Josefin Kenrick (Solna / SE), Fredrik Edfors (Solna / SE), Mathias Uhlen (Solna / SE), Peter Nilsson (Solna / SE), Sofia Bergström (Solna / SE), Elisa Pin (Solna / SE)
Autoimmune diseases are heterogeneous diseases characterized by dysregulation of the immune system. They often result in chronic inflammation and damage to overall health. Due to the complex nature of these diseases, they are frequently difficult to diagnose and present with comorbidities which increase mortality risk. There is a pressing need for the discovery of novel biomarkers to facilitate early diagnosis, stratification and treatment evaluation of patients within these disease populations.
In this study, six autoimmune diseases were selected for plasma profiling as part of the Human Disease Blood Atlas program, including multiple sclerosis (n=234), myositis (n=209), rheumatoid arthritis (n=84), scleroderma (n=100), Sjögren"s syndrome (n=99), and systemic lupus erythematosus (n=97). Additionally, subgroup analysis of these diseases has been performed for multiple sclerosis and myositis.
In total, 823 plasma samples were analysed using the Olink Explore 1536 platform, a highly sensitive and multiplexed antibody-based technology, resulting in expression data of 1463 unique proteins.
Differential expression and supervised machine learning analysis with glmnet lasso identified potential prognostic biomarkers; some of these have previously been found to be associated with autoimmune disease, and others are novel. Interestingly, certain proteins exhibited patterns suggesting patient subgroups separate from what is identified in the clinic.
Pathway analysis provides further insights into the underlying biological processes and molecular interactions involved in the pathogenesis of these autoimmune disorders. Many identified proteins are involved in pro-inflammatory response and have suggested immune system functions. A portion of identified proteins have strong associations with cancer as well as infectious disease.
In summary, this study provides a comprehensive, exploratory analysis with the aim to identify distinct protein profiles both within and across six autoimmune diseases and their subgroups.