Detection of neuroinflammation through the retina by means of Raman spectroscopy and multivariate analysis

Retinal nervous tissue sustains a substantial damage during the autoimmune inflammatory processes characteristic for Multiple Sclerosis (MS). The damage can be characterized non-surgically by Raman Spectroscopy, a non-invasive optical imaging technology. We used non-resonant near-infrared Raman spectrosocopy to create a spectral library of eight pivotal biomolecules known to be involved in neuroinflammation: Nicotinamide Adenine Dinucliotide (NADH), Flavin Adenine Nucleotide (FAD), Lactate, Cytochrome C, Glutamate, N-Acetyl- Aspartate (NAA), Phosphotidylcholine, with Advanced Glycolization End Products (AGEs) analyzed as a reference. Principal Component Analysis (PCA) of 50 spectra taken of murine retinal tissue culture undergoing an inflammatory response and healthy controls was used in order to characterize the molecular makeup of the inflammation. The loading plots revealed a heavy influence of peaks related to Glutamate, NADH, and Phosphotidylcholine to inflammation-related spectral changes. Partial Least Squares - Discriminant analysis (PLS-DA) was performed to create a multivariate classifier for the spectral diagnosis of neuroinflammed tissue and yielded a diagnostic sensitivity of 100% and specificity of 100%. We demonstrate then the effectiveness of combining Raman spectroscopy with PCA and PLS-DA statistical techniques to detect and monitor neuroinflamation in retina. With this technique Glutamate, NAA and NADH are detected in retina tissue as signs for neuroinflammation.