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. 2024 Sep 10;12(1):146.
doi: 10.1186/s40478-024-01854-4.

Infrared spectral profiling of demyelinating activity in multiple sclerosis brain tissue

Oleksandr Gakh #  1 , Jordan M Wilkins #  1 , Yong Guo  1 , Bogdan F Popescu  2   3 , Stephen D Weigand  4 , Alicja Kalinowska-Lyszczarz  5 , Claudia F Lucchinetti  6
Affiliations

Infrared spectral profiling of demyelinating activity in multiple sclerosis brain tissue

Oleksandr Gakh et al. Acta Neuropathol Commun. .

Abstract

Multiple sclerosis (MS) is a leading cause of non-traumatic disability in young adults. The highly dynamic nature of MS lesions has made them difficult to study using traditional histopathology due to the specificity of current stains. This requires numerous stains to track and study demyelinating activity in MS. Thus, we utilized Fourier transform infrared (FTIR) spectroscopy to generate holistic biomolecular profiles of demyelinating activities in MS brain tissue. Multivariate analysis can differentiate MS tissue from controls. Analysis of the absorbance spectra shows profound reductions of lipids, proteins, and phosphate in white matter lesions. Changes in unsaturated lipids and lipid chain length indicate oxidative damage in MS brain tissue. Altered lipid and protein structures suggest changes in MS membrane structure and organization. Unique carbohydrate signatures are seen in MS tissue compared to controls, indicating altered metabolic activities. Cortical lesions had increased olefinic lipid content and abnormal membrane structure in normal appearing MS cortex compared to controls. Our results suggest that FTIR spectroscopy can further our understanding of lesion evolution and disease mechanisms in MS paving the way towards improved diagnosis, prognosis, and development of novel therapeutics.

Keywords: Biomolecular profiling; Cortex; Demyelinating activity; Fourier transform infrared spectroscopy; Human brain tissue; Lesions; Multiple sclerosis; Sparse partial least squares-discriminant analysis; White matter.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1
Fig. 1
Hyperspectral imaging readily detects regions of demyelinating activity in MS brain tissue. A–D Immunohistochemical staining of myelin proteolipid protein (PLP). Active demyelination, inactive demyelinated, and remyelinated regions in MS brain tissue are outlined in red, black, and green, respectively. Hyperspectral images of E–H total lipids and I–L amide I were generated using the absorbance profiles from 3000–2800 cm−1 and 1700–1600 cm−1, respectively. Scale bars are indicative of abundance as determined by absorbance profiles
Fig. 2
Fig. 2
Multivariate analysis of the second derivative spectra distinguishes between MS demyelinating stages in white matter. The average second derivative spectra from active and inactive lesions, remyelinated regions, periplaque white matter (PPWM), normal appearing white matter (NAWM), and control tissue were used for PLS-DA. A A PLS-DA plot using three components with 5, 5, and 10 variables selected. Ellipses depict the 95% confidence interval for each group. B The AUROC curve indicates good separation of different demyelinating stages in MS and control white matter
Fig. 3
Fig. 3
Lipid loss and perturbed membrane organization in demyelinated MS white matter. A The average absorbance spectra of total lipids detected in MS and control white matter brain tissue. Relevant spectral bands are indicated. The integrated area under the absorbance spectra for B total lipids, C total olefinic, and D total carbonyl ester. E–H Quantitative ratios of E total olefin/total lipids, F total CH2/total lipids, G total CH3/total lipids, and H total carbonyl ester/total lipids utilizing the integrated absorbances for the respective regions. I The corresponding second derivative of the absorbance spectra. Red arrows indicate peak shifts. The inset shows the olefinic region from 3050–3000 cm−1. Significance was detected using one-way ANOVA with post hoc Tukey test (* p < 0.05, ** p < 0.01, and *** p < 0.001, and **** p < 0.0001). Red stars indicate inactive lesions that were detected in acute cases. Integrated regions were as follows: asymmetric CH3, 2945–2970 cm−1; asymmetric CH2, 2905–2930 cm−1; symmetric CH3, 2860–2880 cm−1; symmetric CH2, 2840–2860 cm−1; and total lipids, 3000–2800 cm−1. Total CH2 and CH3 is the summation of asymmetric and symmetric peaks
Fig. 4
Fig. 4
Demyelinated MS brain tissue has reduced protein abundance and altered secondary structures. A The average absorbance profile of control and MS white matter tissue. B The integrated area under the absorbance spectra for amide I (1700–1600 cm−1). C The ratio of α-helixes to unordered protein structures. D The second derivative spectra of the amide I absorbance profiles. Peak shifts are indicated. Significance was detected using one-way ANOVA with post hoc Tukey test (* p < 0.05, ** p < 0.01, and *** p < 0.001, and **** p < 0.0001)
Fig. 5
Fig. 5
Reduced asymmetric phosphate and possible metabolic rearrangements in demyelinated MS white matter. A The average absorbance spectra of MS and control white matter brain tissue. B The integrated absorbance of the asymmetric phosphate band (1280–1200 cm−1). C The average second derivative of the absorbance spectra. Peak shifts and relevant bands are indicated by arrows. Significance was detected using one-way ANOVA with post hoc Tukey test (* p < 0.05, ** p < 0.01, and *** p < 0.001, and **** p < 0.0001)
Fig. 6
Fig. 6
Biomolecular alterations detected in MS cortex. A Myelin staining as detected by PLP1 in MS brain tissue. The black outline shows regions of demyelination in the cortex. B, C Hyperspectral images of the tissue seen in A using the abundance of total lipids and amide I, respectively. D–G Quantitative ratios using the integrated area under the absorbance spectra. H–J The average second derivative spectra of total lipids, amide I, and phosphate and carbohydrate regions, respectively. K The second derivative spectra of MS and control cortex was analyzed using sPLS-DA. The first three components with 60, 9, and 80 variables were used. The ellipses indicate the 95% confidence interval. Integrated regions: α-Helix, 1670–1650 cm−1; β-Sheets, 1635–1620 cm−1; Total CH2, 2930–2905 cm−1 + 2860–2840 cm−1; Total lipids, 3000–2800 cm−1; Total olefinic, 3027–3000 cm−1; and unordered structures, 1650–1635 cm−1. Significance was detected using one-way ANOVA with post hoc Tukey test (* p < 0.05 and ** p < 0.01)
Fig. 7
Fig. 7
Unsupervised clustering detects heterogeneity in MS brain lesions. A–C Immunohistochemical staining of myelin using PLP1. Active lesions, inactive plaques, and remyelinated regions are outlined in red, black, and green, respectively. D–F Unsupervised k-means clustering of MS brain tissue seen in A–C using the absorbance spectra as detected by FTIR spectroscopy. A total of eight clusters were used. G–I The average total lipid abundance (3000–2800 cm−1) for each respective cluster as shown in D-F. The NA (not applicable) corresponds to clusters designating background
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