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The aim of this study was to explore the proof of concept for using Raman spectroscopy as a diagnostic platform in the setting of systemic lupus erythematosus (SLE). We sought to identify unique Raman signatures in serum blood samples to successfully segregate SLE patients from healthy controls (HC). In addition, a retrospective audit was undertaken to assess the clinical utility of current testing platforms used to detect anti-double stranded DNA (dsDNA) antibodies (n = 600). We examined 234 Raman spectra to investigate key variances between SLE patients (n = 8) and HC (n = 4). Multi-variant analysis and classification model construction was achieved using principal component analysis (PCA), PCA-linear discriminant analysis and partial least squares-discriminant analysis (PLS-DA). We achieved the successful segregation of Raman spectra from SLE patients and healthy controls (p-value < 0.0001). Classification models built using PLS-DA demonstrated outstanding performance characteristics with 99% accuracy, 100% sensitivity and 99% specificity. Twelve statistically significant (p-value < 0.001) wavenumbers were identified as potential diagnostic spectral markers. Molecular assignments related to proteins and DNA demonstrated significant Raman intensity changes between SLE and HC groups. These wavenumbers may serve as future biomarkers and offer further insight into the pathogenesis of SLE. Our audit confirmed previously reported inconsistencies between two key methodologies used to detect anti-dsDNA, highlighting the need for improved laboratory testing for SLE. Raman spectroscopy has demonstrated powerful performance characteristics in this proof-of-concept study, setting the foundations for future translation into the clinical setting. [ABSTRACT FROM AUTHOR]

Laboratory tests are essential for clinicians to reach an accurate diagnosis and informing appropriate treatments. The expansion in the use of immunotherapies has highlighted the gap between the knowledge of molecular pathways and targeted therapies with availability of laboratory tests. The translation of vibrational spectroscopic techniques such as Fourier-transform infrared (FTIR) spectroscopy and Raman spectroscopy into clinical practice offer rapid-, noninvasive and inexpensive methods to obtain information on the molecular composition of biological samples. Advances in instrumentation, data analysis and machine learning techniques are key developments that have permitted the availability of results to clinicians in an appropriate timescale. Immunological disorders are complex, often demonstrating interaction across multiple molecular pathways which results in delayed diagnosis. Vibrational spectroscopy is being applied in many fields and here we present a review of its potential use in clinical immunology. This review addresses the potential use of spectroscopy in clinical immunology. Potential benefits that these novel techniques offer, including enhanced definition of molecular process and its use in disease diagnosis, monitoring and treatment response is discussed. Whilst not covered extensively, an overview of the method principle, quality control processes, and the requirements for multivariate data analysis is included to provide the reader with sufficient understanding of its application in the clinical setting. [ABSTRACT FROM AUTHOR]