnose EF effectively. Clinicians should enhance their understanding of the differences between EF and scleroderma, and early diagnosis and standardized treatment can improve the prognosis of patients with EF.

Systemic sclerosis (SSc) is an immune-mediated rheumatic disease characterized by fibrosis and vascular lesions. Interstitial lung disease is an early complication of SSc and the main cause of death from SSc. Although baricitinib shows good efficacy in a variety of connective tissue diseases, its role in systemic sclerosis-related interstitial lung disease (SSc-ILD) is unclear. The objective of our study was to explore the effect and mechanism of baricitinib in SSc-ILD.
We explored crosstalk between the JAK2 and TGF-β1 pathways. In vivo experiments, SSc-ILD mice model were constructed by subcutaneous injection of PBS or bleomycin (7.5 mg/kg) and intragastric administration of 0.5% CMC-Na or baricitinib (5 mg/kg) once every two days. We used ELISA, qRT‒PCR, western blot and immunofluorescence staining to evaluate the degree of fibrosis. In vitro experiments, we used TGF-β1 and baricitinib to stimulate human fetal lung fibroblasts (HFLs) and assessed protein expression by western blot.
The vivo experiments showed that baricitinib notably alleviated skin and lung fibrosis, decreased the concentration of pro-inflammatory factors and increased those of the anti-inflammatory factors. Baricitinib affected the expression of TGF-β1 and TβRI/II inhibitiing JAK2. In the vitro experiments, following the culture of HFLs with baricitinib or a STAT3 inhibitor for 48 h, the expression levels of TβRI/II decreased. Conversely, with successful inhibition of TGF-β receptors in HFLs, JAK2 protein expression decreased.
Baricitinib attenuated bleomycin-induced skin and lung fibrosis in SSc-ILD mice model by targeting JAK2 and regulating of the crosstalk between the JAK2 and TGF-β1 signaling pathways.

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