Toward rapid molecular profiling of fibromyalgia: an exploratory study integrating vibrational spectroscopy and metabolomics

Abstract Background There is a critical need to improve diagnostic strategies for syndromes that rely largely on subjective questionnaires. Fibromyalgia (FM), one of the most common rheumatic disorders, is one such syndrome. FM shares clinical features with other disorders, including rheumatoid arthritis (RA), which can complicate diagnostic evaluation. In this exploratory proof-of-concept study, we evaluated the analytical feasibility of integrating Fourier-transform infrared spectroscopy (FTIR) with mass spectrometry (MS)-based metabolomics for molecular profiling of FM. Methods Specimens from 40 participants with FM, 20 with RA, and 10 healthy controls (HC) were evaluated. Because sample preparation strongly influences both spectroscopic and metabolomic measurements, preanalytical sources of interference were systematically examined, and multiple extraction solvents were compared. Methanol (MeOH) and MeOH/1-butanol (MeOH/BuOH) provided broad metabolome coverage. Partial least squares discriminant analysis (PLS-DA) and partial least squares regression (PLSR) were used to develop classification and regression models, respectively. Results Covariate-adjusted multivariate PLS-DA of FM versus RA yielded an internally cross-validated area under the receiver operating characteristic curve (AUC) of 0.84. MS-based metabolomics identified tentatively annotated oligopeptides, inosine monophosphate, and signaling lipid molecules as contributors to group differentiation, which may be associated with dysregulation of oxidative-stress and inflammatory-signaling pathways. PLSR models showed strong correlations between FTIR spectral data and the relative MS feature intensities of inosine monophosphate, NAE, MAG, fructosyl phenylalanine, fructosyl isoleucine, Ser-Phe, and 3,4,5-trihydroxypentanoylcarnitine, with coefficients of determination (R²) ≥ 0.70. Conclusions These results demonstrate the feasibility of an integrated spectroscopic–metabolomic workflow for molecular profiling of fibromyalgia. The findings provide a foundation for larger, independent clinical validation studies to determine the reproducibility and diagnostic performance of molecular signatures and to evaluate the potential development of a future FTIR-based screening assay.