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Potential of FTIR Spectroscopy Applied to Exosomes for Alzheimer's Disease Discrimination: A Pilot Study
Tânia Soares Martins1, Sandra Magalhães2,3, Ilka Martins Rosa1
1Neurosciences and Signalling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal.
Abstract:
Alzheimer's disease (AD) diagnosis is based on psychological and imaging tests but can also include monitoring cerebrospinal fluid (CSF) biomarkers. However, CSF based-neurochemical approaches are expensive and invasive, limiting their use to well-equipped settings. In contrast, blood-based biomarkers are minimally invasive, cost-effective, and a widely accessible alternative. Blood-derived exosomes have recently emerged as a reliable AD biomarker source, carrying disease-specific cargo. Fourier-transformed infrared (FTIR) spectroscopy meets the criteria for an ideal diagnostic methodology since it is rapid, easy to implement, and has high reproducibility. This metabolome-based technique is useful for diagnosing a broad range of diseases, although to our knowledge, no reports for FTIR spectroscopy applied to exosomes in AD exist. In this ground-breaking pilot study, FTIR spectra of serum and serum-derived exosomes from two independent cohorts were acquired and analyzed using multivariate analysis. The regional UA-cohort includes 9 individuals, clinically diagnosed with AD, mean age of 78.7 years old; and the UMG-cohort comprises 12 individuals, clinically diagnosed with AD (based on molecular and/or imaging data), mean age of 73.2 years old. Unsupervised principal component analysis of FTIR spectra of serum-derived exosomes revealed higher discriminatory value for AD cases when compared to serum as a whole. Consistently, the partial least-squares analysis revealed that serum-derived exosomes present higher correlations than serum. In addition, the second derivative peak area calculation also revealed significant differences among Controls and AD cases. The results obtained suggest that this methodology can discriminate cases from Controls and thus be potential useful to assist in AD clinical diagnosis.

