Non‐negative matrix factorisation of Raman spectra finds common patterns relating to neuromuscular disease across differing equipment configurations, preclinical models and human tissue

Abstract

Raman spectroscopy shows promise as a biomarker for complex nerve and muscle (neuromuscular) diseases. To maximise its potential, several challenges remain. These include the sensitivity to different instrument configurations, translation across preclinical/human tissues and the development of multivariate analytics that can derive interpretable spectral outputs for disease identification. Nonnegative matrix factorisation (NMF) can extract features from high-dimensional data sets and the nonnegative constraint results in physically realistic outputs. In this study, we have undertaken NMF on Raman spectra of muscle obtained from different clinical and preclinical settings. First, we obtained and combined Raman spectra from human patients with mitochondrial disease and healthy volunteers, using both a commercial microscope and in-house fibre optic probe. NMF was applied across all data, and spectral patterns common to both equipment configurations were identified. Linear

Conformational fingerprinting with Raman spectroscopy reveals protein structure as a translational biomarker of muscle pathology

“…The number of selected spectral patterns (rank) was determined by calculating the root mean square residual of randomly divided healthy samples in both the preclinical and human datasets, since the difference between two such matrices can be considered to represent biological noise. 13 To estimate the relative contributions of different secondary structures within each spectral pattern (mode), two approaches were employed, First, the second derivative of each mode was calculated and subjected to a Savitzky–Golay smooth (second order, 5 data points). Peaks were then identified using a 20% threshold, which excluded minor peaks, and a Voigt fitting function utilised.…”

“…Work from our group and others has also demonstrated the potential of Raman to identify several neurological diseases from a range of tissues, including serum, [6][7][8] saliva 9 and tears. 10 We have recently developed in vivo muscle recordings for the assessment of preclinical mouse models [11][12][13] and demonstrated efficacy in human biopsy samples. 14 Spontaneous Raman spectroscopy is an attractive potential biomarker for neuromuscular disease as it is simple to implement, requiring no sample preparation or tissue labelling.…”