Document resource
Introduction Validated serum biomarkers in SSc are scarce, and their role at diagnosis or early follow-up remains uncertain. Because single analytes rarely capture the disease’s multidimensional biology, we assessed whether biomarker patterns align with organ manifestations and cardiopulmonary measures. Our aim was to define compact, interpretable signatures that could flag patients at higher risk of specific involvement and support risk-aware monitoring.Material and Methods We performed a retrospective, cross-sectional study; 95 patients fulfilling 2013 ACR/EULAR SSc criteria were consecutively enrolled. Predefined clinical data were collected and circulating biomarkers associated with specific organ involvement were quantified using multiplex panels or ELISA. The evaluated biomarkers included COMP, MUC-1, GDF-15, MMP-7, SPD, YKL-40, PTX-3, VEGF-A, ET-1, BNP, sST2, adiponectin, ICAM-1, VWF, MCP-1, PF4, S100A8/A9, MMP-9, TIMP-1, LOXL2, and PARC (CCL18). Biomarkers were standardized and entered into principal component analusis (PCA) with varimax rotation. Components with eigenvalue >1 and interpretable loadings were retained. Each score was related to prespecified outcomes by logistic or linear regression, adjusted for age, sex, disease duration and skin subset. We report adjusted odds ratios (ORs) or β estimates with 95% CIs and exact p values, accordingly.Results Four PCs were retained, each defined by high-magnitude loadings. PC1 was driven by negative loadings from BNP, SPD, LOXL2, PTX3 and VWF, and was inversely associated with ischemic heart disease (OR 0.69, 95% CI 0.51–0.93; p=0.017). PC2 was defined by positive contributions from GDF-15, MUC-1 and PF4, and negative from PARC and S100A8/A9, and was associated with interstitial lung disease (ILD) (OR 1.39, 95% CI 1.09–1.79; p=0.008), pulmonary artery hypertension (PAH) (OR 1.45, 95% CI 1.03–2.04; p=0.032), right ventricle (RV) dilation (OR 2.17, 95% CI 1.13–4.15; p=0.018) and composite pulmonary outcomes (OR 1.44, 95% CI 1.12–1.86; p=0.004). PC3, characterized by negative contributions from S100A8/A9, MMP-7, MMP-9, and TIMP-1, showed a negative trend with dyschromia/poikiloderma, without statistical significance. Finally, PC4, marked by positive contribution YKL-40 and TIMP-1, and negative from MMP-9, was associated with pericardial involvement (OR 2.11, 95% CI 1.16–3.84; p=0.013), left-ventricular diastolic dysfunction (OR 2.17, 95% CI 1.24–3.79; p=0.006) and any echocardiographic abnormality (OR 1.94, 95% CI 1.19–3.17; p=0.007), suggesting a cardiac remodeling/injury axis.Conclusions PCA of serum biomarkers identified latent components linked to organ phenotypes, particularly a pulmonary component (PC2) and a cardiac component (PC4). These associations reflect multivariate signatures rather than single-biomarker effects. Findings warrant replication and longitudinal validation, but the internal coherence supports their potential as tools for organ-specific surveillance in SSc.Abstract P.241 Table 1Rotated standardized loadings for serum biomarker principal components (PC1- PC4). Bold indicates | loading | ≥ 0.40Abstract P.241 Table 2Significance of correlations between PCA and clinical features