{
  "abstract": "Introduction Systemic sclerosis (SSc) is characterized by complex autoantibody profiles and variable organ involvement. Among these, autoantibodies against G protein–coupled receptors (GPCRs) are increasingly recognized, and networks of dysregulated GPCR autoantibodies have been described in SSc. In particular, Autoantibodies against the angiotensin II receptor type-1 (AT1R) and endothelin-1 receptor type-A (ETAR) have been associated with severe disease pathogenesis. Importantly, they are linked to increased secretion of extracellular vesicles (EVs), which connect the hallmarks of SSc, namely vasculopathy, immune activation, and fibrosis. Antibodies against chemokine receptors CXCR3 and CXCR4 predict progressive deterioration of lung function, further underscoring the role of GPCR autoantibodies. EVs, in parallel, act as critical mediators of intercellular communication by transferring functional GPCRs such as AT1R to recipient resident tissue and immune cells, thereby modulating their responsiveness. Given that EV size determines their biogenesis and function, and that GPCR EV complexes may undergo either recycling or degradation, it is essential to elucidate these dynamics. We hypothesize a complex interplay among EV characteristics, GPCR autoantibodies, disease activity, and organ involvement in SSc.Material and Methods We characterized EVs from 100 SSc patients using nanoparticle tracking analysis (NTA). EV size and concentration parameters were correlated with clinical phenotypes and levels of autoantibodies: AT1R, ETAR, CXCR3, and CXCR4 using multivariate regression models. Machine learning algorithms were employed to evaluate the predictive capacity of EV characteristics for organ involvement.Results Since EV size and concentration are key determinants of their cellular uptake and biomarker potential, we report a fundamental inverse correlation between EV size and concentration (r = -0.68, p < 0.0001). EV concentration demonstrated significant negative correlations with autoantibody levels (AT1R: r = -0.47, p < 0.001; ETAR: r = -0.46, p < 0.001; CXCR3: r = -0.42, p < 0.001; CXCR4: r = -0.33, p < 0.001). Clinically, EV concentration served as a strong predictor of weight loss (AUC = 0.69) and pulmonary arterial hypertension (PAH) (AUC = 0.74). EV size was also a strong predictor of heart involvement (AUC = 0.70) and renal involvement (0.78).Conclusions Our results reveal a previously unrecognized yin-yang relationship between EV physical properties and clinical manifestations in SSc, offering compelling evidence that EVs play a mediating role in SSc disease pathogenesis. Therefore, specific EV profiles may serve as promising biomarkers for predicting organ-specific complications. Clinically, EVs could also act as surrogates of GPCR activity, and targeting GPCR-mediated EV biogenesis might represent a therapeutic strategy to block pathological intercellular communication.",
  "authors": [
    {
      "affiliations": [
        "University Clinic Schleswig-Holstein, Lübeck, Germany"
      ],
      "name": "Alexander Hackel"
    },
    {
      "affiliations": [
        "University Clinic Schleswig-Holstein, Lübeck, Germany"
      ],
      "name": "Precious Bonney"
    },
    {
      "affiliations": [
        "University Clinic Schleswig-Holstein, Lübeck, Germany"
      ],
      "name": "Moritz Jägermann"
    },
    {
      "affiliations": [
        "University Clinic Schleswig-Holstein, Lübeck, Germany"
      ],
      "name": "Hanna Grasshoff"
    },
    {
      "affiliations": [
        "University Clinic Schleswig-Holstein, Lübeck, Germany"
      ],
      "name": "Sebastian Jendrek"
    },
    {
      "affiliations": [
        "University Clinic Schleswig-Holstein, Lübeck, Germany"
      ],
      "name": "Reza Akbarzadeh"
    },
    {
      "affiliations": [
        "University Clinic Schleswig-Holstein, Lübeck, Germany"
      ],
      "name": "Gabriela Riemekasten"
    }
  ],
  "title": "P.058 Dual role of extracellular vesicle size and concentration as inverse correlates in autoantibody profiling and organ involvement prediction in systemic sclerosis",
  "uid": "500f882d-35dd-5237-9988-87e36fd9a099"
}