Autoantibody profiles in systemic sclerosis: predictive value for clinical evaluation and prognosis

Abstract

Systemic sclerosis (SSc) is thought to be an autoimmune disease, as autoantibodies against a variety of extractable nuclear antigens can be detected in patient sera. Subgrouping patients based on the type of autoantibodies present can be useful in diagnosis and management. Anti‐centromere antibodies (ACA) and anti‐topoisomerase I antibodies (anti‐topo I) are the classic autoantibodies associated with SSc. ACA are associated with limited cutaneous involvement and isolated pulmonary hypertension, whereas anti‐topo I are associated with diffuse skin involvement and pulmonary fibrosis. ACA are predictors for a favorable prognosis, while anti‐topo I are correlated with a poor prognosis and SSc‐related mortality. Additionally, anti‐RNA polymerase antibodies (anti‐RNAP) are associated with diffuse cutaneous disease and renal involvement. Anti‐nucleolar antibodies define multiple subgroups of patients with SSc. Of these, anti‐Th/To antibodies (anti‐Th/To) and anti‐PM‐Scl antibodies (anti‐PM‐Scl) are associated with limited cutaneous SSc (lSSc), whereas anti‐U3RNP antibodies (anti‐U3RNP) are associated with diffuse cutaneous SSc (dSSc). In addition, anti‐Th/To and anti‐U3RNP can be predictors for a less favorable prognosis with a higher frequency of organ involvement, such as pulmonary fibrosis, pulmonary hypertension and renal crisis. Other autoantibodies are less frequently reported: anti‐Ku antibodies, anti‐U1RNP antibodies, anti‐human upstream‐binding factor, and anti‐U11/U12 antibodies. These antibodies are generally less specific to SSc, but also define clinically distinct patient subsets. Thus, characterization of autoantibodies in SSc together with knowledge of disease characteristics intrinsic to distinct patient populations is helpful for assessing the clinical presentation and prognosis of this disease, and for monitoring patients with SSc.

Part of CIRS Nexus · Curated by Lauren Lowenstein, The Biotoxin Lady

Key Biomarkers

Symptom Clusters